我编写了一个Keras自定义层的简小实现，其中我直接从https://keras.io/layers/writing-your-own-keras-layers/复制了类定义
然而，当我尝试像调用标准Dense层一样调用这个自定义层时，我得到了“AssertionError”错误，并且我的Pycharm抛出了对象不可调用的警告
我在这里错过了一些基本的东西，但我无法弄清楚
如果我将这行代码
model_out = MyLayer(2)(model_in)改为
model_out = Dense(2)(model_in)它就能工作
这里是无法运行的代码:
from tensorflow.keras.layers import Dense, Inputfrom tensorflow.keras.models import Modelimport numpy as npfrom tensorflow.keras.layers import Layerfrom tensorflow.keras import backend as Kfrom tensorflow.keras import optimizersclass MyLayer(Layer): def __init__(self, output_dim, **kwargs): self.output_dim = output_dim super(MyLayer, self).__init__(**kwargs) def build(self, input_shape): # 为此层创建一个可训练的权重变量。 self.kernel = self.add_weight(name='kernel', shape=(input_shape[1], self.output_dim), initializer='uniform', trainable=True) super(MyLayer, self).build(input_shape) # 确保在最后调用这个 def call(self, x): return K.dot(x, self.kernel) def compute_output_shape(self, input_shape): return (input_shape[0], self.output_dim)model_in = Input([4])model_out = MyLayer(2)(model_in)model = Model(inputs=model_in, outputs=model_out, name='my_model')adamOpt = optimizers.Adam(lr=1e-4)model.compile(optimizer=adamOpt, loss='mean_squared_error')hist = model.fit(np.ones((10, 4)), np.ones((10, 2))+1, verbose=2, epochs=100, batch_size=np.power(2,2))我期望这应该能够编译并运行，就像我调用Dense而不是MyLayer时那样
完整的错误信息
Traceback (most recent call last): File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 527, in make_tensor_proto str_values = [compat.as_bytes(x) for x in proto_values] File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 527, in <listcomp> str_values = [compat.as_bytes(x) for x in proto_values] File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\util\compat.py", line 61, in as_bytes (bytes_or_text,))TypeError: Expected binary or unicode string, got Dimension(4)During handling of the above exception, another exception occurred:Traceback (most recent call last): File "G:/My Drive/python/wholebrain_worm/extra_classes.py", line 31, in <module> model_out = MyLayer(2)(model_in) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\keras\engine\base_layer.py", line 746, in __call__ self.build(input_shapes) File "G:/My Drive/python/wholebrain_worm/extra_classes.py", line 20, in build trainable=True) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\keras\engine\base_layer.py", line 609, in add_weight aggregation=aggregation) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\training\checkpointable\base.py", line 639, in _add_variable_with_custom_getter **kwargs_for_getter) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\keras\engine\base_layer.py", line 1977, in make_variable aggregation=aggregation) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\ops\variables.py", line 183, in __call__ return cls._variable_v1_call(*args, **kwargs) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\ops\variables.py", line 146, in _variable_v1_call aggregation=aggregation) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\ops\variables.py", line 125, in <lambda> previous_getter = lambda **kwargs: default_variable_creator(None, **kwargs) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\ops\variable_scope.py", line 2437, in default_variable_creator import_scope=import_scope) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\ops\variables.py", line 187, in __call__ return super(VariableMetaclass, cls).__call__(*args, **kwargs) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 297, in __init__ constraint=constraint) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\ops\resource_variable_ops.py", line 409, in _init_from_args initial_value() if init_from_fn else initial_value, File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\keras\engine\base_layer.py", line 1959, in <lambda> shape, dtype=dtype, partition_info=partition_info) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\ops\init_ops.py", line 255, in __call__ shape, self.minval, self.maxval, dtype, seed=self.seed) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\ops\random_ops.py", line 235, in random_uniform shape = _ShapeTensor(shape) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\ops\random_ops.py", line 44, in _ShapeTensor return ops.convert_to_tensor(shape, dtype=dtype, name="shape") File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\framework\ops.py", line 1050, in convert_to_tensor as_ref=False) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\framework\ops.py", line 1146, in internal_convert_to_tensor ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\framework\constant_op.py", line 229, in _constant_tensor_conversion_function return constant(v, dtype=dtype, name=name) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\framework\constant_op.py", line 208, in constant value, dtype=dtype, shape=shape, verify_shape=verify_shape)) File "C:\CDocuments\python\venv\lib\site-packages\tensorflow\python\framework\tensor_util.py", line 531, in make_tensor_proto "supported type." % (type(values), values))TypeError: Failed to convert object of type <class 'tuple'> to Tensor. Contents: (Dimension(4), 2). Consider casting elements to a supported type.回答：
我认识到这是Keras创建新层的示例，您可以在这里找到这里。
一个非常重要的细节是，这是一个keras的示例，但您正在与tf.keras一起使用。我认为TensorFlow中一定有一个错误，因为这个示例在keras中工作，但在tf.keras中不工作。
一般来说，您不应该混合使用keras和tf.keras，因为它们具有相同的API但实现不同。如果您将所有tf.keras导入改为普通的keras，那么代码将正确工作。
