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[PyTorch][FP8 CS] Remove the unnecessary torch reciprocal op in fp8 current scaling code path#1950

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zhongbozhu wants to merge 2 commits into from
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[PyTorch][FP8 CS] Remove the unnecessary torch reciprocal op in fp8 current scaling code path #1950

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c6efd90
remove reciprocal op
zhongbozhu Jul 14, 2025
7068321
Merge branch 'main' into zhongbo/fp8_cs_remove_reciprocal_op
yaox12 Jul 15, 2025
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5 changes: 3 additions & 2 deletions transformer_engine/pytorch/csrc/quantizer.cpp
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Original file line numberDiff line numberDiff line change
Expand Up@@ -220,8 +220,9 @@ std::pair<TensorWrapper, py::object> Float8CurrentScalingQuantizer::create_tenso
}
const py::object py_columnwise_data = create_transpose ? py::cast(columnwise_data) : py::none();

// In current scaling, scale is not known but we initialize it with 1 to avoid division by zero. If scale is already calculated, it can be correctly set.
at::Tensor scale_inv = at::reciprocal(scale);
// In current scaling, scale_inv is not known but we initialize it as an empty tensor to be filled later.
at::Tensor scale_inv =
at::empty({1}, at::TensorOptions().dtype(torch::kFloat32).device(torch::kCUDA));

py::object ret;
if (internal) {
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2 changes: 1 addition & 1 deletion transformer_engine/pytorch/tensor/float8_tensor.py
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Expand Up@@ -215,7 +215,7 @@ def __init__(
amax_epsilon: float = 0.0,
) -> None:
super().__init__(rowwise=rowwise, columnwise=columnwise)
self.scale = torch.ones(1, dtype=torch.float32, device=device)
self.scale = torch.empty(1, dtype=torch.float32, device=device)
self.amax = torch.empty(1, dtype=torch.float32, device=device)
self.dtype = fp8_dtype
self.with_amax_reduction = with_amax_reduction
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