提交 6369cf27 编写于 作者: M mindspore-ci-bot 提交者: Gitee

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

Merge pull request !406 from Peilin/first-row-crc-check
......@@ -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++;
......
......@@ -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.")
......
......@@ -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());
}
this is just a text file, not a valid tfrecord 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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