38 lines
1013 B
Python
38 lines
1013 B
Python
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#build the NN models: RNN module
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import tensorflow
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from tensorflow.python.ops import control_flow_ops
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from keras.models import Sequential
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from keras.layers import Dense, Dropout, Activation, Flatten
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from keras.layers import Convolution2D, MaxPooling2D
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from keras.layers import LSTM, Embedding,SimpleRNN
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from keras.utils import np_utils
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from tensorflow.python.platform import flags
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from numpy import shape
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import numpy as np
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from skimage import io, color, exposure, transform
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import os
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import glob
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import h5py
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import pandas as pd
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import numpy
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FLAGS = flags.FLAGS
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#tensorflow.python.control_flow_ops =control_flow_ops
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def rnn_model(seq_length, input_dim):
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model = Sequential()
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model.add((SimpleRNN(64, input_shape=(seq_length, input_dim))))
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model.add(Dropout(0.2))
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model.add(Dense(64))
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model.add(Activation('relu'))
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model.add(Dense(32))
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model.add(Activation('relu'))
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model.add(Dense(16))
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model.add(Activation('relu'))
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model.add(Dense(1,init='normal'))
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return model
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