나는 훈련 한 나의 모델을 사용하려고, tensorflow에서 모델을 복원하고 그런 다음 나는 동일한 그래프를 다시 재현하는 모델을 복원하려고 초기화되지 않은 변수 값 오류 메시지
saver = tf.train.Saver()
saver.save(sess, '/final_model', global_step = i)
를 사용하여 그것을 저장 내 결과, 복원 작동하지만 네트워크 매개 변수 또는 작업의 모든 값에 액세스하려고하면 그것은 초기화되지 않은 변수를 사용하려고하면 오류가 발생합니다.
그래프를 재건 후, 복원하는 데 사용하는 코드는 다음과 같습니다 그러나
sess=tf.Session()
new_saver = tf.train.import_meta_graph('final_model-699.meta')
new_saver.restore(sess, tf.train.latest_checkpoint('./'))
는 나에게 초기화되지 않은 변수
print(sess.run(weights['hidden1']))
print(sess.run(loss_f, feed_dict={x: train_x, y_: train_y}))
어떤 생각을 사용하려고 시도의 오류를주고 그 중 하나를 다음 ? 결과 복원 및 재생
train_x = np.random.rand(200,2)
w= np.array([2,3])
train_y = np.dot(train_x, w)
train_y = np.reshape(train_y, [200,1])
feature_dim = 2
output_dim = 1
x = tf.placeholder(tf.float32, [None, feature_dim])
y_ = tf.placeholder(tf.float32, [None, output_dim])
weights = {
'hidden1': tf.Variable(tf.random_normal([feature_dim, output_dim], stddev=1/np.sqrt(feature_dim)))
}
def network1(data):
output = tf.matmul(x, weights['hidden1'])
return output
y = network1(x)
loss_f = output_dim * tf.reduce_mean(tf.squared_difference(y, y_))
optimizer_f = tf.train.AdamOptimizer(1e-4).minimize(loss_f)
saver = tf.train.Saver()
sess = tf.Session()
sess.run(tf.global_variables_initializer())
for i in range(10000):
batch_x = train_x
batch_y = train_y
sess.run(optimizer_f, feed_dict={x: batch_x, y_: batch_y})
print(sess.run(loss_f, feed_dict={x: batch_x, y_: batch_y}))
saver.save(sess,'./savedmodel/', global_step = i)
import scipy.io
import numpy as np
import tensorflow as tf
import random
train_x = np.random.rand(200,2)
w= np.array([2,3])
train_y = np.dot(train_x, w)
train_y = np.reshape(train_y, [200,1])
feature_dim = 2
output_dim = 1
x = tf.placeholder(tf.float32, [None, feature_dim])
y_ = tf.placeholder(tf.float32, [None, output_dim])
weights = {
'hidden1': tf.Variable(tf.random_normal([feature_dim, output_dim], stddev=1/np.sqrt(feature_dim)))
}
def network1(data):
output = tf.matmul(x, weights['hidden1'])
return output
y = network1(x)
loss_f = tf.reduce_mean(tf.squared_difference(y, y_))
optimizer_f = tf.train.AdamOptimizer(1e-4).minimize(loss_f)
sess = tf.Session()
saver = tf.train.import_meta_graph('./savedmodel/-9999.meta')
saver.restore(sess, tf.train.latest_checkpoint('./savedmodel/'))
print(sess.run(loss_f, feed_dict={x: train_x, y_: train_y}))
오류 : 대한
FailedPreconditionErrorTraceback (most recent call last)
<ipython-input-5-17910473afab> in <module>()
----> 1 print(sess.run(loss_f, feed_dict={x: train_x, y_: train_y}))
/usr/local/lib/python2.7/dist-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)
/usr/local/lib/python2.7/dist-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 = []
/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)
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,
/usr/local/lib/python2.7/dist-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):
FailedPreconditionError: Attempting to use uninitialized value Variable
[[Node: Variable/read = Identity[T=DT_FLOAT, _class=["loc:@Variable"], _device="/job:localhost/replica:0/task:0/gpu:0"](Variable)]]
[[Node: Mean/_15 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_7_Mean", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
Caused by op u'Variable/read', defined at:
File "/usr/lib/python2.7/runpy.py", line 174, 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_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/usr/local/lib/python2.7/dist-packages/traitlets/config/application.py", line 658, in launch_instance
app.start()
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelapp.py", line 477, in start
ioloop.IOLoop.instance().start()
File "/usr/local/lib/python2.7/dist-packages/zmq/eventloop/ioloop.py", line 177, in start
super(ZMQIOLoop, self).start()
File "/usr/local/lib/python2.7/dist-packages/tornado/ioloop.py", line 888, in start
handler_func(fd_obj, events)
File "/usr/local/lib/python2.7/dist-packages/tornado/stack_context.py", line 277, 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 277, in null_wrapper
return fn(*args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 283, in dispatcher
return self.dispatch_shell(stream, msg)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 235, in dispatch_shell
handler(stream, idents, msg)
File "/usr/local/lib/python2.7/dist-packages/ipykernel/kernelbase.py", line 399, in execute_request
user_expressions, allow_stdin)
File "/usr/local/lib/python2.7/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/python2.7/dist-packages/ipykernel/zmqshell.py", line 533, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2718, in run_cell
interactivity=interactivity, compiler=compiler, result=result)
File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2822, in run_ast_nodes
if self.run_code(code, result):
File "/usr/local/lib/python2.7/dist-packages/IPython/core/interactiveshell.py", line 2882, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-3-7d229041d9bb>", line 6, in <module>
'hidden1': tf.Variable(tf.random_normal([feature_dim, output_dim], stddev=1/np.sqrt(feature_dim)))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variables.py", line 197, in __init__
expected_shape=expected_shape)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/variables.py", line 316, in _init_from_args
self._snapshot = array_ops.identity(self._variable, name="read")
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 1338, in identity
result = _op_def_lib.apply_op("Identity", input=input, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2336, 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 1228, in __init__
self._traceback = _extract_stack()
FailedPreconditionError (see above for traceback): Attempting to use uninitialized value Variable
[[Node: Variable/read = Identity[T=DT_FLOAT, _class=["loc:@Variable"], _device="/job:localhost/replica:0/task:0/gpu:0"](Variable)]]
[[Node: Mean/_15 = _Recv[client_terminated=false, recv_device="/job:localhost/replica:0/task:0/cpu:0", send_device="/job:localhost/replica:0/task:0/gpu:0", send_device_incarnation=1, tensor_name="edge_7_Mean", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"]()]]
In [ ]:
print(sess.run(weights['hidden1']))
In [ ]:
같은 오류 간단한 예를 들어
, 여기에 교육 및 모델을 저장 :print(sess.run(weights['hidden1']))
에 대한 링크입니다 : [링크] (HTTP ://cv-tricks.com/tensorflow-tutorial/save-restore-tensorflow-models-quick-complete-tutorial/) –
당신이 경험 한 오류는 복원하기 전에 변수 ('가중치')를 작성 했으므로 그래프를 실행하기 전에 초기화하지 않았기 때문입니다. 자리 표시 자의 이름을 명시 적으로 지정하지 않았기 때문이 아닙니다. TensorFlow는 이름을 지정하지 않더라도 항상 이름을 선택합니다. – iga