- 09 Apr, 2021 1 commit
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Ananth Subramaniam authored
Summary: Before: this test would assume only 2 checkpoints were stored: `last.ckpt`, and `FINAL_MODEL_CKPT` Now: this test asserts that at least these 2 checkpoints are stored. In case the config specifies `save_top_k=-1` for instance, we'd save more checkpoints, causing this test to fail Since this test is only loading the last and the final outputs, I'm changing the behavior to assert that these checkpoints must be saved and ignoring other checkpoint files that could be generated. Reviewed By: kazhang Differential Revision: D27671284 fbshipit-source-id: 0419fb46856d048e7b6eba3ff1dc65b7280a9a90
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- 30 Mar, 2021 1 commit
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Sam Tsai authored
Summary: Separate unit tests into individual folder based on functionality. Reviewed By: wat3rBro Differential Revision: D27132567 fbshipit-source-id: 9a8200be530ca14c7ef42191d59795b05b9800cc
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- 24 Mar, 2021 1 commit
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Kai Zhang authored
Summary: Evaluate the predictor generated by previous step. This diff modify the lightning_train_net to reuse the evaluation logic by adding a `predictor_path` param. This diff also makes Lightning training backend depends on `cfg.MODEL.DEVICE` so that in evaluate_predictor step, user could set backend by changing model device. This is useful for evaluating int8 quantized model. Reviewed By: newstzpz Differential Revision: D27150609 fbshipit-source-id: fb72da3e81db932c0fa479350150720143e09a3e
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- 20 Mar, 2021 1 commit
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Yanghan Wang authored
Summary: Not d2go.tests is not a library for oss, move utils code to d2go.utils.testing Reviewed By: zhanghang1989 Differential Revision: D26706933 fbshipit-source-id: 85767b66bbb6c67db05e11823beb4840220b2aa3
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- 11 Mar, 2021 1 commit
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Kai Zhang authored
Summary: Pull Request resolved: https://github.com/facebookresearch/d2go/pull/17 Use PyTorch Lightning checkpoint in the test. Reviewed By: zhanghang1989 Differential Revision: D26962697 fbshipit-source-id: abe635e374c3ada130243f0eaadff34204f04fa1
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- 03 Mar, 2021 1 commit
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Kai Zhang authored
Summary: As titled. The OSS version only use PyTorch Lightning while internal version leverages some features(e.g. Manifold integration, every_n_step checkpointing). This diff splits train_net.main into smaller functions so that they could be shared across OSS and internal versions. Reviewed By: zhanghang1989 Differential Revision: D26752701 fbshipit-source-id: 7f68e2a81e78193e117517a0ff668ab14b76ea65
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