| # |
| # Copyright (C) 2018 The Android Open Source Project |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| # |
| |
| layout = BoolScalar("layout", False) # NHWC |
| |
| # TEST 1: SPACE_TO_BATCH_NCHW_1, block_size = [2, 2] |
| i1 = Input("op1", "TENSOR_FLOAT32", "{1, 2, 2, 2}") |
| pad1 = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [0, 0, 0, 0]) |
| o1 = Output("op4", "TENSOR_FLOAT32", "{4, 1, 1, 2}") |
| Model().Operation("SPACE_TO_BATCH_ND", i1, [2, 2], pad1, layout).To(o1) |
| |
| # Additional data type |
| quant8 = DataTypeConverter().Identify({ |
| i1: ("TENSOR_QUANT8_ASYMM", 0.1, 0), |
| o1: ("TENSOR_QUANT8_ASYMM", 0.1, 0) |
| }) |
| |
| # Instantiate an example |
| example = Example({ |
| i1: [1.4, 2.3, 3.2, 4.1, 5.4, 6.3, 7.2, 8.1], |
| o1: [1.4, 2.3, 3.2, 4.1, 5.4, 6.3, 7.2, 8.1] |
| }).AddNchw(i1, o1, layout).AddVariations("relaxed", "float16", quant8) |
| |
| |
| # TEST 2: SPACE_TO_BATCH_NCHW_2, block_size = [2, 2] |
| i2 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 4, 1}") |
| o2 = Output("op4", "TENSOR_FLOAT32", "{4, 2, 2, 1}") |
| Model().Operation("SPACE_TO_BATCH_ND", i2, [2, 2], pad1, layout).To(o2) |
| |
| # Additional data type |
| quant8 = DataTypeConverter().Identify({ |
| i2: ("TENSOR_QUANT8_ASYMM", 0.5, 0), |
| o2: ("TENSOR_QUANT8_ASYMM", 0.5, 0) |
| }) |
| |
| # Instantiate an example |
| example = Example({ |
| i2: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16], |
| o2: [1, 3, 9, 11, 2, 4, 10, 12, 5, 7, 13, 15, 6, 8, 14, 16] |
| }).AddNchw(i2, o2, layout).AddVariations("relaxed", "float16", quant8) |
| |
| |
| # TEST 3: SPACE_TO_BATCH_NCHW_3, block_size = [3, 2] |
| i3 = Input("op1", "TENSOR_FLOAT32", "{1, 5, 2, 1}") |
| pad3 = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 0, 2, 0]) |
| o3 = Output("op4", "TENSOR_FLOAT32", "{6, 2, 2, 1}") |
| Model().Operation("SPACE_TO_BATCH_ND", i3, [3, 2], pad3, layout).To(o3) |
| |
| # Additional data type |
| quant8 = DataTypeConverter().Identify({ |
| i3: ("TENSOR_QUANT8_ASYMM", 0.5, 0), |
| o3: ("TENSOR_QUANT8_ASYMM", 0.5, 0) |
| }) |
| |
| # Instantiate an example |
| example = Example({ |
| i3: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], |
| o3: [0, 0, 0, 5, 0, 0, 0, 6, 0, 1, 0, 7, |
| 0, 2, 0, 8, 0, 3, 0, 9, 0, 4, 0, 10] |
| }).AddNchw(i3, o3, layout).AddVariations("relaxed", "float16", quant8) |
| |
| |
| # TEST 4: SPACE_TO_BATCH_NCHW_4, block_size = [3, 2] |
| i4 = Input("op1", "TENSOR_FLOAT32", "{1, 4, 2, 1}") |
| pad4 = Parameter("paddings", "TENSOR_INT32", "{2, 2}", [1, 1, 2, 4]) |
| o4 = Output("op4", "TENSOR_FLOAT32", "{6, 2, 4, 1}") |
| Model().Operation("SPACE_TO_BATCH_ND", i4, [3, 2], pad4, layout).To(o4) |
| |
| # Additional data type |
| quant8 = DataTypeConverter().Identify({ |
| i4: ("TENSOR_QUANT8_ASYMM", 0.25, 0), |
| o4: ("TENSOR_QUANT8_ASYMM", 0.25, 0) |
| }) |
| |
| # Instantiate an example |
| example = Example({ |
| i4: [1, 2, 3, 4, 5, 6, 7, 8], |
| o4: [0, 0, 0, 0, 0, 5, 0, 0, 0, 0, 0, 0, 0, 6, 0, 0, |
| 0, 1, 0, 0, 0, 7, 0, 0, 0, 2, 0, 0, 0, 8, 0, 0, |
| 0, 3, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 0, 0] |
| }).AddNchw(i4, o4, layout).AddVariations("relaxed", "float16", quant8) |