我试图按照Grad-CAM惊人的书中所解释的那样实施this。但是在本书的模型中，他们没有使用dropout层，但我提供的示例代码不能运行。 我使用以下模型：
Layer (type) Output Shape Param #
=================================================================
conv2d_1 (Conv2D) (None, 30, 30, 32) 896
_________________________________________________________________
max_pooling2d_1 (MaxPooling2 (None, 15, 15, 32) 0
_________________________________________________________________
conv2d_2 (Conv2D) (None, 13, 13, 64) 18496
_________________________________________________________________
max_pooling2d_2 (MaxPooling2 (None, 6, 6, 64) 0
_________________________________________________________________
conv2d_3 (Conv2D) (None, 4, 4, 128) 73856
_________________________________________________________________
max_pooling2d_3 (MaxPooling2 (None, 2, 2, 128) 0
_________________________________________________________________
flatten_1 (Flatten) (None, 512) 0
_________________________________________________________________
dropout_1 (Dropout) (None, 512) 0
_________________________________________________________________
dense_1 (Dense) (None, 512) 262656
_________________________________________________________________
dense_2 (Dense) (None, 256) 131328
_________________________________________________________________
dense_3 (Dense) (None, 128) 32896
_________________________________________________________________
dense_4 (Dense) (None, 43) 5547
并希望获得以下代码：
from tensorflow.python.keras.backend import mean, function, gradients
roadwork_output = model.output[:, 25] # 25 is the label for roadwork
last_conv_layer = model.get_layer('conv2d_3')
grads = gradients(roadwork_output, last_conv_layer.output)[0]
pooled_grads = mean(grads, axis=(0, 1, 2))
iterate = function([model.input],
[pooled_grads, last_conv_layer.output[0]])
pooled_grads_value, conv_layer_output_value = iterate([resized_images[4].reshape(1,32,32,3)])
for i in range(128): # 128 channels in last conv layer
conv_layer_output_value[:, :, i] *= pooled_grads_value[i]
heatmap = np.mean(conv_layer_output_value, axis=-1)
但是我收到以下错误：
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
~/miniconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1349 try:
-> 1350 return fn(*args)
1351 except errors.OpError as e:
~/miniconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
1328 feed_dict, fetch_list, target_list,
-> 1329 status, run_metadata)
1330
~/miniconda3/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py in __exit__(self, type_arg, value_arg, traceback_arg)
472 compat.as_text(c_api.TF_Message(self.status.status)),
--> 473 c_api.TF_GetCode(self.status.status))
474 # Delete the underlying status object from memory otherwise it stays alive
InvalidArgumentError: You must feed a value for placeholder tensor 'dropout/keras_learning_phase' with dtype bool
[[Node: dropout/keras_learning_phase = Placeholder[dtype=DT_BOOL, shape=<unknown>, _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
[[Node: Mean_8/_187 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_200_Mean_8", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
During handling of the above exception, another exception occurred:
InvalidArgumentError Traceback (most recent call last)
<ipython-input-53-b1b0b22c0d54> in <module>()
7 iterate = function([model.input],
8 [pooled_grads, last_conv_layer.output[0]])
----> 9 pooled_grads_value, conv_layer_output_value = iterate([resized_images[4].reshape(1,32,32,3)])
10 for i in range(128): # 128 channels in last conv layer
11 conv_layer_output_value[:, :, i] *= pooled_grads_value[i]
~/miniconda3/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py in __call__(self, inputs)
2551 session = get_session()
2552 updated = session.run(
-> 2553 fetches=fetches, feed_dict=feed_dict, **self.session_kwargs)
2554 return updated[:len(self.outputs)]
2555
~/miniconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
893 try:
894 result = self._run(None, fetches, feed_dict, options_ptr,
--> 895 run_metadata_ptr)
896 if run_metadata:
897 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
~/miniconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1126 if final_fetches or final_targets or (handle and feed_dict_tensor):
1127 results = self._do_run(handle, final_targets, final_fetches,
-> 1128 feed_dict_tensor, options, run_metadata)
1129 else:
1130 results = []
~/miniconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1342 if handle is None:
1343 return self._do_call(_run_fn, self._session, feeds, fetches, targets,
-> 1344 options, run_metadata)
1345 else:
1346 return self._do_call(_prun_fn, self._session, handle, feeds, fetches)
~/miniconda3/lib/python3.6/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1361 except KeyError:
1362 pass
-> 1363 raise type(e)(node_def, op, message)
1364
1365 def _extend_graph(self):
InvalidArgumentError: You must feed a value for placeholder tensor 'dropout/keras_learning_phase' with dtype bool
[[Node: dropout/keras_learning_phase = Placeholder[dtype=DT_BOOL, shape=<unknown>, _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
[[Node: Mean_8/_187 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_200_Mean_8", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
Caused by op 'dropout/keras_learning_phase', defined at:
File "/home/henke/miniconda3/lib/python3.6/runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "/home/henke/miniconda3/lib/python3.6/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/henke/miniconda3/lib/python3.6/site-packages/ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/home/henke/miniconda3/lib/python3.6/site-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/home/henke/miniconda3/lib/python3.6/site-packages/ipykernel/kernelapp.py", line 478, in start
self.io_loop.start()
File "/home/henke/miniconda3/lib/python3.6/site-packages/zmq/eventloop/ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "/home/henke/miniconda3/lib/python3.6/site-packages/tornado/ioloop.py", line 888, in start
handler_func(fd_obj, events)
File "/home/henke/miniconda3/lib/python3.6/site-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/home/henke/miniconda3/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "/home/henke/miniconda3/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "/home/henke/miniconda3/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "/home/henke/miniconda3/lib/python3.6/site-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/home/henke/miniconda3/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "/home/henke/miniconda3/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 233, in dispatch_shell
handler(stream, idents, msg)
File "/home/henke/miniconda3/lib/python3.6/site-packages/ipykernel/kernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "/home/henke/miniconda3/lib/python3.6/site-packages/ipykernel/ipkernel.py", line 208, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/home/henke/miniconda3/lib/python3.6/site-packages/ipykernel/zmqshell.py", line 537, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/home/henke/miniconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2728, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/home/henke/miniconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2850, in run_ast_nodes
if self.run_code(code, result):
File "/home/henke/miniconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py", line 2910, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-8-50ed28ee661a>", line 12, in <module>
model.add(layers.Dropout(0.5))
File "/home/henke/miniconda3/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/models.py", line 514, in add
output_tensor = layer(self.outputs[0])
File "/home/henke/miniconda3/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/engine/topology.py", line 258, in __call__
output = super(Layer, self).__call__(inputs, **kwargs)
File "/home/henke/miniconda3/lib/python3.6/site-packages/tensorflow/python/layers/base.py", line 652, in __call__
outputs = self.call(inputs, *args, **kwargs)
File "/home/henke/miniconda3/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/layers/core.py", line 117, in call
training = K.learning_phase()
File "/home/henke/miniconda3/lib/python3.6/site-packages/tensorflow/python/keras/_impl/keras/backend.py", line 331, in learning_phase
phase = array_ops.placeholder(dtype='bool', name='keras_learning_phase')
File "/home/henke/miniconda3/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 1680, in placeholder
return gen_array_ops._placeholder(dtype=dtype, shape=shape, name=name)
File "/home/henke/miniconda3/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 3141, in _placeholder
"Placeholder", dtype=dtype, shape=shape, name=name)
File "/home/henke/miniconda3/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/home/henke/miniconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 3160, in create_op
op_def=op_def)
File "/home/henke/miniconda3/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1625, in __init__
self._traceback = self._graph._extract_stack() # pylint: disable=protected-access
InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'dropout/keras_learning_phase' with dtype bool
[[Node: dropout/keras_learning_phase = Placeholder[dtype=DT_BOOL, shape=<unknown>, _device="/job:localhost/replica:0/task:0/device:GPU:0"]()]]
[[Node: Mean_8/_187 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_200_Mean_8", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
为什么我会收到此错误，我需要更改哪些内容才能解决问题？