71 lines
2.2 KiB
Python
71 lines
2.2 KiB
Python
from keras.models import Sequential, Model
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from keras.layers import Conv2D, ReLU, Lambda, Reshape
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from keras import backend as K
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import numpy as np
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import string, re, collections, os, sys, operator, math
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stopwords = set(open('../stop_words.txt').read().split(','))
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all_words = re.findall('[a-z]{2,}', open(sys.argv[1]).read().lower())
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words = [w for w in all_words if w not in stopwords]
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uniqs = [''] + list(set(words))
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uniqs_indices = dict((w, i) for i, w in enumerate(uniqs))
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indices_uniqs = dict((i, w) for i, w in enumerate(uniqs))
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indices = [uniqs_indices[w] for w in words]
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WORDS_SIZE = len(words)
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VOCAB_SIZE = len(uniqs)
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BIN_SIZE = math.ceil(math.log(VOCAB_SIZE, 2))
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print(f'Words size {WORDS_SIZE}, vocab size {VOCAB_SIZE}, bin size {BIN_SIZE}')
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def encode_binary(W):
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x = np.zeros((1, WORDS_SIZE, BIN_SIZE, 1))
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for i, w in enumerate(W):
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for n in range(BIN_SIZE):
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n2 = pow(2, n)
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x[0, i, n, 0] = 1 if (w & n2) == n2 else 0
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return x
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def conv_layer_set_weights(clayer):
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wb = []
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b = np.zeros((VOCAB_SIZE), dtype=np.float32)
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w = np.zeros((1, BIN_SIZE, 1, VOCAB_SIZE), dtype=np.float32)
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for i in range(VOCAB_SIZE):
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for n in range(BIN_SIZE):
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n2 = pow(2, n)
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w[0][n][0][i] = 1 if (i & n2) == n2 else -1 #-(BIN_SIZE-1)
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for i in range(VOCAB_SIZE):
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slice_1 = w[0, :, 0, i]
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n_ones = len(slice_1[ slice_1 == 1 ])
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if n_ones > 0: slice_1[ slice_1 == 1 ] = 1./n_ones
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n_ones = len(slice_1[ slice_1 == -1 ])
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if n_ones > 0: slice_1[ slice_1 == -1 ] = -1./n_ones
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wb.append(w)
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wb.append(b)
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clayer.set_weights(wb)
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def SumPooling2D(x):
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return K.sum(x, axis = 1)
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def build_model():
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model = Sequential()
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model.add(Conv2D(VOCAB_SIZE, (1, BIN_SIZE), input_shape=(WORDS_SIZE, BIN_SIZE, 1)))
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model.add(ReLU(threshold=1-1/BIN_SIZE))
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model.add(Lambda(SumPooling2D))
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model.add(Reshape((VOCAB_SIZE,)))
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return model
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model = build_model()
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model.summary()
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conv_layer_set_weights(model.layers[0])
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batch_x = encode_binary(indices)
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preds = model.predict(batch_x)
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prediction = preds[0]
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for w, c in sorted(list(zip(uniqs, prediction)), key = operator.itemgetter(1), reverse=True)[:25]:
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print(w, "-", c)
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