def test_examples(self):
# the main functionality is tested in `test_core`, this is just the hint check
try:
require_version_examples("numpy>1000.4.5")
except ImportError as e:
self.assertIn("is required", str(e))
self.assertIn("pip install -r examples/requirements.txt", str(e))
AutoTokenizer,
PretrainedConfig,
PreTrainedTokenizer,
)
from transformers.optimization import (
Adafactor,
get_cosine_schedule_with_warmup,
get_cosine_with_hard_restarts_schedule_with_warmup,
get_linear_schedule_with_warmup,
get_polynomial_decay_schedule_with_warmup,
)
from transformers.utils.versions import require_version_examples
logger = logging.getLogger(__name__)
require_version_examples("pytorch_lightning>=1.0.4")
MODEL_MODES = {
"base": AutoModel,
"sequence-classification": AutoModelForSequenceClassification,
"question-answering": AutoModelForQuestionAnswering,
"pretraining": AutoModelForPreTraining,
"token-classification": AutoModelForTokenClassification,
"language-modeling": AutoModelWithLMHead,
"summarization": AutoModelForSeq2SeqLM,
"translation": AutoModelForSeq2SeqLM,
}
# update this and the import above to support new schedulers from transformers.optimization
arg_to_scheduler = {
"linear": get_linear_schedule_with_warmup,