Koustuv Sinha - 1 month ago 11

Python Question

I am trying to combine two RNN states and run them through another RNN in tensorflow. Here is the code snippet I am trying to work on :

`import numpy as np`

c = [1, 2, 3,4, 5, 6,2, 3,4]

u = [4,5,6,6,7,8,5,6,7]

tf.reset_default_graph()

with tf.Session() as sess:

cell = tf.contrib.rnn.BasicLSTMCell(1)

cn = tf.placeholder(tf.int32, shape=[None, 9],name="cn")

ut = tf.placeholder(tf.int32, shape=[None, 9],name="ut")

with tf.variable_scope("word_emb",reuse=None):

W = tf.get_variable("word_embed",shape=[10,1])

cn_e = tf.nn.embedding_lookup(W, cn)

ut_e = tf.nn.embedding_lookup(W, ut)

cn_e = tf.unstack(cn_e,9,1)

ut_e = tf.unstack(ut_e,9,1)

#print cn_e.get_shape().as_list()

with tf.variable_scope("encoding_1"):

c_out,c_state = tf.contrib.rnn.static_rnn(cell,cn_e,dtype=tf.float32)

with tf.variable_scope("encoding_2"):

u_out,u_state = tf.contrib.rnn.static_rnn(cell,ut_e,dtype=tf.float32)

print c_state[0].eval()

print u_state[0].eval()

comb_out,comb_state = tf.contrib.rnn.static_rnn(cell,tf.concat(c_state,u_state))

init_op = tf.global_variables_initializer()

sess.run(init_op)

sess.run(comb_out,feed_dict={

cn:np.random.randint(0, 25, size=[1, 9])

,ut:np.random.randint(0, 25, size=[1, 9])

})

However, I am facing this error:

`InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'cn' with dtype int32`

which I don't understand as I am feeding cn in the

`feed_dict`

Answer Source

The problem is in these two lines:

```
print c_state[0].eval()
print u_state[0].eval()
```

As both c_state and u_state are dependent on placeholders, you should feed values for them.