Python FailedPremissionError:尝试将未初始化的值与Keras一起使用
我在这里的一篇博文中看到了一个NN体系结构，我试图对其进行调整： 我唯一想改变的是输入，而不是我希望使用（100100,3）RGB的（105105,1）灰度。因此，我在博客文章中使用Keras来定义架构，但输入不同：Python FailedPremissionError:尝试将未初始化的值与Keras一起使用,python,keras,Python,Keras,我在这里的一篇博文中看到了一个NN体系结构，我试图对其进行调整： 我唯一想改变的是输入，而不是我希望使用（100100,3）RGB的（105105,1）灰度。因此，我在博客文章中使用Keras来定义架构，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.varia
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()
#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))
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)]]
---------------------------------------------------------------------------
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)]]
---------------------------------------------------------------------------
FailedPremissionError回溯（最近一次调用上次）
/调用中的usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py（self，fn，*args）
1138尝试：
->1139返回fn（*args）
1140错误除外。操作错误为e:
/运行fn中的usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py（会话、提要、获取列表、目标列表、选项、运行元数据）
1120进货目录、进货目录、目标目录、，
->1121状态，运行（元数据）
1122
/usr/lib/python3.4/contextlib.py in___________（self、type、value、traceback）
65尝试：
--->66下一个（self.gen）
67除停止迭代外：
/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/errors\u impl.py在raise\u exception\u on\u not\u ok\u status（）中
465兼容as_文本（pywrap_tensorflow.TF_消息（状态）），
-->466 pywrap_tensorflow.TF_GetCode（状态））
467最后：
FailedPremissionError:尝试使用未初始化的值conv2d_1/变量
[[Node:conv2d_1/Variable/read=Identity[T=DT_FLOAT，[u class=[“loc:@conv2d_1/Variable”]，[u device=“/job:localhost/replica:0/task:0/cpu:0”]（conv2d_1/Variable）]]
在处理上述异常期间，发生了另一个异常：
FailedPremissionError回溯（最近一次调用上次）
在（）
范围内的i为9（0，最大纪元）：
10（输入，目标）=装入器。获取批次（批次大小）
--->11损失=暹罗净生产线批量（输入、目标）
12如果i%evaluate_every==0：
13 val_acc=加载程序。test_oneshot（暹罗网，N_路，N_val，verbose=True）
/usr/local/lib/python3.4/dist-packages/keras/engine/training.py批量生产（自身、x、y、样品重量、等级重量）
1563英寸=x+y+样本重量
1564自我制作训练功能（）
->1565输出=自列车功能（ins）
1566如果len（输出）==1：
1567返回输出[0]
/usr/local/lib/python3.4/dist-packages/keras/backend/tensorflow\u backend.py in\uuuuuu调用（self，输入）
2263值=（索引、稀疏coo.data、稀疏coo.shape）
2264进给量[tensor]=值
->2265会话=获取会话（）
2266 updated=session.run（self.outputs+[self.updates\u op]，
2267馈送指令=馈送指令，
/get_session（）中的usr/local/lib/python3.4/dist-packages/keras/backend/tensorflow_backend.py
166如果不是手动变量初始化：
167带有session.graph.as_default（）：
-->168_初始化_变量（）
169返回会议
170
/usr/local/lib/python3.4/dist-packages/keras/backend/tensorflow_backend.py in_initialize_variables（）
339如果未初始化的_变量：
340 sess=获取会话（）
-->341 sess.run（tf.variables\u初始值设定项（未初始化的\u变量））
342
343
/运行中的usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py（self、fetches、feed\u dict、options、run\u元数据）
787尝试：
788结果=self.\u运行（无、取数、输入、选项、，
-->789运行（元数据）
790如果运行\u元数据：
791 proto_data=tf_session.tf_GetBuffer（run_metadata_ptr）
/运行中的usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py（self、handle、fetches、feed、dict、options、run\u元数据）
995如果最终_获取或最终_目标：
996 results=self.\u do\u run（句柄、最终目标、最终获取、，
-->997提要内容（字符串、选项、运行元数据）
998其他：
999结果=[]
/usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py in_do_运行（self、handle、target_列表、fetch_列表、feed_dict、options、run_元数据）
1130如果句柄为“无”：
1131返回self.\u do\u call（\u run\u fn，self.\u session，feed\u dict，fetch\u list，
->1132目标\u列表、选项、运行\u元数据）
1133其他：
1134返回self.\u do.\u调用（\u prun\u fn，self.\u会话，句柄，提要\u dict，
/调用中的usr/local/lib/python3.4/dist-packages/tensorflow/python/client/session.py（self，fn，*args）
1150键错误除外：
1151通行证
->1152提升类型（e）（节点定义、操作、消息）
1153
1154定义扩展图（自）：
FailedPremissionError:尝试使用未初始化的值conv2d_1/变量
[[Node:conv2d_1/Variable/read=Identity[T=DT_FLOAT，[u class=[“loc:@conv2d_1/Variable”]，[u device=“/job:localhost/replica:0/task:0/cpu:0”]（conv2d_1/Variable）]]
由op“conv2d_1/变量/读取”引起，定义于：
文件“/usr/lib/python3.4/runpy.py”，第170行，在运行模块中作为主模块
“\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu
文件“/usr/lib/python3.4/runpy.py”，第85行，在运行代码中
exec（代码、运行\全局）
文件“/usr/local/lib/python3.4/dist packages/ipykernel_launcher.py”，第16行，在
app.launch_new_instance（）
文件“/usr/local/lib/python3.4/dist-packages/traitlets/config/application.py”，第658行，在launch_实例中
app.start（）
文件“/usr/local/lib/pytho
convnet.add(Conv2D(64,(10,10),activation='relu',input_shape=input_shape,
kernel_initializer=W_init,kernel_regularizer=l2(2e-4)))
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)))