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Fix a couple typos (#1451)

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* Mixtral quantized instruct.

* Fix a couple typos.
This commit is contained in:
Laurent Mazare
2023-12-17 05:20:05 -06:00
committed by GitHub
parent c630622a07
commit 1e86717bf2
24 changed files with 44 additions and 42 deletions
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2
candle-transformers/src/models/segment_anything/mask_decoder.rs
View File

@ -182,7 +182,7 @@ impl MaskDecoder {
sparse_prompt_embeddings: &Tensor,
dense_prompt_embeddings: &Tensor,
) -> Result<(Tensor, Tensor)> {
// Concatenate ouput tokens.
// Concatenate output tokens.
let output_tokens = Tensor::cat(
&[self.iou_token.embeddings(), self.mask_tokens.embeddings()],
0,

8
candle-transformers/src/models/segment_anything/prompt_encoder.rs
View File

@ -2,11 +2,11 @@ use candle::{DType, IndexOp, Result, Tensor, D};
use candle_nn::VarBuilder;
#[derive(Debug)]
struct PostionEmbeddingRandom {
struct PositionEmbeddingRandom {
positional_encoding_gaussian_matrix: Tensor,
}
impl PostionEmbeddingRandom {
impl PositionEmbeddingRandom {
fn new(num_pos_feats: usize, vb: VarBuilder) -> Result<Self> {
let positional_encoding_gaussian_matrix =
vb.get((2, num_pos_feats), "positional_encoding_gaussian_matrix")?;
@ -52,7 +52,7 @@ impl PostionEmbeddingRandom {
#[derive(Debug)]
pub struct PromptEncoder {
pe_layer: PostionEmbeddingRandom,
pe_layer: PositionEmbeddingRandom,
point_embeddings: Vec<candle_nn::Embedding>,
not_a_point_embed: candle_nn::Embedding,
mask_downscaling_conv1: candle_nn::Conv2d,
@ -76,7 +76,7 @@ impl PromptEncoder {
vb: VarBuilder,
) -> Result<Self> {
let num_points_embeddings = 4;
let pe_layer = PostionEmbeddingRandom::new(embed_dim / 2, vb.pp("pe_layer"))?;
let pe_layer = PositionEmbeddingRandom::new(embed_dim / 2, vb.pp("pe_layer"))?;
let not_a_point_embed = candle_nn::embedding(1, embed_dim, vb.pp("not_a_point_embed"))?;
let no_mask_embed = candle_nn::embedding(1, embed_dim, vb.pp("no_mask_embed"))?;
let cfg = candle_nn::Conv2dConfig {

4
candle-transformers/src/models/stable_diffusion/euler_ancestral_discrete.rs
View File

@ -1,6 +1,6 @@
//! Ancestral sampling with Euler method steps.
//!
//! Reference implemenation in Rust:
//! Reference implementation in Rust:
//!
//! https://github.com/pykeio/diffusers/blob/250b9ad1898af41e76a74c0d8d4292652823338a/src/schedulers/euler_ancestral_discrete.rs
//!
@ -135,7 +135,7 @@ impl EulerAncestralDiscreteScheduler {
);
sigmas_int.push(0.0);
// standard deviation of the inital noise distribution
// standard deviation of the initial noise distribution
// f64 does not implement Ord such that there is no `max`, so we need to use this workaround
let init_noise_sigma = *sigmas_int
.iter()