simple-samples

# coding: utf-8
import tensorflow as tf
import numpy as np
tf.reset_default_graph()

batch_size=2
T=3
input_dim=4
hidden_dim=50

#a = np.arange(batch_size*T*input_dim).reshape(batch_size,T,input_dim).astype(np.float32)
a=np.random.randn(batch_size,T,input_dim)
x = tf.convert_to_tensor(a,tf.float32)
cell = tf.contrib.rnn.GRUCell(num_units=hidden_dim)
initial_state = cell.zero_state(batch_size, tf.float32)

outputs, states = tf.nn.dynamic_rnn(cell,x,initial_state=initial_state,dtype=tf.float32)