Adel Shafiei
5 years ago
parent
822a3160e4
commit
5fcd3f01a6
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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* http://www.apache.org/licenses/LICENSE-2.0
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "dataset/kernels/image/uniform_aug_op.h"
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#include "dataset/kernels/py_func_op.h"
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#include "dataset/util/random.h"
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namespace mindspore {
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namespace dataset {
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const int UniformAugOp::kDefNumOps = 2;
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UniformAugOp::UniformAugOp(py::list op_list, int32_t num_ops) : num_ops_(num_ops) {
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std::shared_ptr<TensorOp> tensor_op;
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// iterate over the op list, cast them to TensorOp and add them to tensor_op_list_
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for (auto op : op_list) {
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if (py::isinstance<py::function>(op)) {
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// python op
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tensor_op = std::make_shared<PyFuncOp>(op.cast<py::function>());
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} else if (py::isinstance<TensorOp>(op)) {
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// C++ op
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tensor_op = op.cast<std::shared_ptr<TensorOp>>();
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}
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tensor_op_list_.insert(tensor_op_list_.begin(), tensor_op);
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}
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rnd_.seed(GetSeed());
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}
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// compute method to apply uniformly random selected augmentations from a list
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Status UniformAugOp::Compute(const std::vector<std::shared_ptr<Tensor>> &input,
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std::vector<std::shared_ptr<Tensor>> *output) {
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IO_CHECK_VECTOR(input, output);
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// variables to generate random number to select ops from the list
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std::vector<int> random_indexes;
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// variables to copy the result to output if it is not already
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std::vector<std::shared_ptr<Tensor>> even_out;
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std::vector<std::shared_ptr<Tensor>> *even_out_ptr = &even_out;
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int count = 1;
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// select random indexes for candidates to be applied
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for (int i = 0; i < num_ops_; ++i) {
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random_indexes.insert(random_indexes.end(),
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std::uniform_int_distribution<int>(0, tensor_op_list_.size() - 1)(rnd_));
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}
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for (auto it = random_indexes.begin(); it != random_indexes.end(); ++it) {
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// Do NOT apply the op, if second random generator returned zero
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if (std::uniform_int_distribution<int>(0, 1)(rnd_)) {
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continue;
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}
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std::shared_ptr<TensorOp> tensor_op = tensor_op_list_[*it];
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// apply python/C++ op
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if (count == 1) {
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(*tensor_op).Compute(input, output);
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} else if (count % 2 == 0) {
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(*tensor_op).Compute(*output, even_out_ptr);
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} else {
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(*tensor_op).Compute(even_out, output);
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}
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count++;
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}
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// copy the result to output if it is not in output
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if (count == 1) {
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*output = input;
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} else if ((count % 2 == 1)) {
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(*output).swap(even_out);
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}
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return Status::OK();
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}
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} // namespace dataset
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} // namespace mindspore
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@ -0,0 +1,60 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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* http://www.apache.org/licenses/LICENSE-2.0
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#ifndef DATASET_KERNELS_IMAGE_UNIFORM_AUG_OP_H_
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#define DATASET_KERNELS_IMAGE_UNIFORM_AUG_OP_H_
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#include <memory>
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#include <random>
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#include <string>
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#include <vector>
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#include "dataset/core/tensor.h"
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#include "dataset/kernels/tensor_op.h"
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#include "dataset/util/status.h"
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#include "dataset/kernels/py_func_op.h"
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#include "pybind11/stl.h"
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namespace mindspore {
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namespace dataset {
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class UniformAugOp : public TensorOp {
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public:
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// Default number of Operations to be applied
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static const int kDefNumOps;
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// Constructor for UniformAugOp
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// @param list op_list: list of candidate python operations
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// @param list num_ops: number of augemtation operations to applied
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UniformAugOp(py::list op_list, int32_t num_ops);
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~UniformAugOp() override = default;
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void Print(std::ostream &out) const override { out << "UniformAugOp:: number of ops " << num_ops_; }
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// Overrides the base class compute function
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// @return Status - The error code return
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Status Compute(const std::vector<std::shared_ptr<Tensor>> &input,
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std::vector<std::shared_ptr<Tensor>> *output) override;
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private:
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int32_t num_ops_;
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std::vector<std::shared_ptr<TensorOp>> tensor_op_list_;
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std::mt19937 rnd_;
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};
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} // namespace dataset
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} // namespace mindspore
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#endif // DATASET_KERNELS_IMAGE_UNIFORM_AUG_OP_H_
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