elephanthunters / deep-dream-using-tensorflow Goto Github PK

Recursive level: 0
Processing image: 
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
~/anaconda/lib/python3.6/site-packages/tensorflow/python/client/session.py in __init__(self, fetches, contraction_fn)
    266         self._unique_fetches.append(ops.get_default_graph().as_graph_element(
--> 267             fetch, allow_tensor=True, allow_operation=True))
    268       except TypeError as e:

~/anaconda/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in as_graph_element(self, obj, allow_tensor, allow_operation)
   2583     with self._lock:
-> 2584       return self._as_graph_element_locked(obj, allow_tensor, allow_operation)
   2585 

~/anaconda/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in _as_graph_element_locked(self, obj, allow_tensor, allow_operation)
   2662       if obj.graph is not self:
-> 2663         raise ValueError("Tensor %s is not an element of this graph." % obj)
   2664       return obj

ValueError: Tensor Tensor("gradients_3/conv2d0_pre_relu/conv_grad/Conv2DBackpropInput:0", shape=(?, ?, ?, ?), dtype=float32) is not an element of this graph.

During handling of the above exception, another exception occurred:

ValueError                                Traceback (most recent call last)
<ipython-input-57-5d83fc662529> in <module>()
      1 img_result = recursive_optimize(layer_tensor=layer_tensor, image=image,
      2                  num_iterations=10, step_size=3.0, rescale_factor=0.7,
----> 3                  num_repeats=4, blend=0.2)

<ipython-input-46-f2d8e35fb16c> in recursive_optimize(layer_tensor, image, num_repeats, rescale_factor, blend, num_iterations, step_size, tile_size)
     42                                         num_iterations=num_iterations,
     43                                         step_size=step_size,
---> 44                                         tile_size=tile_size)
     45 
     46         # Upscale the resulting image back to its original size.

<ipython-input-46-f2d8e35fb16c> in recursive_optimize(layer_tensor, image, num_repeats, rescale_factor, blend, num_iterations, step_size, tile_size)
     42                                         num_iterations=num_iterations,
     43                                         step_size=step_size,
---> 44                                         tile_size=tile_size)
     45 
     46         # Upscale the resulting image back to its original size.

<ipython-input-46-f2d8e35fb16c> in recursive_optimize(layer_tensor, image, num_repeats, rescale_factor, blend, num_iterations, step_size, tile_size)
     42                                         num_iterations=num_iterations,
     43                                         step_size=step_size,
---> 44                                         tile_size=tile_size)
     45 
     46         # Upscale the resulting image back to its original size.

<ipython-input-46-f2d8e35fb16c> in recursive_optimize(layer_tensor, image, num_repeats, rescale_factor, blend, num_iterations, step_size, tile_size)
     42                                         num_iterations=num_iterations,
     43                                         step_size=step_size,
---> 44                                         tile_size=tile_size)
     45 
     46         # Upscale the resulting image back to its original size.

<ipython-input-46-f2d8e35fb16c> in recursive_optimize(layer_tensor, image, num_repeats, rescale_factor, blend, num_iterations, step_size, tile_size)
     57                                 num_iterations=num_iterations,
     58                                 step_size=step_size,
---> 59                                 tile_size=tile_size)
     60 
     61     return img_result

<ipython-input-45-e9bbe3685879> in optimize_image(layer_tensor, image, num_iterations, step_size, tile_size, show_gradient)
     31         # This tells us how to change the image so as to
     32         # maximize the mean of the given layer-tensor.
---> 33         grad = tiled_gradient(gradient=gradient, image=img)
     34 
     35         # Blur the gradient with different amounts and add

<ipython-input-44-c9dbd0c7c029> in tiled_gradient(gradient, image, tile_size)
     50 
     51             # Use TensorFlow to calculate the gradient-value.
---> 52             g = session.run(gradient, feed_dict=feed_dict)
     53 
     54             # Normalize the gradient for the tile. This is

~/anaconda/lib/python3.6/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
    787     try:
    788       result = self._run(None, fetches, feed_dict, options_ptr,
--> 789                          run_metadata_ptr)
    790       if run_metadata:
    791         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

~/anaconda/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
    982     # Create a fetch handler to take care of the structure of fetches.
    983     fetch_handler = _FetchHandler(
--> 984         self._graph, fetches, feed_dict_string, feed_handles=feed_handles)
    985 
    986     # Run request and get response.

~/anaconda/lib/python3.6/site-packages/tensorflow/python/client/session.py in __init__(self, graph, fetches, feeds, feed_handles)
    408     """
    409     with graph.as_default():
--> 410       self._fetch_mapper = _FetchMapper.for_fetch(fetches)
    411     self._fetches = []
    412     self._targets = []

~/anaconda/lib/python3.6/site-packages/tensorflow/python/client/session.py in for_fetch(fetch)
    236         if isinstance(fetch, tensor_type):
    237           fetches, contraction_fn = fetch_fn(fetch)
--> 238           return _ElementFetchMapper(fetches, contraction_fn)
    239     # Did not find anything.
    240     raise TypeError('Fetch argument %r has invalid type %r' %

~/anaconda/lib/python3.6/site-packages/tensorflow/python/client/session.py in __init__(self, fetches, contraction_fn)
    272       except ValueError as e:
    273         raise ValueError('Fetch argument %r cannot be interpreted as a '
--> 274                          'Tensor. (%s)' % (fetch, str(e)))
    275       except KeyError as e:
    276         raise ValueError('Fetch argument %r cannot be interpreted as a '

ValueError: Fetch argument <tf.Tensor 'gradients_3/conv2d0_pre_relu/conv_grad/Conv2DBackpropInput:0' shape=(?, ?, ?, ?) dtype=float32> cannot be interpreted as a Tensor. (Tensor Tensor("gradients_3/conv2d0_pre_relu/conv_grad/Conv2DBackpropInput:0", shape=(?, ?, ?, ?), dtype=float32) is not an element of this graph.)