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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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| .. | ||
| data/ops | ||
| e2e | ||
| unittests | ||
| op-test-schema.json | ||
| suite-test-list.jsonc | ||
| test-main.ts | ||
| test-runner.ts | ||
| test-shared.ts | ||
| test-types.ts | ||