neural-network-genetic-algorithm
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'list' object has no attribute 'train'
nice code, but I seem to be running into problem when going through the 2nd generation (1st gen works fine), the train_network will throw an error: 'list' object has no attribute ' train'.
so basically -----
def train_network(networks): for network in networks: network.train() <---- 'list' has no attribute 'train' error. pbar.update(1)
btw the database I have hardcoded it in the train, so it's not here
The error message "'list' object has no attribute 'train'" suggests that the variable networks
is a list, and the code is trying to call the train
method on this list. However, the intention is likely to iterate over individual network objects within the list and call the train
method on each of them.
Code Analysis:
Here, the networks
parameter is expected to be a list of network objects. The code iterates through each element in the list (for network in networks
) and attempts to call the train
method on each element.
Probable Cause:
The error may occur if, during the second generation, the list networks
is not containing instances of the Network
class as expected but is instead a list of lists or other data structures.
Suggestions:
Ensure Consistency in networks
:
Check the code that generates the networks list, especially during the second generation.
Verify that networks
is a list of Network
instances, not a list of lists or other data types.
Logging for Debugging:
Introduce logging statements in the code to print the type of each element in networks
during the second generation.
This can help identify what type of objects are present in the list.
def train_network(networks): for network in networks: print(f"Type of network: {type(network)}") network.train() pbar.update(1)
Error Handling:
Implement error handling to gracefully handle cases where the elements in networks
are not of the expected type.
For example, use if isinstance(network, Network)
: to check if an element is an instance of the Network
class before calling the train method.
def train_network(networks): for network in networks: if isinstance(network, Network): network.train() pbar.update(1) else: print(f"Skipping non-Network element: {network}")
By addressing these suggestions, you can identify and resolve the issue causing the "'list' object has no attribute 'train'" error during the second generation of training.