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Something Is Using Up Most GPU Memory Not Letting Me Train Models with Tensorflow

After a restart and without touching anything else, I open up the Jupyter Notebook and attempt to run the cells that get the GPU to start training.
But in my Terminal I get this message and in the Notebook I get the long error below. (I'm using Ubuntu 16.04, Keras with Tensorflow backend).
87] Found device 1 with properties:
name: GeForce GTX 1080 Ti
major: 6 minor: 1 memoryClockRate (GHz) 1.582
pciBusID 0000:25:00.0
Total memory: 10.91GiB
Free memory: 396.44MiB
Code of the notebook here https://github.com/fastai/courses/blob/master/deeplearning1/nbs/lesson1.ipynb
In cell [5] I've lowered the batch size to 10 and then tried 5. I also set no_of_epochs=5. In addition to restarts I've also tried looking for any command that gets the system to drop any processes the GPU might be using, but it doesn't appear to be using any.
cell [7] is the cell that gives all the errors below when it is run.
This is the full error under the cell [7] that is trying to utilize the GPU.
---------------------------------------------------------------------------
ResourceExhaustedError Traceback (most recent call last)
<ipython-input-7-2b6861506a11> in <module>()
----> 1 vgg = Vgg16()
2 # Grab a few images at a time for training and validation.
3 # NB: They must be in subdirectories named based on their category
4 batches = vgg.get_batches(path+'train', batch_size=batch_size)
5 val_batches = vgg.get_batches(path+'valid', batch_size=batch_size*2)
/home/eagle/fastai/courses-master/deeplearning1/nbs/vgg16.pyc in __init__(self)
45 def __init__(self):
46 self.FILE_PATH = 'http://files.fast.ai/models/'
---> 47 self.create()
48 self.get_classes()
49
/home/eagle/fastai/courses-master/deeplearning1/nbs/vgg16.pyc in create(self)
137
138 fname = 'vgg16.h5'
--> 139 model.load_weights(get_file(fname, self.FILE_PATH+fname, cache_subdir='models'))
140
141
/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/Keras-1.2.2-py2.7.egg/keras/engine/topology.pyc in load_weights(self, filepath, by_name)
2706 self.load_weights_from_hdf5_group_by_name(f)
2707 else:
-> 2708 self.load_weights_from_hdf5_group(f)
2709
2710 if hasattr(f, 'close'):
/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/Keras-1.2.2-py2.7.egg/keras/engine/topology.pyc in load_weights_from_hdf5_group(self, f)
2792 weight_values[0] = w
2793 weight_value_tuples += zip(symbolic_weights, weight_values)
-> 2794 K.batch_set_value(weight_value_tuples)
2795
2796 def load_weights_from_hdf5_group_by_name(self, f):
/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/Keras-1.2.2-py2.7.egg/keras/backend/tensorflow_backend.pyc in batch_set_value(tuples)
1879 assign_ops.append(assign_op)
1880 feed_dict[assign_placeholder] = value
-> 1881 get_session().run(assign_ops, feed_dict=feed_dict)
1882
1883
/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/Keras-1.2.2-py2.7.egg/keras/backend/tensorflow_backend.pyc in get_session()
123 session = _SESSION
124 if not _MANUAL_VAR_INIT:
--> 125 _initialize_variables()
126 return session
127
/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/Keras-1.2.2-py2.7.egg/keras/backend/tensorflow_backend.pyc in _initialize_variables()
280 sess = get_session()
281 if hasattr(tf, 'variables_initializer'):
--> 282 sess.run(tf.variables_initializer(uninitialized_variables))
283 else:
284 sess.run(tf.initialize_variables(uninitialized_variables))
/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in run(self, fetches, feed_dict, options, run_metadata)
776 try:
777 result = self._run(None, fetches, feed_dict, options_ptr,
--> 778 run_metadata_ptr)
779 if run_metadata:
780 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _run(self, handle, fetches, feed_dict, options, run_metadata)
980 if final_fetches or final_targets:
981 results = self._do_run(handle, final_targets, final_fetches,
--> 982 feed_dict_string, options, run_metadata)
983 else:
984 results = []
/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1030 if handle is None:
1031 return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1032 target_list, options, run_metadata)
1033 else:
1034 return self._do_call(_prun_fn, self._session, handle, feed_dict,
/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/tensorflow/python/client/session.pyc in _do_call(self, fn, *args)
1050 except KeyError:
1051 pass
-> 1052 raise type(e)(node_def, op, message)
1053
1054 def _extend_graph(self):
ResourceExhaustedError: OOM when allocating tensor with shape[25088,4096]
[[Node: random_uniform_13/RandomUniform = RandomUniform[T=DT_INT32, dtype=DT_FLOAT, seed=87654321, seed2=755436606, _device="/job:localhost/replica:0/task:0/gpu:0"](random_uniform_13/shape)]]
Caused by op u'random_uniform_13/RandomUniform', defined at:
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/runpy.py", line 174, in _run_module_as_main
"__main__", fname, loader, pkg_name)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/runpy.py", line 72, in _run_code
exec code in run_globals
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/ipykernel/__main__.py", line 3, in <module>
app.launch_new_instance()
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/ipykernel/kernelapp.py", line 478, in start
self.io_loop.start()
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/zmq/eventloop/ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/tornado/ioloop.py", line 888, in start
handler_func(fd_obj, events)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 281, in dispatcher
return self.dispatch_shell(stream, msg)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 232, in dispatch_shell
handler(stream, idents, msg)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/ipykernel/kernelbase.py", line 397, in execute_request
user_expressions, allow_stdin)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/ipykernel/ipkernel.py", line 208, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/ipykernel/zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2718, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2822, in run_ast_nodes
if self.run_code(code, result):
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/IPython/core/interactiveshell.py", line 2882, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-7-2b6861506a11>", line 1, in <module>
vgg = Vgg16()
File "vgg16.py", line 47, in __init__
self.create()
File "vgg16.py", line 134, in create
self.FCBlock()
File "vgg16.py", line 113, in FCBlock
model.add(Dense(4096, activation='relu'))
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/Keras-1.2.2-py2.7.egg/keras/models.py", line 332, in add
output_tensor = layer(self.outputs[0])
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/Keras-1.2.2-py2.7.egg/keras/engine/topology.py", line 546, in __call__
self.build(input_shapes[0])
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/Keras-1.2.2-py2.7.egg/keras/layers/core.py", line 798, in build
constraint=self.W_constraint)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/Keras-1.2.2-py2.7.egg/keras/engine/topology.py", line 418, in add_weight
weight = initializer(shape, name=name)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/Keras-1.2.2-py2.7.egg/keras/initializations.py", line 66, in glorot_uniform
return uniform(shape, s, name=name)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/Keras-1.2.2-py2.7.egg/keras/initializations.py", line 33, in uniform
return K.random_uniform_variable(shape, -scale, scale, name=name)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/Keras-1.2.2-py2.7.egg/keras/backend/tensorflow_backend.py", line 634, in random_uniform_variable
low, high, dtype=tf_dtype, seed=seed)(shape)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/tensorflow/python/ops/init_ops.py", line 189, in __call__
dtype, seed=self.seed)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/tensorflow/python/ops/random_ops.py", line 236, in random_uniform
shape, dtype, seed=seed1, seed2=seed2)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/tensorflow/python/ops/gen_random_ops.py", line 263, in _random_uniform
seed=seed, seed2=seed2, name=name)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op
op_def=op_def)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2336, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/home/eagle/anaconda3/envs/les1/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1228, in __init__
self._traceback = _extract_stack()
ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[25088,4096]
[[Node: random_uniform_13/RandomUniform = RandomUniform[T=DT_INT32, dtype=DT_FLOAT, seed=87654321, seed2=755436606, _device="/job:localhost/replica:0/task:0/gpu:0"](random_uniform_13/shape)]]

After
nvidia-smi
The last line will show the process with a 'pid' number
Enter with the 'pid' number last
with the following command (your four digit number at the end will be your own)
sudo kill -9 3096

FailedPreconditionError: Attempting to use uninitialized value with Keras

I was trying to adapt an NN architecture I saw in a blog post here: https://sorenbouma.github.io/blog/oneshot/
The only thing I was trying to change about it was the input, instead of (105,105,1) greyscale I was hoping to use (100,100,3) RGB. I thus used Keras to define the architecture as in the blog post but with different input:
def W_init(shape,name=None):
"""Initialize weights as in paper"""
values = rng.normal(loc=0,scale=1e-2,size=shape)
return K.variable(values,name=name)
#//TODO: figure out how to initialize layer biases in keras.
def b_init(shape,name=None):
"""Initialize bias as in paper"""
values=rng.normal(loc=0.5,scale=1e-2,size=shape)
return K.variable(values,name=name)
input_shape = (100, 100, 3)
left_input = Input(input_shape)
right_input = Input(input_shape)
#build convnet to use in each siamese 'leg'
convnet = Sequential()
convnet.add(Conv2D(64,(10,10),activation='relu',input_shape=input_shape,
kernel_initializer=W_init,kernel_regularizer=l2(2e-4)))
convnet.add(MaxPooling2D())
convnet.add(Conv2D(128,(7,7),activation='relu',
kernel_regularizer=l2(2e-4),kernel_initializer=W_init,bias_initializer=b_init))
convnet.add(MaxPooling2D())
convnet.add(Conv2D(128,(4,4),activation='relu',kernel_initializer=W_init,kernel_regularizer=l2(2e-4),bias_initializer=b_init))
convnet.add(MaxPooling2D())
convnet.add(Conv2D(256,(4,4),activation='relu',kernel_initializer=W_init,kernel_regularizer=l2(2e-4),bias_initializer=b_init))
convnet.add(Flatten())
convnet.add(Dense(4096,activation="sigmoid",kernel_regularizer=l2(1e-3),kernel_initializer=W_init,bias_initializer=b_init))
#encode each of the two inputs into a vector with the convnet
encoded_l = convnet(left_input)
encoded_r = convnet(right_input)
#merge two encoded inputs with the l1 distance between them
L1_distance = lambda x: K.abs(x[0]-x[1])
both = merge([encoded_l,encoded_r], mode = L1_distance, output_shape=lambda x: x[0])
prediction = Dense(1,activation='sigmoid',bias_initializer=b_init)(both)
siamese_net = Model(input=[left_input,right_input],output=prediction)
#optimizer = SGD(0.0004,momentum=0.6,nesterov=True,decay=0.0003)
optimizer = Adam(0.00006)
#//TODO: get layerwise learning rates and momentum annealing scheme described in paperworking
siamese_net.compile(loss="binary_crossentropy",optimizer=optimizer)
siamese_net.count_params()
I then train the network on my data as in the paper:
#Training loop
evaluate_every = 500
loss_every=50
batch_size = 20
N_way = 20
n_val = 250
#siamese_net.load_weights("/home/soren/keras-oneshot/weights")
max_epochs = 100
for i in range(0,max_epochs):
(inputs,targets)=loader.get_batch(batch_size)
loss=siamese_net.train_on_batch(inputs,targets)
if i % evaluate_every == 0:
val_acc = loader.test_oneshot(siamese_net,N_way,n_val,verbose=True)
if val_acc >= best:
print("saving")
siamese_net.save('/home/soren/keras-oneshot/weights')
best=val_acc
if i % loss_every == 0:
print("iteration {}, training loss: {:.2f},".format(i,loss))
But I get
FailedPreconditionError: Attempting to use uninitialized value conv2d_1/Variable
[[Node: conv2d_1/Variable/read = Identity[T=DT_FLOAT, _class=["loc:#conv2d_1/Variable"], _device="/job:localhost/replica:0/task:0/cpu:0"](conv2d_1/Variable)]]
Here is full error output:
---------------------------------------------------------------------------
FailedPreconditionError Traceback (most recent call last)
/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1138 try:
-> 1139 return fn(*args)
1140 except errors.OpError as e:
/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
1120 feed_dict, fetch_list, target_list,
-> 1121 status, run_metadata)
1122
/usr/lib/python3.4/contextlib.py in __exit__(self, type, value, traceback)
65 try:
---> 66 next(self.gen)
67 except StopIteration:
/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/errors_impl.py in raise_exception_on_not_ok_status()
465 compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 466 pywrap_tensorflow.TF_GetCode(status))
467 finally:
FailedPreconditionError: Attempting to use uninitialized value conv2d_1/Variable
[[Node: conv2d_1/Variable/read = Identity[T=DT_FLOAT, _class=["loc:#conv2d_1/Variable"], _device="/job:localhost/replica:0/task:0/cpu:0"](conv2d_1/Variable)]]
During handling of the above exception, another exception occurred:
FailedPreconditionError Traceback (most recent call last)
<ipython-input-15-06f79f757a6e> in <module>()
9 for i in range(0,max_epochs):
10 (inputs,targets)=loader.get_batch(batch_size)
---> 11 loss=siamese_net.train_on_batch(inputs,targets)
12 if i % evaluate_every == 0:
13 val_acc = loader.test_oneshot(siamese_net,N_way,n_val,verbose=True)
/usr/local/lib/python3.4/dist-packages/keras/engine/training.py in train_on_batch(self, x, y, sample_weight, class_weight)
1563 ins = x + y + sample_weights
1564 self._make_train_function()
-> 1565 outputs = self.train_function(ins)
1566 if len(outputs) == 1:
1567 return outputs[0]
/usr/local/lib/python3.4/dist-packages/keras/backend/tensorflow_backend.py in __call__(self, inputs)
2263 value = (indices, sparse_coo.data, sparse_coo.shape)
2264 feed_dict[tensor] = value
-> 2265 session = get_session()
2266 updated = session.run(self.outputs + [self.updates_op],
2267 feed_dict=feed_dict,
/usr/local/lib/python3.4/dist-packages/keras/backend/tensorflow_backend.py in get_session()
166 if not _MANUAL_VAR_INIT:
167 with session.graph.as_default():
--> 168 _initialize_variables()
169 return session
170
/usr/local/lib/python3.4/dist-packages/keras/backend/tensorflow_backend.py in _initialize_variables()
339 if uninitialized_variables:
340 sess = get_session()
--> 341 sess.run(tf.variables_initializer(uninitialized_variables))
342
343
/usr/local/lib/python3.4/dist-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)
/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py 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 = []
/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py 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,
/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py 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):
FailedPreconditionError: Attempting to use uninitialized value conv2d_1/Variable
[[Node: conv2d_1/Variable/read = Identity[T=DT_FLOAT, _class=["loc:#conv2d_1/Variable"], _device="/job:localhost/replica:0/task:0/cpu:0"](conv2d_1/Variable)]]
Caused by op 'conv2d_1/Variable/read', defined at:
File "/usr/lib/python3.4/runpy.py", line 170, in _run_module_as_main
"__main__", mod_spec)
File "/usr/lib/python3.4/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.4/dist-packages/ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/usr/local/lib/python3.4/dist-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/usr/local/lib/python3.4/dist-packages/ipykernel/kernelapp.py", line 477, in start
ioloop.IOLoop.instance().start()
File "/usr/local/lib/python3.4/dist-packages/zmq/eventloop/ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "/usr/local/lib/python3.4/dist-packages/tornado/ioloop.py", line 888, in start
handler_func(fd_obj, events)
File "/usr/local/lib/python3.4/dist-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.4/dist-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "/usr/local/lib/python3.4/dist-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "/usr/local/lib/python3.4/dist-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "/usr/local/lib/python3.4/dist-packages/tornado/stack_context.py", line 277, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python3.4/dist-packages/ipykernel/kernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "/usr/local/lib/python3.4/dist-packages/ipykernel/kernelbase.py", line 235, in dispatch_shell
handler(stream, idents, msg)
File "/usr/local/lib/python3.4/dist-packages/ipykernel/kernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "/usr/local/lib/python3.4/dist-packages/ipykernel/ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/usr/local/lib/python3.4/dist-packages/ipykernel/zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/usr/local/lib/python3.4/dist-packages/IPython/core/interactiveshell.py", line 2698, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/usr/local/lib/python3.4/dist-packages/IPython/core/interactiveshell.py", line 2802, in run_ast_nodes
if self.run_code(code, result):
File "/usr/local/lib/python3.4/dist-packages/IPython/core/interactiveshell.py", line 2862, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-2-51595f796dab>", line 17, in <module>
kernel_initializer=W_init,kernel_regularizer=l2(2e-4)))
File "/usr/local/lib/python3.4/dist-packages/keras/models.py", line 436, in add
layer(x)
File "/usr/local/lib/python3.4/dist-packages/keras/engine/topology.py", line 569, in __call__
self.build(input_shapes[0])
File "/usr/local/lib/python3.4/dist-packages/keras/layers/convolutional.py", line 134, in build
constraint=self.kernel_constraint)
File "/usr/local/lib/python3.4/dist-packages/keras/legacy/interfaces.py", line 87, in wrapper
return func(*args, **kwargs)
File "/usr/local/lib/python3.4/dist-packages/keras/engine/topology.py", line 391, in add_weight
weight = K.variable(initializer(shape), dtype=dtype, name=name)
File "<ipython-input-2-51595f796dab>", line 4, in W_init
return K.variable(values,name=name)
File "/usr/local/lib/python3.4/dist-packages/keras/backend/tensorflow_backend.py", line 321, in variable
v = tf.Variable(value, dtype=_convert_string_dtype(dtype), name=name)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/variables.py", line 200, in __init__
expected_shape=expected_shape)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/variables.py", line 319, in _init_from_args
self._snapshot = array_ops.identity(self._variable, name="read")
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 1303, in identity
result = _op_def_lib.apply_op("Identity", input=input, name=name)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op
op_def=op_def)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/ops.py", line 2506, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/ops.py", line 1269, in __init__
self._traceback = _extract_stack()
FailedPreconditionError (see above for traceback): Attempting to use uninitialized value conv2d_1/Variable
[[Node: conv2d_1/Variable/read = Identity[T=DT_FLOAT, _class=["loc:#conv2d_1/Variable"], _device="/job:localhost/replica:0/task:0/cpu:0"](conv2d_1/Variable)]]
Googlign about the error did not really make things clear. I saw some posts about the error coming up when using Tensorflow, but nothing regarding this erro and Keras, so I am a little bit confused about what is going on.

I experienced the same error a few days ago.
The cause of the error is weight initialization.
you try to change the follow code.
(before)
convnet.add(Conv2D(64,(10,10),activation='relu',input_shape=input_shape,
kernel_initializer=W_init,kernel_regularizer=l2(2e-4)))
(after)
convnet.add(Conv2D(64,(10,10),activation='relu',input_shape=input_shape,
kernel_initializer=keras.initializers.RandomNormal(mean=0.0,
stddev=1e-2, seed=None),kernel_regularizer=l2(2e-4)))
Please change from all W_init and b_init to keras.initializers.RandomNormal(...).

Reading PNG files using Tensorflow

I want to build a conVNN based on my own image dataset. for that I first I need to read the files here's what I've done :
import tensorflow as tf
# Here generating a tensor of type string that include all the filename with png extention
filename_queue = tf.train.string_input_producer(tf.train.match_filenames_once("test_png/*.png"))
# Initializing a file Reader
image_reader = tf.WholeFileReader()
# Here the file all the files mentioned ie filename queue and
# returns the the file name and the pixelvalue in form of a tensor !
imageName,imagefile= image_reader.read(filename_queue)
image = tf.image.decode_png(imagefile)
tf.global_variables_initializer()
with tf.Session() as sess:
# Coordinate the loading of image files.
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(coord=coord)
# Get an image tensor and print its value.
image_tensor = sess.run([image])
print(image_tensor)
# Finish off the filename queue coordinator.
coord.request_stop()
coord.join(threads)
to make things easy: the test folder contains 10 png files named 1.png 2.png .... 10.png
when I run the code I get the following :
INFO:tensorflow:Error reported to Coordinator: <class 'tensorflow.python.framework.errors_impl.FailedPreconditionError'>, Attempting to use uninitialized value matching_filenames
[[Node: matching_filenames/read = Identity[T=DT_STRING, _class=["loc:#matching_filenames"], _device="/job:localhost/replica:0/task:0/cpu:0"](matching_filenames)]]
Caused by op 'matching_filenames/read', defined at:
File "c:\users\engine\appdata\local\programs\python\python35\lib\runpy.py", line 184, in _run_module_as_main
"__main__", mod_spec)
File "c:\users\engine\appdata\local\programs\python\python35\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\__main__.py", line 3, in <module>
app.launch_new_instance()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\traitlets\config\application.py", line 658, in launch_instance
app.start()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelapp.py", line 474, in start
ioloop.IOLoop.instance().start()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\ioloop.py", line 887, in start
handler_func(fd_obj, events)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 276, in dispatcher
return self.dispatch_shell(stream, msg)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 228, in dispatch_shell
handler(stream, idents, msg)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 390, in execute_request
user_expressions, allow_stdin)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\zmqshell.py", line 501, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2717, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2821, in run_ast_nodes
if self.run_code(code, result):
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2881, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-1-110a62c88def>", line 3, in <module>
filename_queue = tf.train.string_input_producer(tf.train.match_filenames_once("test_png/*.png"))
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\training\input.py", line 68, in match_filenames_once
collections=[ops.GraphKeys.LOCAL_VARIABLES])
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\ops\variables.py", line 197, in __init__
expected_shape=expected_shape)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\ops\variables.py", line 316, in _init_from_args
self._snapshot = array_ops.identity(self._variable, name="read")
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 1338, in identity
result = _op_def_lib.apply_op("Identity", input=input, name=name)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 768, in apply_op
op_def=op_def)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\ops.py", line 2336, in create_op
original_op=self._default_original_op, op_def=op_def)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\ops.py", line 1228, in __init__
self._traceback = _extract_stack()
FailedPreconditionError (see above for traceback): Attempting to use uninitialized value matching_filenames
[[Node: matching_filenames/read = Identity[T=DT_STRING, _class=["loc:#matching_filenames"], _device="/job:localhost/replica:0/task:0/cpu:0"](matching_filenames)]]
---------------------------------------------------------------------------
OutOfRangeError Traceback (most recent call last)
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args)
1038 try:
-> 1039 return fn(*args)
1040 except errors.OpError as e:
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
1020 feed_dict, fetch_list, target_list,
-> 1021 status, run_metadata)
1022
c:\users\engine\appdata\local\programs\python\python35\lib\contextlib.py in __exit__(self, type, value, traceback)
65 try:
---> 66 next(self.gen)
67 except StopIteration:
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\errors_impl.py in raise_exception_on_not_ok_status()
465 compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 466 pywrap_tensorflow.TF_GetCode(status))
467 finally:
OutOfRangeError: FIFOQueue '_0_input_producer' is closed and has insufficient elements (requested 1, current size 0)
[[Node: ReaderReadV2 = ReaderReadV2[_device="/job:localhost/replica:0/task:0/cpu:0"](WholeFileReaderV2, input_producer)]]
During handling of the above exception, another exception occurred:
OutOfRangeError Traceback (most recent call last)
<ipython-input-1-110a62c88def> in <module>()
16
17 # Get an image tensor and print its value.
---> 18 image_tensor = sess.run([image])
19 print(image_tensor)
20
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in run(self, fetches, feed_dict, options, run_metadata)
776 try:
777 result = self._run(None, fetches, feed_dict, options_ptr,
--> 778 run_metadata_ptr)
779 if run_metadata:
780 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
980 if final_fetches or final_targets:
981 results = self._do_run(handle, final_targets, final_fetches,
--> 982 feed_dict_string, options, run_metadata)
983 else:
984 results = []
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1030 if handle is None:
1031 return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1032 target_list, options, run_metadata)
1033 else:
1034 return self._do_call(_prun_fn, self._session, handle, feed_dict,
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args)
1050 except KeyError:
1051 pass
-> 1052 raise type(e)(node_def, op, message)
1053
1054 def _extend_graph(self):
OutOfRangeError: FIFOQueue '_0_input_producer' is closed and has insufficient elements (requested 1, current size 0)
[[Node: ReaderReadV2 = ReaderReadV2[_device="/job:localhost/replica:0/task:0/cpu:0"](WholeFileReaderV2, input_producer)]]
Caused by op 'ReaderReadV2', defined at:
File "c:\users\engine\appdata\local\programs\python\python35\lib\runpy.py", line 184, in _run_module_as_main
"__main__", mod_spec)
File "c:\users\engine\appdata\local\programs\python\python35\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\__main__.py", line 3, in <module>
app.launch_new_instance()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\traitlets\config\application.py", line 658, in launch_instance
app.start()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelapp.py", line 474, in start
ioloop.IOLoop.instance().start()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\ioloop.py", line 887, in start
handler_func(fd_obj, events)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 276, in dispatcher
return self.dispatch_shell(stream, msg)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 228, in dispatch_shell
handler(stream, idents, msg)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 390, in execute_request
user_expressions, allow_stdin)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\zmqshell.py", line 501, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2717, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2821, in run_ast_nodes
if self.run_code(code, result):
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2881, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-1-110a62c88def>", line 9, in <module>
imageName,imagefile= image_reader.read(filename_queue)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\ops\io_ops.py", line 193, in read
return gen_io_ops._reader_read_v2(self._reader_ref, queue_ref, name=name)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\ops\gen_io_ops.py", line 411, in _reader_read_v2
queue_handle=queue_handle, name=name)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 768, in apply_op
op_def=op_def)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\ops.py", line 2336, in create_op
original_op=self._default_original_op, op_def=op_def)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\ops.py", line 1228, in __init__
self._traceback = _extract_stack()
OutOfRangeError (see above for traceback): FIFOQueue '_0_input_producer' is closed and has insufficient elements (requested 1, current size 0)
[[Node: ReaderReadV2 = ReaderReadV2[_device="/job:localhost/replica:0/task:0/cpu:0"](WholeFileReaderV2, input_producer)]]
To be honest I have no clew how I'm suppose to solve this ?
thanks in advance for any hint
Update
After Ujjwal answer I've the the parameter for tf.train.string_input_producer as followed :
import tensorflow as tf
import os
files = os.listdir('test_png')
# Here generating a tensor of type string that include all the filename with png extention
filename_queue = tf.train.string_input_producer(files)
# Initializing a file Reader
image_reader = tf.WholeFileReader()
# Here the file all the files mentioned ie filename queue and
# returns the the file name and the pixelvalue in form of a tensor !
imageName,imagefile= image_reader.read(filename_queue)
image = tf.image.decode_png(imagefile)
#tf.global_variables_initializer()
with tf.Session() as sess:
tf.global_variables_initializer().run()
# Coordinate the loading of image files.
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(coord=coord)
# Get an image tensor and print its value.
image_tensor = sess.run([image])
print(image_tensor)
# Finish off the filename queue coordinator.
coord.request_stop()
coord.join(threads)
Now it seem that TF can find the files but still can't read them, here's the actual error message :
[Command: python -u D:\Masterarbeit\Tensorflow\Main\convNN\own_DATA.py]
2017-06-08 15:12:31.845015: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE instructions, but these are available on your machine and could speed up CPU computations.
2017-06-08 15:12:31.845384: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE2 instructions, but these are available on your machine and could speed up CPU computations.
2017-06-08 15:12:31.845662: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
2017-06-08 15:12:31.845949: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
2017-06-08 15:12:31.846859: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
2017-06-08 15:12:31.847174: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-06-08 15:12:31.847464: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
2017-06-08 15:12:31.847754: W c:\tf_jenkins\home\workspace\release-win\device\cpu\os\windows\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Traceback (most recent call last):
File "C:\Users\Engine\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1039, in _do_call
return fn(*args)
File "C:\Users\Engine\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1021, in _run_fn
status, run_metadata)
File "C:\Users\Engine\AppData\Local\Programs\Python\Python35\lib\contextlib.py", line 66, in __exit__
next(self.gen)
File "C:\Users\Engine\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 466, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.NotFoundError: Can not get size for: 4.png : The system cannot find the file specified.
[[Node: ReaderReadV2 = ReaderReadV2[_device="/job:localhost/replica:0/task:0/cpu:0"](WholeFileReaderV2, input_producer)]]
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "D:\Masterarbeit\Tensorflow\Main\convNN\own_DATA.py", line 22, in <module>
image_tensor = sess.run([image])
File "C:\Users\Engine\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 778, in run
run_metadata_ptr)
File "C:\Users\Engine\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 982, in _run
feed_dict_string, options, run_metadata)
File "C:\Users\Engine\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1032, in _do_run
target_list, options, run_metadata)
File "C:\Users\Engine\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1052, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.NotFoundError: Can not get size for: 4.png : The system cannot find the file specified.
[[Node: ReaderReadV2 = ReaderReadV2[_device="/job:localhost/replica:0/task:0/cpu:0"](WholeFileReaderV2, input_producer)]]
Caused by op 'ReaderReadV2', defined at:
File "D:\Masterarbeit\Tensorflow\Main\convNN\own_DATA.py", line 12, in <module>
imageName,imagefile= image_reader.read(filename_queue)
File "C:\Users\Engine\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\ops\io_ops.py", line 193, in read
return gen_io_ops._reader_read_v2(self._reader_ref, queue_ref, name=name)
File "C:\Users\Engine\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\ops\gen_io_ops.py", line 411, in _reader_read_v2
queue_handle=queue_handle, name=name)
File "C:\Users\Engine\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 768, in apply_op
op_def=op_def)
File "C:\Users\Engine\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 2336, in create_op
original_op=self._default_original_op, op_def=op_def)
File "C:\Users\Engine\AppData\Local\Programs\Python\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 1228, in __init__
self._traceback = _extract_stack()
NotFoundError (see above for traceback): Can not get size for: 4.png : The system cannot find the file specified.
[[Node: ReaderReadV2 = ReaderReadV2[_device="/job:localhost/replica:0/task:0/cpu:0"](WholeFileReaderV2, input_producer)]]
[Finished in 1.972s]
Update
Based on Ujjwal answer is the code that I'm using now, hopefully it may help someone out there :
import tensorflow as tf
import os
# list files name
files = os.listdir("Test_PNG")
files = ["Test_PNG/" + s for s in files]
files = [os.path.abspath(s) for s in files ]
# Here generating a tensor of type string that include all the filename with png extention
filename_queue = tf.train.string_input_producer(files)
# Initializing a file Reader
image_reader = tf.WholeFileReader()
# Here the file all the files mentioned ie filename queue and
# returns the the file name and the pixelvalue in form of a tensor !
imageName,imagefile= image_reader.read(filename_queue)
image = tf.image.decode_png(imagefile)
#tf.global_variables_initializer()
with tf.Session() as sess:
tf.global_variables_initializer().run()
# Coordinate the loading of image files.
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(coord=coord)
# Get an image tensor and print its value.
image_tensor = sess.run([image])
print(image_tensor)
# Finish off the filename queue coordinator.
coord.request_stop()
coord.join(threads)

You have to initialize the variables. Try moving tf.global_variables_initializer() inside tf.Session() as sess: block and run it as tf.global_variables_initializer().run()

Feed_dict and numpy reshape

say I have a tensorflow shape:
y_ = tf.placeholder(tf.float32,[None,19],name='Labels')
My thinking here is to get each time 19 a vector of 19 elements and add it(pluging) it to y_
and list inputlabel with 57 as length:
I want to feed the line this list into y_
sess.run(train_step,feed_dict={x:xdata,y_:np.reshape(inputlabel,(3,19))})
this feeding isn't working and I really don't get how may I solve itl. here is the error message that I get:
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args)
1021 try:
-> 1022 return fn(*args)
1023 except errors.OpError as e:
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _run_fn(session, feed_dict, fetch_list, target_list, options, run_metadata)
1003 feed_dict, fetch_list, target_list,
-> 1004 status, run_metadata)
1005
c:\users\engine\appdata\local\programs\python\python35\lib\contextlib.py in __exit__(self, type, value, traceback)
65 try:
---> 66 next(self.gen)
67 except StopIteration:
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\errors_impl.py in raise_exception_on_not_ok_status()
465 compat.as_text(pywrap_tensorflow.TF_Message(status)),
--> 466 pywrap_tensorflow.TF_GetCode(status))
467 finally:
InvalidArgumentError: You must feed a value for placeholder tensor 'Labels' with dtype float
[[Node: Labels = Placeholder[dtype=DT_FLOAT, 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-7-1da2dc43ca63> in <module>()
1 for j in range(len(batch_xs)-1):
----> 2 print(sess.run(train_step,feed_dict={x:batch_xs[j],y_:np.reshape(batch_ys[j],(3,numberOFClasses))}))
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in run(self, fetches, feed_dict, options, run_metadata)
765 try:
766 result = self._run(None, fetches, feed_dict, options_ptr,
--> 767 run_metadata_ptr)
768 if run_metadata:
769 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
963 if final_fetches or final_targets:
964 results = self._do_run(handle, final_targets, final_fetches,
--> 965 feed_dict_string, options, run_metadata)
966 else:
967 results = []
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1013 if handle is None:
1014 return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
-> 1015 target_list, options, run_metadata)
1016 else:
1017 return self._do_call(_prun_fn, self._session, handle, feed_dict,
c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\client\session.py in _do_call(self, fn, *args)
1033 except KeyError:
1034 pass
-> 1035 raise type(e)(node_def, op, message)
1036
1037 def _extend_graph(self):
InvalidArgumentError: You must feed a value for placeholder tensor 'Labels' with dtype float
[[Node: Labels = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
Caused by op 'Labels', defined at:
File "c:\users\engine\appdata\local\programs\python\python35\lib\runpy.py", line 184, in _run_module_as_main
"__main__", mod_spec)
File "c:\users\engine\appdata\local\programs\python\python35\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\__main__.py", line 3, in <module>
app.launch_new_instance()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\traitlets\config\application.py", line 658, in launch_instance
app.start()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelapp.py", line 474, in start
ioloop.IOLoop.instance().start()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\ioloop.py", line 887, in start
handler_func(fd_obj, events)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\zmq\eventloop\zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tornado\stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 276, in dispatcher
return self.dispatch_shell(stream, msg)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 228, in dispatch_shell
handler(stream, idents, msg)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\kernelbase.py", line 390, in execute_request
user_expressions, allow_stdin)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\ipkernel.py", line 196, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\ipykernel\zmqshell.py", line 501, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2717, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2821, in run_ast_nodes
if self.run_code(code, result):
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\IPython\core\interactiveshell.py", line 2881, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-3-49d5bdb3e7ad>", line 6, in <module>
y_ = tf.placeholder(tf.float32,[None],name='Labels')
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\ops\array_ops.py", line 1502, in placeholder
name=name)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\ops\gen_array_ops.py", line 2149, in _placeholder
name=name)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 763, in apply_op
op_def=op_def)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\ops.py", line 2327, in create_op
original_op=self._default_original_op, op_def=op_def)
File "c:\users\engine\appdata\local\programs\python\python35\lib\site-packages\tensorflow\python\framework\ops.py", line 1226, in __init__
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Labels' with dtype float
[[Node: Labels = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
**Update **
Inputlabel is declared as followed:
..............
inputlabel =[]
..................
for i in batch(Training_Data,batchSize):
inputlabel.append(i)
def batch(iterable, n=1):
l = len(iterable)
for ndx in range(0, l, n):
yield iterable[ndx:min(ndx + n, l)]
No that the type issue is solve I get an other weird stuff :
InvalidArgumentError (see above for traceback): Incompatible shapes: [3,19] vs. [57,19]
[[Node: gradients/mul_grad/BroadcastGradientArgs = BroadcastGradientArgs[T=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](gradients/mul_grad/Shape, gradients/mul_grad/Shape_1)]]

This works:
import numpy as np
import tensorflow as tf
y_ = tf.placeholder(tf.float32,[None,19],name='Labels')
sess = tf.InteractiveSession()
labels = np.zeros(57, dtype=np.float32)
sess.run(y_, feed_dict = {y_: np.reshape(labels, (3,19))})
Could it be that your inputlabel is of the wrong type?

You just need to convert the list of (nSamples) integers coding the 1-hot label to an array of shape (nSamples, 19) containing only 0s and 1s when you import your data,
eg (1, 8, 2) -> [[1, 0, 0, ...], [0, 0, 1, 0, 0, ...], [0, 1, 0, 0, ...]]
You could do it like that:
label_1_hot_coding = row[-1]
array_of_bits = np.zeros(numberOFClasses)
n = 1
for i,_in enumerate(array_of_bits):
if n== label_1_hot_coding:
array_of_bits[i] = 1
Training_Labels.append(array_of_bits)
Your labels are now naturally of shape (nSamples, numberOfClasses), and the batches of shape (batchSize, numberOfClasses), which is what the rest of your program wants.

TensorFlow missing CPU Op for FFT (InvalidArgumentError: No OpKernel was registered to support Op 'FFT' with these attrs)

I am new to tensorflow and want to create a graph which performs fft on real data, similar to numpys rfft function:
def rfftOp(_in, name='rfft', graph=tf.get_default_graph()):
with graph.as_default():
with tf.device('/cpu:0'):
with tf.name_scope(name):
cast = tf.complex(tf.cast(_in, tf.float32, name='cast_to_float32'), tf.constant(0.0, dtype=tf.float32), name='cast_to_complex')
fftOp = tf.fft(cast, name='fft')
half, _ = tf.split(0, 2, fftOp, name='split')
double = tf.mul(tf.constant(2.0, dtype=tf.complex64), half)
return double
sess = tf.InteractiveSession()
inp = tf.placeholder(np.float64, shape=(256,), name='input')
fftOp = rfftOp(inp)
print(sess.run(fftOp, feed_dict={inp: d}))
However, I am getting the following error message:
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
<ipython-input-18-0f6d789c912c> in <module>()
6 inp = tf.placeholder(np.float64, shape=(256,), name='input')
7 fftOp = rfftOp(inp)
----> 8 print(sess.run(fftOp, feed_dict={inp: d}))
/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in run(self, fetches, feed_dict, options, run_metadata)
338 try:
339 result = self._run(None, fetches, feed_dict, options_ptr,
--> 340 run_metadata_ptr)
341 if run_metadata:
342 proto_data = tf_session.TF_GetBuffer(run_metadata_ptr)
/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _run(self, handle, fetches, feed_dict, options, run_metadata)
562 try:
563 results = self._do_run(handle, target_list, unique_fetches,
--> 564 feed_dict_string, options, run_metadata)
565 finally:
566 # The movers are no longer used. Delete them.
/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
635 if handle is None:
636 return self._do_call(_run_fn, self._session, feed_dict, fetch_list,
--> 637 target_list, options, run_metadata)
638 else:
639 return self._do_call(_prun_fn, self._session, handle, feed_dict,
/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.pyc in _do_call(self, fn, *args)
657 # pylint: disable=protected-access
658 raise errors._make_specific_exception(node_def, op, error_message,
--> 659 e.code)
660 # pylint: enable=protected-access
661
InvalidArgumentError: No OpKernel was registered to support Op 'FFT' with these attrs
[[Node: rfft_4/fft = FFT[_device="/device:CPU:0"](rfft_4/cast_to_complex)]]
Caused by op u'rfft_4/fft', defined at:
File "/usr/lib/python2.7/runpy.py", line 162, in _run_module_as_main
"__main__", fname, loader, pkg_name)
File "/usr/lib/python2.7/runpy.py", line 72, in _run_code
exec code in run_globals
File "/usr/local/lib/python2.7/dist-packages/ipykernel/__main__.py", line 3, in <module>
app.launch_new_instance()
File "/usr/local/lib/python2.7/dist-packages/traitlets/config/application.py", line 596, in launch_instance
app.start()
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelapp.py", line 442, in start
ioloop.IOLoop.instance().start()
File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/ioloop.py", line 162, in start
super(ZMQIOLoop, self).start()
File "/usr/local/lib/python2.7/dist-packages/tornado/ioloop.py", line 883, in start
handler_func(fd_obj, events)
File "/usr/local/lib/python2.7/dist-packages/tornado/stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py", line 440, in _handle_events
self._handle_recv()
File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py", line 472, in _handle_recv
self._run_callback(callback, msg)
File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/zmqstream.py", line 414, in _run_callback
callback(*args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/tornado/stack_context.py", line 275, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 276, in dispatcher
return self.dispatch_shell(stream, msg)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 228, in dispatch_shell
handler(stream, idents, msg)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 391, in execute_request
user_expressions, allow_stdin)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/ipkernel.py", line 199, in do_execute
shell.run_cell(code, store_history=store_history, silent=silent)
File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2723, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2825, in run_ast_nodes
if self.run_code(code, result):
File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2885, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-18-0f6d789c912c>", line 7, in <module>
fftOp = rfftOp(inp)
File "<ipython-input-17-e44d5219afe4>", line 6, in rfftOp
fftOp = tf.fft(cast, name='fft')
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_math_ops.py", line 518, in fft
return _op_def_lib.apply_op("FFT", in_=in_, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/op_def_library.py", line 655, in apply_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2154, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1154, in __init__
self._traceback = _extract_stack()
indicating that the Op for tensorflows fft is missing.
I've found a similar issue, but it focus on the GPU Op.
I am using the tensorflow/tensorflow docker image.
So, is there anything missing in the docker image or do I have to use tensorflows fft another way?

You are forcing TensorFlow to try to run the FFT operation on CPU by calling with tf.device('/cpu:0'). However the FFT operations are currently only implemented for GPU, which is why you end up with an error message.
If you have a GPU available you can simply remove the call to tf.device(). TensorFlow will then automatically run the FFT operation on GPU.

This problem is solved in version 1.3 of TensorFlow.