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 "nnacl/infer/resize_grad_infer.h"
18 #include "nnacl/infer/infer_register.h"
19 #include "nnacl/tensor_c_utils.h"
20
ResizeGradInferShape(const TensorC * const * inputs,size_t inputs_size,TensorC ** outputs,size_t outputs_size,OpParameter * parameter)21 int ResizeGradInferShape(const TensorC *const *inputs, size_t inputs_size, TensorC **outputs, size_t outputs_size,
22 OpParameter *parameter) {
23 int check_ret = CheckAugmentWithMinSize(inputs, inputs_size, outputs, outputs_size, parameter, 2, 1);
24 if (check_ret != NNACL_OK) {
25 return check_ret;
26 }
27
28 const TensorC *input = inputs[0];
29 if (input->format_ != Format_NHWC) {
30 return NNACL_FORMAT_ERROR;
31 }
32 if (input->shape_size_ != 4) {
33 return NNACL_ERR;
34 }
35 TensorC *output = outputs[0];
36 SetDataTypeFormat(output, input);
37 if (!InferFlag(inputs, inputs_size)) {
38 return NNACL_INFER_INVALID;
39 }
40 const TensorC *input_1 = inputs[1];
41 if (input_1->shape_size_ == 4) {
42 ShapeSet(output->shape_, &output->shape_size_, input_1->shape_, input_1->shape_size_);
43 } else if (input_1->shape_size_ == 1 && input_1->shape_[0] == 2 && input_1->data_type_ == kNumberTypeInt32) {
44 int output_shape[MAX_SHAPE_SIZE] = {0};
45 size_t output_shape_size = 0;
46 int32_t *data = (int32_t *)(input_1->data_);
47
48 ShapePush(output_shape, &output_shape_size, GetBatch(input));
49 ShapePush(output_shape, &output_shape_size, data[0]);
50 ShapePush(output_shape, &output_shape_size, data[1]);
51 ShapePush(output_shape, &output_shape_size, GetChannel(input));
52 SetShapeArray(output, output_shape, output_shape_size);
53 } else {
54 return NNACL_ERR;
55 }
56 return NNACL_OK;
57 }
58
59 REG_INFER(ResizeGrad, PrimType_ResizeGrad, ResizeGradInferShape)
60