# 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()