failed to get the ith layer output if Dropout is contained

[zkk995]

def get_ith_layer_output(model, X, i):
    ''' if the model contains Dropout,  it will fail '''
    get_ith_layer = keras.backend.function(
        [model.layers[0].input], [model.layers[i].output])
    layer_output = get_ith_layer([X])[0]
    return layer_output
    
N = nD.shape[1]    
model = Sequential(layers=[
    Dense(150, input_dim=N, init='normal', activation='relu'), # Dropout(0.4),
    Dense(50, init='normal'), Activation(PReLU()),  Dropout(0.2), 
    Dense(1, init='normal', activation='sigmoid'),
])

model.compile(loss='binary_crossentropy',
        optimizer='adadelta', # https://github.com/fchollet/keras/blob/master/keras/optimizers.py
        metrics=['accuracy',])

model.fit(nD.values, D.good_flag.values, batch_size=64, nb_epoch=5, class_weight={1:1,0:10}, validation_split=0.8)

out = {}
for i in range( len(model.layers) ):
    out[i] = get_ith_layer_output(model, nD.values, i)
    display(out[i].shape)

(10000, 150)
(10000, 50)
(10000, 50)
---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
/opt/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1020     try:
-> 1021       return fn(*args)
   1022     except errors.OpError as e:

/opt/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
   1002                                  feed_dict, fetch_list, target_list,
-> 1003                                  status, run_metadata)
   1004 

/opt/anaconda3/lib/python3.5/contextlib.py in __exit__(self, type, value, traceback)
     65             try:
---> 66                 next(self.gen)
     67             except StopIteration:

/opt/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/errors_impl.py in raise_exception_on_not_ok_status()
    468           compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 469           pywrap_tensorflow.TF_GetCode(status))
    470   finally:

InvalidArgumentError: You must feed a value for placeholder tensor 'keras_learning_phase' with dtype bool
	 [[Node: keras_learning_phase = Placeholder[dtype=DT_BOOL, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

During handling of the above exception, another exception occurred:

InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-163-02d2bec78984> in <module>()
      3 out = {}
      4 for i in range( len(model.layers) ):
----> 5     out[i] = get_ith_layer_output(model, X, i)
      6     display(out[i].shape)

<ipython-input-162-b6552422d94b> in get_ith_layer_output(model, X, i)
      4     get_ith_layer = keras.backend.function(
      5         [model.layers[0].input], [model.layers[i].output])
----> 6     layer_output = get_ith_layer([X])[0]
      7     return layer_output
      8 

/opt/anaconda3/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py in __call__(self, inputs)
   1601         session = get_session()
   1602         updated = session.run(self.outputs + [self.updates_op],
-> 1603                               feed_dict=feed_dict)
   1604         return updated[:len(self.outputs)]
   1605 

/opt/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
    764     try:
    765       result = self._run(None, fetches, feed_dict, options_ptr,
--> 766                          run_metadata_ptr)
    767       if run_metadata:
    768         proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)

/opt/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
    962     if final_fetches or final_targets:
    963       results = self._do_run(handle, final_targets, final_fetches,
--> 964                              feed_dict_string, options, run_metadata)
    965     else:
    966       results = []

/opt/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1012     if handle is None:
   1013       return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1014                            target_list, options, run_metadata)
   1015     else:
   1016       return self._do_call(_prun_fn, self._session, handle, feed_dict,

/opt/anaconda3/lib/python3.5/site-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
   1032         except KeyError:
   1033           pass
-> 1034       raise type(e)(node_def, op, message)
   1035 
   1036   def _extend_graph(self):

InvalidArgumentError: You must feed a value for placeholder tensor 'keras_learning_phase' with dtype bool
	 [[Node: keras_learning_phase = Placeholder[dtype=DT_BOOL, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

Caused by op 'keras_learning_phase', defined at:
  File "/opt/anaconda3/lib/python3.5/runpy.py", line 184, in _run_module_as_main
    "__main__", mod_spec)
  File "/opt/anaconda3/lib/python3.5/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/opt/anaconda3/lib/python3.5/site-packages/ipykernel/__main__.py", line 3, in <module>
    app.launch_new_instance()
  File "/opt/anaconda3/lib/python3.5/site-packages/traitlets/config/application.py", line 653, in launch_instance
    app.start()
  File "/opt/anaconda3/lib/python3.5/site-packages/ipykernel/kernelapp.py", line 474, in start
    ioloop.IOLoop.instance().start()
  File "/opt/anaconda3/lib/python3.5/site-packages/zmq/eventloop/ioloop.py", line 162, in start
    super(ZMQIOLoop, self).start()
  File "/opt/anaconda3/lib/python3.5/site-packages/tornado/ioloop.py", line 887, in start
    handler_func(fd_obj, events)
  File "/opt/anaconda3/lib/python3.5/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/opt/anaconda3/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
    self._handle_recv()
  File "/opt/anaconda3/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
    self._run_callback(callback, msg)
  File "/opt/anaconda3/lib/python3.5/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
    callback(*args, **kwargs)
  File "/opt/anaconda3/lib/python3.5/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/opt/anaconda3/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "/opt/anaconda3/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
    handler(stream, idents, msg)
  File "/opt/anaconda3/lib/python3.5/site-packages/ipykernel/kernelbase.py", line 390, in execute_request
    user_expressions, allow_stdin)
  File "/opt/anaconda3/lib/python3.5/site-packages/ipykernel/ipkernel.py", line 196, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/opt/anaconda3/lib/python3.5/site-packages/ipykernel/zmqshell.py", line 501, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/opt/anaconda3/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/opt/anaconda3/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
    if self.run_code(code, result):
  File "/opt/anaconda3/lib/python3.5/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-9-f33e954aab9c>", line 6, in <module>
    Dense(1, init='normal', activation='sigmoid'),
  File "/opt/anaconda3/lib/python3.5/site-packages/keras/models.py", line 268, in __init__
    self.add(layer)
  File "/opt/anaconda3/lib/python3.5/site-packages/keras/models.py", line 327, in add
    output_tensor = layer(self.outputs[0])
  File "/opt/anaconda3/lib/python3.5/site-packages/keras/engine/topology.py", line 569, in __call__
    self.add_inbound_node(inbound_layers, node_indices, tensor_indices)
  File "/opt/anaconda3/lib/python3.5/site-packages/keras/engine/topology.py", line 632, in add_inbound_node
    Node.create_node(self, inbound_layers, node_indices, tensor_indices)
  File "/opt/anaconda3/lib/python3.5/site-packages/keras/engine/topology.py", line 164, in create_node
    output_tensors = to_list(outbound_layer.call(input_tensors[0], mask=input_masks[0]))
  File "/opt/anaconda3/lib/python3.5/site-packages/keras/layers/core.py", line 90, in call
    x = K.in_train_phase(K.dropout(x, self.p, noise_shape), x)
  File "/opt/anaconda3/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 1877, in in_train_phase
    if learning_phase() is 1:
  File "/opt/anaconda3/lib/python3.5/site-packages/keras/backend/tensorflow_backend.py", line 73, in learning_phase
    name='keras_learning_phase')
  File "/opt/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/array_ops.py", line 1587, in placeholder
    name=name)
  File "/opt/anaconda3/lib/python3.5/site-packages/tensorflow/python/ops/gen_array_ops.py", line 2043, in _placeholder
    name=name)
  File "/opt/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 759, in apply_op
    op_def=op_def)
  File "/opt/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 2240, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/opt/anaconda3/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1128, in __init__
    self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'keras_learning_phase' with dtype bool
	 [[Node: keras_learning_phase = Placeholder[dtype=DT_BOOL, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]

[patyork]

The error is self explanatory and well documented in both the Keras docs and a few other issues.

[zkk995]

thanks @patyork.

done as follows.

def get_ith_layer_output(model, X, i, mode='test'):
    ''' see https://keras.io/getting-started/faq/#keras-faq-frequently-asked-keras-questions'''
    get_ith_layer = keras.backend.function(
        [model.layers[0].input, keras.backend.learning_phase()], [model.layers[i].output])
    layer_output = get_ith_layer([X, 0 if mode=='test' else 1])[0]
    return layer_output

[geekan]

Thanks to @zkk995
This function OOM when faced to large X, can you add batch_size to it?
Or could it split and merge mannully?

[coltsfan]

@patyork @zkk995 I am still having this issue even with setting the learning phase. Additionally, in the documentation, it treats K.learning_phase() as a method, should this be updated?

from keras import backend as K
import tensorflow as tf

first_layer = bn_model.layers[0]
get_acts = K.function(outputs=[bn_model.layers[3].output], 
                      inputs=[bn_model.layers[0].input, keras.backend.learning_phase])

---------------------------------------------------------------------------
InvalidArgumentError                      Traceback (most recent call last)
<ipython-input-217-2514d26697e5> in <module>()
----> 1 get_acts([X_test])

/home/ubuntu/anaconda2/lib/python2.7/site-packages/keras/backend/tensorflow_backend.pyc in __call__(self, inputs)
   2266         updated = session.run(self.outputs + [self.updates_op],
   2267                               feed_dict=feed_dict,
-> 2268                               **self.session_kwargs)
   2269         return updated[:len(self.outputs)]
   2270 

/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.pyc 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)

/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _run(self, handle, fetches, feed_dict, options, run_metadata)
    995     if final_fetches or final_targets:
    996       results = self._do_run(handle, final_targets, final_fetches,
--> 997                              feed_dict_string, options, run_metadata)
    998     else:
    999       results = []

/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
   1130     if handle is None:
   1131       return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1132                            target_list, options, run_metadata)
   1133     else:
   1134       return self._do_call(_prun_fn, self._session, handle, feed_dict,

/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _do_call(self, fn, *args)
   1150         except KeyError:
   1151           pass
-> 1152       raise type(e)(node_def, op, message)
   1153 
   1154   def _extend_graph(self):

InvalidArgumentError: You must feed a value for placeholder tensor 'batch_normalization_1/keras_learning_phase' with dtype bool
	 [[Node: batch_normalization_1/keras_learning_phase = Placeholder[dtype=DT_BOOL, shape=<unknown>, _device="/job:localhost/replica:0/task:0/gpu:0"]()]]

Caused by op u'batch_normalization_1/keras_learning_phase', defined at:
  File "/home/ubuntu/anaconda2/lib/python2.7/runpy.py", line 174, in _run_module_as_main
    "__main__", fname, loader, pkg_name)
  File "/home/ubuntu/anaconda2/lib/python2.7/runpy.py", line 72, in _run_code
    exec code in run_globals
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/ipykernel/__main__.py", line 3, in <module>
    app.launch_new_instance()
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/traitlets/config/application.py", line 653, in launch_instance
    app.start()
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/ipykernel/kernelapp.py", line 474, in start
    ioloop.IOLoop.instance().start()
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/zmq/eventloop/ioloop.py", line 162, in start
    super(ZMQIOLoop, self).start()
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/tornado/ioloop.py", line 887, in start
    handler_func(fd_obj, events)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
    self._handle_recv()
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
    self._run_callback(callback, msg)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
    callback(*args, **kwargs)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/tornado/stack_context.py", line 275, in null_wrapper
    return fn(*args, **kwargs)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 276, in dispatcher
    return self.dispatch_shell(stream, msg)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
    handler(stream, idents, msg)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 390, in execute_request
    user_expressions, allow_stdin)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/ipykernel/ipkernel.py", line 196, in do_execute
    res = shell.run_cell(code, store_history=store_history, silent=silent)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/ipykernel/zmqshell.py", line 501, in run_cell
    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2717, in run_cell
    interactivity=interactivity, compiler=compiler, result=result)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2821, in run_ast_nodes
    if self.run_code(code, result):
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2881, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-30-cc226ee011a3>", line 13, in <module>
    model.add(BatchNormalization())
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/keras/models.py", line 469, in add
    output_tensor = layer(self.outputs[0])
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/keras/engine/topology.py", line 596, in __call__
    output = self.call(inputs, **kwargs)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/keras/layers/normalization.py", line 190, in call
    training=training)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/keras/backend/tensorflow_backend.py", line 2600, in in_train_phase
    training = learning_phase()
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/keras/backend/tensorflow_backend.py", line 116, in learning_phase
    name='keras_learning_phase')
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/array_ops.py", line 1530, in placeholder
    return gen_array_ops._placeholder(dtype=dtype, shape=shape, name=name)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1954, in _placeholder
    name=name)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
    op_def=op_def)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2506, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "/home/ubuntu/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1269, in __init__
    self._traceback = _extract_stack()

InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'batch_normalization_1/keras_learning_phase' with dtype bool
	 [[Node: batch_normalization_1/keras_learning_phase = Placeholder[dtype=DT_BOOL, shape=<unknown>, _device="/job:localhost/replica:0/task:0/gpu:0"]()]]

[cwzat]

@coltsfan I have the same problem with you. Do you solve it? Thank you!