1 /**
2 * Copyright 2020-2023 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 #include "minddata/dataset/kernels/data/random_apply_op.h"
17
18 #include "minddata/dataset/core/tensor.h"
19 #include "minddata/dataset/kernels/tensor_op.h"
20 #include "minddata/dataset/util/status.h"
21
22 namespace mindspore {
23 namespace dataset {
RandomApplyOp(const std::vector<std::shared_ptr<TensorOp>> & ops,double prob)24 RandomApplyOp::RandomApplyOp(const std::vector<std::shared_ptr<TensorOp>> &ops, double prob)
25 : prob_(prob), rand_double_(0.0, 1.0) {
26 compose_ = std::make_unique<ComposeOp>(ops);
27 }
28
NumOutput()29 uint32_t RandomApplyOp::NumOutput() {
30 if (compose_->NumOutput() != NumInput()) {
31 MS_LOG(WARNING) << "NumOutput!=NumInput (randomApply would randomly affect number of outputs).";
32 return 0;
33 }
34 return compose_->NumOutput();
35 }
36
OutputShape(const std::vector<TensorShape> & inputs,std::vector<TensorShape> & outputs)37 Status RandomApplyOp::OutputShape(const std::vector<TensorShape> &inputs, std::vector<TensorShape> &outputs) {
38 RETURN_IF_NOT_OK(compose_->OutputShape(inputs, outputs));
39 // randomApply either runs all ops or do nothing. If the two methods don't give the same result. return unknown shape.
40 if (inputs != outputs) { // when RandomApply is not applied, input should be the same as output
41 outputs.clear();
42 outputs.resize(NumOutput(), TensorShape::CreateUnknownRankShape());
43 }
44 return Status::OK();
45 }
46
OutputType(const std::vector<DataType> & inputs,std::vector<DataType> & outputs)47 Status RandomApplyOp::OutputType(const std::vector<DataType> &inputs, std::vector<DataType> &outputs) {
48 RETURN_IF_NOT_OK(compose_->OutputType(inputs, outputs));
49 if (inputs != outputs) { // when RandomApply is not applied, input should be the same as output
50 outputs.clear();
51 outputs.resize(NumOutput(), DataType(DataType::DE_UNKNOWN));
52 }
53 return Status::OK();
54 }
55
Compute(const TensorRow & input,TensorRow * output)56 Status RandomApplyOp::Compute(const TensorRow &input, TensorRow *output) {
57 IO_CHECK_VECTOR(input, output);
58 if (rand_double_(random_generator_) <= prob_) {
59 RETURN_IF_NOT_OK(compose_->Compute(input, output));
60 } else {
61 *output = input; // copy over the tensors
62 }
63 return Status::OK();
64 }
65 } // namespace dataset
66 } // namespace mindspore
67