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https://github.com/explosion/spaCy.git
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Make spacy convert output docbin
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parent
0d22c6e006
commit
7a846921a3
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@ -4,8 +4,9 @@ import srsly
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import re
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import sys
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from .converters import conllu2json, iob2json, conll_ner2json
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from .converters import ner_jsonl2json
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from ..tokens import DocBin
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from ..gold.converters import iob2docs, conll_ner2docs, json2docs
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from ..gold.converters import ner_jsonl2docs
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# Converters are matched by file extension except for ner/iob, which are
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@ -13,13 +14,13 @@ from .converters import ner_jsonl2json
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# entry to this dict with the file extension mapped to the converter function
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# imported from /converters.
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DOC_CONVERTERS = {
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"conllubio": conllu2doc,
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"conllu": conllu2doc,
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"conll": conllu2doc,
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"ner": conll_ner2doc,
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"iob": iob2doc,
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"jsonl": ner_jsonl2doc,
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CONVERTERS = {
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#"conllubio": conllu2docs, TODO
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#"conllu": conllu2docs, TODO
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#"conll": conllu2docs, TODO
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"ner": conll_ner2docs,
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"iob": iob2docs,
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"jsonl": ner_jsonl2docs,
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"json": json2docs,
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}
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@ -42,59 +43,32 @@ FILE_TYPES_STDOUT = ("json", "jsonl")
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def convert(
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# fmt: off
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input_file: ("Input file", "positional", None, str),
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output_dir: ("Output directory. '-' for stdout.", "positional", None, str) = "-",
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file_type: (f"Type of data to produce: {FILE_TYPES}", "option", "t", str, FILE_TYPES) = "json",
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input_path: ("Input file or directory", "positional", None, Path),
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output_dir: ("Output directory.", "positional", None, Path),
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file_type: (f"Type of data to produce: {FILE_TYPES}", "option", "t", str, FILE_TYPES) = "spacy",
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n_sents: ("Number of sentences per doc (0 to disable)", "option", "n", int) = 1,
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seg_sents: ("Segment sentences (for -c ner)", "flag", "s") = False,
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model: ("Model for sentence segmentation (for -s)", "option", "b", str) = None,
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morphology: ("Enable appending morphology to tags", "flag", "m", bool) = False,
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merge_subtokens: ("Merge CoNLL-U subtokens", "flag", "T", bool) = False,
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converter: (f"Converter: {tuple(CONVERTERS.keys())}", "option", "c", str) = "auto",
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ner_map_path: ("NER tag mapping (as JSON-encoded dict of entity types)", "option", "N", Path) = None,
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ner_map: ("NER tag mapping (as JSON-encoded dict of entity types)", "option", "N", Path) = None,
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lang: ("Language (if tokenizer required)", "option", "l", str) = None,
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# fmt: on
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):
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"""
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Convert files into JSON format for use with train command and other
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experiment management functions. If no output_dir is specified, the data
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is written to stdout, so you can pipe them forward to a JSON file:
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$ spacy convert some_file.conllu > some_file.json
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Convert files into json or DocBin format for use with train command and other
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experiment management functions.
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"""
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cli_args = locals()
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no_print = output_dir == "-"
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output_dir = Path(output_dir) if output_dir != "-" else "-"
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msg = Printer(no_print=no_print)
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input_path = Path(input_file)
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if file_type not in FILE_TYPES_STDOUT and output_dir == "-":
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# TODO: support msgpack via stdout in srsly?
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msg.fail(
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f"Can't write .{file_type} data to stdout",
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"Please specify an output directory.",
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exits=1,
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)
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if not input_path.exists():
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msg.fail("Input file not found", input_path, exits=1)
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if output_dir != "-" and not Path(output_dir).exists():
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msg.fail("Output directory not found", output_dir, exits=1)
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input_data = input_path.open("r", encoding="utf-8").read()
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if converter == "auto":
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converter = input_path.suffix[1:]
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if converter == "ner" or converter == "iob":
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converter_autodetect = autodetect_ner_format(input_data)
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if converter_autodetect == "ner":
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msg.info("Auto-detected token-per-line NER format")
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converter = converter_autodetect
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elif converter_autodetect == "iob":
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msg.info("Auto-detected sentence-per-line NER format")
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converter = converter_autodetect
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else:
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msg.warn(
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"Can't automatically detect NER format. Conversion may not succeed. See https://spacy.io/api/cli#convert"
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)
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if converter not in CONVERTERS:
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msg.fail(f"Can't find converter for {converter}", exits=1)
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ner_map = None
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if ner_map_path is not None:
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ner_map = srsly.read_json(ner_map_path)
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verify_cli_args(msg, **cli_args)
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converter = _get_converter(msg, converter, input_path)
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ner_map = srsly.read_json(ner_map) if ner_map is not None else None
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for input_loc in walk_directory(input_path):
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input_data = input_loc.open("r", encoding="utf-8").read()
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# Use converter function to convert data
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func = CONVERTERS[converter]
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docs = func(
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@ -108,27 +82,19 @@ def convert(
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no_print=no_print,
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ner_map=ner_map,
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)
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if write_json:
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suffix = f".{file_type}"
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subpath = input_loc.relative_to(input_path)
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output_file = (output_dir / subpath).with_suffix(suffix)
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if not output_file.parent.exists():
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output_file.parent.mkdir(parents=True)
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if file_type == "json":
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data = docs2json(docs)
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srsly.write_json(output_file, docs2json(docs))
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else:
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data = DocBin(attrs=ALL_ATTRS, docs=docs).to_bytes()
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if output_dir == "-":
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if write_json:
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srsly.write_json("-", data)
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else:
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sys.stdout.write(data)
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else:
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# Export data to a file
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if write_json:
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suffix = f".{file_type}"
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output_file = output_dir / input_path.parts[-1].with_suffix(suffix)
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srsly.write_json(output_file, data)
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else:
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output_file = output_dir / input_path.parts[-1].with_suffix("spacy")
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with output_file.open("wb") as file_:
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file_.write(data)
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msg.good(f"Generated output file ({len(data)} documents): {output_file}")
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msg.good(f"Generated output file ({len(docs)} documents): {output_file}")
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def autodetect_ner_format(input_data):
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@ -148,3 +114,102 @@ def autodetect_ner_format(input_data):
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if format_guesses["ner"] == 0 and format_guesses["iob"] > 0:
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return "iob"
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return None
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def walk_directory(path):
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if not path.is_dir():
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return [path]
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paths = [path]
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locs = []
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seen = set()
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for path in paths:
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if str(path) in seen:
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continue
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seen.add(str(path))
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if path.parts[-1].startswith("."):
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continue
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elif path.is_dir():
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paths.extend(path.iterdir())
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else:
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locs.append(path)
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return locs
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def verify_cli_args(
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msg,
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input_path,
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output_dir,
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file_type,
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n_sents,
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seg_sents,
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model,
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morphology,
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merge_subtokens,
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converter,
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ner_map,
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lang
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):
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if converter == "ner" or converter == "iob":
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input_data = input_path.open("r", encoding="utf-8").read()
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converter_autodetect = autodetect_ner_format(input_data)
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if converter_autodetect == "ner":
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msg.info("Auto-detected token-per-line NER format")
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converter = converter_autodetect
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elif converter_autodetect == "iob":
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msg.info("Auto-detected sentence-per-line NER format")
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converter = converter_autodetect
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else:
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msg.warn(
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"Can't automatically detect NER format. Conversion may not",
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"succeed. See https://spacy.io/api/cli#convert"
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)
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if file_type not in FILE_TYPES_STDOUT and output_dir == "-":
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# TODO: support msgpack via stdout in srsly?
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msg.fail(
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f"Can't write .{file_type} data to stdout",
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"Please specify an output directory.",
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exits=1,
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)
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if not input_path.exists():
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msg.fail("Input file not found", input_path, exits=1)
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if output_dir != "-" and not Path(output_dir).exists():
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msg.fail("Output directory not found", output_dir, exits=1)
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if input_path.is_dir():
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input_locs = walk_directory(input_path)
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if len(input_locs) == 0:
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msg.fail("No input files in directory", input_path, exits=1)
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file_types = list(set([loc.suffix[1:] for loc in input_locs]))
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if len(file_types) >= 2:
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file_types = ",".join(file_types)
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msg.fail("All input files must be same type", file_types, exits=1)
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if converter == "auto":
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converter = file_types[0]
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else:
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converter = input_path.suffix[1:]
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if converter not in CONVERTERS:
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msg.fail(f"Can't find converter for {converter}", exits=1)
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return converter
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def _get_converter(msg, converter, input_path):
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if input_path.is_dir():
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input_path = walk_directory(input_path)[0]
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if converter == "auto":
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converter = input_path.suffix[1:]
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if converter == "ner" or converter == "iob":
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with input_path.open() as file_:
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input_data = file_.read()
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converter_autodetect = autodetect_ner_format(input_data)
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if converter_autodetect == "ner":
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msg.info("Auto-detected token-per-line NER format")
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converter = converter_autodetect
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elif converter_autodetect == "iob":
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msg.info("Auto-detected sentence-per-line NER format")
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converter = converter_autodetect
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else:
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msg.warn(
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"Can't automatically detect NER format. "
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"Conversion may not succeed. "
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"See https://spacy.io/api/cli#convert"
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)
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return converter
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