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| <p>Factory class to create and fill tensors. |
| <a href="classarm__compute_1_1test_1_1_tensor_library.xhtml#details">More...</a></p> |
| |
| <p><code>#include <<a class="el" href="_tensor_library_8h_source.xhtml">TensorLibrary.h</a>></code></p> |
| <table class="memberdecls"> |
| <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a> |
| Public Member Functions</h2></td></tr> |
| <tr class="memitem:a65b3f12d28af30bbb0d6cf75e7c4c316"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a65b3f12d28af30bbb0d6cf75e7c4c316">TensorLibrary</a> (std::string path)</td></tr> |
| <tr class="memdesc:a65b3f12d28af30bbb0d6cf75e7c4c316"><td class="mdescLeft"> </td><td class="mdescRight">Initialises the library with a <code>path</code> to the image directory. <a href="#a65b3f12d28af30bbb0d6cf75e7c4c316">More...</a><br /></td></tr> |
| <tr class="separator:a65b3f12d28af30bbb0d6cf75e7c4c316"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a467809227882867d26c5b5eea969497d"><td class="memItemLeft" align="right" valign="top"> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a467809227882867d26c5b5eea969497d">TensorLibrary</a> (std::string path, std::random_device::result_type <a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a4035a1140831801ced5dfa1d9fe6988a">seed</a>)</td></tr> |
| <tr class="memdesc:a467809227882867d26c5b5eea969497d"><td class="mdescLeft"> </td><td class="mdescRight">Initialises the library with a <code>path</code> to the image directory. <a href="#a467809227882867d26c5b5eea969497d">More...</a><br /></td></tr> |
| <tr class="separator:a467809227882867d26c5b5eea969497d"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a4035a1140831801ced5dfa1d9fe6988a"><td class="memItemLeft" align="right" valign="top">std::random_device::result_type </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a4035a1140831801ced5dfa1d9fe6988a">seed</a> () const </td></tr> |
| <tr class="memdesc:a4035a1140831801ced5dfa1d9fe6988a"><td class="mdescLeft"> </td><td class="mdescRight">Seed that is used to fill tensors with random values. <a href="#a4035a1140831801ced5dfa1d9fe6988a">More...</a><br /></td></tr> |
| <tr class="separator:a4035a1140831801ced5dfa1d9fe6988a"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a024fbe836c85d10afefc81cd2e51658e"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> & </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a024fbe836c85d10afefc81cd2e51658e">get</a> (const std::string &name) const </td></tr> |
| <tr class="memdesc:a024fbe836c85d10afefc81cd2e51658e"><td class="mdescLeft"> </td><td class="mdescRight">Provides a contant raw tensor for the specified image. <a href="#a024fbe836c85d10afefc81cd2e51658e">More...</a><br /></td></tr> |
| <tr class="separator:a024fbe836c85d10afefc81cd2e51658e"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:aa0cf1a79542c521b9f16d117b085c4d5"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#aa0cf1a79542c521b9f16d117b085c4d5">get</a> (const std::string &name)</td></tr> |
| <tr class="memdesc:aa0cf1a79542c521b9f16d117b085c4d5"><td class="mdescLeft"> </td><td class="mdescRight">Provides a raw tensor for the specified image. <a href="#aa0cf1a79542c521b9f16d117b085c4d5">More...</a><br /></td></tr> |
| <tr class="separator:aa0cf1a79542c521b9f16d117b085c4d5"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a3675bd0074fa527b42c6516a37f8f232"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a3675bd0074fa527b42c6516a37f8f232">get</a> (const std::string &name, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> data_type, int num_channels=1) const </td></tr> |
| <tr class="memdesc:a3675bd0074fa527b42c6516a37f8f232"><td class="mdescLeft"> </td><td class="mdescRight">Creates an uninitialised raw tensor with the given <code>data_type</code> and <code>num_channels</code>. <a href="#a3675bd0074fa527b42c6516a37f8f232">More...</a><br /></td></tr> |
| <tr class="separator:a3675bd0074fa527b42c6516a37f8f232"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a0e77935822447adc6cdce586f276f97d"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> & </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a0e77935822447adc6cdce586f276f97d">get</a> (const std::string &name, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format) const </td></tr> |
| <tr class="memdesc:a0e77935822447adc6cdce586f276f97d"><td class="mdescLeft"> </td><td class="mdescRight">Provides a contant raw tensor for the specified image after it has been converted to <code>format</code>. <a href="#a0e77935822447adc6cdce586f276f97d">More...</a><br /></td></tr> |
| <tr class="separator:a0e77935822447adc6cdce586f276f97d"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ab760ccaa18b95b99c73eb0e763f39ec2"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#ab760ccaa18b95b99c73eb0e763f39ec2">get</a> (const std::string &name, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format)</td></tr> |
| <tr class="memdesc:ab760ccaa18b95b99c73eb0e763f39ec2"><td class="mdescLeft"> </td><td class="mdescRight">Provides a raw tensor for the specified image after it has been converted to <code>format</code>. <a href="#ab760ccaa18b95b99c73eb0e763f39ec2">More...</a><br /></td></tr> |
| <tr class="separator:ab760ccaa18b95b99c73eb0e763f39ec2"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a11f5f1baaad31d1067564eccf599e90c"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> & </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a11f5f1baaad31d1067564eccf599e90c">get</a> (const std::string &name, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> channel) const </td></tr> |
| <tr class="memdesc:a11f5f1baaad31d1067564eccf599e90c"><td class="mdescLeft"> </td><td class="mdescRight">Provides a contant raw tensor for the specified channel after it has been extracted form the given image. <a href="#a11f5f1baaad31d1067564eccf599e90c">More...</a><br /></td></tr> |
| <tr class="separator:a11f5f1baaad31d1067564eccf599e90c"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:af6f0ca724e534653925306023dbb88e7"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#af6f0ca724e534653925306023dbb88e7">get</a> (const std::string &name, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> channel)</td></tr> |
| <tr class="memdesc:af6f0ca724e534653925306023dbb88e7"><td class="mdescLeft"> </td><td class="mdescRight">Provides a raw tensor for the specified channel after it has been extracted form the given image. <a href="#af6f0ca724e534653925306023dbb88e7">More...</a><br /></td></tr> |
| <tr class="separator:af6f0ca724e534653925306023dbb88e7"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a8c511f7046a704b8352ea8a8bbf456fa"><td class="memItemLeft" align="right" valign="top">const <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> & </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a8c511f7046a704b8352ea8a8bbf456fa">get</a> (const std::string &name, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> channel) const </td></tr> |
| <tr class="memdesc:a8c511f7046a704b8352ea8a8bbf456fa"><td class="mdescLeft"> </td><td class="mdescRight">Provides a constant raw tensor for the specified channel after it has been extracted form the given image formatted to <code>format</code>. <a href="#a8c511f7046a704b8352ea8a8bbf456fa">More...</a><br /></td></tr> |
| <tr class="separator:a8c511f7046a704b8352ea8a8bbf456fa"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ad6182f07b3eda32931598aa4f2bfc11a"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#ad6182f07b3eda32931598aa4f2bfc11a">get</a> (const std::string &name, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> channel)</td></tr> |
| <tr class="memdesc:ad6182f07b3eda32931598aa4f2bfc11a"><td class="mdescLeft"> </td><td class="mdescRight">Provides a raw tensor for the specified channel after it has been extracted form the given image formatted to <code>format</code>. <a href="#ad6182f07b3eda32931598aa4f2bfc11a">More...</a><br /></td></tr> |
| <tr class="separator:ad6182f07b3eda32931598aa4f2bfc11a"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a80a7b5ae084bf22b91bc5f68a06711c0"><td class="memTemplParams" colspan="2">template<typename T , typename D > </td></tr> |
| <tr class="memitem:a80a7b5ae084bf22b91bc5f68a06711c0"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a> (T &&tensor, D &&distribution, std::random_device::result_type seed_offset) const </td></tr> |
| <tr class="memdesc:a80a7b5ae084bf22b91bc5f68a06711c0"><td class="mdescLeft"> </td><td class="mdescRight">Fills the specified <code>tensor</code> with random values drawn from <code>distribution</code>. <a href="#a80a7b5ae084bf22b91bc5f68a06711c0">More...</a><br /></td></tr> |
| <tr class="separator:a80a7b5ae084bf22b91bc5f68a06711c0"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a935d861fcffb0099b001498c494daaf6"><td class="memTemplParams" colspan="2">template<typename D > </td></tr> |
| <tr class="memitem:a935d861fcffb0099b001498c494daaf6"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a935d861fcffb0099b001498c494daaf6">fill</a> (<a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> &raw, D &&distribution, std::random_device::result_type seed_offset) const </td></tr> |
| <tr class="memdesc:a935d861fcffb0099b001498c494daaf6"><td class="mdescLeft"> </td><td class="mdescRight">Fills the specified <code>raw</code> tensor with random values drawn from <code>distribution</code>. <a href="#a935d861fcffb0099b001498c494daaf6">More...</a><br /></td></tr> |
| <tr class="separator:a935d861fcffb0099b001498c494daaf6"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a5ee4fc10b84f941236df524f618b96c6"><td class="memTemplParams" colspan="2">template<typename T > </td></tr> |
| <tr class="memitem:a5ee4fc10b84f941236df524f618b96c6"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a5ee4fc10b84f941236df524f618b96c6">fill</a> (T &&tensor, const std::string &name, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format) const </td></tr> |
| <tr class="memdesc:a5ee4fc10b84f941236df524f618b96c6"><td class="mdescLeft"> </td><td class="mdescRight">Fills the specified <code>tensor</code> with the content of the specified image converted to the given format. <a href="#a5ee4fc10b84f941236df524f618b96c6">More...</a><br /></td></tr> |
| <tr class="separator:a5ee4fc10b84f941236df524f618b96c6"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a56f49b809537f3564de1eb7703c4dfab"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a56f49b809537f3564de1eb7703c4dfab">fill</a> (<a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> &raw, const std::string &name, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format) const </td></tr> |
| <tr class="memdesc:a56f49b809537f3564de1eb7703c4dfab"><td class="mdescLeft"> </td><td class="mdescRight">Fills the raw tensor with the content of the specified image converted to the given format. <a href="#a56f49b809537f3564de1eb7703c4dfab">More...</a><br /></td></tr> |
| <tr class="separator:a56f49b809537f3564de1eb7703c4dfab"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a4d049b9a5aba1f30b51f4bd36c3db076"><td class="memTemplParams" colspan="2">template<typename T > </td></tr> |
| <tr class="memitem:a4d049b9a5aba1f30b51f4bd36c3db076"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a4d049b9a5aba1f30b51f4bd36c3db076">fill</a> (T &&tensor, const std::string &name, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> channel) const </td></tr> |
| <tr class="memdesc:a4d049b9a5aba1f30b51f4bd36c3db076"><td class="mdescLeft"> </td><td class="mdescRight">Fills the specified <code>tensor</code> with the content of the specified channel extracted from the given image. <a href="#a4d049b9a5aba1f30b51f4bd36c3db076">More...</a><br /></td></tr> |
| <tr class="separator:a4d049b9a5aba1f30b51f4bd36c3db076"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a8fca830911339dca1cefcd78763063cf"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a8fca830911339dca1cefcd78763063cf">fill</a> (<a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> &raw, const std::string &name, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> channel) const </td></tr> |
| <tr class="memdesc:a8fca830911339dca1cefcd78763063cf"><td class="mdescLeft"> </td><td class="mdescRight">Fills the raw tensor with the content of the specified channel extracted from the given image. <a href="#a8fca830911339dca1cefcd78763063cf">More...</a><br /></td></tr> |
| <tr class="separator:a8fca830911339dca1cefcd78763063cf"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a36a9ddc6792949fb561cd788e6e31208"><td class="memTemplParams" colspan="2">template<typename T > </td></tr> |
| <tr class="memitem:a36a9ddc6792949fb561cd788e6e31208"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a36a9ddc6792949fb561cd788e6e31208">fill</a> (T &&tensor, const std::string &name, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> channel) const </td></tr> |
| <tr class="memdesc:a36a9ddc6792949fb561cd788e6e31208"><td class="mdescLeft"> </td><td class="mdescRight">Fills the specified <code>tensor</code> with the content of the specified channel extracted from the given image after it has been converted to the given format. <a href="#a36a9ddc6792949fb561cd788e6e31208">More...</a><br /></td></tr> |
| <tr class="separator:a36a9ddc6792949fb561cd788e6e31208"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a32621ba3c7498c558f27e61606af85f4"><td class="memItemLeft" align="right" valign="top">void </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a32621ba3c7498c558f27e61606af85f4">fill</a> (<a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> &raw, const std::string &name, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> channel) const </td></tr> |
| <tr class="memdesc:a32621ba3c7498c558f27e61606af85f4"><td class="mdescLeft"> </td><td class="mdescRight">Fills the raw tensor with the content of the specified channel extracted from the given image after it has been converted to the given format. <a href="#a32621ba3c7498c558f27e61606af85f4">More...</a><br /></td></tr> |
| <tr class="separator:a32621ba3c7498c558f27e61606af85f4"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:abb6f25295592e886976520216187eed7"><td class="memTemplParams" colspan="2">template<typename T > </td></tr> |
| <tr class="memitem:abb6f25295592e886976520216187eed7"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#abb6f25295592e886976520216187eed7">fill_tensor_uniform</a> (T &&tensor, std::random_device::result_type seed_offset) const </td></tr> |
| <tr class="memdesc:abb6f25295592e886976520216187eed7"><td class="mdescLeft"> </td><td class="mdescRight">Fill a tensor with uniform distribution across the range of its type. <a href="#abb6f25295592e886976520216187eed7">More...</a><br /></td></tr> |
| <tr class="separator:abb6f25295592e886976520216187eed7"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a150d2023c197e197f09f350ede795085"><td class="memTemplParams" colspan="2">template<typename T , typename D > </td></tr> |
| <tr class="memitem:a150d2023c197e197f09f350ede795085"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a150d2023c197e197f09f350ede795085">fill_tensor_uniform</a> (T &&tensor, std::random_device::result_type seed_offset, D low, D high) const </td></tr> |
| <tr class="memdesc:a150d2023c197e197f09f350ede795085"><td class="mdescLeft"> </td><td class="mdescRight">Fill a tensor with uniform distribution across the a specified range. <a href="#a150d2023c197e197f09f350ede795085">More...</a><br /></td></tr> |
| <tr class="separator:a150d2023c197e197f09f350ede795085"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:ad85dc4c57a27c44d114c573b9a80bad6"><td class="memTemplParams" colspan="2">template<typename T > </td></tr> |
| <tr class="memitem:ad85dc4c57a27c44d114c573b9a80bad6"><td class="memTemplItemLeft" align="right" valign="top">void </td><td class="memTemplItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#ad85dc4c57a27c44d114c573b9a80bad6">fill_layer_data</a> (T &&tensor, std::string name) const </td></tr> |
| <tr class="memdesc:ad85dc4c57a27c44d114c573b9a80bad6"><td class="mdescLeft"> </td><td class="mdescRight">Fills the specified <code>tensor</code> with data loaded from binary in specified path. <a href="#ad85dc4c57a27c44d114c573b9a80bad6">More...</a><br /></td></tr> |
| <tr class="separator:ad85dc4c57a27c44d114c573b9a80bad6"><td class="memSeparator" colspan="2"> </td></tr> |
| </table><table class="memberdecls"> |
| <tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a> |
| Static Public Member Functions</h2></td></tr> |
| <tr class="memitem:a34e94c998e4527d9556ccc5da82765fd"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a34e94c998e4527d9556ccc5da82765fd">get</a> (const <a class="el" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &shape, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> data_type, int num_channels=1, int fixed_point_position=0)</td></tr> |
| <tr class="memdesc:a34e94c998e4527d9556ccc5da82765fd"><td class="mdescLeft"> </td><td class="mdescRight">Creates an uninitialised raw tensor with the given <code>shape</code>, <code>data_type</code> and <code>num_channels</code>. <a href="#a34e94c998e4527d9556ccc5da82765fd">More...</a><br /></td></tr> |
| <tr class="separator:a34e94c998e4527d9556ccc5da82765fd"><td class="memSeparator" colspan="2"> </td></tr> |
| <tr class="memitem:a62ee584f91819c3ea097827f7630c1dd"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> </td><td class="memItemRight" valign="bottom"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a62ee584f91819c3ea097827f7630c1dd">get</a> (const <a class="el" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> &shape, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> format)</td></tr> |
| <tr class="memdesc:a62ee584f91819c3ea097827f7630c1dd"><td class="mdescLeft"> </td><td class="mdescRight">Creates an uninitialised raw tensor with the given <code>shape</code> and <code>format</code>. <a href="#a62ee584f91819c3ea097827f7630c1dd">More...</a><br /></td></tr> |
| <tr class="separator:a62ee584f91819c3ea097827f7630c1dd"><td class="memSeparator" colspan="2"> </td></tr> |
| </table> |
| <a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2> |
| <div class="textblock"><p>Factory class to create and fill tensors. </p> |
| <p>Allows to initialise tensors from loaded images or by specifying the shape explicitly. Furthermore, provides methods to fill tensors with the content of loaded images or with random values. </p> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8h_source.xhtml#l00056">56</a> of file <a class="el" href="_tensor_library_8h_source.xhtml">TensorLibrary.h</a>.</p> |
| </div><h2 class="groupheader">Constructor & Destructor Documentation</h2> |
| <a class="anchor" id="a65b3f12d28af30bbb0d6cf75e7c4c316"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml">TensorLibrary</a> </td> |
| <td>(</td> |
| <td class="paramtype">std::string </td> |
| <td class="paramname"><em>path</em></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Initialises the library with a <code>path</code> to the image directory. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">path</td><td>Path to load images from. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00208">208</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00209"></a><span class="lineno"> 209</span>  : _library_path(std::move(path)), _seed{ std::random_device()() }</div><div class="line"><a name="l00210"></a><span class="lineno"> 210</span> {</div><div class="line"><a name="l00211"></a><span class="lineno"> 211</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a467809227882867d26c5b5eea969497d"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml">TensorLibrary</a> </td> |
| <td>(</td> |
| <td class="paramtype">std::string </td> |
| <td class="paramname"><em>path</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">std::random_device::result_type </td> |
| <td class="paramname"><em>seed</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Initialises the library with a <code>path</code> to the image directory. </p> |
| <p>Furthermore, sets the seed for the random generator to <code>seed</code>.</p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">path</td><td>Path to load images from. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">seed</td><td>Seed used to initialise the random number generator. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00213">213</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  : _library_path(std::move(path)), _seed{ <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a4035a1140831801ced5dfa1d9fe6988a">seed</a> }</div><div class="line"><a name="l00215"></a><span class="lineno"> 215</span> {</div><div class="line"><a name="l00216"></a><span class="lineno"> 216</span> }</div><div class="ttc" id="classarm__compute_1_1test_1_1_tensor_library_xhtml_a4035a1140831801ced5dfa1d9fe6988a"><div class="ttname"><a href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a4035a1140831801ced5dfa1d9fe6988a">arm_compute::test::TensorLibrary::seed</a></div><div class="ttdeci">std::random_device::result_type seed() const </div><div class="ttdoc">Seed that is used to fill tensors with random values. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_library_8cpp_source.xhtml#l00218">TensorLibrary.cpp:218</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <h2 class="groupheader">Member Function Documentation</h2> |
| <a class="anchor" id="a80a7b5ae084bf22b91bc5f68a06711c0"></a> |
| <div class="memitem"> |
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| <td class="memname">void fill </td> |
| <td>(</td> |
| <td class="paramtype">T && </td> |
| <td class="paramname"><em>tensor</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">D && </td> |
| <td class="paramname"><em>distribution</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">std::random_device::result_type </td> |
| <td class="paramname"><em>seed_offset</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Fills the specified <code>tensor</code> with random values drawn from <code>distribution</code>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in,out]</td><td class="paramname">tensor</td><td>To be filled tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">distribution</td><td>Distribution used to fill the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">seed_offset</td><td>The offset will be added to the global seed before initialising the random generator.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section note"><dt>Note</dt><dd>The <code>distribution</code> has to provide operator(Generator &) which will be used to draw samples. </dd></dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8h_source.xhtml#l00368">368</a> of file <a class="el" href="_tensor_library_8h_source.xhtml">TensorLibrary.h</a>.</p> |
| |
| <p>References <a class="el" href="_helpers_8inl_source.xhtml#l00176">arm_compute::execute_window_loop()</a>, <a class="el" href="_window_8inl_source.xhtml#l00040">Window::set()</a>, and <a class="el" href="tests_2_utils_8h_source.xhtml#l00526">arm_compute::test::store_value_with_data_type()</a>.</p> |
| |
| <p>Referenced by <a class="el" href="_tensor_library_8cpp_source.xhtml#l00229">TensorLibrary::fill()</a>, and <a class="el" href="_tensor_library_8h_source.xhtml#l00437">TensorLibrary::fill_tensor_uniform()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00369"></a><span class="lineno"> 369</span> {</div><div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  Window window;</div><div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> d = 0; d < tensor.shape().num_dimensions(); ++d)</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>  window.set(d, Window::Dimension(0, tensor.shape()[d], 1));</div><div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  }</div><div class="line"><a name="l00375"></a><span class="lineno"> 375</span> </div><div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  std::mt19937 gen(_seed + seed_offset);</div><div class="line"><a name="l00377"></a><span class="lineno"> 377</span> </div><div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <a class="code" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a>(window, [&](<span class="keyword">const</span> Coordinates & <span class="keywordtype">id</span>)</div><div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  {</div><div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="keyword">using</span> ResultType = <span class="keyword">typename</span> std::remove_reference<D>::type::result_type;</div><div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="keyword">const</span> ResultType value = distribution(gen);</div><div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  <span class="keywordtype">void</span> *<span class="keyword">const</span> out_ptr = tensor(<span class="keywordtype">id</span>);</div><div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <a class="code" href="namespacearm__compute_1_1test.xhtml#a1e6934e95738573214c2ce1d6648d116">store_value_with_data_type</a>(out_ptr, value, tensor.data_type());</div><div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  });</div><div class="line"><a name="l00385"></a><span class="lineno"> 385</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_xhtml_a1e6934e95738573214c2ce1d6648d116"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a1e6934e95738573214c2ce1d6648d116">arm_compute::test::store_value_with_data_type</a></div><div class="ttdeci">void store_value_with_data_type(void *ptr, T value, DataType data_type)</div><div class="ttdoc">Write the value after casting the pointer according to data_type. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00526">Utils.h:526</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a6c0dcc38187027dcb89cd9724bc5a823"><div class="ttname"><a href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">arm_compute::execute_window_loop</a></div><div class="ttdeci">void execute_window_loop(const Window &w, L &&lambda_function, Ts &&...iterators)</div><div class="ttdoc">Iterate through the passed window, automatically adjusting the iterators and calling the lambda_funct...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00176">Helpers.inl:176</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a935d861fcffb0099b001498c494daaf6"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void fill </td> |
| <td>(</td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> & </td> |
| <td class="paramname"><em>raw</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">D && </td> |
| <td class="paramname"><em>distribution</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">std::random_device::result_type </td> |
| <td class="paramname"><em>seed_offset</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Fills the specified <code>raw</code> tensor with random values drawn from <code>distribution</code>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in,out]</td><td class="paramname">raw</td><td>To be filled raw. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">distribution</td><td>Distribution used to fill the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">seed_offset</td><td>The offset will be added to the global seed before initialising the random generator.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section note"><dt>Note</dt><dd>The <code>distribution</code> has to provide operator(Generator &) which will be used to draw samples. </dd></dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8h_source.xhtml#l00388">388</a> of file <a class="el" href="_tensor_library_8h_source.xhtml">TensorLibrary.h</a>.</p> |
| |
| <p>References <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00148">RawTensor::data()</a>, <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00112">RawTensor::data_type()</a>, <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00091">RawTensor::element_size()</a>, <a class="el" href="helpers_8h_source.xhtml#l00201">offset()</a>, <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00101">RawTensor::size()</a>, and <a class="el" href="tests_2_utils_8h_source.xhtml#l00526">arm_compute::test::store_value_with_data_type()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00389"></a><span class="lineno"> 389</span> {</div><div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  std::mt19937 gen(_seed + seed_offset);</div><div class="line"><a name="l00391"></a><span class="lineno"> 391</span> </div><div class="line"><a name="l00392"></a><span class="lineno"> 392</span>  <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> = 0; <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> < raw.size(); <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> += raw.element_size())</div><div class="line"><a name="l00393"></a><span class="lineno"> 393</span>  {</div><div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <span class="keyword">using</span> ResultType = <span class="keyword">typename</span> std::remove_reference<D>::type::result_type;</div><div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  <span class="keyword">const</span> ResultType value = distribution(gen);</div><div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <a class="code" href="namespacearm__compute_1_1test.xhtml#a1e6934e95738573214c2ce1d6648d116">store_value_with_data_type</a>(raw.data() + <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>, value, raw.data_type());</div><div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  }</div><div class="line"><a name="l00398"></a><span class="lineno"> 398</span> }</div><div class="ttc" id="helpers_8h_xhtml_a009469e4d9b8fce3b6d5e97d2077827d"><div class="ttname"><a href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a></div><div class="ttdeci">__global uchar * offset(const Image *img, int x, int y)</div><div class="ttdoc">Get the pointer position of a Image. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00201">helpers.h:201</a></div></div> |
| <div class="ttc" id="namespacearm__compute_1_1test_xhtml_a1e6934e95738573214c2ce1d6648d116"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a1e6934e95738573214c2ce1d6648d116">arm_compute::test::store_value_with_data_type</a></div><div class="ttdeci">void store_value_with_data_type(void *ptr, T value, DataType data_type)</div><div class="ttdoc">Write the value after casting the pointer according to data_type. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00526">Utils.h:526</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a5ee4fc10b84f941236df524f618b96c6"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void fill </td> |
| <td>(</td> |
| <td class="paramtype">T && </td> |
| <td class="paramname"><em>tensor</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> </td> |
| <td class="paramname"><em>format</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Fills the specified <code>tensor</code> with the content of the specified image converted to the given format. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in,out]</td><td class="paramname">tensor</td><td>To be filled tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to fill the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">format</td><td>Format of the image used to fill the tensor.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section warning"><dt>Warning</dt><dd>No check is performed that the specified format actually matches the format of the tensor. </dd></dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8h_source.xhtml#l00401">401</a> of file <a class="el" href="_tensor_library_8h_source.xhtml">TensorLibrary.h</a>.</p> |
| |
| <p>References <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00148">RawTensor::data()</a>, <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00091">RawTensor::element_size()</a>, <a class="el" href="tests_2_utils_8h_source.xhtml#l00611">arm_compute::test::index2coord()</a>, <a class="el" href="helpers_8h_source.xhtml#l00201">offset()</a>, <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00086">RawTensor::shape()</a>, and <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00101">RawTensor::size()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00402"></a><span class="lineno"> 402</span> {</div><div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  <span class="keyword">const</span> RawTensor &raw = <span class="keyword">get</span>(name, format);</div><div class="line"><a name="l00404"></a><span class="lineno"> 404</span> </div><div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> = 0; <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> < raw.size(); <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> += raw.element_size())</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>  <span class="keyword">const</span> Coordinates <span class="keywordtype">id</span> = <a class="code" href="namespacearm__compute_1_1test.xhtml#a24d8c0391cfa38e78969b6ad97c0ff09">index2coord</a>(raw.shape(), <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> / raw.element_size());</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>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">RawTensor::BufferType</a> *<span class="keyword">const</span> raw_ptr = raw.data() + <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>;</div><div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  <span class="keyword">const</span> <span class="keyword">auto</span> out_ptr = <span class="keyword">static_cast<</span><a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">RawTensor::BufferType</a> *<span class="keyword">></span>(tensor(<span class="keywordtype">id</span>));</div><div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  std::copy_n(raw_ptr, raw.element_size(), out_ptr);</div><div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  }</div><div class="line"><a name="l00413"></a><span class="lineno"> 413</span> }</div><div class="ttc" id="helpers_8h_xhtml_a009469e4d9b8fce3b6d5e97d2077827d"><div class="ttname"><a href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a></div><div class="ttdeci">__global uchar * offset(const Image *img, int x, int y)</div><div class="ttdoc">Get the pointer position of a Image. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00201">helpers.h:201</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_a9c3b791dba4a4cff3785264b9260e9d5"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">arm_compute::test::RawTensor::BufferType</a></div><div class="ttdeci">uint8_t BufferType</div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8h_source.xhtml#l00081">RawTensor.h:81</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> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a56f49b809537f3564de1eb7703c4dfab"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void fill </td> |
| <td>(</td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> & </td> |
| <td class="paramname"><em>raw</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> </td> |
| <td class="paramname"><em>format</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Fills the raw tensor with the content of the specified image converted to the given format. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in,out]</td><td class="paramname">raw</td><td>To be filled raw tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to fill the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">format</td><td>Format of the image used to fill the tensor.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section warning"><dt>Warning</dt><dd>No check is performed that the specified format actually matches the format of the tensor. </dd></dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00223">223</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| |
| <p>References <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00148">RawTensor::data()</a>, and <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00101">RawTensor::size()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00224"></a><span class="lineno"> 224</span> {</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keyword">const</span> RawTensor &src = <span class="keyword">get</span>(name, format);</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  std::copy_n(src.data(), raw.size(), raw.data());</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a4d049b9a5aba1f30b51f4bd36c3db076"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void fill </td> |
| <td>(</td> |
| <td class="paramtype">T && </td> |
| <td class="paramname"><em>tensor</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> </td> |
| <td class="paramname"><em>channel</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Fills the specified <code>tensor</code> with the content of the specified channel extracted from the given image. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in,out]</td><td class="paramname">tensor</td><td>To be filled tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to fill the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">channel</td><td>Channel of the image used to fill the tensor.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section note"><dt>Note</dt><dd>The channel has to be unambiguous so that the format can be inferred automatically.</dd></dl> |
| <dl class="section warning"><dt>Warning</dt><dd>No check is performed that the specified format actually matches the format of the tensor. </dd></dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8h_source.xhtml#l00416">416</a> of file <a class="el" href="_tensor_library_8h_source.xhtml">TensorLibrary.h</a>.</p> |
| |
| <p>References <a class="el" href="_tensor_library_8h_source.xhtml#l00368">TensorLibrary::fill()</a>, and <a class="el" href="tests_2_utils_8h_source.xhtml#l00381">arm_compute::test::get_format_for_channel()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00417"></a><span class="lineno"> 417</span> {</div><div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(std::forward<T>(tensor), name, <a class="code" href="namespacearm__compute_1_1test.xhtml#aa337ab76176f3c4193642ac6de3a61cf">get_format_for_channel</a>(channel), channel);</div><div class="line"><a name="l00419"></a><span class="lineno"> 419</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_xhtml_aa337ab76176f3c4193642ac6de3a61cf"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#aa337ab76176f3c4193642ac6de3a61cf">arm_compute::test::get_format_for_channel</a></div><div class="ttdeci">Format get_format_for_channel(Channel channel)</div><div class="ttdoc">Look up the format corresponding to a channel. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00381">Utils.h:381</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_tensor_library_xhtml_a80a7b5ae084bf22b91bc5f68a06711c0"><div class="ttname"><a href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">arm_compute::test::TensorLibrary::fill</a></div><div class="ttdeci">void fill(T &&tensor, D &&distribution, std::random_device::result_type seed_offset) const </div><div class="ttdoc">Fills the specified tensor with random values drawn from distribution. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_library_8h_source.xhtml#l00368">TensorLibrary.h:368</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a8fca830911339dca1cefcd78763063cf"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void fill </td> |
| <td>(</td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> & </td> |
| <td class="paramname"><em>raw</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> </td> |
| <td class="paramname"><em>channel</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Fills the raw tensor with the content of the specified channel extracted from the given image. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in,out]</td><td class="paramname">raw</td><td>To be filled raw tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to fill the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">channel</td><td>Channel of the image used to fill the tensor.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section note"><dt>Note</dt><dd>The channel has to be unambiguous so that the format can be inferred automatically.</dd></dl> |
| <dl class="section warning"><dt>Warning</dt><dd>No check is performed that the specified format actually matches the format of the tensor. </dd></dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00229">229</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| |
| <p>References <a class="el" href="_tensor_library_8h_source.xhtml#l00368">TensorLibrary::fill()</a>, and <a class="el" href="tests_2_utils_8h_source.xhtml#l00381">arm_compute::test::get_format_for_channel()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00230"></a><span class="lineno"> 230</span> {</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(raw, name, <a class="code" href="namespacearm__compute_1_1test.xhtml#aa337ab76176f3c4193642ac6de3a61cf">get_format_for_channel</a>(channel), channel);</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_xhtml_aa337ab76176f3c4193642ac6de3a61cf"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#aa337ab76176f3c4193642ac6de3a61cf">arm_compute::test::get_format_for_channel</a></div><div class="ttdeci">Format get_format_for_channel(Channel channel)</div><div class="ttdoc">Look up the format corresponding to a channel. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00381">Utils.h:381</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_tensor_library_xhtml_a80a7b5ae084bf22b91bc5f68a06711c0"><div class="ttname"><a href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">arm_compute::test::TensorLibrary::fill</a></div><div class="ttdeci">void fill(T &&tensor, D &&distribution, std::random_device::result_type seed_offset) const </div><div class="ttdoc">Fills the specified tensor with random values drawn from distribution. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_library_8h_source.xhtml#l00368">TensorLibrary.h:368</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a36a9ddc6792949fb561cd788e6e31208"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void fill </td> |
| <td>(</td> |
| <td class="paramtype">T && </td> |
| <td class="paramname"><em>tensor</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> </td> |
| <td class="paramname"><em>format</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> </td> |
| <td class="paramname"><em>channel</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Fills the specified <code>tensor</code> with the content of the specified channel extracted from the given image after it has been converted to the given format. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in,out]</td><td class="paramname">tensor</td><td>To be filled tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to fill the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">format</td><td>Format of the image used to fill the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">channel</td><td>Channel of the image used to fill the tensor.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section warning"><dt>Warning</dt><dd>No check is performed that the specified format actually matches the format of the tensor. </dd></dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8h_source.xhtml#l00422">422</a> of file <a class="el" href="_tensor_library_8h_source.xhtml">TensorLibrary.h</a>.</p> |
| |
| <p>References <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00148">RawTensor::data()</a>, <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00091">RawTensor::element_size()</a>, <a class="el" href="tests_2_utils_8h_source.xhtml#l00611">arm_compute::test::index2coord()</a>, <a class="el" href="helpers_8h_source.xhtml#l00201">offset()</a>, <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00086">RawTensor::shape()</a>, and <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00101">RawTensor::size()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00423"></a><span class="lineno"> 423</span> {</div><div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  <span class="keyword">const</span> RawTensor &raw = <span class="keyword">get</span>(name, format, channel);</div><div class="line"><a name="l00425"></a><span class="lineno"> 425</span> </div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> = 0; <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> < raw.size(); <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> += raw.element_size())</div><div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  {</div><div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  <span class="keyword">const</span> Coordinates <span class="keywordtype">id</span> = <a class="code" href="namespacearm__compute_1_1test.xhtml#a24d8c0391cfa38e78969b6ad97c0ff09">index2coord</a>(raw.shape(), <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> / raw.element_size());</div><div class="line"><a name="l00429"></a><span class="lineno"> 429</span> </div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">RawTensor::BufferType</a> *<span class="keyword">const</span> raw_ptr = raw.data() + <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>;</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  <span class="keyword">const</span> <span class="keyword">auto</span> out_ptr = <span class="keyword">static_cast<</span><a class="code" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">RawTensor::BufferType</a> *<span class="keyword">></span>(tensor(<span class="keywordtype">id</span>));</div><div class="line"><a name="l00432"></a><span class="lineno"> 432</span>  std::copy_n(raw_ptr, raw.element_size(), out_ptr);</div><div class="line"><a name="l00433"></a><span class="lineno"> 433</span>  }</div><div class="line"><a name="l00434"></a><span class="lineno"> 434</span> }</div><div class="ttc" id="helpers_8h_xhtml_a009469e4d9b8fce3b6d5e97d2077827d"><div class="ttname"><a href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a></div><div class="ttdeci">__global uchar * offset(const Image *img, int x, int y)</div><div class="ttdoc">Get the pointer position of a Image. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00201">helpers.h:201</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_raw_tensor_xhtml_a9c3b791dba4a4cff3785264b9260e9d5"><div class="ttname"><a href="classarm__compute_1_1test_1_1_raw_tensor.xhtml#a9c3b791dba4a4cff3785264b9260e9d5">arm_compute::test::RawTensor::BufferType</a></div><div class="ttdeci">uint8_t BufferType</div><div class="ttdef"><b>Definition:</b> <a href="_raw_tensor_8h_source.xhtml#l00081">RawTensor.h:81</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> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a32621ba3c7498c558f27e61606af85f4"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void fill </td> |
| <td>(</td> |
| <td class="paramtype"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> & </td> |
| <td class="paramname"><em>raw</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> </td> |
| <td class="paramname"><em>format</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> </td> |
| <td class="paramname"><em>channel</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Fills the raw tensor with the content of the specified channel extracted from the given image after it has been converted to the given format. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in,out]</td><td class="paramname">raw</td><td>To be filled raw tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to fill the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">format</td><td>Format of the image used to fill the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">channel</td><td>Channel of the image used to fill the tensor.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section warning"><dt>Warning</dt><dd>No check is performed that the specified format actually matches the format of the tensor. </dd></dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00234">234</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| |
| <p>References <a class="el" href="_tensor_cache_8h_source.xhtml#l00105">TensorCache::add()</a>, <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00148">RawTensor::data()</a>, <a class="el" href="_tensor_cache_8h_source.xhtml#l00093">TensorCache::find()</a>, <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00107">RawTensor::format()</a>, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aadfcf28d0734569a6a693bc8194de62bf">arm_compute::G</a>, <a class="el" href="tests_2_utils_8h_source.xhtml#l00400">arm_compute::test::get_channel_format()</a>, <a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455aae1e1d3d40573127e9ee0480caf1283d6">arm_compute::R</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0">arm_compute::RGB888</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::S16</a>, <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00086">RawTensor::shape()</a>, <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00101">RawTensor::size()</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::U16</a>, and <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::U8</a>.</p> |
| <div class="fragment"><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="keyword">const</span> RawTensor &src = <span class="keyword">get</span>(name, format, channel);</div><div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  std::copy_n(src.data(), raw.size(), raw.data());</div><div class="line"><a name="l00238"></a><span class="lineno"> 238</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="ad85dc4c57a27c44d114c573b9a80bad6"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void fill_layer_data </td> |
| <td>(</td> |
| <td class="paramtype">T && </td> |
| <td class="paramname"><em>tensor</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">std::string </td> |
| <td class="paramname"><em>name</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Fills the specified <code>tensor</code> with data loaded from binary in specified path. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in,out]</td><td class="paramname">tensor</td><td>To be filled tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td>Data file. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8h_source.xhtml#l00621">621</a> of file <a class="el" href="_tensor_library_8h_source.xhtml">TensorLibrary.h</a>.</p> |
| |
| <p>References <a class="el" href="_helpers_8inl_source.xhtml#l00176">arm_compute::execute_window_loop()</a>, <a class="el" href="_window_8inl_source.xhtml#l00040">Window::set()</a>, and <a class="el" href="tests_2_utils_8h_source.xhtml#l00526">arm_compute::test::store_value_with_data_type()</a>.</p> |
| <div class="fragment"><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> <span class="preprocessor">#ifdef _WIN32</span></div><div class="line"><a name="l00624"></a><span class="lineno"> 624</span>  <span class="keyword">const</span> std::string path_separator(<span class="stringliteral">"\\"</span>);</div><div class="line"><a name="l00625"></a><span class="lineno"> 625</span> <span class="preprocessor">#else</span></div><div class="line"><a name="l00626"></a><span class="lineno"> 626</span>  <span class="keyword">const</span> std::string path_separator(<span class="stringliteral">"/"</span>);</div><div class="line"><a name="l00627"></a><span class="lineno"> 627</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00628"></a><span class="lineno"> 628</span> </div><div class="line"><a name="l00629"></a><span class="lineno"> 629</span>  <span class="keyword">const</span> std::string path = _library_path + path_separator + name;</div><div class="line"><a name="l00630"></a><span class="lineno"> 630</span> </div><div class="line"><a name="l00631"></a><span class="lineno"> 631</span>  <span class="comment">// Open file</span></div><div class="line"><a name="l00632"></a><span class="lineno"> 632</span>  std::ifstream file(path, std::ios::in | std::ios::binary);</div><div class="line"><a name="l00633"></a><span class="lineno"> 633</span>  <span class="keywordflow">if</span>(!file.good())</div><div class="line"><a name="l00634"></a><span class="lineno"> 634</span>  {</div><div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  <span class="keywordflow">throw</span> std::runtime_error(<span class="stringliteral">"Could not load binary data: "</span> + path);</div><div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  }</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>  Window window;</div><div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  <span class="keywordflow">for</span>(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> d = 0; d < tensor.shape().num_dimensions(); ++d)</div><div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  {</div><div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  window.set(d, Window::Dimension(0, tensor.shape()[d], 1));</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> </div><div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  <a class="code" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a>(window, [&](<span class="keyword">const</span> Coordinates & <span class="keywordtype">id</span>)</div><div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  {</div><div class="line"><a name="l00646"></a><span class="lineno"> 646</span>  <span class="keywordtype">float</span> val;</div><div class="line"><a name="l00647"></a><span class="lineno"> 647</span>  file.read(reinterpret_cast<char *>(&val), <span class="keyword">sizeof</span>(<span class="keywordtype">float</span>));</div><div class="line"><a name="l00648"></a><span class="lineno"> 648</span>  <span class="keywordtype">void</span> *<span class="keyword">const</span> out_ptr = tensor(<span class="keywordtype">id</span>);</div><div class="line"><a name="l00649"></a><span class="lineno"> 649</span>  <a class="code" href="namespacearm__compute_1_1test.xhtml#a1e6934e95738573214c2ce1d6648d116">store_value_with_data_type</a>(out_ptr, val, tensor.data_type());</div><div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  });</div><div class="line"><a name="l00651"></a><span class="lineno"> 651</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_xhtml_a1e6934e95738573214c2ce1d6648d116"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a1e6934e95738573214c2ce1d6648d116">arm_compute::test::store_value_with_data_type</a></div><div class="ttdeci">void store_value_with_data_type(void *ptr, T value, DataType data_type)</div><div class="ttdoc">Write the value after casting the pointer according to data_type. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00526">Utils.h:526</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_a6c0dcc38187027dcb89cd9724bc5a823"><div class="ttname"><a href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">arm_compute::execute_window_loop</a></div><div class="ttdeci">void execute_window_loop(const Window &w, L &&lambda_function, Ts &&...iterators)</div><div class="ttdoc">Iterate through the passed window, automatically adjusting the iterators and calling the lambda_funct...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00176">Helpers.inl:176</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="abb6f25295592e886976520216187eed7"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void fill_tensor_uniform </td> |
| <td>(</td> |
| <td class="paramtype">T && </td> |
| <td class="paramname"><em>tensor</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">std::random_device::result_type </td> |
| <td class="paramname"><em>seed_offset</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Fill a tensor with uniform distribution across the range of its type. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in,out]</td><td class="paramname">tensor</td><td>To be filled tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">seed_offset</td><td>The offset will be added to the global seed before initialising the random generator. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8h_source.xhtml#l00437">437</a> of file <a class="el" href="_tensor_library_8h_source.xhtml">TensorLibrary.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#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::F16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::F32</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e">arm_compute::F64</a>, <a class="el" href="_tensor_library_8h_source.xhtml#l00368">TensorLibrary::fill()</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="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543">arm_compute::QS8</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::S16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::S32</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc">arm_compute::S64</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">arm_compute::S8</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6abd7ef6d4f35bc7d05c559b65032f15d1">arm_compute::SIZET</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::U16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::U32</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa">arm_compute::U64</a>, and <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::U8</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> {</div><div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <span class="keywordflow">switch</span>(tensor.data_type())</div><div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  {</div><div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>:</div><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>  std::uniform_int_distribution<uint8_t> distribution_u8(std::numeric_limits<uint8_t>::lowest(), <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::numeric_limits<uint8_t>::max</a>());</div><div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_u8, seed_offset);</div><div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  <span class="keywordflow">break</span>;</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">DataType::S8</a>:</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543">DataType::QS8</a>:</div><div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  {</div><div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  std::uniform_int_distribution<int8_t> distribution_s8(std::numeric_limits<int8_t>::lowest(), <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::numeric_limits<int8_t>::max</a>());</div><div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_s8, seed_offset);</div><div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  <span class="keywordflow">break</span>;</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">DataType::U16</a>:</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>  std::uniform_int_distribution<uint16_t> distribution_u16(std::numeric_limits<uint16_t>::lowest(), <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::numeric_limits<uint16_t>::max</a>());</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_u16, seed_offset);</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  }</div><div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">DataType::S16</a>:</div><div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  {</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  std::uniform_int_distribution<int16_t> distribution_s16(std::numeric_limits<int16_t>::lowest(), <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::numeric_limits<int16_t>::max</a>());</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_s16, seed_offset);</div><div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00465"></a><span class="lineno"> 465</span>  }</div><div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>:</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  {</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  std::uniform_int_distribution<uint32_t> distribution_u32(std::numeric_limits<uint32_t>::lowest(), <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::numeric_limits<uint32_t>::max</a>());</div><div class="line"><a name="l00469"></a><span class="lineno"> 469</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_u32, seed_offset);</div><div class="line"><a name="l00470"></a><span class="lineno"> 470</span>  <span class="keywordflow">break</span>;</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>:</div><div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  {</div><div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  std::uniform_int_distribution<int32_t> distribution_s32(std::numeric_limits<int32_t>::lowest(), <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::numeric_limits<int32_t>::max</a>());</div><div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_s32, seed_offset);</div><div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  }</div><div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa">DataType::U64</a>:</div><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>  std::uniform_int_distribution<uint64_t> distribution_u64(std::numeric_limits<uint64_t>::lowest(), <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::numeric_limits<uint64_t>::max</a>());</div><div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_u64, seed_offset);</div><div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  <span class="keywordflow">break</span>;</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>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc">DataType::S64</a>:</div><div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  {</div><div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  std::uniform_int_distribution<int64_t> distribution_s64(std::numeric_limits<int64_t>::lowest(), <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::numeric_limits<int64_t>::max</a>());</div><div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_s64, seed_offset);</div><div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00489"></a><span class="lineno"> 489</span>  }</div><div class="line"><a name="l00490"></a><span class="lineno"> 490</span> <span class="preprocessor">#ifdef ENABLE_FP16</span></div><div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>:</div><div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  {</div><div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  std::uniform_real_distribution<float16_t> distribution_f16(std::numeric_limits<float16_t>::lowest(), <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::numeric_limits<float16_t>::max</a>());</div><div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_f16, seed_offset);</div><div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  }</div><div class="line"><a name="l00497"></a><span class="lineno"> 497</span> <span class="preprocessor">#endif</span></div><div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>:</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>  <span class="comment">// It doesn't make sense to check [-inf, inf], so hard code it to a big number</span></div><div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  std::uniform_real_distribution<float> distribution_f32(-1000.f, 1000.f);</div><div class="line"><a name="l00502"></a><span class="lineno"> 502</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_f32, seed_offset);</div><div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00504"></a><span class="lineno"> 504</span>  }</div><div class="line"><a name="l00505"></a><span class="lineno"> 505</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e">DataType::F64</a>:</div><div class="line"><a name="l00506"></a><span class="lineno"> 506</span>  {</div><div class="line"><a name="l00507"></a><span class="lineno"> 507</span>  <span class="comment">// It doesn't make sense to check [-inf, inf], so hard code it to a big number</span></div><div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  std::uniform_real_distribution<double> distribution_f64(-1000.f, 1000.f);</div><div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_f64, seed_offset);</div><div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  <span class="keywordflow">break</span>;</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">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6abd7ef6d4f35bc7d05c559b65032f15d1">DataType::SIZET</a>:</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>  std::uniform_int_distribution<size_t> distribution_sizet(std::numeric_limits<size_t>::lowest(), <a class="code" href="namespacearm__compute_1_1test_1_1fixed__point__arithmetic_1_1detail.xhtml#ad91bb73431b4de1f4946ed949d444849">std::numeric_limits<size_t>::max</a>());</div><div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_sizet, seed_offset);</div><div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  <span class="keywordflow">break</span>;</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">default</span>:</div><div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"NOT SUPPORTED!"</span>);</div><div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  }</div><div class="line"><a name="l00521"></a><span class="lineno"> 521</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_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543">arm_compute::DataType::QS8</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::Format::U8</a></div><div class="ttdoc">Unknown image format. </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F16 per channel </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::Format::U16</a></div><div class="ttdoc">1 channel, 1 S16 per channel </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 U32 per channel </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::Format::S32</a></div><div class="ttdoc">1 channel, 1 U16 per channel </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc">arm_compute::DataType::S64</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6abd7ef6d4f35bc7d05c559b65032f15d1"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6abd7ef6d4f35bc7d05c559b65032f15d1">arm_compute::DataType::SIZET</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::Format::U32</a></div><div class="ttdoc">1 channel, 1 S32 per channel </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::Format::S16</a></div><div class="ttdoc">1 channel, 1 U8 per channel </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_ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e">arm_compute::DataType::F64</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa">arm_compute::DataType::U64</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">arm_compute::DataType::S8</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_tensor_library_xhtml_a80a7b5ae084bf22b91bc5f68a06711c0"><div class="ttname"><a href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">arm_compute::test::TensorLibrary::fill</a></div><div class="ttdeci">void fill(T &&tensor, D &&distribution, std::random_device::result_type seed_offset) const </div><div class="ttdoc">Fills the specified tensor with random values drawn from distribution. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_library_8h_source.xhtml#l00368">TensorLibrary.h:368</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a150d2023c197e197f09f350ede795085"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">void fill_tensor_uniform </td> |
| <td>(</td> |
| <td class="paramtype">T && </td> |
| <td class="paramname"><em>tensor</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">std::random_device::result_type </td> |
| <td class="paramname"><em>seed_offset</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">D </td> |
| <td class="paramname"><em>low</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">D </td> |
| <td class="paramname"><em>high</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Fill a tensor with uniform distribution across the a specified range. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in,out]</td><td class="paramname">tensor</td><td>To be filled tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">seed_offset</td><td>The offset will be added to the global seed before initialising the random generator. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">low</td><td>lowest value in the range (inclusive) </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">high</td><td>highest value in the range (inclusive)</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section note"><dt>Note</dt><dd><code>low</code> and <code>high</code> must be of the same type as the data type of <code>tensor</code> </dd></dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8h_source.xhtml#l00524">524</a> of file <a class="el" href="_tensor_library_8h_source.xhtml">TensorLibrary.h</a>.</p> |
| |
| <p>References <a class="el" href="_error_8h_source.xhtml#l00031">ARM_COMPUTE_ERROR</a>, <a class="el" href="_error_8h_source.xhtml#l00124">ARM_COMPUTE_ERROR_ON</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::F16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::F32</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e">arm_compute::F64</a>, <a class="el" href="_tensor_library_8h_source.xhtml#l00368">TensorLibrary::fill()</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543">arm_compute::QS8</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::S16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::S32</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc">arm_compute::S64</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">arm_compute::S8</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6abd7ef6d4f35bc7d05c559b65032f15d1">arm_compute::SIZET</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::U16</a>, <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::U32</a>, <a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa">arm_compute::U64</a>, and <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::U8</a>.</p> |
| <div class="fragment"><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="keywordflow">switch</span>(tensor.data_type())</div><div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  {</div><div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>:</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>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!(std::is_same<uint8_t, D>::value));</div><div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  std::uniform_int_distribution<uint8_t> distribution_u8(low, high);</div><div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_u8, seed_offset);</div><div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  }</div><div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">DataType::S8</a>:</div><div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543">DataType::QS8</a>:</div><div class="line"><a name="l00537"></a><span class="lineno"> 537</span>  {</div><div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!(std::is_same<int8_t, D>::value));</div><div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  std::uniform_int_distribution<int8_t> distribution_s8(low, high);</div><div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_s8, seed_offset);</div><div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  }</div><div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">DataType::U16</a>:</div><div class="line"><a name="l00544"></a><span class="lineno"> 544</span>  {</div><div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!(std::is_same<uint16_t, D>::value));</div><div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  std::uniform_int_distribution<uint16_t> distribution_u16(low, high);</div><div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_u16, seed_offset);</div><div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  }</div><div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">DataType::S16</a>:</div><div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  {</div><div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!(std::is_same<int16_t, D>::value));</div><div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  std::uniform_int_distribution<int16_t> distribution_s16(low, high);</div><div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_s16, seed_offset);</div><div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  }</div><div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>:</div><div class="line"><a name="l00558"></a><span class="lineno"> 558</span>  {</div><div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!(std::is_same<uint32_t, D>::value));</div><div class="line"><a name="l00560"></a><span class="lineno"> 560</span>  std::uniform_int_distribution<uint32_t> distribution_u32(low, high);</div><div class="line"><a name="l00561"></a><span class="lineno"> 561</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_u32, seed_offset);</div><div class="line"><a name="l00562"></a><span class="lineno"> 562</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00563"></a><span class="lineno"> 563</span>  }</div><div class="line"><a name="l00564"></a><span class="lineno"> 564</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>:</div><div class="line"><a name="l00565"></a><span class="lineno"> 565</span>  {</div><div class="line"><a name="l00566"></a><span class="lineno"> 566</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!(std::is_same<int32_t, D>::value));</div><div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  std::uniform_int_distribution<int32_t> distribution_s32(low, high);</div><div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_s32, seed_offset);</div><div class="line"><a name="l00569"></a><span class="lineno"> 569</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  }</div><div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa">DataType::U64</a>:</div><div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  {</div><div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!(std::is_same<uint64_t, D>::value));</div><div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  std::uniform_int_distribution<uint64_t> distribution_u64(low, high);</div><div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_u64, seed_offset);</div><div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  }</div><div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc">DataType::S64</a>:</div><div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  {</div><div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!(std::is_same<int64_t, D>::value));</div><div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  std::uniform_int_distribution<int64_t> distribution_s64(low, high);</div><div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_s64, seed_offset);</div><div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  <span class="keywordflow">break</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="preprocessor">#if ENABLE_FP16</span></div><div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>:</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>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!(std::is_same<float16_t, D>::value));</div><div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  std::uniform_real_distribution<float16_t> distribution_f16(low, high);</div><div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_f16, seed_offset);</div><div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  <span class="keywordflow">break</span>;</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="preprocessor">#endif</span></div><div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>:</div><div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  {</div><div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!(std::is_same<float, D>::value));</div><div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  std::uniform_real_distribution<float> distribution_f32(low, high);</div><div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_f32, seed_offset);</div><div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  }</div><div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e">DataType::F64</a>:</div><div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  {</div><div class="line"><a name="l00603"></a><span class="lineno"> 603</span>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!(std::is_same<double, D>::value));</div><div class="line"><a name="l00604"></a><span class="lineno"> 604</span>  std::uniform_real_distribution<double> distribution_f64(low, high);</div><div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_f64, seed_offset);</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>  }</div><div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6abd7ef6d4f35bc7d05c559b65032f15d1">DataType::SIZET</a>:</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>  <a class="code" href="_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(!(std::is_same<size_t, D>::value));</div><div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  std::uniform_int_distribution<size_t> distribution_sizet(low, high);</div><div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <a class="code" href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">fill</a>(tensor, distribution_sizet, seed_offset);</div><div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  <span class="keywordflow">break</span>;</div><div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  }</div><div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  <span class="keywordflow">default</span>:</div><div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  <a class="code" href="_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">"NOT SUPPORTED!"</span>);</div><div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  }</div><div class="line"><a name="l00618"></a><span class="lineno"> 618</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_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543">arm_compute::DataType::QS8</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::Format::U8</a></div><div class="ttdoc">Unknown image format. </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F16 per channel </div></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="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::Format::U16</a></div><div class="ttdoc">1 channel, 1 S16 per channel </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 U32 per channel </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::Format::S32</a></div><div class="ttdoc">1 channel, 1 U16 per channel </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc">arm_compute::DataType::S64</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6abd7ef6d4f35bc7d05c559b65032f15d1"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6abd7ef6d4f35bc7d05c559b65032f15d1">arm_compute::DataType::SIZET</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::Format::U32</a></div><div class="ttdoc">1 channel, 1 S32 per channel </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::Format::S16</a></div><div class="ttdoc">1 channel, 1 U8 per channel </div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e">arm_compute::DataType::F64</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa">arm_compute::DataType::U64</a></div></div> |
| <div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">arm_compute::DataType::S8</a></div></div> |
| <div class="ttc" id="classarm__compute_1_1test_1_1_tensor_library_xhtml_a80a7b5ae084bf22b91bc5f68a06711c0"><div class="ttname"><a href="classarm__compute_1_1test_1_1_tensor_library.xhtml#a80a7b5ae084bf22b91bc5f68a06711c0">arm_compute::test::TensorLibrary::fill</a></div><div class="ttdeci">void fill(T &&tensor, D &&distribution, std::random_device::result_type seed_offset) const </div><div class="ttdoc">Fills the specified tensor with random values drawn from distribution. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_library_8h_source.xhtml#l00368">TensorLibrary.h:368</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a34e94c998e4527d9556ccc5da82765fd"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="mlabels"> |
| <tr> |
| <td class="mlabels-left"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> get </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> & </td> |
| <td class="paramname"><em>shape</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> </td> |
| <td class="paramname"><em>data_type</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">int </td> |
| <td class="paramname"><em>num_channels</em> = <code>1</code>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">int </td> |
| <td class="paramname"><em>fixed_point_position</em> = <code>0</code> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">static</span></span> </td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Creates an uninitialised raw tensor with the given <code>shape</code>, <code>data_type</code> and <code>num_channels</code>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">shape</td><td>Shape used to initialise the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">data_type</td><td>Data type used to initialise the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">num_channels</td><td>(Optional) Number of channels used to initialise the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">fixed_point_position</td><td>(Optional) Number of bits for the fractional part of the fixed point numbers </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00413">413</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00414"></a><span class="lineno"> 414</span> {</div><div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <span class="keywordflow">return</span> RawTensor(shape, data_type, num_channels, fixed_point_position);</div><div class="line"><a name="l00416"></a><span class="lineno"> 416</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a62ee584f91819c3ea097827f7630c1dd"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="mlabels"> |
| <tr> |
| <td class="mlabels-left"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> get </td> |
| <td>(</td> |
| <td class="paramtype">const <a class="el" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a> & </td> |
| <td class="paramname"><em>shape</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> </td> |
| <td class="paramname"><em>format</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </td> |
| <td class="mlabels-right"> |
| <span class="mlabels"><span class="mlabel">static</span></span> </td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Creates an uninitialised raw tensor with the given <code>shape</code> and <code>format</code>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">shape</td><td>Shape used to initialise the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">format</td><td>Format used to initialise the tensor. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00418">418</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00419"></a><span class="lineno"> 419</span> {</div><div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <span class="keywordflow">return</span> RawTensor(shape, format);</div><div class="line"><a name="l00421"></a><span class="lineno"> 421</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a024fbe836c85d10afefc81cd2e51658e"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">const <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> & get </td> |
| <td>(</td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em></td><td>)</td> |
| <td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Provides a contant raw tensor for the specified image. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to look up the raw tensor. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00423">423</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| |
| <p>References <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0">arm_compute::RGB888</a>.</p> |
| <div class="fragment"><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>  <span class="keywordflow">return</span> find_or_create_raw_tensor(name, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0">Format::RGB888</a>);</div><div class="line"><a name="l00426"></a><span class="lineno"> 426</span> }</div><div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0">arm_compute::Format::RGB888</a></div><div class="ttdoc">2 channel, 1 U8 per channel </div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="aa0cf1a79542c521b9f16d117b085c4d5"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> get </td> |
| <td>(</td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em></td><td>)</td> |
| <td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Provides a raw tensor for the specified image. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to look up the raw tensor. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00428">428</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| |
| <p>References <a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0">arm_compute::RGB888</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00429"></a><span class="lineno"> 429</span> {</div><div class="line"><a name="l00430"></a><span class="lineno"> 430</span>  <span class="keywordflow">return</span> RawTensor(find_or_create_raw_tensor(name, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0">Format::RGB888</a>));</div><div class="line"><a name="l00431"></a><span class="lineno"> 431</span> }</div><div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a30ff380a3be74628024063a99fba10f0">arm_compute::Format::RGB888</a></div><div class="ttdoc">2 channel, 1 U8 per channel </div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a3675bd0074fa527b42c6516a37f8f232"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> get </td> |
| <td>(</td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6">DataType</a> </td> |
| <td class="paramname"><em>data_type</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype">int </td> |
| <td class="paramname"><em>num_channels</em> = <code>1</code> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Creates an uninitialised raw tensor with the given <code>data_type</code> and <code>num_channels</code>. </p> |
| <p>The shape is derived from the specified image.</p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to initialise the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">data_type</td><td>Data type used to initialise the tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">num_channels</td><td>Number of channels used to initialise the tensor. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00433">433</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| |
| <p>References <a class="el" href="_raw_tensor_8cpp_source.xhtml#l00086">RawTensor::shape()</a>.</p> |
| <div class="fragment"><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="keyword">const</span> RawTensor &raw = <span class="keyword">get</span>(name);</div><div class="line"><a name="l00436"></a><span class="lineno"> 436</span> </div><div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <span class="keywordflow">return</span> RawTensor(raw.shape(), data_type, num_channels);</div><div class="line"><a name="l00438"></a><span class="lineno"> 438</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a0e77935822447adc6cdce586f276f97d"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">const <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> & get </td> |
| <td>(</td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> </td> |
| <td class="paramname"><em>format</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Provides a contant raw tensor for the specified image after it has been converted to <code>format</code>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to look up the raw tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">format</td><td>Format used to look up the raw tensor. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00440">440</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00441"></a><span class="lineno"> 441</span> {</div><div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <span class="keywordflow">return</span> find_or_create_raw_tensor(name, format);</div><div class="line"><a name="l00443"></a><span class="lineno"> 443</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="ab760ccaa18b95b99c73eb0e763f39ec2"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> get </td> |
| <td>(</td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> </td> |
| <td class="paramname"><em>format</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Provides a raw tensor for the specified image after it has been converted to <code>format</code>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to look up the raw tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">format</td><td>Format used to look up the raw tensor. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00445">445</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| <div class="fragment"><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>  <span class="keywordflow">return</span> RawTensor(find_or_create_raw_tensor(name, format));</div><div class="line"><a name="l00448"></a><span class="lineno"> 448</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a11f5f1baaad31d1067564eccf599e90c"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">const <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> & get </td> |
| <td>(</td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> </td> |
| <td class="paramname"><em>channel</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Provides a contant raw tensor for the specified channel after it has been extracted form the given image. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to look up the raw tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">channel</td><td>Channel used to look up the raw tensor.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section note"><dt>Note</dt><dd>The channel has to be unambiguous so that the format can be inferred automatically. </dd></dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00450">450</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| |
| <p>References <a class="el" href="tests_2_utils_8h_source.xhtml#l00381">arm_compute::test::get_format_for_channel()</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">return</span> <span class="keyword">get</span>(name, <a class="code" href="namespacearm__compute_1_1test.xhtml#aa337ab76176f3c4193642ac6de3a61cf">get_format_for_channel</a>(channel), channel);</div><div class="line"><a name="l00453"></a><span class="lineno"> 453</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_xhtml_aa337ab76176f3c4193642ac6de3a61cf"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#aa337ab76176f3c4193642ac6de3a61cf">arm_compute::test::get_format_for_channel</a></div><div class="ttdeci">Format get_format_for_channel(Channel channel)</div><div class="ttdoc">Look up the format corresponding to a channel. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00381">Utils.h:381</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="af6f0ca724e534653925306023dbb88e7"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> get </td> |
| <td>(</td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> </td> |
| <td class="paramname"><em>channel</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Provides a raw tensor for the specified channel after it has been extracted form the given image. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to look up the raw tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">channel</td><td>Channel used to look up the raw tensor.</td></tr> |
| </table> |
| </dd> |
| </dl> |
| <dl class="section note"><dt>Note</dt><dd>The channel has to be unambiguous so that the format can be inferred automatically. </dd></dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00455">455</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| |
| <p>References <a class="el" href="tests_2_utils_8h_source.xhtml#l00381">arm_compute::test::get_format_for_channel()</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00456"></a><span class="lineno"> 456</span> {</div><div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="keywordflow">return</span> RawTensor(<span class="keyword">get</span>(name, <a class="code" href="namespacearm__compute_1_1test.xhtml#aa337ab76176f3c4193642ac6de3a61cf">get_format_for_channel</a>(channel), channel));</div><div class="line"><a name="l00458"></a><span class="lineno"> 458</span> }</div><div class="ttc" id="namespacearm__compute_1_1test_xhtml_aa337ab76176f3c4193642ac6de3a61cf"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#aa337ab76176f3c4193642ac6de3a61cf">arm_compute::test::get_format_for_channel</a></div><div class="ttdeci">Format get_format_for_channel(Channel channel)</div><div class="ttdoc">Look up the format corresponding to a channel. </div><div class="ttdef"><b>Definition:</b> <a href="tests_2_utils_8h_source.xhtml#l00381">Utils.h:381</a></div></div> |
| </div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a8c511f7046a704b8352ea8a8bbf456fa"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">const <a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> & get </td> |
| <td>(</td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> </td> |
| <td class="paramname"><em>format</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> </td> |
| <td class="paramname"><em>channel</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Provides a constant raw tensor for the specified channel after it has been extracted form the given image formatted to <code>format</code>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to look up the raw tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">format</td><td>Format used to look up the raw tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">channel</td><td>Channel used to look up the raw tensor. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00460">460</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00461"></a><span class="lineno"> 461</span> {</div><div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  <span class="keywordflow">return</span> find_or_create_raw_tensor(name, format, channel);</div><div class="line"><a name="l00463"></a><span class="lineno"> 463</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="ad6182f07b3eda32931598aa4f2bfc11a"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname"><a class="el" href="classarm__compute_1_1test_1_1_raw_tensor.xhtml">RawTensor</a> get </td> |
| <td>(</td> |
| <td class="paramtype">const std::string & </td> |
| <td class="paramname"><em>name</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58">Format</a> </td> |
| <td class="paramname"><em>format</em>, </td> |
| </tr> |
| <tr> |
| <td class="paramkey"></td> |
| <td></td> |
| <td class="paramtype"><a class="el" href="namespacearm__compute.xhtml#a1ce9b523fd4f3b5bbcadcd796183455a">Channel</a> </td> |
| <td class="paramname"><em>channel</em> </td> |
| </tr> |
| <tr> |
| <td></td> |
| <td>)</td> |
| <td></td><td></td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Provides a raw tensor for the specified channel after it has been extracted form the given image formatted to <code>format</code>. </p> |
| <dl class="params"><dt>Parameters</dt><dd> |
| <table class="params"> |
| <tr><td class="paramdir">[in]</td><td class="paramname">name</td><td><a class="el" href="struct_image.xhtml" title="Structure to hold Image information. ">Image</a> file used to look up the raw tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">format</td><td>Format used to look up the raw tensor. </td></tr> |
| <tr><td class="paramdir">[in]</td><td class="paramname">channel</td><td>Channel used to look up the raw tensor. </td></tr> |
| </table> |
| </dd> |
| </dl> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00465">465</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00466"></a><span class="lineno"> 466</span> {</div><div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <span class="keywordflow">return</span> RawTensor(find_or_create_raw_tensor(name, format, channel));</div><div class="line"><a name="l00468"></a><span class="lineno"> 468</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <a class="anchor" id="a4035a1140831801ced5dfa1d9fe6988a"></a> |
| <div class="memitem"> |
| <div class="memproto"> |
| <table class="memname"> |
| <tr> |
| <td class="memname">std::random_device::result_type seed </td> |
| <td>(</td> |
| <td class="paramname"></td><td>)</td> |
| <td> const</td> |
| </tr> |
| </table> |
| </div><div class="memdoc"> |
| |
| <p>Seed that is used to fill tensors with random values. </p> |
| |
| <p>Definition at line <a class="el" href="_tensor_library_8cpp_source.xhtml#l00218">218</a> of file <a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a>.</p> |
| <div class="fragment"><div class="line"><a name="l00219"></a><span class="lineno"> 219</span> {</div><div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <span class="keywordflow">return</span> _seed;</div><div class="line"><a name="l00221"></a><span class="lineno"> 221</span> }</div></div><!-- fragment --> |
| </div> |
| </div> |
| <hr/>The documentation for this class was generated from the following files:<ul> |
| <li>tests/<a class="el" href="_tensor_library_8h_source.xhtml">TensorLibrary.h</a></li> |
| <li>tests/<a class="el" href="_tensor_library_8cpp_source.xhtml">TensorLibrary.cpp</a></li> |
| </ul> |
| </div><!-- contents --> |
| </div><!-- doc-content --> |
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| <li class="navelem"><a class="el" href="namespacearm__compute.xhtml">arm_compute</a></li><li class="navelem"><a class="el" href="namespacearm__compute_1_1test.xhtml">test</a></li><li class="navelem"><a class="el" href="classarm__compute_1_1test_1_1_tensor_library.xhtml">TensorLibrary</a></li> |
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