Callable should be a list of existing layers in the pipeline only.

[SaashaJoshi]

The error handling logic in qcnn.py (will be transferred to quantum_neural_network.py after #36) that checks if operations[0][0] is a Callable should be specific in what callable functions/classes are allowed. For neural networks in general, sequence expects operations that are inherited from the BaseLayer class in base_layer.py.

https://github.com/SaashaJoshi/quantum-image-processing/blob/828a9297f9fa1976f531b23c98ad05623c2a1390/quantum_image_processing/neural_networks/qcnn.py#L57-L60

Without a specification of a particular quantum layer callable, in-built functions like print, sum, etc. pass the current tests.

[amansingh2116]

I want to work on this issue to solve it. Can you please assign me this issue ?

[SaashaJoshi]

Hi @amansingh2116, sure! Let me know if you need any help or intro to the problem.

[amansingh2116]

My idea : Instead of checking if the first element of each tuple is callable, check whether it’s a class that inherits from BaseLayer using issubclass function for each item in the list. Like this:

for layer, params in operations:
        if not isinstance(layer, type) or not issubclass(layer, BaseLayer):
            raise TypeError(f"Operation {layer} must inherit from BaseLayer.")

Please review this and check if this would solve the issue or not, so I can create a PR.

[amansingh2116]

My idea : Instead of checking if the first element of each tuple is callable, check whether it’s a class that inherits from BaseLayer using issubclass function for each item in the list. Like this:

for layer, params in operations:
        if not isinstance(layer, type) or not issubclass(layer, BaseLayer):
            raise TypeError(f"Operation {layer} must inherit from BaseLayer.")

Please review this and check if this would solve the issue or not, so I can create a PR.

Could you please review and reply, so I would be assigned and can start working on the issue.