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openvino/ngraph/test/backend/quantized_dot.in.cpp
Ilya Churaev d25bb6314a Deprecate nGraph v0 ops and builders (#1856)
* Deprecate nGraph v0 ops

* Fixed build

* Added deprecated defines to fix windows
2020-08-20 12:27:14 +03:00

120 lines
5.4 KiB
C++

//*****************************************************************************
// Copyright 2017-2020 Intel Corporation
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//*****************************************************************************
#include "gtest/gtest.h"
#include "ngraph/ngraph.hpp"
#include "ngraph/runtime/tensor.hpp"
#include "runtime/backend.hpp"
#include "util/all_close.hpp"
#include "util/all_close_f.hpp"
#include "util/known_element_types.hpp"
#include "util/ndarray.hpp"
#include "util/test_control.hpp"
#include "util/test_tools.hpp"
NGRAPH_SUPPRESS_DEPRECATED_START
using namespace std;
using namespace ngraph;
static string s_manifest = "${MANIFEST}";
NGRAPH_TEST(${BACKEND_NAME}, quantized_dot_u8u8)
{
Shape shape_a{1, 2}; // input shape
vector<uint8_t> a_data = {2, 3};
Shape shape_b{2, 3}; // filter shape
vector<uint8_t> b_data = {0, 2, 4, 1, 3, 5};
auto A = make_shared<op::Parameter>(element::u8, shape_a);
auto B = make_shared<op::Parameter>(element::u8, shape_b);
auto input_scale = op::Constant::create(element::f32, Shape{}, {2});
auto input_zero_point = op::Constant::create(element::u8, Shape{}, {0});
auto filter_scale = op::Constant::create(element::f32, Shape{}, {1});
auto filter_zero_point = op::Constant::create(element::u8, Shape{}, {0});
auto output_scale = op::Constant::create(element::f32, Shape{}, {2});
auto output_zero_point = op::Constant::create(element::u8, Shape{}, {0});
AxisSet axes{};
Shape shape_r{1, 3}; // output shape
auto QD = make_shared<op::QuantizedDot>(A,
B,
1,
input_scale,
input_zero_point,
filter_scale,
filter_zero_point,
output_scale,
output_zero_point,
element::u8,
axes,
axes,
axes);
auto f = make_shared<Function>(NodeVector{QD}, ParameterVector{A, B});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
// Create some tensors for input/output
auto a = backend->create_tensor(element::u8, shape_a);
copy_data(a, a_data);
auto b = backend->create_tensor(element::u8, shape_b);
copy_data(b, b_data);
auto result = backend->create_tensor(element::u8, shape_r);
auto handle = backend->compile(f);
handle->call_with_validate({result}, {a, b});
EXPECT_EQ((vector<uint8_t>{3, 13, 23}), read_vector<uint8_t>(result));
}
NGRAPH_TEST(${BACKEND_NAME}, quantized_dot_int32_output)
{
Shape shape_a{1, 2}; // input shape
vector<uint8_t> a_data = {2, 3};
Shape shape_b{2, 3}; // filter shape
vector<int8_t> b_data = {0, 1, 2, 3, 4, 5};
auto A = make_shared<op::Parameter>(element::u8, shape_a);
auto B = make_shared<op::Parameter>(element::i8, shape_b);
auto input_scale = op::Constant::create(element::f32, Shape{}, {1});
auto input_zero_point = op::Constant::create(element::u8, Shape{}, {0});
auto filter_scale = op::Constant::create(element::f32, Shape{}, {1});
auto filter_zero_point = op::Constant::create(element::i8, Shape{}, {0});
auto output_scale = op::Constant::create(element::f32, Shape{}, {1});
auto output_zero_point = op::Constant::create(element::i32, Shape{}, {0});
AxisSet axes{};
Shape shape_r{1, 3}; // output shape
auto QD = make_shared<op::QuantizedDot>(A,
B,
1,
input_scale,
input_zero_point,
filter_scale,
filter_zero_point,
output_scale,
output_zero_point,
element::i32,
axes,
axes,
axes);
auto f = make_shared<Function>(NodeVector{QD}, ParameterVector{A, B});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
// Create some tensors for input/output
auto a = backend->create_tensor(element::u8, shape_a);
copy_data(a, a_data);
auto b = backend->create_tensor(element::i8, shape_b);
copy_data(b, b_data);
auto result = backend->create_tensor(element::i32, shape_r);
auto handle = backend->compile(f);
handle->call_with_validate({result}, {a, b});
EXPECT_EQ((vector<int32_t>{9, 14, 19}), read_vector<int32_t>(result));
}