keras-team/keras · error · ValueError

Expected `size` to be a tuple of 2 integers. Received: size=

Error message

Expected `size` to be a tuple of 2 integers. Received: size={size}

What it means

keras.ops.image.resize requires size to be exactly a 2-element sequence (height, width). Passing an int, a 3-tuple, a nested list, or an empty sequence raises this ValueError before any resizing.

Source

Thrown at keras/src/ops/image.py:359

    >>> x = np.random.random((2, 4, 4, 3)) # batch of 2 RGB images
    >>> y = keras.ops.image.resize(x, (2, 2))
    >>> y.shape
    (2, 2, 2, 3)

    >>> x = np.random.random((4, 4, 3)) # single RGB image
    >>> y = keras.ops.image.resize(x, (2, 2))
    >>> y.shape
    (2, 2, 3)

    >>> x = np.random.random((2, 3, 4, 4)) # batch of 2 RGB images
    >>> y = keras.ops.image.resize(x, (2, 2),
    ...     data_format="channels_first")
    >>> y.shape
    (2, 3, 2, 2)
    """
    if len(size) != 2:
        raise ValueError(
            "Expected `size` to be a tuple of 2 integers. "
            f"Received: size={size}"
        )
    if (isinstance(size[0], int) and size[0] <= 0) or (
        isinstance(size[1], int) and size[1] <= 0
    ):
        raise ValueError(
            f"`size` must have positive height and width. Received: size={size}"
        )
    if len(images.shape) < 3 or len(images.shape) > 4:
        raise ValueError(
            "Invalid images rank: expected rank 3 (single image) "
            "or rank 4 (batch of images). Received input with shape: "
            f"images.shape={images.shape}"
        )
    if pad_to_aspect_ratio and crop_to_aspect_ratio:
        raise ValueError(
            "Only one of `pad_to_aspect_ratio` & `crop_to_aspect_ratio` "

View on GitHub (pinned to 7a34a03db6)

Solutions

1. Pass exactly two values: resize(images, (224, 224))
2. If your target came as a full shape, slice it: resize(images, shape[:-1]) for channels_last or shape[1:3] as appropriate

Example fix

# before
y = keras.ops.image.resize(x, (224, 224, 3))

# after
y = keras.ops.image.resize(x, (224, 224))

size = tuple(size)
assert len(size) == 2, f'size must have 2 entries, got {size!r}'

def is_valid_resize_size(size) -> bool:
    try:
        s = tuple(size)
    except TypeError:
        return False
    return len(s) == 2

When it happens

Trigger: Calling resize(images, 224); resize(images, (224, 224, 3)) (including channels); passing the output shape of another op that has 3+ entries.

Common situations: Confusing target size with full output shape including channels; passing a config value parsed as int; chaining ops where .shape slices are the wrong length.

Related errors

• `size` must have positive height and width. Received: size={
• Only one of `pad_to_aspect_ratio` & `crop_to_aspect_ratio` c
• {name} must be >= 0. Received: {name}={value}
• Must specify exactly two of top_padding, bottom_padding, tar
• Must specify exactly two of left_padding, right_padding, tar

AI-assisted analysis of keras-team/keras@7a34a03db6 (2026-08-25). Data as JSON: /api/errors/2a44c5f2a2c97cd2. Report an issue: GitHub.