GitLab

Summary:
Currently, the exporter method takes in a compare_accuracy parameter, which after all the compute (exporting etc.) raises an exception if it is set to True.

This looks like an antipattern, and causes a waste of compute.

Therefore, I am proposing to raise the exception at the very beginning of method call to let the client know in advance that this argument's functionality isn't implemented yet.

NOTE: We might also choose to get rid of the entire parameter. I am open for suggestions.

Differential Revision: D34186578

fbshipit-source-id: d7fbe7589dfe2d2f688b870885ca61e6829c9329

Summary: make it an option

Differential Revision: D32601981

fbshipit-source-id: 308a0c49939531d840914aa8e256aae6db463929

Differential Revision: D30973518

fbshipit-source-id: fbdfb862ab23d5141553499471f92d2218addf91

Summary:
Added predictor_type `boltnn_int8` to export to BoltNN via torch delegate.

- `int8` needs to be in the name, otherwise the post-train quantization won't happen;

```
cfg.QUANTIZATION.BACKEND = "qnnpack"
// cfg.QUANTIZATION.CUSTOM_QSCHEME = "per_tensor_affine"
```

Seems that ` QUANTIZATION.CUSTOM_QSCHEME per_tensor_affine` is not needed - likely covered by "qnnpack".

Reviewed By: wat3rBro

Differential Revision: D29106043

fbshipit-source-id: 865ac5af86919fe7b4530b48433a1bd11e295bf4

Summary: Use all training dataset for export instead of just first. This is to support use cases where there is only a small amount of images per jsons but a number of jsons. Since calibration uses the first dataset, it is limited by the number of images in a single dataset.

Reviewed By: ppwwyyxx

Differential Revision: D28902673

fbshipit-source-id: f80146b02d2d1bc04703fbb21ef410f5e26ba64c

Differential Revision:
D27881742 (https://github.com/facebookresearch/d2go/commit/90aff5daf608473dd312b300db8615326fa40a37)

Original commit changeset: 34a3ab7a88f4

fbshipit-source-id: 42c03b4f2b69c656b26774a4665b84b832262650

Summary:
- Enable sdk inference config specification in export step. This enables adding the sdk configuration as part of model file in the export step. The sdk config can be specified as infernece_config.yaml and is zipped together with torchscript model. The main goal of sdk configuration is to control the model inference behavior with model.
- SDK inference config design doc: https://docs.google.com/document/d/1j5qx8IrnFg1DJFzTnu4W8WmXFYJ-AgCDfSQHb2ACJsk/edit
- One click fblearner pipeline is in next diff on the stack

Differential Revision: D27881742

fbshipit-source-id: 34a3ab7a88f456b74841cf671ea1b3f678cdb733

Summary:
Fix typos in exporter

Pull Request resolved: https://github.com/facebookresearch/d2go/pull/45

Reviewed By: wat3rBro

Differential Revision: D27779963

Pulled By: zhanghang1989

fbshipit-source-id: bcf7922afe6d4cccc074615069538eb5a6098b98

Summary:
Change depoyment to deployment in README.md.
Change datasest to datasets in tools/exporter.py.

Pull Request resolved: https://github.com/facebookresearch/d2go/pull/7

Reviewed By: newstzpz

Differential Revision: D26821039

Pulled By: zhanghang1989

fbshipit-source-id: 5056d15c877c4b3d771d33267139e73f1527da21

fbshipit-source-id: f4a8ba78691d8cf46e003ef0bd2e95f170932778