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Add a Context trait similar to anyhow::Context. (#2676)

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* Add a Context trait similar to anyhow::Context.

* Switch two unwrap to context.
This commit is contained in:
Laurent Mazare
2024-12-22 09:18:13 +01:00
committed by GitHub
parent 5c2f893e5a
commit 62ced44ea9
13 changed files with 97 additions and 41 deletions
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4
candle-transformers/src/models/fastvit.rs
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@ -5,7 +5,7 @@
//!
//! Implementation based on [timm model](https://github.com/huggingface/pytorch-image-models/blob/main/timm/models/fastvit.py)
use candle::{DType, Result, Tensor, D};
use candle::{Context, DType, Result, Tensor, D};
use candle_nn::{
batch_norm, conv2d, conv2d_no_bias, linear, linear_no_bias, ops::sigmoid, ops::softmax,
BatchNorm, Conv2d, Conv2dConfig, Func, VarBuilder,
@ -178,7 +178,7 @@ fn squeeze_and_excitation(
// based on the _fuse_bn_tensor method in timm
// see https://github.com/huggingface/pytorch-image-models/blob/main/timm/models/byobnet.py#L602
fn fuse_conv_bn(weights: &Tensor, bn: BatchNorm) -> Result<(Tensor, Tensor)> {
let (gamma, beta) = bn.weight_and_bias().unwrap();
let (gamma, beta) = bn.weight_and_bias().context("no weight-bias")?;
let mu = bn.running_mean();
let sigma = (bn.running_var() + bn.eps())?.sqrt();
let gps = (gamma / sigma)?;