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Diffstat (limited to 'python/pyarmnn/test/test_descriptors.py')
| -rw-r--r-- | python/pyarmnn/test/test_descriptors.py | 528 |
1 files changed, 528 insertions, 0 deletions
diff --git a/python/pyarmnn/test/test_descriptors.py b/python/pyarmnn/test/test_descriptors.py new file mode 100644 index 0000000000..edca7ed024 --- /dev/null +++ b/python/pyarmnn/test/test_descriptors.py @@ -0,0 +1,528 @@ +# Copyright © 2019 Arm Ltd. All rights reserved. +# SPDX-License-Identifier: MIT +import inspect + +import pytest + +import pyarmnn as ann +import numpy as np +import pyarmnn._generated.pyarmnn as generated + + +def test_activation_descriptor_default_values(): + desc = ann.ActivationDescriptor() + assert desc.m_Function == ann.ActivationFunction_Sigmoid + assert desc.m_A == 0 + assert desc.m_B == 0 + + +def test_argminmax_descriptor_default_values(): + desc = ann.ArgMinMaxDescriptor() + assert desc.m_Function == ann.ArgMinMaxFunction_Min + assert desc.m_Axis == -1 + + +def test_batchnormalization_descriptor_default_values(): + desc = ann.BatchNormalizationDescriptor() + assert desc.m_DataLayout == ann.DataLayout_NCHW + np.allclose(0.0001, desc.m_Eps) + + +def test_batchtospacend_descriptor_default_values(): + desc = ann.BatchToSpaceNdDescriptor() + assert desc.m_DataLayout == ann.DataLayout_NCHW + assert [1, 1] == desc.m_BlockShape + assert [(0, 0), (0, 0)] == desc.m_Crops + + +def test_batchtospacend_descriptor_assignment(): + desc = ann.BatchToSpaceNdDescriptor() + desc.m_BlockShape = (1, 2, 3) + + ololo = [(1, 2), (3, 4)] + size_1 = len(ololo) + desc.m_Crops = ololo + + assert size_1 == len(ololo) + desc.m_DataLayout = ann.DataLayout_NHWC + assert ann.DataLayout_NHWC == desc.m_DataLayout + assert [1, 2, 3] == desc.m_BlockShape + assert [(1, 2), (3, 4)] == desc.m_Crops + + +@pytest.mark.parametrize("input_shape, value, vtype", [([-1], -1, 'int'), (("one", "two"), "'one'", 'str'), + ([1.33, 4.55], 1.33, 'float'), + ([{1: "one"}], "{1: 'one'}", 'dict')], ids=lambda x: str(x)) +def test_batchtospacend_descriptor_rubbish_assignment_shape(input_shape, value, vtype): + desc = ann.BatchToSpaceNdDescriptor() + with pytest.raises(TypeError) as err: + desc.m_BlockShape = input_shape + + assert "Failed to convert python input value {} of type '{}' to C type 'j'".format(value, vtype) in str(err.value) + + +@pytest.mark.parametrize("input_crops, value, vtype", [([(1, 2), (3, 4, 5)], '(3, 4, 5)', 'tuple'), + ([(1, 'one')], "(1, 'one')", 'tuple'), + ([-1], -1, 'int'), + ([(1, (1, 2))], '(1, (1, 2))', 'tuple'), + ([[1, [1, 2]]], '[1, [1, 2]]', 'list') + ], ids=lambda x: str(x)) +def test_batchtospacend_descriptor_rubbish_assignment_crops(input_crops, value, vtype): + desc = ann.BatchToSpaceNdDescriptor() + with pytest.raises(TypeError) as err: + desc.m_Crops = input_crops + + assert "Failed to convert python input value {} of type '{}' to C type".format(value, vtype) in str(err.value) + + +def test_batchtospacend_descriptor_empty_assignment(): + desc = ann.BatchToSpaceNdDescriptor() + desc.m_BlockShape = [] + assert [] == desc.m_BlockShape + + +def test_batchtospacend_descriptor_ctor(): + desc = ann.BatchToSpaceNdDescriptor([1, 2, 3], [(4, 5), (6, 7)]) + assert desc.m_DataLayout == ann.DataLayout_NCHW + assert [1, 2, 3] == desc.m_BlockShape + assert [(4, 5), (6, 7)] == desc.m_Crops + + +def test_convolution2d_descriptor_default_values(): + desc = ann.Convolution2dDescriptor() + assert desc.m_PadLeft == 0 + assert desc.m_PadTop == 0 + assert desc.m_PadRight == 0 + assert desc.m_PadBottom == 0 + assert desc.m_StrideX == 0 + assert desc.m_StrideY == 0 + assert desc.m_DilationX == 1 + assert desc.m_DilationY == 1 + assert desc.m_BiasEnabled == False + assert desc.m_DataLayout == ann.DataLayout_NCHW + + +def test_depthtospace_descriptor_default_values(): + desc = ann.DepthToSpaceDescriptor() + assert desc.m_BlockSize == 1 + assert desc.m_DataLayout == ann.DataLayout_NHWC + + +def test_depthwise_convolution2d_descriptor_default_values(): + desc = ann.DepthwiseConvolution2dDescriptor() + assert desc.m_PadLeft == 0 + assert desc.m_PadTop == 0 + assert desc.m_PadRight == 0 + assert desc.m_PadBottom == 0 + assert desc.m_StrideX == 0 + assert desc.m_StrideY == 0 + assert desc.m_DilationX == 1 + assert desc.m_DilationY == 1 + assert desc.m_BiasEnabled == False + assert desc.m_DataLayout == ann.DataLayout_NCHW + + +def test_detectionpostprocess_descriptor_default_values(): + desc = ann.DetectionPostProcessDescriptor() + assert desc.m_MaxDetections == 0 + assert desc.m_MaxClassesPerDetection == 1 + assert desc.m_DetectionsPerClass == 1 + assert desc.m_NmsScoreThreshold == 0 + assert desc.m_NmsIouThreshold == 0 + assert desc.m_NumClasses == 0 + assert desc.m_UseRegularNms == False + assert desc.m_ScaleH == 0 + assert desc.m_ScaleW == 0 + assert desc.m_ScaleX == 0 + assert desc.m_ScaleY == 0 + + +def test_fakequantization_descriptor_default_values(): + desc = ann.FakeQuantizationDescriptor() + np.allclose(6, desc.m_Max) + np.allclose(-6, desc.m_Min) + + +def test_fully_connected_descriptor_default_values(): + desc = ann.FullyConnectedDescriptor() + assert desc.m_BiasEnabled == False + assert desc.m_TransposeWeightMatrix == False + + +def test_instancenormalization_descriptor_default_values(): + desc = ann.InstanceNormalizationDescriptor() + assert desc.m_Gamma == 1 + assert desc.m_Beta == 0 + assert desc.m_DataLayout == ann.DataLayout_NCHW + np.allclose(1e-12, desc.m_Eps) + + +def test_lstm_descriptor_default_values(): + desc = ann.LstmDescriptor() + assert desc.m_ActivationFunc == 1 + assert desc.m_ClippingThresCell == 0 + assert desc.m_ClippingThresProj == 0 + assert desc.m_CifgEnabled == True + assert desc.m_PeepholeEnabled == False + assert desc.m_ProjectionEnabled == False + assert desc.m_LayerNormEnabled == False + + +def test_l2normalization_descriptor_default_values(): + desc = ann.L2NormalizationDescriptor() + assert desc.m_DataLayout == ann.DataLayout_NCHW + np.allclose(1e-12, desc.m_Eps) + + +def test_mean_descriptor_default_values(): + desc = ann.MeanDescriptor() + assert desc.m_KeepDims == False + + +def test_normalization_descriptor_default_values(): + desc = ann.NormalizationDescriptor() + assert desc.m_NormChannelType == ann.NormalizationAlgorithmChannel_Across + assert desc.m_NormMethodType == ann.NormalizationAlgorithmMethod_LocalBrightness + assert desc.m_NormSize == 0 + assert desc.m_Alpha == 0 + assert desc.m_Beta == 0 + assert desc.m_K == 0 + assert desc.m_DataLayout == ann.DataLayout_NCHW + + +def test_origin_descriptor_default_values(): + desc = ann.ConcatDescriptor() + assert 0 == desc.GetNumViews() + assert 0 == desc.GetNumDimensions() + assert 1 == desc.GetConcatAxis() + + +def test_origin_descriptor_incorrect_views(): + desc = ann.ConcatDescriptor(2, 2) + with pytest.raises(RuntimeError) as err: + desc.SetViewOriginCoord(1000, 100, 1000) + assert "Failed to set view origin coordinates." in str(err.value) + + +def test_origin_descriptor_ctor(): + desc = ann.ConcatDescriptor(2, 2) + value = 5 + for i in range(desc.GetNumViews()): + for j in range(desc.GetNumDimensions()): + desc.SetViewOriginCoord(i, j, value+i) + desc.SetConcatAxis(1) + + assert 2 == desc.GetNumViews() + assert 2 == desc.GetNumDimensions() + assert [5, 5] == desc.GetViewOrigin(0) + assert [6, 6] == desc.GetViewOrigin(1) + assert 1 == desc.GetConcatAxis() + + +def test_pad_descriptor_default_values(): + desc = ann.PadDescriptor() + assert desc.m_PadValue == 0 + + +def test_permute_descriptor_default_values(): + pv = ann.PermutationVector((0, 2, 3, 1)) + desc = ann.PermuteDescriptor(pv) + assert desc.m_DimMappings.GetSize() == 4 + assert desc.m_DimMappings[0] == 0 + assert desc.m_DimMappings[1] == 2 + assert desc.m_DimMappings[2] == 3 + assert desc.m_DimMappings[3] == 1 + + +def test_pooling_descriptor_default_values(): + desc = ann.Pooling2dDescriptor() + assert desc.m_PoolType == ann.PoolingAlgorithm_Max + assert desc.m_PadLeft == 0 + assert desc.m_PadTop == 0 + assert desc.m_PadRight == 0 + assert desc.m_PadBottom == 0 + assert desc.m_PoolHeight == 0 + assert desc.m_PoolWidth == 0 + assert desc.m_StrideX == 0 + assert desc.m_StrideY == 0 + assert desc.m_OutputShapeRounding == ann.OutputShapeRounding_Floor + assert desc.m_PaddingMethod == ann.PaddingMethod_Exclude + assert desc.m_DataLayout == ann.DataLayout_NCHW + + +def test_reshape_descriptor_default_values(): + desc = ann.ReshapeDescriptor() + # check the empty Targetshape + assert desc.m_TargetShape.GetNumDimensions() == 0 + + +def test_slice_descriptor_default_values(): + desc = ann.SliceDescriptor() + assert desc.m_TargetWidth == 0 + assert desc.m_TargetHeight == 0 + assert desc.m_Method == ann.ResizeMethod_NearestNeighbor + assert desc.m_DataLayout == ann.DataLayout_NCHW + + +def test_resize_descriptor_default_values(): + desc = ann.ResizeDescriptor() + assert desc.m_TargetWidth == 0 + assert desc.m_TargetHeight == 0 + assert desc.m_Method == ann.ResizeMethod_NearestNeighbor + assert desc.m_DataLayout == ann.DataLayout_NCHW + + +def test_spacetobatchnd_descriptor_default_values(): + desc = ann.SpaceToBatchNdDescriptor() + assert desc.m_DataLayout == ann.DataLayout_NCHW + + +def test_spacetodepth_descriptor_default_values(): + desc = ann.SpaceToDepthDescriptor() + assert desc.m_BlockSize == 1 + assert desc.m_DataLayout == ann.DataLayout_NHWC + + +def test_stack_descriptor_default_values(): + desc = ann.StackDescriptor() + assert desc.m_Axis == 0 + assert desc.m_NumInputs == 0 + # check the empty Inputshape + assert desc.m_InputShape.GetNumDimensions() == 0 + + +def test_slice_descriptor_default_values(): + desc = ann.SliceDescriptor() + desc.m_Begin = [1, 2, 3, 4, 5] + desc.m_Size = (1, 2, 3, 4) + + assert [1, 2, 3, 4, 5] == desc.m_Begin + assert [1, 2, 3, 4] == desc.m_Size + + +def test_slice_descriptor_ctor(): + desc = ann.SliceDescriptor([1, 2, 3, 4, 5], (1, 2, 3, 4)) + + assert [1, 2, 3, 4, 5] == desc.m_Begin + assert [1, 2, 3, 4] == desc.m_Size + + +def test_strided_slice_descriptor_default_values(): + desc = ann.StridedSliceDescriptor() + desc.m_Begin = [1, 2, 3, 4, 5] + desc.m_End = [6, 7, 8, 9, 10] + desc.m_Stride = (10, 10) + desc.m_BeginMask = 1 + desc.m_EndMask = 2 + desc.m_ShrinkAxisMask = 3 + desc.m_EllipsisMask = 4 + desc.m_NewAxisMask = 5 + + assert [1, 2, 3, 4, 5] == desc.m_Begin + assert [6, 7, 8, 9, 10] == desc.m_End + assert [10, 10] == desc.m_Stride + assert 1 == desc.m_BeginMask + assert 2 == desc.m_EndMask + assert 3 == desc.m_ShrinkAxisMask + assert 4 == desc.m_EllipsisMask + assert 5 == desc.m_NewAxisMask + + +def test_strided_slice_descriptor_ctor(): + desc = ann.StridedSliceDescriptor([1, 2, 3, 4, 5], [6, 7, 8, 9, 10], (10, 10)) + desc.m_Begin = [1, 2, 3, 4, 5] + desc.m_End = [6, 7, 8, 9, 10] + desc.m_Stride = (10, 10) + + assert [1, 2, 3, 4, 5] == desc.m_Begin + assert [6, 7, 8, 9, 10] == desc.m_End + assert [10, 10] == desc.m_Stride + + +def test_softmax_descriptor_default_values(): + desc = ann.SoftmaxDescriptor() + assert desc.m_Axis == -1 + np.allclose(1.0, desc.m_Beta) + + +def test_space_to_batch_nd_descriptor_default_values(): + desc = ann.SpaceToBatchNdDescriptor() + assert [1, 1] == desc.m_BlockShape + assert [(0, 0), (0, 0)] == desc.m_PadList + assert ann.DataLayout_NCHW == desc.m_DataLayout + + +def test_space_to_batch_nd_descriptor_assigned_values(): + desc = ann.SpaceToBatchNdDescriptor() + desc.m_BlockShape = (90, 100) + desc.m_PadList = [(1, 2), (3, 4)] + assert [90, 100] == desc.m_BlockShape + assert [(1, 2), (3, 4)] == desc.m_PadList + assert ann.DataLayout_NCHW == desc.m_DataLayout + + +def test_space_to_batch_nd_descriptor_ctor(): + desc = ann.SpaceToBatchNdDescriptor((1, 2, 3), [(1, 2), (3, 4)]) + assert [1, 2, 3] == desc.m_BlockShape + assert [(1, 2), (3, 4)] == desc.m_PadList + assert ann.DataLayout_NCHW == desc.m_DataLayout + + +def test_transpose_convolution2d_descriptor_default_values(): + desc = ann.DepthwiseConvolution2dDescriptor() + assert desc.m_PadLeft == 0 + assert desc.m_PadTop == 0 + assert desc.m_PadRight == 0 + assert desc.m_PadBottom == 0 + assert desc.m_StrideX == 0 + assert desc.m_StrideY == 0 + assert desc.m_BiasEnabled == False + assert desc.m_DataLayout == ann.DataLayout_NCHW + + +def test_view_descriptor_default_values(): + desc = ann.SplitterDescriptor() + assert 0 == desc.GetNumViews() + assert 0 == desc.GetNumDimensions() + + +def test_view_descriptor_incorrect_input(): + desc = ann.SplitterDescriptor(2, 3) + with pytest.raises(RuntimeError) as err: + desc.SetViewOriginCoord(1000, 100, 1000) + assert "Failed to set view origin coordinates." in str(err.value) + + with pytest.raises(RuntimeError) as err: + desc.SetViewSize(1000, 100, 1000) + assert "Failed to set view size." in str(err.value) + + +def test_view_descriptor_ctor(): + desc = ann.SplitterDescriptor(2, 3) + value_size = 1 + value_orig_coord = 5 + for i in range(desc.GetNumViews()): + for j in range(desc.GetNumDimensions()): + desc.SetViewOriginCoord(i, j, value_orig_coord+i) + desc.SetViewSize(i, j, value_size+i) + + assert 2 == desc.GetNumViews() + assert 3 == desc.GetNumDimensions() + assert [5, 5] == desc.GetViewOrigin(0) + assert [6, 6] == desc.GetViewOrigin(1) + assert [1, 1] == desc.GetViewSizes(0) + assert [2, 2] == desc.GetViewSizes(1) + + +def test_createdescriptorforconcatenation_ctor(): + input_shape_vector = [ann.TensorShape((2, 1)), ann.TensorShape((3, 1)), ann.TensorShape((4, 1))] + desc = ann.CreateDescriptorForConcatenation(input_shape_vector, 0) + assert 3 == desc.GetNumViews() + assert 0 == desc.GetConcatAxis() + assert 2 == desc.GetNumDimensions() + c = desc.GetViewOrigin(1) + d = desc.GetViewOrigin(0) + + +def test_createdescriptorforconcatenation_wrong_shape_for_axis(): + input_shape_vector = [ann.TensorShape((1, 2)), ann.TensorShape((3, 4)), ann.TensorShape((5, 6))] + with pytest.raises(RuntimeError) as err: + desc = ann.CreateDescriptorForConcatenation(input_shape_vector, 0) + + assert "All inputs to concatenation must be the same size along all dimensions except the concatenation dimension" in str( + err.value) + + +@pytest.mark.parametrize("input_shape_vector", [([-1, "one"]), + ([1.33, 4.55]), + ([{1: "one"}])], ids=lambda x: str(x)) +def test_createdescriptorforconcatenation_rubbish_assignment_shape_vector(input_shape_vector): + with pytest.raises(TypeError) as err: + desc = ann.CreateDescriptorForConcatenation(input_shape_vector, 0) + + assert "in method 'CreateDescriptorForConcatenation', argument 1 of type 'std::vector< armnn::TensorShape,std::allocator< armnn::TensorShape > >'" in str( + err.value) + + +generated_classes = inspect.getmembers(generated, inspect.isclass) +generated_classes_names = list(map(lambda x: x[0], generated_classes)) +@pytest.mark.parametrize("desc_name", ['ActivationDescriptor', + 'ArgMinMaxDescriptor', + 'PermuteDescriptor', + 'SoftmaxDescriptor', + 'ConcatDescriptor', + 'SplitterDescriptor', + 'Pooling2dDescriptor', + 'FullyConnectedDescriptor', + 'Convolution2dDescriptor', + 'DepthwiseConvolution2dDescriptor', + 'DetectionPostProcessDescriptor', + 'NormalizationDescriptor', + 'L2NormalizationDescriptor', + 'BatchNormalizationDescriptor', + 'InstanceNormalizationDescriptor', + 'BatchToSpaceNdDescriptor', + 'FakeQuantizationDescriptor', + 'ResizeDescriptor', + 'ReshapeDescriptor', + 'SpaceToBatchNdDescriptor', + 'SpaceToDepthDescriptor', + 'LstmDescriptor', + 'MeanDescriptor', + 'PadDescriptor', + 'SliceDescriptor', + 'StackDescriptor', + 'StridedSliceDescriptor', + 'TransposeConvolution2dDescriptor']) +class TestDescriptorMassChecks: + + def test_desc_implemented(self, desc_name): + assert desc_name in generated_classes_names + + def test_desc_equal(self, desc_name): + desc_class = next(filter(lambda x: x[0] == desc_name ,generated_classes))[1] + + assert desc_class() == desc_class() + + + +generated_classes = inspect.getmembers(generated, inspect.isclass) +generated_classes_names = list(map(lambda x: x[0], generated_classes)) +@pytest.mark.parametrize("desc_name", ['ActivationDescriptor', + 'ArgMinMaxDescriptor', + 'PermuteDescriptor', + 'SoftmaxDescriptor', + 'ConcatDescriptor', + 'SplitterDescriptor', + 'Pooling2dDescriptor', + 'FullyConnectedDescriptor', + 'Convolution2dDescriptor', + 'DepthwiseConvolution2dDescriptor', + 'DetectionPostProcessDescriptor', + 'NormalizationDescriptor', + 'L2NormalizationDescriptor', + 'BatchNormalizationDescriptor', + 'InstanceNormalizationDescriptor', + 'BatchToSpaceNdDescriptor', + 'FakeQuantizationDescriptor', + 'ResizeDescriptor', + 'ReshapeDescriptor', + 'SpaceToBatchNdDescriptor', + 'SpaceToDepthDescriptor', + 'LstmDescriptor', + 'MeanDescriptor', + 'PadDescriptor', + 'SliceDescriptor', + 'StackDescriptor', + 'StridedSliceDescriptor', + 'TransposeConvolution2dDescriptor']) +class TestDescriptorMassChecks: + + def test_desc_implemented(self, desc_name): + assert desc_name in generated_classes_names + + def test_desc_equal(self, desc_name): + desc_class = next(filter(lambda x: x[0] == desc_name ,generated_classes))[1] + + assert desc_class() == desc_class() + |