snownus

from scipy.misc import imread, imresize

from keras.layers import Input, Dense, Convolution2D, MaxPooling2D, AveragePooling2D, ZeroPadding2D, Dropout, Flatten, merge, Reshape, Activation
from keras.models import Model
from keras.regularizers import l2
from keras.optimizers import SGD
from googlenet_custom_layers import PoolHelper,LRN


def create_googlenet(weights_path=None):

snownus

snownus

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'''This scripts implements Kim's paper "Convolutional Neural Networks for Sentence Classification"
with a very small embedding size (20) than the commonly used values (100 - 300) as it gives better
result with much less parameters.

Run on GPU: THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python imdb_cnn.py

Get to 0.853 test accuracy after 5 epochs. 13s/epoch on Nvidia GTX980 GPU.
'''

from __future__ import print_function

snownus

import nltk

text = """The Buddha, the Godhead, resides quite as comfortably in the circuits of a digital
computer or the gears of a cycle transmission as he does at the top of a mountain
or in the petals of a flower. To think otherwise is to demean the Buddha...which is
to demean oneself."""

# Used when tokenizing words
sentence_re = r'''(?x)      # set flag to allow verbose regexps
      ([A-Z])(\.[A-Z])+\.?  # abbreviations, e.g. U.S.A.