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a1cf9f3390
Fixed 2 issues regarding `tests/trainer/test_data_collator.py::TFDataCollatorIntegrationTest::test_all_mask_replacement`: 1. I got the error `RuntimeError: "bernoulli_tensor_cpu_p_" not implemented for 'Long'`. This is because the `mask_replacement_prob=1` and `torch.bernoulli` doesn't accept this type (which would be a `torch.long` dtype instead. I fixed this by manually casting the probability arguments in the `__post_init__` function of `DataCollatorForLanguageModeling`. 2. I also got the error `tensorflow.python.framework.errors_impl.InvalidArgumentError: cannot compute Equal as input #1(zero-based) was expected to be a int64 tensor but is a int32 tensor [Op:Equal]` due to the line `tf.reduce_all((batch["input_ids"] == inputs) | (batch["input_ids"] == tokenizer.mask_token_id))` in `test_data_collator.py`. This occurs because the type of the `inputs` variable is `tf.int32`. Solved this by manually casting it to `tf.int64` in the test, as the expected return type of `batch["input_ids"]` is `tf.int64`. |
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| .. | ||
| agents | ||
| bettertransformer | ||
| deepspeed | ||
| extended | ||
| fixtures | ||
| fsdp | ||
| generation | ||
| models | ||
| optimization | ||
| peft_integration | ||
| pipelines | ||
| quantization | ||
| repo_utils | ||
| sagemaker | ||
| tokenization | ||
| tp | ||
| trainer | ||
| utils | ||
| __init__.py | ||
| test_backbone_common.py | ||
| test_configuration_common.py | ||
| test_feature_extraction_common.py | ||
| test_image_processing_common.py | ||
| test_image_transforms.py | ||
| test_modeling_common.py | ||
| test_modeling_flax_common.py | ||
| test_modeling_tf_common.py | ||
| test_pipeline_mixin.py | ||
| test_processing_common.py | ||
| test_sequence_feature_extraction_common.py | ||
| test_tokenization_common.py | ||
| test_training_args.py | ||