pulling tqdm imports in functions to avoid bug (tmp fix) (#4263)

bin/ud/ud_run_test.py

@@ -5,7 +5,6 @@
 from __future__ import unicode_literals
 
 import plac
-import tqdm
 from pathlib import Path
 import re
 import sys

bin/ud/ud_train.py

@@ -5,7 +5,6 @@
 from __future__ import unicode_literals
 
 import plac
-import tqdm
 from pathlib import Path
 import re
 import sys
@@ -462,6 +461,9 @@ def main(
     vectors_dir=None,
     use_oracle_segments=False,
 ):
+    # temp fix to avoid import issues cf https://github.com/explosion/spaCy/issues/4200
+    import tqdm
+
     spacy.util.fix_random_seed()
     lang.zh.Chinese.Defaults.use_jieba = False
     lang.ja.Japanese.Defaults.use_janome = False

examples/training/conllu.py

@@ -3,11 +3,9 @@
 """
 from __future__ import unicode_literals
 import plac
-import tqdm
 import attr
 from pathlib import Path
 import re
-import sys
 import json
 
 import spacy
@@ -23,7 +21,7 @@ import itertools
 import random
 import numpy.random
 
-import conll17_ud_eval
+from bin.ud import conll17_ud_eval
 
 import spacy.lang.zh
 import spacy.lang.ja
@@ -394,6 +392,9 @@ class TreebankPaths(object):
     limit=("Size limit", "option", "n", int),
 )
 def main(ud_dir, parses_dir, config, corpus, limit=0):
+    # temp fix to avoid import issues cf https://github.com/explosion/spaCy/issues/4200
+    import tqdm
+
     paths = TreebankPaths(ud_dir, corpus)
     if not (parses_dir / corpus).exists():
         (parses_dir / corpus).mkdir()

examples/training/pretrain_textcat.py

@@ -18,7 +18,6 @@ import random
 import spacy
 import thinc.extra.datasets
 from spacy.util import minibatch, use_gpu, compounding
-import tqdm
 from spacy._ml import Tok2Vec
 from spacy.pipeline import TextCategorizer
 import numpy
@@ -107,6 +106,9 @@ def create_pipeline(width, embed_size, vectors_model):
 
 
 def train_tensorizer(nlp, texts, dropout, n_iter):
+    # temp fix to avoid import issues cf https://github.com/explosion/spaCy/issues/4200
+    import tqdm
+
     tensorizer = nlp.create_pipe("tensorizer")
     nlp.add_pipe(tensorizer)
     optimizer = nlp.begin_training()
@@ -120,6 +122,9 @@ def train_tensorizer(nlp, texts, dropout, n_iter):
 
 
 def train_textcat(nlp, n_texts, n_iter=10):
+    # temp fix to avoid import issues cf https://github.com/explosion/spaCy/issues/4200
+    import tqdm
+
     textcat = nlp.get_pipe("textcat")
     tok2vec_weights = textcat.model.tok2vec.to_bytes()
     (train_texts, train_cats), (dev_texts, dev_cats) = load_textcat_data(limit=n_texts)

examples/vectors_tensorboard.py

@@ -13,7 +13,6 @@ import numpy
 import plac
 import spacy
 import tensorflow as tf
-import tqdm
 from tensorflow.contrib.tensorboard.plugins.projector import (
     visualize_embeddings,
     ProjectorConfig,
@@ -36,6 +35,9 @@ from tensorflow.contrib.tensorboard.plugins.projector import (
     ),
 )
 def main(vectors_loc, out_loc, name="spaCy_vectors"):
+    # temp fix to avoid import issues cf https://github.com/explosion/spaCy/issues/4200
+    import tqdm
+
     meta_file = "{}.tsv".format(name)
     out_meta_file = path.join(out_loc, meta_file)
 

spacy/cli/init_model.py

@@ -3,7 +3,6 @@ from __future__ import unicode_literals
 
 import plac
 import math
-from tqdm import tqdm
 import numpy
 from ast import literal_eval
 from pathlib import Path
@@ -109,6 +108,9 @@ def open_file(loc):
 
 
 def read_attrs_from_deprecated(freqs_loc, clusters_loc):
+    # temp fix to avoid import issues cf https://github.com/explosion/spaCy/issues/4200
+    from tqdm import tqdm
+
     if freqs_loc is not None:
         with msg.loading("Counting frequencies..."):
             probs, _ = read_freqs(freqs_loc)
@@ -186,6 +188,9 @@ def add_vectors(nlp, vectors_loc, prune_vectors):
 
 
 def read_vectors(vectors_loc):
+    # temp fix to avoid import issues cf https://github.com/explosion/spaCy/issues/4200
+    from tqdm import tqdm
+
     f = open_file(vectors_loc)
     shape = tuple(int(size) for size in next(f).split())
     vectors_data = numpy.zeros(shape=shape, dtype="f")
@@ -202,6 +207,9 @@ def read_vectors(vectors_loc):
 
 
 def read_freqs(freqs_loc, max_length=100, min_doc_freq=5, min_freq=50):
+    # temp fix to avoid import issues cf https://github.com/explosion/spaCy/issues/4200
+    from tqdm import tqdm
+
     counts = PreshCounter()
     total = 0
     with freqs_loc.open() as f:
@@ -231,6 +239,9 @@ def read_freqs(freqs_loc, max_length=100, min_doc_freq=5, min_freq=50):
 
 
 def read_clusters(clusters_loc):
+    # temp fix to avoid import issues cf https://github.com/explosion/spaCy/issues/4200
+    from tqdm import tqdm
+
     clusters = {}
     if ftfy is None:
         user_warning(Warnings.W004)

spacy/cli/profile.py

@@ -7,7 +7,6 @@ import srsly
 import cProfile
 import pstats
 import sys
-import tqdm
 import itertools
 import thinc.extra.datasets
 from wasabi import Printer
@@ -48,6 +47,9 @@ def profile(model, inputs=None, n_texts=10000):
 
 
 def parse_texts(nlp, texts):
+    # temp fix to avoid import issues cf https://github.com/explosion/spaCy/issues/4200
+    import tqdm
+
     for doc in nlp.pipe(tqdm.tqdm(texts), batch_size=16):
         pass
 

spacy/cli/train.py

@@ -4,7 +4,6 @@ from __future__ import unicode_literals, division, print_function
 import plac
 import os
 from pathlib import Path
-import tqdm
 from thinc.neural._classes.model import Model
 from timeit import default_timer as timer
 import shutil
@@ -101,6 +100,10 @@ def train(
     JSON format. To convert data from other formats, use the `spacy convert`
     command.
     """
+
+    # temp fix to avoid import issues cf https://github.com/explosion/spaCy/issues/4200
+    import tqdm
+
     msg = Printer()
     util.fix_random_seed()
     util.set_env_log(verbose)
@@ -390,6 +393,9 @@ def _score_for_model(meta):
 
 @contextlib.contextmanager
 def _create_progress_bar(total):
+    # temp fix to avoid import issues cf https://github.com/explosion/spaCy/issues/4200
+    import tqdm
+
     if int(os.environ.get("LOG_FRIENDLY", 0)):
         yield
     else: