我试图调整我在博客文章中看到的NN架构：https://sorenbouma.github.io/blog/oneshot/ 我唯一想改变的是输入，而不是（105,105,1）灰度，我希望使用（100,100,3）RGB。因此，我使用Keras来定义博客文章中的架构，但输入不同：
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()
然后我按照论文对我的数据进行网络训练：
#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))
但是我得到了
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)]]
这是完整的错误输出：
---------------------------------------------------------------------------
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)]]
关于错误的Googlign并没有真正说清楚。我在使用Tensorflow时看到了一些关于错误的帖子，但没有关于这个错误和Keras的内容，所以我对发生的事情感到有点困惑。
答案 0 :(得分：0)
我几天前经历过同样的错误 错误的原因是重量初始化 您尝试更改以下代码。
（之前）
convnet.add(Conv2D(64,(10,10),activation='relu',input_shape=input_shape,
kernel_initializer=W_init,kernel_regularizer=l2(2e-4)))
（后）
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)))
请从所有W_init和b_init更改为keras.initializers.RandomNormal（...）。