MNN/source/backend/cpu/compute/ConvOpt.h

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//
// ConvOpt.h
// MNN
//
// Created by MNN on 2018/07/16.
// Copyright © 2018, Alibaba Group Holding Limited
//
#ifndef ConvOpt_h
#define ConvOpt_h
#include <stdint.h>
#include <stdio.h>
#ifdef __cplusplus
extern "C" {
#endif
#define CONVOLUVTION_RUN_BASIC(l, t, r, b, TYPE, alpha) \
for (dy = t; dy < b; ++dy) { \
int srcStartY = dy * strideY - padY; \
float* dst_y = dst_z + width * 4 * dy; \
const TYPE* src_dy = srcOrigin + srcStartY * src_width * 4; \
int sfy = ALIMAX(0, (UP_DIV(-srcStartY, dilateY))); \
int efy = ALIMIN(kernel_height, UP_DIV(src_height - srcStartY, dilateY)); \
for (dx = l; dx < r; ++dx) { \
int srcStartX = dx * strideX - padX; \
const TYPE* src_dx = src_dy + 4 * srcStartX; \
float* dst_x = dst_y + 4 * dx; \
int sfx = ALIMAX(0, (UP_DIV(-srcStartX, dilateX))); \
int efx = ALIMIN(kernel_width, UP_DIV(src_width - srcStartX, dilateX)); \
const TYPE* src_unit = src_dx + (sfx * dilateX_step + sfy * dilateY_step); \
const TYPE* weight_start = weight_dz + (16 * sfx + weight_sy_step * sfy); \
MNNConvSlideWindowBorder(dst_x, src_unit, weight_start, src_depth_quad, src_z_step, efx - sfx, efy - sfy, \
weight_sy_step, weight_sz_step, dilateX_step, dilateY_step, alpha); \
} \
}
void MNNConvRunForUnitDepthWise(float* dst, const float* src, const float* weight, size_t fw, size_t fh,
size_t weight_y_step, size_t dilateX_step, size_t dilateY_step);
void MNNConvRunForLineDepthwise(float* dst, const float* src, const float* weight, size_t width, size_t src_w_setup,
size_t fw, size_t fh, size_t dilateX_step, size_t dilateY_step, size_t height,
size_t srcHStep, size_t dstHStep);
void MNNDeconvRunForUnitDepthWise(const float* dst, float* src, const float* weight, size_t fw, size_t fh,
size_t weight_y_step, size_t dilateX_step, size_t dilateY_step);
void MNNDeconvRunForLineDepthwise(const float* dst, float* src, const float* weight, size_t width, size_t src_w_setup,
size_t fw, size_t fh, size_t dilateX_step, size_t dilateY_step);
void MNNGemmFloatUnit_4(float* dst, const float* src, const float* weight, size_t src_depth_quad, size_t dst_step,
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size_t dst_depth_quad, size_t weight_depth_offset);
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void MNNGemmFloatOne_4(float* dst, const float* src, const float* weight, size_t src_depth_quad, size_t dst_step,
size_t dst_depth_quad, size_t weight_depth_offset);
void MNNGemmFloatCommon_4(float* dst, const float* src, const float* weight, size_t src_depth_quad, size_t dst_step,
size_t dst_depth_quad, size_t width, size_t weight_depth_offset);
void MNNMatrixAdd(float* C, const float* A, const float* B, size_t widthC4, size_t cStride, size_t aStride,
size_t bStride, size_t height);
void MNNMatrixSub(float* C, const float* A, const float* B, size_t widthC4, size_t cStride, size_t aStride,
size_t bStride, size_t height);
void MNNMatrixMax(float* C, const float* A, const float* B, size_t widthC4, size_t cStride, size_t aStride,
size_t bStride, size_t height);
void MNNMatrixProd(float* C, const float* A, const float* B, size_t widthC4, size_t cStride, size_t aStride,
size_t bStride, size_t height);
- build: - unify schema building in core and converter; - add more build script for android; - add linux build script for python; - ops impl: - add floor mod support in binary; - use eltwise impl in add/max/sub/mul binary for optimization; - remove fake double support in cast; - fix 5d support for concat; - add adjX and adjY support for batch matmul; - optimize conv2d back prop filter; - add pad mode support for conv3d; - fix bug in conv2d & conv depthwise with very small feature map; - optimize binary without broacast; - add data types support for gather; - add gather ND support; - use uint8 data type in gather v2; - add transpose support for matmul; - add matrix band part; - add dim != 4 support for padding, reshape & tensor convert; - add pad type support for pool3d; - make ops based on TensorFlow Lite quantization optional; - add all & any support for reduction; - use type in parameter as output type in reduction; - add int support for unary; - add variable weight support for conv2d; - fix conv2d depthwise weights initialization; - fix type support for transpose; - fix grad outputs count for reduce grad and reshape grad; - fix priorbox & detection output; - fix metal softmax error; - python: - add runSessionWithCallBackInfo interface; - add max nodes limit (1400) for visualization tool; - fix save error in python3; - align default dim; - convert: - add extra design for optimization; - add more post converting optimizers; - add caffe v1 weights blob support; - add cast, unary, conv transpose support for onnx model; - optimize batchnorm, conv with variable weights, prelu, reshape, slice, upsample for onnx model; - add cos/sin/atan/tan support for unary for tensorflow model; - add any/all support for reduction for tensorflow model; - add elu, conv3d, pool3d support for tensorflow model; - optimize argmax, batchnorm, concat, batch to space, conv with variable weights, prelu, slice for tensorflow model; - others: - fix size computer lock; - fix thread pool deadlock; - add express & parameters in express; - rewrite blitter chooser without static map; - add tests for expr;
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void MNNMatrixAddCommon(float* C, const float* A, const float* B, size_t width, size_t cStride, size_t aStride, size_t bStride, size_t height);
void MNNMatrixSubCommon(float* C, const float* A, const float* B, size_t width, size_t cStride, size_t aStride, size_t bStride, size_t height);
void MNNMatrixMaxCommon(float* C, const float* A, const float* B, size_t width, size_t cStride, size_t aStride, size_t bStride, size_t height);
void MNNMatrixProdCommon(float* C, const float* A, const float* B, size_t width, size_t cStride, size_t aStride, size_t bStride, size_t height);
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int MNNGetConvolutionTileNumber();
- build: - unify schema building in core and converter; - add more build script for android; - add linux build script for python; - ops impl: - add floor mod support in binary; - use eltwise impl in add/max/sub/mul binary for optimization; - remove fake double support in cast; - fix 5d support for concat; - add adjX and adjY support for batch matmul; - optimize conv2d back prop filter; - add pad mode support for conv3d; - fix bug in conv2d & conv depthwise with very small feature map; - optimize binary without broacast; - add data types support for gather; - add gather ND support; - use uint8 data type in gather v2; - add transpose support for matmul; - add matrix band part; - add dim != 4 support for padding, reshape & tensor convert; - add pad type support for pool3d; - make ops based on TensorFlow Lite quantization optional; - add all & any support for reduction; - use type in parameter as output type in reduction; - add int support for unary; - add variable weight support for conv2d; - fix conv2d depthwise weights initialization; - fix type support for transpose; - fix grad outputs count for reduce grad and reshape grad; - fix priorbox & detection output; - fix metal softmax error; - python: - add runSessionWithCallBackInfo interface; - add max nodes limit (1400) for visualization tool; - fix save error in python3; - align default dim; - convert: - add extra design for optimization; - add more post converting optimizers; - add caffe v1 weights blob support; - add cast, unary, conv transpose support for onnx model; - optimize batchnorm, conv with variable weights, prelu, reshape, slice, upsample for onnx model; - add cos/sin/atan/tan support for unary for tensorflow model; - add any/all support for reduction for tensorflow model; - add elu, conv3d, pool3d support for tensorflow model; - optimize argmax, batchnorm, concat, batch to space, conv with variable weights, prelu, slice for tensorflow model; - others: - fix size computer lock; - fix thread pool deadlock; - add express & parameters in express; - rewrite blitter chooser without static map; - add tests for expr;
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#ifdef __cplusplus
}
#endif
#endif /* ConvOpt_h */