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| <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a> |
| Functions</h2></td></tr> |
| <tr class="memitem:a068d9be2e13dddcb8c8ab9f91e934a75"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a068d9be2e13dddcb8c8ab9f91e934a75">integral_image</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint8_t > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint32_t > &out)</td></tr> |
| <tr class="separator:a068d9be2e13dddcb8c8ab9f91e934a75"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ab508d3cd11ab140d782c716debfcb25f"><td class="memTemplParams" colspan="2">template<typename T1 , typename T2 , typename T3 > </td></tr> |
| <tr class="memitem:ab508d3cd11ab140d782c716debfcb25f"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#ab508d3cd11ab140d782c716debfcb25f">absolute_difference</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > &in1, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > &in2, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T3 > &out)</td></tr> |
| <tr class="separator:ab508d3cd11ab140d782c716debfcb25f"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:af995ccfae7ea6d83f47d1212c3c7af28"><td class="memTemplParams" colspan="2">template<typename T1 , typename T2 > </td></tr> |
| <tr class="memitem:af995ccfae7ea6d83f47d1212c3c7af28"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#af995ccfae7ea6d83f47d1212c3c7af28">accumulate</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > &out)</td></tr> |
| <tr class="separator:af995ccfae7ea6d83f47d1212c3c7af28"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a53a4d082f0a3ae1523d728a4f1a5f22b"><td class="memTemplParams" colspan="2">template<typename T1 , typename T2 > </td></tr> |
| <tr class="memitem:a53a4d082f0a3ae1523d728a4f1a5f22b"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a53a4d082f0a3ae1523d728a4f1a5f22b">accumulate_squared</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > &out, uint32_t shift)</td></tr> |
| <tr class="separator:a53a4d082f0a3ae1523d728a4f1a5f22b"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:afabf1ef7194a0156c90b3393e2a90cfa"><td class="memTemplParams" colspan="2">template<typename T > </td></tr> |
| <tr class="memitem:afabf1ef7194a0156c90b3393e2a90cfa"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#afabf1ef7194a0156c90b3393e2a90cfa">accumulate_weighted</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out, float alpha)</td></tr> |
| <tr class="separator:afabf1ef7194a0156c90b3393e2a90cfa"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a0500e22e76099c68d3e41b46e0cdd54c"><td class="memTemplParams" colspan="2">template<typename T1 , typename T2 , typename T3 > </td></tr> |
| <tr class="memitem:a0500e22e76099c68d3e41b46e0cdd54c"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a0500e22e76099c68d3e41b46e0cdd54c">arithmetic_addition</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > &in1, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > &in2, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T3 > &out, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> convert_policy)</td></tr> |
| <tr class="separator:a0500e22e76099c68d3e41b46e0cdd54c"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a135ce9546985c784175156c32fa014af"><td class="memTemplParams" colspan="2">template<typename T1 , typename T2 , typename T3 > </td></tr> |
| <tr class="memitem:a135ce9546985c784175156c32fa014af"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a135ce9546985c784175156c32fa014af">arithmetic_subtraction</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > &in1, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > &in2, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T3 > &out, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> convert_policy)</td></tr> |
| <tr class="separator:a135ce9546985c784175156c32fa014af"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a6e865331e6ad22ab8c6a47c836068eae"><td class="memTemplParams" colspan="2">template<typename T , typename = typename std::enable_if<std::is_integral<T>::value>::type> </td></tr> |
| <tr class="memitem:a6e865331e6ad22ab8c6a47c836068eae"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a6e865331e6ad22ab8c6a47c836068eae">bitwise_and</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in1, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in2, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out)</td></tr> |
| <tr class="separator:a6e865331e6ad22ab8c6a47c836068eae"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a524e781138b8143ce949f16aca47632d"><td class="memTemplParams" colspan="2">template<typename T , typename = typename std::enable_if<std::is_integral<T>::value>::type> </td></tr> |
| <tr class="memitem:a524e781138b8143ce949f16aca47632d"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a524e781138b8143ce949f16aca47632d">bitwise_or</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in1, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in2, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out)</td></tr> |
| <tr class="separator:a524e781138b8143ce949f16aca47632d"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:aeef005a6d652352fd78acf84fd8fdb0e"><td class="memTemplParams" colspan="2">template<typename T , typename = typename std::enable_if<std::is_integral<T>::value>::type> </td></tr> |
| <tr class="memitem:aeef005a6d652352fd78acf84fd8fdb0e"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#aeef005a6d652352fd78acf84fd8fdb0e">bitwise_xor</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in1, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in2, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out)</td></tr> |
| <tr class="separator:aeef005a6d652352fd78acf84fd8fdb0e"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a9629af50ada3b5dca5f23a639f6c8045"><td class="memTemplParams" colspan="2">template<typename T , typename = typename std::enable_if<std::is_integral<T>::value>::type> </td></tr> |
| <tr class="memitem:a9629af50ada3b5dca5f23a639f6c8045"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a9629af50ada3b5dca5f23a639f6c8045">bitwise_not</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out)</td></tr> |
| <tr class="separator:a9629af50ada3b5dca5f23a639f6c8045"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a934ba47d23b89b5868c6fad054e5a59d"><td class="memTemplParams" colspan="2">template<typename T , typename = typename std::enable_if<std::is_integral<T>::value>::type> </td></tr> |
| <tr class="memitem:a934ba47d23b89b5868c6fad054e5a59d"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a934ba47d23b89b5868c6fad054e5a59d">box3x3</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out)</td></tr> |
| <tr class="separator:a934ba47d23b89b5868c6fad054e5a59d"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a4485bbf8646087afcb6d724e613da68f"><td class="memTemplParams" colspan="2">template<typename T1 , typename T2 > </td></tr> |
| <tr class="memitem:a4485bbf8646087afcb6d724e613da68f"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a4485bbf8646087afcb6d724e613da68f">depth_convert</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > &out, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> policy, uint32_t shift)</td></tr> |
| <tr class="separator:a4485bbf8646087afcb6d724e613da68f"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a963f96bc7caff7e733ba2bfed26e453b"><td class="memTemplParams" colspan="2">template<> </td></tr> |
| <tr class="memitem:a963f96bc7caff7e733ba2bfed26e453b"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a963f96bc7caff7e733ba2bfed26e453b">depth_convert< int8_t, float ></a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int8_t > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< float > &out, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> policy, uint32_t shift)</td></tr> |
| <tr class="separator:a963f96bc7caff7e733ba2bfed26e453b"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a531358310cc70fdd4f59637db7ce1b3e"><td class="memTemplParams" colspan="2">template<> </td></tr> |
| <tr class="memitem:a531358310cc70fdd4f59637db7ce1b3e"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a531358310cc70fdd4f59637db7ce1b3e">depth_convert< float, int8_t ></a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< float > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int8_t > &out, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> policy, uint32_t shift)</td></tr> |
| <tr class="separator:a531358310cc70fdd4f59637db7ce1b3e"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a09a0ab9b11ba12a3d4230bb07198a06d"><td class="memTemplParams" colspan="2">template<> </td></tr> |
| <tr class="memitem:a09a0ab9b11ba12a3d4230bb07198a06d"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a09a0ab9b11ba12a3d4230bb07198a06d">depth_convert< uint8_t, uint16_t ></a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint8_t > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint16_t > &out, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> policy, uint32_t shift)</td></tr> |
| <tr class="separator:a09a0ab9b11ba12a3d4230bb07198a06d"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a0e91470444d96ed45eae0bac5b7c6042"><td class="memTemplParams" colspan="2">template<> </td></tr> |
| <tr class="memitem:a0e91470444d96ed45eae0bac5b7c6042"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a0e91470444d96ed45eae0bac5b7c6042">depth_convert< uint8_t, int16_t ></a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint8_t > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int16_t > &out, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> policy, uint32_t shift)</td></tr> |
| <tr class="separator:a0e91470444d96ed45eae0bac5b7c6042"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a6b46cf712c2bf1e96eef20c6b1b816f5"><td class="memTemplParams" colspan="2">template<> </td></tr> |
| <tr class="memitem:a6b46cf712c2bf1e96eef20c6b1b816f5"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a6b46cf712c2bf1e96eef20c6b1b816f5">depth_convert< uint8_t, int32_t ></a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint8_t > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int32_t > &out, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> policy, uint32_t shift)</td></tr> |
| <tr class="separator:a6b46cf712c2bf1e96eef20c6b1b816f5"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a34b3b2d8ce85841a51f517bf38d3d3b3"><td class="memTemplParams" colspan="2">template<> </td></tr> |
| <tr class="memitem:a34b3b2d8ce85841a51f517bf38d3d3b3"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a34b3b2d8ce85841a51f517bf38d3d3b3">depth_convert< uint16_t, uint8_t ></a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint16_t > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint8_t > &out, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> policy, uint32_t shift)</td></tr> |
| <tr class="separator:a34b3b2d8ce85841a51f517bf38d3d3b3"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a79219b20a374800b7da7222a70db89b2"><td class="memTemplParams" colspan="2">template<> </td></tr> |
| <tr class="memitem:a79219b20a374800b7da7222a70db89b2"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a79219b20a374800b7da7222a70db89b2">depth_convert< uint16_t, uint32_t ></a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint16_t > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint32_t > &out, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> policy, uint32_t shift)</td></tr> |
| <tr class="separator:a79219b20a374800b7da7222a70db89b2"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a447ea0d3749644c6eb970d78ff7e11db"><td class="memTemplParams" colspan="2">template<> </td></tr> |
| <tr class="memitem:a447ea0d3749644c6eb970d78ff7e11db"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a447ea0d3749644c6eb970d78ff7e11db">depth_convert< int16_t, uint8_t ></a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int16_t > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint8_t > &out, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> policy, uint32_t shift)</td></tr> |
| <tr class="separator:a447ea0d3749644c6eb970d78ff7e11db"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ac0098bc6f892a87934f223210dbfd6a9"><td class="memTemplParams" colspan="2">template<> </td></tr> |
| <tr class="memitem:ac0098bc6f892a87934f223210dbfd6a9"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#ac0098bc6f892a87934f223210dbfd6a9">depth_convert< int16_t, int32_t ></a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int16_t > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int32_t > &out, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> policy, uint32_t shift)</td></tr> |
| <tr class="separator:ac0098bc6f892a87934f223210dbfd6a9"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:aca1385f622ea543d14bdd997a2bcebcf"><td class="memTemplParams" colspan="2">template<typename T , typename std::enable_if< std::is_floating_point< T >::value, int >::type * = nullptr> </td></tr> |
| <tr class="memitem:aca1385f622ea543d14bdd997a2bcebcf"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#aca1385f622ea543d14bdd997a2bcebcf">gemm</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in1, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in2, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in3, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out, float alpha, float beta)</td></tr> |
| <tr class="separator:aca1385f622ea543d14bdd997a2bcebcf"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:acee95d0eabaf4dc59612123c1fbbffb1"><td class="memTemplParams" colspan="2">template<typename T1 , typename T2 , typename T3 > </td></tr> |
| <tr class="memitem:acee95d0eabaf4dc59612123c1fbbffb1"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#acee95d0eabaf4dc59612123c1fbbffb1">pixel_wise_multiplication</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > &in1, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > &in2, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T3 > &out, float scale, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> convert_policy, <a class="el" href="namespacearm__compute.xhtml#add6426cbf2e057a195846d4ba09a50be">RoundingPolicy</a> rounding_policy)</td></tr> |
| <tr class="separator:acee95d0eabaf4dc59612123c1fbbffb1"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:af8ba83a7ab2a51404613c27f4bf1b502"><td class="memTemplParams" colspan="2">template<typename T , typename = typename std::enable_if<std::is_integral<T>::value>::type> </td></tr> |
| <tr class="memitem:af8ba83a7ab2a51404613c27f4bf1b502"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#af8ba83a7ab2a51404613c27f4bf1b502">fixed_point_pixel_wise_multiplication</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in1, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in2, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out, int scale, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> convert_policy, <a class="el" href="namespacearm__compute.xhtml#add6426cbf2e057a195846d4ba09a50be">RoundingPolicy</a> rounding_policy)</td></tr> |
| <tr class="separator:af8ba83a7ab2a51404613c27f4bf1b502"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:aa2a75d7fb5a1cca91d6eab7888fc3431"><td class="memTemplParams" colspan="2">template<typename T > </td></tr> |
| <tr class="memitem:aa2a75d7fb5a1cca91d6eab7888fc3431"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#aa2a75d7fb5a1cca91d6eab7888fc3431">threshold</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out, uint8_t threshold, uint8_t false_value, uint8_t true_value, <a class="el" href="namespacearm__compute.xhtml#a3e6b23e675649b83240691abbc42a649">ThresholdType</a> type, uint8_t upper)</td></tr> |
| <tr class="separator:aa2a75d7fb5a1cca91d6eab7888fc3431"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ac41b6c35f336e0a97f9b8823ff7fcd05"><td class="memTemplParams" colspan="2">template<typename T , typename std::enable_if< std::is_floating_point< T >::value, int >::type * = nullptr> </td></tr> |
| <tr class="memitem:ac41b6c35f336e0a97f9b8823ff7fcd05"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#ac41b6c35f336e0a97f9b8823ff7fcd05">activation_layer</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out, <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> act_info)</td></tr> |
| <tr class="separator:ac41b6c35f336e0a97f9b8823ff7fcd05"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ab8680238fafb5a48dc1ebe47217f54e0"><td class="memTemplParams" colspan="2">template<typename T , typename std::enable_if< std::is_integral< T >::value, int >::type * = nullptr> </td></tr> |
| <tr class="memitem:ab8680238fafb5a48dc1ebe47217f54e0"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#ab8680238fafb5a48dc1ebe47217f54e0">batch_normalization_layer</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &mean, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &var, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &beta, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &gamma, float epsilon, int fixed_point_position)</td></tr> |
| <tr class="separator:ab8680238fafb5a48dc1ebe47217f54e0"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ae19ece6824a2bc089edcc619124d95d3"><td class="memTemplParams" colspan="2">template<typename T > </td></tr> |
| <tr class="memitem:ae19ece6824a2bc089edcc619124d95d3"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#ae19ece6824a2bc089edcc619124d95d3">convolution_layer</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &weights, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &bias, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out, const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> &conv_info)</td></tr> |
| <tr class="separator:ae19ece6824a2bc089edcc619124d95d3"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a590f86899d2cdff14487c16ce361d2a9"><td class="memTemplParams" colspan="2">template<typename T > </td></tr> |
| <tr class="memitem:a590f86899d2cdff14487c16ce361d2a9"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a590f86899d2cdff14487c16ce361d2a9">fully_connected_layer</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &weights, const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &bias, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out)</td></tr> |
| <tr class="separator:a590f86899d2cdff14487c16ce361d2a9"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a31ecd095dd99ad3b8527bb4736c79f4d"><td class="memTemplParams" colspan="2">template<typename T , typename std::enable_if< std::is_floating_point< T >::value, int >::type * = nullptr> </td></tr> |
| <tr class="memitem:a31ecd095dd99ad3b8527bb4736c79f4d"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a31ecd095dd99ad3b8527bb4736c79f4d">normalization_layer</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out, <a class="el" href="classarm__compute_1_1_normalization_layer_info.xhtml">NormalizationLayerInfo</a> norm_info)</td></tr> |
| <tr class="separator:a31ecd095dd99ad3b8527bb4736c79f4d"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a8e93dde24e9dfb46feaec452e192977c"><td class="memTemplParams" colspan="2">template<typename T > </td></tr> |
| <tr class="memitem:a8e93dde24e9dfb46feaec452e192977c"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a8e93dde24e9dfb46feaec452e192977c">pooling_layer</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out, <a class="el" href="classarm__compute_1_1_pooling_layer_info.xhtml">PoolingLayerInfo</a> pool_info, int fixed_point_position)</td></tr> |
| <tr class="separator:a8e93dde24e9dfb46feaec452e192977c"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a8db9e6c61d6d8399da28198a81a2c92b"><td class="memTemplParams" colspan="2">template<typename T , typename std::enable_if< std::is_floating_point< T >::value, int >::type * = nullptr> </td></tr> |
| <tr class="memitem:a8db9e6c61d6d8399da28198a81a2c92b"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a8db9e6c61d6d8399da28198a81a2c92b">softmax_layer</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out)</td></tr> |
| <tr class="separator:a8db9e6c61d6d8399da28198a81a2c92b"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:aeffa8efd0492f825570507bc628e2968"><td class="memTemplParams" colspan="2">template<typename T > </td></tr> |
| <tr class="memitem:aeffa8efd0492f825570507bc628e2968"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#aeffa8efd0492f825570507bc628e2968">fixed_point_operation</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in, <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &out, <a class="el" href="namespacearm__compute.xhtml#afa20b6a7f4383003babd690f026f22dc">FixedPointOp</a> op)</td></tr> |
| <tr class="separator:aeffa8efd0492f825570507bc628e2968"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a4a10dcdb4134d755119468d8464d7604"><td class="memTemplParams" colspan="2">template<typename T > </td></tr> |
| <tr class="memitem:a4a10dcdb4134d755119468d8464d7604"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a4a10dcdb4134d755119468d8464d7604">print</a> (const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > &in, std::ostream &out)</td></tr> |
| <tr class="separator:a4a10dcdb4134d755119468d8464d7604"><td class="memSeparator" colspan="2"> </td></tr> |
| </table> |
| <h2 class="groupheader">Function Documentation</h2> |
| <a class="anchor" id="ab508d3cd11ab140d782c716debfcb25f"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void arm_compute::test::validation::tensor_operations::absolute_difference </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > & </td> |
| <td class="paramname"><em>in1</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > & </td> |
| <td class="paramname"><em>in2</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T3 > & </td> |
| <td class="paramname"><em>out</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00270">270</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00905">arm_compute::test::fixed_point_arithmetic::detail::abs()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>, and <a class="el" href="tests_2_utils_8h_source.xhtml#l00581">arm_compute::test::saturate_cast()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00056">Reference::compute_reference_absolute_difference()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00048">absolute_difference_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00271"></a><span class="lineno"> 271</span> {</div><div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  <span class="keyword">using</span> intermediate_type = <span class="keyword">typename</span> common_promoted_signed_type<T1, T2, T3>::intermediate_type;</div><div class="line"><a name="l00273"></a><span class="lineno"> 273</span> </div><div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in1.num_elements(); ++i)</div><div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  {</div><div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  intermediate_type val = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ae115fc750a92fb6a5e094998b56fcc56">std::abs</a>(static_cast<intermediate_type>(in1[i]) - static_cast<intermediate_type>(in2[i]));</div><div class="line"><a name="l00277"></a><span class="lineno"> 277</span>  out[i] = <a class="code" href="namespacearm__compute_1_1test.xhtml#a4965b2f6821e0cf0afee738158bd8377">saturate_cast</a><T3>(val);</div><div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  }</div><div class="line"><a name="l00279"></a><span class="lineno"> 279</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_xhtml_a4965b2f6821e0cf0afee738158bd8377"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a4965b2f6821e0cf0afee738158bd8377">arm_compute::test::saturate_cast</a></div><div class="ttdeci">T saturate_cast(T val)</div><div class="ttdoc">Saturate a value of type T against the numeric limits of type U. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00581">Utils.h:581</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_ae115fc750a92fb6a5e094998b56fcc56"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ae115fc750a92fb6a5e094998b56fcc56">arm_compute::test::fixed_point_arithmetic::detail::abs</a></div><div class="ttdeci">fixed_point< T > abs(fixed_point< T > x)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00905">FixedPoint.h:905</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="af995ccfae7ea6d83f47d1212c3c7af28"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void arm_compute::test::validation::tensor_operations::accumulate </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > & </td> |
| <td class="paramname"><em>out</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00283">283</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>, and <a class="el" href="tests_2_utils_8h_source.xhtml#l00581">arm_compute::test::saturate_cast()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_c_p_p_8cpp_source.xhtml#l00068">ReferenceCPP::accumulate()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00284"></a><span class="lineno"> 284</span> {</div><div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  <span class="keyword">using</span> intermediate_type = <span class="keyword">typename</span> common_promoted_signed_type<T1, T2>::intermediate_type;</div><div class="line"><a name="l00286"></a><span class="lineno"> 286</span> </div><div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  {</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  intermediate_type val = <span class="keyword">static_cast<</span>intermediate_type<span class="keyword">></span>(out[i]) + static_cast<intermediate_type>(in[i]);</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  out[i] = <a class="code" href="namespacearm__compute_1_1test.xhtml#a4965b2f6821e0cf0afee738158bd8377">saturate_cast</a><T2>(val);</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  }</div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_xhtml_a4965b2f6821e0cf0afee738158bd8377"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a4965b2f6821e0cf0afee738158bd8377">arm_compute::test::saturate_cast</a></div><div class="ttdeci">T saturate_cast(T val)</div><div class="ttdoc">Saturate a value of type T against the numeric limits of type U. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00581">Utils.h:581</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a53a4d082f0a3ae1523d728a4f1a5f22b"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void arm_compute::test::validation::tensor_operations::accumulate_squared </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint32_t </td> |
| <td class="paramname"><em>shift</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00296">296</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="_error_8h_source.xhtml#l00031">ARM_COMPUTE_ERROR</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>, and <a class="el" href="tests_2_utils_8h_source.xhtml#l00581">arm_compute::test::saturate_cast()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_c_p_p_8cpp_source.xhtml#l00077">ReferenceCPP::accumulate_squared()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00297"></a><span class="lineno"> 297</span> {</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keywordflow">if</span>(shift > 15)</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  {</div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Shift in accumulate_squared must be within the range [0, 15]"</span>);</div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  }</div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="keyword">using</span> intermediate_type = <span class="keyword">typename</span> common_promoted_signed_type<T1, T2>::intermediate_type;</div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  intermediate_type denom = 1 << shift;</div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span> </div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  {</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  intermediate_type val = <span class="keyword">static_cast<</span>intermediate_type<span class="keyword">></span>(out[i]) + (static_cast<intermediate_type>(in[i]) * <span class="keyword">static_cast<</span>intermediate_type<span class="keyword">></span>(in[i]) / denom);</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  out[i] = <a class="code" href="namespacearm__compute_1_1test.xhtml#a4965b2f6821e0cf0afee738158bd8377">saturate_cast</a><T2>(val);</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  }</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span> }</div><div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00031">Error.h:31</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_xhtml_a4965b2f6821e0cf0afee738158bd8377"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a4965b2f6821e0cf0afee738158bd8377">arm_compute::test::saturate_cast</a></div><div class="ttdeci">T saturate_cast(T val)</div><div class="ttdoc">Saturate a value of type T against the numeric limits of type U. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00581">Utils.h:581</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="afabf1ef7194a0156c90b3393e2a90cfa"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void arm_compute::test::validation::tensor_operations::accumulate_weighted </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">float </td> |
| <td class="paramname"><em>alpha</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00314">314</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="_error_8h_source.xhtml#l00031">ARM_COMPUTE_ERROR</a>, and <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_c_p_p_8cpp_source.xhtml#l00086">ReferenceCPP::accumulate_weighted()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00315"></a><span class="lineno"> 315</span> {</div><div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="keywordflow">if</span>(alpha < 0.f || alpha > 1.f)</div><div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  {</div><div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Weight (alpha) specified in accumulate_weighted must be within the range [0, 1]"</span>);</div><div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  }</div><div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  <span class="keyword">using</span> intermediate_type = <span class="keyword">typename</span> common_promoted_signed_type<T>::intermediate_type;</div><div class="line"><a name="l00321"></a><span class="lineno"> 321</span> </div><div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  {</div><div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <span class="keywordtype">double</span> val = (1. - <span class="keyword">static_cast<</span><span class="keywordtype">double</span><span class="keyword">></span>(alpha)) * <span class="keyword">static_cast<</span>intermediate_type<span class="keyword">></span>(out[i]) + static_cast<double>(alpha) * <span class="keyword">static_cast<</span>intermediate_type<span class="keyword">></span>(in[i]);</div><div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  out[i] = <span class="keyword">static_cast<</span>T<span class="keyword">></span>(val);</div><div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  }</div><div class="line"><a name="l00327"></a><span class="lineno"> 327</span> }</div><div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00031">Error.h:31</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="ac41b6c35f336e0a97f9b8823ff7fcd05"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void activation_layer </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml">ActivationLayerInfo</a> </td> |
| <td class="paramname"><em>act_info</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00686">686</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00490">ActivationLayerInfo::a()</a>, <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaa7d8a220d2262f9d6c658d549ee12cf2c">ActivationLayerInfo::ABS</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00905">arm_compute::test::fixed_point_arithmetic::detail::abs()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00486">ActivationLayerInfo::activation()</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00885">arm_compute::test::fixed_point_arithmetic::detail::add()</a>, <a class="el" href="_error_8h_source.xhtml#l00031">ARM_COMPUTE_ERROR</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00494">ActivationLayerInfo::b()</a>, <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaacc516ab03b98f1c908ddf6ed4a7c45e9">ActivationLayerInfo::BOUNDED_RELU</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00915">arm_compute::test::fixed_point_arithmetic::detail::exp()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00081">Tensor< T >::fixed_point_position()</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00925">arm_compute::test::fixed_point_arithmetic::detail::inv_sqrt()</a>, <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaaaac544aacc3615aada24897a215f5046">ActivationLayerInfo::LINEAR</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00920">arm_compute::test::fixed_point_arithmetic::detail::log()</a>, <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaa72ee60fba0509af07cbbd91398d8db9d">ActivationLayerInfo::LOGISTIC</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00880">arm_compute::test::fixed_point_arithmetic::detail::max()</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00875">arm_compute::test::fixed_point_arithmetic::detail::min()</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00895">arm_compute::test::fixed_point_arithmetic::detail::mul()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>, <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaad346bb4679d29be241279f15d7795c1c">ActivationLayerInfo::RELU</a>, <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaadcc44a50c791a591c74e00ecdda7c58d">ActivationLayerInfo::SOFT_RELU</a>, <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaa36875f2500a09ee35d0bb7eb8c0b91b0">ActivationLayerInfo::SQRT</a>, <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaa12dec4e1f7ec620651b2b95c440ffac0">ActivationLayerInfo::SQUARE</a>, <a class="el" href="classarm__compute_1_1_activation_layer_info.xhtml#a56297e0f7b215eea46c818cb7528d9eaa143c8c6f51b9bb893ce71e38702e3cc1">ActivationLayerInfo::TANH</a>, and <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00930">arm_compute::test::fixed_point_arithmetic::detail::tanh()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_tensor_visitors_8h_source.xhtml#l00195">activation_layer_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00687"></a><span class="lineno"> 687</span> {</div><div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  <span class="keyword">const</span> T a = <span class="keyword">static_cast<</span>T<span class="keyword">></span>(act_info.a());</div><div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  <span class="keyword">const</span> T b = <span class="keyword">static_cast<</span>T<span class="keyword">></span>(act_info.b());</div><div class="line"><a name="l00690"></a><span class="lineno"> 690</span> </div><div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  {</div><div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  T x = in[i];</div><div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  <span class="keywordflow">switch</span>(act_info.activation())</div><div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  {</div><div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  <span class="keywordflow">case</span> ActivationLayerInfo::ActivationFunction::ABS:</div><div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  out[i] = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ae115fc750a92fb6a5e094998b56fcc56">std::abs</a>(x);</div><div class="line"><a name="l00698"></a><span class="lineno"> 698</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  <span class="keywordflow">case</span> ActivationLayerInfo::ActivationFunction::BOUNDED_RELU:</div><div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  out[i] = std::min<T>(a, std::max<T>(0, x));</div><div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  <span class="keywordflow">case</span> ActivationLayerInfo::ActivationFunction::LINEAR:</div><div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  out[i] = a * x + b;</div><div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  <span class="keywordflow">case</span> ActivationLayerInfo::ActivationFunction::LOGISTIC:</div><div class="line"><a name="l00706"></a><span class="lineno"> 706</span>  out[i] = <span class="keyword">static_cast<</span>T<span class="keyword">></span>(1) / (static_cast<T>(1) + <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aa4e01e9be9adcc40a69a4da48fa83a43">std::exp</a>(-x));</div><div class="line"><a name="l00707"></a><span class="lineno"> 707</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00708"></a><span class="lineno"> 708</span>  <span class="keywordflow">case</span> ActivationLayerInfo::ActivationFunction::RELU:</div><div class="line"><a name="l00709"></a><span class="lineno"> 709</span>  out[i] = std::max<T>(0, x);</div><div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00711"></a><span class="lineno"> 711</span>  <span class="keywordflow">case</span> ActivationLayerInfo::ActivationFunction::SOFT_RELU:</div><div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  out[i] = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a8c8ce35c61b4f71cccec28d18161eaa1">std::log</a>(static_cast<T>(1) + <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aa4e01e9be9adcc40a69a4da48fa83a43">std::exp</a>(x));</div><div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  <span class="keywordflow">case</span> ActivationLayerInfo::ActivationFunction::SQRT:</div><div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  out[i] = std::sqrt(x);</div><div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  <span class="keywordflow">case</span> ActivationLayerInfo::ActivationFunction::SQUARE:</div><div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  out[i] = x * x;</div><div class="line"><a name="l00719"></a><span class="lineno"> 719</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  <span class="keywordflow">case</span> ActivationLayerInfo::ActivationFunction::TANH:</div><div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  out[i] = a * <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a6854479935f66029852441b051e1a3e0">std::tanh</a>(b * x);</div><div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Activation function not recognised"</span>);</div><div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  }</div><div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  }</div><div class="line"><a name="l00728"></a><span class="lineno"> 728</span> }</div><div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00031">Error.h:31</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_aa4e01e9be9adcc40a69a4da48fa83a43"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aa4e01e9be9adcc40a69a4da48fa83a43">arm_compute::test::fixed_point_arithmetic::detail::exp</a></div><div class="ttdeci">fixed_point< T > exp(fixed_point< T > x)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00915">FixedPoint.h:915</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_a8c8ce35c61b4f71cccec28d18161eaa1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a8c8ce35c61b4f71cccec28d18161eaa1">arm_compute::test::fixed_point_arithmetic::detail::log</a></div><div class="ttdeci">fixed_point< T > log(fixed_point< T > x)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00920">FixedPoint.h:920</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_a6854479935f66029852441b051e1a3e0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a6854479935f66029852441b051e1a3e0">arm_compute::test::fixed_point_arithmetic::detail::tanh</a></div><div class="ttdeci">fixed_point< T > tanh(fixed_point< T > x)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00930">FixedPoint.h:930</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_ae115fc750a92fb6a5e094998b56fcc56"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ae115fc750a92fb6a5e094998b56fcc56">arm_compute::test::fixed_point_arithmetic::detail::abs</a></div><div class="ttdeci">fixed_point< T > abs(fixed_point< T > x)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00905">FixedPoint.h:905</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a0500e22e76099c68d3e41b46e0cdd54c"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void arm_compute::test::validation::tensor_operations::arithmetic_addition </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > & </td> |
| <td class="paramname"><em>in1</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > & </td> |
| <td class="paramname"><em>in2</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T3 > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>convert_policy</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00331">331</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>, and <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6fa4729d95f983955f0d93a30179deb2b86">arm_compute::SATURATE</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00122">Reference::compute_reference_arithmetic_addition()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00063">arithmetic_addition_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00332"></a><span class="lineno"> 332</span> {</div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keyword">using</span> intermediate_type = <span class="keyword">typename</span> common_promoted_signed_type<T1, T2, T3>::intermediate_type;</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span> </div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in1.num_elements(); ++i)</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  {</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  intermediate_type val = <span class="keyword">static_cast<</span>intermediate_type<span class="keyword">></span>(in1[i]) + static_cast<intermediate_type>(in2[i]);</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  out[i] = (convert_policy == ConvertPolicy::SATURATE) ? saturate_cast<T3>(val) : <span class="keyword">static_cast<</span>T3<span class="keyword">></span>(val);</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  }</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a135ce9546985c784175156c32fa014af"></a> |
| <div class="memitem"> |
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| <table class="memname"> |
| <tr> |
| <td class="memname">void arm_compute::test::validation::tensor_operations::arithmetic_subtraction </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > & </td> |
| <td class="paramname"><em>in1</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > & </td> |
| <td class="paramname"><em>in2</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T3 > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>convert_policy</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00344">344</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>, and <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6fa4729d95f983955f0d93a30179deb2b86">arm_compute::SATURATE</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00139">Reference::compute_reference_arithmetic_subtraction()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00081">arithmetic_subtraction_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00345"></a><span class="lineno"> 345</span> {</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="keyword">using</span> intermediate_type = <span class="keyword">typename</span> common_promoted_signed_type<T1, T2, T3>::intermediate_type;</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span> </div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in1.num_elements(); ++i)</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  {</div><div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  intermediate_type val = <span class="keyword">static_cast<</span>intermediate_type<span class="keyword">></span>(in1[i]) - static_cast<intermediate_type>(in2[i]);</div><div class="line"><a name="l00351"></a><span class="lineno"> 351</span>  out[i] = (convert_policy == ConvertPolicy::SATURATE) ? saturate_cast<T3>(val) : <span class="keyword">static_cast<</span>T3<span class="keyword">></span>(val);</div><div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  }</div><div class="line"><a name="l00353"></a><span class="lineno"> 353</span> }</div></div><!-- fragment --> |
| </div> |
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| <a class="anchor" id="ab8680238fafb5a48dc1ebe47217f54e0"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
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| <td class="memname">void batch_normalization_layer </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>mean</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>var</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>beta</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>gamma</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">float </td> |
| <td class="paramname"><em>epsilon</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">int </td> |
| <td class="paramname"><em>fixed_point_position</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00783">783</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00925">arm_compute::test::fixed_point_arithmetic::detail::inv_sqrt()</a>, and <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00071">Tensor< T >::shape()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00361">Reference::compute_reference_batch_normalization_layer()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00216">batch_normalization_layer_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00784"></a><span class="lineno"> 784</span> {</div><div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> cols = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(in.shape()[0]);</div><div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> rows = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(in.shape()[1]);</div><div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> depth = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(in.shape()[2]);</div><div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  <span class="keywordtype">int</span> upper_dims = in.shape().total_size() / (cols * rows * depth);</div><div class="line"><a name="l00789"></a><span class="lineno"> 789</span> </div><div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> r = 0; r < upper_dims; ++r)</div><div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  {</div><div class="line"><a name="l00792"></a><span class="lineno"> 792</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < depth; ++i)</div><div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  {</div><div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> k = 0; k < rows; ++k)</div><div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  {</div><div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> l = 0; l < cols; ++l)</div><div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  {</div><div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> pos = l + k * cols + i * rows * cols + r * cols * rows * depth;</div><div class="line"><a name="l00799"></a><span class="lineno"> 799</span>  fixed_point_arithmetic::fixed_point<T> in_qs8(in[pos], fixed_point_position, <span class="keyword">true</span>);</div><div class="line"><a name="l00800"></a><span class="lineno"> 800</span>  fixed_point_arithmetic::fixed_point<T> var_qs8(var[i], fixed_point_position, <span class="keyword">true</span>);</div><div class="line"><a name="l00801"></a><span class="lineno"> 801</span>  fixed_point_arithmetic::fixed_point<T> mean_qs8(mean[i], fixed_point_position, <span class="keyword">true</span>);</div><div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  fixed_point_arithmetic::fixed_point<T> beta_qs8(beta[i], fixed_point_position, <span class="keyword">true</span>);</div><div class="line"><a name="l00803"></a><span class="lineno"> 803</span>  fixed_point_arithmetic::fixed_point<T> gamma_qs8(gamma[i], fixed_point_position, <span class="keyword">true</span>);</div><div class="line"><a name="l00804"></a><span class="lineno"> 804</span>  fixed_point_arithmetic::fixed_point<T> epsilon_qs8(epsilon, fixed_point_position);</div><div class="line"><a name="l00805"></a><span class="lineno"> 805</span> </div><div class="line"><a name="l00806"></a><span class="lineno"> 806</span>  <span class="keyword">auto</span> denominator = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a2b7623d9dd3fde1d0a3bbe034967cff5">fixed_point_arithmetic::inv_sqrt</a>(var_qs8 + epsilon_qs8);</div><div class="line"><a name="l00807"></a><span class="lineno"> 807</span>  <span class="keyword">auto</span> numerator = in_qs8 - mean_qs8;</div><div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  <span class="keyword">auto</span> x_bar = numerator * denominator;</div><div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  x_bar = beta_qs8 + x_bar * gamma_qs8;</div><div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  out[pos] = x_bar.raw();</div><div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  }</div><div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  }</div><div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  }</div><div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  }</div><div class="line"><a name="l00815"></a><span class="lineno"> 815</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_a2b7623d9dd3fde1d0a3bbe034967cff5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a2b7623d9dd3fde1d0a3bbe034967cff5">arm_compute::test::fixed_point_arithmetic::detail::inv_sqrt</a></div><div class="ttdeci">fixed_point< T > inv_sqrt(fixed_point< T > x)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00925">FixedPoint.h:925</a></div></div> |
| </div><!-- fragment --> |
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| <a class="anchor" id="a6e865331e6ad22ab8c6a47c836068eae"></a> |
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| <td class="memname">void arm_compute::test::validation::tensor_operations::bitwise_and </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in1</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in2</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00357">357</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_c_p_p_8cpp_source.xhtml#l00113">ReferenceCPP::bitwise_and()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00358"></a><span class="lineno"> 358</span> {</div><div class="line"><a name="l00359"></a><span class="lineno"> 359</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in1.num_elements(); ++i)</div><div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  {</div><div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  out[i] = in1[i] & in2[i];</div><div class="line"><a name="l00362"></a><span class="lineno"> 362</span>  }</div><div class="line"><a name="l00363"></a><span class="lineno"> 363</span> }</div></div><!-- fragment --> |
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| <a class="anchor" id="a9629af50ada3b5dca5f23a639f6c8045"></a> |
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| <td class="memname">void arm_compute::test::validation::tensor_operations::bitwise_not </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00387">387</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_c_p_p_8cpp_source.xhtml#l00143">ReferenceCPP::bitwise_not()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00388"></a><span class="lineno"> 388</span> {</div><div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  {</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  out[i] = ~in[i];</div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  }</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span> }</div></div><!-- fragment --> |
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| <a class="anchor" id="a524e781138b8143ce949f16aca47632d"></a> |
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| <td class="memname">void arm_compute::test::validation::tensor_operations::bitwise_or </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in1</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in2</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
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| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00367">367</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_c_p_p_8cpp_source.xhtml#l00123">ReferenceCPP::bitwise_or()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00368"></a><span class="lineno"> 368</span> {</div><div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in1.num_elements(); ++i)</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  {</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  out[i] = in1[i] | in2[i];</div><div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  }</div><div class="line"><a name="l00373"></a><span class="lineno"> 373</span> }</div></div><!-- fragment --> |
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| <a class="anchor" id="aeef005a6d652352fd78acf84fd8fdb0e"></a> |
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| <td class="memname">void arm_compute::test::validation::tensor_operations::bitwise_xor </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in1</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in2</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
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| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00377">377</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_c_p_p_8cpp_source.xhtml#l00133">ReferenceCPP::bitwise_xor()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00378"></a><span class="lineno"> 378</span> {</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in1.num_elements(); ++i)</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  {</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  out[i] = in1[i] ^ in2[i];</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  }</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span> }</div></div><!-- fragment --> |
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| <a class="anchor" id="a934ba47d23b89b5868c6fad054e5a59d"></a> |
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| <td class="memname">void arm_compute::test::validation::tensor_operations::box3x3 </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
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| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00397">397</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2_utils_8h_source.xhtml#l00611">arm_compute::test::index2coord()</a>, <a class="el" href="tests_2_utils_8h_source.xhtml#l00658">arm_compute::test::is_in_valid_region()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00071">Tensor< T >::shape()</a>, <a class="el" href="tests_2_utils_8h_source.xhtml#l00466">arm_compute::test::shape_to_valid_region_undefined_border()</a>, and <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aa4c614360da93c0a041b22e537de151eb">arm_compute::U</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_c_p_p_8cpp_source.xhtml#l00152">ReferenceCPP::box3x3()</a>, and <a class="el" href="_reference_8cpp_source.xhtml#l00222">Reference::compute_reference_box3x3()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00398"></a><span class="lineno"> 398</span> {</div><div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  <span class="keyword">const</span> std::array<T, 9> filter{ { 1, 1, 1, 1, 1, 1, 1, 1, 1 } };</div><div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  <span class="keywordtype">float</span> scale = 1.f / <span class="keyword">static_cast<</span><span class="keywordtype">float</span><span class="keyword">></span>(filter.size());</div><div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  <span class="keyword">const</span> ValidRegion valid_region = <a class="code" href="namespacearm__compute_1_1test.xhtml#a6b97d7bba7b5cee833eb5c2282e8d246">shape_to_valid_region_undefined_border</a>(in.shape(), BorderSize(1));</div><div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> element_idx = 0; element_idx < in.num_elements(); ++element_idx)</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  {</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  <span class="keyword">const</span> Coordinates <span class="keywordtype">id</span> = <a class="code" href="namespacearm__compute_1_1test.xhtml#a24d8c0391cfa38e78969b6ad97c0ff09">index2coord</a>(in.shape(), element_idx);</div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <span class="keywordflow">if</span>(<a class="code" href="namespacearm__compute_1_1test.xhtml#a58ee979a599b3b6a2587964106b1910c">is_in_valid_region</a>(valid_region, <span class="keywordtype">id</span>))</div><div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  {</div><div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  apply_2d_spatial_filter(<span class="keywordtype">id</span>, in, out, TensorShape(3U, 3U), filter.data(), scale);</div><div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  }</div><div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  }</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_xhtml_a6b97d7bba7b5cee833eb5c2282e8d246"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a6b97d7bba7b5cee833eb5c2282e8d246">arm_compute::test::shape_to_valid_region_undefined_border</a></div><div class="ttdeci">ValidRegion shape_to_valid_region_undefined_border(TensorShape shape, BorderSize border_size)</div><div class="ttdoc">Create a valid region covering the tensor shape with UNDEFINED border mode and specified border size...</div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00466">Utils.h:466</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_xhtml_a58ee979a599b3b6a2587964106b1910c"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a58ee979a599b3b6a2587964106b1910c">arm_compute::test::is_in_valid_region</a></div><div class="ttdeci">bool is_in_valid_region(const ValidRegion &valid_region, const Coordinates &coord)</div><div class="ttdoc">Check if a coordinate is within a valid region. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00658">Utils.h:658</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_xhtml_a24d8c0391cfa38e78969b6ad97c0ff09"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a24d8c0391cfa38e78969b6ad97c0ff09">arm_compute::test::index2coord</a></div><div class="ttdeci">Coordinates index2coord(const TensorShape &shape, int index)</div><div class="ttdoc">Convert a linear index into n-dimensional coordinates. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00611">Utils.h:611</a></div></div> |
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| <a class="anchor" id="ae19ece6824a2bc089edcc619124d95d3"></a> |
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| <td class="memname">void arm_compute::test::validation::tensor_operations::convolution_layer </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>weights</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>bias</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_pad_stride_info.xhtml">PadStrideInfo</a> & </td> |
| <td class="paramname"><em>conv_info</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00847">847</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00086">Tensor< T >::data()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00081">Tensor< T >::fixed_point_position()</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00875">arm_compute::test::fixed_point_arithmetic::detail::min()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00409">PadStrideInfo::pad()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00071">Tensor< T >::shape()</a>, and <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00405">PadStrideInfo::stride()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00405">Reference::compute_reference_convolution_layer()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00241">convolution_layer_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00848"></a><span class="lineno"> 848</span> {</div><div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> width_in = in.shape().x();</div><div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> height_in = in.shape().y();</div><div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> depth_in = in.shape().z();</div><div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> width_out = out.shape().x();</div><div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> height_out = out.shape().y();</div><div class="line"><a name="l00854"></a><span class="lineno"> 854</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> depth_out = out.shape().z();</div><div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> width_weights = weights.shape().x();</div><div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> height_weights = weights.shape().y();</div><div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> depth_weights = weights.shape().z();</div><div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> pad_xi = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aabcf39e3917f842dbc5fbb0d802f24d5">std::min</a>(static_cast<int>(conv_info.pad().first), width_weights / 2);</div><div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> pad_yi = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aabcf39e3917f842dbc5fbb0d802f24d5">std::min</a>(static_cast<int>(conv_info.pad().second), height_weights / 2);</div><div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> start_xi = width_weights / 2 - pad_xi;</div><div class="line"><a name="l00861"></a><span class="lineno"> 861</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> start_yi = height_weights / 2 - pad_yi;</div><div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> end_xi = width_in - start_xi;</div><div class="line"><a name="l00863"></a><span class="lineno"> 863</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> end_yi = height_in - start_yi;</div><div class="line"><a name="l00864"></a><span class="lineno"> 864</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> stride_xi = conv_info.stride().first;</div><div class="line"><a name="l00865"></a><span class="lineno"> 865</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> stride_yi = conv_info.stride().second;</div><div class="line"><a name="l00866"></a><span class="lineno"> 866</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> num_batches = in.shape().total_size() / (width_in * height_in * depth_in);</div><div class="line"><a name="l00867"></a><span class="lineno"> 867</span> </div><div class="line"><a name="l00868"></a><span class="lineno"> 868</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> r = 0; r < num_batches; ++r)</div><div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  {</div><div class="line"><a name="l00870"></a><span class="lineno"> 870</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> yi = start_yi; yi < end_yi; yi += stride_yi)</div><div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  {</div><div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> xi = start_xi; xi < end_xi; xi += stride_xi)</div><div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  {</div><div class="line"><a name="l00874"></a><span class="lineno"> 874</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> ofm = 0; ofm < depth_out; ++ofm)</div><div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  {</div><div class="line"><a name="l00876"></a><span class="lineno"> 876</span>  <span class="comment">// Compute input and output offsets</span></div><div class="line"><a name="l00877"></a><span class="lineno"> 877</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> offset_in = r * width_in * height_in * depth_in;</div><div class="line"><a name="l00878"></a><span class="lineno"> 878</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> xo = (xi - start_xi) / stride_xi;</div><div class="line"><a name="l00879"></a><span class="lineno"> 879</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> yo = (yi - start_yi) / stride_yi;</div><div class="line"><a name="l00880"></a><span class="lineno"> 880</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> offset_out = xo + yo * width_out + ofm * width_out * height_out + r * width_out * height_out * depth_out;</div><div class="line"><a name="l00881"></a><span class="lineno"> 881</span> </div><div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  <span class="comment">// Compute 3D convolution</span></div><div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  convolution3d(in.data() + offset_in,</div><div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  weights.data() + ofm * width_weights * height_weights * depth_weights,</div><div class="line"><a name="l00885"></a><span class="lineno"> 885</span>  bias.data() + ofm,</div><div class="line"><a name="l00886"></a><span class="lineno"> 886</span>  out.data() + offset_out,</div><div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  xi, yi,</div><div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  width_in, height_in, depth_in,</div><div class="line"><a name="l00889"></a><span class="lineno"> 889</span>  width_weights, height_weights,</div><div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  <span class="keyword">static_cast<</span>int8_t<span class="keyword">></span>(in.fixed_point_position()));</div><div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  }</div><div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  }</div><div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  }</div><div class="line"><a name="l00894"></a><span class="lineno"> 894</span>  }</div><div class="line"><a name="l00895"></a><span class="lineno"> 895</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_aabcf39e3917f842dbc5fbb0d802f24d5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aabcf39e3917f842dbc5fbb0d802f24d5">arm_compute::test::fixed_point_arithmetic::detail::min</a></div><div class="ttdeci">fixed_point< T > min(fixed_point< T > x, fixed_point< T > y)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00875">FixedPoint.h:875</a></div></div> |
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| <td class="memname">void arm_compute::test::validation::tensor_operations::depth_convert </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>policy</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint32_t </td> |
| <td class="paramname"><em>shift</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
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| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00414">414</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="_error_8h_source.xhtml#l00031">ARM_COMPUTE_ERROR</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00237">Reference::compute_reference_depth_convert()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00099">depth_convert_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00415"></a><span class="lineno"> 415</span> {</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"The conversion is not supported"</span>);</div><div class="line"><a name="l00417"></a><span class="lineno"> 417</span> }</div><div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00031">Error.h:31</a></div></div> |
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| <a class="anchor" id="a531358310cc70fdd4f59637db7ce1b3e"></a> |
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| <td class="memname">void <a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a4485bbf8646087afcb6d724e613da68f">arm_compute::test::validation::tensor_operations::depth_convert</a>< float, int8_t > </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< float > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int8_t > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>policy</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint32_t </td> |
| <td class="paramname"><em>shift</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00430">430</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6fa4729d95f983955f0d93a30179deb2b86">arm_compute::SATURATE</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00431"></a><span class="lineno"> 431</span> {</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  <span class="keyword">const</span> int8_t fixed_point_position = <span class="keyword">static_cast<</span>int8_t<span class="keyword">></span>(in.fixed_point_position());</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span>  {</div><div class="line"><a name="l00435"></a><span class="lineno"> 435</span>  <span class="keywordtype">float</span> val = in[i] * (1 << fixed_point_position) + 0.5f;</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  out[i] = ((policy == ConvertPolicy::SATURATE) ? saturate_cast<int8_t>(val) : <span class="keyword">static_cast<</span>int8_t<span class="keyword">></span>(val));</div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  }</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> }</div></div><!-- fragment --> |
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| <a class="anchor" id="ac0098bc6f892a87934f223210dbfd6a9"></a> |
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| <td class="memname">void <a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a4485bbf8646087afcb6d724e613da68f">arm_compute::test::validation::tensor_operations::depth_convert</a>< int16_t, int32_t > </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int16_t > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int32_t > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>policy</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint32_t </td> |
| <td class="paramname"><em>shift</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
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| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00496">496</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00497"></a><span class="lineno"> 497</span> {</div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  {</div><div class="line"><a name="l00500"></a><span class="lineno"> 500</span>  out[i] = <span class="keyword">static_cast<</span>int32_t<span class="keyword">></span>(in[i]) << shift;</div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  }</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span> }</div></div><!-- fragment --> |
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| <a class="anchor" id="a447ea0d3749644c6eb970d78ff7e11db"></a> |
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| <td class="memname">void <a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a4485bbf8646087afcb6d724e613da68f">arm_compute::test::validation::tensor_operations::depth_convert</a>< int16_t, uint8_t > </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int16_t > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint8_t > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>policy</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint32_t </td> |
| <td class="paramname"><em>shift</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
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| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00487">487</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6fa4729d95f983955f0d93a30179deb2b86">arm_compute::SATURATE</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00488"></a><span class="lineno"> 488</span> {</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  {</div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  int16_t val = in[i] >> shift;</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  out[i] = ((policy == ConvertPolicy::SATURATE) ? saturate_cast<uint8_t>(val) : <span class="keyword">static_cast<</span>uint8_t<span class="keyword">></span>(val));</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  }</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span> }</div></div><!-- fragment --> |
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| <td class="memname">void <a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a4485bbf8646087afcb6d724e613da68f">arm_compute::test::validation::tensor_operations::depth_convert</a>< int8_t, float > </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int8_t > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< float > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>policy</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint32_t </td> |
| <td class="paramname"><em>shift</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00420">420</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00421"></a><span class="lineno"> 421</span> {</div><div class="line"><a name="l00422"></a><span class="lineno"> 422</span>  <span class="keyword">const</span> int8_t fixed_point_position = <span class="keyword">static_cast<</span>int8_t<span class="keyword">></span>(in.fixed_point_position());</div><div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  {</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span>  out[i] = <span class="keyword">static_cast<</span><span class="keywordtype">float</span><span class="keyword">></span>(in[i]) * (1.0f / (1 << fixed_point_position));</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  }</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a79219b20a374800b7da7222a70db89b2"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void <a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a4485bbf8646087afcb6d724e613da68f">arm_compute::test::validation::tensor_operations::depth_convert</a>< uint16_t, uint32_t > </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint16_t > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint32_t > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>policy</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint32_t </td> |
| <td class="paramname"><em>shift</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00478">478</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00479"></a><span class="lineno"> 479</span> {</div><div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  {</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  out[i] = <span class="keyword">static_cast<</span>uint32_t<span class="keyword">></span>(in[i]) << shift;</div><div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  }</div><div class="line"><a name="l00484"></a><span class="lineno"> 484</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a34b3b2d8ce85841a51f517bf38d3d3b3"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void <a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a4485bbf8646087afcb6d724e613da68f">arm_compute::test::validation::tensor_operations::depth_convert</a>< uint16_t, uint8_t > </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint16_t > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint8_t > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>policy</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint32_t </td> |
| <td class="paramname"><em>shift</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00468">468</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6fa4729d95f983955f0d93a30179deb2b86">arm_compute::SATURATE</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00469"></a><span class="lineno"> 469</span> {</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00471"></a><span class="lineno"> 471</span>  {</div><div class="line"><a name="l00472"></a><span class="lineno"> 472</span>  uint16_t val = in[i] >> shift;</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  out[i] = ((policy == ConvertPolicy::SATURATE) ? saturate_cast<uint8_t>(val) : <span class="keyword">static_cast<</span>uint8_t<span class="keyword">></span>(val));</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  }</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a0e91470444d96ed45eae0bac5b7c6042"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void <a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a4485bbf8646087afcb6d724e613da68f">arm_compute::test::validation::tensor_operations::depth_convert</a>< uint8_t, int16_t > </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint8_t > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int16_t > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>policy</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint32_t </td> |
| <td class="paramname"><em>shift</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00450">450</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00451"></a><span class="lineno"> 451</span> {</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  {</div><div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  out[i] = <span class="keyword">static_cast<</span>int16_t<span class="keyword">></span>(in[i]) << shift;</div><div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  }</div><div class="line"><a name="l00456"></a><span class="lineno"> 456</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a6b46cf712c2bf1e96eef20c6b1b816f5"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void <a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a4485bbf8646087afcb6d724e613da68f">arm_compute::test::validation::tensor_operations::depth_convert</a>< uint8_t, int32_t > </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint8_t > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< int32_t > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>policy</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint32_t </td> |
| <td class="paramname"><em>shift</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00459">459</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00460"></a><span class="lineno"> 460</span> {</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  {</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  out[i] = <span class="keyword">static_cast<</span>int32_t<span class="keyword">></span>(in[i]) << shift;</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  }</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a09a0ab9b11ba12a3d4230bb07198a06d"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void <a class="el" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#a4485bbf8646087afcb6d724e613da68f">arm_compute::test::validation::tensor_operations::depth_convert</a>< uint8_t, uint16_t > </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint8_t > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint16_t > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>policy</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint32_t </td> |
| <td class="paramname"><em>shift</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00441">441</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00442"></a><span class="lineno"> 442</span> {</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  {</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  out[i] = <span class="keyword">static_cast<</span>uint16_t<span class="keyword">></span>(in[i]) << shift;</div><div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  }</div><div class="line"><a name="l00447"></a><span class="lineno"> 447</span> }</div></div><!-- fragment --> |
| </div> |
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| <a class="anchor" id="aeffa8efd0492f825570507bc628e2968"></a> |
| <div class="memitem"> |
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| <td class="memname">void arm_compute::test::validation::tensor_operations::fixed_point_operation </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#afa20b6a7f4383003babd690f026f22dc">FixedPointOp</a> </td> |
| <td class="paramname"><em>op</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l01319">1319</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="_error_8h_source.xhtml#l00031">ARM_COMPUTE_ERROR</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00900">arm_compute::test::fixed_point_arithmetic::detail::div()</a>, <a class="el" href="namespacearm__compute.xhtml#afa20b6a7f4383003babd690f026f22dca8c670f8c37b95e1ed14a0ce414b049c7">arm_compute::EXP</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00915">arm_compute::test::fixed_point_arithmetic::detail::exp()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00081">Tensor< T >::fixed_point_position()</a>, <a class="el" href="namespacearm__compute.xhtml#afa20b6a7f4383003babd690f026f22dca59c58364795af22cad54630be156712b">arm_compute::INV_SQRT</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00925">arm_compute::test::fixed_point_arithmetic::detail::inv_sqrt()</a>, <a class="el" href="namespacearm__compute.xhtml#afa20b6a7f4383003babd690f026f22dca4b5ffcdaf38ce4d463171f5c977c5ab3">arm_compute::LOG</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00920">arm_compute::test::fixed_point_arithmetic::detail::log()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>, and <a class="el" href="namespacearm__compute.xhtml#afa20b6a7f4383003babd690f026f22dca4d98346f3d5cc5fa5666f0715abf25b1">arm_compute::RECIPROCAL</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00555">Reference::compute_reference_fixed_point_operation()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00348">fixed_point_operation_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l01320"></a><span class="lineno"> 1320</span> {</div><div class="line"><a name="l01321"></a><span class="lineno"> 1321</span>  <span class="keywordtype">int</span> p = in.fixed_point_position();</div><div class="line"><a name="l01322"></a><span class="lineno"> 1322</span>  <span class="keywordflow">switch</span>(op)</div><div class="line"><a name="l01323"></a><span class="lineno"> 1323</span>  {</div><div class="line"><a name="l01324"></a><span class="lineno"> 1324</span>  <span class="keywordflow">case</span> FixedPointOp::EXP:</div><div class="line"><a name="l01325"></a><span class="lineno"> 1325</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l01326"></a><span class="lineno"> 1326</span>  {</div><div class="line"><a name="l01327"></a><span class="lineno"> 1327</span>  out[i] = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aa4e01e9be9adcc40a69a4da48fa83a43">fixed_point_arithmetic::exp</a>(fixed_point_arithmetic::fixed_point<T>(in[i], p, <span class="keyword">true</span>)).raw();</div><div class="line"><a name="l01328"></a><span class="lineno"> 1328</span>  }</div><div class="line"><a name="l01329"></a><span class="lineno"> 1329</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01330"></a><span class="lineno"> 1330</span>  <span class="keywordflow">case</span> FixedPointOp::LOG:</div><div class="line"><a name="l01331"></a><span class="lineno"> 1331</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l01332"></a><span class="lineno"> 1332</span>  {</div><div class="line"><a name="l01333"></a><span class="lineno"> 1333</span>  out[i] = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a8c8ce35c61b4f71cccec28d18161eaa1">fixed_point_arithmetic::log</a>(fixed_point_arithmetic::fixed_point<T>(in[i], p, <span class="keyword">true</span>)).raw();</div><div class="line"><a name="l01334"></a><span class="lineno"> 1334</span>  }</div><div class="line"><a name="l01335"></a><span class="lineno"> 1335</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01336"></a><span class="lineno"> 1336</span>  <span class="keywordflow">case</span> FixedPointOp::INV_SQRT:</div><div class="line"><a name="l01337"></a><span class="lineno"> 1337</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l01338"></a><span class="lineno"> 1338</span>  {</div><div class="line"><a name="l01339"></a><span class="lineno"> 1339</span>  out[i] = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a2b7623d9dd3fde1d0a3bbe034967cff5">fixed_point_arithmetic::inv_sqrt</a>(fixed_point_arithmetic::fixed_point<T>(in[i], p, <span class="keyword">true</span>)).raw();</div><div class="line"><a name="l01340"></a><span class="lineno"> 1340</span>  }</div><div class="line"><a name="l01341"></a><span class="lineno"> 1341</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01342"></a><span class="lineno"> 1342</span>  <span class="keywordflow">case</span> FixedPointOp::RECIPROCAL:</div><div class="line"><a name="l01343"></a><span class="lineno"> 1343</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l01344"></a><span class="lineno"> 1344</span>  {</div><div class="line"><a name="l01345"></a><span class="lineno"> 1345</span>  out[i] = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a9d53af9692ab2f7ae6fc0017faeb46f0">fixed_point_arithmetic::div</a>(fixed_point_arithmetic::fixed_point<T>(1, p), fixed_point_arithmetic::fixed_point<T>(in[i], p, <span class="keyword">true</span>)).raw();</div><div class="line"><a name="l01346"></a><span class="lineno"> 1346</span>  }</div><div class="line"><a name="l01347"></a><span class="lineno"> 1347</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01348"></a><span class="lineno"> 1348</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l01349"></a><span class="lineno"> 1349</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Fixed point operation not supported"</span>);</div><div class="line"><a name="l01350"></a><span class="lineno"> 1350</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l01351"></a><span class="lineno"> 1351</span>  }</div><div class="line"><a name="l01352"></a><span class="lineno"> 1352</span> }</div><div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00031">Error.h:31</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_aa4e01e9be9adcc40a69a4da48fa83a43"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aa4e01e9be9adcc40a69a4da48fa83a43">arm_compute::test::fixed_point_arithmetic::detail::exp</a></div><div class="ttdeci">fixed_point< T > exp(fixed_point< T > x)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00915">FixedPoint.h:915</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_a8c8ce35c61b4f71cccec28d18161eaa1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a8c8ce35c61b4f71cccec28d18161eaa1">arm_compute::test::fixed_point_arithmetic::detail::log</a></div><div class="ttdeci">fixed_point< T > log(fixed_point< T > x)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00920">FixedPoint.h:920</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_a2b7623d9dd3fde1d0a3bbe034967cff5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a2b7623d9dd3fde1d0a3bbe034967cff5">arm_compute::test::fixed_point_arithmetic::detail::inv_sqrt</a></div><div class="ttdeci">fixed_point< T > inv_sqrt(fixed_point< T > x)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00925">FixedPoint.h:925</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_a9d53af9692ab2f7ae6fc0017faeb46f0"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a9d53af9692ab2f7ae6fc0017faeb46f0">arm_compute::test::fixed_point_arithmetic::detail::div</a></div><div class="ttdeci">fixed_point< T > div(fixed_point< T > x, fixed_point< T > y)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00900">FixedPoint.h:900</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="af8ba83a7ab2a51404613c27f4bf1b502"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void arm_compute::test::validation::tensor_operations::fixed_point_pixel_wise_multiplication </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in1</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in2</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">int </td> |
| <td class="paramname"><em>scale</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>convert_policy</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#add6426cbf2e057a195846d4ba09a50be">RoundingPolicy</a> </td> |
| <td class="paramname"><em>rounding_policy</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00617">617</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="_error_8h_source.xhtml#l00124">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="_error_8h_source.xhtml#l00115">ARM_COMPUTE_ERROR_ON_MSG</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00076">Tensor< T >::data_type()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00081">Tensor< T >::fixed_point_position()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a48d877702a2957f5a932c43a357866f9">arm_compute::QS16</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543">arm_compute::QS8</a>, and <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6fa4729d95f983955f0d93a30179deb2b86">arm_compute::SATURATE</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00298">Reference::compute_reference_fixed_point_pixel_wise_multiplication()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00161">fixed_point_pixel_wise_multiplication_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00618"></a><span class="lineno"> 618</span> {</div><div class="line"><a name="l00619"></a><span class="lineno"> 619</span>  <span class="keyword">using namespace </span>fixed_point_arithmetic;</div><div class="line"><a name="l00620"></a><span class="lineno"> 620</span> </div><div class="line"><a name="l00621"></a><span class="lineno"> 621</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> fixed_point_position = in1.fixed_point_position();</div><div class="line"><a name="l00622"></a><span class="lineno"> 622</span> </div><div class="line"><a name="l00623"></a><span class="lineno"> 623</span>  <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(in1.data_type() != in2.data_type() || in1.data_type() != out.data_type(),</div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  <span class="stringliteral">"Tensors must all have the same DataType"</span>);</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span>  <a class="code" href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(fixed_point_position != in2.fixed_point_position() || fixed_point_position != out.fixed_point_position(),</div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  <span class="stringliteral">"Fixed-point position must be the same for both inputs and outputs"</span>);</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span> </div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span>  <span class="comment">// Validate fixed_point_position</span></div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>((in1.data_type() == DataType::QS8) && (fixed_point_position == 0 || fixed_point_position > 7));</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>((in1.data_type() == DataType::QS16) && (fixed_point_position == 0 || fixed_point_position > 15));</div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span> </div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  fixed_point<T> fp_scale(scale, fixed_point_position);</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> is_sat = convert_policy == ConvertPolicy::SATURATE;</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  <span class="keyword">const</span> <span class="keywordtype">bool</span> do_scaling = scale != 1;</div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span> </div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in1.num_elements(); ++i)</div><div class="line"><a name="l00637"></a><span class="lineno"> 637</span>  {</div><div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  fixed_point<T> val1(in1[i], fixed_point_position, <span class="keyword">true</span>);</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  fixed_point<T> val2(in2[i], fixed_point_position, <span class="keyword">true</span>);</div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  fixed_point<T> res = (is_sat) ? val1 * val2 : mul<OverflowPolicy::WRAP>(val1, val2);</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  <span class="keywordflow">if</span>(do_scaling)</div><div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  {</div><div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  res = (is_sat) ? res * fp_scale : mul<OverflowPolicy::WRAP>(res, fp_scale);</div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  }</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  out[i] = res.raw();</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  }</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span> }</div><div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00124">Error.h:124</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a5bbdcf574d3f5e412fa6a1117911e67b"><div class="ttname"><a href="_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_MSG(cond,...)</div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00115">Error.h:115</a></div></div> |
| </div><!-- fragment --> |
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| <a class="anchor" id="a590f86899d2cdff14487c16ce361d2a9"></a> |
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| <table class="memname"> |
| <tr> |
| <td class="memname">void arm_compute::test::validation::tensor_operations::fully_connected_layer </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>weights</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>bias</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00899">899</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="_error_8h_source.xhtml#l00124">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00086">Tensor< T >::data()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00081">Tensor< T >::fixed_point_position()</a>, and <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00071">Tensor< T >::shape()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00435">Reference::compute_reference_fully_connected_layer()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00264">fully_connected_layer_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00900"></a><span class="lineno"> 900</span> {</div><div class="line"><a name="l00901"></a><span class="lineno"> 901</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(weights.shape().x() != out.shape().x());</div><div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(weights.shape().y() != in.shape().x() * in.shape().y() * in.shape().z());</div><div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> cols_weights = weights.shape().x();</div><div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> rows_weights = weights.shape().y();</div><div class="line"><a name="l00905"></a><span class="lineno"> 905</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> num_batches = in.shape().total_size() / rows_weights;</div><div class="line"><a name="l00906"></a><span class="lineno"> 906</span> </div><div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> k = 0; k < num_batches; ++k)</div><div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  {</div><div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  vector_matrix_multiply<T>(in.data() + k * rows_weights,</div><div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  weights.data(),</div><div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  bias.data(),</div><div class="line"><a name="l00912"></a><span class="lineno"> 912</span>  out.data() + k * cols_weights,</div><div class="line"><a name="l00913"></a><span class="lineno"> 913</span>  cols_weights,</div><div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  rows_weights,</div><div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  in.fixed_point_position());</div><div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  }</div><div class="line"><a name="l00917"></a><span class="lineno"> 917</span> }</div><div class="ttc" id="_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00124">Error.h:124</a></div></div> |
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| <td class="memname">void gemm </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in1</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in2</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in3</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">float </td> |
| <td class="paramname"><em>alpha</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">float </td> |
| <td class="paramname"><em>beta</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00506">506</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00081">Tensor< T >::fixed_point_position()</a>, and <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00071">Tensor< T >::shape()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00251">Reference::compute_reference_gemm()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00118">gemm_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00507"></a><span class="lineno"> 507</span> {</div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> M = out.shape().y();</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> N = out.shape().x();</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> K = in1.shape().x();</div><div class="line"><a name="l00511"></a><span class="lineno"> 511</span> </div><div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> r = 0; r < M; ++r)</div><div class="line"><a name="l00513"></a><span class="lineno"> 513</span>  {</div><div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> c = 0; c < N; ++c)</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  {</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  T acc = 0.0f;</div><div class="line"><a name="l00517"></a><span class="lineno"> 517</span> </div><div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> k = 0; k < K; ++k)</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  {</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <span class="keyword">const</span> T a0 = in1[r * K + k];</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  <span class="keyword">const</span> T b0 = in2[k * N + c];</div><div class="line"><a name="l00522"></a><span class="lineno"> 522</span> </div><div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  acc += a0 * b0;</div><div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  }</div><div class="line"><a name="l00525"></a><span class="lineno"> 525</span> </div><div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  <span class="comment">// Finalize the result: A * B * alpha + C * beta</span></div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  <span class="keyword">const</span> T c0 = in3[c + r * N];</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  out[c + r * N] = alpha * acc + beta * c0;</div><div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  }</div><div class="line"><a name="l00530"></a><span class="lineno"> 530</span>  }</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span> }</div></div><!-- fragment --> |
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| <td class="memname">void arm_compute::test::validation::tensor_operations::integral_image </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint8_t > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< uint32_t > & </td> |
| <td class="paramname"><em>out</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
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| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00225">225</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00071">Tensor< T >::shape()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00042">Reference::compute_reference_integral_image()</a>, and <a class="el" href="_reference_c_p_p_8cpp_source.xhtml#l00060">ReferenceCPP::integral_image()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00226"></a><span class="lineno"> 226</span> {</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  <span class="comment">// Length of dimensions</span></div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> width = in.shape().x();</div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> height = in.shape().y();</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> depth = in.shape().z() * in.shape()[3] * in.shape()[4] * in.shape()[5];</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span> </div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> image_size = width * height;</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span> </div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> z = 0; z < depth; ++z)</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  {</div><div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <span class="keywordtype">size_t</span> current_image = z * image_size;</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span> </div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span>  <span class="comment">//First element of each image</span></div><div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  out[current_image] = in[current_image];</div><div class="line"><a name="l00240"></a><span class="lineno"> 240</span> </div><div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  <span class="comment">// First row of each image (add only pixel on the left)</span></div><div class="line"><a name="l00242"></a><span class="lineno"> 242</span>  <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> x = 1; x < width; ++x)</div><div class="line"><a name="l00243"></a><span class="lineno"> 243</span>  {</div><div class="line"><a name="l00244"></a><span class="lineno"> 244</span>  out[current_image + x] = <span class="keyword">static_cast<</span>uint32_t<span class="keyword">></span>(in[current_image + x]) + out[current_image + x - 1];</div><div class="line"><a name="l00245"></a><span class="lineno"> 245</span>  }</div><div class="line"><a name="l00246"></a><span class="lineno"> 246</span> </div><div class="line"><a name="l00247"></a><span class="lineno"> 247</span>  <span class="comment">// Subsequent rows</span></div><div class="line"><a name="l00248"></a><span class="lineno"> 248</span>  <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> y = 1; y < height; ++y)</div><div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  {</div><div class="line"><a name="l00250"></a><span class="lineno"> 250</span>  <span class="keywordtype">size_t</span> current_row = current_image + (width * y);</div><div class="line"><a name="l00251"></a><span class="lineno"> 251</span> </div><div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="comment">// First element of each row (add only pixel up)</span></div><div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  out[current_row] = <span class="keyword">static_cast<</span>uint32_t<span class="keyword">></span>(in[current_row]) + out[current_row - width];</div><div class="line"><a name="l00254"></a><span class="lineno"> 254</span> </div><div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="comment">// Following row elements</span></div><div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> x = 1; x < width; ++x)</div><div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  {</div><div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keywordtype">size_t</span> current_pixel = current_row + x;</div><div class="line"><a name="l00259"></a><span class="lineno"> 259</span> </div><div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="comment">// out = in + up(out) + left(out) - up_left(out)</span></div><div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  out[current_pixel] = <span class="keyword">static_cast<</span>uint32_t<span class="keyword">></span>(in[current_pixel]) + out[current_pixel - 1]</div><div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  + out[current_pixel - width] - out[current_pixel - width - 1];</div><div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  }</div><div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  }</div><div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  }</div><div class="line"><a name="l00266"></a><span class="lineno"> 266</span> }</div></div><!-- fragment --> |
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| <td class="memname">void normalization_layer </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_normalization_layer_info.xhtml">NormalizationLayerInfo</a> </td> |
| <td class="paramname"><em>norm_info</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
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| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00921">921</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00885">arm_compute::test::fixed_point_arithmetic::detail::add()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00533">NormalizationLayerInfo::beta()</a>, <a class="el" href="namespacearm__compute.xhtml#ad4bb8dabdbf8ad75e34220cc666b59caa980fef040549733973683b1a868f96e5">arm_compute::CROSS_MAP</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00900">arm_compute::test::fixed_point_arithmetic::detail::div()</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00915">arm_compute::test::fixed_point_arithmetic::detail::exp()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00081">Tensor< T >::fixed_point_position()</a>, <a class="el" href="namespacearm__compute.xhtml#ad4bb8dabdbf8ad75e34220cc666b59caa6ff8bd96743aae9fd283cd822b84278e">arm_compute::IN_MAP_2D</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00537">NormalizationLayerInfo::kappa()</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00920">arm_compute::test::fixed_point_arithmetic::detail::log()</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00895">arm_compute::test::fixed_point_arithmetic::detail::mul()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00525">NormalizationLayerInfo::norm_size()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00935">arm_compute::test::fixed_point_arithmetic::detail::pow()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00548">NormalizationLayerInfo::scale_coeff()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00071">Tensor< T >::shape()</a>, and <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00521">NormalizationLayerInfo::type()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00475">Reference::compute_reference_normalization_layer()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00288">normalization_layer_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00922"></a><span class="lineno"> 922</span> {</div><div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  <span class="keyword">const</span> uint32_t norm_size = norm_info.norm_size();</div><div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  <a class="code" href="namespacearm__compute.xhtml#ad4bb8dabdbf8ad75e34220cc666b59ca">NormType</a> type = norm_info.type();</div><div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  <span class="keywordtype">float</span> beta = norm_info.beta();</div><div class="line"><a name="l00926"></a><span class="lineno"> 926</span>  uint32_t kappa = norm_info.kappa();</div><div class="line"><a name="l00927"></a><span class="lineno"> 927</span> </div><div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> cols = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(in.shape()[0]);</div><div class="line"><a name="l00929"></a><span class="lineno"> 929</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> rows = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(in.shape()[1]);</div><div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> depth = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(in.shape()[2]);</div><div class="line"><a name="l00931"></a><span class="lineno"> 931</span>  <span class="keywordtype">int</span> upper_dims = in.shape().total_size() / (cols * rows);</div><div class="line"><a name="l00932"></a><span class="lineno"> 932</span> </div><div class="line"><a name="l00933"></a><span class="lineno"> 933</span>  <span class="keywordtype">float</span> coeff = norm_info.scale_coeff();</div><div class="line"><a name="l00934"></a><span class="lineno"> 934</span>  <span class="keywordtype">int</span> radius_cols = norm_size / 2;</div><div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  <span class="comment">// IN_MAP_1D and CROSS_MAP normalize over a single axis only</span></div><div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  <span class="keywordtype">int</span> radius_rows = (NormType::IN_MAP_2D == type) ? norm_size / 2 : 0;</div><div class="line"><a name="l00937"></a><span class="lineno"> 937</span> </div><div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  <span class="keywordflow">if</span>(type == NormType::CROSS_MAP)</div><div class="line"><a name="l00939"></a><span class="lineno"> 939</span>  {</div><div class="line"><a name="l00940"></a><span class="lineno"> 940</span>  <span class="comment">// Remove also depth from upper dimensions since it is the axes we want</span></div><div class="line"><a name="l00941"></a><span class="lineno"> 941</span>  <span class="comment">// to use for normalization</span></div><div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  upper_dims /= depth;</div><div class="line"><a name="l00943"></a><span class="lineno"> 943</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> r = 0; r < upper_dims; ++r)</div><div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  {</div><div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < rows; ++i)</div><div class="line"><a name="l00946"></a><span class="lineno"> 946</span>  {</div><div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> k = 0; k < cols; ++k)</div><div class="line"><a name="l00948"></a><span class="lineno"> 948</span>  {</div><div class="line"><a name="l00949"></a><span class="lineno"> 949</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> l = 0; l < depth; ++l)</div><div class="line"><a name="l00950"></a><span class="lineno"> 950</span>  {</div><div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  <span class="keywordtype">float</span> accumulated_scale = 0.f;</div><div class="line"><a name="l00952"></a><span class="lineno"> 952</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> j = -radius_cols; j <= radius_cols; ++j)</div><div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  {</div><div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> z = l + j;</div><div class="line"><a name="l00955"></a><span class="lineno"> 955</span>  <span class="keywordflow">if</span>(z >= 0 && z < depth)</div><div class="line"><a name="l00956"></a><span class="lineno"> 956</span>  {</div><div class="line"><a name="l00957"></a><span class="lineno"> 957</span>  <span class="keyword">const</span> T value = in[k + i * cols + z * rows * cols + r * cols * rows * depth];</div><div class="line"><a name="l00958"></a><span class="lineno"> 958</span>  accumulated_scale += value * value;</div><div class="line"><a name="l00959"></a><span class="lineno"> 959</span>  }</div><div class="line"><a name="l00960"></a><span class="lineno"> 960</span>  }</div><div class="line"><a name="l00961"></a><span class="lineno"> 961</span>  out[k + i * cols + l * rows * cols + r * cols * rows * depth] = kappa + accumulated_scale * coeff;</div><div class="line"><a name="l00962"></a><span class="lineno"> 962</span>  }</div><div class="line"><a name="l00963"></a><span class="lineno"> 963</span>  }</div><div class="line"><a name="l00964"></a><span class="lineno"> 964</span>  }</div><div class="line"><a name="l00965"></a><span class="lineno"> 965</span>  }</div><div class="line"><a name="l00966"></a><span class="lineno"> 966</span>  }</div><div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00968"></a><span class="lineno"> 968</span>  {</div><div class="line"><a name="l00969"></a><span class="lineno"> 969</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> r = 0; r < upper_dims; ++r)</div><div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  {</div><div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < rows; ++i)</div><div class="line"><a name="l00972"></a><span class="lineno"> 972</span>  {</div><div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> k = 0; k < cols; ++k)</div><div class="line"><a name="l00974"></a><span class="lineno"> 974</span>  {</div><div class="line"><a name="l00975"></a><span class="lineno"> 975</span>  <span class="keywordtype">float</span> accumulated_scale = 0.f;</div><div class="line"><a name="l00976"></a><span class="lineno"> 976</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> j = -radius_rows; j <= radius_rows; ++j)</div><div class="line"><a name="l00977"></a><span class="lineno"> 977</span>  {</div><div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> y = i + j;</div><div class="line"><a name="l00979"></a><span class="lineno"> 979</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> l = -radius_cols; l <= radius_cols; ++l)</div><div class="line"><a name="l00980"></a><span class="lineno"> 980</span>  {</div><div class="line"><a name="l00981"></a><span class="lineno"> 981</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> x = k + l;</div><div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  <span class="keywordflow">if</span>((x >= 0 && y >= 0) && (x < cols && y < rows))</div><div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  {</div><div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  <span class="keyword">const</span> T value = in[x + y * cols + r * cols * rows];</div><div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  accumulated_scale += value * value;</div><div class="line"><a name="l00986"></a><span class="lineno"> 986</span>  }</div><div class="line"><a name="l00987"></a><span class="lineno"> 987</span>  }</div><div class="line"><a name="l00988"></a><span class="lineno"> 988</span>  }</div><div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  out[k + i * cols + r * cols * rows] = kappa + accumulated_scale * coeff;</div><div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  }</div><div class="line"><a name="l00991"></a><span class="lineno"> 991</span>  }</div><div class="line"><a name="l00992"></a><span class="lineno"> 992</span>  }</div><div class="line"><a name="l00993"></a><span class="lineno"> 993</span>  }</div><div class="line"><a name="l00994"></a><span class="lineno"> 994</span> </div><div class="line"><a name="l00995"></a><span class="lineno"> 995</span>  <span class="keywordflow">if</span>(beta == 1.f)</div><div class="line"><a name="l00996"></a><span class="lineno"> 996</span>  {</div><div class="line"><a name="l00997"></a><span class="lineno"> 997</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < out.num_elements(); ++i)</div><div class="line"><a name="l00998"></a><span class="lineno"> 998</span>  {</div><div class="line"><a name="l00999"></a><span class="lineno"> 999</span>  out[i] = in[i] / out[i];</div><div class="line"><a name="l01000"></a><span class="lineno"> 1000</span>  }</div><div class="line"><a name="l01001"></a><span class="lineno"> 1001</span>  }</div><div class="line"><a name="l01002"></a><span class="lineno"> 1002</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(beta == 0.5f)</div><div class="line"><a name="l01003"></a><span class="lineno"> 1003</span>  {</div><div class="line"><a name="l01004"></a><span class="lineno"> 1004</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < out.num_elements(); ++i)</div><div class="line"><a name="l01005"></a><span class="lineno"> 1005</span>  {</div><div class="line"><a name="l01006"></a><span class="lineno"> 1006</span>  out[i] = in[i] / std::sqrt(out[i]);</div><div class="line"><a name="l01007"></a><span class="lineno"> 1007</span>  }</div><div class="line"><a name="l01008"></a><span class="lineno"> 1008</span>  }</div><div class="line"><a name="l01009"></a><span class="lineno"> 1009</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l01010"></a><span class="lineno"> 1010</span>  {</div><div class="line"><a name="l01011"></a><span class="lineno"> 1011</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < out.num_elements(); ++i)</div><div class="line"><a name="l01012"></a><span class="lineno"> 1012</span>  {</div><div class="line"><a name="l01013"></a><span class="lineno"> 1013</span>  out[i] = in[i] * <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aa4e01e9be9adcc40a69a4da48fa83a43">std::exp</a>(<a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a8c8ce35c61b4f71cccec28d18161eaa1">std::log</a>(out[i]) * -beta);</div><div class="line"><a name="l01014"></a><span class="lineno"> 1014</span>  }</div><div class="line"><a name="l01015"></a><span class="lineno"> 1015</span>  }</div><div class="line"><a name="l01016"></a><span class="lineno"> 1016</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_aa4e01e9be9adcc40a69a4da48fa83a43"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aa4e01e9be9adcc40a69a4da48fa83a43">arm_compute::test::fixed_point_arithmetic::detail::exp</a></div><div class="ttdeci">fixed_point< T > exp(fixed_point< T > x)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00915">FixedPoint.h:915</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_a8c8ce35c61b4f71cccec28d18161eaa1"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#a8c8ce35c61b4f71cccec28d18161eaa1">arm_compute::test::fixed_point_arithmetic::detail::log</a></div><div class="ttdeci">fixed_point< T > log(fixed_point< T > x)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00920">FixedPoint.h:920</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad4bb8dabdbf8ad75e34220cc666b59ca"><div class="ttname"><a href="namespacearm__compute.xhtml#ad4bb8dabdbf8ad75e34220cc666b59ca">arm_compute::NormType</a></div><div class="ttdeci">NormType</div><div class="ttdoc">The normalization type used for the normalization layer. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00338">Types.h:338</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="acee95d0eabaf4dc59612123c1fbbffb1"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void arm_compute::test::validation::tensor_operations::pixel_wise_multiplication </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T1 > & </td> |
| <td class="paramname"><em>in1</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T2 > & </td> |
| <td class="paramname"><em>in2</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T3 > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">float </td> |
| <td class="paramname"><em>scale</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6f">ConvertPolicy</a> </td> |
| <td class="paramname"><em>convert_policy</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#add6426cbf2e057a195846d4ba09a50be">RoundingPolicy</a> </td> |
| <td class="paramname"><em>rounding_policy</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
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| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00579">579</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="_error_8h_source.xhtml#l00031">ARM_COMPUTE_ERROR</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>, <a class="el" href="tests_2_utils_8h_source.xhtml#l00289">arm_compute::test::cpp11::round_half_even()</a>, <a class="el" href="tests_2_utils_8h_source.xhtml#l00276">arm_compute::test::cpp11::round_half_up()</a>, <a class="el" href="namespacearm__compute.xhtml#a82b8ac759c804bc1fb4e2d21e178fb6fa4729d95f983955f0d93a30179deb2b86">arm_compute::SATURATE</a>, <a class="el" href="namespacearm__compute.xhtml#add6426cbf2e057a195846d4ba09a50bea02ff1fff1812f84c89547fcd6c176150">arm_compute::TO_NEAREST_EVEN</a>, <a class="el" href="namespacearm__compute.xhtml#add6426cbf2e057a195846d4ba09a50bea8c0084566b290fa9e5e429f4ae241f95">arm_compute::TO_NEAREST_UP</a>, <a class="el" href="namespacearm__compute.xhtml#add6426cbf2e057a195846d4ba09a50bea5631ad8e27788edfca7e13535d862c06">arm_compute::TO_ZERO</a>, and <a class="el" href="tests_2_utils_8h_source.xhtml#l00247">arm_compute::test::cpp11::trunc()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00280">Reference::compute_reference_pixel_wise_multiplication()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00141">pixel_wise_multiplication_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00580"></a><span class="lineno"> 580</span> {</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <span class="keywordflow">if</span>(scale < 0)</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  {</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Scale of pixel-wise multiplication must be non-negative"</span>);</div><div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  }</div><div class="line"><a name="l00585"></a><span class="lineno"> 585</span>  <span class="keyword">using</span> intermediate_type = <span class="keyword">typename</span> common_promoted_signed_type<T1, T2, T3>::intermediate_type;</div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in1.num_elements(); ++i)</div><div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  {</div><div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  <span class="keywordtype">double</span> val = <span class="keyword">static_cast<</span>intermediate_type<span class="keyword">></span>(in1[i]) * static_cast<intermediate_type>(in2[i]) * <span class="keyword">static_cast<</span><span class="keywordtype">double</span><span class="keyword">></span>(scale);</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <span class="keywordflow">if</span>(std::is_floating_point<T3>::value)</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  {</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  out[i] = val;</div><div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  }</div><div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  {</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <span class="keywordtype">double</span> rounded_val = 0;</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  <span class="keywordflow">switch</span>(rounding_policy)</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  {</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  <span class="keywordflow">case</span>(RoundingPolicy::TO_ZERO):</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  rounded_val = <a class="code" href="namespacearm__compute_1_1test_1_1cpp11.xhtml#ae8ee44ec85e2dd519488bfccf91db2dc">cpp11::trunc</a>(val);</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  <span class="keywordflow">case</span>(RoundingPolicy::TO_NEAREST_UP):</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  rounded_val = <a class="code" href="namespacearm__compute_1_1test_1_1cpp11.xhtml#ad473ea84f8bab197d5e32d7693f3f121">cpp11::round_half_up</a>(val);</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  <span class="keywordflow">case</span>(RoundingPolicy::TO_NEAREST_EVEN):</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  rounded_val = <a class="code" href="namespacearm__compute_1_1test_1_1cpp11.xhtml#aac60e291929bd45df7800bb860f7bf4f">cpp11::round_half_even</a>(val);</div><div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Unsupported rounding policy"</span>);</div><div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  }</div><div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  out[i] = (convert_policy == ConvertPolicy::SATURATE) ? saturate_cast<T3>(rounded_val) : <span class="keyword">static_cast<</span>T3<span class="keyword">></span>(rounded_val);</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  }</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  }</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_1_1cpp11_xhtml_ad473ea84f8bab197d5e32d7693f3f121"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1cpp11.xhtml#ad473ea84f8bab197d5e32d7693f3f121">arm_compute::test::cpp11::round_half_up</a></div><div class="ttdeci">T round_half_up(T value)</div><div class="ttdoc">Round floating-point value with half value rounding to positive infinity. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00276">Utils.h:276</a></div></div> |
| <div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00031">Error.h:31</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1cpp11_xhtml_ae8ee44ec85e2dd519488bfccf91db2dc"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1cpp11.xhtml#ae8ee44ec85e2dd519488bfccf91db2dc">arm_compute::test::cpp11::trunc</a></div><div class="ttdeci">T trunc(T value)</div><div class="ttdoc">Truncate floating-point value. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00247">Utils.h:247</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1cpp11_xhtml_aac60e291929bd45df7800bb860f7bf4f"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1cpp11.xhtml#aac60e291929bd45df7800bb860f7bf4f">arm_compute::test::cpp11::round_half_even</a></div><div class="ttdeci">T round_half_even(T value, T epsilon=std::numeric_limits< T >::epsilon())</div><div class="ttdoc">Round floating-point value with half value rounding to nearest even. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00289">Utils.h:289</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a8e93dde24e9dfb46feaec452e192977c"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void arm_compute::test::validation::tensor_operations::pooling_layer </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1_pooling_layer_info.xhtml">PoolingLayerInfo</a> </td> |
| <td class="paramname"><em>pool_info</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">int </td> |
| <td class="paramname"><em>fixed_point_position</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l01123">1123</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="namespacearm__compute.xhtml#adf2ced65e536375a1c96425d9fced858a26a4b44a837bf97b972628509912b4a5">arm_compute::MAX</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00880">arm_compute::test::fixed_point_arithmetic::detail::max()</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00875">arm_compute::test::fixed_point_arithmetic::detail::min()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00409">PadStrideInfo::pad()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00446">PoolingLayerInfo::pad_stride_info()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00442">PoolingLayerInfo::pool_size()</a>, <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00438">PoolingLayerInfo::pool_type()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00071">Tensor< T >::shape()</a>, <a class="el" href="_fixed_point_8inl_source.xhtml#l00063">arm_compute::sqadd_qs8()</a>, <a class="el" href="_fixed_point_8inl_source.xhtml#l00107">arm_compute::sqmul_qs8()</a>, and <a class="el" href="arm__compute_2core_2_types_8h_source.xhtml#l00405">PadStrideInfo::stride()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00499">Reference::compute_reference_pooling_layer()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00308">pooling_layer_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l01124"></a><span class="lineno"> 1124</span> {</div><div class="line"><a name="l01125"></a><span class="lineno"> 1125</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> pool_size = pool_info.pool_size();</div><div class="line"><a name="l01126"></a><span class="lineno"> 1126</span>  <a class="code" href="namespacearm__compute.xhtml#a9172da722f0a434e5cc07c0a3c115d93">PoolingType</a> type = pool_info.pool_type();</div><div class="line"><a name="l01127"></a><span class="lineno"> 1127</span>  <span class="keywordtype">int</span> pool_stride_x = 0;</div><div class="line"><a name="l01128"></a><span class="lineno"> 1128</span>  <span class="keywordtype">int</span> pool_stride_y = 0;</div><div class="line"><a name="l01129"></a><span class="lineno"> 1129</span>  <span class="keywordtype">int</span> pad_x = 0;</div><div class="line"><a name="l01130"></a><span class="lineno"> 1130</span>  <span class="keywordtype">int</span> pad_y = 0;</div><div class="line"><a name="l01131"></a><span class="lineno"> 1131</span>  std::tie(pool_stride_x, pool_stride_y) = pool_info.pad_stride_info().stride();</div><div class="line"><a name="l01132"></a><span class="lineno"> 1132</span>  std::tie(pad_x, pad_y) = pool_info.pad_stride_info().pad();</div><div class="line"><a name="l01133"></a><span class="lineno"> 1133</span> </div><div class="line"><a name="l01134"></a><span class="lineno"> 1134</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> cols_in = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(in.shape()[0]);</div><div class="line"><a name="l01135"></a><span class="lineno"> 1135</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> rows_in = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(in.shape()[1]);</div><div class="line"><a name="l01136"></a><span class="lineno"> 1136</span> </div><div class="line"><a name="l01137"></a><span class="lineno"> 1137</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> cols_out = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(out.shape()[0]);</div><div class="line"><a name="l01138"></a><span class="lineno"> 1138</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> rows_out = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(out.shape()[1]);</div><div class="line"><a name="l01139"></a><span class="lineno"> 1139</span> </div><div class="line"><a name="l01140"></a><span class="lineno"> 1140</span>  <span class="keywordtype">int</span> upper_dims = in.shape().total_size() / (cols_in * rows_in);</div><div class="line"><a name="l01141"></a><span class="lineno"> 1141</span> </div><div class="line"><a name="l01142"></a><span class="lineno"> 1142</span>  <span class="keywordtype">int</span> pooled_height = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(ceil(static_cast<float>(rows_in + 2 * pad_x - pool_size) / pool_stride_x)) + 1;</div><div class="line"><a name="l01143"></a><span class="lineno"> 1143</span>  <span class="keywordtype">int</span> pooled_width = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(ceil(static_cast<float>(cols_in + 2 * pad_y - pool_size) / pool_stride_y)) + 1;</div><div class="line"><a name="l01144"></a><span class="lineno"> 1144</span> </div><div class="line"><a name="l01145"></a><span class="lineno"> 1145</span>  <span class="keywordflow">if</span>((pooled_height - 1) * pool_stride_x >= rows_in + pad_x)</div><div class="line"><a name="l01146"></a><span class="lineno"> 1146</span>  {</div><div class="line"><a name="l01147"></a><span class="lineno"> 1147</span>  --pooled_height;</div><div class="line"><a name="l01148"></a><span class="lineno"> 1148</span>  }</div><div class="line"><a name="l01149"></a><span class="lineno"> 1149</span>  <span class="keywordflow">if</span>((pooled_width - 1) * pool_stride_y >= cols_in + pad_y)</div><div class="line"><a name="l01150"></a><span class="lineno"> 1150</span>  {</div><div class="line"><a name="l01151"></a><span class="lineno"> 1151</span>  --pooled_width;</div><div class="line"><a name="l01152"></a><span class="lineno"> 1152</span>  }</div><div class="line"><a name="l01153"></a><span class="lineno"> 1153</span> </div><div class="line"><a name="l01154"></a><span class="lineno"> 1154</span>  <span class="keywordflow">if</span>(type == PoolingType::MAX)</div><div class="line"><a name="l01155"></a><span class="lineno"> 1155</span>  {</div><div class="line"><a name="l01156"></a><span class="lineno"> 1156</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> r = 0; r < upper_dims; ++r)</div><div class="line"><a name="l01157"></a><span class="lineno"> 1157</span>  {</div><div class="line"><a name="l01158"></a><span class="lineno"> 1158</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < pooled_height; ++i)</div><div class="line"><a name="l01159"></a><span class="lineno"> 1159</span>  {</div><div class="line"><a name="l01160"></a><span class="lineno"> 1160</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> k = 0; k < pooled_width; ++k)</div><div class="line"><a name="l01161"></a><span class="lineno"> 1161</span>  {</div><div class="line"><a name="l01162"></a><span class="lineno"> 1162</span>  <span class="keywordtype">int</span> hstart = i * pool_stride_x - pad_x;</div><div class="line"><a name="l01163"></a><span class="lineno"> 1163</span>  <span class="keywordtype">int</span> wstart = k * pool_stride_y - pad_y;</div><div class="line"><a name="l01164"></a><span class="lineno"> 1164</span>  <span class="keywordtype">int</span> hend = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aabcf39e3917f842dbc5fbb0d802f24d5">std::min</a>(hstart + pool_size, rows_in);</div><div class="line"><a name="l01165"></a><span class="lineno"> 1165</span>  <span class="keywordtype">int</span> wend = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aabcf39e3917f842dbc5fbb0d802f24d5">std::min</a>(wstart + pool_size, cols_in);</div><div class="line"><a name="l01166"></a><span class="lineno"> 1166</span>  hstart = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::max</a>(hstart, 0);</div><div class="line"><a name="l01167"></a><span class="lineno"> 1167</span>  wstart = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::max</a>(wstart, 0);</div><div class="line"><a name="l01168"></a><span class="lineno"> 1168</span> </div><div class="line"><a name="l01169"></a><span class="lineno"> 1169</span>  T max_val = std::numeric_limits<T>::lowest();</div><div class="line"><a name="l01170"></a><span class="lineno"> 1170</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> y = hstart; y < hend; ++y)</div><div class="line"><a name="l01171"></a><span class="lineno"> 1171</span>  {</div><div class="line"><a name="l01172"></a><span class="lineno"> 1172</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> x = wstart; x < wend; ++x)</div><div class="line"><a name="l01173"></a><span class="lineno"> 1173</span>  {</div><div class="line"><a name="l01174"></a><span class="lineno"> 1174</span>  T val = in[r * cols_in * rows_in + y * cols_in + x];</div><div class="line"><a name="l01175"></a><span class="lineno"> 1175</span>  <span class="keywordflow">if</span>(val > max_val)</div><div class="line"><a name="l01176"></a><span class="lineno"> 1176</span>  {</div><div class="line"><a name="l01177"></a><span class="lineno"> 1177</span>  max_val = val;</div><div class="line"><a name="l01178"></a><span class="lineno"> 1178</span>  }</div><div class="line"><a name="l01179"></a><span class="lineno"> 1179</span>  }</div><div class="line"><a name="l01180"></a><span class="lineno"> 1180</span>  }</div><div class="line"><a name="l01181"></a><span class="lineno"> 1181</span> </div><div class="line"><a name="l01182"></a><span class="lineno"> 1182</span>  out[r * rows_out * cols_out + i * pooled_width + k] = max_val;</div><div class="line"><a name="l01183"></a><span class="lineno"> 1183</span>  }</div><div class="line"><a name="l01184"></a><span class="lineno"> 1184</span>  }</div><div class="line"><a name="l01185"></a><span class="lineno"> 1185</span>  }</div><div class="line"><a name="l01186"></a><span class="lineno"> 1186</span>  }</div><div class="line"><a name="l01187"></a><span class="lineno"> 1187</span>  <span class="keywordflow">else</span> <span class="comment">// Average pooling</span></div><div class="line"><a name="l01188"></a><span class="lineno"> 1188</span>  {</div><div class="line"><a name="l01189"></a><span class="lineno"> 1189</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> r = 0; r < upper_dims; ++r)</div><div class="line"><a name="l01190"></a><span class="lineno"> 1190</span>  {</div><div class="line"><a name="l01191"></a><span class="lineno"> 1191</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < pooled_height; ++i)</div><div class="line"><a name="l01192"></a><span class="lineno"> 1192</span>  {</div><div class="line"><a name="l01193"></a><span class="lineno"> 1193</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> k = 0; k < pooled_width; ++k)</div><div class="line"><a name="l01194"></a><span class="lineno"> 1194</span>  {</div><div class="line"><a name="l01195"></a><span class="lineno"> 1195</span>  T avg_val = 0;</div><div class="line"><a name="l01196"></a><span class="lineno"> 1196</span> </div><div class="line"><a name="l01197"></a><span class="lineno"> 1197</span>  <span class="keywordtype">int</span> hstart = i * pool_stride_x - pad_x;</div><div class="line"><a name="l01198"></a><span class="lineno"> 1198</span>  <span class="keywordtype">int</span> wstart = k * pool_stride_y - pad_y;</div><div class="line"><a name="l01199"></a><span class="lineno"> 1199</span>  <span class="keywordtype">int</span> hend = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aabcf39e3917f842dbc5fbb0d802f24d5">std::min</a>(hstart + pool_size, cols_in + pad_x);</div><div class="line"><a name="l01200"></a><span class="lineno"> 1200</span>  <span class="keywordtype">int</span> wend = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aabcf39e3917f842dbc5fbb0d802f24d5">std::min</a>(wstart + pool_size, rows_in + pad_y);</div><div class="line"><a name="l01201"></a><span class="lineno"> 1201</span>  <span class="keywordtype">int</span> pool = (hend - hstart) * (wend - wstart);</div><div class="line"><a name="l01202"></a><span class="lineno"> 1202</span>  hstart = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::max</a>(hstart, 0);</div><div class="line"><a name="l01203"></a><span class="lineno"> 1203</span>  wstart = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::max</a>(wstart, 0);</div><div class="line"><a name="l01204"></a><span class="lineno"> 1204</span>  hend = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aabcf39e3917f842dbc5fbb0d802f24d5">std::min</a>(hend, rows_in);</div><div class="line"><a name="l01205"></a><span class="lineno"> 1205</span>  wend = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aabcf39e3917f842dbc5fbb0d802f24d5">std::min</a>(wend, cols_in);</div><div class="line"><a name="l01206"></a><span class="lineno"> 1206</span> </div><div class="line"><a name="l01207"></a><span class="lineno"> 1207</span>  <span class="keywordflow">if</span>(std::is_floating_point<T>::value)</div><div class="line"><a name="l01208"></a><span class="lineno"> 1208</span>  {</div><div class="line"><a name="l01209"></a><span class="lineno"> 1209</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> y = hstart; y < hend; ++y)</div><div class="line"><a name="l01210"></a><span class="lineno"> 1210</span>  {</div><div class="line"><a name="l01211"></a><span class="lineno"> 1211</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> x = wstart; x < wend; ++x)</div><div class="line"><a name="l01212"></a><span class="lineno"> 1212</span>  {</div><div class="line"><a name="l01213"></a><span class="lineno"> 1213</span>  avg_val += in[r * cols_in * rows_in + y * cols_in + x];</div><div class="line"><a name="l01214"></a><span class="lineno"> 1214</span>  }</div><div class="line"><a name="l01215"></a><span class="lineno"> 1215</span>  }</div><div class="line"><a name="l01216"></a><span class="lineno"> 1216</span>  out[r * rows_out * cols_out + i * pooled_width + k] = avg_val / pool;</div><div class="line"><a name="l01217"></a><span class="lineno"> 1217</span>  }</div><div class="line"><a name="l01218"></a><span class="lineno"> 1218</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l01219"></a><span class="lineno"> 1219</span>  {</div><div class="line"><a name="l01220"></a><span class="lineno"> 1220</span>  <span class="keyword">static</span> std::array<qint8_t, 10> scale_values_q8 =</div><div class="line"><a name="l01221"></a><span class="lineno"> 1221</span>  { { 0x0, 0x0, 0x40, 0x2A, 0x20, 0x19, 0x15, 0x12, 0x10, 0xE } };</div><div class="line"><a name="l01222"></a><span class="lineno"> 1222</span> </div><div class="line"><a name="l01223"></a><span class="lineno"> 1223</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> y = hstart; y < hend; ++y)</div><div class="line"><a name="l01224"></a><span class="lineno"> 1224</span>  {</div><div class="line"><a name="l01225"></a><span class="lineno"> 1225</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> x = wstart; x < wend; ++x)</div><div class="line"><a name="l01226"></a><span class="lineno"> 1226</span>  {</div><div class="line"><a name="l01227"></a><span class="lineno"> 1227</span>  avg_val = <a class="code" href="namespacearm__compute.xhtml#a532d90e007d0cb6f3d43107229c40c32">sqadd_qs8</a>(avg_val, in[r * cols_in * rows_in + y * cols_in + x]);</div><div class="line"><a name="l01228"></a><span class="lineno"> 1228</span>  }</div><div class="line"><a name="l01229"></a><span class="lineno"> 1229</span>  }</div><div class="line"><a name="l01230"></a><span class="lineno"> 1230</span>  out[r * rows_out * cols_out + i * pooled_width + k] = <a class="code" href="namespacearm__compute.xhtml#af0b73b0c4980a551d7cd4edec43ffd92">sqmul_qs8</a>(avg_val, (scale_values_q8[pool] >> (7 - fixed_point_position)), fixed_point_position);</div><div class="line"><a name="l01231"></a><span class="lineno"> 1231</span>  }</div><div class="line"><a name="l01232"></a><span class="lineno"> 1232</span>  }</div><div class="line"><a name="l01233"></a><span class="lineno"> 1233</span>  }</div><div class="line"><a name="l01234"></a><span class="lineno"> 1234</span>  }</div><div class="line"><a name="l01235"></a><span class="lineno"> 1235</span>  }</div><div class="line"><a name="l01236"></a><span class="lineno"> 1236</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_aabcf39e3917f842dbc5fbb0d802f24d5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aabcf39e3917f842dbc5fbb0d802f24d5">arm_compute::test::fixed_point_arithmetic::detail::min</a></div><div class="ttdeci">fixed_point< T > min(fixed_point< T > x, fixed_point< T > y)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00875">FixedPoint.h:875</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a9172da722f0a434e5cc07c0a3c115d93"><div class="ttname"><a href="namespacearm__compute.xhtml#a9172da722f0a434e5cc07c0a3c115d93">arm_compute::PoolingType</a></div><div class="ttdeci">PoolingType</div><div class="ttdoc">Available pooling types. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00379">Types.h:379</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_af0b73b0c4980a551d7cd4edec43ffd92"><div class="ttname"><a href="namespacearm__compute.xhtml#af0b73b0c4980a551d7cd4edec43ffd92">arm_compute::sqmul_qs8</a></div><div class="ttdeci">qint8_t sqmul_qs8(qint8_t a, qint8_t b, int fixed_point_position)</div><div class="ttdoc">8 bit fixed point scalar saturating multiply </div><div class="ttdef"><b>Definition:</b> <a href="_fixed_point_8inl_source.xhtml#l00107">FixedPoint.inl:107</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_ad91bb73431b4de1f4946ed949d444849"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">arm_compute::test::fixed_point_arithmetic::detail::max</a></div><div class="ttdeci">fixed_point< T > max(fixed_point< T > x, fixed_point< T > y)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00880">FixedPoint.h:880</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a532d90e007d0cb6f3d43107229c40c32"><div class="ttname"><a href="namespacearm__compute.xhtml#a532d90e007d0cb6f3d43107229c40c32">arm_compute::sqadd_qs8</a></div><div class="ttdeci">qint8_t sqadd_qs8(qint8_t a, qint8_t b)</div><div class="ttdoc">8 bit fixed point scalar saturating add </div><div class="ttdef"><b>Definition:</b> <a href="_fixed_point_8inl_source.xhtml#l00063">FixedPoint.inl:63</a></div></div> |
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| <a class="anchor" id="a4a10dcdb4134d755119468d8464d7604"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void arm_compute::test::validation::tensor_operations::print </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">std::ostream & </td> |
| <td class="paramname"><em>out</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l01356">1356</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_tensor_visitors_8h_source.xhtml#l00373">print_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l01357"></a><span class="lineno"> 1357</span> {</div><div class="line"><a name="l01358"></a><span class="lineno"> 1358</span>  out << <span class="stringliteral">"\n"</span>;</div><div class="line"><a name="l01359"></a><span class="lineno"> 1359</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l01360"></a><span class="lineno"> 1360</span>  {</div><div class="line"><a name="l01361"></a><span class="lineno"> 1361</span>  out << in[i] << <span class="stringliteral">" "</span>;</div><div class="line"><a name="l01362"></a><span class="lineno"> 1362</span>  }</div><div class="line"><a name="l01363"></a><span class="lineno"> 1363</span>  out << <span class="stringliteral">"\n"</span>;</div><div class="line"><a name="l01364"></a><span class="lineno"> 1364</span> }</div></div><!-- fragment --> |
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| <td class="memname">void softmax_layer </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l01240">1240</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00885">arm_compute::test::fixed_point_arithmetic::detail::add()</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00900">arm_compute::test::fixed_point_arithmetic::detail::div()</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00915">arm_compute::test::fixed_point_arithmetic::detail::exp()</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00081">Tensor< T >::fixed_point_position()</a>, <a class="el" href="tests_2validation_2_fixed_point_8h_source.xhtml#l00880">arm_compute::test::fixed_point_arithmetic::detail::max()</a>, and <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00071">Tensor< T >::shape()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00530">Reference::compute_reference_softmax_layer()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00329">softmax_layer_visitor::operator()()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l01241"></a><span class="lineno"> 1241</span> {</div><div class="line"><a name="l01242"></a><span class="lineno"> 1242</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> cols = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(in.shape()[0]);</div><div class="line"><a name="l01243"></a><span class="lineno"> 1243</span>  <span class="keyword">const</span> <span class="keywordtype">int</span> upper_dims = in.shape().total_size() / cols;</div><div class="line"><a name="l01244"></a><span class="lineno"> 1244</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> r = 0; r < upper_dims; ++r)</div><div class="line"><a name="l01245"></a><span class="lineno"> 1245</span>  {</div><div class="line"><a name="l01246"></a><span class="lineno"> 1246</span>  <span class="comment">// Find max</span></div><div class="line"><a name="l01247"></a><span class="lineno"> 1247</span>  T <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">max</a> = std::numeric_limits<T>::lowest();</div><div class="line"><a name="l01248"></a><span class="lineno"> 1248</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> c = 0; c < cols; ++c)</div><div class="line"><a name="l01249"></a><span class="lineno"> 1249</span>  {</div><div class="line"><a name="l01250"></a><span class="lineno"> 1250</span>  <span class="keyword">const</span> T x = in[r * cols + c];</div><div class="line"><a name="l01251"></a><span class="lineno"> 1251</span>  <span class="keywordflow">if</span>(x > max)</div><div class="line"><a name="l01252"></a><span class="lineno"> 1252</span>  {</div><div class="line"><a name="l01253"></a><span class="lineno"> 1253</span>  max = x;</div><div class="line"><a name="l01254"></a><span class="lineno"> 1254</span>  }</div><div class="line"><a name="l01255"></a><span class="lineno"> 1255</span>  }</div><div class="line"><a name="l01256"></a><span class="lineno"> 1256</span> </div><div class="line"><a name="l01257"></a><span class="lineno"> 1257</span>  <span class="comment">// Regularize</span></div><div class="line"><a name="l01258"></a><span class="lineno"> 1258</span>  T sum = 0;</div><div class="line"><a name="l01259"></a><span class="lineno"> 1259</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> c = 0; c < cols; ++c)</div><div class="line"><a name="l01260"></a><span class="lineno"> 1260</span>  {</div><div class="line"><a name="l01261"></a><span class="lineno"> 1261</span>  <span class="keyword">const</span> T res = <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aa4e01e9be9adcc40a69a4da48fa83a43">exp</a>(in[r * cols + c] - max);</div><div class="line"><a name="l01262"></a><span class="lineno"> 1262</span>  out[r * cols + c] = res;</div><div class="line"><a name="l01263"></a><span class="lineno"> 1263</span>  sum += res;</div><div class="line"><a name="l01264"></a><span class="lineno"> 1264</span>  }</div><div class="line"><a name="l01265"></a><span class="lineno"> 1265</span> </div><div class="line"><a name="l01266"></a><span class="lineno"> 1266</span>  <span class="comment">// Normalize</span></div><div class="line"><a name="l01267"></a><span class="lineno"> 1267</span>  <span class="keyword">const</span> T norm_val = 1 / sum;</div><div class="line"><a name="l01268"></a><span class="lineno"> 1268</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> c = 0; c < cols; ++c)</div><div class="line"><a name="l01269"></a><span class="lineno"> 1269</span>  {</div><div class="line"><a name="l01270"></a><span class="lineno"> 1270</span>  out[r * cols + c] *= norm_val;</div><div class="line"><a name="l01271"></a><span class="lineno"> 1271</span>  }</div><div class="line"><a name="l01272"></a><span class="lineno"> 1272</span>  }</div><div class="line"><a name="l01273"></a><span class="lineno"> 1273</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_aa4e01e9be9adcc40a69a4da48fa83a43"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#aa4e01e9be9adcc40a69a4da48fa83a43">arm_compute::test::fixed_point_arithmetic::detail::exp</a></div><div class="ttdeci">fixed_point< T > exp(fixed_point< T > x)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00915">FixedPoint.h:915</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail_xhtml_ad91bb73431b4de1f4946ed949d444849"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">arm_compute::test::fixed_point_arithmetic::detail::max</a></div><div class="ttdeci">fixed_point< T > max(fixed_point< T > x, fixed_point< T > y)</div><div class="ttdef"><b>Definition:</b> <a href="tests_2validation_2_fixed_point_8h_source.xhtml#l00880">FixedPoint.h:880</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="aa2a75d7fb5a1cca91d6eab7888fc3431"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void arm_compute::test::validation::tensor_operations::threshold </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>in</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1validation_1_1_tensor.xhtml">Tensor</a>< T > & </td> |
| <td class="paramname"><em>out</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint8_t </td> |
| <td class="paramname"><em>threshold</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint8_t </td> |
| <td class="paramname"><em>false_value</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint8_t </td> |
| <td class="paramname"><em>true_value</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a3e6b23e675649b83240691abbc42a649">ThresholdType</a> </td> |
| <td class="paramname"><em>type</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">uint8_t </td> |
| <td class="paramname"><em>upper</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Definition at line <a class="el" href="_tensor_operations_8h_source.xhtml#l00651">651</a> of file <a class="el" href="_tensor_operations_8h_source.xhtml">TensorOperations.h</a>.</p> |
| |
| <p>References <a class="el" href="_error_8h_source.xhtml#l00031">ARM_COMPUTE_ERROR</a>, <a class="el" href="namespacearm__compute.xhtml#a3e6b23e675649b83240691abbc42a649a98ad0e8750ae10ad556ed7a62affb452">arm_compute::BINARY</a>, <a class="el" href="tests_2validation_2_tensor_8h_source.xhtml#l00066">Tensor< T >::num_elements()</a>, and <a class="el" href="namespacearm__compute.xhtml#a3e6b23e675649b83240691abbc42a649a01036ddcc971d02f6c32c3da31a119f2">arm_compute::RANGE</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_reference_8cpp_source.xhtml#l00316">Reference::compute_reference_threshold()</a>, <a class="el" href="fast__corners_8cl_source.xhtml#l00098">compute_strength()</a>, <a class="el" href="fast__corners_8cl_source.xhtml#l00155">fast_corners()</a>, and <a class="el" href="_tensor_visitors_8h_source.xhtml#l00181">arm_compute::test::validation::tensor_visitors::threshold_operation()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00652"></a><span class="lineno"> 652</span> {</div><div class="line"><a name="l00653"></a><span class="lineno"> 653</span>  <span class="keywordflow">switch</span>(type)</div><div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  {</div><div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  <span class="keywordflow">case</span> ThresholdType::BINARY:</div><div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  {</div><div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  out[i] = ((in[i] > <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#aa2a75d7fb5a1cca91d6eab7888fc3431">threshold</a>) ? true_value : false_value);</div><div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  }</div><div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00661"></a><span class="lineno"> 661</span>  <span class="keywordflow">case</span> ThresholdType::RANGE:</div><div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = 0; i < in.num_elements(); ++i)</div><div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  {</div><div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  <span class="keywordflow">if</span>(in[i] > upper)</div><div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  {</div><div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  out[i] = false_value;</div><div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  }</div><div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  <span class="keywordflow">else</span> <span class="keywordflow">if</span>(in[i] < <a class="code" href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#aa2a75d7fb5a1cca91d6eab7888fc3431">threshold</a>)</div><div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  {</div><div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  out[i] = false_value;</div><div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  }</div><div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  <span class="keywordflow">else</span></div><div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  {</div><div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  out[i] = true_value;</div><div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  }</div><div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  }</div><div class="line"><a name="l00677"></a><span class="lineno"> 677</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"Thresholding type not recognised"</span>);</div><div class="line"><a name="l00680"></a><span class="lineno"> 680</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00681"></a><span class="lineno"> 681</span>  }</div><div class="line"><a name="l00682"></a><span class="lineno"> 682</span> }</div><div class="ttc" id="_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error. </div><div class="ttdef"><b>Definition:</b> <a href="_error_8h_source.xhtml#l00031">Error.h:31</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations_xhtml_aa2a75d7fb5a1cca91d6eab7888fc3431"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation_1_1tensor__operations.xhtml#aa2a75d7fb5a1cca91d6eab7888fc3431">arm_compute::test::validation::tensor_operations::threshold</a></div><div class="ttdeci">void threshold(const Tensor< T > &in, Tensor< T > &out, uint8_t threshold, uint8_t false_value, uint8_t true_value, ThresholdType type, uint8_t upper)</div><div class="ttdef"><b>Definition:</b> <a href="_tensor_operations_8h_source.xhtml#l00651">TensorOperations.h:651</a></div></div> |
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