keras-team/keras · error · ValueError

The `weights` argument should be either `None` (random initi

Error message

The `weights` argument should be either `None` (random initialization), `imagenet` (pre-training on ImageNet), or the path to the weights file to be loaded.  Received `weights={weights}`

What it means

Error "The `weights` argument should be either `None` (random initialization), `imagenet` (pre-training on ImageNet), or the path to the weights file to be loaded. Received `weights={weights}`" thrown in keras-team/keras.

Source

Thrown at keras/src/applications/mobilenet_v2.py:113

                will be applied to the output of the
                last convolutional block, and thus
                the output of the model will be a 2D tensor.
            - `max` means that global max pooling will be applied.
        classes: Optional number of classes to classify images into,
            only to be specified if `include_top` is `True`, and if
            no `weights` argument is specified. Defaults to `1000`.
        classifier_activation: A `str` or callable. The activation function
            to use on the "top" layer. Ignored unless `include_top=True`.
            Set `classifier_activation=None` to return the logits of the "top"
            layer. When loading pretrained weights, `classifier_activation`
            can only be `None` or `"softmax"`.
        name: String, the name of the model.

    Returns:
        A model instance.
    """
    if not (weights in {"imagenet", None} or file_utils.exists(weights)):
        raise ValueError(
            "The `weights` argument should be either "
            "`None` (random initialization), `imagenet` "
            "(pre-training on ImageNet), "
            "or the path to the weights file to be loaded.  "
            f"Received `weights={weights}`"
        )

    if weights == "imagenet" and include_top and classes != 1000:
        raise ValueError(
            'If using `weights="imagenet"` with `include_top` '
            f"as true, `classes` should be 1000. Received `classes={classes}`"
        )

    # Determine proper input shape and default size.
    # If both input_shape and input_tensor are used, they should match
    if input_shape is not None and input_tensor is not None:
        try:
            is_input_t_tensor = backend.is_keras_tensor(input_tensor)

View on GitHub (pinned to 7a34a03db6)

When it happens

Trigger: Thrown at keras/src/applications/mobilenet_v2.py:113 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/51f2000a193a6b0f. Report an issue: GitHub.