pengwa 3e954da3e6 Fix and enable few ORTModule Unit Tests (#19847) ... ### Fix and enable few ORTModule Unit Tests Fix 'test_bert_inputs_with_dynamic_shape' and 'test_bert_result_with_layerwise_recompute' generate Nan loss in ORT run. The root cause is, the logic to generatic attention mask test data is not correct, only 0 or 1 is allowed in the dataset, but we see lots of other numbers. ( The reason we don't have this using old version of transformers for example v4.4.2 or 4.16.2 is because they don't contains such d3cb28886a, which increase the scaling to a bigger number, causing a overflow to inf) Another improvement during the investigation using convergence tools: Don't dump the activations during model export phase, otherwise, the dumped data might contains some PyTorch run's result making us confused during comparing with stock PyTorch run results. ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. -->		2024-03-12 10:49:19 +08:00
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orttraining	Fix and enable few ORTModule Unit Tests (#19847)	2024-03-12 10:49:19 +08:00
tools	Bump ruff linter to 0.2.1 (#19471)	2024-02-08 16:08:27 -08:00