0f0d8be884a5383f29c945d7fe3a1baf4d3b11e2,keras/layers/convolutional.py,Cropping3D,__init__,#Cropping3D#Any#Any#,1800

Before Change

        self.cropping = tuple(cropping)
        assert len(self.cropping) == 3, "cropping must be a tuple length of 3"
        assert len(self.cropping[0]) == 2, "cropping[0] must be a tuple length of 2"
        assert len(self.cropping[1]) == 2, "cropping[1] must be a tuple length of 2"
        assert len(self.cropping[2]) == 2, "cropping[2] must be a tuple length of 2"
        assert dim_ordering in {"tf", "th"}, "dim_ordering must be in {tf, th}"
        self.dim_ordering = dim_ordering
        self.input_spec = [InputSpec(ndim=5)]

After Change

        if dim_ordering == "default":
            dim_ordering = K.image_dim_ordering()
        self.cropping = tuple(cropping)
        if len(self.cropping) != 3:
            raise ValueError("`cropping` must be a tuple length of 3.")
        if len(self.cropping[0]) != 2:
            raise ValueError("`cropping[0]` must be a tuple length of 2.")
        if len(self.cropping[1]) != 2:
            raise ValueError("`cropping[1]` must be a tuple length of 2.")
        if len(self.cropping[2]) != 2:
            raise ValueError("`cropping[2]` must be a tuple length of 2.")
        if dim_ordering not in {"tf", "th"}:
            raise ValueError("dim_ordering must be in {tf, th}.")
        self.dim_ordering = dim_ordering
        self.input_spec = [InputSpec(ndim=5)]

    def build(self, input_shape):

Instances