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