⚡ Bolt: Optimize autograd backpropagation pass

[teerthsharma]

💡 What: Refactored accumulate_grad to take ownership of Tensors, and replaced .clone() in backward loop with .take() and re-insertion.
🎯 Why: Tensor instances carry heap-allocated metadata (shape, strides). Cloning gradients at every step in backprop unnecessarily replicates metadata.
📊 Impact: Removes redundant deep cloning of Tensor wrappers during reverse-mode diff, resulting in faster and more memory-efficient gradient updates.
🔬 Measurement: Backpropagation allocates significantly fewer heap elements; validated by autograd test suite passing.

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PR created automatically by Jules for task 15719591753338873973 started by @teerthsharma

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