Changing Backend Tensor initialization #5056
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added 2 commits
October 24, 2025 21:17
Summary: X-link: facebookresearch/FBGEMM#2065 **Context:** Currently, RocksDB stores data on row-wise format, to enable optimizer offloading for the Kernel. We will append the optimizer state to its corresponding row. During initialization, we need to randomly initialize weights while the optimizer values need to initialized to zero. When optimizer offloading is enabled, **In this diff:** We add two new arguments: 1. enable_optimizer_offloading: This flag toggles between initializing the last optimizer_D rows to zero 2. optimizer_D: The number of columns in the table that needs to be initialized to zero. This set of columns represent the optimizer values (w/wo padding). **Scenarios:** 1. Optimizer_offloading is False: max_D = Dimensions of weights only, optimizer_D = 0 2. Optimizer_offloading is True: max_D = Dimension of weights (w_D) + optimizers (o_D) optimizer_D = dimensions of optimizers (o_D) initialize o_D columns with zero Differential Revision: D85157732
Summary: X-link: meta-pytorch/torchrec#3484 X-link: facebookresearch/FBGEMM#2066 **Context:** Currently, we are enabling SSD optimizer offloading for the ssd tbe kernel **In this diff:** We retrieve the newly added parameters from the tbe config and pass it down to the tbe Differential Revision: D85353134
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Summary:
X-link: meta-pytorch/torchrec#3484
X-link: https://github.com/facebookresearch/FBGEMM/pull/2066
Context:
Currently, we are enabling SSD optimizer offloading for the ssd tbe kernel
In this diff:
We retrieve the newly added parameters from the tbe config and pass it down to the tbe
Differential Revision: D85353134