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# Copyright © 2020 Arm Ltd and Contributors. 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_channelshuffle_descriptor_default_values():
desc = ann.ChannelShuffleDescriptor()
assert desc.m_Axis == 0
assert desc.m_NumGroups == 0
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 == 1
assert desc.m_StrideY == 1
assert desc.m_DilationX == 1
assert desc.m_DilationY == 1
assert desc.m_BiasEnabled == False
assert desc.m_DataLayout == ann.DataLayout_NCHW
def test_convolution3d_descriptor_default_values():
desc = ann.Convolution3dDescriptor()
assert desc.m_PadLeft == 0
assert desc.m_PadTop == 0
assert desc.m_PadRight == 0
assert desc.m_PadBottom == 0
assert desc.m_PadFront == 0
assert desc.m_PadBack == 0
assert desc.m_StrideX == 1
assert desc.m_StrideY == 1
assert desc.m_StrideZ == 1
assert desc.m_DilationX == 1
assert desc.m_DilationY == 1
assert desc.m_DilationZ == 1
assert desc.m_BiasEnabled == False
assert desc.m_DataLayout == ann.DataLayout_NDHWC
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 == 1
assert desc.m_StrideY == 1
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_fill_descriptor_default_values():
desc = ann.FillDescriptor()
np.allclose(0, desc.m_Value)
def test_gather_descriptor_default_values():
desc = ann.GatherDescriptor()
assert desc.m_Axis == 0
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
assert desc.m_PaddingMode == ann.PaddingMode_Constant
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_pooling_3d_descriptor_default_values():
desc = ann.Pooling3dDescriptor()
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_PadFront == 0
assert desc.m_PadBack == 0
assert desc.m_PoolHeight == 0
assert desc.m_PoolWidth == 0
assert desc.m_StrideX == 0
assert desc.m_StrideY == 0
assert desc.m_StrideZ == 0
assert desc.m_OutputShapeRounding == ann.OutputShapeRounding_Floor
assert desc.m_PaddingMethod == ann.PaddingMethod_Exclude
assert desc.m_DataLayout == ann.DataLayout_NCDHW
def test_reshape_descriptor_default_values():
desc = ann.ReshapeDescriptor()
# check the empty Targetshape
assert desc.m_TargetShape.GetNumDimensions() == 0
def test_reduce_descriptor_default_values():
desc = ann.ReduceDescriptor()
assert desc.m_KeepDims == False
assert desc.m_vAxis == []
assert desc.m_ReduceOperation == ann.ReduceOperation_Sum
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
assert desc.m_AlignCorners == False
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.TransposeConvolution2dDescriptor()
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
assert desc.m_OutputShapeEnabled == False
def test_transpose_descriptor_default_values():
pv = ann.PermutationVector((0, 3, 2, 1, 4))
desc = ann.TransposeDescriptor(pv)
assert desc.m_DimMappings.GetSize() == 5
assert desc.m_DimMappings[0] == 0
assert desc.m_DimMappings[1] == 3
assert desc.m_DimMappings[2] == 2
assert desc.m_DimMappings[3] == 1
assert desc.m_DimMappings[4] == 4
def test_view_descriptor_default_values():
desc = ann.SplitterDescriptor()
assert 0 == desc.GetNumViews()
assert 0 == desc.GetNumDimensions()
def test_elementwise_unary_descriptor_default_values():
desc = ann.ElementwiseUnaryDescriptor()
assert desc.m_Operation == ann.UnaryOperation_Abs
def test_logical_binary_descriptor_default_values():
desc = ann.LogicalBinaryDescriptor()
assert desc.m_Operation == ann.LogicalBinaryOperation_LogicalAnd
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',
'Convolution3dDescriptor',
'DepthwiseConvolution2dDescriptor',
'DetectionPostProcessDescriptor',
'NormalizationDescriptor',
'L2NormalizationDescriptor',
'BatchNormalizationDescriptor',
'InstanceNormalizationDescriptor',
'BatchToSpaceNdDescriptor',
'FakeQuantizationDescriptor',
'ReduceDescriptor',
'ResizeDescriptor',
'ReshapeDescriptor',
'SpaceToBatchNdDescriptor',
'SpaceToDepthDescriptor',
'LstmDescriptor',
'MeanDescriptor',
'PadDescriptor',
'SliceDescriptor',
'StackDescriptor',
'StridedSliceDescriptor',
'TransposeConvolution2dDescriptor',
'TransposeDescriptor',
'ElementwiseUnaryDescriptor',
'FillDescriptor',
'GatherDescriptor',
'LogicalBinaryDescriptor',
'ChannelShuffleDescriptor'])
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',
'Convolution3dDescriptor',
'DepthwiseConvolution2dDescriptor',
'DetectionPostProcessDescriptor',
'NormalizationDescriptor',
'L2NormalizationDescriptor',
'BatchNormalizationDescriptor',
'InstanceNormalizationDescriptor',
'BatchToSpaceNdDescriptor',
'FakeQuantizationDescriptor',
'ReduceDescriptor',
'ResizeDescriptor',
'ReshapeDescriptor',
'SpaceToBatchNdDescriptor',
'SpaceToDepthDescriptor',
'LstmDescriptor',
'MeanDescriptor',
'PadDescriptor',
'SliceDescriptor',
'StackDescriptor',
'StridedSliceDescriptor',
'TransposeConvolution2dDescriptor',
'TransposeDescriptor',
'ElementwiseUnaryDescriptor',
'FillDescriptor',
'GatherDescriptor',
'LogicalBinaryDescriptor',
'ChannelShuffleDescriptor'])
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()
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