Error when running the conversation_GAN.py

[balagopal24]

Traceback (most recent call last):
File "conversation_GAN.py", line 136, in
input_context = Input(shape=(maxlen_input,), dtype='int32', name='the context text')
File "/home/bala/.local/lib/python2.7/site-packages/keras/engine/input_layer.py", line 176, in Input
input_tensor=tensor)
File "/home/bala/.local/lib/python2.7/site-packages/keras/legacy/interfaces.py", line 91, in wrapper
return func(*args, **kwargs)
File "/home/bala/.local/lib/python2.7/site-packages/keras/engine/input_layer.py", line 85, in init
name=self.name)
File "/home/bala/.local/lib/python2.7/site-packages/keras/backend/tensorflow_backend.py", line 514, in placeholder
x = tf.placeholder(dtype, shape=shape, name=name)
File "/home/bala/.local/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 1808, in placeholder
return gen_array_ops.placeholder(dtype=dtype, shape=shape, name=name)
File "/home/bala/.local/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 4848, in placeholder
"Placeholder", dtype=dtype, shape=shape, name=name)
File "/home/bala/.local/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 394, in _apply_op_helper
with g.as_default(), ops.name_scope(name) as scope:
File "/home/bala/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 5982, in enter
return self._name_scope.enter()
File "/usr/lib/python2.7/contextlib.py", line 17, in enter
return self.gen.next()
File "/home/bala/.local/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 4105, in name_scope
raise ValueError("'%s' is not a valid scope name" % name)
ValueError: 'the context text' is not a valid scope name

[oswaldoludwig]

You can remove the parameter "name", so Line 136 can be rewritten as: input_context = Input(shape=(maxlen_input,), dtype='int32')

[johndpope]

it's possible to upgrade any python2 code to python 3 automatically using the following command.

2to3 *.py -w
this will convert file to python3
the error I get in python 3 is more accurately

raise ValueError("'%s' is not a valid scope name" % name)

ValueError: 'the context text' is not a valid scope name

this can be resolved by removing the spaces in the name parameter.
I believe you still want a name params / scope built into the graph rather than ditching them.

side note - I've been tinkering with livepython to spit out tensorflow graph at run time.

agermanidis/livepython#24

[johndpope]

problem I get with replacing strings

python conversation_GAN.py
/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
 from ._conv import register_converters as _register_converters
Using TensorFlow backend.
/Users/jpope/miniconda2/envs/tensorflow/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: compiletime version 3.6 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.5
 return f(*args, **kwds)
Starting the model...
conversation_GAN.py:138: UserWarning: Update your `LSTM` call to the Keras 2 API: `LSTM(300, name="Encodecontext", kernel_initializer="lecun_uniform")`
 LSTM_encoder = LSTM(sentence_embedding_size, init= 'lecun_uniform', name='Encodecontext')
conversation_GAN.py:139: UserWarning: Update your `LSTM` call to the Keras 2 API: `LSTM(300, name="Encodeansweruptothecurrenttoken", kernel_initializer="lecun_uniform")`
 LSTM_decoder = LSTM(sentence_embedding_size, init= 'lecun_uniform', name='Encodeansweruptothecurrenttoken')
Traceback (most recent call last):
 File "conversation_GAN.py", line 148, in <module>
   merge_layer = merge([context_embedding, answer_embedding], mode='concat', concat_axis=1, name='concatenatetheembeddingsofthecontextandtheansweruptocurrenttoken')
TypeError: 'module' object is not callable

[johndpope]

related - zhixuhao/unet#45

[johndpope]

thanks @oswaldoludwig - I got it working in python 3

https://gist.github.com/johndpope/62c3e2117c9de625b7f82f3356a7430d

Using TensorFlow backend.
Starting the model...
__________________________________________________________________________________________________
Layer (type)                    Output Shape         Param #     Connected to
==================================================================================================
thecontexttext (InputLayer)     (None, 50)           0
__________________________________________________________________________________________________
theanswertextuptothecurrenttoke (None, 50)           0
__________________________________________________________________________________________________
Shared (Embedding)              (None, 50, 100)      700000      thecontexttext[0][0]
                                                                 theanswertextuptothecurrenttoken[
__________________________________________________________________________________________________
Encodecontext (LSTM)            (None, 300)          481200      Shared[0][0]
__________________________________________________________________________________________________
Encodeansweruptothecurrenttoken (None, 300)          481200      Shared[1][0]
__________________________________________________________________________________________________
concatenate_1 (Concatenate)     (None, 600)          0           Encodecontext[0][0]
                                                                 Encodeansweruptothecurrenttoken[0
__________________________________________________________________________________________________
reluactivation (Dense)          (None, 3500)         2103500     concatenate_1[0][0]
__________________________________________________________________________________________________
dense_1 (Dense)                 (None, 7000)         24507000    reluactivation[0][0]
==================================================================================================
Total params: 28,272,900
Trainable params: 28,272,900
Non-trainable params: 0