mindspore-ci-bot
5 years ago
committed by
Gitee
commit
40f0a4a4f4
@ -0,0 +1,128 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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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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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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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 <iostream>
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#include <utility>
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#include "dataset/engine/data_buffer.h"
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#include "dataset/engine/datasetops/skip_op.h"
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#include "dataset/engine/db_connector.h"
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#include "dataset/engine/execution_tree.h"
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#include "utils/log_adapter.h"
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namespace mindspore {
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namespace dataset {
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// Builder constructor. Creates the builder object.
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SkipOp::Builder::Builder(int32_t count) : build_max_skips_(count) {}
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Status SkipOp::Builder::SanityCheck() const {
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if (build_max_skips_ < 0) {
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std::string err_msg("Skip count must be positive integer or 0.");
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RETURN_STATUS_UNEXPECTED(err_msg);
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}
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return Status::OK();
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}
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// The builder "build" method creates the final object.
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Status SkipOp::Builder::Build(std::shared_ptr<SkipOp> *ptr) {
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RETURN_IF_NOT_OK(SanityCheck());
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*ptr = std::make_shared<SkipOp>(build_max_skips_);
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return Status::OK();
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}
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// Constructor of the SkipOp.
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SkipOp::SkipOp(int32_t count) : PipelineOp(0), max_skips_(count), skip_count_(0) {}
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// Destructor
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SkipOp::~SkipOp() {}
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// A print method typically used for debugging
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void SkipOp::Print(std::ostream &out, bool show_all) const {
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// Call base class printer first
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PipelineOp::Print(out, show_all);
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// Then display our own stuff
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out << "SkipOp:"
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<< "\nCurrent skip count: " << skip_count_ << "\nMax skip count: " << max_skips_;
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}
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// Since the buffer may contain multi rows, this function will drop the rows
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// that need to skip in it, and then return the buffer.
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Status SkipOp::GetNextBuffer(std::unique_ptr<DataBuffer> *p_buffer, int32_t worker_id, bool retry_if_eoe) {
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if (child_.empty()) {
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RETURN_STATUS_UNEXPECTED("SkipOp can't be the leaf node.");
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}
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std::unique_ptr<DataBuffer> buf;
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// Drop first max_skips_ rows
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while (skip_count_ < max_skips_) {
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RETURN_IF_NOT_OK(child_[0]->GetNextBuffer(&buf, worker_id, true));
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if (buf->eoe() || buf->eof()) {
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break;
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}
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// Consider the rows of buffer more than 1
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TensorRow drop_row;
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int row_num = buf->NumRows();
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for (int i = 0; i < row_num; i++) {
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RETURN_IF_NOT_OK(buf->PopRow(&drop_row));
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if (++skip_count_ == max_skips_) {
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break;
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}
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}
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}
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// If buffer is none or the rows of buffer is 0,
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// then get a buffer from child.
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if (!buf || buf->NumRows() == 0) {
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RETURN_IF_NOT_OK(child_[0]->GetNextBuffer(&buf, worker_id, true));
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}
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// Handling eoe and eof
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if (buf->eoe() || buf->eof()) {
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RETURN_IF_NOT_OK(EoeReceived(worker_id));
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if (state_ == OpState::kDeOpIdle) {
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*p_buffer = std::move(buf);
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return Status::OK();
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}
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}
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*p_buffer = std::move(buf);
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return Status::OK();
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}
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// Base-class override for handling cases when an eoe is received.
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Status SkipOp::EoeReceived(int32_t worker_id) {
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skip_count_ = 0;
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state_ = OpState::kDeOpIdle;
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return Status::OK();
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}
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// Class functor operator () override.
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// Most dataset ops operate by launching a thread (see ExecutionTree).
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// However, the SkipOp is defined as a inlined operator, so it is invalid to
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// launch the functor since this op runs inlined inside another operator. The
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// function is overloaded to ensure that it is not called by mistake (it will
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// generate an error).
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Status SkipOp::operator()() { RETURN_STATUS_UNEXPECTED("Logic error. SkipOp is an inlined operator."); }
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// Base-class override for handling cases when an eof is received.
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Status SkipOp::EofReceived(int32_t worker_id) {
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MS_LOG(INFO) << "Skip operator EOF received, do nothing now.";
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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 +1,95 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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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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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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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_ENGINE_DATASETOPS_SKIP_OP_H_
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#define DATASET_ENGINE_DATASETOPS_SKIP_OP_H_
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#include <memory>
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#include <string>
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#include <vector>
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#include "dataset/engine/datasetops/pipeline_op.h"
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namespace mindspore {
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namespace dataset {
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class SkipOp : public PipelineOp {
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public:
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class Builder {
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public:
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// Builder constructor. Creates the builder object.
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// @note No default args
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// @param count - The number of skip to do
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// @return This is a constructor.
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explicit Builder(int32_t count);
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// Default destructor
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~Builder() = default;
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// The builder "build" method creates the final object.
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// @return shared_ptr to the new StorageOp object
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Status Build(std::shared_ptr<SkipOp> *);
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private:
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int32_t build_max_skips_;
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Status SanityCheck() const;
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};
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// Constructor of the SkipOp.
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// @note The builder class should be used to call it
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// @param count - The number of skips to do
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explicit SkipOp(int32_t count);
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// Destructor
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~SkipOp();
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// A print method typically used for debugging
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// @param out - The output stream to write output to
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// @param show_all - A bool to control if you want to show all info or just a summary
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void Print(std::ostream &out, bool show_all) const override;
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// Class functor operator () override.
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// Most dataset ops operate by launching a thread (see ExecutionTree).
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// However, the SkipOp is defined as a inlined operator, so it is invalid to launch the
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// functor since this op runs inlined inside another operator. The function is overloaded to
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// ensure that it is not called by mistake (it will generate an error).
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// @return Status - The error code return
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Status operator()() override;
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// This function returns the buffer that is at the top of our output connector. The caller is
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// typically our parent node, when the parent is asking us to provide the next buffer of data.
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// Since SkipOp is an inlined op, getting a buffer from us will simply bounce you to get
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// a buffer from our child.
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// @param p_buffer - output pointer to the buffer that it will fetch.
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// @param worker_id - The worker id
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// @param retry_if_eoe Set this flag to true to allow calling pop() again after the first pop() returns EOE.
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// @return Status - The error code return
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Status GetNextBuffer(std::unique_ptr<DataBuffer> *p_buffer, int32_t worker_id, bool retry_if_eoe) override;
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// Base-class override for handling cases when an eoe is received.
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// @param worker_id - The worker id
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Status EoeReceived(int32_t worker_id) override;
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// Base-class override for handling cases when an eof is received.
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// @param worker_id - The worker id
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Status EofReceived(int32_t worker_id) override;
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private:
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int32_t max_skips_; // The number of skips that the user requested
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int32_t skip_count_; // A counter for the current number of executed skips
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};
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} // namespace dataset
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} // namespace mindspore
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#endif // DATASET_ENGINE_DATASETOPS_SKIP_OP_H_
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@ -0,0 +1,91 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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*
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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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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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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/util/circular_pool.h"
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#include "dataset/core/client.h"
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#include "common/common.h"
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#include "gtest/gtest.h"
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#include "utils/log_adapter.h"
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using namespace mindspore::dataset;
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using mindspore::MsLogLevel::INFO;
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using mindspore::ExceptionType::NoExceptionType;
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using mindspore::LogStream;
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class MindDataTestSkipOp : public UT::DatasetOpTesting {};
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TEST_F(MindDataTestSkipOp, TestSkipOpFuntions) {
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// Start with an empty execution tree
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auto my_tree = std::make_shared<ExecutionTree>();
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std::string dataset_path;
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dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";
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std::shared_ptr<TFReaderOp> my_tfreader_op;
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TFReaderOp::Builder builder;
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builder.SetDatasetFilesList({dataset_path})
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.SetRowsPerBuffer(16)
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.SetWorkerConnectorSize(16)
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.SetNumWorkers(16);
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std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
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schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
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builder.SetDataSchema(std::move(schema));
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Status rc = builder.Build(&my_tfreader_op); ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssociateNode(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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// SkipOp
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std::shared_ptr<SkipOp> skip_op = std::make_shared<SkipOp>(5);
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rc = my_tree->AssociateNode(skip_op);
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ASSERT_TRUE(rc.IsOk());
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// Set children/root layout.
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rc = skip_op->AddChild(my_tfreader_op);
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->AssignRoot(skip_op);
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ASSERT_TRUE(rc.IsOk());
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MS_LOG(INFO) << "Launching tree and begin iteration.";
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rc = my_tree->Prepare();
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ASSERT_TRUE(rc.IsOk());
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rc = my_tree->Launch();
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ASSERT_TRUE(rc.IsOk());
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// Start the loop of reading tensors from our pipeline
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DatasetIterator di(my_tree);
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TensorRow tensor_list;
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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int row_count = 0;
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while (!tensor_list.empty()) {
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MS_LOG(INFO) << "Row display for row #: " << row_count << ".";
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// Display the tensor by calling the printer on it
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for (int i = 0; i < tensor_list.size(); i++) {
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std::ostringstream ss;
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ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
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MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
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}
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rc = di.FetchNextTensorRow(&tensor_list);
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ASSERT_TRUE(rc.IsOk());
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row_count++;
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}
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ASSERT_EQ(row_count, 7);
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}
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@ -0,0 +1,130 @@
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# Copyright 2020 Huawei Technologies Co., Ltd
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#
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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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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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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import numpy as np
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import mindspore.dataset.transforms.vision.c_transforms as vision
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import mindspore.dataset as ds
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from mindspore import log as logger
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DATA_DIR_TF2 = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"]
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SCHEMA_DIR_TF2 = "../data/dataset/test_tf_file_3_images/datasetSchema.json"
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def test_tf_skip():
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data1 = ds.TFRecordDataset(DATA_DIR_TF2, SCHEMA_DIR_TF2, shuffle=False)
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resize_height, resize_width = 32, 32
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decode_op = vision.Decode()
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resize_op = vision.Resize((resize_height, resize_width), interpolation=ds.transforms.vision.Inter.LINEAR)
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data1 = data1.map(input_columns=["image"], operations=decode_op)
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data1 = data1.map(input_columns=["image"], operations=resize_op)
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data1 = data1.skip(2)
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num_iter = 0
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for item in data1.create_dict_iterator():
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num_iter += 1
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assert num_iter == 1
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def generator_md():
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# Create a dataset with [0, 1, 2, 3, 4]
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for i in range(5):
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yield (np.array([i]), )
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def test_generator_skip():
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ds1 = ds.GeneratorDataset(generator_md, ["data"])
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# Here ds1 should be [3, 4]
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ds1 = ds1.skip(3)
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buf = []
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for data in ds1:
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buf.append(data[0][0])
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assert len(buf) == 2
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def test_skip_1():
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ds1 = ds.GeneratorDataset(generator_md, ["data"])
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# Here ds1 should be []
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ds1 = ds1.skip(7)
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buf = []
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for data in ds1:
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buf.append(data[0][0])
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assert len(buf) == 0
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def test_skip_2():
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ds1 = ds.GeneratorDataset(generator_md, ["data"])
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# Here ds1 should be [0, 1, 2, 3, 4]
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ds1 = ds1.skip(0)
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buf = []
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for data in ds1:
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buf.append(data[0][0])
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assert len(buf) == 5
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def test_skip_repeat_1():
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ds1 = ds.GeneratorDataset(generator_md, ["data"])
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# Here ds1 should be [0, 1, 2, 3, 4, 0, 1, 2, 3, 4]
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ds1 = ds1.repeat(2)
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# Here ds1 should be [3, 4, 0, 1, 2, 3, 4]
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ds1 = ds1.skip(3)
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buf = []
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for data in ds1:
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buf.append(data[0][0])
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assert len(buf) == 7
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def test_skip_repeat_2():
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ds1 = ds.GeneratorDataset(generator_md, ["data"])
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# Here ds1 should be [3, 4]
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ds1 = ds1.skip(3)
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# Here ds1 should be [3, 4, 3, 4]
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ds1 = ds1.repeat(2)
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buf = []
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for data in ds1:
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buf.append(data[0][0])
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assert len(buf) == 4
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def test_skip_repeat_3():
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ds1 = ds.GeneratorDataset(generator_md, ["data"])
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# Here ds1 should be [0, 1, 2, 3, 4, 0, 1, 2, 3, 4]
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ds1 = ds1.repeat(2)
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# Here ds1 should be [3, 4]
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ds1 = ds1.skip(8)
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# Here ds1 should be [3, 4, 3, 4, 3, 4]
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ds1 = ds1.repeat(3)
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buf = []
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for data in ds1:
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buf.append(data[0][0])
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assert len(buf) == 6
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if __name__ == "__main__":
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test_tf_skip()
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test_generator_skip()
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test_skip_1()
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test_skip_2()
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test_skip_repeat_1()
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test_skip_repeat_2()
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test_skip_repeat_3()
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