配置为M1 pro芯片，keras==2.6.0
model = Sequential()
TypeError Traceback (most recent call last)
/var/folders/h0/j1d38bxd4295htjpcn2wwpwc0000gn/T/ipykernel_48710/1518389220.py in <module>
----> 1 model = Sequential()
~/anaconda3/envs/py39/lib/python3.9/site-packages/tensorflow/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
528 self._self_setattr_tracking = False # pylint: disable=protected-access
529 try:
--> 530 result = method(self, *args, **kwargs)
531 finally:
532 self._self_setattr_tracking = previous_value # pylint: disable=protected-access
~/anaconda3/envs/py39/lib/python3.9/site-packages/keras/engine/sequential.py in __init__(self, layers, name)
105 """
106 # Skip the init in FunctionalModel since model doesn't have input/output yet
--> 107 super(functional.Functional, self).__init__( # pylint: disable=bad-super-call
108 name=name, autocast=False)
109 base_layer.keras_api_gauge.get_cell('Sequential').set(True)
~/anaconda3/envs/py39/lib/python3.9/site-packages/tensorflow/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
528 self._self_setattr_tracking = False # pylint: disable=protected-access
529 try:
--> 530 result = method(self, *args, **kwargs)
531 finally:
532 self._self_setattr_tracking = previous_value # pylint: disable=protected-access
~/anaconda3/envs/py39/lib/python3.9/site-packages/keras/engine/training.py in __init__(self, *args, **kwargs)
287 self._steps_per_execution = None
288
--> 289 self._init_batch_counters()
290 self._base_model_initialized = True
291
~/anaconda3/envs/py39/lib/python3.9/site-packages/tensorflow/python/training/tracking/base.py in _method_wrapper(self, *args, **kwargs)
528 self._self_setattr_tracking = False # pylint: disable=protected-access
529 try:
--> 530 result = method(self, *args, **kwargs)
531 finally:
532 self._self_setattr_tracking = previous_value # pylint: disable=protected-access
~/anaconda3/envs/py39/lib/python3.9/site-packages/keras/engine/training.py in _init_batch_counters(self)
295 # `evaluate`, and `predict`.
296 agg = tf.VariableAggregation.ONLY_FIRST_REPLICA
--> 297 self._train_counter = tf.Variable(0, dtype='int64', aggregation=agg)
298 self._test_counter = tf.Variable(0, dtype='int64', aggregation=agg)
299 self._predict_counter = tf.Variable(
~/anaconda3/envs/py39/lib/python3.9/site-packages/tensorflow/python/ops/variables.py in __call__(cls, *args, **kwargs)
266 return cls._variable_v1_call(*args, **kwargs)
267 elif cls is Variable:
--> 268 return cls._variable_v2_call(*args, **kwargs)
269 else:
270 return super(VariableMetaclass, cls).__call__(*args, **kwargs)
~/anaconda3/envs/py39/lib/python3.9/site-packages/tensorflow/python/ops/variables.py in _variable_v2_call(cls, initial_value, trainable, validate_shape, caching_device, name, variable_def, dtype, import_scope, constraint, synchronization, aggregation, shape)
248 if aggregation is None:
249 aggregation = VariableAggregation.NONE
--> 250 return previous_getter(
251 initial_value=initial_value,
252 trainable=trainable,
~/anaconda3/envs/py39/lib/python3.9/site-packages/tensorflow/python/ops/variables.py in <lambda>(**kws)
241 shape=None):
242 """Call on Variable class. Useful to force the signature."""
--> 243 previous_getter = lambda **kws: default_variable_creator_v2(None, **kws)
244 for _, getter in ops.get_default_graph()._variable_creator_stack: # pylint: disable=protected-access
245 previous_getter = _make_getter(getter, previous_getter)
~/anaconda3/envs/py39/lib/python3.9/site-packages/tensorflow/python/ops/variable_scope.py in default_variable_creator_v2(next_creator, **kwargs)
2660 shape = kwargs.get("shape", None)
2661
-> 2662 return resource_variable_ops.ResourceVariable(
2663 initial_value=initial_value,
2664 trainable=trainable,
~/anaconda3/envs/py39/lib/python3.9/site-packages/tensorflow/python/ops/variables.py in __call__(cls, *args, **kwargs)
268 return cls._variable_v2_call(*args, **kwargs)
269 else:
--> 270 return super(VariableMetaclass, cls).__call__(*args, **kwargs)
271
272
~/anaconda3/envs/py39/lib/python3.9/site-packages/tensorflow/python/ops/resource_variable_ops.py in __init__(self, initial_value, trainable, collections, validate_shape, caching_device, name, dtype, variable_def, import_scope, constraint, distribute_strategy, synchronization, aggregation, shape)
1600 self._init_from_proto(variable_def, import_scope=import_scope)
1601 else:
-> 1602 self._init_from_args(
1603 initial_value=initial_value,
1604 trainable=trainable,
~/anaconda3/envs/py39/lib/python3.9/site-packages/tensorflow/python/ops/resource_variable_ops.py in _init_from_args(self, initial_value, trainable, collections, caching_device, name, dtype, constraint, synchronization, aggregation, distribute_strategy, shape)
1754 else:
1755 shape = initial_value.shape
-> 1756 handle = eager_safe_variable_handle(
1757 initial_value=initial_value,
1758 shape=shape,
~/anaconda3/envs/py39/lib/python3.9/site-packages/tensorflow/python/ops/resource_variable_ops.py in eager_safe_variable_handle(initial_value, shape, shared_name, name, graph_mode)
236 """
237 dtype = initial_value.dtype.base_dtype
--> 238 return _variable_handle_from_shape_and_dtype(shape, dtype, shared_name, name,
239 graph_mode, initial_value)
240
~/anaconda3/envs/py39/lib/python3.9/site-packages/tensorflow/python/ops/resource_variable_ops.py in _variable_handle_from_shape_and_dtype(shape, dtype, shared_name, name, graph_mode, initial_value)
176 handle_data.is_set = True
177 handle_data.shape_and_type.append(
--> 178 cpp_shape_inference_pb2.CppShapeInferenceResult.HandleShapeAndType(
179 shape=shape.as_proto(), dtype=dtype.as_datatype_enum))
180
TypeError: Parameter to MergeFrom() must be instance of same class: expected tensorflow.TensorShapeProto got tensorflow.TensorShapeProto.
我的解答思路和尝试过的方法
我想要达到的结果
