# Path: data/common.py
# WORD_EMB_PATH = '/path/to/word/embedding/'
# 
# Path: data/bookcorpus.py
# VOCAB_PATH = os.path.join(BOOKCORPUS_DATA_DIR, 'word_count{}')


from gensim.models import KeyedVectors
from data.common import WORD_EMB_PATH
from data.bookcorpus import VOCAB_PATH
import collections
import os
import tqdm
import numpy as np
import sklearn.linear_model
import tensorflow as tf
# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function



GLOVE_EMBEDDING_PATH = WORD_EMB_PATH + 'glove.840B.300d_gensim.txt'

# Path: data/common.py
# WORD_EMB_PATH = '/path/to/word/embedding/'
# 
# Path: data/bookcorpus.py
# VOCAB_PATH = os.path.join(BOOKCORPUS_DATA_DIR, 'word_count{}')


# Path: thought/vocabulary_expansion.py
from gensim.models import KeyedVectors
from data.common import WORD_EMB_PATH
from data.bookcorpus import VOCAB_PATH
import collections
import os
import tqdm
import numpy as np
import sklearn.linear_model
import tensorflow as tf

# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function



GLOVE_EMBEDDING_PATH = WORD_EMB_PATH + 'glove.840B.300d_gensim.txt'

W2V_EMBEDDING_PATH = WORD_EMB_PATH + 'GoogleNews-vectors-negative300.bin'