[Fix] : Broadcasting in division and power operations with tests #25
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- Refactored GradFn_div and GradFn_pow to handle broadcasting correctly with modulo indexing - Preserved original tensors in Tensor_div and Tensor_pow before broadcasting - Fixed gradient computation in both operations to work with tensors of different shapes - Simplified gradient function implementation by reusing result tensor - Fixed power operation's gradient calculation to use cached result instead of recalculating
Advaitgaur004
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Advaitgaur004
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I've fixed the broadcasting implementation in the division and power operations, similar to our previous fix for the multiplication operation. I've also added backwards tests for both operations to ensure they're working correctly.