(self, dtype,
                   op, N, C,
                   D=1, H=1, W=1,
                   J=1, T=1, R=1, S=1,
                   pad_j=0, pad_d=0, pad_h=0, pad_w=0,
                   str_j=None, str_d=None, str_h=None, str_w=None)
Create a new PoolLayer parameter object.
        This then is passed as an argument to all pooling kernels.

        Arguments:
            op (str): "max", "avg", "l2" pooling (currently bprop only supports
                      max, but not avg and l2)
            N (int): Number of images in mini-batch

            C (int): Number of input feature maps
            D (int, optional): Depth of input image.  Defaults to 1
            H (int, optional): Height of input image.  Defaults to 1
            W (int, optional): Width of input image.  Defaults to 1

            J (int, optional): Size of feature map pooling window
                               (maxout n_pieces).  Defaults to 1
            T (int, optional): Depth of pooling window.  Defaults to 1
            R (int, optional): Height of pooling window.  Defaults to 1
            S (int, optional): Width of pooling window.  Defaults to 1

            pad_j (int, optional): amount of zero-padding around the fm pooling
                                   window edge.  Defaults to 0.
            pad_d (int, optional): amount of zero-padding around the depth edge
                                   Defaults to 0.
            pad_h (int, optional): amount of zero-padding around the height edge
                                   Defaults to 0.
            pad_w (int, optional): amount of zero-padding around the width edge
                                   Defaults to 0.

            str_j (int, optional): factor to step the filters by in the fm
                                   pooling window direction.  Defaults to 1
            str_d (int, optional): factor to step the filters by in the depth
                                   direction.  Defaults to 1
            str_h (int, optional): factor to step the filters by in the depth
                                   direction.  Defaults to 1
            str_w (int, optional): factor to step the filters by in the depth
                                   direction.  Defaults to 1

        Leave spatial dimensions at 1 to allow feature map pooling in the fc layers.
Create a new PoolLayer parameter object.
        This then is passed as an argument to all pooling kernels.
Create a new PoolLayer parameter object . This then is passed as an argument to all pooling kernels .
def pool_layer(self, dtype,
                   op, N, C,
                   D=1, H=1, W=1,
                   J=1, T=1, R=1, S=1,
                   pad_j=0, pad_d=0, pad_h=0, pad_w=0,
                   str_j=None, str_d=None, str_h=None, str_w=None):
        """
        Create a new PoolLayer parameter object.
        This then is passed as an argument to all pooling kernels.

        Arguments:
            op (str): "max", "avg", "l2" pooling (currently bprop only supports
                      max, but not avg and l2)
            N (int): Number of images in mini-batch

            C (int): Number of input feature maps
            D (int, optional): Depth of input image.  Defaults to 1
            H (int, optional): Height of input image.  Defaults to 1
            W (int, optional): Width of input image.  Defaults to 1

            J (int, optional): Size of feature map pooling window
                               (maxout n_pieces).  Defaults to 1
            T (int, optional): Depth of pooling window.  Defaults to 1
            R (int, optional): Height of pooling window.  Defaults to 1
            S (int, optional): Width of pooling window.  Defaults to 1

            pad_j (int, optional): amount of zero-padding around the fm pooling
                                   window edge.  Defaults to 0.
            pad_d (int, optional): amount of zero-padding around the depth edge
                                   Defaults to 0.
            pad_h (int, optional): amount of zero-padding around the height edge
                                   Defaults to 0.
            pad_w (int, optional): amount of zero-padding around the width edge
                                   Defaults to 0.

            str_j (int, optional): factor to step the filters by in the fm
                                   pooling window direction.  Defaults to 1
            str_d (int, optional): factor to step the filters by in the depth
                                   direction.  Defaults to 1
            str_h (int, optional): factor to step the filters by in the depth
                                   direction.  Defaults to 1
            str_w (int, optional): factor to step the filters by in the depth
                                   direction.  Defaults to 1

        Leave spatial dimensions at 1 to allow feature map pooling in the fc layers.
        """
        raise NotImplementedError()
def pool_layer ( self , dtype , op , N , C , D = 1 , H = 1 , W = 1 , J = 1 , T = 1 , R = 1 , S = 1 , pad_j = 0 , pad_d = 0 , pad_h = 0 , pad_w = 0 , str_j = None , str_d = None , str_h = None , str_w = None ) : raise NotImplementedError ( )