keras-team/keras · error · ValueError

A merge layer should be called on a list of at least 1…

Error message

A merge layer should be called on a list of at least 1 input. Received {len(input_shape)} inputs. Full input_shape received: {input_shape}

What it means

Merge layers validate that build() received at least one input shape. This error is raised when the input_shape list is empty (len < 1), meaning the layer was called with an empty list of inputs and there is nothing to merge.

Solutions

1. Ensure at least one (usually two or more) tensors are passed to the merge layer
2. Guard dynamic pipelines: if not tensors: skip or raise your own descriptive error
3. Check upstream filtering/conditionals that assemble the input list

Example fix

# before
out = merge_layer([])

# after
out = merge_layer(tensors)  # tensors has >= 1 element

assert isinstance(inputs, (list, tuple)) and len(inputs) >= 1, 'merge needs at least one input'

def has_merge_inputs(inputs) -> bool:
    return isinstance(inputs, (list, tuple)) and len(inputs) >= 1

When it happens

Trigger: Calling a merge layer with an empty list: Add()([]); programmatically building a model whose input list is empty due to filtering bugs.

Common situations: Dynamic input collection code that can produce an empty list (e.g. filtering layers that match nothing); model surgery scripts that rebuild merge nodes with no inputs.

Related errors

• A merge layer should be called on a list of inputs…
• A merge layer should be called on a list of inputs…
• Cannot merge tensors with different batch sizes. Received…
• Cannot set an empty vocabulary. Received: vocabulary=
• Inputs have incompatible shapes. Received shapes

AI-assisted analysis of keras-team/keras@7a34a03db6 (2026-08-25). Data as JSON: /api/errors/24543a274dbdf3b1. Report an issue: GitHub.

Appendix: source

Thrown at keras/src/layers/merging/base_merge.py:108

                output_shape.append(i)
            else:
                if i != j:
                    raise ValueError(
                        "Inputs have incompatible shapes. "
                        f"Received shapes {shape1} and {shape2}"
                    )
                output_shape.append(i)
        return tuple(output_shape)

    def build(self, input_shape):
        # Used purely for shape validation.
        if not isinstance(input_shape[0], (tuple, list)):
            raise ValueError(
                "A merge layer should be called on a list of inputs. "
                f"Received: input_shape={input_shape} (not a list of shapes)"
            )
        if len(input_shape) < 1:
            raise ValueError(
                "A merge layer should be called "
                "on a list of at least 1 input. "
                f"Received {len(input_shape)} inputs. "
                f"Full input_shape received: {input_shape}"
            )

        batch_sizes = {s[0] for s in input_shape if s} - {None}
        if len(batch_sizes) > 1:
            raise ValueError(
                "Cannot merge tensors with different batch sizes. "
                f"Received tensors with shapes {input_shape}"
            )

        if input_shape[0] is None:
            output_shape = None
        else:
            output_shape = input_shape[0][1:]

View on GitHub (pinned to 7a34a03db6)