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implemented std_grad in backward.mojo #16

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@ManishAradwad ManishAradwad commented Nov 6, 2023

@TilliFe @andresnowak please verify the implementation #9

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andresnowak commented Nov 6, 2023

From what i understand, the only thing that is incorrect is this a.grad.simd_load[_nelts](idx_a) * std_derivativeinstead of a multiplication it should be a sum, we have to accumulate the gradient in the a Tensor and doing the chain rule in this operation std_derivative * b.grad.load(idx_b)

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TilliFe commented Nov 7, 2023

Thanks @ManishAradwad :). I will merge this as soon as I am back. Leave this PR open.

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From what i understand, the only thing that is incorrect is this a.grad.simd_load[_nelts](idx_a) * std_derivativeinstead of a multiplication it should be a sum, we have to accumulate the gradient in the a Tensor and doing the chain rule in this operation std_derivative * b.grad.load(idx_b)

Right! I'll correct it

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