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| author | Laurent Mazare <laurent.mazare@gmail.com> | 2024-04-28 08:30:35 +0200 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2024-04-28 08:30:35 +0200 |
| commit | e5c8b88f90763073fc927ee232bda30fcbc05595 (patch) | |
| tree | 4abf7f650b791ce7b64c2ebe7a9f88703771bf09 /candle-nn | |
| parent | 805f3be8e1f28135b015ddebbe6c8ef3a8c53d13 (diff) | |
| download | candle-e5c8b88f90763073fc927ee232bda30fcbc05595.tar.gz candle-e5c8b88f90763073fc927ee232bda30fcbc05595.tar.bz2 candle-e5c8b88f90763073fc927ee232bda30fcbc05595.zip | |
Apply the cast before the scaling. (#2135)
Diffstat (limited to 'candle-nn')
| -rw-r--r-- | candle-nn/src/ops.rs | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/candle-nn/src/ops.rs b/candle-nn/src/ops.rs index 1dac8c3b..7fc26c3f 100644 --- a/candle-nn/src/ops.rs +++ b/candle-nn/src/ops.rs @@ -70,7 +70,7 @@ pub fn dropout(xs: &Tensor, drop_p: f32) -> Result<Tensor> { let rand = Tensor::rand(0f32, 1f32, xs.shape(), xs.device())?; let scale = 1.0 / (1.0 - drop_p as f64); let drop_p = Tensor::new(drop_p, xs.device())?.broadcast_as(xs.shape())?; - let mask = (rand.ge(&drop_p)? * scale)?.to_dtype(xs.dtype())?; + let mask = (rand.ge(&drop_p)?.to_dtype(xs.dtype())? * scale)?; xs * mask } |