2022-01-02 18:41:16.826148: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2)
Traceback (most recent call last):
  File "E:/Code/PyCharm/TensorFlow学习/Keras/自定义评估指标.py", line 59, in <module>
    validation_split=0.2
  File "D:\Anaconda\lib\site-packages\keras\engine\training.py", line 1184, in fit
    tmp_logs = self.train_function(iterator)
  File "D:\Anaconda\lib\site-packages\tensorflow\python\eager\def_function.py", line 885, in __call__
    result = self._call(*args, **kwds)
  File "D:\Anaconda\lib\site-packages\tensorflow\python\eager\def_function.py", line 933, in _call
    self._initialize(args, kwds, add_initializers_to=initializers)
  File "D:\Anaconda\lib\site-packages\tensorflow\python\eager\def_function.py", line 760, in _initialize
    *args, **kwds))
  File "D:\Anaconda\lib\site-packages\tensorflow\python\eager\function.py", line 3066, in _get_concrete_function_internal_garbage_collected
    graph_function, _ = self._maybe_define_function(args, kwargs)
  File "D:\Anaconda\lib\site-packages\tensorflow\python\eager\function.py", line 3463, in _maybe_define_function
    graph_function = self._create_graph_function(args, kwargs)
  File "D:\Anaconda\lib\site-packages\tensorflow\python\eager\function.py", line 3308, in _create_graph_function
    capture_by_value=self._capture_by_value),
  File "D:\Anaconda\lib\site-packages\tensorflow\python\framework\func_graph.py", line 1007, in func_graph_from_py_func
    func_outputs = python_func(*func_args, **func_kwargs)
  File "D:\Anaconda\lib\site-packages\tensorflow\python\eager\def_function.py", line 668, in wrapped_fn
    out = weak_wrapped_fn().__wrapped__(*args, **kwds)
  File "D:\Anaconda\lib\site-packages\tensorflow\python\framework\func_graph.py", line 994, in wrapper
    raise e.ag_error_metadata.to_exception(e)
TypeError: in user code:

    D:\Anaconda\lib\site-packages\keras\engine\training.py:853 train_function  *
        return step_function(self, iterator)

    TypeError: tf__update_state() got an unexpected keyword argument 'sample_weight'

问题原因：
使用TensorFlow实现一些自定义层或者指标等，在一些需要实现的函数参数没有加上默认参数，导致模型训练时传递参数出现问题

解决办法：
在指定地方添加上默认参数

    def update_state(self, y_true, y_pred, sample_weight=None):
        y_pred = tf.reshape(tf.argmax(y_pred, axis=1), shape=(-1, 1))
        values = tf.cast(y_true, 'int32') == tf.cast(y_pred, 'int32')
        values = tf.cast(values, 'float32')
        self.true_positives.assign_add(tf.reduce_sum(values))