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Fix bad handling of env variable USE_TF / USE_TORCH leading to invalid framework being used.

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Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
This commit is contained in:
Morgan Funtowicz
2020-01-10 14:20:10 +01:00
committed by Lysandre Debut
parent 23c6998bf4
commit 6e6c8c52ed
1 changed files with 6 additions and 9 deletions
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15
src/transformers/file_utils.py
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@@ -4,7 +4,6 @@ This file is adapted from the AllenNLP library at https://github.com/allenai/all
Copyright by the AllenNLP authors.
"""
import fnmatch
import json
import logging
@@ -26,32 +25,31 @@ from tqdm.auto import tqdm
from . import __version__
logger = logging.getLogger(__name__) # pylint: disable=invalid-name
try:
os.environ.setdefault("USE_TORCH", "YES")
if os.environ["USE_TORCH"].upper() in ("1", "ON", "YES"):
if os.environ.get("USE_TORCH", 'AUTO').upper() in ("1", "ON", "YES", "AUTO") and \
os.environ.get("USE_TF", 'AUTO').upper() not in ("1", "ON", "YES"):
import torch
_torch_available = True # pylint: disable=invalid-name
logger.info("PyTorch version {} available.".format(torch.__version__))
else:
logger.info("USE_TORCH override through env variable, disabling PyTorch")
logger.info("Disabling PyTorch because USE_TF is set")
_torch_available = False
except ImportError:
_torch_available = False # pylint: disable=invalid-name
try:
os.environ.setdefault("USE_TF", "YES")
if os.environ["USE_TF"].upper() in ("1", "ON", "YES"):
if os.environ.get("USE_TF", 'AUTO').upper() in ("1", "ON", "YES", "AUTO") and \
os.environ.get("USE_TORCH", 'AUTO').upper() not in ("1", "ON", "YES"):
import tensorflow as tf
assert hasattr(tf, "__version__") and int(tf.__version__[0]) >= 2
_tf_available = True # pylint: disable=invalid-name
logger.info("TensorFlow version {} available.".format(tf.__version__))
else:
logger.info("USE_TF override through env variable, disabling Tensorflow")
logger.info("Disabling Tensorflow because USE_TORCH is set")
_tf_available = False
except (ImportError, AssertionError):
_tf_available = False # pylint: disable=invalid-name
@@ -66,7 +64,6 @@ except ImportError:
)
default_cache_path = os.path.join(torch_cache_home, "transformers")
try:
from pathlib import Path