keras-team/keras · error · ValueError

Cannot infer argument `num` from shape {x.shape}. Either pro

Error message

Cannot infer argument `num` from shape {x.shape}. Either provide a tensor with a concrete shape in the `axis` dimension or explicitly pass the `num` argument.

What it means

For element-count based behavior (e.g. boolean all/any), num defaults to the size of the reduced axis. In symbolic tracing that dimension may be None, so the count cannot be inferred and you must supply num.

Source

Thrown at keras/src/ops/core.py:764

class Unstack(Operation):
    def __init__(self, num=None, axis=0, *, name=None):
        super().__init__(name=name)
        self.num = num
        self.axis = axis

    def call(self, x):
        return backend.core.unstack(x, self.num, self.axis)

    def compute_output_spec(self, x):
        axis = canonicalize_axis(self.axis, len(x.shape))
        output_shapes = x.shape[:axis] + x.shape[axis + 1 :]
        num = self.num
        if num is None:
            num = x.shape[axis]
        if num is None:
            raise ValueError(
                "Cannot infer argument `num` from shape "
                f"{x.shape}. Either provide a tensor with a "
                "concrete shape in the `axis` dimension or "
                "explicitly pass the `num` argument."
            )
        output = [
            KerasTensor(shape=output_shapes, dtype=x.dtype) for _ in range(num)
        ]
        return output


@keras_export("keras.ops.unstack")
def unstack(x, num=None, axis=0):
    """Unpacks the given dimension of a rank-R tensor into rank-(R-1) tensors.

    Args:
        x: The input tensor.
        num: The length of the dimension axis. Automatically inferred

View on GitHub (pinned to 7a34a03db6)

Solutions

1. Pass num explicitly
2. Run outside symbolic tracing or with concrete shapes
3. Reshape the tensor so the axis dim is concrete before the reduction

Example fix

# before
keras.ops.all(x)  # x.shape[axis] is None under tracing

# after
keras.ops.all(x, num=128)  # or pass a concrete-shaped tensor

if num is None:
    num = x.shape[axis]
assert num is not None, 'pass num explicitly when axis dim is dynamic'

When it happens

Trigger: Calling an op with num=None on a KerasTensor whose shape[axis] is None inside a functional model or symbolic call

Common situations: Using count-based reductions on boolean tensors inside a symbolic (KerasTensor) trace or functional model

Related errors

• The `weights` argument should be either `None` (random initi
• RandomCrop requires the input to have a fully defined height
• All `axis` values to be kept must have a known shape. Receiv
• R2Score expects 2D inputs with shape (batch_size, output_dim
• Array inputs to associative_scan must have the same first di

AI-assisted analysis of keras-team/keras@7a34a03db6 (2026-08-25). Data as JSON: /api/errors/3f3d73247c906221. Report an issue: GitHub.