unplugged-system/external/XNNPACK/test/convolution-test-helpers.h

225 lines
6.4 KiB
C++

// Copyright 2022 Google LLC
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.
#pragma once
#include <cstdint>
#include <cstddef>
#include <vector>
namespace xnnpack {
void compute_convolution_qs8_reference_results(
size_t batch_size,
size_t output_height,
size_t output_width,
size_t input_height,
size_t input_width,
size_t input_padding_top,
size_t input_padding_right,
size_t input_padding_bottom,
size_t input_padding_left,
size_t kernel_height,
size_t kernel_width,
size_t subsampling_height,
size_t subsampling_width,
size_t dilation_height,
size_t dilation_width,
size_t groups,
size_t group_input_channels,
size_t group_output_channels,
size_t input_channel_stride,
int8_t input_zero_point,
const std::vector<int8_t>& input,
const std::vector<int8_t>& filter,
std::vector<int32_t>& accumulators,
bool has_bias,
const std::vector<int32_t>& bias);
void compute_convolution_qs8_reference_results(
size_t batch_size,
size_t output_height,
size_t output_width,
size_t input_height,
size_t input_width,
size_t input_padding_top,
size_t input_padding_right,
size_t input_padding_bottom,
size_t input_padding_left,
size_t kernel_height,
size_t kernel_width,
size_t subsampling_height,
size_t subsampling_width,
size_t dilation_height,
size_t dilation_width,
size_t groups,
size_t group_input_channels,
size_t group_output_channels,
int8_t input_zero_point,
const std::vector<int8_t>& input,
const std::vector<int8_t>& filter,
std::vector<int32_t>& accumulators,
bool has_bias,
const std::vector<int32_t>& bias);
void compute_convolution_qu8_reference_results(
size_t batch_size,
size_t output_height,
size_t output_width,
size_t input_height,
size_t input_width,
size_t input_padding_top,
size_t input_padding_right,
size_t input_padding_bottom,
size_t input_padding_left,
size_t kernel_height,
size_t kernel_width,
size_t subsampling_height,
size_t subsampling_width,
size_t dilation_height,
size_t dilation_width,
size_t groups,
size_t group_input_channels,
size_t group_output_channels,
uint8_t input_zero_point,
uint8_t kernel_zero_point,
const std::vector<uint8_t>& input,
const std::vector<uint8_t>& filter,
std::vector<int32_t>& accumulators,
bool has_bias,
const std::vector<int32_t>& bias);
void compute_convolution_qu8_reference_results(
size_t batch_size,
size_t output_height,
size_t output_width,
size_t input_height,
size_t input_width,
size_t input_padding_top,
size_t input_padding_right,
size_t input_padding_bottom,
size_t input_padding_left,
size_t kernel_height,
size_t kernel_width,
size_t subsampling_height,
size_t subsampling_width,
size_t dilation_height,
size_t dilation_width,
size_t groups,
size_t group_input_channels,
size_t group_output_channels,
size_t input_channel_stride,
uint8_t input_zero_point,
uint8_t kernel_zero_point,
const std::vector<uint8_t>& input,
const std::vector<uint8_t>& filter,
std::vector<int32_t>& accumulators,
bool has_bias,
const std::vector<int32_t>& bias);
void compute_depthwise_convolution_qs8_reference_results(
size_t batch_size,
size_t output_height,
size_t output_width,
size_t input_height,
size_t input_width,
size_t input_padding_top,
size_t input_padding_right,
size_t input_padding_bottom,
size_t input_padding_left,
size_t kernel_height,
size_t kernel_width,
size_t subsampling_height,
size_t subsampling_width,
size_t dilation_height,
size_t dilation_width,
size_t input_channels,
size_t depth_multiplier,
size_t input_channel_stride,
int8_t input_zero_point,
const std::vector<int8_t>& input,
const std::vector<int8_t>& filter,
std::vector<int32_t>& accumulators,
bool has_bias,
const std::vector<int32_t>& bias);
void compute_depthwise_convolution_qs8_reference_results(
size_t batch_size,
size_t output_height,
size_t output_width,
size_t input_height,
size_t input_width,
size_t input_padding_top,
size_t input_padding_right,
size_t input_padding_bottom,
size_t input_padding_left,
size_t kernel_height,
size_t kernel_width,
size_t subsampling_height,
size_t subsampling_width,
size_t dilation_height,
size_t dilation_width,
size_t input_channels,
size_t depth_multiplier,
int8_t input_zero_point,
const std::vector<int8_t>& input,
const std::vector<int8_t>& filter,
std::vector<int32_t>& accumulators,
bool has_bias,
const std::vector<int32_t>& bias);
void compute_depthwise_convolution_qu8_reference_results(
size_t batch_size,
size_t output_height,
size_t output_width,
size_t input_height,
size_t input_width,
size_t input_padding_top,
size_t input_padding_right,
size_t input_padding_bottom,
size_t input_padding_left,
size_t kernel_height,
size_t kernel_width,
size_t subsampling_height,
size_t subsampling_width,
size_t dilation_height,
size_t dilation_width,
size_t input_channels,
size_t depth_multiplier,
size_t input_channel_stride,
uint8_t input_zero_point,
uint8_t kernel_zero_point,
const std::vector<uint8_t>& input,
const std::vector<uint8_t>& filter,
std::vector<int32_t>& accumulators,
bool has_bias,
const std::vector<int32_t>& bias);
void compute_depthwise_convolution_qu8_reference_results(
size_t batch_size,
size_t output_height,
size_t output_width,
size_t input_height,
size_t input_width,
size_t input_padding_top,
size_t input_padding_right,
size_t input_padding_bottom,
size_t input_padding_left,
size_t kernel_height,
size_t kernel_width,
size_t subsampling_height,
size_t subsampling_width,
size_t dilation_height,
size_t dilation_width,
size_t input_channels,
size_t depth_multiplier,
uint8_t input_zero_point,
uint8_t kernel_zero_point,
const std::vector<uint8_t>& input,
const std::vector<uint8_t>& filter,
std::vector<int32_t>& accumulators,
bool has_bias,
const std::vector<int32_t>& bias);
} // namespace xnnpack