From dc0c6ed9f8b993e63f492f203d7d7080ab4c835c Mon Sep 17 00:00:00 2001 From: Richard Burton Date: Wed, 8 Apr 2020 16:39:05 +0100 Subject: Add PyArmNN to work with ArmNN API of 20.02 * Add Swig rules for generating python wrapper * Add documentation * Add tests and testing data Change-Id: If48eda08931514fa21e72214dfead2835f07237c Signed-off-by: Richard Burton Signed-off-by: Derek Lamberti --- python/pyarmnn/test/test_tensor.py | 144 +++++++++++++++++++++++++++++++++++++ 1 file changed, 144 insertions(+) create mode 100644 python/pyarmnn/test/test_tensor.py (limited to 'python/pyarmnn/test/test_tensor.py') diff --git a/python/pyarmnn/test/test_tensor.py b/python/pyarmnn/test/test_tensor.py new file mode 100644 index 0000000000..8b57169596 --- /dev/null +++ b/python/pyarmnn/test/test_tensor.py @@ -0,0 +1,144 @@ +# Copyright © 2020 Arm Ltd. All rights reserved. +# SPDX-License-Identifier: MIT +from copy import copy + +import pytest +import numpy as np +import pyarmnn as ann + + +def __get_tensor_info(dt): + tensor_info = ann.TensorInfo(ann.TensorShape((2, 3)), dt) + + return tensor_info + + +@pytest.mark.parametrize("dt", [ann.DataType_Float32, ann.DataType_Float16, + ann.DataType_QAsymmU8, ann.DataType_QSymmS8, + ann.DataType_QAsymmS8]) +def test_create_tensor_with_info(dt): + tensor_info = __get_tensor_info(dt) + elements = tensor_info.GetNumElements() + num_bytes = tensor_info.GetNumBytes() + d_type = dt + + tensor = ann.Tensor(tensor_info) + + assert tensor_info != tensor.GetInfo(), "Different objects" + assert elements == tensor.GetNumElements() + assert num_bytes == tensor.GetNumBytes() + assert d_type == tensor.GetDataType() + + +def test_create_tensor_undefined_datatype(): + tensor_info = ann.TensorInfo() + tensor_info.SetDataType(99) + + with pytest.raises(ValueError) as err: + ann.Tensor(tensor_info) + + assert 'The data type provided for this Tensor is not supported.' in str(err.value) + + +@pytest.mark.parametrize("dt", [ann.DataType_Float32]) +def test_tensor_memory_output(dt): + tensor_info = __get_tensor_info(dt) + tensor = ann.Tensor(tensor_info) + + # empty memory area because inference has not yet been run. + assert tensor.get_memory_area().tolist() # has random stuff + assert 4 == tensor.get_memory_area().itemsize, "it is float32" + + +@pytest.mark.parametrize("dt", [ann.DataType_Float32, ann.DataType_Float16, + ann.DataType_QAsymmU8, ann.DataType_QSymmS8, + ann.DataType_QAsymmS8]) +def test_tensor__str__(dt): + tensor_info = __get_tensor_info(dt) + elements = tensor_info.GetNumElements() + num_bytes = tensor_info.GetNumBytes() + d_type = dt + dimensions = tensor_info.GetNumDimensions() + + tensor = ann.Tensor(tensor_info) + + assert str(tensor) == "Tensor{{DataType: {}, NumBytes: {}, NumDimensions: " \ + "{}, NumElements: {}}}".format(d_type, num_bytes, dimensions, elements) + + +def test_create_empty_tensor(): + tensor = ann.Tensor() + + assert 0 == tensor.GetNumElements() + assert 0 == tensor.GetNumBytes() + assert tensor.get_memory_area() is None + + +@pytest.mark.parametrize("dt", [ann.DataType_Float32, ann.DataType_Float16, + ann.DataType_QAsymmU8, ann.DataType_QSymmS8, + ann.DataType_QAsymmS8]) +def test_create_tensor_from_tensor(dt): + tensor_info = __get_tensor_info(dt) + tensor = ann.Tensor(tensor_info) + copied_tensor = ann.Tensor(tensor) + + assert copied_tensor != tensor, "Different objects" + assert copied_tensor.GetInfo() != tensor.GetInfo(), "Different objects" + assert copied_tensor.get_memory_area().ctypes.data == tensor.get_memory_area().ctypes.data, "Same memory area" + assert copied_tensor.GetNumElements() == tensor.GetNumElements() + assert copied_tensor.GetNumBytes() == tensor.GetNumBytes() + assert copied_tensor.GetDataType() == tensor.GetDataType() + + +@pytest.mark.parametrize("dt", [ann.DataType_Float32, ann.DataType_Float16, + ann.DataType_QAsymmU8, ann.DataType_QSymmS8, + ann.DataType_QAsymmS8]) +def test_copy_tensor(dt): + tensor = ann.Tensor(__get_tensor_info(dt)) + copied_tensor = copy(tensor) + + assert copied_tensor != tensor, "Different objects" + assert copied_tensor.GetInfo() != tensor.GetInfo(), "Different objects" + assert copied_tensor.get_memory_area().ctypes.data == tensor.get_memory_area().ctypes.data, "Same memory area" + assert copied_tensor.GetNumElements() == tensor.GetNumElements() + assert copied_tensor.GetNumBytes() == tensor.GetNumBytes() + assert copied_tensor.GetDataType() == tensor.GetDataType() + + +@pytest.mark.parametrize("dt", [ann.DataType_Float32, ann.DataType_Float16, + ann.DataType_QAsymmU8, ann.DataType_QSymmS8, + ann.DataType_QAsymmS8]) +def test_copied_tensor_has_memory_area_access_after_deletion_of_original_tensor(dt): + + tensor = ann.Tensor(__get_tensor_info(dt)) + + tensor.get_memory_area()[0] = 100 + + initial_mem_copy = np.array(tensor.get_memory_area()) + + assert 100 == initial_mem_copy[0] + + copied_tensor = ann.Tensor(tensor) + + del tensor + np.testing.assert_array_equal(copied_tensor.get_memory_area(), initial_mem_copy) + assert 100 == copied_tensor.get_memory_area()[0] + + +def test_create_const_tensor_incorrect_args(): + with pytest.raises(ValueError) as err: + ann.Tensor('something', 'something') + + expected_error_message = "Incorrect number of arguments or type of arguments provided to create Tensor." + assert expected_error_message in str(err.value) + + +@pytest.mark.parametrize("dt", [ann.DataType_Float16]) +def test_tensor_memory_output_fp16(dt): + # Check Tensor with float16 + tensor_info = __get_tensor_info(dt) + tensor = ann.Tensor(tensor_info) + + assert tensor.GetNumElements() == 6 + assert tensor.GetNumBytes() == 12 + assert tensor.GetDataType() == ann.DataType_Float16 -- cgit v1.2.1