问题描述
我正在尝试在TF 1.15中将resnet50初始化为模型的主干，并且该模型在google TPU V2上运行。我的代码是这样的：
backbone_model=tf.keras.applications.resnet50(include_top=False,weights='imagenet',pooling=None)
我遇到以下错误。
<pre><code>
E1014 09:57:09.458413 140497105635136 tpu.py:425] Operation of type Placeholder (input_1) is not supported on the TPU. Execution will fail if this op is used in the graph.
app.run(main)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/absl/app.py",line 300,in run
_run_main(main,args)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/absl/app.py",line 251,in _run_main
sys.exit(main(argv))
File "/home/usman/nas/tpu.py",line 232,in main
max_steps=FLAGS.train_steps)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py",line 3035,in train
rendezvous.raise_errors()
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/tpu/error_handling.py",line 136,in raise_errors
six.reraise(typ,value,traceback)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/six.py",line 703,in reraise
raise value
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py",line 3030,in train
saving_listeners=saving_listeners)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/estimator.py",line 370,in train
loss = self._train_model(input_fn,hooks,saving_listeners)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/estimator.py",line 1161,in _train_model
return self._train_model_default(input_fn,line 1191,in _train_model_default
features,labels,ModeKeys.TRAIN,self.config)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py",line 2857,in _call_model_fn
config)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/estimator.py",line 1149,in _call_model_fn
model_fn_results = self._model_fn(features=features,**kwargs)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py",line 3159,in _model_fn
_train_on_tpu_system(ctx,model_fn_wrapper,dequeue_fn))
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py",line 3604,in _train_on_tpu_system
device_assignment=ctx.device_assignment)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/tpu/tpu.py",line 1277,in split_compile_and_shard
name=name)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/tpu/tpu.py",line 992,in split_compile_and_replicate
outputs = computation(*computation_inputs)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py",line 3589,in multi_tpu_train_steps_on_single_shard
inputs=[0,_INITIAL_LOSS])
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/tpu/training_loop.py",line 178,in while_loop
condition_wrapper,body_wrapper,inputs,name="",parallel_iterations=1)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/ops/control_flow_ops.py",line 2753,in while_loop
return_same_structure)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/ops/control_flow_ops.py",line 2245,in BuildLoop
pred,body,original_loop_vars,loop_vars,shape_invariants)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/ops/control_flow_ops.py",line 2170,in _BuildLoop
body_result = body(*packed_vars_for_body)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/tpu/training_loop.py",line 121,in body_wrapper
outputs = body(*(inputs + dequeue_ops))
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py",line 3588,in <lambda>
lambda i,loss: [i + 1,single_tpu_train_step(i)],File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py",line 1715,in train_step
self._call_model_fn(features,labels))
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_estimator/python/estimator/tpu/tpu_estimator.py",line 1994,in _call_model_fn
estimator_spec = self._model_fn(features=features,**kwargs)
File "/home/usman/nas/tpu.py",line 120,in model
pooling=None)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/keras/applications/__init__.py",line 49,in wrapper
return base_fun(*args,**kwargs)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/keras/applications/resnet.py",line 33,in resnet50
return resnet.resnet50(*args,**kwargs)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/keras_applications/resnet_common.py",line 435,in resnet50
**kwargs)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/keras_applications/resnet_common.py",line 411,in resnet
model.load_weights(weights_path)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training.py",line 182,in load_weights
return super(Model,self).load_weights(filepath,by_name)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/network.py",line 1373,in load_weights
saving.load_weights_from_hdf5_group(f,self.layers)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/keras/saving/hdf5_format.py",line 693,in load_weights_from_hdf5_group
K.batch_set_value(weight_value_tuples)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/keras/backend.py",line 3259,in batch_set_value
get_session().run(assign_ops,Feed_dict=Feed_dict)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/keras/backend.py",line 486,in get_session
_initialize_variables(session)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/keras/backend.py",line 903,in _initialize_variables
[variables_module.is_variable_initialized(v) for v in candidate_vars])
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/client/session.py",line 956,in run
run_Metadata_ptr)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/client/session.py",line 1165,in _run
self._graph,fetches,Feed_dict_tensor,Feed_handles=Feed_handles)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/client/session.py",line 488,in __init__
self._assert_fetchable(graph,fetch.op)
File "/home/usman/anaconda3/envs/py37/lib/python3.7/site-packages/tensorflow_core/python/client/session.py",line 505,in _assert_fetchable
% op.name)
tensorflow.python.framework.errors_impl.InaccessibleTensorError: Operation 'VarIsInitializedOp' has been marked as not fetchable. Typically this happens when it is defined in another function or code block. Use return values,explicit Python locals or TensorFlow collections to access it.
</code></pre>
根据我的搜索，以下是最接近我得到的错误的猜测，无法获取在while循环主体中创建的op的结果，因为该主体可能执行0次或多次，基于在循环条件下。要从循环中获取一个值，您需要从body函数（作为循环变量之一）返回它，并且所有迭代之后的最终值将从tf.while_loop（）中返回。但这发生在tf代码内部，而不是外部，因为我只运行一行代码来初始化模型。
解决方法
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