In [2]:

    

import tensorflow as tf


    

In [3]:

    

import numpy as np


    

In [7]:

    

n_neurons = 5


    

In [8]:

    

n_steps = 5


    

In [10]:

    

n_inputs = 3


    

In [11]:

    

X = tf.placeholder(tf.float32, [None, n_steps, n_inputs])


    

In [12]:

    

X_seqs = tf.unpack(tf.transpose(X, perm = [1, 0, 2]))


    

In [13]:

    

with tf.variable_scope('s1'):
    cell1 = tf.nn.rnn_cell.BasicRNNCell(num_units = n_neurons)
    output_seqs, states = tf.nn.rnn(cell1, X_seqs, dtype=tf.float32)
    outputs = tf.transpose(tf.pack(output_seqs), perm = [1, 0, 2])


    

In [ ]:

    

X_batch = np.array([
    # t = 0      t = 1
    [[0, 1, 2], [9, 8, 7]], # instance 0
    [[3, 4, 5], [0, 0, 0]], # instance 1
])