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### 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. |
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| .. | ||
| onnxjs | ||
| wasm | ||
| backend-onnxjs.ts | ||
| backend-wasm-inference.ts | ||
| backend-wasm-training.ts | ||
| backend-wasm.ts | ||
| build-def.d.ts | ||
| index.ts | ||
| version.ts | ||