keras-team/keras · error · ValueError

`padding` should be either an int, a tuple of 3 ints (symmet

Error message

`padding` should be either an int, a tuple of 3 ints (symmetric_dim1_pad, symmetric_dim2_pad, symmetric_dim3_pad), or a tuple of 3 tuples of 2 ints ((left_dim1_pad, right_dim1_pad), (left_dim2_pad, right_dim2_pad), (left_dim3_pad, right_dim2_pad)). Received: padding={padding}.

What it means

Error "`padding` should be either an int, a tuple of 3 ints (symmetric_dim1_pad, symmetric_dim2_pad, symmetric_dim3_pad), or a tuple of 3 tuples of 2 ints ((left_dim1_pad, right_dim1_pad), (left_dim2_pad, right_dim2_pad), (left_dim3_pad, right_dim2_pad)). Received: padding={padding}." thrown in keras-team/keras.

Source

Thrown at keras/src/layers/reshaping/zero_padding3d.py:87

                (padding, padding),
            )
        elif hasattr(padding, "__len__"):
            if len(padding) != 3:
                raise ValueError(
                    f"`padding` should have 3 elements. Received: {padding}."
                )
            dim1_padding = argument_validation.standardize_tuple(
                padding[0], 2, "1st entry of padding", allow_zero=True
            )
            dim2_padding = argument_validation.standardize_tuple(
                padding[1], 2, "2nd entry of padding", allow_zero=True
            )
            dim3_padding = argument_validation.standardize_tuple(
                padding[2], 2, "3rd entry of padding", allow_zero=True
            )
            self.padding = (dim1_padding, dim2_padding, dim3_padding)
        else:
            raise ValueError(
                "`padding` should be either an int, a tuple of 3 ints "
                "(symmetric_dim1_pad, symmetric_dim2_pad, symmetric_dim3_pad), "
                "or a tuple of 3 tuples of 2 ints "
                "((left_dim1_pad, right_dim1_pad),"
                " (left_dim2_pad, right_dim2_pad),"
                " (left_dim3_pad, right_dim2_pad)). "
                f"Received: padding={padding}."
            )
        self.input_spec = InputSpec(ndim=5)

    def compute_output_shape(self, input_shape):
        output_shape = list(input_shape)
        spatial_dims_offset = 2 if self.data_format == "channels_first" else 1
        for index in range(0, 3):
            if output_shape[index + spatial_dims_offset] is not None:
                output_shape[index + spatial_dims_offset] += (
                    self.padding[index][0] + self.padding[index][1]
                )

View on GitHub (pinned to 7a34a03db6)

When it happens

Trigger: Thrown at keras/src/layers/reshaping/zero_padding3d.py:87 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of keras-team/keras@7a34a03db6 (2026-08-25). Data as JSON: /api/errors/81cc9d1eb9d55aa3. Report an issue: GitHub.