The "tensor" type of the error object doesn't repeat itself when I use tf.contrib.rnn.LayerNormBasicLSTMCell
My tensorflow version is 1.0.0. When I run with tf.contrib.rnn.GRUCell (n_hidden_units) ok but running error tf.contrib.rnn.LayerNormBasicLSTMCell (n_hidden_units): "error type tensor object is not iterable"
`with tf.variable_scope('init_name',initializer=tf.orthogonal_initializer()):
cell = tf.contrib.rnn.LayerNormBasicLSTMCell(n_hidden_units)
init_state = tf.get_variable('init_state', [1, n_hidden_units],initializer=tf.constant_initializer(0.0)) #tf.constant_initializer(0.0)
init_state = tf.tile(init_state, [train_batch_size, 1])
outputs, states = tf.nn.dynamic_rnn(
cell,X,dtype=tf.float32,sequence_length=true_lenth,initial_state=init_state)`
And the error:
/usr/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/rnn.py in <lambda>()
681
682 input_t = nest.pack_sequence_as(structure=inputs, flat_sequence=input_t)--> 683 call_cell = lambda: cell(input_t, state) 684 685 if sequence_length is not None:/usr/anaconda3/lib/python3.5/site-packages/tensorflow/contrib/rnn/python/ops/rnn_cell.py in __call__(self, inputs, state, scope)1228 1229 with vs.variable_scope(scope or
"layer_norm_basic_lstm_cell"):
-> 1230 c, h = state
1231 args = array_ops.concat ([Inputs, h], 1) 1232 concat = self._linear (args)
/usr/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py in iter (self)
514 TypeError: when invoked.
515 """
--> 516 raise TypeError("'Tensor' object is not iterable.")
517
518 def __bool__(self):
TypeError: 'Tensor' object is not iterable.
Can anyone help me? Thank you very much.
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1 answer
LayerNormBasicLSTMCell
requires the initial state to be a tuple ( num_units
, num_units
).
You can make your code by doing
cell = tf.contrib.rnn.LayerNormBasicLSTMCell(n_hidden_units)
init_state = (tf.zeros([train_batch_size, n_hidden_units]),
tf.zeros([train_batch_size, n_hidden_units]))
outputs, states = tf.nn.dynamic_rnn(
cell, X, dtype=tf.float32,
sequence_length=true_lenth,initial_state=init_state)
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