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/*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
* 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 "fbgemm/FbgemmBuild.h"
namespace fbgemm {
class FBGEMM_API PackedDepthWiseConvMatrix {
public:
/**
* @params K the number of channels (same as the number of groups because
* depth-wise convolution has one input/output channel per group)
* @params kernel_prod the product of all kernels. For example, kernel_prod =
* 9 for 3x3 conv, and 27 for 3x3x3 conv.
* @param smat the source unpacked weight in GRS layout
*/
PackedDepthWiseConvMatrix(int K, int kernel_prod, const std::int8_t* smat);
virtual ~PackedDepthWiseConvMatrix();
const std::int8_t* PackedMat() const {
return pmat_;
}
int GetKernelProduct() const {
return kernel_prod_;
}
/**
* @brief Unpacks pmat_ into unpack_data.
* Used for recovering the weight matrix into the original format
*/
void unpack(std::int8_t* unpacked_data);
/**
* @brief returns the index into pmat_ given the row and column for smat
*/
int addr(int r, int c);
private:
const int K_; /**< the number of channels */
const int kernel_prod_; /** the product of all kernel dims */
std::int8_t* pmat_; /** packed weight */
}; // PackedDepthWiseConvMatrix
class FBGEMM_API Packed3x3ConvMatrix : public PackedDepthWiseConvMatrix {
public:
Packed3x3ConvMatrix(int K, const std::int8_t* smat)
: PackedDepthWiseConvMatrix(K, 3 * 3, smat) {}
};
class FBGEMM_API Packed3x3x3ConvMatrix : public PackedDepthWiseConvMatrix {
public:
Packed3x3x3ConvMatrix(int K, const std::int8_t* smat)
: PackedDepthWiseConvMatrix(K, 3 * 3 * 3, smat) {}
};
/** To be removed. Keeping it just to make sure we don't change C2 files and
* fbgemm files in a single diff
*
*/
FBGEMM_API void depthwise_3x3_pad_1(
int N,
int H,
int W,
int K,
int stride_h,
int stride_w,
std::int32_t A_zero_point,
const std::uint8_t* A,
std::int32_t B_zero_point,
const PackedDepthWiseConvMatrix& Bp,
float C_multiplier,
std::int32_t C_zero_point,
std::uint8_t* C,
const std::int32_t* col_offsets,
const std::int32_t* bias,
bool fuse_relu = false,
int thread_id = 0,
int num_threads = 1);
/**
* Depth-wise 3x3 convolution with pad=1 and stride=1 and K a multiple of 8
* This version is fused with requantization.
*
* @col_offsets nullptr if col_offsets are folded into bias
* @act_times_w_scale Only used if BIAS_TYPE is float, i.e., bias is
* unquantized.
*/
template <typename BIAS_TYPE = std::int32_t>
FBGEMM_API void depthwise_3x3_pad_1(
int N,
int H,
int W,
int K,
int stride_h,
int stride_w,
std::int32_t A_zero_point,
const std::uint8_t* A,
std::int32_t B_zero_point,
const PackedDepthWiseConvMatrix& Bp,
float C_multiplier,
std::int32_t C_zero_point,
std::uint8_t* C,
const std::int32_t* col_offsets,
const BIAS_TYPE* bias,
bool fuse_relu = false,
float act_times_w_scale = 1.0f,
int thread_id = 0,
int num_threads = 1);
/**
* Depth-wise 3x3 convolution with pad=1 and K a multiple of 8, fused with
* requantization, and using per-channel quantization.
*
* @col_offsets nullptr if col_offsets are folded into bias
*/
template <typename BIAS_TYPE = std::int32_t>
FBGEMM_API void depthwise_3x3_per_channel_quantization_pad_1(
int N,
int H,
int W,
int K,
int stride_h,
int stride_w,
std::int32_t A_zero_point,
const std::uint8_t* A,
const std::int32_t* B_zero_point,
const PackedDepthWiseConvMatrix& Bp,
const float* C_multiplier,
std::int32_t C_zero_point,
std::uint8_t* C,
const std::int32_t* col_offsets,
const BIAS_TYPE* bias,
bool fuse_relu = false,
const float* act_times_w_scale = nullptr,
int thread_id = 0,
int num_threads = 1);
/** To be removed. Keeping it just to make sure we don't change C2 files and
* fbgemm files in a single diff
*/
FBGEMM_API void depthwise_3x3_per_channel_quantization_pad_1(
int N,
int H,
int W,
int K,
int stride_h,
int stride_w,
std::int32_t A_zero_point,
const std::uint8_t* A,
const std::int32_t* B_zero_point,
const PackedDepthWiseConvMatrix& Bp,
const float* C_multiplier,
std::int32_t C_zero_point,
std::uint8_t* C,
const std::int32_t* col_offsets,
const std::int32_t* bias,
bool fuse_relu = false,
int thread_id = 0,
int num_threads = 1);
/** To be removed. Keeping it just to make sure we don't change C2 files and
* fbgemm files in a single diff
*
*/
FBGEMM_API void depthwise_3x3x3_pad_1(
int N,
int T,
int H,
int W,
int K,
int stride_t,
int stride_h,
int stride_w,
std::int32_t A_zero_point,
const std::uint8_t* A,
std::int32_t B_zero_point,
const PackedDepthWiseConvMatrix& Bp,
float C_multiplier,
std::int32_t C_zero_point,
std::uint8_t* C,
const std::int32_t* col_offsets,
const std::int32_t* bias,
bool fuse_relu = false,
int thread_id = 0,
int num_threads = 1);
/**
* @col_offsets nullptr if col_offsets are folded into bias
*/
template <typename BIAS_TYPE = std::int32_t>
FBGEMM_API void depthwise_3x3x3_pad_1(
int N,
int T,
int H,
int W,
int K,
int stride_t,
int stride_h,
int stride_w,
std::int32_t A_zero_point,
const std::uint8_t* A,
std::int32_t B_zero_point,
const PackedDepthWiseConvMatrix& Bp,
float C_multiplier,
std::int32_t C_zero_point,
std::uint8_t* C,
const std::int32_t* col_offsets,
const BIAS_TYPE* bias,
bool fuse_relu = false,
float act_times_w_scale = 1.0f,
int thread_id = 0,
int num_threads = 1);
/** To be removed. Keeping it just to make sure we don't change C2 files and
* fbgemm files in a single diff
*
*/
FBGEMM_API void depthwise_3x3x3_per_channel_quantization_pad_1(
int N,
int T,
int H,
int W,
int K,
int stride_t,
int stride_h,
int stride_w,
std::int32_t A_zero_point,
const std::uint8_t* A,
const std::int32_t* B_zero_point,
const PackedDepthWiseConvMatrix& Bp,
const float* C_multiplier,
std::int32_t C_zero_point,
std::uint8_t* C,
const std::int32_t* col_offsets,
const std::int32_t* bias,
bool fuse_relu = false,
int thread_id = 0,
int num_threads = 1);
/**
* @col_offsets nullptr if col_offsets are folded into bias
*/
template <typename BIAS_TYPE = std::int32_t>
FBGEMM_API void depthwise_3x3x3_per_channel_quantization_pad_1(
int N,
int T,
int H,
int W,
int K,
int stride_t,
int stride_h,
int stride_w,
std::int32_t A_zero_point,
const std::uint8_t* A,
const std::int32_t* B_zero_point,
const PackedDepthWiseConvMatrix& Bp,
const float* C_multiplier,
std::int32_t C_zero_point,
std::uint8_t* C,
const std::int32_t* col_offsets,
const BIAS_TYPE* bias,
bool fuse_relu = false,
const float* act_times_w_scale = nullptr,
int thread_id = 0,
int num_threads = 1);
} // namespace fbgemm
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