我正在开发colab并使用TPU，但不幸的是，它无法正常工作，模型在安装时面临问题。。
这是我的代码：
resolver = tf.distribute.cluster_resolver.TPUClusterResolver(tpu_address)
tf.config.experimental_connect_to_cluster(resolver)
strategy = tf.distribute.TPUStrategy(resolver)
with strategy.scope():
model = create_model(input_shape=(HEIGHT, WIDTH, CANAL), n_out=N_CLASSES)
for layer in model.layers:
layer.trainable = False
for i in range(-5, 0):
model.layers[i].trainable = True
es = EarlyStopping(monitor='val_loss', mode='min', patience=ES_PATIENCE, restore_best_weights=True, verbose=1)
rlrop = ReduceLROnPlateau(monitor='val_loss', mode='min', patience=RLROP_PATIENCE, factor=DECAY_DROP, min_lr=1e-6, verbose=1)
callback_list = [es, rlrop]
optimizer = optimizers.Adam(lr=LEARNING_RATE)
model.compile(optimizer = optimizers.Adam(lr=WARMUP_LEARNING_RATE),
loss = 'categorical_crossentropy',
metrics = ['accuracy'])
model.summary()
STEP_SIZE_TRAIN = train_generator.n//train_generator.batch_size
STEP_SIZE_VALID = valid_generator.n//valid_generator.batch_size
history_finetunning = model.fit_generator(generator=train_generator,
steps_per_epoch=STEP_SIZE_TRAIN,
epochs=EPOCHS,
validation_data=valid_generator,
validation_steps=STEP_SIZE_VALID,
verbose =1)
这就是错误。。
/usr/local/lib/python3.7/dist-packages/keras/engine/training.py:1915: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.
warnings.warn('`Model.fit_generator` is deprecated and '
Epoch 1/40
---------------------------------------------------------------------------
UnavailableError Traceback (most recent call last)
<ipython-input-41-1c157bad2449> in <module>()
4 validation_data=valid_generator,
5 validation_steps=STEP_SIZE_VALID,
----> 6 verbose =1)
14 frames
/usr/local/lib/python3.7/dist-packages/keras/engine/training.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, validation_freq, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)
1930 use_multiprocessing=use_multiprocessing,
1931 shuffle=shuffle,
-> 1932 initial_epoch=initial_epoch)
1933
1934 def evaluate_generator(self,
/usr/local/lib/python3.7/dist-packages/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)
1161 logs = tmp_logs # No error, now safe to assign to logs.
1162 end_step = step + data_handler.step_increment
-> 1163 callbacks.on_train_batch_end(end_step, logs)
1164 if self.stop_training:
1165 break
/usr/local/lib/python3.7/dist-packages/keras/callbacks.py in on_train_batch_end(self, batch, logs)
434 """
435 if self._should_call_train_batch_hooks:
--> 436 self._call_batch_hook(ModeKeys.TRAIN, 'end', batch, logs=logs)
437
438 def on_test_batch_begin(self, batch, logs=None):
/usr/local/lib/python3.7/dist-packages/keras/callbacks.py in _call_batch_hook(self, mode, hook, batch, logs)
276 self._call_batch_begin_hook(mode, batch, logs)
277 elif hook == 'end':
--> 278 self._call_batch_end_hook(mode, batch, logs)
279 else:
280 raise ValueError('Unrecognized hook: {}'.format(hook))
/usr/local/lib/python3.7/dist-packages/keras/callbacks.py in _call_batch_end_hook(self, mode, batch, logs)
296 self._batch_times.append(batch_time)
297
--> 298 self._call_batch_hook_helper(hook_name, batch, logs)
299
300 if len(self._batch_times) >= self._num_batches_for_timing_check:
/usr/local/lib/python3.7/dist-packages/keras/callbacks.py in _call_batch_hook_helper(self, hook_name, batch, logs)
336 hook = getattr(callback, hook_name)
337 if getattr(callback, '_supports_tf_logs', False):
--> 338 hook(batch, logs)
339 else:
340 if numpy_logs is None: # Only convert once.
/usr/local/lib/python3.7/dist-packages/keras/callbacks.py in on_train_batch_end(self, batch, logs)
1042
1043 def on_train_batch_end(self, batch, logs=None):
-> 1044 self._batch_update_progbar(batch, logs)
1045
1046 def on_test_batch_end(self, batch, logs=None):
/usr/local/lib/python3.7/dist-packages/keras/callbacks.py in _batch_update_progbar(self, batch, logs)
1106 if self.verbose == 1:
1107 # Only block async when verbose = 1.
-> 1108 logs = tf_utils.sync_to_numpy_or_python_type(logs)
1109 self.progbar.update(self.seen, list(logs.items()), finalize=False)
1110
/usr/local/lib/python3.7/dist-packages/keras/utils/tf_utils.py in sync_to_numpy_or_python_type(tensors)
505 return t # Don't turn ragged or sparse tensors to NumPy.
506
--> 507 return tf.nest.map_structure(_to_single_numpy_or_python_type, tensors)
508
509
/usr/local/lib/python3.7/dist-packages/tensorflow/python/util/nest.py in map_structure(func, *structure, **kwargs)
865
866 return pack_sequence_as(
--> 867 structure[0], [func(*x) for x in entries],
868 expand_composites=expand_composites)
869
/usr/local/lib/python3.7/dist-packages/tensorflow/python/util/nest.py in <listcomp>(.0)
865
866 return pack_sequence_as(
--> 867 structure[0], [func(*x) for x in entries],
868 expand_composites=expand_composites)
869
/usr/local/lib/python3.7/dist-packages/keras/utils/tf_utils.py in _to_single_numpy_or_python_type(t)
501 def _to_single_numpy_or_python_type(t):
502 if isinstance(t, tf.Tensor):
--> 503 x = t.numpy()
504 return x.item() if np.ndim(x) == 0 else x
505 return t # Don't turn ragged or sparse tensors to NumPy.
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/ops.py in numpy(self)
1092 """
1093 # TODO(slebedev): Consider avoiding a copy for non-CPU or remote tensors.
-> 1094 maybe_arr = self._numpy() # pylint: disable=protected-access
1095 return maybe_arr.copy() if isinstance(maybe_arr, np.ndarray) else maybe_arr
1096
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/ops.py in _numpy(self)
1060 return self._numpy_internal()
1061 except core._NotOkStatusException as e: # pylint: disable=protected-access
-> 1062 six.raise_from(core._status_to_exception(e.code, e.message), None) # pylint: disable=protected-access
1063
1064 @property
/usr/local/lib/python3.7/dist-packages/six.py in raise_from(value, from_value)
UnavailableError: 3 root error(s) found.
(0) Unavailable: {{function_node __inference_train_function_53748}} failed to connect to all addresses
Additional GRPC error information from remote target /job:localhost/replica:0/task:0/device:CPU:0:
:{"created":"@1626347736.544045826","description":"Failed to pick subchannel","file":"third_party/grpc/src/core/ext/filters/client_channel/client_channel.cc","file_line":5420,"referenced_errors":[{"created":"@1626347735.785465323","description":"failed to connect to all addresses","file":"third_party/grpc/src/core/ext/filters/client_channel/lb_policy/pick_first/pick_first.cc","file_line":398,"grpc_status":14}]}
[[{{node MultiDeviceIteratorGetNextFromShard}}]]
[[RemoteCall]]
[[IteratorGetNextAsOptional]]
[[cond_11/switch_pred/_107/_76]]
(1) Unavailable: {{function_node __inference_train_function_53748}} failed to connect to all addresses
Additional GRPC error information from remote target /job:localhost/replica:0/task:0/device:CPU:0:
:{"created":"@1626347736.544045826","description":"Failed to pick subchannel","file":"third_party/grpc/src/core/ext/filters/client_channel/client_channel.cc","file_line":5420,"referenced_errors":[{"created":"@1626347735.785465323","description":"failed to connect to all addresses","file":"third_party/grpc/src/core/ext/filters/client_channel/lb_policy/pick_first/pick_first.cc","file_line":398,"grpc_status":14}]}
[[{{node MultiDeviceIteratorGetNextFromShard}}]]
[[RemoteCall]]
[[IteratorGetNextAsOptional]]
[[cluster_train_function/_execute_2_0/_333]]
(2) Unavailable: {{function_node __inference_train_function_53748}} failed to connect to all addresses
Additional GRPC error information from remote target /job:localhost/replica:0/task:0/device:CPU:0:
:{"created":"@1626347736.544045826","description":"Failed to pick subchannel","file":"third_party/grpc/src/core/ext/filters/client_channel/client_channel.cc","file_line":5420,"referenced_errors":[{"created":"@1626347735.785465323","description":"failed to connect to all addresses","file":"third_party/grpc/src/core/ext/filters/client_channel/lb_policy/pick_first/pick_first.cc","file_line":398,"grpc_status":14}]}
[[{{node MultiDeviceIteratorGetNextFromShard}}]]
[[RemoteCall]]
[[IteratorGetNextAsOptional]]
0 successful operations.
6 derived errors ignored.
使用来自tensorflow_datasets的tfds对TPU配置使用相同的代码，并用model.fit方法拟合模型。方法不会产生任何错误，
Model.fit_generator已被弃用，不适用于TPU。
尝试使用tf.keras.preprocessing.image_dataset_from_directory或tf.data.Dataset并将其与Keras预处理层相结合