layer.py 文件源码

def __init__(self, num_internals=0, scope='layer', summary_labels=None):
        self.num_internals = num_internals
        self.summary_labels = set(summary_labels or ())

        self.named_tensors = dict()
        self.variables = dict()
        self.all_variables = dict()
        self.summaries = list()

        def custom_getter(getter, name, registered=False, **kwargs):
            variable = getter(name=name, registered=True, **kwargs)
            if not registered:
                self.all_variables[name] = variable
                if kwargs.get('trainable', True) and not name.startswith('optimization'):
                    self.variables[name] = variable
                    if 'variables' in self.summary_labels:
                        summary = tf.summary.histogram(name=name, values=variable)
                        self.summaries.append(summary)
            return variable

        self.apply = tf.make_template(
            name_=(scope + '/apply'),
            func_=self.tf_apply,
            custom_getter_=custom_getter
        )
        self.regularization_loss = tf.make_template(
            name_=(scope + '/regularization-loss'),
            func_=self.tf_regularization_loss,
            custom_getter_=custom_getter
        )