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1 /**
2  * Copyright 2021 Huawei Technologies Co., Ltd
3  *
4  * Licensed under the Apache License, Version 2.0 (the "License");
5  * you may not use this file except in compliance with the License.
6  * You may obtain a copy of the License at
7  *
8  * http://www.apache.org/licenses/LICENSE-2.0
9  *
10  * Unless required by applicable law or agreed to in writing, software
11  * distributed under the License is distributed on an "AS IS" BASIS,
12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13  * See the License for the specific language governing permissions and
14  * limitations under the License.
15  */
16 
17 #include <stdio.h>
18 #include "nnacl/infer/conv2d_grad_filter_infer.h"
19 #include "nnacl/infer/infer_register.h"
20 
Conv2dGradFilterInferShape(const TensorC * const * inputs,size_t inputs_size,TensorC ** outputs,size_t outputs_size,OpParameter * parameter)21 int Conv2dGradFilterInferShape(const TensorC *const *inputs, size_t inputs_size, TensorC **outputs, size_t outputs_size,
22                                OpParameter *parameter) {
23   int ret = CheckAugmentNull(inputs, inputs_size, outputs, outputs_size, parameter);
24   if (ret != NNACL_OK) {
25     return ret;
26   }
27   if (inputs_size < 3 || outputs_size != 1) {
28     return NNACL_ERR;
29   }
30   if (inputs[FIRST_INPUT]->format_ != Format_NHWC || inputs[SECOND_INPUT]->format_ != Format_NHWC) {
31     return NNACL_FORMAT_ERROR;
32   }
33   SetDataTypeFormat(outputs[FIRST_INPUT], inputs[FIRST_INPUT]);
34 
35   if (inputs[THIRD_INPUT]->shape_size_ < DIMENSION_1D || inputs[THIRD_INPUT]->data_ == NULL) {
36     return NNACL_ERR;
37   }
38   if (inputs[THIRD_INPUT]->shape_[kNCHW_N] < 0) {
39     return NNACL_ERR;
40   }
41   size_t filter_shape_size = (size_t)(inputs[THIRD_INPUT]->shape_[kNCHW_N]);
42   if (filter_shape_size != DIMENSION_4D) {
43     return NNACL_ERR;
44   }
45 
46   int filter_shape[MAX_SHAPE_SIZE];
47   if (inputs[THIRD_INPUT]->format_ == Format_NCHW || inputs[THIRD_INPUT]->format_ == Format_KCHW) {
48     const int nchw2nhwc[] = {kNCHW_N, kNCHW_H, kNCHW_W, kNCHW_C};
49     for (size_t i = 0; i < filter_shape_size; i++) {
50       filter_shape[i] = *((int *)(inputs[THIRD_INPUT]->data_) + nchw2nhwc[i]);
51     }
52   } else if (inputs[THIRD_INPUT]->format_ == Format_NHWC || inputs[THIRD_INPUT]->format_ == Format_KHWC) {
53     memcpy(filter_shape, inputs[THIRD_INPUT]->data_, filter_shape_size * sizeof(int));
54   } else {
55     return NNACL_ERR;
56   }
57   SetShapeArray(outputs[0], filter_shape, filter_shape_size);
58   return NNACL_OK;
59 }
60 
61 REG_INFER(Conv2DBackpropFilterFusion, PrimType_Conv2DBackpropFilterFusion, Conv2dGradFilterInferShape)
62