mirror of https://github.com/explosion/spaCy.git
133 lines
4.9 KiB
Python
133 lines
4.9 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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import plac
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from pathlib import Path
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from wasabi import Printer
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import srsly
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import re
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from .converters import conllu2json, iob2json, conll_ner2json
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from .converters import ner_jsonl2json
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# Converters are matched by file extension except for ner/iob, which are
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# matched by file extension and content. To add a converter, add a new
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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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CONVERTERS = {
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"conllubio": conllu2json,
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"conllu": conllu2json,
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"conll": conllu2json,
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"ner": conll_ner2json,
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"iob": iob2json,
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"jsonl": ner_jsonl2json,
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}
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# File types
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FILE_TYPES = ("json", "jsonl", "msg")
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FILE_TYPES_STDOUT = ("json", "jsonl")
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@plac.annotations(
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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=("Type of data to produce: {}".format(FILE_TYPES), "option", "t", str),
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n_sents=("Number of sentences per doc (0 to disable)", "option", "n", int),
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seg_sents=("Segment sentences (for -c ner)", "flag", "s"),
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model=("Model for sentence segmentation (for -s)", "option", "b", str),
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converter=("Converter: {}".format(tuple(CONVERTERS.keys())), "option", "c", str),
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lang=("Language (if tokenizer required)", "option", "l", str),
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morphology=("Enable appending morphology to tags", "flag", "m", bool),
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)
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def convert(
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input_file,
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output_dir="-",
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file_type="json",
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n_sents=1,
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seg_sents=False,
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model=None,
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morphology=False,
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converter="auto",
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lang=None,
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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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"""
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msg = Printer()
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input_path = Path(input_file)
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if file_type not in FILE_TYPES:
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msg.fail(
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"Unknown file type: '{}'".format(file_type),
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"Supported file types: '{}'".format(", ".join(FILE_TYPES)),
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exits=1,
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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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"Can't write .{} data to stdout.".format(file_type),
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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("Can't automatically detect NER format. Conversion may not succeed. See https://spacy.io/api/cli#convert")
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if converter not in CONVERTERS:
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msg.fail("Can't find converter for {}".format(converter), exits=1)
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# Use converter function to convert data
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func = CONVERTERS[converter]
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data = func(input_data, n_sents=n_sents, seg_sents=seg_sents, use_morphology=morphology, lang=lang, model=model)
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if output_dir != "-":
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# Export data to a file
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suffix = ".{}".format(file_type)
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output_file = Path(output_dir) / Path(input_path.parts[-1]).with_suffix(suffix)
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if file_type == "json":
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srsly.write_json(output_file, data)
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elif file_type == "jsonl":
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srsly.write_jsonl(output_file, data)
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elif file_type == "msg":
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srsly.write_msgpack(output_file, data)
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msg.good("Generated output file ({} documents): {}".format(len(data), output_file))
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else:
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# Print to stdout
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if file_type == "json":
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srsly.write_json("-", data)
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elif file_type == "jsonl":
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srsly.write_jsonl("-", data)
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def autodetect_ner_format(input_data):
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# guess format from the first 20 lines
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lines = input_data.split("\n")[:20]
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format_guesses = {"ner": 0, "iob": 0}
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iob_re = re.compile(r"\S+\|(O|[IB]-\S+)")
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ner_re = re.compile(r"\S+\s+(O|[IB]-\S+)$")
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for line in lines:
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line = line.strip()
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if iob_re.search(line):
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format_guesses["iob"] += 1
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if ner_re.search(line):
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format_guesses["ner"] += 1
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if format_guesses["iob"] == 0 and format_guesses["ner"] > 0:
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return "ner"
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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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