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The 'label_smoothed_cross_entropy_with_rdrop.py' file has a bug, preventing validation.
🐛 Bug
There is a bug in the label_smoothed_cross_entropy_with_rdrop.py file that causes an abnormality in the sample, leading to an array index out-of-bounds exception during validation. Specifically, in the label_smoothed_cross_entropy_with_rdrop.py file, the RdropLabelSmoothedCrossEntropyCriterion class defines the forward propagation, where a section of the code involves copying certain fields of the sample, as follows:
if self.rdrop_alpha > 0 and sample["net_input"]["src_tokens"].size(0) == sample["target"].size(0):
sample = duplicate_input(sample)
net_output = model(**sample["net_input"])
The method duplicate_input used for copying in this context is as follows:
def duplicate_input(sample):
if "net_input" in sample.keys():
sample_input = sample["net_input"]
else:
sample_input = sample
for k, v in sample_input.items():
if isinstance(v, torch.Tensor):
sample_input[k] = torch.cat([v, v.clone()], dim=0)
if "net_input" in sample.keys():
sample["net_input"] = sample_input
else:
sample = sample_input
return sample
This piece of code essentially modifies the sample, and this modification affects the subsequent validation process (see the 'To Reproduce' section for error details). Upon reviewing the original paper 'R-Drop: Regularized Dropout for Neural Networks' and its corresponding code repository, it was found that the operation of copying certain fields of the sample in the original implementation does not use the original sample. Instead, a duplicate is created, and this duplicate is then fed into the model for forward propagation. Such an approach does not affect later validation operations.
I suggest the two parts of the code mentioned above can be modified as follows:
if self.rdrop_alpha > 0 and sample["net_input"]["src_tokens"].size(0) == sample["target"].size(0):
sample_concat_input = duplicate_sample_input(sample["net_input"])
net_output = model(**sample_concat_input)
else:
net_output = model(**sample["net_input"])
def duplicate_sample_input(sample_input):
sample_concat_input = dict()
for k, v in sample_input.items():
if k in ["src_tokens", "src_lengths", "prev_output_tokens"]:
sample_concat_input[k] = torch.cat([v, v.clone()], dim=0)
return sample_concat_input
Environment
- fairseq Version (e.g., 1.0 or main): 0.12.2
- PyTorch Version (e.g., 1.0): 1.11.0
- OS (e.g., Linux): Linux
- How you installed fairseq (
pip, source): source - Build command you used (if compiling from source):
pip install --editable . python setup.py build_ext --inplace - Python version: 3.8.0
- CUDA/cuDNN version: CUDA 11.6
To Reproduce
Steps to reproduce the behavior (always include the command you ran):
- Run cmd '....'
export CUDA_LAUNCH_BLOCKING=1
export CUDA_VISIBLE_DIVICES=0
fairseq-train ${DATA_PATH} \
-s ${SRC} -t ${TGT} \
--arch transformer_iwslt_de_en \
--share-all-embeddings \
--optimizer adam --adam-betas '(0.9,0.98)' \
--lr 0.0005 --lr-scheduler inverse_sqrt \
--max-update 250000 --warmup-updates 4000 --warmup-init-lr 1e-07 \
--criterion label_smoothed_cross_entropy_with_rdrop --label-smoothing 0.1 \
--rdrop-alpha ${RDROP_ALPHA} \
--dropout 0.3 \
--max-tokens 4096 \
--no-progress-bar \
--seed 64 \
--fp16 \
--eval-bleu \
--eval-bleu-args '{"beam": 5, "max_len_a": 1.2, "max_len_b": 10}' \
--eval-bleu-detok moses \
--eval-bleu-remove-bpe \
--best-checkpoint-metric bleu --maximize-best-checkpoint-metric \
--keep-best-checkpoints 3 --keep-last-epochs 1 \
--save-dir ${MODEL_PATH} |
tee -a ${MODEL_PATH}/train.log
- See error
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [32,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [33,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [34,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [35,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [36,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [37,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [38,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [39,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [40,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [41,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [42,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [43,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [44,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [45,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [46,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [47,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
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/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [50,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [51,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [52,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [53,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [54,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
/opt/conda/conda-bld/pytorch_1646755903507/work/aten/src/ATen/native/cuda/IndexKernel.cu:91: operator(): block: [1,0,0], thread: [55,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
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Traceback (most recent call last):
File "/home/yzh/anaconda3/envs/ps/bin/fairseq-train", line 8, in <module>
sys.exit(cli_main())
File "/sda/yzh/my_param_sharing/fairseq_cli/train.py", line 574, in cli_main
distributed_utils.call_main(cfg, main)
File "/sda/yzh/my_param_sharing/fairseq/distributed/utils.py", line 404, in call_main
main(cfg, **kwargs)
File "/sda/yzh/my_param_sharing/fairseq_cli/train.py", line 205, in main
valid_losses, should_stop = train(cfg, trainer, task, epoch_itr)
File "/home/yzh/anaconda3/envs/ps/lib/python3.8/contextlib.py", line 75, in inner
return func(*args, **kwds)
File "/sda/yzh/my_param_sharing/fairseq_cli/train.py", line 345, in train
valid_losses, should_stop = validate_and_save(
File "/sda/yzh/my_param_sharing/fairseq_cli/train.py", line 436, in validate_and_save
valid_losses = validate(cfg, trainer, task, epoch_itr, valid_subsets)
File "/sda/yzh/my_param_sharing/fairseq_cli/train.py", line 522, in validate
trainer.valid_step(sample)
File "/home/yzh/anaconda3/envs/ps/lib/python3.8/contextlib.py", line 75, in inner
return func(*args, **kwds)
File "/sda/yzh/my_param_sharing/fairseq/trainer.py", line 1168, in valid_step
raise e
File "/sda/yzh/my_param_sharing/fairseq/trainer.py", line 1152, in valid_step
_loss, sample_size, logging_output = self.task.valid_step(
File "/sda/yzh/my_param_sharing/fairseq/tasks/translation.py", line 386, in valid_step
bleu = self._inference_with_bleu(self.sequence_generator, sample, model)
File "/sda/yzh/my_param_sharing/fairseq/tasks/translation.py", line 482, in _inference_with_bleu
gen_out = self.inference_step(generator, [model], sample, prefix_tokens=None)
File "/sda/yzh/my_param_sharing/fairseq/tasks/fairseq_task.py", line 557, in inference_step
return generator.generate(
File "/home/yzh/anaconda3/envs/ps/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/sda/yzh/my_param_sharing/fairseq/sequence_generator.py", line 204, in generate
return self._generate(sample, **kwargs)
File "/sda/yzh/my_param_sharing/fairseq/sequence_generator.py", line 352, in _generate
original_batch_idxs = original_batch_idxs[batch_idxs]
RuntimeError: CUDA error: device-side assert triggered
I ran into the same problem as you, but I only ran into it in the last batch of dev. Interestingly enough, I am reporting this error in todevice in sequence_genertor. I choose to skip this batch to solve this problem