[英]How to deal with tf.saved_model.save(model, filepath) Error?
我使用 TFRS 構建了一個自定義的混合推薦器； model 經過訓練，能夠很好地進行預測。 但是當我保存它時：
model = ...
filepath = 'saved_model/model0'
tf.saved_model.save(model, filepath)
錯誤：
--------------------------------------------------------------------------- FailedPreconditionError Traceback (most recent call last) /tmp/ipykernel_2678112/2773535809.py in <module>
5 #!mkdir -p saved_model
6 filepath = 'saved_model/model0'
----> 7 tf.saved_model.save(model, filepath)
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/saved_model/save.py in save(obj, export_dir, signatures, options) 1278 # pylint: enable=line-too-long 1279 metrics.IncrementWriteApi(_SAVE_V2_LABEL)
-> 1280 save_and_return_nodes(obj, export_dir, signatures, options) 1281 metrics.IncrementWrite(write_version="2") 1282
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/saved_model/save.py in save_and_return_nodes(obj, export_dir, signatures, options, experimental_skip_checkpoint) 1313 1314 _, exported_graph, object_saver, asset_info, saved_nodes, node_paths = (
-> 1315 _build_meta_graph(obj, signatures, options, meta_graph_def)) 1316 saved_model.saved_model_schema_version = ( 1317 constants.SAVED_MODEL_SCHEMA_VERSION)
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/saved_model/save.py in _build_meta_graph(obj, signatures, options, meta_graph_def) 1485 1486 with save_context.save_context(options):
-> 1487 return _build_meta_graph_impl(obj, signatures, options, meta_graph_def)
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/saved_model/save.py in _build_meta_graph_impl(obj, signatures, options, meta_graph_def) 1434 1435 # Use _SaveableView to provide a frozen listing of properties and functions.
-> 1436 saveable_view = _SaveableView(checkpoint_graph_view, options, 1437 wrapped_functions) 1438 object_saver = util.TrackableSaver(checkpoint_graph_view)
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/saved_model/save.py in __init__(self, checkpoint_view, options, wrapped_functions)
200 # Run through the nodes in the object graph first for side effects of
201 # creating variables.
--> 202 self._trace_all_concrete_functions()
203
204 (self._trackable_objects, self.node_paths, self._node_ids,
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/saved_model/save.py in _trace_all_concrete_functions(self)
304 for function in self.checkpoint_view.list_functions(obj).values():
305 if isinstance(function, def_function.Function):
--> 306 function._list_all_concrete_functions_for_serialization() # pylint: disable=protected-access
307
308 @property
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/eager/def_function.py in _list_all_concrete_functions_for_serialization(self) 1194 A list of instances of `ConcreteFunction`. 1195 """
-> 1196 concrete_functions = self._list_all_concrete_functions() 1197 seen_signatures = [] 1198 for concrete_function in concrete_functions:
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/eager/def_function.py in _list_all_concrete_functions(self) 1176 """Returns all concrete functions.""" 1177 if self.input_signature is not None:
-> 1178 self.get_concrete_function() 1179 concrete_functions = [] 1180 # pylint: disable=protected-access
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/eager/def_function.py in get_concrete_function(self, *args, **kwargs) 1257 def get_concrete_function(self, *args, **kwargs): 1258 # Implements GenericFunction.get_concrete_function.
-> 1259 concrete = self._get_concrete_function_garbage_collected(*args, **kwargs) 1260 concrete._garbage_collector.release() # pylint: disable=protected-access 1261 return concrete
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/eager/def_function.py in _get_concrete_function_garbage_collected(self, *args, **kwargs) 1237 if self._stateful_fn is None: 1238 initializers
= []
-> 1239 self._initialize(args, kwargs, add_initializers_to=initializers) 1240 self._initialize_uninitialized_variables(initializers) 1241
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/eager/def_function.py in _initialize(self, args, kwds, add_initializers_to)
778 self._graph_deleter = FunctionDeleter(self._lifted_initializer_graph)
779 self._concrete_stateful_fn = (
--> 780 self._stateful_fn._get_concrete_function_internal_garbage_collected(
# pylint: disable=protected-access
781 *args, **kwds))
782
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/eager/function.py in _get_concrete_function_internal_garbage_collected(self, *args,
**kwargs) 3155 args, kwargs = None, None 3156 with self._lock:
-> 3157 graph_function, _ = self._maybe_define_function(args, kwargs) 3158 return graph_function 3159
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/eager/function.py in _maybe_define_function(self, args, kwargs) 3555 3556 self._function_cache.missed.add(call_context_key)
-> 3557 graph_function = self._create_graph_function(args, kwargs) 3558 self._function_cache.primary[cache_key] = graph_function 3559
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/eager/function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes) 3390 arg_names = base_arg_names + missing_arg_names 3391 graph_function = ConcreteFunction(
-> 3392 func_graph_module.func_graph_from_py_func( 3393 self._name, 3394 self._python_function,
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/framework/func_graph.py in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes, acd_record_initial_resource_uses) 1141
_, original_func = tf_decorator.unwrap(python_func) 1142
-> 1143 func_outputs = python_func(*func_args, **func_kwargs) 1144 1145 # invariant: `func_outputs` contains only Tensors, CompositeTensors,
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/eager/def_function.py in wrapped_fn(*args, **kwds)
670 # the function a weak reference to itself to avoid a reference cycle.
671 with OptionalXlaContext(compile_with_xla):
--> 672 out = weak_wrapped_fn().__wrapped__(*args, **kwds)
673 return out
674
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/training/tracking/tracking.py in _creator()
279 @def_function.function(input_signature=[], autograph=False)
280 def _creator():
--> 281 resource = self._create_resource()
282 return resource
283
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/data/ops/dataset_ops.py in <lambda>()
241 # to have a weak reference to the Dataset to avoid creating
242 # reference cycles and making work for the garbage collector.
--> 243 lambda: weak_self._trace_variant_creation()()), # pylint: disable=unnecessary-lambda,protected-access
244 name="_variant_tracker")
245 self._graph_attr = ops.get_default_graph()
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/data/ops/dataset_ops.py in _trace_variant_creation(self)
363 # pylint: disable=protected-access
364 graph_def = graph_pb2.GraphDef().FromString(
--> 365 self._as_serialized_graph(external_state_policy=options_lib
366 .ExternalStatePolicy.FAIL).numpy())
367 output_node_names = []
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/util/deprecation.py in new_func(*args, **kwargs)
550 'in a future version' if date is None else ('after %s' % date),
551 instructions)
--> 552 return func(*args, **kwargs)
553
554 doc = _add_deprecated_arg_notice_to_docstring(
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/data/ops/dataset_ops.py in _as_serialized_graph(self, allow_stateful, strip_device_assignment, external_state_policy)
302 if external_state_policy:
303 policy = external_state_policy.value
--> 304 return gen_dataset_ops.dataset_to_graph_v2(
305 self._variant_tensor,
306 external_state_policy=policy,
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/ops/gen_dataset_ops.py in dataset_to_graph_v2(input_dataset, external_state_policy, strip_device_assignment, name) 1158 return _result 1159 except _core._NotOkStatusException as e:
-> 1160 _ops.raise_from_not_ok_status(e, name) 1161 except _core._FallbackException: 1162 pass
/napi/k_working_dir/ds_test/shared-space/venv/lib/python3.9/site-packages/tensorflow/python/framework/ops.py in raise_from_not_ok_status(e, name) 7105 def raise_from_not_ok_status(e, name): 7106 e.message += (" name: " + name if name is not None else "")
-> 7107 raise core._status_to_exception(e) from None # pylint: disable=protected-access 7108 7109
FailedPreconditionError: Failed to serialize the input pipeline graph: ResourceGather is stateful. [Op:DatasetToGraphV2]
# original code does not work
tf.keras.models.save_model(model, filepath)
# new code: set parameter save_format='tf'
tf.keras.models.save_model(
model, filepath, overwrite=True, include_optimizer=True, save_format='tf',
signatures=None, options=None, save_traces=True
)
您也可以使用其他格式
# original code does not work
model.save(filepath)
# new code: set parameter save_format='tf'
model.save(filepath, save_format='tf')
我在我的多任務 model (TFRS) 中遇到了同樣的問題，按照這里發布的解決方案解決了這個問題。
檢索任務中使用的指標是問題所在。
在訓練和評估 model 之后，我運行以下代碼來保存它：
model.retrieval_task = tfrs.tasks.Retrieval() # Removes the metrics.
model.compile()
model.save("./models/my_rec_model")
當我需要進行推理時，我使用這個：
model = tf.keras.models.load_model("./models/my_rec_model")
tf.saved_model.save(model, path_to_dir) 和 tf.keras.model.save 的區別
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[英]Using tf.saved_model.save() to save a model to GCS bucket from local
Convert a Tensorflow model in SavedModel format (.pb file) saved with tf.saved_model.save to a Keras model (.h5 file)
[英]Convert a Tensorflow model in SavedModel format (.pb file) saved with tf.saved_model.save to a Keras model (.h5 file)
如何加載訓練模型的權重，這些權重是用 tf.keras.models.save_model 保存的？
[英]How to load a trained model's weights, which were saved with tf.keras.models.save_model?
如何使用通過`saved_model.simple_save`保存的tensorflow model？
[英]How to use a saved tensorflow model by `saved_model.simple_save`?
從 Keras 模型轉換時，tf.saved_model.simple_save 失敗
[英]tf.saved_model.simple_save fail when converting from Keras model
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