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I found that there are some differences between r0.7 and r0.9 which is that : class EmbeddingWrapper in rnn_cell.py in r0.9 doens't has some @Property values, just like def input_size , def output_size . and when i run rnn.rnn with embeded cell, it causes an NotImplementedError which is from RNNCell 's function
def__call__(self,inputs,state,scope=None):
"""Run this RNN cell on inputs, starting from the given state. Args: inputs: `2-D` tensor with shape `[batch_size x input_size]`. state: if `self.state_size` is an integer, this should be a `2-D Tensor` with shape `[batch_size x self.state_size]`. Otherwise, if `self.state_size` is a tuple of integers, this should be a tuple with shapes `[batch_size x s] for s in self.state_size`. scope: VariableScope for the created subgraph; defaults to class name. Returns: A pair containing: - Output: A `2-D` tensor with shape `[batch_size x self.output_size]`. - New state: Either a single `2-D` tensor, or a tuple of tensors matching the arity and shapes of `state`. """raiseNotImplementedError("Abstract method")
Did i do something wrong?
The text was updated successfully, but these errors were encountered:
I made a code change correcting it (adding output_state to EmbeddingWrapper), so that should be working now on master. Closing, please re-open if it's still not working.
I found that there are some differences between r0.7 and r0.9 which is that : class EmbeddingWrapper in rnn_cell.py in r0.9 doens't has some @Property values, just like
def input_size
,def output_size
. and when i run rnn.rnn with embeded cell, it causes an NotImplementedError which is from RNNCell 's functionDid i do something wrong?
The text was updated successfully, but these errors were encountered: