Commit graph

5 commits

Author SHA1 Message Date
Yulong Wang
abdc31de40
[js] change default formatter for JavaScript/TypeScript from clang-format to Prettier (#21728)
### Description

See
454996d496
for manual changes (excluded auto-generated formatting changes)

### Why

Because the toolsets for old clang-format is out-of-date. This reduces
the development efficiency.

- The NPM package `clang-format` is already in maintenance mode. not
updated since 2 years ago.
- The VSCode extension for clang-format is not maintained for a while,
and a recent Node.js security update made it not working at all in
Windows.

No one in community seems interested in fixing those.

Choose Prettier as it is the most popular TS/JS formatter.

### How to merge

It's easy to break the build:
- Be careful of any new commits on main not included in this PR.
- Be careful that after this PR is merged, other PRs that already passed
CI can merge.

So, make sure there is no new commits before merging this one, and
invalidate js PRs that already passed CI, force them to merge to latest.
2024-08-14 16:51:22 -07:00
Xu Xing
d73131cf0f
[js/webgpu] Use DataType as uniform cpu type (#19281)
This saves turning data type to string by tensorDataTypeEnumToString.
2024-01-30 21:05:08 -08:00
Xu Xing
624b4e2063
[js/webgpu] Remove enableShapesUniforms (#19279) 2024-01-29 17:49:06 -08:00
Jiajie Hu
acba63c36a
[js/webgpu] Change A/sqrt(B) to A*inverseSqrt(B) in normalization ops (#19101)
### Description
Change `A / sqrt(B)` to `A * inverseSqrt(B)` in BatchNormalization,
InstanceNormalization, LayerNormalization and SkipLayerNormalization.

### Motivation and Context
For the same reason as the existence of the `inverseSqrt` built-in in
WebGPU spec.
2024-01-12 00:08:16 -08:00
Jiajia Qin
64dacc2892
[js/webgpu] Add BatchNormalization Op (#18468)
### Description
This PR adds `BatchNormalization` with `float` support.

Some Todos:
1. all inputs don't have same data type. For example, x/y is float16,
but bias/scale is float32 or double.
2. training mode support.

We see many models are using `BatchNormalization` ops. However, due to
the missing in jsep, all of them run on cpu, which result very poor
performance. With this PR's support, densenet-9 model becomes 20.29 ms
from 250.69 ms.
2023-11-22 15:58:06 -08:00