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!406 added first row crc check for when reading tfrecord files

Merge pull request !406 from Peilin/first-row-crc-check
tags/v0.2.0-alpha
mindspore-ci-bot Gitee 6 years ago
parent
commit
6369cf27bd
8 changed files with 127 additions and 11 deletions
  1. +51
    -6
      mindspore/ccsrc/dataset/engine/datasetops/source/tf_reader_op.cc
  2. +13
    -4
      mindspore/dataset/engine/datasets.py
  3. +34
    -0
      tests/ut/cpp/dataset/tfReader_op_test.cc
  4. BIN
      tests/ut/data/dataset/testTFBert5Rows/5TFDatas.data
  5. BIN
      tests/ut/data/dataset/testTFBert5Rows1/5TFDatas.data
  6. BIN
      tests/ut/data/dataset/testTFBert5Rows2/5TFDatas.data
  7. +1
    -0
      tests/ut/data/dataset/testTFTestAllTypes/invalidFile.txt
  8. +28
    -1
      tests/ut/python/dataset/test_tfreader_op.py

+ 51
- 6
mindspore/ccsrc/dataset/engine/datasetops/source/tf_reader_op.cc View File

@@ -42,6 +42,7 @@
#include "dataset/util/status.h"
#include "dataset/util/task_manager.h"
#include "dataset/util/wait_post.h"
#include "utils/system/crc32c.h"

namespace mindspore {
namespace dataset {
@@ -56,15 +57,58 @@ TFReaderOp::Builder::Builder()
builder_data_schema_ = std::make_unique<DataSchema>();
}

bool ValidateFirstRowCrc(const std::string &filename) {
std::ifstream reader;
reader.open(filename);
if (!reader) {
return false;
}

// read data
int64_t record_length = 0;
(void)reader.read(reinterpret_cast<char *>(&record_length), static_cast<std::streamsize>(sizeof(int64_t)));

// read crc from file
uint32_t masked_crc = 0;
(void)reader.read(reinterpret_cast<char *>(&masked_crc), static_cast<std::streamsize>(sizeof(uint32_t)));

// generate crc from data
uint32_t generated_crc =
system::Crc32c::GetMaskCrc32cValue(reinterpret_cast<char *>(&record_length), sizeof(int64_t));

return masked_crc == generated_crc;
}

Status TFReaderOp::Builder::ValidateInputs() const {
std::string err_msg;
err_msg += builder_num_workers_ <= 0 ? "Number of parallel workers is smaller or equal to 0\n" : "";
if (!builder_equal_rows_per_shard_) {
err_msg += builder_dataset_files_list_.size() < static_cast<uint32_t>(builder_num_devices_)
? "No enough tf_file files provided\n"
: "";

if (builder_num_workers_ <= 0) {
err_msg += "Number of parallel workers is smaller or equal to 0\n";
}

if (!builder_equal_rows_per_shard_ &&
builder_dataset_files_list_.size() < static_cast<uint32_t>(builder_num_devices_)) {
err_msg += "Not enough tfrecord files provided\n";
}

if (builder_device_id_ >= builder_num_devices_ || builder_num_devices_ < 1) {
err_msg += "Wrong sharding configs\n";
}
err_msg += builder_device_id_ >= builder_num_devices_ || builder_num_devices_ < 1 ? "Wrong sharding configs\n" : "";

std::vector<std::string> invalid_files(builder_dataset_files_list_.size());
auto it = std::copy_if(builder_dataset_files_list_.begin(), builder_dataset_files_list_.end(), invalid_files.begin(),
[](const std::string &filename) { return !ValidateFirstRowCrc(filename); });
invalid_files.resize(std::distance(invalid_files.begin(), it));

if (!invalid_files.empty()) {
err_msg += "The following files either cannot be opened, or are not valid tfrecord files:\n";

std::string accumulated_filenames = std::accumulate(
invalid_files.begin(), invalid_files.end(), std::string(""),
[](const std::string &accumulated, const std::string &next) { return accumulated + " " + next + "\n"; });
err_msg += accumulated_filenames;
}

return err_msg.empty() ? Status::OK() : Status(StatusCode::kUnexpectedError, __LINE__, __FILE__, err_msg);
}

@@ -523,6 +567,7 @@ Status TFReaderOp::LoadFile(const std::string &filename, const int64_t start_off
RETURN_IF_NOT_OK(LoadExample(&tf_file, &new_tensor_table, rows_read));
rows_read++;
}

// ignore crc footer
(void)reader.ignore(static_cast<std::streamsize>(sizeof(int32_t)));
rows_total++;


+ 13
- 4
mindspore/dataset/engine/datasets.py View File

@@ -926,13 +926,22 @@ class SourceDataset(Dataset):
List, files.
"""

def flat(lists):
return list(np.array(lists).flatten())

if not isinstance(patterns, list):
patterns = [patterns]

file_list = flat([glob.glob(file, recursive=True) for file in patterns])
file_list = []
unmatched_patterns = []
for pattern in patterns:
matches = [match for match in glob.glob(pattern, recursive=True) if os.path.isfile(match)]

if matches:
file_list.extend(matches)
else:
unmatched_patterns.append(pattern)

if unmatched_patterns:
raise ValueError("The following patterns did not match any files: ", unmatched_patterns)

if file_list: # not empty
return file_list
raise ValueError("The list of path names matching the patterns is empty.")


+ 34
- 0
tests/ut/cpp/dataset/tfReader_op_test.cc View File

@@ -697,3 +697,37 @@ TEST_F(MindDataTestTFReaderOp, TestTotalRowsBasic) {
TFReaderOp::CountTotalRows(&total_rows, filenames, 729, true);
ASSERT_EQ(total_rows, 60);
}

TEST_F(MindDataTestTFReaderOp, TestTFReaderInvalidFiles) {
// Start with an empty execution tree
auto my_tree = std::make_shared<ExecutionTree>();

std::string valid_file = datasets_root_path_ + "/testTFTestAllTypes/test.data";
std::string schema_file = datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json";
std::string invalid_file = datasets_root_path_ + "/testTFTestAllTypes/invalidFile.txt";
std::string nonexistent_file = "this/file/doesnt/exist";

std::shared_ptr<TFReaderOp> my_tfreader_op;
TFReaderOp::Builder builder;
builder.SetDatasetFilesList({invalid_file, valid_file, schema_file})
.SetRowsPerBuffer(16)
.SetNumWorkers(16);

std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
schema->LoadSchemaFile(schema_file, {});
builder.SetDataSchema(std::move(schema));

Status rc = builder.Build(&my_tfreader_op);
ASSERT_TRUE(!rc.IsOk());

builder.SetDatasetFilesList({invalid_file, valid_file, schema_file, nonexistent_file})
.SetRowsPerBuffer(16)
.SetNumWorkers(16);

schema = std::make_unique<DataSchema>();
schema->LoadSchemaFile(schema_file, {});
builder.SetDataSchema(std::move(schema));

rc = builder.Build(&my_tfreader_op);
ASSERT_TRUE(!rc.IsOk());
}

BIN
tests/ut/data/dataset/testTFBert5Rows/5TFDatas.data View File


BIN
tests/ut/data/dataset/testTFBert5Rows1/5TFDatas.data View File


BIN
tests/ut/data/dataset/testTFBert5Rows2/5TFDatas.data View File


+ 1
- 0
tests/ut/data/dataset/testTFTestAllTypes/invalidFile.txt View File

@@ -0,0 +1 @@
this is just a text file, not a valid tfrecord file.

+ 28
- 1
tests/ut/python/dataset/test_tfreader_op.py View File

@@ -32,7 +32,7 @@ def test_case_tf_shape():
ds1 = ds.TFRecordDataset(FILES, schema_file)
ds1 = ds1.batch(2)
for data in ds1.create_dict_iterator():
print(data)
logger.info(data)
output_shape = ds1.output_shapes()
assert (len(output_shape[-1]) == 1)

@@ -203,6 +203,32 @@ def test_tf_record_schema_columns_list():
a = row["col_sint32"]
assert "col_sint32" in str(info.value)

def test_case_invalid_files():
valid_file = "../data/dataset/testTFTestAllTypes/test.data"
invalid_file = "../data/dataset/testTFTestAllTypes/invalidFile.txt"
files = [invalid_file, valid_file, SCHEMA_FILE]

data = ds.TFRecordDataset(files, SCHEMA_FILE, shuffle=ds.Shuffle.FILES)

with pytest.raises(RuntimeError) as info:
row = data.create_dict_iterator().get_next()
assert "cannot be opened" in str(info.value)
assert "not valid tfrecord files" in str(info.value)
assert valid_file not in str(info.value)
assert invalid_file in str(info.value)
assert SCHEMA_FILE in str(info.value)

nonexistent_file = "this/file/does/not/exist"
files = [invalid_file, valid_file, SCHEMA_FILE, nonexistent_file]

with pytest.raises(ValueError) as info:
data = ds.TFRecordDataset(files, SCHEMA_FILE, shuffle=ds.Shuffle.FILES)
assert "did not match any files" in str(info.value)
assert valid_file not in str(info.value)
assert invalid_file not in str(info.value)
assert SCHEMA_FILE not in str(info.value)
assert nonexistent_file in str(info.value)

if __name__ == '__main__':
test_case_tf_shape()
test_case_tf_file()
@@ -212,3 +238,4 @@ if __name__ == '__main__':
test_tf_record_schema()
test_tf_record_shuffle()
test_tf_shard_equal_rows()
test_case_invalid_files()

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