无法使用我的 TensorFlow 模型进行分类：FailedPreconditionError
Cannot classify with my TensorFlow model: FailedPreconditionError
我正尝试在多 class class 化问题中使用 TensorFlow 模型 class 化输入图像。我想绘制前 10 个最高预测 class 的概率。我通过以下步骤进行操作：
1.加载模型
import tensorflow as tf
import tensorflow.compat.v1 as tfc
import PIL
import numpy as np
import cv2
from tensorflow.keras.models import model_from_json
import warnings
import matplotlib.pyplot as plt
warnings.filterwarnings('ignore')
tf.compat.v1.disable_eager_execution()
json_file = open('resnet-model.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
loaded_model_json = loaded_model_json.replace('"activation":"softmax"', '"activation":"linear"')
model = tf.keras.models.model_from_json(loaded_model_json)
2。准备函数 return logits 和概率
#Sets the threshold for what messages will be logged
tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)
#Starts the Interactive Session
sess=tfc.InteractiveSession()
#Size of the image that will be classified
image=tf.Variable(tf.zeros((1,224,224,3)))
def resnet2(image,model):
logits = model(image)
probs = tf.nn.softmax(logits)
return logits, probs
#Returns logits and probabilities from the network
logits, probs = resnet2(image, model)
3。 classify 和 return top10 概率
的函数
def classify(img, correct_class=None, target_class=None):
#Get probabilities given the input image
p = sess.run(probs, feed_dict={image: img})[0]
#get top-10 probablilities
topk = list(p.argsort()[-10:][::-1])
#Select top10 probabilities
topprobs = p[topk]
print(topprobs)
4。准备要class化的图像并class化它
#Image class is 11
img_class = 11
#Open the image
img = cv2.imread("sample-image.jpg")
img= img.reshape(1,224,224,3)
img = (np.asarray(img) / 255.0).astype(np.float32)
classify(img, correct_class=img_class)
但是，每当我 运行 它时，我都会遇到以下错误：
---------------------------------------------------------------------------
FailedPreconditionError Traceback (most recent call last)
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1364 try:
-> 1365 return fn(*args)
1366 except errors.OpError as e:
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
1348 self._extend_graph()
-> 1349 return self._call_tf_sessionrun(options, feed_dict, fetch_list,
1350 target_list, run_metadata)
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
1440 run_metadata):
-> 1441 return tf_session.TF_SessionRun_wrapper(self._session, options, feed_dict,
1442 fetch_list, target_list,
FailedPreconditionError: 2 root error(s) found.
(0) Failed precondition: Error while reading resource variable conv4_block4_3_bn_9/beta from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/conv4_block4_3_bn_9/beta)
[[{{node functional_1_5/conv4_block4_3_bn/ReadVariableOp_1}}]]
[[functional_1_5/dropout/cond/then/_0/dropout/GreaterEqual/y/_41]]
(1) Failed precondition: Error while reading resource variable conv4_block4_3_bn_9/beta from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/conv4_block4_3_bn_9/beta)
[[{{node functional_1_5/conv4_block4_3_bn/ReadVariableOp_1}}]]
0 successful operations.
0 derived errors ignored.
During handling of the above exception, another exception occurred:
FailedPreconditionError Traceback (most recent call last)
<ipython-input-116-291671c55c1a> in <module>
----> 1 classify(img, correct_class=img_class)
<ipython-input-114-f609e06291c4> in classify(img, correct_class, target_class)
6
7 #Get probabilities given the input image
----> 8 p = sess.run(probs, feed_dict={image: img})[0]
9 #ax1.imshow(img)
10 #fig.sca(ax1)
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
955
956 try:
--> 957 result = self._run(None, fetches, feed_dict, options_ptr,
958 run_metadata_ptr)
959 if run_metadata:
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1178 # or if the call is a partial run that specifies feeds.
1179 if final_fetches or final_targets or (handle and feed_dict_tensor):
-> 1180 results = self._do_run(handle, final_targets, final_fetches,
1181 feed_dict_tensor, options, run_metadata)
1182 else:
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1356
1357 if handle is None:
-> 1358 return self._do_call(_run_fn, feeds, fetches, targets, options,
1359 run_metadata)
1360 else:
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1382 '\nsession_config.graph_options.rewrite_options.'
1383 'disable_meta_optimizer = True')
-> 1384 raise type(e)(node_def, op, message)
1385
1386 def _extend_graph(self):
FailedPreconditionError: 2 root error(s) found.
(0) Failed precondition: Error while reading resource variable conv4_block4_3_bn_9/beta from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/conv4_block4_3_bn_9/beta)
[[node functional_1_5/conv4_block4_3_bn/ReadVariableOp_1 (defined at <ipython-input-113-a25550204dc5>:3) ]]
[[functional_1_5/dropout/cond/then/_0/dropout/GreaterEqual/y/_41]]
(1) Failed precondition: Error while reading resource variable conv4_block4_3_bn_9/beta from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/conv4_block4_3_bn_9/beta)
[[node functional_1_5/conv4_block4_3_bn/ReadVariableOp_1 (defined at <ipython-input-113-a25550204dc5>:3) ]]
0 successful operations.
0 derived errors ignored.
Errors may have originated from an input operation.
Input Source operations connected to node functional_1_5/conv4_block4_3_bn/ReadVariableOp_1:
conv4_block4_3_bn_9/beta (defined at <ipython-input-111-e21a4c41d093>:12)
Input Source operations connected to node functional_1_5/conv4_block4_3_bn/ReadVariableOp_1:
conv4_block4_3_bn_9/beta (defined at <ipython-input-111-e21a4c41d093>:12)
Original stack trace for 'functional_1_5/conv4_block4_3_bn/ReadVariableOp_1':
File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/usr/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/home/anselmo/.local/lib/python3.8/site-packages/traitlets/config/application.py", line 845, in launch_instance
app.start()
File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 612, in start
self.io_loop.start()
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 149, in start
self.asyncio_loop.run_forever()
File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever
self._run_once()
File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once
handle._run()
File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run
self._context.run(self._callback, *self._args)
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/ioloop.py", line 690, in <lambda>
lambda f: self._run_callback(functools.partial(callback, future))
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/ioloop.py", line 743, in _run_callback
ret = callback()
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/gen.py", line 787, in inner
self.run()
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/gen.py", line 748, in run
yielded = self.gen.send(value)
File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 365, in process_one
yield gen.maybe_future(dispatch(*args))
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/gen.py", line 209, in wrapper
yielded = next(result)
File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 268, in dispatch_shell
yield gen.maybe_future(handler(stream, idents, msg))
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/gen.py", line 209, in wrapper
yielded = next(result)
File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 543, in execute_request
self.do_execute(
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/gen.py", line 209, in wrapper
yielded = next(result)
File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 306, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 536, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/home/anselmo/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 2876, in run_cell
result = self._run_cell(
File "/home/anselmo/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 2922, in _run_cell
return runner(coro)
File "/home/anselmo/.local/lib/python3.8/site-packages/IPython/core/async_helpers.py", line 68, in _pseudo_sync_runner
coro.send(None)
File "/home/anselmo/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3145, in run_cell_async
has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
File "/home/anselmo/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3337, in run_ast_nodes
if (await self.run_code(code, result, async_=asy)):
File "/home/anselmo/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3417, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-113-a25550204dc5>", line 8, in <module>
logits, probs = resnet2(image, model)
File "<ipython-input-113-a25550204dc5>", line 3, in resnet2
logits = model(image)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/base_layer_v1.py", line 776, in __call__
outputs = call_fn(cast_inputs, *args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/functional.py", line 385, in call
return self._run_internal_graph(
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/functional.py", line 508, in _run_internal_graph
outputs = node.layer(*args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/base_layer_v1.py", line 776, in __call__
outputs = call_fn(cast_inputs, *args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/normalization.py", line 720, in call
outputs = self._fused_batch_norm(inputs, training=training)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/normalization.py", line 576, in _fused_batch_norm
output, mean, variance = tf_utils.smart_cond(training, train_op,
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/tf_utils.py", line 64, in smart_cond
return smart_module.smart_cond(
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/smart_cond.py", line 56, in smart_cond
return false_fn()
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/normalization.py", line 558, in _fused_batch_norm_inference
return nn.fused_batch_norm(
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/util/dispatch.py", line 201, in wrapper
return target(*args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/nn_impl.py", line 1626, in fused_batch_norm
offset = ops.convert_to_tensor(offset, name="offset")
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/ops.py", line 1499, in convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/resource_variable_ops.py", line 1909, in _dense_var_to_tensor
return var._dense_var_to_tensor(dtype=dtype, name=name, as_ref=as_ref) # pylint: disable=protected-access
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/resource_variable_ops.py", line 1326, in _dense_var_to_tensor
return self.value()
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/resource_variable_ops.py", line 555, in value
return self._read_variable_op()
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/resource_variable_ops.py", line 657, in _read_variable_op
result = read_and_set_handle()
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/resource_variable_ops.py", line 647, in read_and_set_handle
result = gen_resource_variable_ops.read_variable_op(self._handle,
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_resource_variable_ops.py", line 490, in read_variable_op
_, _, _op, _outputs = _op_def_library._apply_op_helper(
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/op_def_library.py", line 742, in _apply_op_helper
op = g._create_op_internal(op_type_name, inputs, dtypes=None,
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/ops.py", line 3477, in _create_op_internal
ret = Operation(
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/ops.py", line 1949, in __init__
self._traceback = tf_stack.extract_stack()
我的代码有什么问题？模型没有初始化？如何解决？
P.s1= 我可以用输入图像正常调用函数 resnet2，它 return 既有 logits 又有 probs。问题是当我 运行 sess.run()
P.s2=使用的模型和图片可以找到HERE
由于您正在使用 tfc.InteractiveSession() 初始化 tensorflow（版本 < 2）会话，因此您可能需要在 运行 通过调用以下方式初始化会话之前初始化所有值：
tfc.initialize_all_variables().run()
这应该初始化所有变量。这也支持你的情况，你可以单独使用 运行 Resnet，但不能使用 sess.run().
我正尝试在多 class class 化问题中使用 TensorFlow 模型 class 化输入图像。我想绘制前 10 个最高预测 class 的概率。我通过以下步骤进行操作：
1.加载模型
import tensorflow as tf
import tensorflow.compat.v1 as tfc
import PIL
import numpy as np
import cv2
from tensorflow.keras.models import model_from_json
import warnings
import matplotlib.pyplot as plt
warnings.filterwarnings('ignore')
tf.compat.v1.disable_eager_execution()
json_file = open('resnet-model.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
loaded_model_json = loaded_model_json.replace('"activation":"softmax"', '"activation":"linear"')
model = tf.keras.models.model_from_json(loaded_model_json)
2。准备函数 return logits 和概率
#Sets the threshold for what messages will be logged
tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)
#Starts the Interactive Session
sess=tfc.InteractiveSession()
#Size of the image that will be classified
image=tf.Variable(tf.zeros((1,224,224,3)))
def resnet2(image,model):
logits = model(image)
probs = tf.nn.softmax(logits)
return logits, probs
#Returns logits and probabilities from the network
logits, probs = resnet2(image, model)
3。 classify 和 return top10 概率
的函数def classify(img, correct_class=None, target_class=None):
#Get probabilities given the input image
p = sess.run(probs, feed_dict={image: img})[0]
#get top-10 probablilities
topk = list(p.argsort()[-10:][::-1])
#Select top10 probabilities
topprobs = p[topk]
print(topprobs)
4。准备要class化的图像并class化它
#Image class is 11
img_class = 11
#Open the image
img = cv2.imread("sample-image.jpg")
img= img.reshape(1,224,224,3)
img = (np.asarray(img) / 255.0).astype(np.float32)
classify(img, correct_class=img_class)
但是，每当我 运行 它时，我都会遇到以下错误：
---------------------------------------------------------------------------
FailedPreconditionError Traceback (most recent call last)
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1364 try:
-> 1365 return fn(*args)
1366 except errors.OpError as e:
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in _run_fn(feed_dict, fetch_list, target_list, options, run_metadata)
1348 self._extend_graph()
-> 1349 return self._call_tf_sessionrun(options, feed_dict, fetch_list,
1350 target_list, run_metadata)
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in _call_tf_sessionrun(self, options, feed_dict, fetch_list, target_list, run_metadata)
1440 run_metadata):
-> 1441 return tf_session.TF_SessionRun_wrapper(self._session, options, feed_dict,
1442 fetch_list, target_list,
FailedPreconditionError: 2 root error(s) found.
(0) Failed precondition: Error while reading resource variable conv4_block4_3_bn_9/beta from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/conv4_block4_3_bn_9/beta)
[[{{node functional_1_5/conv4_block4_3_bn/ReadVariableOp_1}}]]
[[functional_1_5/dropout/cond/then/_0/dropout/GreaterEqual/y/_41]]
(1) Failed precondition: Error while reading resource variable conv4_block4_3_bn_9/beta from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/conv4_block4_3_bn_9/beta)
[[{{node functional_1_5/conv4_block4_3_bn/ReadVariableOp_1}}]]
0 successful operations.
0 derived errors ignored.
During handling of the above exception, another exception occurred:
FailedPreconditionError Traceback (most recent call last)
<ipython-input-116-291671c55c1a> in <module>
----> 1 classify(img, correct_class=img_class)
<ipython-input-114-f609e06291c4> in classify(img, correct_class, target_class)
6
7 #Get probabilities given the input image
----> 8 p = sess.run(probs, feed_dict={image: img})[0]
9 #ax1.imshow(img)
10 #fig.sca(ax1)
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in run(self, fetches, feed_dict, options, run_metadata)
955
956 try:
--> 957 result = self._run(None, fetches, feed_dict, options_ptr,
958 run_metadata_ptr)
959 if run_metadata:
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in _run(self, handle, fetches, feed_dict, options, run_metadata)
1178 # or if the call is a partial run that specifies feeds.
1179 if final_fetches or final_targets or (handle and feed_dict_tensor):
-> 1180 results = self._do_run(handle, final_targets, final_fetches,
1181 feed_dict_tensor, options, run_metadata)
1182 else:
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in _do_run(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)
1356
1357 if handle is None:
-> 1358 return self._do_call(_run_fn, feeds, fetches, targets, options,
1359 run_metadata)
1360 else:
/usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py in _do_call(self, fn, *args)
1382 '\nsession_config.graph_options.rewrite_options.'
1383 'disable_meta_optimizer = True')
-> 1384 raise type(e)(node_def, op, message)
1385
1386 def _extend_graph(self):
FailedPreconditionError: 2 root error(s) found.
(0) Failed precondition: Error while reading resource variable conv4_block4_3_bn_9/beta from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/conv4_block4_3_bn_9/beta)
[[node functional_1_5/conv4_block4_3_bn/ReadVariableOp_1 (defined at <ipython-input-113-a25550204dc5>:3) ]]
[[functional_1_5/dropout/cond/then/_0/dropout/GreaterEqual/y/_41]]
(1) Failed precondition: Error while reading resource variable conv4_block4_3_bn_9/beta from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/conv4_block4_3_bn_9/beta)
[[node functional_1_5/conv4_block4_3_bn/ReadVariableOp_1 (defined at <ipython-input-113-a25550204dc5>:3) ]]
0 successful operations.
0 derived errors ignored.
Errors may have originated from an input operation.
Input Source operations connected to node functional_1_5/conv4_block4_3_bn/ReadVariableOp_1:
conv4_block4_3_bn_9/beta (defined at <ipython-input-111-e21a4c41d093>:12)
Input Source operations connected to node functional_1_5/conv4_block4_3_bn/ReadVariableOp_1:
conv4_block4_3_bn_9/beta (defined at <ipython-input-111-e21a4c41d093>:12)
Original stack trace for 'functional_1_5/conv4_block4_3_bn/ReadVariableOp_1':
File "/usr/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/usr/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/usr/local/lib/python3.8/dist-packages/ipykernel_launcher.py", line 16, in <module>
app.launch_new_instance()
File "/home/anselmo/.local/lib/python3.8/site-packages/traitlets/config/application.py", line 845, in launch_instance
app.start()
File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelapp.py", line 612, in start
self.io_loop.start()
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/platform/asyncio.py", line 149, in start
self.asyncio_loop.run_forever()
File "/usr/lib/python3.8/asyncio/base_events.py", line 570, in run_forever
self._run_once()
File "/usr/lib/python3.8/asyncio/base_events.py", line 1859, in _run_once
handle._run()
File "/usr/lib/python3.8/asyncio/events.py", line 81, in _run
self._context.run(self._callback, *self._args)
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/ioloop.py", line 690, in <lambda>
lambda f: self._run_callback(functools.partial(callback, future))
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/ioloop.py", line 743, in _run_callback
ret = callback()
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/gen.py", line 787, in inner
self.run()
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/gen.py", line 748, in run
yielded = self.gen.send(value)
File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 365, in process_one
yield gen.maybe_future(dispatch(*args))
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/gen.py", line 209, in wrapper
yielded = next(result)
File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 268, in dispatch_shell
yield gen.maybe_future(handler(stream, idents, msg))
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/gen.py", line 209, in wrapper
yielded = next(result)
File "/usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py", line 543, in execute_request
self.do_execute(
File "/home/anselmo/.local/lib/python3.8/site-packages/tornado/gen.py", line 209, in wrapper
yielded = next(result)
File "/usr/local/lib/python3.8/dist-packages/ipykernel/ipkernel.py", line 306, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "/usr/local/lib/python3.8/dist-packages/ipykernel/zmqshell.py", line 536, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "/home/anselmo/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 2876, in run_cell
result = self._run_cell(
File "/home/anselmo/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 2922, in _run_cell
return runner(coro)
File "/home/anselmo/.local/lib/python3.8/site-packages/IPython/core/async_helpers.py", line 68, in _pseudo_sync_runner
coro.send(None)
File "/home/anselmo/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3145, in run_cell_async
has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
File "/home/anselmo/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3337, in run_ast_nodes
if (await self.run_code(code, result, async_=asy)):
File "/home/anselmo/.local/lib/python3.8/site-packages/IPython/core/interactiveshell.py", line 3417, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-113-a25550204dc5>", line 8, in <module>
logits, probs = resnet2(image, model)
File "<ipython-input-113-a25550204dc5>", line 3, in resnet2
logits = model(image)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/base_layer_v1.py", line 776, in __call__
outputs = call_fn(cast_inputs, *args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/functional.py", line 385, in call
return self._run_internal_graph(
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/functional.py", line 508, in _run_internal_graph
outputs = node.layer(*args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/base_layer_v1.py", line 776, in __call__
outputs = call_fn(cast_inputs, *args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/normalization.py", line 720, in call
outputs = self._fused_batch_norm(inputs, training=training)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/normalization.py", line 576, in _fused_batch_norm
output, mean, variance = tf_utils.smart_cond(training, train_op,
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/tf_utils.py", line 64, in smart_cond
return smart_module.smart_cond(
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/smart_cond.py", line 56, in smart_cond
return false_fn()
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/normalization.py", line 558, in _fused_batch_norm_inference
return nn.fused_batch_norm(
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/util/dispatch.py", line 201, in wrapper
return target(*args, **kwargs)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/nn_impl.py", line 1626, in fused_batch_norm
offset = ops.convert_to_tensor(offset, name="offset")
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/ops.py", line 1499, in convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/resource_variable_ops.py", line 1909, in _dense_var_to_tensor
return var._dense_var_to_tensor(dtype=dtype, name=name, as_ref=as_ref) # pylint: disable=protected-access
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/resource_variable_ops.py", line 1326, in _dense_var_to_tensor
return self.value()
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/resource_variable_ops.py", line 555, in value
return self._read_variable_op()
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/resource_variable_ops.py", line 657, in _read_variable_op
result = read_and_set_handle()
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/resource_variable_ops.py", line 647, in read_and_set_handle
result = gen_resource_variable_ops.read_variable_op(self._handle,
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_resource_variable_ops.py", line 490, in read_variable_op
_, _, _op, _outputs = _op_def_library._apply_op_helper(
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/op_def_library.py", line 742, in _apply_op_helper
op = g._create_op_internal(op_type_name, inputs, dtypes=None,
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/ops.py", line 3477, in _create_op_internal
ret = Operation(
File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/ops.py", line 1949, in __init__
self._traceback = tf_stack.extract_stack()
我的代码有什么问题？模型没有初始化？如何解决？
P.s1= 我可以用输入图像正常调用函数 resnet2，它 return 既有 logits 又有 probs。问题是当我 运行 sess.run()
P.s2=使用的模型和图片可以找到HERE
由于您正在使用 tfc.InteractiveSession() 初始化 tensorflow（版本 < 2）会话，因此您可能需要在 运行 通过调用以下方式初始化会话之前初始化所有值：
tfc.initialize_all_variables().run()
这应该初始化所有变量。这也支持你的情况，你可以单独使用 运行 Resnet，但不能使用 sess.run().