def test_issue_65():
"""test file reader when file name is illegal."""
reader = ShardReader()
file_name = os.path.join(os.getcwd(), "imagenet.mindrecord01qwert")
with pytest.raises(Exception) as e:
reader.open(file_name)
assert str(e.value) == "[MRMOpenError]: error_code: 1347690596, " \
"error_msg: " \
"MindRecord File could not open successfully."
def test_issue_84():
"""test file reader when db does not match."""
writer = FileWriter(CV_FILE_NAME, FILES_NUM)
data = get_data("../data/mindrecord/testImageNetData/")
cv_schema_json = {"file_name": {"type": "string"},
"label": {"type": "number"}, "data": {"type": "bytes"}}
writer.add_schema(cv_schema_json, "img_schema")
writer.add_index(["file_name", "label"])
writer.write_raw_data(data)
writer.commit()
writer = FileWriter(NLP_FILE_NAME, FILES_NUM)
data = list(get_nlp_data("../data/mindrecord/testAclImdbData/pos",
"../data/mindrecord/testAclImdbData/vocab.txt",
10))
nlp_schema_json = {"id": {"type": "string"}, "label": {"type": "number"},
"rating": {"type": "number"},
"input_ids": {"type": "array",
"items": {"type": "number"}},
"input_mask": {"type": "array",
"items": {"type": "number"}},
"segment_ids": {"type": "array",
"items": {"type": "number"}}
}
writer.set_header_size(1 << 14)
writer.set_page_size(1 << 15)
writer.add_schema(nlp_schema_json, "nlp_schema")
writer.add_index(["id", "rating"])
writer.write_raw_data(data)
writer.commit()
reader = ShardReader()
os.rename("imagenet.mindrecord1.db", "imagenet.mindrecord1.db.bk")
os.rename("aclImdb.mindrecord1.db", "imagenet.mindrecord1.db")
file_name = os.path.join(os.getcwd(), "imagenet.mindrecord1")
with pytest.raises(Exception) as e:
reader.open(file_name)
assert str(e.value) == "[MRMOpenError]: error_code: 1347690596, " \
"error_msg: " \
"MindRecord File could not open successfully."
os.rename("imagenet.mindrecord1.db", "aclImdb.mindrecord1.db")
paths = ["{}{}".format(NLP_FILE_NAME, str(x).rjust(1, '0'))
for x in range(FILES_NUM)]
for item in paths:
os.remove("{}".format(item))
os.remove("{}.db".format(item))
os.rename("imagenet.mindrecord1.db.bk", "imagenet.mindrecord1.db")
paths = ["{}{}".format(CV_FILE_NAME, str(x).rjust(1, '0'))
for x in range(FILES_NUM)]
for item in paths:
os.remove("{}".format(item))
os.remove("{}.db".format(item))
def test_file_writer_fail_add_index():
"""test file writer, read when failed on adding index."""
data_raw = get_data("../data/mindrecord/testImageNetData/")
schema_json = {"file_name": {"type": "string"}, "label": {"type": "number"}}
header = ShardHeader()
schema = header.build_schema(schema_json, ["data"], "img") # create schema
schema_id = header.add_schema(schema) # add schema
with pytest.raises(TypeError, match="missing 1 "):
ret = header.add_index_fields()
assert ret == FAILED
with pytest.raises(MRMAddIndexError):
index_fields = []
ret = header.add_index_fields(index_fields)
assert ret == FAILED
file_name = os.path.join(os.getcwd(), "test_001.mindrecord") # set output filename
writer = ShardWriter() # test_file_writer
ret = writer.open([file_name])
assert ret == SUCCESS, 'failed on opening files.'
ret = writer.set_shard_header(header) # write header
assert ret == SUCCESS, 'failed on setting header.'
ret = writer.write_raw_cv_data({schema_id: data_raw})
assert ret == SUCCESS, 'failed on writing raw data.'
ret = writer.commit() # commit data
assert ret == SUCCESS, "commit failed"
# ShardIndexGenerator
generator = ShardIndexGenerator(os.path.realpath(file_name))
generator.build()
generator.write_to_db()
reader = ShardReader()
ret = reader.open(file_name)
reader.launch()
index = 0
_, blob_fields = reader.get_blob_fields()
iterator = reader.get_next()
while iterator:
for blob, raw in iterator:
raw[blob_fields[0]] = bytes(blob)
logger.info("#item{}: {}".format(index, raw))
index += 1
iterator = reader.get_next()
reader.finish()
reader.close()
os.remove("{}".format(file_name))
os.remove("{}.db".format(file_name))
def test_nlp_file_reader():
"""test nlp file reader using shard api"""
dataset = ShardReader()
dataset.open(NLP_FILE_NAME + "0")
dataset.launch()
index = 0
iterator = dataset.get_next()
while iterator:
for _, raw in iterator:
logger.info("#item{}: {}".format(index, raw))
index += 1
iterator = dataset.get_next()
dataset.finish()
dataset.close()
def test_mkv_file_reader_with_exactly_schema():
"""test mkv file reader using shard api"""
dataset = ShardReader()
dataset.open(MKV_FILE_NAME + "0")
dataset.launch()
index = 0
_, blob_fields = dataset.get_blob_fields()
iterator = dataset.get_next()
while iterator:
for blob, raw in iterator:
raw[blob_fields[0]] = bytes(blob)
logger.info("#item{}: {}".format(index, raw))
index += 1
iterator = dataset.get_next()
dataset.finish()
dataset.close()
paths = [
"{}{}".format(MKV_FILE_NAME,
str(x).rjust(1, '0')) for x in range(1)
]
for x in paths:
os.remove("{}".format(x))
os.remove("{}.db".format(x))
def test_cv_file_reader():
"""test cv file reader using shard api"""
dataset = ShardReader()
dataset.open(CV_FILE_NAME + "0")
dataset.launch()
index = 0
_, blob_fields = dataset.get_blob_fields()
iterator = dataset.get_next()
while iterator:
for blob, raw in iterator:
raw[blob_fields[0]] = bytes(blob)
logger.info("#item{}: {}".format(index, raw))
index += 1
iterator = dataset.get_next()
dataset.finish()
dataset.close()