forked from mindspore-Ecosystem/mindspore
init commit of concat dataset
change to use __add__ operation instead ds.concat
This commit is contained in:
ms_yan
parent
e2951707f2
commit
c0fa7b4b19
|
|
@ -53,6 +53,7 @@ static std::unordered_map<uint32_t, pFunction> g_parse_op_func_ = {{kStorage, &D
|
|||
{kRepeat, &DEPipeline::ParseRepeatOp},
|
||||
{kSkip, &DEPipeline::ParseSkipOp},
|
||||
{kZip, &DEPipeline::ParseZipOp},
|
||||
{kConcat, &DEPipeline::ParseConcatOp},
|
||||
{kRename, &DEPipeline::ParseRenameOp},
|
||||
{kDeviceQueue, &DEPipeline::ParseDeviceQueueOp},
|
||||
{kGenerator, &DEPipeline::ParseGeneratorOp},
|
||||
|
|
@ -757,6 +758,14 @@ Status DEPipeline::ParseZipOp(const py::dict &args, std::shared_ptr<DatasetOp> *
|
|||
return Status::OK();
|
||||
}
|
||||
|
||||
Status DEPipeline::ParseConcatOp(const py::dict &args, std::shared_ptr<DatasetOp> *ptr) {
|
||||
std::shared_ptr<ConcatOp::Builder> builder = std::make_shared<ConcatOp::Builder>();
|
||||
std::shared_ptr<ConcatOp> op;
|
||||
RETURN_IF_NOT_OK(builder->Build(&op));
|
||||
*ptr = op;
|
||||
return Status::OK();
|
||||
}
|
||||
|
||||
Status DEPipeline::ParseTFReaderOp(const py::dict &args, std::shared_ptr<DatasetOp> *ptr) {
|
||||
// Required arguments
|
||||
std::shared_ptr<TFReaderOp::Builder> builder = std::make_shared<TFReaderOp::Builder>();
|
||||
|
|
|
|||
|
|
@ -46,6 +46,7 @@ enum OpName {
|
|||
kSkip,
|
||||
kTake,
|
||||
kZip,
|
||||
kConcat,
|
||||
kMap,
|
||||
kFilter,
|
||||
kDeviceQueue,
|
||||
|
|
@ -127,6 +128,8 @@ class DEPipeline {
|
|||
|
||||
Status ParseZipOp(const py::dict &args, std::shared_ptr<DatasetOp> *ptr);
|
||||
|
||||
Status ParseConcatOp(const py::dict &args, std::shared_ptr<DatasetOp> *ptr);
|
||||
|
||||
Status ParseDeviceQueueOp(const py::dict &args, std::shared_ptr<DatasetOp> *ptr);
|
||||
|
||||
Status ParseTFReaderOp(const py::dict &args, std::shared_ptr<DatasetOp> *ptr);
|
||||
|
|
|
|||
|
|
@ -468,6 +468,7 @@ PYBIND11_MODULE(_c_dataengine, m) {
|
|||
.value("SKIP", OpName::kSkip)
|
||||
.value("TAKE", OpName::kTake)
|
||||
.value("ZIP", OpName::kZip)
|
||||
.value("CONCAT", OpName::kConcat)
|
||||
.value("MAP", OpName::kMap)
|
||||
.value("FILTER", OpName::kFilter)
|
||||
.value("DEVICEQUEUE", OpName::kDeviceQueue)
|
||||
|
|
|
|||
|
|
@ -42,6 +42,7 @@
|
|||
#include "dataset/engine/datasetops/source/tf_reader_op.h"
|
||||
#include "dataset/engine/datasetops/take_op.h"
|
||||
#include "dataset/engine/datasetops/zip_op.h"
|
||||
#include "dataset/engine/datasetops/concat_op.h"
|
||||
#include "dataset/engine/execution_tree.h"
|
||||
#include "dataset/util/status.h"
|
||||
|
||||
|
|
|
|||
|
|
@ -17,6 +17,7 @@ add_library(engine-datasetops OBJECT
|
|||
take_op.cc
|
||||
shuffle_op.cc
|
||||
zip_op.cc
|
||||
concat_op.cc
|
||||
filter_op.cc
|
||||
)
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,145 @@
|
|||
/**
|
||||
* Copyright 2020 Huawei Technologies Co., Ltd
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
#include <iomanip>
|
||||
#include <utility>
|
||||
|
||||
#include "common/utils.h"
|
||||
#include "dataset/core/config_manager.h"
|
||||
#include "dataset/engine/data_buffer.h"
|
||||
#include "dataset/engine/datasetops/concat_op.h"
|
||||
#include "dataset/engine/db_connector.h"
|
||||
#include "dataset/engine/execution_tree.h"
|
||||
|
||||
namespace mindspore {
|
||||
namespace dataset {
|
||||
// Builder constructor. Creates the builder object.
|
||||
ConcatOp::Builder::Builder() {
|
||||
std::shared_ptr<ConfigManager> cfg = GlobalContext::config_manager();
|
||||
builder_op_connector_size_ = cfg->op_connector_size();
|
||||
}
|
||||
|
||||
// The builder "build" method creates the final object.
|
||||
Status ConcatOp::Builder::Build(std::shared_ptr<ConcatOp> *ptr) {
|
||||
*ptr = std::make_shared<ConcatOp>(builder_op_connector_size_);
|
||||
return Status::OK();
|
||||
}
|
||||
|
||||
// Constructor of the ConcatOp.
|
||||
ConcatOp::ConcatOp(int32_t op_connector_size) : PipelineOp(op_connector_size), children_num_(0) {}
|
||||
|
||||
// A function that prints info about the Operator
|
||||
void ConcatOp::Print(std::ostream &out, bool show_all) const {
|
||||
// Always show the id and name as first line regardless if this is summary or detailed print
|
||||
out << "(" << std::setw(2) << operator_id_ << ") <ConcatOp>:";
|
||||
if (!show_all) {
|
||||
// Call the super class for displaying any common 1-liner info
|
||||
PipelineOp::Print(out, show_all);
|
||||
// Then show any custom derived-internal 1-liner info for this op
|
||||
out << "\n";
|
||||
} else {
|
||||
// Call the super class for displaying any common detailed info
|
||||
PipelineOp::Print(out, show_all);
|
||||
// Then show any custom derived-internal stuff
|
||||
out << "\nDatasets: " << children_num_ << "\n\n";
|
||||
}
|
||||
}
|
||||
|
||||
// Main entry point for Concat
|
||||
Status ConcatOp::operator()() {
|
||||
// The children_num_ parameter needs to be put here
|
||||
children_num_ = static_cast<int32_t>(child_.size());
|
||||
|
||||
TaskManager::FindMe()->Post();
|
||||
std::unique_ptr<DataBuffer> buf;
|
||||
RETURN_IF_NOT_OK(child_[0]->GetNextBuffer(&buf));
|
||||
|
||||
// Obtain columns_name_id_map from child_[0]
|
||||
column_name_id_map_ = child_[0]->column_name_id_map();
|
||||
if (column_name_id_map_.empty()) {
|
||||
RETURN_STATUS_UNEXPECTED("Child column name map cannot be empty!");
|
||||
}
|
||||
|
||||
int eof_count = 0;
|
||||
while (eof_count != children_num_) {
|
||||
for (int i = 0; i < children_num_; i++) {
|
||||
// 1. Throw the eof buffer when meet it
|
||||
if (buf->eof() || buf->eoe()) {
|
||||
RETURN_IF_NOT_OK(child_[i]->GetNextBuffer(&buf));
|
||||
}
|
||||
// 2. Do varification as for column name, column data type and rank of column data
|
||||
RETURN_IF_NOT_OK(Verify(i, buf));
|
||||
|
||||
// 3. Put the data into output_connector
|
||||
while (!buf->eoe() && !buf->eof()) {
|
||||
RETURN_IF_NOT_OK(out_connector_->Add(0, std::move(buf)));
|
||||
RETURN_IF_NOT_OK(child_[i]->GetNextBuffer(&buf));
|
||||
}
|
||||
|
||||
// 4. Throw the eoe buffer when meet it
|
||||
if (buf->eoe() && (!BitTest(op_ctrl_flags_, kDeOpRepeated) || BitTest(op_ctrl_flags_, kDeOpLastRepeat))) {
|
||||
RETURN_IF_NOT_OK(child_[i]->GetNextBuffer(&buf));
|
||||
}
|
||||
// 5. Add eoe buffer after get buffer from all child
|
||||
if (i == (children_num_ - 1)) {
|
||||
auto eoe_buffer = std::make_unique<DataBuffer>(0, DataBuffer::kDeBFlagEOE);
|
||||
RETURN_IF_NOT_OK(out_connector_->Add(0, std::move(eoe_buffer)));
|
||||
}
|
||||
if (buf->eof()) {
|
||||
eof_count++;
|
||||
}
|
||||
}
|
||||
}
|
||||
// 6. Add eof buffer in the end manually
|
||||
MS_LOG(DEBUG) << "Add the eof buffer manualy in the end.";
|
||||
auto eof_buffer = std::make_unique<DataBuffer>(0, DataBuffer::kDeBFlagEOF);
|
||||
RETURN_IF_NOT_OK(out_connector_->Add(0, std::move(eof_buffer)));
|
||||
|
||||
return Status::OK();
|
||||
}
|
||||
|
||||
Status ConcatOp::Verify(int32_t id, const std::unique_ptr<DataBuffer> &buf) {
|
||||
TensorRow new_row;
|
||||
buf->GetRow(0, &new_row);
|
||||
|
||||
if (id == 0) {
|
||||
// Obtain the column name, data type and data rank in child[0]
|
||||
column_name_id_ = child_[id]->column_name_id_map();
|
||||
for (auto item : new_row) {
|
||||
data_type_.push_back(item->type());
|
||||
data_rank_.push_back(item->Rank());
|
||||
}
|
||||
} else {
|
||||
// Compare the column name, data type and data rank with these in child[0]
|
||||
if (child_[id]->column_name_id_map() != column_name_id_) {
|
||||
RETURN_STATUS_UNEXPECTED("The column name or column order is not the same with previous dataset.");
|
||||
}
|
||||
int32_t index = 0;
|
||||
for (auto item : new_row) {
|
||||
if ((item->type() != data_type_[index]) || item->Rank() != data_rank_[index++]) {
|
||||
RETURN_STATUS_UNEXPECTED("The data type or data rank is not the same with previous dataset.");
|
||||
}
|
||||
}
|
||||
}
|
||||
return Status::OK();
|
||||
}
|
||||
|
||||
Status ConcatOp::PrepareNodePostAction() {
|
||||
RETURN_IF_NOT_OK(PipelineOp::PrepareNodePostAction());
|
||||
tree_->AddToRepeatStack(shared_from_this());
|
||||
return Status::OK();
|
||||
}
|
||||
} // namespace dataset
|
||||
} // namespace mindspore
|
||||
|
|
@ -0,0 +1,95 @@
|
|||
/**
|
||||
* Copyright 2020 Huawei Technologies Co., Ltd
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
#ifndef DATASET_ENGINE_DATASETOPS_CONCAT_OP_H_
|
||||
#define DATASET_ENGINE_DATASETOPS_CONCAT_OP_H_
|
||||
|
||||
#include <memory>
|
||||
#include <string>
|
||||
#include <unordered_map>
|
||||
#include <vector>
|
||||
#include "dataset/engine/datasetops/pipeline_op.h"
|
||||
|
||||
namespace mindspore {
|
||||
namespace dataset {
|
||||
class ConcatOp : public PipelineOp {
|
||||
public:
|
||||
// The nested builder class inside of the ConcatOp is used to help manage all of the arguments
|
||||
// for constructing it. This Concat op is very simple though, so this builder is really just
|
||||
// provided for a consistent look and feel for creators of Dataset operators overall.
|
||||
class Builder {
|
||||
public:
|
||||
// Builder constructor. Creates the builder object.
|
||||
// @note No default args
|
||||
// @return This is a constructor.
|
||||
Builder();
|
||||
|
||||
// Default destructor
|
||||
~Builder() = default;
|
||||
|
||||
// The builder "build" method creates the final object.
|
||||
// @return shared_ptr to the new StorageOp object
|
||||
Status Build(std::shared_ptr<ConcatOp> *);
|
||||
|
||||
private:
|
||||
int32_t builder_op_connector_size_;
|
||||
};
|
||||
|
||||
// Constructor of the ConcatOp.
|
||||
// @note The builder class should be used to call it
|
||||
// @param op_connector_size - connector size
|
||||
explicit ConcatOp(int32_t op_connector_size);
|
||||
|
||||
// Destructor
|
||||
~ConcatOp() = default;
|
||||
|
||||
// A print method typically used for debugging
|
||||
// @param out - The output stream to write output to
|
||||
// @param show_all - A bool to control if you want to show all info or just a summary
|
||||
void Print(std::ostream &out, bool show_all) const override;
|
||||
|
||||
// << Stream output operator overload
|
||||
// @notes This allows you to write the debug print info using stream operators
|
||||
// @param out - reference to the output stream being overloaded
|
||||
// @param ro - reference to the ConcatOp to display
|
||||
// @return - the output stream must be returned
|
||||
friend std::ostream &operator<<(std::ostream &out, const ConcatOp &ro) {
|
||||
ro.Print(out, false);
|
||||
return out;
|
||||
}
|
||||
|
||||
// All dataset ops operate by launching a thread (see ExecutionTree). This class functor will
|
||||
// provide the master loop that drives the logic for performing the work
|
||||
// @return Status - The error code return
|
||||
Status operator()() override;
|
||||
|
||||
// During tree prepare phase, operators may have specific post-operations to perform depending on
|
||||
// their role.
|
||||
// @notes Derived versions of this function should always call it's superclass version first
|
||||
// before providing their own implementations.
|
||||
Status PrepareNodePostAction() override;
|
||||
|
||||
private:
|
||||
Status Verify(int32_t id, const std::unique_ptr<DataBuffer> &buf);
|
||||
|
||||
int32_t children_num_; // The num of child of parent node.
|
||||
std::unordered_map<std::string, int32_t> column_name_id_; // Mapping between col index and col name
|
||||
std::vector<DataType> data_type_;
|
||||
std::vector<dsize_t> data_rank_;
|
||||
};
|
||||
} // namespace dataset
|
||||
} // namespace mindspore
|
||||
|
||||
#endif // DATASET_ENGINE_DATASETOPS_CONCAT_OP_H_
|
||||
|
|
@ -44,7 +44,7 @@ from .validators import check, check_batch, check_shuffle, check_map, check_filt
|
|||
check_rename, \
|
||||
check_take, check_project, check_imagefolderdatasetv2, check_mnist_cifar_dataset, check_manifestdataset, \
|
||||
check_tfrecorddataset, check_vocdataset, check_celebadataset, check_minddataset, check_generatordataset, \
|
||||
check_sync_wait, check_zip_dataset, check_add_column, check_textfiledataset
|
||||
check_sync_wait, check_zip_dataset, check_add_column, check_textfiledataset, check_concat
|
||||
from ..core.datatypes import mstype_to_detype, mstypelist_to_detypelist
|
||||
|
||||
try:
|
||||
|
|
@ -147,6 +147,9 @@ class Dataset:
|
|||
self._repeat_count = None
|
||||
self._sync = False
|
||||
|
||||
def __add__(self, datasets):
|
||||
return self.concat(datasets)
|
||||
|
||||
def get_args(self):
|
||||
"""
|
||||
Returns attributes (member variables) related to the current class.
|
||||
|
|
@ -560,6 +563,37 @@ class Dataset:
|
|||
raise TypeError("The zip function %s type error!" % (datasets))
|
||||
return ZipDataset(datasets)
|
||||
|
||||
@check_concat
|
||||
def concat(self, datasets):
|
||||
"""
|
||||
Concat the datasets in the input list of datasets, supported using "+" to reload concat operation.
|
||||
|
||||
Note:
|
||||
The column name，column data type and rank of column data should be the same in input datasets.
|
||||
|
||||
Args:
|
||||
datasets (list or class Dataset): A list of datasets or a single class Dataset
|
||||
to be concated together with this dataset.
|
||||
|
||||
Returns:
|
||||
ConcatDataset, dataset concated.
|
||||
|
||||
Examples:
|
||||
>>> import mindspore.dataset as ds
|
||||
>>> # ds1 and ds2 are instances of Dataset object
|
||||
>>> # creates a dataset by concating ds1 and ds2 with "+" operation
|
||||
>>> data1 = ds1 + ds2
|
||||
>>> # creates a dataset by concating ds1 and ds2 with concat operation
|
||||
>>> data1 = ds1.concat(ds2)
|
||||
"""
|
||||
if isinstance(datasets, Dataset):
|
||||
datasets = [self] + [datasets]
|
||||
elif isinstance(datasets, list):
|
||||
datasets = [self] + datasets
|
||||
else:
|
||||
raise TypeError("The concat_dataset function %s type error!" % (datasets))
|
||||
return ConcatDataset(datasets)
|
||||
|
||||
@check_rename
|
||||
def rename(self, input_columns, output_columns):
|
||||
"""
|
||||
|
|
@ -1658,6 +1692,39 @@ class ZipDataset(DatasetOp):
|
|||
return args
|
||||
|
||||
|
||||
class ConcatDataset(DatasetOp):
|
||||
"""
|
||||
The result of applying concat dataset operator to the input Dataset.
|
||||
|
||||
Args:
|
||||
datasets (list): A list of datasets to be concated together.
|
||||
|
||||
Raises:
|
||||
TypeError: If dataset is not an instance of Dataset.
|
||||
"""
|
||||
|
||||
def __init__(self, datasets):
|
||||
super().__init__()
|
||||
for dataset in datasets:
|
||||
if not isinstance(dataset, Dataset):
|
||||
raise TypeError("The parameter %s of concat has type error!" % (dataset))
|
||||
self.datasets = datasets
|
||||
for data in datasets:
|
||||
self.input.append(data)
|
||||
data.output.append(self)
|
||||
|
||||
def get_dataset_size(self):
|
||||
"""
|
||||
Get the number of batches in an epoch.
|
||||
|
||||
Return:
|
||||
Number, number of batches.
|
||||
"""
|
||||
children_sizes = [c.get_dataset_size() for c in self.input]
|
||||
dataset_size = np.sum(children_sizes)
|
||||
return dataset_size
|
||||
|
||||
|
||||
class RenameDataset(DatasetOp):
|
||||
"""
|
||||
The result of applying Rename operator to the input Dataset.
|
||||
|
|
|
|||
|
|
@ -156,6 +156,8 @@ class Iterator:
|
|||
op_type = OpName.BARRIER
|
||||
elif isinstance(dataset, de.ZipDataset):
|
||||
op_type = OpName.ZIP
|
||||
elif isinstance(dataset, de.ConcatDataset):
|
||||
op_type = OpName.CONCAT
|
||||
elif isinstance(dataset, de.MapDataset):
|
||||
op_type = OpName.MAP
|
||||
elif isinstance(dataset, de.FilterDataset):
|
||||
|
|
|
|||
|
|
@ -335,6 +335,10 @@ def create_node(node):
|
|||
# Create ZipDataset instance, giving dummy input dataset that will be overrided in the caller.
|
||||
pyobj = de.ZipDataset((de.Dataset(), de.Dataset()))
|
||||
|
||||
elif dataset_op == 'ConcatDataset':
|
||||
# Create ConcatDataset instance, giving dummy input dataset that will be overrided in the caller.
|
||||
pyobj = de.ConcatDataset((de.Dataset(), de.Dataset()))
|
||||
|
||||
elif dataset_op == 'RenameDataset':
|
||||
pyobj = de.Dataset().rename(node['input_columns'], node['output_columns'])
|
||||
|
||||
|
|
|
|||
|
|
@ -875,6 +875,26 @@ def check_zip_dataset(method):
|
|||
return new_method
|
||||
|
||||
|
||||
def check_concat(method):
|
||||
"""check the input arguments of concat_dataset method in `Dataset`."""
|
||||
|
||||
@wraps(method)
|
||||
def new_method(*args, **kwargs):
|
||||
param_dict = make_param_dict(method, args, kwargs)
|
||||
|
||||
# check datasets; required argument
|
||||
ds = param_dict.get("datasets")
|
||||
if ds is None:
|
||||
raise ValueError("datasets is not provided.")
|
||||
|
||||
if not isinstance(ds, (list, datasets.Dataset)):
|
||||
raise ValueError("datasets is not list or of type Dataset.")
|
||||
|
||||
return method(*args, **kwargs)
|
||||
|
||||
return new_method
|
||||
|
||||
|
||||
def check_rename(method):
|
||||
"""check the input arguments of rename."""
|
||||
|
||||
|
|
|
|||
|
|
@ -66,6 +66,7 @@ SET(DE_UT_SRCS
|
|||
take_op_test.cc
|
||||
text_file_op_test.cc
|
||||
filter_op_test.cc
|
||||
concat_op_test.cc
|
||||
)
|
||||
|
||||
add_executable(de_ut_tests ${DE_UT_SRCS})
|
||||
|
|
|
|||
|
|
@ -0,0 +1,125 @@
|
|||
/**
|
||||
* Copyright 2020 Huawei Technologies Co., Ltd
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at
|
||||
*
|
||||
* http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
#include <iostream>
|
||||
#include <memory>
|
||||
#include <vector>
|
||||
|
||||
#include "common/common.h"
|
||||
#include "common/utils.h"
|
||||
#include "dataset/core/client.h"
|
||||
#include "gtest/gtest.h"
|
||||
#include "utils/log_adapter.h"
|
||||
|
||||
namespace common = mindspore::common;
|
||||
|
||||
using namespace mindspore::dataset;
|
||||
using mindspore::MsLogLevel::INFO;
|
||||
using mindspore::ExceptionType::NoExceptionType;
|
||||
using mindspore::LogStream;
|
||||
|
||||
class MindDataTestConcatOp : public UT::DatasetOpTesting {};
|
||||
|
||||
|
||||
TEST_F(MindDataTestConcatOp, TestConcatProject) {
|
||||
/* Tree:
|
||||
*
|
||||
* OpId(2) ConcatOp
|
||||
* / \
|
||||
* OpId(0) TFReaderOp OpId(1) TFReaderOp
|
||||
*
|
||||
* Start with an empty execution tree
|
||||
*/
|
||||
MS_LOG(INFO) << "UT test TestConcatProject.";
|
||||
auto my_tree = std::make_shared<ExecutionTree>();
|
||||
|
||||
std::string dataset_path;
|
||||
dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";
|
||||
|
||||
// TFReaderOp1
|
||||
std::shared_ptr<TFReaderOp> my_tfreader_op1;
|
||||
TFReaderOp::Builder builder1;
|
||||
builder1.SetDatasetFilesList({dataset_path})
|
||||
.SetRowsPerBuffer(16)
|
||||
.SetWorkerConnectorSize(16)
|
||||
.SetNumWorkers(16);
|
||||
std::unique_ptr<DataSchema> schema1 = std::make_unique<DataSchema>();
|
||||
schema1->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
|
||||
builder1.SetDataSchema(std::move(schema1));
|
||||
Status rc = builder1.Build(&my_tfreader_op1);
|
||||
ASSERT_TRUE(rc.IsOk());
|
||||
rc = my_tree->AssociateNode(my_tfreader_op1);
|
||||
ASSERT_TRUE(rc.IsOk());
|
||||
|
||||
// TFReaderOp2
|
||||
std::shared_ptr<TFReaderOp> my_tfreader_op2;
|
||||
TFReaderOp::Builder builder2;
|
||||
builder2.SetDatasetFilesList({dataset_path})
|
||||
.SetRowsPerBuffer(16)
|
||||
.SetWorkerConnectorSize(16)
|
||||
.SetNumWorkers(16);
|
||||
std::unique_ptr<DataSchema> schema2 = std::make_unique<DataSchema>();
|
||||
schema2->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
|
||||
builder2.SetDataSchema(std::move(schema2));
|
||||
rc = builder2.Build(&my_tfreader_op2);
|
||||
ASSERT_TRUE(rc.IsOk());
|
||||
rc = my_tree->AssociateNode(my_tfreader_op2);
|
||||
ASSERT_TRUE(rc.IsOk());
|
||||
|
||||
// Creating ConcatOp
|
||||
std::shared_ptr<ConcatOp> concat_op;
|
||||
rc = ConcatOp::Builder().Build(&concat_op);
|
||||
EXPECT_TRUE(rc.IsOk());
|
||||
|
||||
rc = my_tree->AssociateNode(concat_op);
|
||||
EXPECT_TRUE(rc.IsOk());
|
||||
rc = concat_op->AddChild(std::move(my_tfreader_op1));
|
||||
EXPECT_TRUE(rc.IsOk());
|
||||
rc = concat_op->AddChild(std::move(my_tfreader_op2));
|
||||
EXPECT_TRUE(rc.IsOk());
|
||||
rc = my_tree->AssignRoot(concat_op);
|
||||
EXPECT_TRUE(rc.IsOk());
|
||||
rc = my_tree->Prepare();
|
||||
EXPECT_TRUE(rc.IsOk());
|
||||
|
||||
// Launch the tree execution to kick off threads and start running the pipeline
|
||||
MS_LOG(INFO) << "Launching my tree.";
|
||||
rc = my_tree->Launch();
|
||||
EXPECT_TRUE(rc.IsOk());
|
||||
|
||||
// Simulate a parse of data from our pipeline.
|
||||
std::shared_ptr<DatasetOp> rootNode = my_tree->root();
|
||||
|
||||
DatasetIterator di(my_tree);
|
||||
TensorRow tensor_list;
|
||||
rc = di.FetchNextTensorRow(&tensor_list);
|
||||
EXPECT_TRUE(rc.IsOk());
|
||||
|
||||
int row_count = 0;
|
||||
while (!tensor_list.empty()) {
|
||||
MS_LOG(INFO) << "Row display for row #: " << row_count << ".";
|
||||
|
||||
// Display the tensor by calling the printer on it
|
||||
for (int i = 0; i < tensor_list.size(); i++) {
|
||||
std::ostringstream ss;
|
||||
ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
|
||||
MS_LOG(INFO) << "Tensor print: " << common::SafeCStr(ss.str()) << ".";
|
||||
}
|
||||
rc = di.FetchNextTensorRow(&tensor_list);
|
||||
EXPECT_TRUE(rc.IsOk());
|
||||
row_count++;
|
||||
}
|
||||
ASSERT_EQ(row_count, 24); // Should be 24 rows fetched
|
||||
}
|
||||
|
|
@ -0,0 +1,377 @@
|
|||
# Copyright 2020 Huawei Technologies Co., Ltd
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
# ==============================================================================
|
||||
import mindspore.dataset as ds
|
||||
import mindspore.dataset.transforms.vision.py_transforms as F
|
||||
import mindspore.dataset.transforms.c_transforms as C
|
||||
import mindspore.common.dtype as mstype
|
||||
from mindspore import log as logger
|
||||
import numpy as np
|
||||
|
||||
|
||||
# In generator dataset: Number of rows is 3, its value is 0, 1, 2
|
||||
def generator():
|
||||
for i in range(3):
|
||||
yield np.array([i]),
|
||||
|
||||
|
||||
# In generator_10 dataset: Number of rows is 7, its value is 3, 4, 5 ... 10
|
||||
def generator_10():
|
||||
for i in range(3, 10):
|
||||
yield np.array([i]),
|
||||
|
||||
# In generator_20 dataset: Number of rows is 10, its value is 10, 11, 12 ... 20
|
||||
def generator_20():
|
||||
for i in range(10, 20):
|
||||
yield np.array([i]),
|
||||
|
||||
|
||||
def test_concat_01():
|
||||
"""
|
||||
Test concat: test concat 2 datasets that have the same column name and data type
|
||||
"""
|
||||
logger.info("test_concat_01")
|
||||
data1 = ds.GeneratorDataset(generator, ["col1"])
|
||||
data2 = ds.GeneratorDataset(generator_10, ["col1"])
|
||||
|
||||
data3 = data1 + data2
|
||||
|
||||
# Here i refers to index, d refers to data element
|
||||
for i, d in enumerate(data3):
|
||||
logger.info("data: %i", d[0][0])
|
||||
assert i == d[0][0]
|
||||
|
||||
assert sum([1 for _ in data3]) == 10
|
||||
|
||||
|
||||
def test_concat_02():
|
||||
"""
|
||||
Test concat: test concat 2 datasets using concat operation not "+" operation
|
||||
"""
|
||||
logger.info("test_concat_02")
|
||||
data1 = ds.GeneratorDataset(generator, ["col1"])
|
||||
data2 = ds.GeneratorDataset(generator_10, ["col1"])
|
||||
|
||||
data3 = data1.concat(data2)
|
||||
|
||||
# Here i refers to index, d refers to data element
|
||||
for i, d in enumerate(data3):
|
||||
logger.info("data: %i", d[0][0])
|
||||
assert i == d[0][0]
|
||||
|
||||
assert sum([1 for _ in data3]) == 10
|
||||
|
||||
|
||||
def test_concat_03():
|
||||
"""
|
||||
Test concat: test concat dataset that has different column
|
||||
"""
|
||||
logger.info("test_concat_03")
|
||||
data1 = ds.GeneratorDataset(generator, ["col1"])
|
||||
data2 = ds.GeneratorDataset(generator_10, ["col2"])
|
||||
|
||||
data3 = data1 + data2
|
||||
|
||||
try:
|
||||
for i, d in enumerate(data3):
|
||||
pass
|
||||
assert False
|
||||
except RuntimeError:
|
||||
pass
|
||||
|
||||
|
||||
def test_concat_04():
|
||||
"""
|
||||
Test concat: test concat dataset that has different rank
|
||||
"""
|
||||
logger.info("test_concat_04")
|
||||
data1 = ds.GeneratorDataset(generator, ["col1"])
|
||||
data2 = ds.GeneratorDataset(generator_10, ["col2"])
|
||||
data2 = data2.batch(3)
|
||||
|
||||
data3 = data1 + data2
|
||||
|
||||
try:
|
||||
for i, d in enumerate(data3):
|
||||
pass
|
||||
assert False
|
||||
except RuntimeError:
|
||||
pass
|
||||
|
||||
|
||||
def test_concat_05():
|
||||
"""
|
||||
Test concat: test concat dataset that has different data type
|
||||
"""
|
||||
logger.info("test_concat_05")
|
||||
data1 = ds.GeneratorDataset(generator, ["col1"])
|
||||
data2 = ds.GeneratorDataset(generator_10, ["col1"])
|
||||
|
||||
type_cast_op = C.TypeCast(mstype.float32)
|
||||
data1 = data1.map(input_columns=["col1"], operations=type_cast_op)
|
||||
|
||||
data3 = data1 + data2
|
||||
|
||||
try:
|
||||
for i, d in enumerate(data3):
|
||||
pass
|
||||
assert False
|
||||
except RuntimeError:
|
||||
pass
|
||||
|
||||
|
||||
def test_concat_06():
|
||||
"""
|
||||
Test concat: test concat muti datasets in one time
|
||||
"""
|
||||
logger.info("test_concat_06")
|
||||
data1 = ds.GeneratorDataset(generator, ["col1"])
|
||||
data2 = ds.GeneratorDataset(generator_10, ["col1"])
|
||||
data3 = ds.GeneratorDataset(generator_20, ["col1"])
|
||||
|
||||
dataset = data1 + data2 + data3
|
||||
|
||||
# Here i refers to index, d refers to data element
|
||||
for i, d in enumerate(dataset):
|
||||
logger.info("data: %i", d[0][0])
|
||||
assert i == d[0][0]
|
||||
|
||||
assert sum([1 for _ in dataset]) == 20
|
||||
|
||||
|
||||
def test_concat_07():
|
||||
"""
|
||||
Test concat: test concat one dataset with multi datasets (datasets list)
|
||||
"""
|
||||
logger.info("test_concat_07")
|
||||
data1 = ds.GeneratorDataset(generator, ["col1"])
|
||||
data2 = ds.GeneratorDataset(generator_10, ["col1"])
|
||||
data3 = ds.GeneratorDataset(generator_20, ["col1"])
|
||||
|
||||
dataset = [data2] + [data3]
|
||||
data4 = data1 + dataset
|
||||
|
||||
# Here i refers to index, d refers to data element
|
||||
for i, d in enumerate(data4):
|
||||
logger.info("data: %i", d[0][0])
|
||||
assert i == d[0][0]
|
||||
|
||||
assert sum([1 for _ in data4]) == 20
|
||||
|
||||
|
||||
def test_concat_08():
|
||||
"""
|
||||
Test concat: test concat 2 datasets, and then repeat
|
||||
"""
|
||||
logger.info("test_concat_08")
|
||||
data1 = ds.GeneratorDataset(generator, ["col1"])
|
||||
data2 = ds.GeneratorDataset(generator_10, ["col1"])
|
||||
|
||||
data3 = data1 + data2
|
||||
data3 = data3.repeat(2)
|
||||
|
||||
# Here i refers to index, d refers to data element
|
||||
for i, d in enumerate(data3):
|
||||
logger.info("data: %i", d[0][0])
|
||||
assert i % 10 == d[0][0]
|
||||
|
||||
assert sum([1 for _ in data3]) == 20
|
||||
|
||||
|
||||
def test_concat_09():
|
||||
"""
|
||||
Test concat: test concat 2 datasets, both of them have been repeat before
|
||||
"""
|
||||
logger.info("test_concat_09")
|
||||
data1 = ds.GeneratorDataset(generator, ["col1"])
|
||||
data2 = ds.GeneratorDataset(generator_10, ["col1"])
|
||||
|
||||
data1 = data1.repeat(2)
|
||||
data2 = data2.repeat(2)
|
||||
data3 = data1 + data2
|
||||
|
||||
res = [0, 1, 2, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 3, 4, 5, 6, 7, 8, 9]
|
||||
# Here i refers to index, d refers to data element
|
||||
for i, d in enumerate(data3):
|
||||
logger.info("data: %i", d[0][0])
|
||||
assert res[i] == d[0][0]
|
||||
|
||||
assert sum([1 for _ in data3]) == 20
|
||||
|
||||
|
||||
def test_concat_10():
|
||||
"""
|
||||
Test concat: test concat 2 datasets, one of them have repeat before
|
||||
"""
|
||||
logger.info("test_concat_10")
|
||||
data1 = ds.GeneratorDataset(generator, ["col1"])
|
||||
data2 = ds.GeneratorDataset(generator_10, ["col1"])
|
||||
|
||||
data1 = data1.repeat(2)
|
||||
data3 = data1 + data2
|
||||
|
||||
res = [0, 1, 2, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
|
||||
# Here i refers to index, d refers to data element
|
||||
for i, d in enumerate(data3):
|
||||
logger.info("data: %i", d[0][0])
|
||||
assert res[i] == d[0][0]
|
||||
|
||||
assert sum([1 for _ in data3]) == 13
|
||||
|
||||
|
||||
def test_concat_11():
|
||||
"""
|
||||
Test concat: test dataset batch then concat
|
||||
"""
|
||||
logger.info("test_concat_11")
|
||||
data1 = ds.GeneratorDataset(generator, ["col1"])
|
||||
data2 = ds.GeneratorDataset(generator_20, ["col1"])
|
||||
|
||||
data1 = data1.batch(3)
|
||||
data2 = data2.batch(5)
|
||||
|
||||
data3 = data1 + data2
|
||||
res = [0, 10, 15, 20]
|
||||
|
||||
# Here i refers to index, d refers to data element
|
||||
for i, d in enumerate(data3):
|
||||
logger.info("data: %i", d[0][0])
|
||||
assert res[i] == d[0][0]
|
||||
|
||||
assert sum([1 for _ in data3]) == 3
|
||||
|
||||
|
||||
def test_concat_12():
|
||||
"""
|
||||
Test concat: test dataset concat then shuffle
|
||||
"""
|
||||
logger.info("test_concat_12")
|
||||
data1 = ds.GeneratorDataset(generator, ["col1"])
|
||||
data2 = ds.GeneratorDataset(generator_10, ["col1"])
|
||||
|
||||
data1.set_dataset_size(3)
|
||||
data2.set_dataset_size(7)
|
||||
|
||||
data3 = data1 + data2
|
||||
res = [8, 6, 2, 5, 0, 4, 9, 3, 7, 1]
|
||||
|
||||
ds.config.set_seed(1)
|
||||
assert data3.get_dataset_size() == 10
|
||||
data3 = data3.shuffle(buffer_size=10)
|
||||
|
||||
# Here i refers to index, d refers to data element
|
||||
for i, d in enumerate(data3):
|
||||
logger.info("data: %i", d[0][0])
|
||||
assert res[i] == d[0][0]
|
||||
|
||||
assert sum([1 for _ in data3]) == 10
|
||||
|
||||
|
||||
def test_concat_13():
|
||||
"""
|
||||
Test concat: test dataset batch then shuffle and concat
|
||||
"""
|
||||
logger.info("test_concat_13")
|
||||
data1 = ds.GeneratorDataset(generator, ["col1"])
|
||||
data2 = ds.GeneratorDataset(generator_20, ["col1"])
|
||||
|
||||
data1.set_dataset_size(3)
|
||||
data2.set_dataset_size(10)
|
||||
|
||||
data1 = data1.batch(3)
|
||||
data2 = data2.batch(5)
|
||||
|
||||
data3 = data1 + data2
|
||||
res = [15, 0, 10]
|
||||
|
||||
ds.config.set_seed(1)
|
||||
assert data3.get_dataset_size() == 3
|
||||
|
||||
data3 = data3.shuffle(buffer_size=int(data3.get_dataset_size()))
|
||||
|
||||
# Here i refers to index, d refers to data element
|
||||
for i, d in enumerate(data3):
|
||||
logger.info("data: %i", d[0][0])
|
||||
assert res[i] == d[0][0]
|
||||
|
||||
assert sum([1 for _ in data3]) == 3
|
||||
|
||||
|
||||
def test_concat_14():
|
||||
"""
|
||||
Test concat: create dataset with different dataset folder, and do diffrent operation then concat
|
||||
"""
|
||||
logger.info("test_concat_14")
|
||||
DATA_DIR = "../data/dataset/testPK/data"
|
||||
DATA_DIR2 = "../data/dataset/testImageNetData/train/"
|
||||
|
||||
data1 = ds.ImageFolderDatasetV2(DATA_DIR, num_samples=3)
|
||||
data2 = ds.ImageFolderDatasetV2(DATA_DIR2, num_samples=2)
|
||||
|
||||
transforms1 = F.ComposeOp([F.Decode(),
|
||||
F.Resize((224,224)),
|
||||
F.ToTensor()])
|
||||
|
||||
data1 = data1.map(input_columns=["image"], operations=transforms1())
|
||||
data2 = data2.map(input_columns=["image"], operations=transforms1())
|
||||
data3 = data1 + data2
|
||||
|
||||
expected, output = [], []
|
||||
for d in data1:
|
||||
expected.append(d[0])
|
||||
for d in data2:
|
||||
expected.append(d[0])
|
||||
for d in data3:
|
||||
output.append(d[0])
|
||||
|
||||
assert len(expected) == len(output)
|
||||
np.array_equal(np.array(output), np.array(expected))
|
||||
|
||||
assert sum([1 for _ in data3]) == 5
|
||||
assert data3.get_dataset_size() == 5
|
||||
|
||||
|
||||
def test_concat_15():
|
||||
"""
|
||||
Test concat: create dataset with different format of dataset file, and then concat
|
||||
"""
|
||||
logger.info("test_concat_15")
|
||||
DATA_DIR = "../data/dataset/testPK/data"
|
||||
DATA_DIR2 = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"]
|
||||
|
||||
data1 = ds.ImageFolderDatasetV2(DATA_DIR)
|
||||
data2 = ds.TFRecordDataset(DATA_DIR2, columns_list=["image"])
|
||||
|
||||
data1 = data1.project(["image"])
|
||||
data3 = data1 + data2
|
||||
|
||||
assert sum([1 for _ in data3]) == 47
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
test_concat_01()
|
||||
test_concat_02()
|
||||
test_concat_03()
|
||||
test_concat_04()
|
||||
test_concat_05()
|
||||
test_concat_06()
|
||||
test_concat_07()
|
||||
test_concat_08()
|
||||
test_concat_09()
|
||||
test_concat_10()
|
||||
test_concat_11()
|
||||
test_concat_12()
|
||||
test_concat_13()
|
||||
test_concat_14()
|
||||
test_concat_15()
|
||||
Loading…
Reference in New Issue