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.)
