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import tensorflow as tf
from tensorflow.contrib import rnn
class RNNGenerator:
def create_LSTM(self, inputs, weights, biases, seq_size, num_units):
# Reshape input to [1, sequence_size] and split it into sequences
inputs = tf.reshape(inputs, [-1, seq_size])
inputs = tf.split(inputs, seq_size, 1)
# LSTM with 2 layers
rnn_model = rnn.MultiRNNCell([rnn.BasicLSTMCell(num_units),rnn.BasicLSTMCell(num_units)])
# Generate prediction
outputs, states = rnn.static_rnn(rnn_model, inputs, dtype=tf.float32)
return tf.matmul(outputs[-1], weights['out']) + biases['out']
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