您好,我电脑没有gpu,在运行您代码过程中直接跳过model = multi_gpu_model(model, gpus=NUM_GPUS)这步,在训练模型的过程中报如下错误NotImplementedError,请问有什么解决措施吗。
NotImplementedError Traceback (most recent call last)
in ()
----> 1 history = model.fit(train_dataseq, epochs=num_epochs, callbacks=callbacks)
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py in _method_wrapper(self, *args, **kwargs)
64 def _method_wrapper(self, *args, **kwargs):
65 if not self._in_multi_worker_mode(): # pylint: disable=protected-access
---> 66 return method(self, *args, **kwargs)
67
68 # Running inside run_distribute_coordinator
already.
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)
846 batch_size=batch_size):
847 callbacks.on_train_batch_begin(step)
--> 848 tmp_logs = train_function(iterator)
849 # Catch OutOfRangeError for Datasets of unknown size.
850 # This blocks until the batch has finished executing.
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py in call(self, *args, **kwds)
578 xla_context.Exit()
579 else:
--> 580 result = self._call(*args, **kwds)
581
582 if tracing_count == self._get_tracing_count():
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py in _call(self, *args, **kwds)
625 # This is the first call of call, so we have to initialize.
626 initializers = []
--> 627 self._initialize(args, kwds, add_initializers_to=initializers)
628 finally:
629 # At this point we know that the initialization is complete (or less
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py in _initialize(self, args, kwds, add_initializers_to)
504 self._concrete_stateful_fn = (
505 self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access
--> 506 *args, **kwds))
507
508 def invalid_creator_scope(*unused_args, **unused_kwds):
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/eager/function.py in _get_concrete_function_internal_garbage_collected(self, *args, **kwargs)
2444 args, kwargs = None, None
2445 with self._lock:
-> 2446 graph_function, _, _ = self._maybe_define_function(args, kwargs)
2447 return graph_function
2448
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/eager/function.py in _maybe_define_function(self, args, kwargs)
2775
2776 self._function_cache.missed.add(call_context_key)
-> 2777 graph_function = self._create_graph_function(args, kwargs)
2778 self._function_cache.primary[cache_key] = graph_function
2779 return graph_function, args, kwargs
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/eager/function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes)
2665 arg_names=arg_names,
2666 override_flat_arg_shapes=override_flat_arg_shapes,
-> 2667 capture_by_value=self._capture_by_value),
2668 self._function_attributes,
2669 # Tell the ConcreteFunction to clean up its graph once it goes out of
/data/software/anaconda3/lib/python3.7/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)
979 _, original_func = tf_decorator.unwrap(python_func)
980
--> 981 func_outputs = python_func(*func_args, **func_kwargs)
982
983 # invariant: func_outputs
contains only Tensors, CompositeTensors,
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/eager/def_function.py in wrapped_fn(*args, **kwds)
439 # wrapped allows AutoGraph to swap in a converted function. We give
440 # the function a weak reference to itself to avoid a reference cycle.
--> 441 return weak_wrapped_fn().wrapped(*args, **kwds)
442 weak_wrapped_fn = weakref.ref(wrapped_fn)
443
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/framework/func_graph.py in wrapper(*args, **kwargs)
966 except Exception as e: # pylint:disable=broad-except
967 if hasattr(e, "ag_error_metadata"):
--> 968 raise e.ag_error_metadata.to_exception(e)
969 else:
970 raise
NotImplementedError: in user code:
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py:571 train_function *
outputs = self.distribute_strategy.run(
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:951 run **
return self._extended.call_for_each_replica(fn, args=args, kwargs=kwargs)
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:2290 call_for_each_replica
return self._call_for_each_replica(fn, args, kwargs)
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:2649 _call_for_each_replica
return fn(*args, **kwargs)
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py:541 train_step **
self.trainable_variables)
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/engine/training.py:1814 _minimize
optimizer.apply_gradients(zip(gradients, trainable_variables))
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/optimizer_v2/optimizer_v2.py:508 apply_gradients
"name": name,
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:2420 merge_call
return self._merge_call(merge_fn, args, kwargs)
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:2427 _merge_call
return merge_fn(self._strategy, *args, **kwargs)
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/optimizer_v2/optimizer_v2.py:592 _distributed_apply **
var, apply_grad_to_update_var, args=(grad,), group=False))
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:2013 update
return self._update(var, fn, args, kwargs, group)
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:2659 _update
return self._update_non_slot(var, fn, (var,) + tuple(args), kwargs, group)
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/distribute/distribute_lib.py:2665 _update_non_slot
result = fn(*args, **kwargs)
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/optimizer_v2/optimizer_v2.py:563 apply_grad_to_update_var **
grad.values, var, grad.indices, **apply_kwargs)
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/optimizer_v2/optimizer_v2.py:1083 _resource_apply_sparse_duplicate_indices
**kwargs)
/data/software/anaconda3/lib/python3.7/site-packages/tensorflow/python/keras/optimizer_v2/optimizer_v2.py:1104 _resource_apply_sparse
raise NotImplementedError()
NotImplementedError:
后面我用默认的optimizer model.compile( loss='sparse_categorical_crossentropy', optimizer = 'adam'),会报如下错误,请问能指点一下imput哪里有问题导致的吗? 不胜感激
InvalidArgumentError: indices[27,3] = 33 is not in [0, 32)
[[node model_5/header_seq_gather/GatherV2 (defined at :4) ]] [Op:__inference_train_function_122352]
Errors may have originated from an input operation.
Input Source operations connected to node model_5/header_seq_gather/GatherV2:
IteratorGetNext (defined at :1)
model_5/model_4/Encoder-12-FeedForward-Norm/add_1 (defined at /data/software/anaconda3/lib/python3.7/site-packages/keras_layer_normalization/layer_normalization.py:99)
Function call stack:
train_function