mirror of https://github.com/explosion/spaCy.git
Fix deep learning tutorial
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@ -4,9 +4,8 @@ import random
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import cytoolz
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import cytoolz
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import numpy
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import numpy
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from keras.layers import Sequential, LSTM, Dense, Embedding, Dropout
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from keras.models import Sequential, model_from_json
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from keras.wrappers import Bidirectional
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from keras.layers import LSTM, Dense, Embedding, Dropout, Bidirectional
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from keras import model_from_json
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import cPickle as pickle
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import cPickle as pickle
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import spacy
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import spacy
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@ -127,17 +126,16 @@ def read_data(data_dir, limit=0):
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@plac.annotations(
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@plac.annotations(
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language=("The language to train", "positional", None, str, ['en','de', 'zh']),
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train_dir=("Location of training file or directory"),
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train_loc=("Location of training file or directory"),
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dev_dir=("Location of development file or directory"),
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dev_loc=("Location of development file or directory"),
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model_dir=("Location of output model directory",),
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model_dir=("Location of output model directory",),
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is_runtime=("Demonstrate run-time usage", "flag", "r", bool),
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is_runtime=("Demonstrate run-time usage", "flag", "r", bool),
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nr_hidden=("Number of hidden units", "flag", "H", int),
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nr_hidden=("Number of hidden units", "option", "H", int),
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max_length=("Maximum sentence length", "flag", "L", int),
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max_length=("Maximum sentence length", "option", "L", int),
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dropout=("Dropout", "flag", "d", float),
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dropout=("Dropout", "option", "d", float),
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nr_epoch=("Number of training epochs", "flag", "i", int),
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nb_epoch=("Number of training epochs", "option", "i", int),
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batch_size=("Size of minibatches for training LSTM", "flag", "b", int),
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batch_size=("Size of minibatches for training LSTM", "option", "b", int),
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nr_examples=("Limit to N examples", "flag", "n", int)
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nr_examples=("Limit to N examples", "option", "n", int)
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)
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)
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def main(model_dir, train_dir, dev_dir,
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def main(model_dir, train_dir, dev_dir,
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is_runtime=False,
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is_runtime=False,
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