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!10787 [MSLITE] arithmetic optimize 

From: @ling_qiao_min
Reviewed-by: 
Signed-off-by:
This commit is contained in:
mindspore-ci-bot 2020-12-31 17:09:49 +08:00 committed by Gitee
parent eb147d0911 1e60984f29
commit 0aac2892d8
61 changed files with 697 additions and 2508 deletions
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2
mindspore/lite/nnacl/adder.h
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@ -16,9 +16,7 @@
#ifndef MINDSPORE_LITE_NNACL_ADDER_H_
#define MINDSPORE_LITE_NNACL_ADDER_H_
#include <math.h>
#include "nnacl/op_base.h"
#include "nnacl/quantization/fixed_point.h"
typedef struct AdderParameter {
OpParameter op_parameter_;

17
mindspore/lite/nnacl/flatten.c → mindspore/lite/nnacl/arithmetic.c
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@ -13,9 +13,18 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "nnacl/flatten.h"
#include <string.h>
void Flatten(const void *input, void *output, const FlattenParameter *flatten_param) {
memcpy(output, input, flatten_param->size);
#include "nnacl/arithmetic.h"
void CalcMultiplesAndStrides(ArithmeticParameter *param) {
NNACL_ASSERT(param->in_shape0_[i] != 0);
NNACL_ASSERT(param->in_shape1_[i] != 0);
for (size_t i = 0; i < param->ndim_; i++) {
param->multiples0_[i] = param->out_shape_[i] / param->in_shape0_[i];
param->multiples1_[i] = param->out_shape_[i] / param->in_shape1_[i];
}
// cal strides
ComputeStrides(param->in_shape0_, param->in_strides0_, param->ndim_);
ComputeStrides(param->in_shape1_, param->in_strides1_, param->ndim_);
ComputeStrides(param->out_shape_, param->out_strides_, param->ndim_);
}

38
mindspore/lite/nnacl/flatten.h → mindspore/lite/nnacl/arithmetic.h
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@ -13,23 +13,41 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef MINDSPORE_LITE_NNACL_FLATTEN_H_
#define MINDSPORE_LITE_NNACL_FLATTEN_H_
#include "nnacl/op_base.h"
typedef struct FlattenParameter {
// Primitive parameter
#ifndef MINDSPORE_LITE_NNACL_ARTITHMETIC_H_
#define MINDSPORE_LITE_NNACL_ARTITHMETIC_H_
#include "nnacl/op_base.h"
#include "nnacl/common_func.h"
#include "nnacl/nnacl_utils.h"
typedef struct ArithmeticParameter {
OpParameter op_parameter_;
// other parameter
int size;
} FlattenParameter;
bool broadcasting_;
size_t ndim_;
int activation_type_;
int in_shape0_[10];
int in_elements_num0_;
int in_shape1_[10];
int in_elements_num1_;
int out_shape_[10];
int out_elements_num_;
int in_strides0_[10];
int in_strides1_[10];
int out_strides_[10];
int multiples0_[10];
int multiples1_[10];
} ArithmeticParameter;
#ifdef __cplusplus
extern "C" {
#endif
void Flatten(const void *input, void *output, const FlattenParameter *flatten_param);
void CalcMultiplesAndStrides(ArithmeticParameter *param);
#ifdef __cplusplus
}
#endif
#endif // MINDSPORE_LITE_NNACL_FLATTEN_H_
#endif // MINDSPORE_LITE_NNACL_ARTITHMETIC_H_

102
mindspore/lite/nnacl/arithmetic_common.c
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@ -1,102 +0,0 @@
/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "nnacl/arithmetic_common.h"
#include "nnacl/nnacl_utils.h"
void TileOneDimension(const float *inData, float *outData, int dim, size_t ndim, const int *inShape,
const int *inStrides, const int *outStrides, const int *multiple) {
int srcDimSize = inShape[dim];
if (dim == ndim - 1) {
for (int i = 0; i < multiple[dim]; i++) {
memcpy(outData, inData, srcDimSize * sizeof(float));
outData += srcDimSize;
}
return;
}
for (size_t i = 0; i < srcDimSize; i++) {
for (size_t j = 0; j < multiple[dim]; j++) {
TileOneDimension(inData + inStrides[dim] * i, outData + outStrides[dim] * (i + j * srcDimSize), dim + 1, ndim,
inShape, inStrides, outStrides, multiple);
}
}
}
void TileOneDimensionUint8(const uint8_t *inData, uint8_t *outData, int dim, size_t ndim, const int *inShape,
const int *inStrides, const int *outStrides, const int *multiple) {
int srcDimSize = inShape[dim];
if (dim == ndim - 1) {
for (int i = 0; i < multiple[dim]; i++) {
memcpy(outData, inData, srcDimSize * sizeof(uint8_t));
outData += srcDimSize;
}
return;
}
for (size_t i = 0; i < srcDimSize; i++) {
for (size_t j = 0; j < multiple[dim]; j++) {
TileOneDimensionUint8(inData + inStrides[dim] * i, outData + outStrides[dim] * (i + j * srcDimSize), dim + 1,
ndim, inShape, inStrides, outStrides, multiple);
}
}
}
void ComputeStrides(const int *shape, int *strides, const int ndim) {
int stride = 1;
for (int i = ndim - 1; i >= 0; i--) {
strides[i] = stride;
stride *= shape[i];
}
}
void CalcMultiplesAndStrides(ArithmeticParameter *param) {
NNACL_ASSERT(param->in_shape0_[i] != 0);
NNACL_ASSERT(param->in_shape1_[i] != 0);
for (size_t i = 0; i < param->ndim_; i++) {
param->multiples0_[i] = param->out_shape_[i] / param->in_shape0_[i];
param->multiples1_[i] = param->out_shape_[i] / param->in_shape1_[i];
}
// cal strides
ComputeStrides(param->in_shape0_, param->in_strides0_, param->ndim_);
ComputeStrides(param->in_shape1_, param->in_strides1_, param->ndim_);
ComputeStrides(param->out_shape_, param->out_strides_, param->ndim_);
}
void TileDimensions(const float *data0, const float *data1, float *tile_data0, float *tile_data1,
ArithmeticParameter *param) {
CalcMultiplesAndStrides(param);
TileOneDimension(data0, tile_data0, 0, param->ndim_, param->in_shape0_, param->in_strides0_, param->out_strides_,
param->multiples0_);
TileOneDimension(data1, tile_data1, 0, param->ndim_, param->in_shape1_, param->in_strides1_, param->out_strides_,
param->multiples1_);
}
void TileDimensionsUint8(const uint8_t *data0, const uint8_t *data1, uint8_t *tile_data0, uint8_t *tile_data1,
ArithmeticParameter *param) {
CalcMultiplesAndStrides(param);
TileOneDimensionUint8(data0, tile_data0, 0, param->ndim_, param->in_shape0_, param->in_strides0_, param->out_strides_,
param->multiples0_);
TileOneDimensionUint8(data1, tile_data1, 0, param->ndim_, param->in_shape1_, param->in_strides1_, param->out_strides_,
param->multiples1_);
}
void TileDimensionsInt8(const int8_t *data0, const int8_t *data1, int8_t *tile_data0, int8_t *tile_data1,
ArithmeticParameter *param) {
CalcMultiplesAndStrides(param);
TileOneDimensionUint8((uint8_t *)(data0), (uint8_t *)(tile_data0), 0, param->ndim_, param->in_shape0_,
param->in_strides0_, param->out_strides_, param->multiples0_);
TileOneDimensionUint8((uint8_t *)(data1), (uint8_t *)(tile_data1), 0, param->ndim_, param->in_shape1_,
param->in_strides1_, param->out_strides_, param->multiples1_);
}

68
mindspore/lite/nnacl/arithmetic_common.h
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@ -1,68 +0,0 @@
/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef MINDSPORE_LITE_NNACL_ARITHMETIC_COMMON_H_
#define MINDSPORE_LITE_NNACL_ARITHMETIC_COMMON_H_
#ifdef ENABLE_NEON
#include <arm_neon.h>
#endif
#include <string.h>
#include "nnacl/op_base.h"
#include "nnacl/arithmetic_common.h"
typedef struct ArithmeticParameter {
OpParameter op_parameter_;
bool broadcasting_;
size_t ndim_;
int activation_type_;
int in_shape0_[10];
int in_elements_num0_;
int in_shape1_[10];
int in_elements_num1_;
int out_shape_[10];
int out_elements_num_;
int in_strides0_[10];
int in_strides1_[10];
int out_strides_[10];
int multiples0_[10];
int multiples1_[10];
} ArithmeticParameter;
#ifdef __cplusplus
extern "C" {
#endif
void TileOneDimension(const float *inData, float *outData, int dim, size_t ndim, const int *inShape,
const int *inStrides, const int *outStrides, const int *multiple);
void ComputeStrides(const int *shape, int *strides, const int ndim);
void CalcMultiplesAndStrides(ArithmeticParameter *param);
void TileOneDimensionUint8(const uint8_t *inData, uint8_t *outData, int dim, size_t ndim, const int *inShape,
const int *inStrides, const int *outStrides, const int *multiple);
void TileDimensions(const float *data0, const float *data1, float *tile_data0, float *tile_data1,
ArithmeticParameter *param);
void TileDimensionsUint8(const uint8_t *data0, const uint8_t *data1, uint8_t *tile_data0, uint8_t *tile_data1,
ArithmeticParameter *param);
void TileDimensionsInt8(const int8_t *data0, const int8_t *data1, int8_t *tile_data0, int8_t *tile_data1,
ArithmeticParameter *param);
#ifdef __cplusplus
}
#endif
#endif // MINDSPORE_LITE_NNACL_ARITHMETIC_COMMON_H_

22
mindspore/lite/nnacl/arithmetic_parameter.h
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@ -1,22 +0,0 @@
/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef MINDSPORE_LITE_NNACL_ARTITHMETIC_PARAMETER_H_
#define MINDSPORE_LITE_NNACL_ARTITHMETIC_PARAMETER_H_
#include "nnacl/op_attribute.h"
#endif // MINDSPORE_LITE_NNACL_ARTITHMETIC_PARAMETER_H_

1
mindspore/lite/nnacl/batch_to_space.c
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@ -15,7 +15,6 @@
*/
#include "nnacl/batch_to_space.h"
#include "nnacl/arithmetic_common.h"
void BatchToSpaceNoCropForNHWC(const void *input, void *output, const int *in_shape, int out_n, const int *block,
int data_size) {

2
mindspore/lite/nnacl/batch_to_space.h
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@ -15,6 +15,8 @@
*/
#ifndef MINDSPORE_LITE_NNACL_BATCH_TO_SPACE_H_
#define MINDSPORE_LITE_NNACL_BATCH_TO_SPACE_H_
#include <string.h>
#include "nnacl/op_base.h"
#define BATCH_TO_SPACE_BLOCK_SHAPE_SIZE 2

8
mindspore/lite/nnacl/common_func.h
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@ -63,6 +63,14 @@ static inline int GetStride(int *strides, const int *shape, int length) {
return stride;
}
inline void ComputeStrides(const int *shape, int *strides, const int ndim) {
int stride = 1;
for (int i = ndim - 1; i >= 0; i--) {
strides[i] = stride;
stride *= shape[i];
}
}
#ifdef ENABLE_ARM64
void BiasAdd(const float *bias, float *data, size_t oc4, size_t plan_size);
void BiasAddRelu6(const float *bias, float *data, size_t oc4, size_t plan_size);

2
mindspore/lite/nnacl/fp16/arithmetic_fp16.c
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@ -16,7 +16,7 @@
#include "nnacl/fp16/arithmetic_fp16.h"
#include <math.h>
#include "nnacl/arithmetic_common.h"
#include "nnacl/common_func.h"
#include "nnacl/nnacl_utils.h"
void TileOneDimensionFp16(float16_t *inData, float16_t *outData, int dim, size_t ndim, int *inShape, int *inStrides,

4
mindspore/lite/nnacl/fp16/arithmetic_fp16.h
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@ -20,7 +20,7 @@
#include <arm_neon.h>
#endif
#include "nnacl/op_base.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/arithmetic.h"
#include "nnacl/errorcode.h"
#ifdef __cplusplus
@ -107,7 +107,7 @@ int ElementMinimumFp16(float16_t *input0, float16_t *input1, float16_t *output,
int ElementNotEqualFp16(float16_t *input0, float16_t *input1, uint8_t *output, int element_size);
int ElementEqualFp16(float16_t *input0, float16_t *input1, uint8_t *output, int element_size);
int ElementLessFp16(float16_t *input0, float16_t *input1, uint8_t *output, int element_size);
int ElementLessEqual(float16_t *input0, float16_t *input1, uint8_t *output, int element_size);
int ElementLessEqualFp16(float16_t *input0, float16_t *input1, uint8_t *output, int element_size);
int ElementGreaterFp16(float16_t *input0, float16_t *input1, uint8_t *output, int element_size);
int ElementGreaterEqualFp16(float16_t *input0, float16_t *input1, uint8_t *output, int element_size);

2
mindspore/lite/nnacl/fp16/stack_fp16.c
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@ -15,7 +15,7 @@
*/
#include "nnacl/fp16/stack_fp16.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/common_func.h"
size_t Fp16GetStackCopyNum(int axis, int *in_shape, size_t shape_size) {
size_t one_input_size = 1;

1082
mindspore/lite/nnacl/fp32/arithmetic_fp32.c
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File diff suppressed because it is too large Load Diff

197
mindspore/lite/nnacl/fp32/arithmetic_fp32.h
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@ -20,144 +20,97 @@
#include <arm_neon.h>
#endif
#include "nnacl/op_base.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/arithmetic.h"
#include "nnacl/errorcode.h"
#ifdef __cplusplus
extern "C" {
#endif
int ElementOptAdd(const float *input0, const float *input1, float *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptAddInt(const int *input0, const int *input1, int *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptAddRelu(const float *input0, const float *input1, float *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptAddRelu6(const float *input0, const float *input1, float *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptSub(const float *input0, const float *input1, float *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptSubInt(const int *input0, const int *input1, int *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptSubRelu(const float *input0, const float *input1, float *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptSubRelu6(const float *input0, const float *input1, float *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptMul(const float *input0, const float *input1, float *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptMulRelu(const float *input0, const float *input1, float *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptMulRelu6(const float *input0, const float *input1, float *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptMulInt(const int *input0, const int *input1, int *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptMulReluInt(const int *input0, const int *input1, int *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptMulRelu6Int(const int *input0, const int *input1, int *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptDiv(const float *input0, const float *input1, float *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptDivRelu(const float *input0, const float *input1, float *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptDivRelu6(const float *input0, const float *input1, float *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptDivInt(const int *input0, const int *input1, int *output, const int element_size,
const ArithmeticParameter *param);
int ElementMul(const float *input0, const float *input1, float *output, const int element_size);
int ElementMulRelu(const float *input0, const float *input1, float *output, const int element_size);
int ElementMulRelu6(const float *input0, const float *input1, float *output, const int element_size);
int ElementMulInt(const int *input0, const int *input1, int *output, const int element_size);
int ElementMulReluInt(const int *input0, const int *input1, int *output, const int element_size);
int ElementMulRelu6Int(const int *input0, const int *input1, int *output, const int element_size);
int BroadcastMul(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
void TileOneDimensionFp32(const float *inData, float *outData, int dim, size_t ndim, const int *inShape,
const int *inStrides, const int *outStrides, const int *multiple);
void TileDimensionsFp32(const float *data0, const float *data1, float *tile_data0, float *tile_data1,
ArithmeticParameter *param);
int ElementAdd(const float *input0, const float *input1, float *output, const int element_size);
int ElementAddRelu(const float *input0, const float *input1, float *output, const int element_size);
int ElementAddRelu6(const float *input0, const float *input1, float *output, const int element_size);
int ElementAddInt(const int *input0, const int *input1, int *output, const int element_size);
int BroadcastAdd(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
int BroadcastAddInt8(const int8_t *input0, const int8_t *input1, int8_t *tile_input0, int8_t *tile_input1,
int8_t *output, int element_size, ArithmeticParameter *param);
/* Mul */
int ElementMul(const float *in0, const float *in1, float *out, int size);
int ElementMulRelu(const float *in0, const float *in1, float *out, int size);
int ElementMulRelu6(const float *in0, const float *in1, float *out, int size);
int ElementMulInt(const int *in0, const int *in1, int *out, int size);
int ElementMulReluInt(const int *in0, const int *in1, int *out, int size);
int ElementMulRelu6Int(const int *in0, const int *in1, int *out, int size);
int ElementOptMul(const float *in0, const float *in1, float *out, int size, const ArithmeticParameter *param);
int ElementOptMulRelu(const float *in0, const float *in1, float *out, int size, const ArithmeticParameter *param);
int ElementOptMulRelu6(const float *in0, const float *in1, float *out, int size, const ArithmeticParameter *param);
int ElementOptMulInt(const int *in0, const int *in1, int *out, int size, const ArithmeticParameter *param);
int ElementOptMulReluInt(const int *in0, const int *in1, int *out, int size, const ArithmeticParameter *param);
int ElementOptMulRelu6Int(const int *in0, const int *in1, int *out, int size, const ArithmeticParameter *param);
int BroadcastMul(const float *in0, const float *in1, float *tile_in0, float *tile_in1, float *out, int size,
ArithmeticParameter *param);
int ElementSub(const float *input0, const float *input1, float *output, const int element_size);
int ElementSubInt(const int *input0, const int *input1, int *output, const int element_size);
int ElementSubRelu(const float *input0, const float *input1, float *output, const int element_size);
int ElementSubRelu6(const float *input0, const float *input1, float *output, const int element_size);
int BroadcastSub(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
/* Add */
int ElementAdd(const float *in0, const float *in1, float *out, int size);
int ElementAddRelu(const float *in0, const float *in1, float *out, int size);
int ElementAddRelu6(const float *in0, const float *in1, float *out, int size);
int ElementAddInt(const int *in0, const int *in1, int *out, int size);
int ElementOptAdd(const float *in0, const float *in1, float *out, int size, const ArithmeticParameter *param);
int ElementOptAddInt(const int *in0, const int *in1, int *out, int size, const ArithmeticParameter *param);
int ElementOptAddRelu(const float *in0, const float *in1, float *out, int size, const ArithmeticParameter *param);
int ElementOptAddRelu6(const float *in0, const float *in1, float *out, int size, const ArithmeticParameter *param);
int BroadcastAdd(const float *in0, const float *in1, float *tile_in0, float *tile_in1, float *out, int size,
ArithmeticParameter *param);
int ElementDiv(const float *input0, const float *input1, float *output, const int element_size);
int ElementDivRelu(const float *input0, const float *input1, float *output, const int element_size);
int ElementDivRelu6(const float *input0, const float *input1, float *output, const int element_size);
int BroadcastDiv(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
/* Sub */
int ElementSub(const float *in0, const float *in1, float *out, int size);
int ElementSubInt(const int *in0, const int *in1, int *out, int size);
int ElementSubRelu(const float *in0, const float *in1, float *out, int size);
int ElementSubRelu6(const float *in0, const float *in1, float *out, int size);
int ElementOptSub(const float *in0, const float *in1, float *out, int size, const ArithmeticParameter *param);
int ElementOptSubRelu(const float *in0, const float *in1, float *out, int size, const ArithmeticParameter *param);
int ElementOptSubRelu6(const float *in0, const float *in1, float *out, int size, const ArithmeticParameter *param);
int ElementOptSubInt(const int *in0, const int *in1, int *out, int size, const ArithmeticParameter *param);
int ElementLogicalAnd(const float *input0, const float *input1, float *output, const int element_size);
int ElementLogicalAndInt(const int *input0, const int *input1, int *output, const int element_size);
int ElementLogicalAndBool(const bool *input0, const bool *input1, bool *output, const int element_size);
int BroadcastLogicalAnd(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
/* Div */
int ElementDiv(const float *in0, const float *in1, float *out, int size);
int ElementDivRelu(const float *in0, const float *in1, float *out, int size);
int ElementDivRelu6(const float *in0, const float *in1, float *out, int size);
int ElementOptDiv(const float *in0, const float *in1, float *out, int size, const ArithmeticParameter *param);
int ElementOptDivRelu(const float *in0, const float *in1, float *out, int size, const ArithmeticParameter *param);
int ElementOptDivRelu6(const float *in0, const float *in1, float *out, int size, const ArithmeticParameter *param);
int ElementOptDivInt(const int *in0, const int *in1, int *out, int size, const ArithmeticParameter *param);
int BroadcastDiv(const float *in0, const float *in1, float *tile_in0, float *tile_in1, float *out, int size,
ArithmeticParameter *param);
int ElementLogicalOr(const float *input0, const float *input1, float *output, const int element_size);
int BroadcastLogicalOr(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
/* logical and */
int ElementLogicalAnd(const float *in0, const float *in1, float *out, int size);
int ElementLogicalAndInt(const int *in0, const int *in1, int *out, int size);
int ElementLogicalAndBool(const bool *in0, const bool *in1, bool *out, int size);
int ElementMaximum(const float *input0, const float *input1, float *output, const int element_size);
int ElementMaximumInt(const int *input0, const int *input1, int *output, const int element_size);
int BroadcastMaximum(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
/* logical or */
int ElementLogicalOr(const float *in0, const float *in1, float *out, int size);
int ElementMinimum(const float *input0, const float *input1, float *output, const int element_size);
int BroadcastMinimum(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
/* Element Squared Difference */
int ElementSquaredDifference(const float *in0, const float *in1, float *out, int size);
int ElementFloorDiv(const float *input0, const float *input1, float *output, const int element_size);
int ElementFloorDivInt(const int *input0, const int *input1, int *output, const int element_size);
int BroadcastFloorDiv(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
/* max min */
int ElementMaximum(const float *in0, const float *in1, float *out, int size);
int ElementMinimum(const float *in0, const float *in1, float *out, int size);
int ElementMaximumInt(const int *in0, const int *in1, int *out, int size);
int BroadcastMaximum(const float *in0, const float *in1, float *tile_input0, float *tile_input1, float *out, int size,
ArithmeticParameter *param);
int ElementFloorMod(const float *input0, const float *input1, float *output, const int element_size);
int ElementFloorModInt(const int *input0, const int *input1, int *output, const int element_size);
int BroadcastFloorMod(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
/* floor div */
int ElementFloorDiv(const float *in0, const float *in1, float *out, int size);
int ElementFloorDivInt(const int *in0, const int *in1, int *out, int size);
int ElementMod(const float *input0, const float *input1, float *output, const int element_size);
int ElementModInt(const int *input0, const int *input1, int *output, const int element_size);
int ElementOptMod(const float *input0, const float *input1, float *output, const int element_size,
const ArithmeticParameter *param);
int ElementOptModInt(const int *input0, const int *input1, int *output, const int element_size,
const ArithmeticParameter *param);
/* floor mod */
int ElementFloorMod(const float *in0, const float *in1, float *out, int size);
int ElementFloorModInt(const int *in0, const int *in1, int *out, int size);
int ElementSquaredDifference(const float *input0, const float *input1, float *output, const int element_size);
int BroadcastSquaredDifference(const float *input0, const float *input1, float *tile_input0, float *tile_input1,
float *output, int element_size, ArithmeticParameter *param);
int ElementNotEqual(const float *input0, const float *input1, float *output, const int element_size);
int BroadcastNotEqual(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
int ElementEqual(const float *input0, const float *input1, float *output, const int element_size);
int BroadcastEqual(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
int ElementLess(const float *input0, const float *input1, float *output, const int element_size);
int BroadcastLess(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
int ElementLessEqual(const float *input0, const float *input1, float *output, const int element_size);
int BroadcastLessEqual(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
int ElementGreater(const float *input0, const float *input1, float *output, const int element_size);
int BroadcastGreater(const float *input0, const float *input1, float *tile_input0, float *tile_input1, float *output,
int element_size, ArithmeticParameter *param);
int ElementGreaterEqual(const float *input0, const float *input1, float *output, const int element_size);
int BroadcastGreaterEqual(const float *input0, const float *input1, float *tile_input0, float *tile_input1,
float *output, int element_size, ArithmeticParameter *param);
/* mod */
int ElementMod(const float *in0, const float *in1, float *out, int size);
int ElementModInt(const int *in0, const int *in1, int *out, int size);
int ElementOptMod(const float *in0, const float *in1, float *out, int size, const ArithmeticParameter *param);
int ElementOptModInt(const int *in0, const int *in1, int *out, int size, const ArithmeticParameter *param);
#ifdef ENABLE_NNACL_INFER_SHAPE
int ArithmeticInferShape(int **in_shape, size_t *dim_size, int *out_shape, int *in_format, int *out_format,

1
mindspore/lite/nnacl/fp32/space_to_batch_fp32.c
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@ -14,7 +14,6 @@
* limitations under the License.
*/
#include "nnacl/fp32/space_to_batch_fp32.h"
#include "nnacl/arithmetic_common.h"
void DoSpaceToBatch(const float *input, float *output, const int *in_shape, const int *out_shape, const int *in_stride,
const int *out_stride, const int *blocks, const int *paddings, int thread, int task_id) {

2
mindspore/lite/nnacl/fp32/space_to_batch_fp32.h
View File

@ -15,6 +15,8 @@
*/
#ifndef MINDSPORE_LITE_SRC_BACKEND_ARM_NNACL_FP32_SPACE_TO_BATCH_H_
#define MINDSPORE_LITE_SRC_BACKEND_ARM_NNACL_FP32_SPACE_TO_BATCH_H_
#include <string.h>
#include "nnacl/op_base.h"
typedef struct SpaceToBatchParameter {

2
mindspore/lite/nnacl/fp32/space_to_depth_fp32.c
View File

@ -14,7 +14,7 @@
* limitations under the License.
*/
#include "nnacl/fp32/space_to_depth_fp32.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/common_func.h"
#include "nnacl/errorcode.h"
#include "nnacl/op_base.h"

2
mindspore/lite/nnacl/fp32/stack_fp32.c
View File

@ -15,7 +15,7 @@
*/
#include "nnacl/fp32/stack_fp32.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/common_func.h"
size_t GetStackCopyNum(int axis, const int *in_shape, size_t shape_size) {
size_t one_input_size = 1;

13
mindspore/lite/nnacl/int8/add_int8.c
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@ -312,3 +312,16 @@ void AddOptInt8(const int8_t *ptr_in, const int8_t element_in, int8_t *output, i
}
return;
}
int ElementAddInt8(const int8_t *in0, const int8_t *in1, int8_t *out, int size) {
for (int i = 0; i < size; i++) {
out[i] = in0[i] + in1[i];
}
return NNACL_OK;
}
int BroadcastAddInt8(const int8_t *in0, const int8_t *in1, int8_t *tile_in0, int8_t *tile_in1, int8_t *out, int size,
ArithmeticParameter *param) {
TileDimensionsInt8(in0, in1, tile_in0, tile_in1, param);
return ElementAddInt8(tile_in0, tile_in1, out, size);
}

7
mindspore/lite/nnacl/int8/add_int8.h
View File

@ -18,6 +18,9 @@
#define MINDSPORE_LITE_NNACL_ADD_INT8_H_
#include "nnacl/op_base.h"
#include "nnacl/errorcode.h"
#include "nnacl/arithmetic.h"
#include "nnacl/int8/arithmetic_int8.h"
typedef struct AddQuantQrgs {
int32_t zp_;
@ -48,6 +51,10 @@ void AddInt8(const int8_t *input0, const int8_t *input1, int8_t *output, int siz
void AddOptInt8(const int8_t *ptr_in, const int8_t element_in, int8_t *output, int size, AddQuantParameter *params,
AddQuantQrgs *ptr_args, AddQuantQrgs *ele_args);
int ElementAddInt8(const int8_t *in0, const int8_t *in1, int8_t *out, int size);
int BroadcastAddInt8(const int8_t *in0, const int8_t *in1, int8_t *tile_in0, int8_t *tile_in1, int8_t *out, int size,
ArithmeticParameter *param);
#ifdef __cplusplus
}
#endif

27
mindspore/lite/nnacl/int8/arithmetic_int8.c
View File

@ -20,6 +20,33 @@
#endif
#include "nnacl/errorcode.h"
void TileOneDimensionInt8(const int8_t *inData, int8_t *outData, int dim, size_t ndim, const int *inShape,
const int *inStrides, const int *outStrides, const int *multiple) {
int srcDimSize = inShape[dim];
if (dim == ndim - 1) {
for (int i = 0; i < multiple[dim]; i++) {
memcpy(outData, inData, srcDimSize * sizeof(int8_t));
outData += srcDimSize;
}
return;
}
for (size_t i = 0; i < srcDimSize; i++) {
for (size_t j = 0; j < multiple[dim]; j++) {
TileOneDimensionInt8(inData + inStrides[dim] * i, outData + outStrides[dim] * (i + j * srcDimSize), dim + 1, ndim,
inShape, inStrides, outStrides, multiple);
}
}
}
void TileDimensionsInt8(const int8_t *data0, const int8_t *data1, int8_t *tile_data0, int8_t *tile_data1,
ArithmeticParameter *param) {
CalcMultiplesAndStrides(param);
TileOneDimensionInt8(data0, tile_data0, 0, param->ndim_, param->in_shape0_, param->in_strides0_, param->out_strides_,
param->multiples0_);
TileOneDimensionInt8(data1, tile_data1, 0, param->ndim_, param->in_shape1_, param->in_strides1_, param->out_strides_,
param->multiples1_);
}
#define ACCURACY_DATA 0.00000001
int ElementNotEqualInt8(int8_t *input0, int8_t *input1, uint8_t *output, int element_size,

6
mindspore/lite/nnacl/int8/arithmetic_int8.h
View File

@ -17,11 +17,17 @@
#define MINDSPORE_LITE_NNACL_INT8_ARITHMETIC_INT8_H_
#include "nnacl/op_base.h"
#include "nnacl/arithmetic.h"
#include "nnacl/quantization/quantize.h"
#ifdef __cplusplus
extern "C" {
#endif
void TileOneDimensionInt8(const int8_t *inData, int8_t *outData, int dim, size_t ndim, const int *inShape,
const int *inStrides, const int *outStrides, const int *multiple);
void TileDimensionsInt8(const int8_t *data0, const int8_t *data1, int8_t *tile_data0, int8_t *tile_data1,
ArithmeticParameter *param);
int ElementNotEqualInt8(int8_t *input0, int8_t *input1, uint8_t *output, int element_size,
ArithmeticQuantArg *quant_arg);

2
mindspore/lite/nnacl/int8/space_to_batch_int8.c
View File

@ -14,7 +14,7 @@
* limitations under the License.
*/
#include "nnacl/int8/space_to_batch_int8.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/common_func.h"
void DoSpaceToBatchNHWCInt8(const int8_t *input, int8_t *output, const int *block_sizes, const int *in_shape,
const int *out_shape) {

2
mindspore/lite/nnacl/reverse_sequence.c
View File

@ -16,7 +16,7 @@
#include "nnacl/reverse_sequence.h"
#include <string.h>
#include "nnacl/arithmetic_common.h"
#include "nnacl/common_func.h"
void ReverseSequence(float *input0, const void *input1, float *output, ReverseSequenceParameter *para) {
(void)memcpy(output, input0, para->total_data_size_);

2
mindspore/lite/src/ops/arithmetic.h
View File

@ -21,7 +21,7 @@
#include <set>
#include <cmath>
#include "src/ops/primitive_c.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/arithmetic.h"
namespace mindspore {
namespace lite {

2
mindspore/lite/src/ops/populate/add_populate.cc
View File

@ -17,7 +17,7 @@
#include "src/ops/add.h"
#include "src/ops/primitive_c.h"
#include "src/ops/populate/populate_register.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/arithmetic.h"
#include "src/ops/populate/arithmetic_populate.h"
namespace mindspore {

2
mindspore/lite/src/ops/populate/bias_add_populate.cc
View File

@ -16,7 +16,7 @@
#include "src/ops/primitive_c.h"
#include "src/ops/populate/populate_register.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/arithmetic.h"
namespace mindspore {
namespace lite {

2
mindspore/lite/src/ops/populate/bias_grad_populate.cc
View File

@ -16,7 +16,7 @@
#include "src/ops/primitive_c.h"
#include "src/ops/populate/populate_register.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/arithmetic.h"
namespace mindspore {
namespace lite {

7
mindspore/lite/src/ops/populate/flatten_populate.cc
View File

@ -16,18 +16,17 @@
#include "src/ops/primitive_c.h"
#include "src/ops/populate/populate_register.h"
#include "nnacl/flatten.h"
namespace mindspore {
namespace lite {
OpParameter *PopulateFlattenParameter(const mindspore::lite::PrimitiveC *primitive) {
FlattenParameter *flatten_param = reinterpret_cast<FlattenParameter *>(malloc(sizeof(FlattenParameter)));
OpParameter *flatten_param = reinterpret_cast<OpParameter *>(malloc(sizeof(OpParameter)));
if (flatten_param == nullptr) {
MS_LOG(ERROR) << "malloc FlattenParameter failed.";
return nullptr;
}
memset(flatten_param, 0, sizeof(FlattenParameter));
flatten_param->op_parameter_.type_ = primitive->Type();
memset(flatten_param, 0, sizeof(OpParameter));
flatten_param->type_ = primitive->Type();
return reinterpret_cast<OpParameter *>(flatten_param);
}

2
mindspore/lite/src/ops/populate/mul_populate.cc
View File

@ -15,7 +15,7 @@
*/
#include "src/ops/mul.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/arithmetic.h"
#include "src/ops/primitive_c.h"
#include "src/ops/populate/populate_register.h"
#include "src/ops/populate/arithmetic_populate.h"

6
mindspore/lite/src/ops/populate/squeeze_populate.cc
View File

@ -23,13 +23,13 @@ namespace mindspore {
namespace lite {
OpParameter *PopulateSqueezeParameter(const mindspore::lite::PrimitiveC *primitive) {
SqueezeParameter *squeeze_param = reinterpret_cast<SqueezeParameter *>(malloc(sizeof(SqueezeParameter)));
OpParameter *squeeze_param = reinterpret_cast<OpParameter *>(malloc(sizeof(OpParameter)));
if (squeeze_param == nullptr) {
MS_LOG(ERROR) << "malloc SqueezeParameter failed.";
return nullptr;
}
memset(squeeze_param, 0, sizeof(SqueezeParameter));
squeeze_param->op_parameter_.type_ = primitive->Type();
memset(squeeze_param, 0, sizeof(OpParameter));
squeeze_param->type_ = primitive->Type();
return reinterpret_cast<OpParameter *>(squeeze_param);
}
Registry SqueezeParameterRegistry(schema::PrimitiveType_Squeeze, PopulateSqueezeParameter);

2
mindspore/lite/src/ops/populate/sub_populate.cc
View File

@ -17,7 +17,7 @@
#include "src/ops/sub.h"
#include "src/ops/primitive_c.h"
#include "src/ops/populate/populate_register.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/arithmetic.h"
#include "src/ops/populate/arithmetic_populate.h"
namespace mindspore {

2
mindspore/lite/src/runtime/kernel/arm/base/depth_to_space_base.cc
View File

@ -16,7 +16,7 @@
#include "src/runtime/kernel/arm/base/depth_to_space_base.h"
#include "nnacl/depth_to_space.h"
#include "src/runtime/kernel/arm/fp32/depth_to_space_fp32.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/common_func.h"
#include "schema/model_generated.h"
#include "src/kernel_registry.h"
#include "include/errorcode.h"

2
mindspore/lite/src/runtime/kernel/arm/fp16/arithmetic_compare_fp16.cc
View File

@ -39,7 +39,7 @@ ARITHMETIC_COMPARE_FUNC_INFO_FP16 arithmetic_cp_fun_table_fp16[] = {
{PrimitiveType_NotEqual, schema::ActivationType_NO_ACTIVATION, ElementNotEqualFp16, ElementOptNotEqualFp16},
{PrimitiveType_Equal, schema::ActivationType_NO_ACTIVATION, ElementEqualFp16, ElementOptEqualFp16},
{PrimitiveType_Less, schema::ActivationType_NO_ACTIVATION, ElementLessFp16, ElementOptLessFp16},
{PrimitiveType_LessEqual, schema::ActivationType_NO_ACTIVATION, ElementLessEqual, ElementOptLessEqualFp16},
{PrimitiveType_LessEqual, schema::ActivationType_NO_ACTIVATION, ElementLessEqualFp16, ElementOptLessEqualFp16},
{PrimitiveType_Greater, schema::ActivationType_NO_ACTIVATION, ElementGreaterFp16, ElementOptGreaterFp16},
{PrimitiveType_GreaterEqual, schema::ActivationType_NO_ACTIVATION, ElementGreaterEqualFp16,
ElementOptGreaterEqualFp16}};

2
mindspore/lite/src/runtime/kernel/arm/fp32/argminmax_fp32.h
View File

@ -19,7 +19,7 @@
#include <vector>
#include "include/errorcode.h"
#include "nnacl/fp32/arg_min_max_fp32.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/common_func.h"
#include "src/lite_kernel.h"
namespace mindspore::kernel {

15
mindspore/lite/src/runtime/kernel/arm/fp32/arithmetic_fp32.cc
View File

@ -29,7 +29,6 @@ using mindspore::lite::RET_OK;
using mindspore::schema::PrimitiveType_Eltwise;
namespace mindspore::kernel {
ArithmeticCPUKernel::~ArithmeticCPUKernel() {
FreeTmpPtr();
return;
@ -72,9 +71,10 @@ int ArithmeticCPUKernel::InitBroadCastCase() {
if (input0_ptr_ == nullptr) {
return RET_ERROR;
}
TileOneDimension(reinterpret_cast<float *>(in_tensors_[0]->data_c()), reinterpret_cast<float *>(input0_ptr_), 0,
arithmeticParameter_->ndim_, arithmeticParameter_->in_shape0_, arithmeticParameter_->in_strides0_,
arithmeticParameter_->out_strides_, arithmeticParameter_->multiples0_);
TileOneDimensionFp32(reinterpret_cast<float *>(in_tensors_[0]->data_c()), reinterpret_cast<float *>(input0_ptr_), 0,
arithmeticParameter_->ndim_, arithmeticParameter_->in_shape0_,
arithmeticParameter_->in_strides0_, arithmeticParameter_->out_strides_,
arithmeticParameter_->multiples0_);
arithmeticParameter_->broadcasting_ = false;
input0_broadcast_ = true;
}
@ -85,9 +85,10 @@ int ArithmeticCPUKernel::InitBroadCastCase() {
FreeTmpPtr();
return RET_ERROR;
}
TileOneDimension(reinterpret_cast<float *>(in_tensors_[1]->data_c()), reinterpret_cast<float *>(input1_ptr_), 0,
arithmeticParameter_->ndim_, arithmeticParameter_->in_shape1_, arithmeticParameter_->in_strides1_,
arithmeticParameter_->out_strides_, arithmeticParameter_->multiples1_);
TileOneDimensionFp32(reinterpret_cast<float *>(in_tensors_[1]->data_c()), reinterpret_cast<float *>(input1_ptr_), 0,
arithmeticParameter_->ndim_, arithmeticParameter_->in_shape1_,
arithmeticParameter_->in_strides1_, arithmeticParameter_->out_strides_,
arithmeticParameter_->multiples1_);
arithmeticParameter_->broadcasting_ = false;
input1_broadcast_ = true;
}

1
mindspore/lite/src/runtime/kernel/arm/fp32/depth_to_space_fp32.h
View File

@ -18,7 +18,6 @@
#include <vector>
#include "include/errorcode.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/depth_to_space.h"
#include "src/runtime/kernel/arm/base/depth_to_space_base.h"

16
mindspore/lite/src/runtime/kernel/arm/fp32/flatten_fp32.cc
View File

@ -17,7 +17,6 @@
#include "src/runtime/kernel/arm/fp32/flatten_fp32.h"
#include "schema/model_generated.h"
#include "src/kernel_registry.h"
#include "nnacl/flatten.h"
#include "include/errorcode.h"
using mindspore::kernel::KERNEL_ARCH::kCPU;
@ -34,19 +33,12 @@ int FlattenCPUKernel::Init() {
return ReSize();
}
int FlattenCPUKernel::ReSize() {
auto output_shape = out_tensors_.at(0)->shape();
flatten_param_->size = sizeof(float);
for (size_t i = 0; i < output_shape.size(); i++) {
flatten_param_->size *= output_shape.at(i);
}
return RET_OK;
}
int FlattenCPUKernel::ReSize() { return RET_OK; }
int FlattenCPUKernel::Run() {
auto input = reinterpret_cast<float *>(in_tensors_.at(0)->MutableData());
auto output = reinterpret_cast<float *>(out_tensors_.at(0)->MutableData());
Flatten(input, output, flatten_param_);
auto input = in_tensors_.at(0);
auto output = out_tensors_.at(0);
memcpy(output->data_c(), input->data_c(), output->Size());
return RET_OK;
}

9
mindspore/lite/src/runtime/kernel/arm/fp32/flatten_fp32.h
View File

@ -18,9 +18,7 @@
#include <vector>
#include "src/lite_kernel.h"
#include "include/context.h"
#include "nnacl/flatten.h"
using mindspore::lite::InnerContext;
@ -30,17 +28,12 @@ class FlattenCPUKernel : public LiteKernel {
FlattenCPUKernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,
const std::vector<lite::Tensor *> &outputs, const lite::InnerContext *ctx,
const mindspore::lite::PrimitiveC *primitive)
: LiteKernel(parameter, inputs, outputs, ctx, primitive) {
flatten_param_ = reinterpret_cast<FlattenParameter *>(parameter);
}
: LiteKernel(parameter, inputs, outputs, ctx, primitive) {}
~FlattenCPUKernel() override = default;
int Init() override;
int ReSize() override;
int Run() override;
private:
FlattenParameter *flatten_param_;
};
} // namespace mindspore::kernel

2
mindspore/lite/src/runtime/kernel/arm/fp32/space_to_batch_fp32.h
View File

@ -19,7 +19,7 @@
#include <vector>
#include "src/lite_kernel.h"
#include "nnacl/fp32/space_to_batch_fp32.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/common_func.h"
namespace mindspore::kernel {
class SpaceToBatchCPUKernel : public LiteKernel {

3
mindspore/lite/src/runtime/kernel/arm/int8/add_int8.cc
View File

@ -15,9 +15,6 @@
*/
#include "src/runtime/kernel/arm/int8/add_int8.h"
#include <limits>
#include <algorithm>
#include "nnacl/arithmetic_common.h"
#include "nnacl/quantization/quantize.h"
#include "src/runtime/runtime_api.h"
#include "src/kernel_registry.h"

4
mindspore/lite/src/runtime/kernel/arm/int8/add_int8.h
View File

@ -17,9 +17,11 @@
#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_INT8_ADD_INT8_H_
#include <vector>
#include <limits>
#include <algorithm>
#include "src/lite_kernel.h"
#include "nnacl/int8/add_int8.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/arithmetic.h"
#include "src/runtime/runtime_api.h"
namespace mindspore::kernel {

2
mindspore/lite/src/runtime/kernel/arm/int8/argminmax_int8.h
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@ -19,7 +19,7 @@
#include <vector>
#include "nnacl/quantization/quantize.h"
#include "nnacl/int8/arg_min_max_int8.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/common_func.h"
#include "include/errorcode.h"
#include "src/lite_kernel.h"

2
mindspore/lite/src/runtime/kernel/arm/int8/arithmetic_int8.cc
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@ -17,7 +17,7 @@
#include "src/runtime/kernel/arm/int8/arithmetic_int8.h"
#include "src/runtime/kernel/arm/int8/add_int8.h"
#include "src/runtime/kernel/arm/int8/mul_int8.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/arithmetic.h"
#include "schema/model_generated.h"
#include "src/kernel_registry.h"
#include "src/runtime/runtime_api.h"

5
mindspore/lite/src/runtime/kernel/arm/int8/bias_add_int8.h
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@ -18,8 +18,9 @@
#include <vector>
#include "src/lite_kernel.h"
#include "nnacl/fp32/unique_fp32.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/arithmetic.h"
#include "nnacl/int8/add_int8.h"
#include "nnacl/int8/arithmetic_int8.h"
namespace mindspore::kernel {
class BiasAddInt8CPUKernel : public LiteKernel {

1
mindspore/lite/src/runtime/kernel/arm/int8/deconvolution_int8.h
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@ -27,7 +27,6 @@
#include "nnacl/int8/matmul_int8.h"
#include "src/runtime/kernel/arm/base/layout_transform.h"
#include "src/runtime/kernel/arm/base/convolution_base.h"
#include "nnacl/arithmetic_common.h"
namespace mindspore::kernel {
class DeConvInt8CPUKernel : public ConvolutionBaseCPUKernel {

8
mindspore/lite/src/runtime/kernel/arm/int8/div_int8.cc
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@ -17,7 +17,7 @@
#include "src/runtime/kernel/arm/int8/div_int8.h"
#include <limits>
#include <algorithm>
#include "nnacl/arithmetic_common.h"
#include "nnacl/int8/arithmetic_int8.h"
#include "src/runtime/runtime_api.h"
#include "src/kernel_registry.h"
#include "include/errorcode.h"
@ -114,9 +114,9 @@ int DivInt8CPUKernel::Run() {
tile1_data_ = nullptr;
return RET_ERROR;
}
TileDimensionsUint8(static_cast<uint8_t *>(in_tensors_.at(0)->MutableData()),
static_cast<uint8_t *>(in_tensors_.at(1)->MutableData()),
reinterpret_cast<uint8_t *>(tile0_data_), reinterpret_cast<uint8_t *>(tile1_data_), &tile_para);
TileDimensionsInt8(static_cast<int8_t *>(in_tensors_.at(0)->MutableData()),
static_cast<int8_t *>(in_tensors_.at(1)->MutableData()), reinterpret_cast<int8_t *>(tile0_data_),
reinterpret_cast<int8_t *>(tile1_data_), &tile_para);
}
auto ret = ParallelLaunch(this->context_->thread_pool_, DivInt8Run, this, op_parameter_->thread_num_);
if (broadcast_) {

4
mindspore/lite/src/runtime/kernel/arm/int8/mul_int8.cc
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@ -15,10 +15,6 @@
*/
#include "src/runtime/kernel/arm/int8/mul_int8.h"
#include <limits>
#include <algorithm>
#include "nnacl/arithmetic_common.h"
#include "nnacl/int8/mul_int8.h"
#include "src/runtime/runtime_api.h"
#include "src/kernel_registry.h"
#include "include/errorcode.h"

5
mindspore/lite/src/runtime/kernel/arm/int8/mul_int8.h
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@ -17,9 +17,12 @@
#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_INT8_MUL_INT8_H_
#include <vector>
#include <limits>
#include <algorithm>
#include "src/lite_kernel.h"
#include "nnacl/mul_parameter.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/int8/mul_int8.h"
#include "nnacl/int8/arithmetic_int8.h"
#include "src/runtime/runtime_api.h"
namespace mindspore::kernel {

29
mindspore/lite/src/runtime/kernel/arm/int8/scale_int8.cc
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@ -15,11 +15,6 @@
*/
#include "src/runtime/kernel/arm/int8/scale_int8.h"
#include <string.h>
#include <vector>
#include "nnacl/int8/scale_int8.h"
#include "nnacl/arithmetic_common.h"
#include "schema/model_generated.h"
#include "src/kernel_registry.h"
#include "include/errorcode.h"
@ -66,9 +61,9 @@ int ScaleInt8CPUKernel::InitScaleOffset() {
return RET_ERROR;
}
malloced_scale_ = true;
TileOneDimensionUint8(reinterpret_cast<uint8_t *>(in_tensors_.at(1)->data_c()),
reinterpret_cast<uint8_t *>(input1_data_), 0, tile_para->ndim_, tile_para->in_shape1_,
tile_para->in_strides1_, tile_para->out_strides_, tile_para->multiples1_);
TileOneDimensionInt8(reinterpret_cast<int8_t *>(in_tensors_.at(1)->data_c()),
reinterpret_cast<int8_t *>(input1_data_), 0, tile_para->ndim_, tile_para->in_shape1_,
tile_para->in_strides1_, tile_para->out_strides_, tile_para->multiples1_);
}
}
@ -93,9 +88,9 @@ int ScaleInt8CPUKernel::InitScaleOffset() {
return RET_ERROR;
}
malloced_offset_ = true;
TileOneDimensionUint8(reinterpret_cast<uint8_t *>(in_tensors_.at(2)->data_c()),
reinterpret_cast<uint8_t *>(input2_data_), 0, tile_para->ndim_, tile_para->in_shape1_,
tile_para->in_strides1_, tile_para->out_strides_, tile_para->multiples1_);
TileOneDimensionInt8(reinterpret_cast<int8_t *>(in_tensors_.at(2)->data_c()),
reinterpret_cast<int8_t *>(input2_data_), 0, tile_para->ndim_, tile_para->in_shape1_,
tile_para->in_strides1_, tile_para->out_strides_, tile_para->multiples1_);
}
}
}
@ -305,9 +300,9 @@ int ScaleInt8CPUKernel::Run() {
MS_LOG(ERROR) << "malloc input1_data_ failed.";
return RET_ERROR;
}
TileOneDimensionUint8(reinterpret_cast<uint8_t *>(in_tensors_.at(1)->data_c()),
reinterpret_cast<uint8_t *>(input1_data_), 0, tile_para->ndim_, tile_para->in_shape1_,
tile_para->in_strides1_, tile_para->out_strides_, tile_para->multiples1_);
TileOneDimensionInt8(reinterpret_cast<int8_t *>(in_tensors_.at(1)->data_c()),
reinterpret_cast<int8_t *>(input1_data_), 0, tile_para->ndim_, tile_para->in_shape1_,
tile_para->in_strides1_, tile_para->out_strides_, tile_para->multiples1_);
}
// If has bias, bias is passed by previous node case, need do broadcasting online
@ -319,9 +314,9 @@ int ScaleInt8CPUKernel::Run() {
input1_data_ = nullptr;
return RET_ERROR;
}
TileOneDimensionUint8(reinterpret_cast<uint8_t *>(in_tensors_.at(2)->data_c()),
reinterpret_cast<uint8_t *>(input2_data_), 0, tile_para->ndim_, tile_para->in_shape1_,
tile_para->in_strides1_, tile_para->out_strides_, tile_para->multiples1_);
TileOneDimensionInt8(reinterpret_cast<int8_t *>(in_tensors_.at(2)->data_c()),
reinterpret_cast<int8_t *>(input2_data_), 0, tile_para->ndim_, tile_para->in_shape1_,
tile_para->in_strides1_, tile_para->out_strides_, tile_para->multiples1_);
}
auto ret = ParallelLaunch(this->context_->thread_pool_, ScaleRunInt8, this, op_parameter_->thread_num_);

5
mindspore/lite/src/runtime/kernel/arm/int8/scale_int8.h
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@ -17,14 +17,15 @@
#ifndef MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_INT8_SCALE_INT8_H_
#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_INT8_SCALE_INT8_H_
#include <string.h>
#include <vector>
#include "src/lite_kernel.h"
#include "nnacl/scale.h"
#include "nnacl/quantization/quantize.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/int8/arithmetic_int8.h"
#include "nnacl/int8/scale_int8.h"
namespace mindspore::kernel {
class ScaleInt8CPUKernel : public LiteKernel {
public:
ScaleInt8CPUKernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,

11
mindspore/lite/src/runtime/kernel/arm/int8/sub_int8.cc
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@ -15,10 +15,6 @@
*/
#include "src/runtime/kernel/arm/int8/sub_int8.h"
#include <limits>
#include <algorithm>
#include "nnacl/arithmetic_common.h"
#include "nnacl/quantization/quantize.h"
#include "src/runtime/runtime_api.h"
#include "src/kernel_registry.h"
#include "include/errorcode.h"
@ -29,7 +25,6 @@ using mindspore::lite::RET_OK;
using mindspore::schema::PrimitiveType_Sub;
namespace mindspore::kernel {
int SubInt8CPUKernel::Init() {
lite::Tensor *input0 = in_tensors_.at(0);
lite::Tensor *input1 = in_tensors_.at(1);
@ -142,9 +137,9 @@ int SubInt8CPUKernel::Run() {
context_->allocator->Free(tile0_data_);
return RET_ERROR;
}
TileDimensionsUint8(static_cast<uint8_t *>(in_tensors_.at(0)->MutableData()),
static_cast<uint8_t *>(in_tensors_.at(1)->MutableData()),
reinterpret_cast<uint8_t *>(tile0_data_), reinterpret_cast<uint8_t *>(tile1_data_), &tile_para);
TileDimensionsInt8(static_cast<int8_t *>(in_tensors_.at(0)->data_c()),
static_cast<int8_t *>(in_tensors_.at(1)->data_c()), reinterpret_cast<int8_t *>(tile0_data_),
reinterpret_cast<int8_t *>(tile1_data_), &tile_para);
}
auto ret = ParallelLaunch(this->context_->thread_pool_, SubInt8Run, this, op_parameter_->thread_num_);
if (broadcast_) {

4
mindspore/lite/src/runtime/kernel/arm/int8/sub_int8.h
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@ -17,6 +17,10 @@
#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_INT8_SUB_INT8_H_
#include <vector>
#include <limits>
#include <algorithm>
#include "nnacl/int8/arithmetic_int8.h"
#include "nnacl/quantization/quantize.h"
#include "src/lite_kernel.h"
#include "nnacl/int8/sub_int8.h"
#include "src/runtime/runtime_api.h"

1
mindspore/lite/src/runtime/kernel/npu/eltwise_npu.h
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@ -18,7 +18,6 @@
#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_NPU_ELTWISE_NPU_H_
#include <vector>
#include "src/ops/eltwise.h"
#include "nnacl/arithmetic_common.h"
#include "src/runtime/kernel/npu/npu_kernel.h"
#include "include/graph/op/all_ops.h"
namespace mindspore::kernel {

1
mindspore/lite/src/runtime/kernel/npu/resize_npu.h
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@ -19,7 +19,6 @@
#include <vector>
#include "nnacl/resize_parameter.h"
#include "src/ops/resize.h"
#include "nnacl/arithmetic_common.h"
#include "src/runtime/kernel/npu/npu_kernel.h"
#include "include/graph/op/all_ops.h"
namespace mindspore::kernel {

2
mindspore/lite/src/train/train_populate_parameter.cc
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@ -30,7 +30,7 @@
#include "src/ops/power_grad.h"
#include "nnacl/power_parameter.h"
#include "src/ops/bias_grad.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/arithmetic.h"
#include "nnacl/fp32_grad/optimizer.h"
#include "src/ops/apply_momentum.h"
#include "src/ops/sgd.h"

1350
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/arithmetic_fp32_tests.cc
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2
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/batch_to_space_fp32_test.cc
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@ -16,7 +16,7 @@
#include "src/common/log_adapter.h"
#include "common/common_test.h"
#include "mindspore/lite/nnacl/batch_to_space.h"
#include "mindspore/lite/nnacl/arithmetic_common.h"
#include "mindspore/lite/nnacl/common_func.h"
namespace mindspore {

2
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/depth_to_space_fp32_test.cc
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@ -16,7 +16,7 @@
#include "src/common/log_adapter.h"
#include "common/common_test.h"
#include "mindspore/lite/nnacl/depth_to_space.h"
#include "mindspore/lite/nnacl/arithmetic_common.h"
#include "mindspore/lite/nnacl/common_func.h"
namespace mindspore {

77
mindspore/lite/test/ut/src/runtime/kernel/arm/int8/bias_add_int8_tests.cc
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@ -1,77 +0,0 @@
/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <iostream>
#include <memory>
#include "schema/inner/model_generated.h"
#include "common/common_test.h"
#include "mindspore/lite/src/runtime/kernel/arm/int8/bias_add_int8.h"
#include "mindspore/lite/src/kernel_registry.h"
using mindspore::lite::DeviceType;
namespace mindspore {
class TestBiasAddInt8 : public mindspore::CommonTest {
public:
TestBiasAddInt8() {}
};
TEST_F(TestBiasAddInt8, BiasAdd) {
lite::Tensor in_tensor0(kNumberTypeInt8, {1, 2, 3, 2});
lite::Tensor in_tensor1(kNumberTypeInt8, {2});
lite::Tensor out_tensor(kNumberTypeInt8, {1, 2, 3, 2});
int8_t input_data0[] = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12};
int8_t input_data1[] = {1, 1};
int8_t output_data[12] = {0};
in_tensor0.set_data(input_data0);
in_tensor1.set_data(input_data1);
out_tensor.set_data(output_data);
std::vector<lite::Tensor *> inputs = {&in_tensor0, &in_tensor1};
std::vector<lite::Tensor *> outputs = {&out_tensor};
ArithmeticParameter parameter = {};
int dims[] = {1, 2, 3, 4};
parameter.ndim_ = 4;
for (int i = 0; i < 4; i++) {
parameter.in_shape0_[i] = dims[i];
parameter.in_shape1_[i] = 1;
parameter.out_shape_[i] = dims[i];
}
parameter.in_shape1_[3] = dims[3];
kernel::KernelKey desc = {kernel::KERNEL_ARCH::kCPU, kNumberTypeInt8, schema::PrimitiveType_BiasAdd};
auto creator = lite::KernelRegistry::GetInstance()->GetCreator(desc);
EXPECT_NE(creator, nullptr);
auto ctx = std::make_shared<lite::InnerContext>();
ASSERT_EQ(lite::RET_OK, ctx->Init());
auto kernel = creator(inputs, outputs, reinterpret_cast<OpParameter *>(&parameter), ctx.get(), desc, nullptr);
EXPECT_NE(kernel, nullptr);
auto ret = kernel->Run();
EXPECT_EQ(0, ret);
float expect[] = {2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13};
for (int i = 0; i < 12; ++i) {
EXPECT_EQ(output_data[i], expect[i]);
}
in_tensor0.set_data(nullptr);
in_tensor1.set_data(nullptr);
out_tensor.set_data(nullptr);
}
} // namespace mindspore

2
mindspore/lite/test/ut/src/runtime/kernel/opencl/arithmetic_tests.cc
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@ -14,7 +14,7 @@
* limitations under the License.
*/
#include "ut/src/runtime/kernel/opencl/common.h"
#include "nnacl/arithmetic_common.h"
#include "nnacl/arithmetic.h"
namespace mindspore::lite::opencl::test {