Aryan_33290
Author: Aryan8912
Pull request: yes

# What does this PR do?
Minimized Gradient Casting to float32:

Instead of casting gradients to float32 upfront, the optimizer now retains the original precision of grad (float16 or bfloat16), using that precision for all calculations unless a specific operation demands higher precision.
Precision Management for Moment States:

The moment estimates (exp_avg, exp_avg_sq_row, exp_avg_sq_col, exp_avg_sq) are initialized and updated in the same precision as grad, reducing the memory overhead compared to float32 calculations.
In-place Operations for Intermediate Calculations:

Operations like grad**2 + group["eps"][0] and mean calculations are now done in-place (e.g., add_ instead of +), which avoids temporary tensor creation and reduces memory consumption.
Streamlined Factored Updates:

For factored updates, the calculations of exp_avg_sq_row and exp_avg_sq_col mean values are done in place, reducing the peak memory usage at each step.
Reusing update after calculating exp_avg_sq_row and exp_avg_sq_col saves memory by avoiding multiple copies.
Direct In-Place Updates for p_data_fp32:

Instead of copying p_data_fp32 back and forth, we update it directly in place, and only if p was initially in float16 or bfloat16, we convert p_data_fp32 back at the end.

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Fixes #33290 


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