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bidirectional_rnn.ipynb error #1

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mrubashkin-svds opened this issue Mar 28, 2017 · 0 comments
Open

bidirectional_rnn.ipynb error #1

mrubashkin-svds opened this issue Mar 28, 2017 · 0 comments

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@mrubashkin-svds
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mrubashkin-svds commented Mar 28, 2017

When running the def BiRNN(x, weights, biases) cell with nothing changed in the code from the repository, I get the following error (I tried some quick fixes, but would love some advice on how to fix):

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/usr/local/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py in apply_op(self, op_type_name, name, **keywords)
    489                 as_ref=input_arg.is_ref,
--> 490                 preferred_dtype=default_dtype)
    491           except TypeError as err:

/usr/local/lib/python3.5/site-packages/tensorflow/python/framework/ops.py in convert_to_tensor(value, dtype, name, as_ref, preferred_dtype)
    668         if ret is None:
--> 669           ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
    670 

/usr/local/lib/python3.5/site-packages/tensorflow/python/framework/ops.py in _TensorTensorConversionFunction(t, dtype, name, as_ref)
    582         "Tensor conversion requested dtype %s for Tensor with dtype %s: %r"
--> 583         % (dtype.name, t.dtype.name, str(t)))
    584   return t

ValueError: Tensor conversion requested dtype int32 for Tensor with dtype float32: 'Tensor("Reshape_3:0", shape=(?, 28), dtype=float32)'

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
<ipython-input-7-795f6f262cc6> in <module>()
     29     return tf.matmul(outputs[-1], weights['out']) + biases['out']
     30 
---> 31 pred = BiRNN(x, weights, biases)
     32 
     33 # Define loss and optimizer

<ipython-input-7-795f6f262cc6> in BiRNN(x, weights, biases)
     10     x = tf.reshape(x, [-1, n_input])
     11     # Split to get a list of 'n_steps' tensors of shape (batch_size, n_input)
---> 12     x = tf.split(x, n_steps, 0)
     13 
     14     # Define lstm cells with tensorflow

/usr/local/lib/python3.5/site-packages/tensorflow/python/ops/array_ops.py in split(split_dim, num_split, value, name)
   1232                               num_split=num_split,
   1233                               value=value,
-> 1234                               name=name)
   1235 
   1236 

/usr/local/lib/python3.5/site-packages/tensorflow/python/ops/gen_array_ops.py in _split(split_dim, value, num_split, name)
   3239   """
   3240   result = _op_def_lib.apply_op("Split", split_dim=split_dim, value=value,
-> 3241                                 num_split=num_split, name=name)
   3242   return result
   3243 

/usr/local/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py in apply_op(self, op_type_name, name, **keywords)
    506             if input_arg.type != types_pb2.DT_INVALID:
    507               raise TypeError("%s expected type of %s." %
--> 508                               (prefix, dtypes.as_dtype(input_arg.type).name))
    509             else:
    510               # Update the maps with the default, if needed.

TypeError: Input 'split_dim' of 'Split' Op has type float32 that does not match expected type of int32.
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