def add_eval_data(self, filename: str, doc_index: str = "eval_document", label_index: str = "label",
batch_size: Optional[int] = None, preprocessor: Optional[PreProcessor] = None,
max_docs: Union[int, bool] = None):
"""
Adds a SQuAD-formatted file to the DocumentStore in order to be able to perform evaluation on it.
If a jsonl file and a batch_size is passed to the function, documents are loaded batchwise
from disk and also indexed batchwise to the DocumentStore in order to prevent out of memory errors.
:param filename: Name of the file containing evaluation data (json or jsonl)
:param doc_index: Elasticsearch index where evaluation documents should be stored
:param label_index: Elasticsearch index where labeled questions should be stored
:param batch_size: Optional number of documents that are loaded and processed at a time.
When set to None (default) all documents are processed at once.
:param preprocessor: Optional PreProcessor to preprocess evaluation documents.
It can be used for splitting documents into passages (and assigning labels to corresponding passages).
Currently the PreProcessor does not support split_by sentence, cleaning nor split_overlap != 0.
When set to None (default) preprocessing is disabled.
:param max_docs: Optional number of documents that will be loaded.
When set to None (default) all available eval documents are used.
"""
# TODO improve support for PreProcessor when adding eval data
if preprocessor is not None:
assert preprocessor.split_by != "sentence", f"Split by sentence not supported.\n" \
f"Please set 'split_by' to either 'word' or 'passage' in the supplied PreProcessor."
assert preprocessor.split_overlap == 0, f"Overlapping documents are currently not supported when adding eval data.\n" \
f"Please set 'split_overlap=0' in the supplied PreProcessor."
assert preprocessor.clean_empty_lines == False, f"clean_empty_lines currently not supported when adding eval data.\n" \
f"Please set 'clean_empty_lines=False' in the supplied PreProcessor."
assert preprocessor.clean_whitespace == False, f"clean_whitespace is currently not supported when adding eval data.\n" \
f"Please set 'clean_whitespace=False' in the supplied PreProcessor."
assert preprocessor.clean_header_footer == False, f"clean_header_footer is currently not supported when adding eval data.\n" \
f"Please set 'clean_header_footer=False' in the supplied PreProcessor."
file_path = Path(filename)
if file_path.suffix == ".json":
if batch_size is None:
docs, labels = eval_data_from_json(filename, max_docs=max_docs, preprocessor=preprocessor)
self.write_documents(docs, index=doc_index)
self.write_labels(labels, index=label_index)
else:
jsonl_filename = (file_path.parent / (file_path.stem + '.jsonl')).as_posix()
logger.info(f"Adding evaluation data batch-wise is not compatible with json-formatted SQuAD files. "
f"Converting json to jsonl to: {jsonl_filename}")
squad_json_to_jsonl(filename, jsonl_filename)
self.add_eval_data(jsonl_filename, doc_index, label_index, batch_size)
elif file_path.suffix == ".jsonl":
for docs, labels in eval_data_from_jsonl(filename, batch_size, max_docs=max_docs, preprocessor=preprocessor):
if docs:
self.write_documents(docs, index=doc_index)
if labels:
self.write_labels(labels, index=label_index)
else:
logger.error("File needs to be in json or jsonl format.")
def add_eval_data(self,
filename: str,
doc_index: str = "eval_document",
label_index: str = "label",
batch_size: Optional[int] = None):
"""
Adds a SQuAD-formatted file to the DocumentStore in order to be able to perform evaluation on it.
If a jsonl file and a batch_size is passed to the function, documents are loaded batchwise
from disk and also indexed batchwise to the DocumentStore in order to prevent out of memory errors.
:param filename: Name of the file containing evaluation data (json or jsonl)
:type filename: str
:param doc_index: Elasticsearch index where evaluation documents should be stored
:type doc_index: str
:param label_index: Elasticsearch index where labeled questions should be stored
:type label_index: str
:param batch_size: Number of documents that are loaded and processed at a time.
Only works with jsonl formatted files. Setting batch_size and
using a json formatted file will convert the json to jsonl prior
to adding eval data.
:type batch_size: int
"""
if filename.endswith(".json"):
if batch_size is None:
docs, labels = eval_data_from_json(filename)
self.write_documents(docs, index=doc_index)
self.write_labels(labels, index=label_index)
else:
jsonl_filename = filename + "l"
logger.info(
f"Adding evaluation data batch-wise is not compatible with json-formatted SQuAD files. "
f"Converting json to jsonl to: {jsonl_filename}")
squad_json_to_jsonl(filename, jsonl_filename)
self.add_eval_data(jsonl_filename, doc_index, label_index,
batch_size)
elif filename.endswith(".jsonl"):
for docs, labels in eval_data_from_jsonl(filename, batch_size):
if docs:
self.write_documents(docs, index=doc_index)
if labels:
self.write_labels(labels, index=label_index)
else:
logger.error("File needs to be in json or jsonl format.")