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openvino/ngraph/test/backend/binary_convolution.in.cpp

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Align copyright notice in cpp and cmake source files (CVS-51320) (#4950)
2021-03-25 02:40:09 +03:00
// Copyright (C) 2018-2021 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
BinaryConvolution Reference Implementation (#4278) * Add BinaryConvolution unit tests. * Changed types to u1. * Add BIN precision handling in TestCase class. * Refactored validate and infer types to enhance dynamic shape inference * Add type_prop test to cover invalid op cases and dynamic shapes * Fix style * Disable check for float type of data batch input * Add type_prop test for incompatible input channels in inputs * Disable backend unit tests * Fix style * Add reference implementation * Add backend tests * Add single layer tests * Add check for float element type of batch data input * Refactor backend test cases to compare with regular convolution * Add serialization tests * Clean up * Add 1D and 3D tests into op_eval * Changes in reference implementation to improve readability * Add ticket information for todo tasks * Fix implementation misbehavior for filter channels * Add backend unit tests to cover strides, dilations, padding, channels and batches * Add end of line into files * Change name of type_prop unit tests * Simplified lambda to get spatial dimensions of filters * Add comment to support filters input as Parameter * Add namespace details for BinaryConvolution utility functions * Address review comments Co-authored-by: jdanieck <jozef.daniecki@intel.com>
2021-03-09 20:58:25 +01:00
//
#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/test_control.hpp"
using namespace std;
using namespace ngraph;
static string s_manifest = "${MANIFEST}";
template <typename T_IN, typename T_KERN>
static void BinaryConvolutionTest(const std::vector<T_IN>& inputs,
const Shape inputs_shape,
const std::vector<T_KERN>& filters,
const Shape filters_shape,
const std::vector<T_IN>& outputs,
const Shape outputs_shape,
const Strides& strides,
const CoordinateDiff& padding,
const Strides& dilations,
const float pad_value = 0.0f)
{
const CoordinateDiff pads_begin{padding};
const CoordinateDiff pads_end{padding};
const op::PadType auto_pad{op::PadType::EXPLICIT};
auto inputs_param = make_shared<op::Parameter>(element::from<T_IN>(), inputs_shape);
auto filters_const = make_shared<op::Constant>(element::u1, filters_shape, &filters[0]);
auto bin_conv = make_shared<op::v1::BinaryConvolution>(
inputs_param,
filters_const,
strides,
pads_begin,
pads_end,
dilations,
op::v1::BinaryConvolution::BinaryConvolutionMode::XNOR_POPCOUNT,
pad_value,
auto_pad);
auto f = make_shared<Function>(bin_conv, ParameterVector{inputs_param});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
auto input_tensor = backend->create_tensor(element::from<T_IN>(), inputs_shape);
copy_data(input_tensor, inputs);
auto result = backend->create_tensor(element::from<T_IN>(), outputs_shape);
auto handle = backend->compile(f);
handle->call_with_validate({result}, {input_tensor});
EXPECT_TRUE(test::all_close_f((outputs), read_vector<T_IN>(result), MIN_FLOAT_TOLERANCE_BITS));
}
template <typename T_IN>
static void ConvolutionTest(const std::vector<T_IN>& inputs,
const Shape inputs_shape,
const std::vector<T_IN>& filters,
const Shape filters_shape,
const std::vector<T_IN>& outputs,
const Shape outputs_shape,
const Strides& strides,
const CoordinateDiff& padding,
const Strides& dilations)
{
const CoordinateDiff pads_begin{padding};
const CoordinateDiff pads_end{padding};
const op::PadType auto_pad{op::PadType::EXPLICIT};
auto inputs_param = make_shared<op::Parameter>(element::from<T_IN>(), inputs_shape);
auto filters_param = make_shared<op::Parameter>(element::from<T_IN>(), filters_shape);
auto conv = make_shared<op::v1::Convolution>(
inputs_param, filters_param, strides, pads_begin, pads_end, dilations, auto_pad);
auto f = make_shared<Function>(conv, ParameterVector{inputs_param, filters_param});
auto backend = runtime::Backend::create("${BACKEND_NAME}");
auto input_tensor = backend->create_tensor(element::from<T_IN>(), inputs_shape);
copy_data(input_tensor, inputs);
auto filters_tensor = backend->create_tensor(element::from<T_IN>(), filters_shape);
copy_data(filters_tensor, filters);
auto result = backend->create_tensor(element::from<T_IN>(), outputs_shape);
auto handle = backend->compile(f);
handle->call_with_validate({result}, {input_tensor, filters_tensor});
EXPECT_TRUE(test::all_close_f((outputs), read_vector<T_IN>(result), MIN_FLOAT_TOLERANCE_BITS));
}
// clang-format off
// --------------------- 2D convolution ------------------------------------------
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_1batch_1channel)
{
const Strides strides{1, 1};
const CoordinateDiff padding{0, 0};
const Strides dilations{1, 1};
const Shape inputs_shape{1, 1, 4, 4};
const std::vector<float> inputs_conv{1.0f, -1.0f, -1.0f, 1.0f,
1.0f, 1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, -1.0f, 1.0f,
1.0f, -1.0f, 1.0f, 1.0f};
const std::vector<float> inputs_bin_conv{1.0f, 0.0f, 0.0f, 1.0f,
1.0f, 1.0f, 0.0f, 0.0f,
0.0f, 0.0f, 0.0f, 1.0f,
1.0f, 0.0f, 1.0f, 1.0f};
const Shape filters_shape{1, 1, 3, 3};
const std::vector<float> filters_conv{1.0f, -1.0f, 1.0f,
-1.0f, 1.0f, -1.0f,
1.0f, -1.0f, 1.0f};
const std::vector<uint8_t> filters_bin_conv{0xAA, 0x80}; // 10101010 10000000
const Shape outputs_shape{1, 1, 2, 2};
const std::vector<float> outputs{1.0f, 1.0f,
3.0f, -1.0f};
BinaryConvolutionTest(
inputs_bin_conv,
inputs_shape,
filters_bin_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding,
dilations);
ConvolutionTest(
inputs_conv,
inputs_shape,
filters_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding,
dilations);
}
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_1batch_1channel_padding_pad_val_0)
{
const Strides strides{1, 1};
const Strides dilations{1, 1};
const CoordinateDiff padding_conv{0, 0};
const Shape inputs_conv_shape{1, 1, 6, 6};
const std::vector<float> inputs_conv{-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f,
-1.0f, 1.0f, -1.0f, -1.0f, 1.0f, -1.0f,
-1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, -1.0f, -1.0f, 1.0f, -1.0f,
-1.0f, 1.0f, -1.0f, 1.0f, 1.0f, -1.0f,
-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f};
const CoordinateDiff padding_bin_conv{1, 1};
const Shape inputs_bin_conv_shape{1, 1, 4, 4};
const std::vector<float> inputs_bin_conv{1.0f, 0.0f, 0.0f, 1.0f,
1.0f, 1.0f, 0.0f, 0.0f,
0.0f, 0.0f, 0.0f, 1.0f,
1.0f, 0.0f, 1.0f, 1.0f};
const Shape filters_shape{1, 1, 3, 3};
const std::vector<float> filters_conv{1.0f, -1.0f, 1.0f,
-1.0f, 1.0f, -1.0f,
1.0f, -1.0f, 1.0f};
const std::vector<uint8_t> filters_bin_conv{0xAA, 0x80}; // 10101010 10000000
const Shape outputs_shape{1, 1, 4, 4};
const std::vector<float> outputs{1.0f, -3.0f, -1.0f, 1.0f,
-3.0f, 1.0f, 1.0f, -5.0f,
-3.0f, 3.0f, -1.0f, 1.0f,
1.0f, -5.0f, 1.0f, -3.0f};
BinaryConvolutionTest(
inputs_bin_conv,
inputs_bin_conv_shape,
filters_bin_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding_bin_conv,
dilations);
ConvolutionTest(
inputs_conv,
inputs_conv_shape,
filters_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding_conv,
dilations);
}
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_1batch_1channel_padding_pad_val_1)
{
const Strides strides{1, 1};
const Strides dilations{1, 1};
const float pad_value = 1.0f;
const CoordinateDiff padding_conv{0, 0};
const Shape inputs_conv_shape{1, 1, 6, 6};
const std::vector<float> inputs_conv{1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
1.0f, 1.0f, -1.0f, -1.0f, 1.0f, 1.0f,
1.0f, 1.0f, 1.0f, -1.0f, -1.0f, 1.0f,
1.0f, -1.0f, -1.0f, -1.0f, 1.0f, 1.0f,
1.0f, 1.0f, -1.0f, 1.0f, 1.0f, 1.0f,
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f};
const CoordinateDiff padding_bin_conv{1, 1};
const Shape inputs_bin_conv_shape{1, 1, 4, 4};
const std::vector<float> inputs_bin_conv{1.0f, 0.0f, 0.0f, 1.0f,
1.0f, 1.0f, 0.0f, 0.0f,
0.0f, 0.0f, 0.0f, 1.0f,
1.0f, 0.0f, 1.0f, 1.0f};
const Shape filters_shape{1, 1, 3, 3};
const std::vector<float> filters_conv{1.0f, -1.0f, 1.0f,
-1.0f, 1.0f, -1.0f,
1.0f, -1.0f, 1.0f};
const std::vector<uint8_t> filters_bin_conv{0xAA, 0x80}; // 10101010 10000000
const Shape outputs_shape{1, 1, 4, 4};
const std::vector<float> outputs{3.0f, -1.0f, 1.0f, 3.0f,
-1.0f, 1.0f, 1.0f, -3.0f,
-1.0f, 3.0f, -1.0f, 3.0f,
3.0f, -3.0f, 3.0f, -1.0f,};
BinaryConvolutionTest(
inputs_bin_conv,
inputs_bin_conv_shape,
filters_bin_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding_bin_conv,
dilations,
pad_value);
ConvolutionTest(
inputs_conv,
inputs_conv_shape,
filters_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding_conv,
dilations);
}
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_1batch_1channel_stride)
{
const Strides strides{2, 2};
const CoordinateDiff padding{0, 0};
const Strides dilations{1, 1};
const Shape inputs_shape{1, 1, 5, 5};
const std::vector<float> inputs_conv{-1.0f, 1.0f, 1.0f, -1.0f, 1.0f,
1.0f, 1.0f, -1.0f, 1.0f, -1.0f,
-1.0f, -1.0f, 1.0f, -1.0f, 1.0f,
1.0f, 1.0f, -1.0f, 1.0f, -1.0f,
-1.0f, -1.0f, 1.0f, 1.0f, 1.0f};
const std::vector<float> inputs_bin_conv{0.0f, 1.0f, 1.0f, 0.0f, 1.0f,
1.0f, 1.0f, 0.0f, 1.0f, 0.0f,
0.0f, 0.0f, 1.0f, 0.0f, 1.0f,
1.0f, 1.0f, 0.0f, 1.0f, 0.0f,
0.0f, 0.0f, 1.0f, 1.0f, 1.0f};
const Shape filters_shape{1, 1, 3, 3};
const std::vector<float> filters_conv{-1.0f, -1.0f, 1.0f,
-1.0f, 1.0f, 1.0f,
1.0f, -1.0f, -1.0f};
const std::vector<uint8_t> filters_bin_conv{0x2E, 0x00}; // 00101110 00000000
const Shape outputs_shape{1, 1, 2, 2};
const std::vector<float> outputs{-1.0f, 3.0f,
1.0f, 1.0f};
BinaryConvolutionTest(
inputs_bin_conv,
inputs_shape,
filters_bin_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding,
dilations);
ConvolutionTest(
inputs_conv,
inputs_shape,
filters_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding,
dilations);
}
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_1batch_1channel_dilation)
{
const Strides strides{1, 1};
const CoordinateDiff padding{0, 0};
const Strides dilations{2, 2};
const Shape inputs_shape{1, 1, 7, 7};
const std::vector<float> inputs_conv{1.0f, 1.0f, -1.0f, -1.0f, -1.0f, 1.0f, -1.0f,
-1.0f, -1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f,
1.0f, 1.0f, 1.0f, 1.0f, -1.0f, 1.0f, 1.0f,
-1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f, -1.0f,
-1.0f, 1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f,
1.0f, -1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f,
1.0f, 1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f};
const std::vector<float> inputs_bin_conv{1.0f, 1.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f,
0.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f,
1.0f, 1.0f, 1.0f, 1.0f, 0.0f, 1.0f, 1.0f,
0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f,
0.0f, 1.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f,
1.0f, 0.0f, 1.0f, 1.0f, 0.0f, 0.0f, 0.0f,
1.0f, 1.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f};
const Shape filters_shape{1, 1, 3, 3};
const std::vector<float> filters_conv{-1.0f, 1.0f, 1.0f,
-1.0f, 1.0f, -1.0f,
1.0f, 1.0f, -1.0f};
const std::vector<uint8_t> filters_bin_conv{0x6B, 0x00}; // 01101011 00000000
const Shape outputs_shape{1, 1, 3, 3};
const std::vector<float> outputs{-5.0f, -3.0f, -5.0f,
5.0f, 1.0f, 3.0f,
-1.0f, -1.0f, 3.0f};
BinaryConvolutionTest(
inputs_bin_conv,
inputs_shape,
filters_bin_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding,
dilations);
ConvolutionTest(
inputs_conv,
inputs_shape,
filters_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding,
dilations);
}
NGRAPH_TEST(${BACKEND_NAME},
bin_convolution_2D_1batch_1channel_strides_dilation_padding_pad_val_0)
{
const Strides strides{2, 2};
const Strides dilations{2, 2};
const CoordinateDiff padding_conv{0, 0};
const Shape inputs_conv_shape{1, 1, 11, 11};
const std::vector<float> inputs_conv{
-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f,-1.0f, -1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f, 1.0f, -1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, -1.0f, -1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, 1.0f, 1.0f, 1.0f, 1.0f, -1.0f, 1.0f, 1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, -1.0f, 1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, 1.0f, -1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, 1.0f, 1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f, -1.0f};
const CoordinateDiff padding_bin_conv{2, 2};
const Shape inputs_bin_conv_shape{1, 1, 7, 7};
const std::vector<float> inputs_bin_conv{1.0f, 1.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f,
0.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f,
1.0f, 1.0f, 1.0f, 1.0f, 0.0f, 1.0f, 1.0f,
0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f,
0.0f, 1.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f,
1.0f, 0.0f, 1.0f, 1.0f, 0.0f, 0.0f, 0.0f,
1.0f, 1.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f};
const Shape filters_shape{1, 1, 3, 3};
const std::vector<float> filters_conv{-1.0f, 1.0f, 1.0f,
-1.0f, 1.0f, -1.0f,
1.0f, 1.0f, -1.0f};
const std::vector<uint8_t> filters_bin_conv{0x6B, 0x00}; // 01101011 00000000
const Shape outputs_shape{1, 1, 4, 4};
const std::vector<float> outputs{1.0f, 1.0f, -1.0f, 1.0f,
1.0f, -5.0f, -5.0f, 5.0f,
3.0f, -1.0f, 3.0f, 3.0f,
-1.0f, -1.0f, 3.0f, -3.0f};
BinaryConvolutionTest(
inputs_bin_conv,
inputs_bin_conv_shape,
filters_bin_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding_bin_conv,
dilations);
ConvolutionTest(
inputs_conv,
inputs_conv_shape,
filters_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding_conv,
dilations);
}
NGRAPH_TEST(${BACKEND_NAME},
bin_convolution_2D_1batch_1channel_strides_dilation_padding_pad_val_1)
{
const Strides strides{2, 2};
const Strides dilations{2, 2};
const float pad_value = 1.0f;
const CoordinateDiff padding_conv{0, 0};
const Shape inputs_conv_shape{1, 1, 11, 11};
const std::vector<float> inputs_conv{
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
1.0f, 1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f, 1.0f, -1.0f, 1.0f, 1.0f,
1.0f, 1.0f, -1.0f, -1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f, 1.0f, 1.0f,
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, -1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
1.0f, 1.0f, -1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f, -1.0f, 1.0f, 1.0f,
1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
1.0f, 1.0f, 1.0f, -1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f, 1.0f, 1.0f,
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, -1.0f, 1.0f, -1.0f, -1.0f, 1.0f, 1.0f,
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f};
const CoordinateDiff padding_bin_conv{2, 2};
const Shape inputs_bin_conv_shape{1, 1, 7, 7};
const std::vector<float> inputs_bin_conv{1.0f, 1.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f,
0.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f,
1.0f, 1.0f, 1.0f, 1.0f, 0.0f, 1.0f, 1.0f,
0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f,
0.0f, 1.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f,
1.0f, 0.0f, 1.0f, 1.0f, 0.0f, 0.0f, 0.0f,
1.0f, 1.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f};
const Shape filters_shape{1, 1, 3, 3};
const std::vector<float> filters_conv{-1.0f, 1.0f, 1.0f,
-1.0f, 1.0f, -1.0f,
1.0f, 1.0f, -1.0f};
const std::vector<uint8_t> filters_bin_conv{0x6B, 0x00}; // 01101011 00000000
const Shape outputs_shape{1, 1, 4, 4};
const std::vector<float> outputs{3.0f, 3.0f, 1.0f, -1.0f,
-1.0f, -5.0f, -5.0f, 3.0f,
1.0f, -1.0f, 3.0f, 1.0f,
-3.0f, 1.0f, 5.0f, -1.0f};
BinaryConvolutionTest(
inputs_bin_conv,
inputs_bin_conv_shape,
filters_bin_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding_bin_conv,
dilations,
pad_value);
ConvolutionTest(
inputs_conv,
inputs_conv_shape,
filters_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding_conv,
dilations);
}
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_1batch_2channel)
{
const Strides strides{1, 1};
const CoordinateDiff padding{0, 0};
const Strides dilations{1, 1};
const Shape inputs_shape{1, 2, 4, 4};
const std::vector<float> inputs_conv{
// channel 1
1.0f, -1.0f, -1.0f, 1.0f,
1.0f, 1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, -1.0f, 1.0f,
1.0f, -1.0f, 1.0f, 1.0f,
// channel 2
-1.0f, 1.0f, 1.0f, -1.0f,
-1.0f, -1.0f, 1.0f, 1.0f,
1.0f, 1.0f, 1.0f, -1.0f,
-1.0f, 1.0f, -1.0f, -1.0f};
const std::vector<float> inputs_bin_conv{
// channel 1
1.0f, 0.0f, 0.0f, 1.0f,
1.0f, 1.0f, 0.0f, 0.0f,
0.0f, 0.0f, 0.0f, 1.0f,
1.0f, 0.0f, 1.0f, 1.0f,
// channel 2
0.0f, 1.0f, 1.0f, 0.0f,
0.0f, 0.0f, 1.0f, 1.0f,
1.0f, 1.0f, 1.0f, 0.0f,
0.0f, 1.0f, 0.0f, 0.0f};
const Shape filters_shape{1, 2, 3, 3};
const std::vector<float> filters_conv{
// channel 1
1.0f, -1.0f, 1.0f,
-1.0f, 1.0f, -1.0f,
1.0f, -1.0f, 1.0f,
// channel 2
-1.0f, 1.0f, -1.0f,
1.0f, -1.0f, 1.0f,
-1.0f, 1.0f, -1.0f};
// 10101010 10101010 10000000
const std::vector<uint8_t> filters_bin_conv{0xAA, 0xAA, 0x80};
const Shape outputs_shape{1, 1, 2, 2};
const std::vector<float> outputs{2.0f, 2.0f,
6.0f, -2.0f};
BinaryConvolutionTest(
inputs_bin_conv,
inputs_shape,
filters_bin_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding,
dilations);
ConvolutionTest(
inputs_conv,
inputs_shape,
filters_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding,
dilations);
}
NGRAPH_TEST(${BACKEND_NAME}, bin_convolution_2D_2batch_1channel)
{
const Strides strides{1, 1};
const CoordinateDiff padding{0, 0};
const Strides dilations{1, 1};
const Shape inputs_shape{2, 1, 4, 4};
const std::vector<float> inputs_conv{
// batch 1
1.0f, -1.0f, -1.0f, 1.0f,
1.0f, 1.0f, -1.0f, -1.0f,
-1.0f, -1.0f, -1.0f, 1.0f,
1.0f, -1.0f, 1.0f, 1.0f,
// batch 2
-1.0f, -1.0f, -1.0f, -1.0f,
1.0f, 1.0f, 1.0f, -1.0f,
1.0f, 1.0f, -1.0f, 1.0f,
1.0f, -1.0f, 1.0f, -1.0f};
const std::vector<float> inputs_bin_conv{
// batch 1
1.0f, 0.0f, 0.0f, 1.0f,
1.0f, 1.0f, 0.0f, 0.0f,
0.0f, 0.0f, 0.0f, 1.0f,
1.0f, 0.0f, 1.0f, 1.0f,
// batch 2
0.0f, 0.0f, 0.0f, 0.0f,
1.0f, 1.0f, 1.0f, 0.0f,
1.0f, 1.0f, 0.0f, 1.0f,
1.0f, 0.0f, 1.0f, 0.0f};
const Shape filters_shape{1, 1, 3, 3};
const std::vector<float> filters_conv{1.0f, -1.0f, 1.0f,
-1.0f, 1.0f, -1.0f,
1.0f, -1.0f, 1.0f};
const std::vector<uint8_t> filters_bin_conv{0xAA, 0x80}; // 10101010 10000000
const Shape outputs_shape{2, 1, 2, 2};
const std::vector<float> outputs{
// batch 1
1.0f, 1.0f,
3.0f, -1.0f,
// batch 2
-3.0f, 3.0f,
5.0f, -7.0f};
BinaryConvolutionTest(
inputs_bin_conv,
inputs_shape,
filters_bin_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding,
dilations);
ConvolutionTest(
inputs_conv,
inputs_shape,
filters_conv,
filters_shape,
outputs,
outputs_shape,
strides,
padding,
dilations);
}
// clang-format on
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