Richard Burton | dc0c6ed | 2020-04-08 16:39:05 +0100 | [diff] [blame] | 1 | # Copyright © 2020 Arm Ltd. All rights reserved. |
| 2 | # SPDX-License-Identifier: MIT |
| 3 | import inspect |
| 4 | |
| 5 | import pytest |
| 6 | |
| 7 | import pyarmnn as ann |
| 8 | import numpy as np |
| 9 | import pyarmnn._generated.pyarmnn as generated |
| 10 | |
| 11 | |
| 12 | def test_activation_descriptor_default_values(): |
| 13 | desc = ann.ActivationDescriptor() |
| 14 | assert desc.m_Function == ann.ActivationFunction_Sigmoid |
| 15 | assert desc.m_A == 0 |
| 16 | assert desc.m_B == 0 |
| 17 | |
| 18 | |
| 19 | def test_argminmax_descriptor_default_values(): |
| 20 | desc = ann.ArgMinMaxDescriptor() |
| 21 | assert desc.m_Function == ann.ArgMinMaxFunction_Min |
| 22 | assert desc.m_Axis == -1 |
| 23 | |
| 24 | |
| 25 | def test_batchnormalization_descriptor_default_values(): |
| 26 | desc = ann.BatchNormalizationDescriptor() |
| 27 | assert desc.m_DataLayout == ann.DataLayout_NCHW |
| 28 | np.allclose(0.0001, desc.m_Eps) |
| 29 | |
| 30 | |
| 31 | def test_batchtospacend_descriptor_default_values(): |
| 32 | desc = ann.BatchToSpaceNdDescriptor() |
| 33 | assert desc.m_DataLayout == ann.DataLayout_NCHW |
| 34 | assert [1, 1] == desc.m_BlockShape |
| 35 | assert [(0, 0), (0, 0)] == desc.m_Crops |
| 36 | |
| 37 | |
| 38 | def test_batchtospacend_descriptor_assignment(): |
| 39 | desc = ann.BatchToSpaceNdDescriptor() |
| 40 | desc.m_BlockShape = (1, 2, 3) |
| 41 | |
| 42 | ololo = [(1, 2), (3, 4)] |
| 43 | size_1 = len(ololo) |
| 44 | desc.m_Crops = ololo |
| 45 | |
| 46 | assert size_1 == len(ololo) |
| 47 | desc.m_DataLayout = ann.DataLayout_NHWC |
| 48 | assert ann.DataLayout_NHWC == desc.m_DataLayout |
| 49 | assert [1, 2, 3] == desc.m_BlockShape |
| 50 | assert [(1, 2), (3, 4)] == desc.m_Crops |
| 51 | |
| 52 | |
| 53 | @pytest.mark.parametrize("input_shape, value, vtype", [([-1], -1, 'int'), (("one", "two"), "'one'", 'str'), |
| 54 | ([1.33, 4.55], 1.33, 'float'), |
| 55 | ([{1: "one"}], "{1: 'one'}", 'dict')], ids=lambda x: str(x)) |
| 56 | def test_batchtospacend_descriptor_rubbish_assignment_shape(input_shape, value, vtype): |
| 57 | desc = ann.BatchToSpaceNdDescriptor() |
| 58 | with pytest.raises(TypeError) as err: |
| 59 | desc.m_BlockShape = input_shape |
| 60 | |
| 61 | assert "Failed to convert python input value {} of type '{}' to C type 'j'".format(value, vtype) in str(err.value) |
| 62 | |
| 63 | |
| 64 | @pytest.mark.parametrize("input_crops, value, vtype", [([(1, 2), (3, 4, 5)], '(3, 4, 5)', 'tuple'), |
| 65 | ([(1, 'one')], "(1, 'one')", 'tuple'), |
| 66 | ([-1], -1, 'int'), |
| 67 | ([(1, (1, 2))], '(1, (1, 2))', 'tuple'), |
| 68 | ([[1, [1, 2]]], '[1, [1, 2]]', 'list') |
| 69 | ], ids=lambda x: str(x)) |
| 70 | def test_batchtospacend_descriptor_rubbish_assignment_crops(input_crops, value, vtype): |
| 71 | desc = ann.BatchToSpaceNdDescriptor() |
| 72 | with pytest.raises(TypeError) as err: |
| 73 | desc.m_Crops = input_crops |
| 74 | |
| 75 | assert "Failed to convert python input value {} of type '{}' to C type".format(value, vtype) in str(err.value) |
| 76 | |
| 77 | |
| 78 | def test_batchtospacend_descriptor_empty_assignment(): |
| 79 | desc = ann.BatchToSpaceNdDescriptor() |
| 80 | desc.m_BlockShape = [] |
| 81 | assert [] == desc.m_BlockShape |
| 82 | |
| 83 | |
| 84 | def test_batchtospacend_descriptor_ctor(): |
| 85 | desc = ann.BatchToSpaceNdDescriptor([1, 2, 3], [(4, 5), (6, 7)]) |
| 86 | assert desc.m_DataLayout == ann.DataLayout_NCHW |
| 87 | assert [1, 2, 3] == desc.m_BlockShape |
| 88 | assert [(4, 5), (6, 7)] == desc.m_Crops |
| 89 | |
| 90 | |
| 91 | def test_convolution2d_descriptor_default_values(): |
| 92 | desc = ann.Convolution2dDescriptor() |
| 93 | assert desc.m_PadLeft == 0 |
| 94 | assert desc.m_PadTop == 0 |
| 95 | assert desc.m_PadRight == 0 |
| 96 | assert desc.m_PadBottom == 0 |
| 97 | assert desc.m_StrideX == 0 |
| 98 | assert desc.m_StrideY == 0 |
| 99 | assert desc.m_DilationX == 1 |
| 100 | assert desc.m_DilationY == 1 |
| 101 | assert desc.m_BiasEnabled == False |
| 102 | assert desc.m_DataLayout == ann.DataLayout_NCHW |
| 103 | |
| 104 | |
| 105 | def test_depthtospace_descriptor_default_values(): |
| 106 | desc = ann.DepthToSpaceDescriptor() |
| 107 | assert desc.m_BlockSize == 1 |
| 108 | assert desc.m_DataLayout == ann.DataLayout_NHWC |
| 109 | |
| 110 | |
| 111 | def test_depthwise_convolution2d_descriptor_default_values(): |
| 112 | desc = ann.DepthwiseConvolution2dDescriptor() |
| 113 | assert desc.m_PadLeft == 0 |
| 114 | assert desc.m_PadTop == 0 |
| 115 | assert desc.m_PadRight == 0 |
| 116 | assert desc.m_PadBottom == 0 |
| 117 | assert desc.m_StrideX == 0 |
| 118 | assert desc.m_StrideY == 0 |
| 119 | assert desc.m_DilationX == 1 |
| 120 | assert desc.m_DilationY == 1 |
| 121 | assert desc.m_BiasEnabled == False |
| 122 | assert desc.m_DataLayout == ann.DataLayout_NCHW |
| 123 | |
| 124 | |
| 125 | def test_detectionpostprocess_descriptor_default_values(): |
| 126 | desc = ann.DetectionPostProcessDescriptor() |
| 127 | assert desc.m_MaxDetections == 0 |
| 128 | assert desc.m_MaxClassesPerDetection == 1 |
| 129 | assert desc.m_DetectionsPerClass == 1 |
| 130 | assert desc.m_NmsScoreThreshold == 0 |
| 131 | assert desc.m_NmsIouThreshold == 0 |
| 132 | assert desc.m_NumClasses == 0 |
| 133 | assert desc.m_UseRegularNms == False |
| 134 | assert desc.m_ScaleH == 0 |
| 135 | assert desc.m_ScaleW == 0 |
| 136 | assert desc.m_ScaleX == 0 |
| 137 | assert desc.m_ScaleY == 0 |
| 138 | |
| 139 | |
| 140 | def test_fakequantization_descriptor_default_values(): |
| 141 | desc = ann.FakeQuantizationDescriptor() |
| 142 | np.allclose(6, desc.m_Max) |
| 143 | np.allclose(-6, desc.m_Min) |
| 144 | |
| 145 | |
| 146 | def test_fully_connected_descriptor_default_values(): |
| 147 | desc = ann.FullyConnectedDescriptor() |
| 148 | assert desc.m_BiasEnabled == False |
| 149 | assert desc.m_TransposeWeightMatrix == False |
| 150 | |
| 151 | |
| 152 | def test_instancenormalization_descriptor_default_values(): |
| 153 | desc = ann.InstanceNormalizationDescriptor() |
| 154 | assert desc.m_Gamma == 1 |
| 155 | assert desc.m_Beta == 0 |
| 156 | assert desc.m_DataLayout == ann.DataLayout_NCHW |
| 157 | np.allclose(1e-12, desc.m_Eps) |
| 158 | |
| 159 | |
| 160 | def test_lstm_descriptor_default_values(): |
| 161 | desc = ann.LstmDescriptor() |
| 162 | assert desc.m_ActivationFunc == 1 |
| 163 | assert desc.m_ClippingThresCell == 0 |
| 164 | assert desc.m_ClippingThresProj == 0 |
| 165 | assert desc.m_CifgEnabled == True |
| 166 | assert desc.m_PeepholeEnabled == False |
| 167 | assert desc.m_ProjectionEnabled == False |
| 168 | assert desc.m_LayerNormEnabled == False |
| 169 | |
| 170 | |
| 171 | def test_l2normalization_descriptor_default_values(): |
| 172 | desc = ann.L2NormalizationDescriptor() |
| 173 | assert desc.m_DataLayout == ann.DataLayout_NCHW |
| 174 | np.allclose(1e-12, desc.m_Eps) |
| 175 | |
| 176 | |
| 177 | def test_mean_descriptor_default_values(): |
| 178 | desc = ann.MeanDescriptor() |
| 179 | assert desc.m_KeepDims == False |
| 180 | |
| 181 | |
| 182 | def test_normalization_descriptor_default_values(): |
| 183 | desc = ann.NormalizationDescriptor() |
| 184 | assert desc.m_NormChannelType == ann.NormalizationAlgorithmChannel_Across |
| 185 | assert desc.m_NormMethodType == ann.NormalizationAlgorithmMethod_LocalBrightness |
| 186 | assert desc.m_NormSize == 0 |
| 187 | assert desc.m_Alpha == 0 |
| 188 | assert desc.m_Beta == 0 |
| 189 | assert desc.m_K == 0 |
| 190 | assert desc.m_DataLayout == ann.DataLayout_NCHW |
| 191 | |
| 192 | |
| 193 | def test_origin_descriptor_default_values(): |
| 194 | desc = ann.ConcatDescriptor() |
| 195 | assert 0 == desc.GetNumViews() |
| 196 | assert 0 == desc.GetNumDimensions() |
| 197 | assert 1 == desc.GetConcatAxis() |
| 198 | |
| 199 | |
| 200 | def test_origin_descriptor_incorrect_views(): |
| 201 | desc = ann.ConcatDescriptor(2, 2) |
| 202 | with pytest.raises(RuntimeError) as err: |
| 203 | desc.SetViewOriginCoord(1000, 100, 1000) |
| 204 | assert "Failed to set view origin coordinates." in str(err.value) |
| 205 | |
| 206 | |
| 207 | def test_origin_descriptor_ctor(): |
| 208 | desc = ann.ConcatDescriptor(2, 2) |
| 209 | value = 5 |
| 210 | for i in range(desc.GetNumViews()): |
| 211 | for j in range(desc.GetNumDimensions()): |
| 212 | desc.SetViewOriginCoord(i, j, value+i) |
| 213 | desc.SetConcatAxis(1) |
| 214 | |
| 215 | assert 2 == desc.GetNumViews() |
| 216 | assert 2 == desc.GetNumDimensions() |
| 217 | assert [5, 5] == desc.GetViewOrigin(0) |
| 218 | assert [6, 6] == desc.GetViewOrigin(1) |
| 219 | assert 1 == desc.GetConcatAxis() |
| 220 | |
| 221 | |
| 222 | def test_pad_descriptor_default_values(): |
| 223 | desc = ann.PadDescriptor() |
| 224 | assert desc.m_PadValue == 0 |
| 225 | |
| 226 | |
| 227 | def test_permute_descriptor_default_values(): |
| 228 | pv = ann.PermutationVector((0, 2, 3, 1)) |
| 229 | desc = ann.PermuteDescriptor(pv) |
| 230 | assert desc.m_DimMappings.GetSize() == 4 |
| 231 | assert desc.m_DimMappings[0] == 0 |
| 232 | assert desc.m_DimMappings[1] == 2 |
| 233 | assert desc.m_DimMappings[2] == 3 |
| 234 | assert desc.m_DimMappings[3] == 1 |
| 235 | |
| 236 | |
| 237 | def test_pooling_descriptor_default_values(): |
| 238 | desc = ann.Pooling2dDescriptor() |
| 239 | assert desc.m_PoolType == ann.PoolingAlgorithm_Max |
| 240 | assert desc.m_PadLeft == 0 |
| 241 | assert desc.m_PadTop == 0 |
| 242 | assert desc.m_PadRight == 0 |
| 243 | assert desc.m_PadBottom == 0 |
| 244 | assert desc.m_PoolHeight == 0 |
| 245 | assert desc.m_PoolWidth == 0 |
| 246 | assert desc.m_StrideX == 0 |
| 247 | assert desc.m_StrideY == 0 |
| 248 | assert desc.m_OutputShapeRounding == ann.OutputShapeRounding_Floor |
| 249 | assert desc.m_PaddingMethod == ann.PaddingMethod_Exclude |
| 250 | assert desc.m_DataLayout == ann.DataLayout_NCHW |
| 251 | |
| 252 | |
| 253 | def test_reshape_descriptor_default_values(): |
| 254 | desc = ann.ReshapeDescriptor() |
| 255 | # check the empty Targetshape |
| 256 | assert desc.m_TargetShape.GetNumDimensions() == 0 |
| 257 | |
| 258 | |
| 259 | def test_slice_descriptor_default_values(): |
| 260 | desc = ann.SliceDescriptor() |
| 261 | assert desc.m_TargetWidth == 0 |
| 262 | assert desc.m_TargetHeight == 0 |
| 263 | assert desc.m_Method == ann.ResizeMethod_NearestNeighbor |
| 264 | assert desc.m_DataLayout == ann.DataLayout_NCHW |
| 265 | |
| 266 | |
| 267 | def test_resize_descriptor_default_values(): |
| 268 | desc = ann.ResizeDescriptor() |
| 269 | assert desc.m_TargetWidth == 0 |
| 270 | assert desc.m_TargetHeight == 0 |
| 271 | assert desc.m_Method == ann.ResizeMethod_NearestNeighbor |
| 272 | assert desc.m_DataLayout == ann.DataLayout_NCHW |
| 273 | assert desc.m_BilinearAlignCorners == False |
| 274 | |
| 275 | |
| 276 | def test_spacetobatchnd_descriptor_default_values(): |
| 277 | desc = ann.SpaceToBatchNdDescriptor() |
| 278 | assert desc.m_DataLayout == ann.DataLayout_NCHW |
| 279 | |
| 280 | |
| 281 | def test_spacetodepth_descriptor_default_values(): |
| 282 | desc = ann.SpaceToDepthDescriptor() |
| 283 | assert desc.m_BlockSize == 1 |
| 284 | assert desc.m_DataLayout == ann.DataLayout_NHWC |
| 285 | |
| 286 | |
| 287 | def test_stack_descriptor_default_values(): |
| 288 | desc = ann.StackDescriptor() |
| 289 | assert desc.m_Axis == 0 |
| 290 | assert desc.m_NumInputs == 0 |
| 291 | # check the empty Inputshape |
| 292 | assert desc.m_InputShape.GetNumDimensions() == 0 |
| 293 | |
| 294 | |
| 295 | def test_slice_descriptor_default_values(): |
| 296 | desc = ann.SliceDescriptor() |
| 297 | desc.m_Begin = [1, 2, 3, 4, 5] |
| 298 | desc.m_Size = (1, 2, 3, 4) |
| 299 | |
| 300 | assert [1, 2, 3, 4, 5] == desc.m_Begin |
| 301 | assert [1, 2, 3, 4] == desc.m_Size |
| 302 | |
| 303 | |
| 304 | def test_slice_descriptor_ctor(): |
| 305 | desc = ann.SliceDescriptor([1, 2, 3, 4, 5], (1, 2, 3, 4)) |
| 306 | |
| 307 | assert [1, 2, 3, 4, 5] == desc.m_Begin |
| 308 | assert [1, 2, 3, 4] == desc.m_Size |
| 309 | |
| 310 | |
| 311 | def test_strided_slice_descriptor_default_values(): |
| 312 | desc = ann.StridedSliceDescriptor() |
| 313 | desc.m_Begin = [1, 2, 3, 4, 5] |
| 314 | desc.m_End = [6, 7, 8, 9, 10] |
| 315 | desc.m_Stride = (10, 10) |
| 316 | desc.m_BeginMask = 1 |
| 317 | desc.m_EndMask = 2 |
| 318 | desc.m_ShrinkAxisMask = 3 |
| 319 | desc.m_EllipsisMask = 4 |
| 320 | desc.m_NewAxisMask = 5 |
| 321 | |
| 322 | assert [1, 2, 3, 4, 5] == desc.m_Begin |
| 323 | assert [6, 7, 8, 9, 10] == desc.m_End |
| 324 | assert [10, 10] == desc.m_Stride |
| 325 | assert 1 == desc.m_BeginMask |
| 326 | assert 2 == desc.m_EndMask |
| 327 | assert 3 == desc.m_ShrinkAxisMask |
| 328 | assert 4 == desc.m_EllipsisMask |
| 329 | assert 5 == desc.m_NewAxisMask |
| 330 | |
| 331 | |
| 332 | def test_strided_slice_descriptor_ctor(): |
| 333 | desc = ann.StridedSliceDescriptor([1, 2, 3, 4, 5], [6, 7, 8, 9, 10], (10, 10)) |
| 334 | desc.m_Begin = [1, 2, 3, 4, 5] |
| 335 | desc.m_End = [6, 7, 8, 9, 10] |
| 336 | desc.m_Stride = (10, 10) |
| 337 | |
| 338 | assert [1, 2, 3, 4, 5] == desc.m_Begin |
| 339 | assert [6, 7, 8, 9, 10] == desc.m_End |
| 340 | assert [10, 10] == desc.m_Stride |
| 341 | |
| 342 | |
| 343 | def test_softmax_descriptor_default_values(): |
| 344 | desc = ann.SoftmaxDescriptor() |
| 345 | assert desc.m_Axis == -1 |
| 346 | np.allclose(1.0, desc.m_Beta) |
| 347 | |
| 348 | |
| 349 | def test_space_to_batch_nd_descriptor_default_values(): |
| 350 | desc = ann.SpaceToBatchNdDescriptor() |
| 351 | assert [1, 1] == desc.m_BlockShape |
| 352 | assert [(0, 0), (0, 0)] == desc.m_PadList |
| 353 | assert ann.DataLayout_NCHW == desc.m_DataLayout |
| 354 | |
| 355 | |
| 356 | def test_space_to_batch_nd_descriptor_assigned_values(): |
| 357 | desc = ann.SpaceToBatchNdDescriptor() |
| 358 | desc.m_BlockShape = (90, 100) |
| 359 | desc.m_PadList = [(1, 2), (3, 4)] |
| 360 | assert [90, 100] == desc.m_BlockShape |
| 361 | assert [(1, 2), (3, 4)] == desc.m_PadList |
| 362 | assert ann.DataLayout_NCHW == desc.m_DataLayout |
| 363 | |
| 364 | |
| 365 | def test_space_to_batch_nd_descriptor_ctor(): |
| 366 | desc = ann.SpaceToBatchNdDescriptor((1, 2, 3), [(1, 2), (3, 4)]) |
| 367 | assert [1, 2, 3] == desc.m_BlockShape |
| 368 | assert [(1, 2), (3, 4)] == desc.m_PadList |
| 369 | assert ann.DataLayout_NCHW == desc.m_DataLayout |
| 370 | |
| 371 | |
| 372 | def test_transpose_convolution2d_descriptor_default_values(): |
| 373 | desc = ann.DepthwiseConvolution2dDescriptor() |
| 374 | assert desc.m_PadLeft == 0 |
| 375 | assert desc.m_PadTop == 0 |
| 376 | assert desc.m_PadRight == 0 |
| 377 | assert desc.m_PadBottom == 0 |
| 378 | assert desc.m_StrideX == 0 |
| 379 | assert desc.m_StrideY == 0 |
| 380 | assert desc.m_BiasEnabled == False |
| 381 | assert desc.m_DataLayout == ann.DataLayout_NCHW |
| 382 | |
| 383 | |
| 384 | def test_view_descriptor_default_values(): |
| 385 | desc = ann.SplitterDescriptor() |
| 386 | assert 0 == desc.GetNumViews() |
| 387 | assert 0 == desc.GetNumDimensions() |
| 388 | |
| 389 | |
| 390 | def test_elementwise_unary_descriptor_default_values(): |
| 391 | desc = ann.ElementwiseUnaryDescriptor() |
| 392 | assert desc.m_Operation == ann.UnaryOperation_Abs |
| 393 | |
| 394 | |
| 395 | def test_view_descriptor_incorrect_input(): |
| 396 | desc = ann.SplitterDescriptor(2, 3) |
| 397 | with pytest.raises(RuntimeError) as err: |
| 398 | desc.SetViewOriginCoord(1000, 100, 1000) |
| 399 | assert "Failed to set view origin coordinates." in str(err.value) |
| 400 | |
| 401 | with pytest.raises(RuntimeError) as err: |
| 402 | desc.SetViewSize(1000, 100, 1000) |
| 403 | assert "Failed to set view size." in str(err.value) |
| 404 | |
| 405 | |
| 406 | def test_view_descriptor_ctor(): |
| 407 | desc = ann.SplitterDescriptor(2, 3) |
| 408 | value_size = 1 |
| 409 | value_orig_coord = 5 |
| 410 | for i in range(desc.GetNumViews()): |
| 411 | for j in range(desc.GetNumDimensions()): |
| 412 | desc.SetViewOriginCoord(i, j, value_orig_coord+i) |
| 413 | desc.SetViewSize(i, j, value_size+i) |
| 414 | |
| 415 | assert 2 == desc.GetNumViews() |
| 416 | assert 3 == desc.GetNumDimensions() |
| 417 | assert [5, 5] == desc.GetViewOrigin(0) |
| 418 | assert [6, 6] == desc.GetViewOrigin(1) |
| 419 | assert [1, 1] == desc.GetViewSizes(0) |
| 420 | assert [2, 2] == desc.GetViewSizes(1) |
| 421 | |
| 422 | |
| 423 | def test_createdescriptorforconcatenation_ctor(): |
| 424 | input_shape_vector = [ann.TensorShape((2, 1)), ann.TensorShape((3, 1)), ann.TensorShape((4, 1))] |
| 425 | desc = ann.CreateDescriptorForConcatenation(input_shape_vector, 0) |
| 426 | assert 3 == desc.GetNumViews() |
| 427 | assert 0 == desc.GetConcatAxis() |
| 428 | assert 2 == desc.GetNumDimensions() |
| 429 | c = desc.GetViewOrigin(1) |
| 430 | d = desc.GetViewOrigin(0) |
| 431 | |
| 432 | |
| 433 | def test_createdescriptorforconcatenation_wrong_shape_for_axis(): |
| 434 | input_shape_vector = [ann.TensorShape((1, 2)), ann.TensorShape((3, 4)), ann.TensorShape((5, 6))] |
| 435 | with pytest.raises(RuntimeError) as err: |
| 436 | desc = ann.CreateDescriptorForConcatenation(input_shape_vector, 0) |
| 437 | |
| 438 | assert "All inputs to concatenation must be the same size along all dimensions except the concatenation dimension" in str( |
| 439 | err.value) |
| 440 | |
| 441 | |
| 442 | @pytest.mark.parametrize("input_shape_vector", [([-1, "one"]), |
| 443 | ([1.33, 4.55]), |
| 444 | ([{1: "one"}])], ids=lambda x: str(x)) |
| 445 | def test_createdescriptorforconcatenation_rubbish_assignment_shape_vector(input_shape_vector): |
| 446 | with pytest.raises(TypeError) as err: |
| 447 | desc = ann.CreateDescriptorForConcatenation(input_shape_vector, 0) |
| 448 | |
| 449 | assert "in method 'CreateDescriptorForConcatenation', argument 1 of type 'std::vector< armnn::TensorShape,std::allocator< armnn::TensorShape > >'" in str( |
| 450 | err.value) |
| 451 | |
| 452 | |
| 453 | generated_classes = inspect.getmembers(generated, inspect.isclass) |
| 454 | generated_classes_names = list(map(lambda x: x[0], generated_classes)) |
| 455 | @pytest.mark.parametrize("desc_name", ['ActivationDescriptor', |
| 456 | 'ArgMinMaxDescriptor', |
| 457 | 'PermuteDescriptor', |
| 458 | 'SoftmaxDescriptor', |
| 459 | 'ConcatDescriptor', |
| 460 | 'SplitterDescriptor', |
| 461 | 'Pooling2dDescriptor', |
| 462 | 'FullyConnectedDescriptor', |
| 463 | 'Convolution2dDescriptor', |
| 464 | 'DepthwiseConvolution2dDescriptor', |
| 465 | 'DetectionPostProcessDescriptor', |
| 466 | 'NormalizationDescriptor', |
| 467 | 'L2NormalizationDescriptor', |
| 468 | 'BatchNormalizationDescriptor', |
| 469 | 'InstanceNormalizationDescriptor', |
| 470 | 'BatchToSpaceNdDescriptor', |
| 471 | 'FakeQuantizationDescriptor', |
| 472 | 'ResizeDescriptor', |
| 473 | 'ReshapeDescriptor', |
| 474 | 'SpaceToBatchNdDescriptor', |
| 475 | 'SpaceToDepthDescriptor', |
| 476 | 'LstmDescriptor', |
| 477 | 'MeanDescriptor', |
| 478 | 'PadDescriptor', |
| 479 | 'SliceDescriptor', |
| 480 | 'StackDescriptor', |
| 481 | 'StridedSliceDescriptor', |
| 482 | 'TransposeConvolution2dDescriptor', |
| 483 | 'ElementwiseUnaryDescriptor']) |
| 484 | class TestDescriptorMassChecks: |
| 485 | |
| 486 | def test_desc_implemented(self, desc_name): |
| 487 | assert desc_name in generated_classes_names |
| 488 | |
| 489 | def test_desc_equal(self, desc_name): |
| 490 | desc_class = next(filter(lambda x: x[0] == desc_name, generated_classes))[1] |
| 491 | |
| 492 | assert desc_class() == desc_class() |
| 493 | |
| 494 | |
| 495 | generated_classes = inspect.getmembers(generated, inspect.isclass) |
| 496 | generated_classes_names = list(map(lambda x: x[0], generated_classes)) |
| 497 | @pytest.mark.parametrize("desc_name", ['ActivationDescriptor', |
| 498 | 'ArgMinMaxDescriptor', |
| 499 | 'PermuteDescriptor', |
| 500 | 'SoftmaxDescriptor', |
| 501 | 'ConcatDescriptor', |
| 502 | 'SplitterDescriptor', |
| 503 | 'Pooling2dDescriptor', |
| 504 | 'FullyConnectedDescriptor', |
| 505 | 'Convolution2dDescriptor', |
| 506 | 'DepthwiseConvolution2dDescriptor', |
| 507 | 'DetectionPostProcessDescriptor', |
| 508 | 'NormalizationDescriptor', |
| 509 | 'L2NormalizationDescriptor', |
| 510 | 'BatchNormalizationDescriptor', |
| 511 | 'InstanceNormalizationDescriptor', |
| 512 | 'BatchToSpaceNdDescriptor', |
| 513 | 'FakeQuantizationDescriptor', |
| 514 | 'ResizeDescriptor', |
| 515 | 'ReshapeDescriptor', |
| 516 | 'SpaceToBatchNdDescriptor', |
| 517 | 'SpaceToDepthDescriptor', |
| 518 | 'LstmDescriptor', |
| 519 | 'MeanDescriptor', |
| 520 | 'PadDescriptor', |
| 521 | 'SliceDescriptor', |
| 522 | 'StackDescriptor', |
| 523 | 'StridedSliceDescriptor', |
| 524 | 'TransposeConvolution2dDescriptor', |
| 525 | 'ElementwiseUnaryDescriptor']) |
| 526 | class TestDescriptorMassChecks: |
| 527 | |
| 528 | def test_desc_implemented(self, desc_name): |
| 529 | assert desc_name in generated_classes_names |
| 530 | |
| 531 | def test_desc_equal(self, desc_name): |
| 532 | desc_class = next(filter(lambda x: x[0] == desc_name, generated_classes))[1] |
| 533 | |
| 534 | assert desc_class() == desc_class() |
| 535 | |