Comments (3)
Thanks for your attention to our work!
- The datatype of the first moment is fp8-e4m3, and that of the second one is fp16. They are both scaling tensors with scaling factors,which are computed just in time.
- The weight gradient is a fp8-e4m3 scaling tensor with a just-in-time scaling factor.
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Thank you for your answer.
So, why is the reason you define the first moment as uint8 datatype :
from ms-amp.
Thank you for your answer. So, why is the reason you define the first moment as uint8 datatype :
There is no native FP8 datatype in PyTorch yet, therefore we use uint8 to store FP8-E4M3 value.
from ms-amp.
Related Issues (20)
- Huggingface Accelerate Support HOT 2
- Please update obsolete dependencies HOT 7
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- Support for latest Megatron-LM and transformer-engine 1.0 + HOT 2
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- Is MS-AMP reproducing the FP8-LM paper's results? HOT 2
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- Optimizer compilation fails with PyTorch 2.2 HOT 1
- [Question] How to apply MS-AMP to only part of the model? HOT 2
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- Is activation checkpointing used for Table 5 from the FP8-LM paper? HOT 1
- MNIST single GPU example: GradScaler AssertionError
- how can i export the model from pytorch to onnx? HOT 1
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- Why does using msamp decrease throughput HOT 4
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