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!7990 fix static checking of lite ops

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Merge pull request !7990 from liuwenhao/master
pull/7990/MERGE
mindspore-ci-bot 4 years ago committed by Gitee
parent 5f3fcf2260 765afb2bb1
commit 2cd48d8cc9
52 changed files with 150 additions and 115 deletions
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1
mindspore/lite/nnacl/common_func.c
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@ -15,7 +15,6 @@
*/
#include "nnacl/common_func.h"
#include "nnacl/quantization/fixed_point.h"
int offset(const int *shape, const int dim0, const int dim1, const int dim2, const int dim3) {
return ((dim0 * shape[1] + dim1) * shape[2] + dim2) * shape[3] + dim3;

4
mindspore/lite/nnacl/fp32/conv.c
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@ -21,7 +21,7 @@
#include "nnacl/fp32/matmul.h"
// fp32 conv common
void ConvFp32(float *input_data, float *packed_input, const float *packed_weight, const float *bias_data,
void ConvFp32(const float *input_data, float *packed_input, const float *packed_weight, const float *bias_data,
float *col_major_input, float *output_data, int task_id, ConvParameter *conv_param) {
int kernel_h = conv_param->kernel_h_;
int kernel_w = conv_param->kernel_w_;
@ -70,7 +70,7 @@ void ConvFp32(float *input_data, float *packed_input, const float *packed_weight
}
// fp32 conv winograd
void ConvWinogardFp32(float *input_data, const float *trans_weight, const float *bias_data, float *output_data,
void ConvWinogardFp32(const float *input_data, const float *trans_weight, const float *bias_data, float *output_data,
TmpBufferAddress *buffer_list, int task_id, ConvParameter *conv_param, InputTransFunc in_func,
OutputTransFunc out_func) {
int thread_num = conv_param->thread_num_;

4
mindspore/lite/nnacl/fp32/conv.h
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@ -34,11 +34,11 @@ extern "C" {
#endif
// fp32 convolution common (im2col+gemm)
void ConvFp32(float *input_data, float *packed_input, const float *packed_weight, const float *bias_data,
void ConvFp32(const float *input_data, float *packed_input, const float *packed_weight, const float *bias_data,
float *col_major_input, float *output_data, int task_id, ConvParameter *conv_param);
// fp32 convolution winograd
void ConvWinogardFp32(float *input_data, const float *trans_weight, const float *bias_data, float *output_data,
void ConvWinogardFp32(const float *input_data, const float *trans_weight, const float *bias_data, float *output_data,
TmpBufferAddress *buffer_list, int task_id, ConvParameter *conv_param, InputTransFunc in_func,
OutputTransFunc out_func);
#ifdef __cplusplus

11
mindspore/lite/nnacl/fp32/deconv_winograd.c
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@ -50,6 +50,7 @@ int PackDeConvWgDataFp32(float *nhwc_weight, DeConvComputeUnit *unit, ConvParame
DECONV_WINOGRAD_DEFAULT_UNIT, unit->h_size_);
if (ret != NNACL_OK) {
free(current_unit_weight);
current_unit_weight = NULL;
return NNACL_ERRCODE_WINOGRAD_GENERATOR_ERROR;
}
@ -58,6 +59,7 @@ int PackDeConvWgDataFp32(float *nhwc_weight, DeConvComputeUnit *unit, ConvParame
if (unit->winograd_.AT_ == NULL) {
if (current_unit_weight != NULL) {
free(current_unit_weight);
current_unit_weight = NULL;
}
return NNACL_NULL_PTR;
}
@ -68,9 +70,11 @@ int PackDeConvWgDataFp32(float *nhwc_weight, DeConvComputeUnit *unit, ConvParame
if (unit->winograd_.BT_ == NULL) {
if (current_unit_weight != NULL) {
free(current_unit_weight);
current_unit_weight = NULL;
}
if (unit->winograd_.AT_ != NULL) {
free(unit->winograd_.AT_);
unit->winograd_.AT_ = NULL;
}
return NNACL_NULL_PTR;
}
@ -82,12 +86,15 @@ int PackDeConvWgDataFp32(float *nhwc_weight, DeConvComputeUnit *unit, ConvParame
if (winograd_unit_weight == NULL) {
if (current_unit_weight != NULL) {
free(current_unit_weight);
current_unit_weight = NULL;
}
if (unit->winograd_.AT_ != NULL) {
free(unit->winograd_.AT_);
unit->winograd_.AT_ = NULL;
}
if (unit->winograd_.BT_ != NULL) {
free(unit->winograd_.BT_);
unit->winograd_.BT_ = NULL;
}
return NNACL_NULL_PTR;
}
@ -97,6 +104,7 @@ int PackDeConvWgDataFp32(float *nhwc_weight, DeConvComputeUnit *unit, ConvParame
/* reset weight data & info */
tmp_kernel_plane = unit->winograd_.kh_ * unit->winograd_.kw_;
free(current_unit_weight);
current_unit_weight = NULL;
current_unit_weight = winograd_unit_weight;
winograd_unit_weight = NULL;
}
@ -119,6 +127,7 @@ int PackDeConvWgDataFp32(float *nhwc_weight, DeConvComputeUnit *unit, ConvParame
if (current_unit_weight != NULL) {
free(current_unit_weight);
current_unit_weight = NULL;
}
return NNACL_OK;
}
@ -332,7 +341,7 @@ void DeConvWgMerge(const float *src, float *dst, size_t src_stride, size_t dst_s
}
void _deConvWinograd(const float *tile_in, float *tile_out, float *weight_buf, float *tmp_buf, float *at_buf,
float *a_mid_buf, float *trans_a_buf, bool *transfered, float *bt_buf, float *b_tmp_buf,
float *a_mid_buf, float *trans_a_buf, bool *transfered, const float *bt_buf, float *b_tmp_buf,
int unit_size, int w_start, int h_start, ConvParameter *conv_param, DeConvParam *deconv_param) {
int winograd_plane = unit_size * unit_size;
if (!transfered[unit_size]) {

2
mindspore/lite/nnacl/fp32/elu.c
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@ -22,7 +22,7 @@ void Calculate_Data(const float *input_data, float *output_data, int num, EluPar
output_data[num] = input_data[num] < 0 ? parameter->alpha_ * expm1(input_data[num]) : input_data[num];
}
int Elu(float *input_data, float *output_data, EluParameter *parameter, int task_id) {
int Elu(const float *input_data, float *output_data, EluParameter *parameter, int task_id) {
for (size_t i = task_id; i < parameter->in_size_; i += parameter->thread_num_) {
Calculate_Data(input_data, output_data, i, parameter);
}

2
mindspore/lite/nnacl/fp32/elu.h
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@ -29,7 +29,7 @@ typedef struct EluParameter {
#ifdef __cplusplus
extern "C" {
#endif
int Elu(float *input_data, float *output_data, EluParameter *parameter, int task_id);
int Elu(const float *input_data, float *output_data, EluParameter *parameter, int task_id);
#ifdef __cplusplus
}
#endif

2
mindspore/lite/nnacl/fp32/gatherNd.c
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@ -18,7 +18,7 @@
#include <string.h>
#include "nnacl/errorcode.h"
int GatherNd(const float *input, float *output, int *in_offset, int area, int count) {
int GatherNd(const float *input, float *output, const int *in_offset, int area, int count) {
int i = 0;
for (i = 0; i < count; i++) {
(void)memcpy(output + area * i, input + in_offset[i], area * sizeof(float));

2
mindspore/lite/nnacl/fp32/gatherNd.h
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@ -27,7 +27,7 @@ typedef struct GatherNdParameter {
#ifdef __cplusplus
extern "C" {
#endif
int GatherNd(const float *input, float *output, int *in_offset, int area, int count);
int GatherNd(const float *input, float *output, const int *in_offset, int area, int count);
#ifdef __cplusplus
}
#endif

4
mindspore/lite/nnacl/fp32/lstm.c
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@ -79,13 +79,13 @@ void ElementMulAcc(const float *input0, const float *input1, float *output, int
}
}
void UpdataState(float *cell_state, float *forget_gate, const float *input_gate, float *cell_gate, int batch,
void UpdataState(float *cell_state, const float *forget_gate, const float *input_gate, float *cell_gate, int batch,
int hidden_size) {
ElementMul(forget_gate, cell_state, cell_state, batch * hidden_size);
ElementMulAcc(input_gate, cell_gate, cell_state, batch * hidden_size);
}
void UpdataOutput(const float *cell_state, float *output_gate, float *hidden_state, int batch, int hidden_size) {
void UpdataOutput(const float *cell_state, const float *output_gate, float *hidden_state, int batch, int hidden_size) {
Tanh(cell_state, batch * hidden_size, hidden_state);
ElementMul(hidden_state, output_gate, hidden_state, batch * hidden_size);
}

6
mindspore/lite/nnacl/fp32/resize.c
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@ -65,7 +65,7 @@ int PrepareResizeBilinear(const int *input_shape, const int *output_shape, bool
}
int ResizeBilinear(const float *input_data, float *output_data, const int *input_shape, const int *output_shape,
int *y_bottoms, const int *y_tops, int *x_lefts, int *x_rights, float *y_bottom_weights,
const int *y_bottoms, const int *y_tops, int *x_lefts, int *x_rights, float *y_bottom_weights,
float *x_left_weights, int n_h_begin, int n_h_end) {
if (input_data == NULL || output_data == NULL || input_shape == NULL || output_shape == NULL || y_bottoms == NULL ||
y_tops == NULL || x_lefts == NULL || x_rights == NULL || y_bottom_weights == NULL || x_left_weights == NULL) {
@ -154,7 +154,7 @@ int ResizeBilinear(const float *input_data, float *output_data, const int *input
return NNACL_OK;
}
int InterpRow(const float *src_line, float *linear_output, int new_width, float *x_left_weights, int *x_lefts,
int InterpRow(const float *src_line, float *linear_output, int new_width, float *x_left_weights, const int *x_lefts,
const int *x_rights, int in_c) {
int w;
for (w = 0; w < new_width; w++) {
@ -208,7 +208,7 @@ int InterpCol(const float *bottom_line, const float *top_line, float *output, in
}
int ResizeBilinear2(const float *input_data, float *output_data, const int *input_shape, const int *output_shape,
int *y_bottoms, const int *y_tops, int *x_lefts, int *x_rights, float *y_bottom_weights,
const int *y_bottoms, const int *y_tops, int *x_lefts, int *x_rights, float *y_bottom_weights,
float *x_left_weights, float *line0, float *line1, int n_h_begin, int n_h_end) {
if (input_data == NULL || output_data == NULL || input_shape == NULL || output_shape == NULL || y_bottoms == NULL ||
y_tops == NULL || x_lefts == NULL || x_rights == NULL || y_bottom_weights == NULL || x_left_weights == NULL) {

4
mindspore/lite/nnacl/fp32/resize.h
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@ -30,11 +30,11 @@ int PrepareResizeBilinear(const int *input_shape, const int *output_shape, bool
int *y_tops, int *x_lefts, int *x_rights, float *y_bottom_weights, float *x_left_weights);
int ResizeBilinear(const float *input_data, float *output_data, const int *input_shape, const int *output_shape,
int *y_bottoms, const int *y_tops, int *x_lefts, int *x_rights, float *y_bottom_weights,
const int *y_bottoms, const int *y_tops, int *x_lefts, int *x_rights, float *y_bottom_weights,
float *x_left_weights, int n_h_begin, int n_h_end);
int ResizeBilinear2(const float *input_data, float *output_data, const int *input_shape, const int *output_shape,
int *y_bottoms, const int *y_tops, int *x_lefts, int *x_rights, float *y_bottom_weights,
const int *y_bottoms, const int *y_tops, int *x_lefts, int *x_rights, float *y_bottom_weights,
float *x_left_weights, float *line0, float *line1, int n_h_begin, int n_h_end);
int ResizeNearestNeighbor(const float *input_data, float *output_data, const int *input_shape, const int *output_shape,

29
mindspore/lite/nnacl/fp32/scale.c
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@ -18,8 +18,8 @@
#ifdef ENABLE_ARM
#include <arm_neon.h>
#endif
void ScaleInner(float *in_data, float *out_data, const float *scale, float *offset, int outer_start, int outer_end,
int axis_size, int inner_size) {
void ScaleInner(float *in_data, float *out_data, const float *scale, const float *offset, int outer_start,
int outer_end, int axis_size, int inner_size) {
for (int out = outer_start; out < outer_end; out++) {
int out_offset = out * axis_size * inner_size;
for (int i = 0; i < axis_size; i++) {
@ -43,7 +43,7 @@ void ScaleInner(float *in_data, float *out_data, const float *scale, float *offs
}
}
void ScaleAxis(float *in_data, float *out_data, const float *scale, float *offset, int outer_start, int outer_end,
void ScaleAxis(float *in_data, float *out_data, const float *scale, const float *offset, int outer_start, int outer_end,
int axis_size) {
for (int out = outer_start; out < outer_end; out++) {
int out_offset = out * axis_size;
@ -65,7 +65,8 @@ void ScaleAxis(float *in_data, float *out_data, const float *scale, float *offse
}
}
void DoScale(float *in_data, float *out_data, float *scale, float *offset, int task_id, ScaleParameter *scale_param) {
void DoScale(float *in_data, float *out_data, const float *scale, float *offset, int task_id,
ScaleParameter *scale_param) {
int outer_step = UP_DIV(scale_param->outer_size_, scale_param->op_parameter_.thread_num_);
int outer_start = task_id * outer_step;
int outer_end = MSMIN(outer_start + outer_step, scale_param->outer_size_);
@ -78,8 +79,8 @@ void DoScale(float *in_data, float *out_data, float *scale, float *offset, int t
}
}
void ScaleInnerRelu(float *in_data, float *out_data, const float *scale, float *offset, int outer_start, int outer_end,
int axis_size, int inner_size) {
void ScaleInnerRelu(float *in_data, float *out_data, const float *scale, const float *offset, int outer_start,
int outer_end, int axis_size, int inner_size) {
#ifdef ENABLE_ARM64
float32x4_t zeros = {0, 0, 0, 0};
#endif
@ -108,8 +109,8 @@ void ScaleInnerRelu(float *in_data, float *out_data, const float *scale, float *
}
}
void ScaleAxisRelu(float *in_data, float *out_data, const float *scale, float *offset, int outer_start, int outer_end,
int axis_size) {
void ScaleAxisRelu(float *in_data, float *out_data, const float *scale, const float *offset, int outer_start,
int outer_end, int axis_size) {
#ifdef ENABLE_ARM64
float32x4_t zeros = {0, 0, 0, 0};
#endif
@ -135,7 +136,7 @@ void ScaleAxisRelu(float *in_data, float *out_data, const float *scale, float *o
}
}
void DoScaleRelu(float *in_data, float *out_data, float *scale, float *offset, int task_id,
void DoScaleRelu(float *in_data, float *out_data, const float *scale, float *offset, int task_id,
ScaleParameter *scale_param) {
int outer_step = UP_DIV(scale_param->outer_size_, scale_param->op_parameter_.thread_num_);
int outer_start = task_id * outer_step;
@ -149,8 +150,8 @@ void DoScaleRelu(float *in_data, float *out_data, float *scale, float *offset, i
}
}
void ScaleInnerRelu6(float *in_data, float *out_data, const float *scale, float *offset, int outer_start, int outer_end,
int axis_size, int inner_size) {
void ScaleInnerRelu6(float *in_data, float *out_data, const float *scale, const float *offset, int outer_start,
int outer_end, int axis_size, int inner_size) {
#ifdef ENABLE_ARM64
float32x4_t zeros = {0, 0, 0, 0};
float32x4_t bounds = {6, 6, 6, 6};
@ -180,8 +181,8 @@ void ScaleInnerRelu6(float *in_data, float *out_data, const float *scale, float
}
}
void ScaleAxisRelu6(float *in_data, float *out_data, const float *scale, float *offset, int outer_start, int outer_end,
int axis_size) {
void ScaleAxisRelu6(float *in_data, float *out_data, const float *scale, const float *offset, int outer_start,
int outer_end, int axis_size) {
#ifdef ENABLE_ARM64
float32x4_t zeros = {0, 0, 0, 0};
float32x4_t bounds = {6, 6, 6, 6};
@ -208,7 +209,7 @@ void ScaleAxisRelu6(float *in_data, float *out_data, const float *scale, float *
}
}
void DoScaleRelu6(float *in_data, float *out_data, float *scale, float *offset, int task_id,
void DoScaleRelu6(float *in_data, float *out_data, const float *scale, float *offset, int task_id,
ScaleParameter *scale_param) {
int outer_step = UP_DIV(scale_param->outer_size_, scale_param->op_parameter_.thread_num_);
int outer_start = task_id * outer_step;

7
mindspore/lite/nnacl/fp32/scale.h
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@ -22,10 +22,11 @@
#ifdef __cplusplus
extern "C" {
#endif
void DoScale(float *in_data, float *out_data, float *scale, float *offset, int task_id, ScaleParameter *scale_param);
void DoScaleRelu(float *in_data, float *out_data, float *scale, float *offset, int task_id,
void DoScale(float *in_data, float *out_data, const float *scale, float *offset, int task_id,
ScaleParameter *scale_param);
void DoScaleRelu(float *in_data, float *out_data, const float *scale, float *offset, int task_id,
ScaleParameter *scale_param);
void DoScaleRelu6(float *in_data, float *out_data, float *scale, float *offset, int task_id,
void DoScaleRelu6(float *in_data, float *out_data, const float *scale, float *offset, int task_id,
ScaleParameter *scale_param);
#ifdef __cplusplus
}

1
mindspore/lite/nnacl/fp32/softmax.c
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@ -16,7 +16,6 @@
#include "nnacl/fp32/softmax.h"
#include <math.h>
#include <float.h>
// output = exp(input) / reduce_sum(exp(input), axis)
void Softmax(const float *input_ptr, float *output_ptr, float *sum_data, SoftmaxParameter *parameter) {

6
mindspore/lite/nnacl/fp32/space_to_batch.c
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@ -16,7 +16,8 @@
#include "nnacl/fp32/space_to_batch.h"
#include "nnacl/arithmetic_common.h"
void DoSpaceToBatchNHWC(const float *input, float *output, const int *block_sizes, int *in_shape, int *out_shape) {
void DoSpaceToBatchNHWC(const float *input, float *output, const int *block_sizes, int *in_shape,
const int *out_shape) {
int out_dim0 = out_shape[0];
int out_dim1 = out_shape[1];
int out_dim2 = out_shape[2];
@ -45,7 +46,8 @@ void DoSpaceToBatchNHWC(const float *input, float *output, const int *block_size
}
}
void DoSpaceToBatchPaddingNHWC(const float *input, float *output, int *in_shape, const int *padding, int *out_shape) {
void DoSpaceToBatchPaddingNHWC(const float *input, float *output, int *in_shape, const int *padding,
const int *out_shape) {
int in_h = in_shape[1];
int in_w = in_shape[2];
int in_c = in_shape[3];

5
mindspore/lite/nnacl/fp32/space_to_batch.h
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@ -30,8 +30,9 @@ typedef struct SpaceToBatchParameter {
#ifdef __cplusplus
extern "C" {
#endif
void DoSpaceToBatchNHWC(const float *input, float *output, const int *block_sizes, int *in_shape, int *out_shape);
void DoSpaceToBatchPaddingNHWC(const float *input, float *output, int *in_shape, const int *padding, int *out_shape);
void DoSpaceToBatchNHWC(const float *input, float *output, const int *block_sizes, int *in_shape, const int *out_shape);
void DoSpaceToBatchPaddingNHWC(const float *input, float *output, int *in_shape, const int *padding,
const int *out_shape);
#ifdef __cplusplus
}
#endif

2
mindspore/lite/nnacl/fp32/space_to_depth.c
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@ -18,7 +18,7 @@
#include "nnacl/errorcode.h"
#include "nnacl/op_base.h"
int SpaceToDepthForNHWC(const float *input, float *output, int *in_shape, int *out_shape, int shape_size,
int SpaceToDepthForNHWC(const float *input, float *output, int *in_shape, const int *out_shape, int shape_size,
int block_size, int h_start, int h_end) {
if (input == NULL || output == NULL) {
return NNACL_NULL_PTR;

2
mindspore/lite/nnacl/fp32/space_to_depth.h
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@ -24,7 +24,7 @@ typedef struct SpaceToDepthParameter {
#ifdef __cplusplus
extern "C" {
#endif
int SpaceToDepthForNHWC(const float *input, float *output, int *in_shape, int *out_shape, int shape_size,
int SpaceToDepthForNHWC(const float *input, float *output, int *in_shape, const int *out_shape, int shape_size,
int block_size, int h_start, int h_end);
#ifdef __cplusplus
}

2
mindspore/lite/nnacl/fp32/sparse_to_dense.c
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@ -15,7 +15,7 @@
*/
#include "nnacl/fp32/sparse_to_dense.h"
void SparseToDense(int **sparse_indices, int *output_shape, const float *sparse_values, float default_value,
void SparseToDense(int **sparse_indices, const int *output_shape, const float *sparse_values, float default_value,
float *output, bool isScalar, int index_start, int index_end, int out_width) {
for (int i = index_start; i < index_end; i++) {
for (int j = 0; j < out_width; j++) {

2
mindspore/lite/nnacl/fp32/sparse_to_dense.h
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@ -21,7 +21,7 @@
#ifdef __cplusplus
extern "C" {
#endif
void SparseToDense(int **sparse_indices_vect, int *output_shape, const float *sparse_values, float default_value,
void SparseToDense(int **sparse_indices_vect, const int *output_shape, const float *sparse_values, float default_value,
float *output, bool isScalar, int index_start, int index_end, int out_width);
#ifdef __cplusplus
}

6
mindspore/lite/nnacl/fp32/stack.c
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@ -17,7 +17,7 @@
#include "nnacl/fp32/stack.h"
#include "nnacl/arithmetic_common.h"
size_t GetStackCopyNum(int axis, int *in_shape, size_t shape_size) {
size_t GetStackCopyNum(int axis, const int *in_shape, size_t shape_size) {
size_t one_input_size = 1;
for (size_t i = 0; i < shape_size; ++i) {
one_input_size *= in_shape[i];
@ -68,6 +68,4 @@ void DoStackInt32(const int32_t *const *inputs, size_t input_num, int *in_shape,
}
}
void DoStackOneInput(const int8_t *input, int8_t *output, size_t data_size) {
memcpy(output, input, data_size);
}
void DoStackOneInput(const int8_t *input, int8_t *output, size_t data_size) { memcpy(output, input, data_size); }

1
mindspore/lite/nnacl/int8/batch_to_space_int8.c
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@ -15,7 +15,6 @@
*/
#include "nnacl/int8/batch_to_space_int8.h"
#include "nnacl/arithmetic_common.h"
void BatchToSpaceNoCropForNHWCInt8(const int8_t *input, int8_t *output, const int *in_shape, int out_n,
const int *block, QuantArg *in_quant_arg, QuantArg *out_quant_arg) {

4
mindspore/lite/nnacl/int8/conv_depthwise_int8.c
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@ -491,7 +491,7 @@ void ConvDw3x3Int8Pad(int8_t *output_data, const int8_t *input_data, const int16
/*conv depthwise sliding window perchannel int8 begin*/
void DepthwiseBorderPixelInt8(int8_t *dst, const int8_t *src, const int16_t *weight, const int32_t *bias, int height,
int width, int in_kh_step, int in_kw_step, int kernel_w, int8_t *input_zp,
int32_t *out_zp, int *out_multiplier, int *left_shift, const int *right_shift,
int32_t *out_zp, const int *out_multiplier, int *left_shift, const int *right_shift,
int32_t *acc_min, int32_t *acc_max) {
int tmp_buffer[C8NUM];
for (int i = 0; i < C8NUM; i++) {
@ -528,7 +528,7 @@ void DepthwiseBorderPixelInt8(int8_t *dst, const int8_t *src, const int16_t *wei
void DepthwiseBorderInt8(int8_t *dst, const int8_t *src, const int16_t *weight, const int32_t *bias, int top,
int bottom, int left, int right, const ConvParameter *conv_param,
const SlidingWindowParam *sliding, int8_t *in_zp, int32_t *out_zp, int *out_multiplier,
int *left_shift, int *right_shift, int32_t *acc_min, int32_t *acc_max) {
int *left_shift, const int *right_shift, int32_t *acc_min, int32_t *acc_max) {
int8_t *dst_h = dst + top * sliding->out_h_step_;
for (int oh = top; oh < bottom; oh++) {
int ih = oh * conv_param->stride_h_ - conv_param->pad_u_;

4
mindspore/lite/nnacl/int8/space_to_batch_int8.c
Unescape View File

@ -17,7 +17,7 @@
#include "nnacl/arithmetic_common.h"
void DoSpaceToBatchNHWCInt8(const int8_t *input, int8_t *output, const int *block_sizes, int *in_shape,
int *out_shape) {
const int *out_shape) {
int out_dim0 = out_shape[0];
int out_dim1 = out_shape[1];
int out_dim2 = out_shape[2];
@ -47,7 +47,7 @@ void DoSpaceToBatchNHWCInt8(const int8_t *input, int8_t *output, const int *bloc
}
void DoSpaceToBatchPaddingNHWCInt8(const int8_t *input, int8_t *output, int *in_shape, const int *padding,
int *out_shape, int32_t zp) {
const int *out_shape, int32_t zp) {
int in_h = in_shape[1];
int in_w = in_shape[2];
int in_c = in_shape[3];

5
mindspore/lite/nnacl/int8/space_to_batch_int8.h
Unescape View File

@ -21,9 +21,10 @@
#ifdef __cplusplus
extern "C" {
#endif
void DoSpaceToBatchNHWCInt8(const int8_t *input, int8_t *output, const int *block_sizes, int *in_shape, int *out_shape);
void DoSpaceToBatchNHWCInt8(const int8_t *input, int8_t *output, const int *block_sizes, int *in_shape,
const int *out_shape);
void DoSpaceToBatchPaddingNHWCInt8(const int8_t *input, int8_t *output, int *in_shape, const int *padding,
int *out_shape, int32_t zp);
const int *out_shape, int32_t zp);
#ifdef __cplusplus
}
#endif

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