e87cc3fa9e
* Added OpenVINO Tensor API * Tensor API improvements * Moved Tensor to ngraph * Moved Tensor tests * Fixed docs and code style * Trying to fix Windows * Fixed clang-format * Moved Tensor to runtime namespace * Fixed compilation * Fixed clang-format * Fixed tests in debug Co-authored-by: apankratovantonp <anton.pankratov@intel.com>
197 lines
7.6 KiB
C++
197 lines
7.6 KiB
C++
// Copyright (C) 2018-2021 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#include <gmock/gmock-spec-builders.h>
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#include <gmock/gmock.h>
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#include <gtest/gtest.h>
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#include <cstdint>
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#include <openvino/core/shape.hpp>
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#include <openvino/core/strides.hpp>
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#include <openvino/core/type/element_type.hpp>
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#include "openvino/runtime/allocator.hpp"
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#include "openvino/runtime/tensor.hpp"
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using OVTensorTest = ::testing::Test;
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TEST_F(OVTensorTest, canCreateTensor) {
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ov::Shape shape = {4, 3, 2};
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ov::runtime::Tensor t{ov::element::f32, shape};
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const std::size_t totalSize = ov::shape_size(shape);
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ASSERT_EQ(totalSize, t.get_size());
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ASSERT_NE(nullptr, t.data());
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ASSERT_EQ(ov::element::f32, t.get_element_type());
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ASSERT_EQ(shape, t.get_shape());
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ASSERT_NE(shape, t.get_strides());
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ASSERT_EQ(ov::Strides({6, 2, 1}), t.get_strides());
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ASSERT_EQ(ov::element::f32.size() * totalSize, t.get_byte_size());
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ASSERT_THROW(t.data(ov::element::i64), ov::Exception);
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ASSERT_THROW(t.data<std::int32_t>(), ov::Exception);
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}
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TEST_F(OVTensorTest, operators) {
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ov::runtime::Tensor t;
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ASSERT_FALSE(t);
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ASSERT_TRUE(!t);
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}
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class OVMockAllocator : public ov::runtime::AllocatorImpl {
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public:
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MOCK_METHOD(void*, allocate, (size_t, size_t), ());
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MOCK_METHOD(void, deallocate, (void*, size_t, size_t), ()); // NOLINT(readability/casting)
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MOCK_METHOD(bool, is_equal, (const ov::runtime::AllocatorImpl&), (const, noexcept)); // NOLINT(readability/casting)
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};
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TEST_F(OVTensorTest, canCreateTensorUsingMockAllocator) {
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ov::Shape shape = {1, 2, 3};
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auto allocator = std::make_shared<OVMockAllocator>();
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EXPECT_CALL(*allocator, allocate(::testing::_, ::testing::_))
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.WillRepeatedly(testing::Return(reinterpret_cast<void*>(1)));
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EXPECT_CALL(*allocator, deallocate(::testing::_, ::testing::_, ::testing::_)).Times(1);
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{ ov::runtime::Tensor t{ov::element::f32, shape, ov::runtime::Allocator{allocator}}; }
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}
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TEST_F(OVTensorTest, canAccessExternalData) {
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ov::Shape shape = {1, 1, 3};
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float data[] = {5.f, 6.f, 7.f};
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ov::runtime::Tensor t{ov::element::f32, shape, data, 3};
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{
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float* ptr = t.data<float>();
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ASSERT_EQ(ptr[2], 7);
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ASSERT_EQ(data, t.data(ov::element::f32));
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ASSERT_EQ(data, ptr);
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ASSERT_THROW(t.data<std::int16_t>(), ov::Exception);
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ASSERT_EQ(ov::row_major_strides(shape), t.get_strides());
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ASSERT_EQ(ov::shape_size(shape), t.get_size());
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ASSERT_EQ(ov::shape_size(shape) * ov::element::f32.size(), t.get_byte_size());
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}
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}
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TEST_F(OVTensorTest, canAccessExternalDataWithStrides) {
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ov::Shape shape = {2, 3};
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float data[] = {5.f, 6.f, 7.f, 0.f, 1.f, 42.f, 3.f, 0.f};
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ov::runtime::Tensor t{ov::element::f32, shape, data, 8, {4, 1}};
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{
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ASSERT_EQ((ov::Shape{2, 3}), t.get_shape());
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float* ptr = t.data<float>();
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ASSERT_EQ(ptr[5], 42);
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}
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}
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TEST_F(OVTensorTest, cannotCreateTensorWithExternalNullptr) {
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ov::Shape shape = {2, 3};
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ASSERT_THROW(ov::runtime::Tensor(ov::element::f32, shape, nullptr), ov::Exception);
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}
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TEST_F(OVTensorTest, cannotCreateTensorWithWrongStrides) {
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ov::Shape shape = {2, 3};
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float data[] = {5.f, 6.f, 7.f, 0.f, 1.f, 42.f, 3.f, 0.f};
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ASSERT_THROW(ov::runtime::Tensor(ov::element::f32, shape, data, 8, {4, 1, 2}), ov::Exception);
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}
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TEST_F(OVTensorTest, saveDimsAndSizeAfterMove) {
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ov::Shape shape = {1, 2, 3};
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ov::runtime::Tensor t{ov::element::f32, shape};
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ov::runtime::Tensor new_tensor(std::move(t));
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ASSERT_EQ(shape, new_tensor.get_shape());
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ASSERT_EQ(ov::element::f32, new_tensor.get_element_type());
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ASSERT_EQ(ov::row_major_strides(shape), new_tensor.get_strides());
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ASSERT_THROW(t.get_size(), ov::Exception);
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ASSERT_THROW(t.get_element_type(), ov::Exception);
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ASSERT_THROW(t.get_byte_size(), ov::Exception);
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ASSERT_THROW(t.get_strides(), ov::Exception);
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ASSERT_THROW(t.get_shape(), ov::Exception);
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ASSERT_THROW(t.set_shape({}), ov::Exception);
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ASSERT_THROW(t.data(), ov::Exception);
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ASSERT_THROW(t.data<float>(), ov::Exception);
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}
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// SetShape
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TEST_F(OVTensorTest, canSetShape) {
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ov::runtime::Tensor t{ov::element::f32, {1, 2, 3}};
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const ov::Shape newShape({4, 5, 6});
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ASSERT_EQ(t.get_shape(), (ov::Shape{1, 2, 3}));
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ASSERT_NO_THROW(t.set_shape({4, 5, 6}));
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ASSERT_EQ(newShape, t.get_shape());
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ASSERT_EQ(ov::row_major_strides(newShape), t.get_strides());
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// check that setShape for copy changes original Tensor
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{
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ov::runtime::Tensor t2 = t;
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t2.set_shape(newShape);
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ASSERT_EQ(newShape, t.get_shape());
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ASSERT_EQ(t2.get_shape(), t.get_shape());
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}
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}
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TEST_F(OVTensorTest, makeRangeRoiTensor) {
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ov::runtime::Tensor t{ov::element::i8, {1, 3, 6, 5}}; // RGBp picture of size (WxH) = 5x6
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ov::runtime::Tensor roi_tensor{t, {0, 0, 1, 2}, {1, 3, 5, 4}};
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ov::Shape ref_shape = {1, 3, 4, 2};
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ptrdiff_t ref_offset = 7;
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ov::Strides ref_strides = {90, 30, 5, 1};
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ASSERT_EQ(roi_tensor.get_shape(), ref_shape);
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ASSERT_EQ(roi_tensor.data<int8_t>() - t.data<int8_t>(), ref_offset);
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ASSERT_EQ(reinterpret_cast<uint8_t*>(roi_tensor.data()) - reinterpret_cast<uint8_t*>(t.data()), ref_offset);
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ASSERT_EQ(roi_tensor.get_strides(), t.get_strides());
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ASSERT_EQ(ref_strides, roi_tensor.get_strides());
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ASSERT_EQ(roi_tensor.get_element_type(), t.get_element_type());
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}
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TEST_F(OVTensorTest, makeRangeRoiTensorInt4) {
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ov::runtime::Tensor t{ov::element::i4, {1, 6, 5, 3}}; // RGB picture of size (WxH) = 5x6
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ov::runtime::Tensor roi_tensor{t, {0, 1, 2, 0}, {1, 5, 4, 3}};
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ov::Shape ref_shape = {1, 4, 2, 3};
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ptrdiff_t ref_offset = 21;
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ov::Strides ref_strides = {90, 15, 3, 1};
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ASSERT_EQ(roi_tensor.get_shape(), ref_shape);
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ASSERT_EQ(roi_tensor.data<int8_t>() - t.data<int8_t>(), ref_offset);
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ASSERT_EQ(roi_tensor.get_strides(), ref_strides);
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ASSERT_EQ(roi_tensor.get_strides(), t.get_strides());
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ASSERT_EQ(ref_strides, roi_tensor.get_strides());
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ASSERT_EQ(roi_tensor.get_element_type(), t.get_element_type());
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}
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TEST_F(OVTensorTest, makeRangeRoiBlobWrongSize) {
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ov::runtime::Tensor t{ov::element::f32, {1, 3, 4, 4}};
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ASSERT_THROW((ov::runtime::Tensor{t, {0, 0, 1, 1}, {1, 3, 5, 5}}), ov::Exception);
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ASSERT_THROW((ov::runtime::Tensor{t, {0, 0, 1, 1, 3}, {1, 3, 4, 4}}), ov::Exception);
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}
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TEST_F(OVTensorTest, readRangeRoiBlob) {
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ov::runtime::Tensor t{ov::element::i32, {1, 3, 4, 8}};
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{
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const auto origPtr = t.data<int32_t>();
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ASSERT_NE(nullptr, origPtr);
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for (size_t i = 0; i < t.get_size(); ++i) {
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origPtr[i] = i;
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}
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}
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ov::runtime::Tensor roi_tensor{t, {0, 0, 2, 4}, {1, 3, 4, 8}};
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ASSERT_NE(false, static_cast<bool>(roi_tensor));
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{
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auto roi = roi_tensor.data<int32_t>();
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ASSERT_NE(nullptr, roi);
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auto strides = roi_tensor.get_strides();
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for (size_t n = 0; n < roi_tensor.get_shape()[0]; ++n) {
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for (size_t c = 0; c < roi_tensor.get_shape()[1]; ++c) {
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for (size_t h = 0; h < roi_tensor.get_shape()[2]; ++h) {
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for (size_t w = 0; w < roi_tensor.get_shape()[3]; ++w) {
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auto actual = roi[w * strides[3] + h * strides[2] + c * strides[1] + n * strides[0]];
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auto expected = t.data<int32_t>()[(w + 4) * strides[3] + (h + 2) * strides[2] +
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(c + 0) * strides[1] + (n + 0) * strides[0]];
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ASSERT_EQ(expected, actual) << ov::Shape{n, c, h, w};
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}
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}
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}
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}
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}
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}
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