keras-team/keras · error · ValueError

`cropping` should be either an int, a tuple of 3 ints (symme

Error message

`cropping` should be either an int, a tuple of 3 ints (symmetric_dim1_crop, symmetric_dim2_crop, symmetric_dim3_crop), or a tuple of 3 tuples of 2 ints ((left_dim1_crop, right_dim1_crop), (left_dim2_crop, right_dim2_crop), (left_dim3_crop, right_dim2_crop)). Received: {cropping}.

What it means

Error "`cropping` should be either an int, a tuple of 3 ints (symmetric_dim1_crop, symmetric_dim2_crop, symmetric_dim3_crop), or a tuple of 3 tuples of 2 ints ((left_dim1_crop, right_dim1_crop), (left_dim2_crop, right_dim2_crop), (left_dim3_crop, right_dim2_crop)). Received: {cropping}." thrown in keras-team/keras.

Source

Thrown at keras/src/layers/reshaping/cropping3d.py:91

                (cropping, cropping),
            )
        elif hasattr(cropping, "__len__"):
            if len(cropping) != 3:
                raise ValueError(
                    f"`cropping` should have 3 elements. Received: {cropping}."
                )
            dim1_cropping = argument_validation.standardize_tuple(
                cropping[0], 2, "1st entry of cropping", allow_zero=True
            )
            dim2_cropping = argument_validation.standardize_tuple(
                cropping[1], 2, "2nd entry of cropping", allow_zero=True
            )
            dim3_cropping = argument_validation.standardize_tuple(
                cropping[2], 2, "3rd entry of cropping", allow_zero=True
            )
            self.cropping = (dim1_cropping, dim2_cropping, dim3_cropping)
        else:
            raise ValueError(
                "`cropping` should be either an int, a tuple of 3 ints "
                "(symmetric_dim1_crop, symmetric_dim2_crop, "
                "symmetric_dim3_crop), "
                "or a tuple of 3 tuples of 2 ints "
                "((left_dim1_crop, right_dim1_crop),"
                " (left_dim2_crop, right_dim2_crop),"
                " (left_dim3_crop, right_dim2_crop)). "
                f"Received: {cropping}."
            )
        self.input_spec = InputSpec(ndim=5)

    def compute_output_shape(self, input_shape):
        if self.data_format == "channels_first":
            spatial_dims = list(input_shape[2:5])
        else:
            spatial_dims = list(input_shape[1:4])

        for index in range(0, 3):

View on GitHub (pinned to 7a34a03db6)

When it happens

Trigger: Thrown at keras/src/layers/reshaping/cropping3d.py:91 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/620bb79c3f6f8ced. Report an issue: GitHub.