6710396acaf62b40ba01fadd9d488d6641995d83,keras/layers/pooling.py,_Pooling2D,__init__,#_Pooling2D#Any#Any#Any#Any#,114

Before Change

        super(_Pooling2D, self).__init__(**kwargs)
        if data_format == "default":
            data_format = K.image_data_format()
        self.pool_size = tuple(pool_size)
        if strides is None:
            strides = self.pool_size
        self.strides = tuple(strides)
        if border_mode not in {"valid", "same"}:
            raise ValueError("`border_mode` must be in {valid, same}.")
        self.border_mode = border_mode
        if data_format not in {"channels_last", "channels_first"}:
            raise ValueError("`data_format` must be in {"channels_last", "channels_first"}.")
        self.data_format = data_format
        self.input_spec = [InputSpec(ndim=4)]

    def get_output_shape_for(self, input_shape):

After Change

    Abstract class for different pooling 2D layers.
    

    def __init__(self, pool_size=(2, 2), strides=None, padding="valid",
                 data_format=None, **kwargs):
        super(_Pooling2D, self).__init__(**kwargs)
        data_format = conv_utils.normalize_data_format(data_format)
        if strides is None:
            strides = pool_size
        self.pool_size = conv_utils.normalize_tuple(pool_size, 2, "pool_size")
        self.strides = conv_utils.normalize_tuple(pool_size, 2, "strides")
        self.padding = conv_utils.normalize_padding(padding)
        self.data_format = conv_utils.normalize_data_format(data_format)
        self.input_spec = [InputSpec(ndim=4)]

    def get_output_shape_for(self, input_shape):

Instances