Centralize logging (#6434)

* Logging

* Style

* hf_logging > utils.logging

* Address @thomwolf's comments

* Update test

* Update src/transformers/benchmark/benchmark_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Revert bad change
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

src/transformers/data/processors/xnli.py

@@ -16,13 +16,13 @@
 """ XNLI utils (dataset loading and evaluation) """
 
 
-import logging
 import os
 
+from ...utils import logging
 from .utils import DataProcessor, InputExample
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 
 class XnliProcessor(DataProcessor):

src/transformers/file_utils.py

@@ -6,7 +6,6 @@ Copyright by the AllenNLP authors.
 
 import fnmatch
 import json
-import logging
 import os
 import re
 import shutil
@@ -30,9 +29,10 @@ import requests
 from filelock import FileLock
 
 from . import __version__
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
+logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
 
 try:
     USE_TF = os.environ.get("USE_TF", "AUTO").upper()
@@ -757,7 +757,7 @@ def http_get(url, temp_file, proxies=None, resume_size=0, user_agent: Union[Dict
         total=total,
         initial=resume_size,
         desc="Downloading",
-        disable=bool(logger.getEffectiveLevel() == logging.NOTSET),
+        disable=bool(logging.get_verbosity() > logging.NOTSET),
     )
     for chunk in response.iter_content(chunk_size=1024):
         if chunk:  # filter out keep-alive new chunks

src/transformers/generation_tf_utils.py

@@ -14,13 +14,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
-
 import numpy as np
 import tensorflow as tf
 
+from .utils import logging
+
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 
 class TFGenerationMixin:

src/transformers/generation_utils.py

@@ -14,15 +14,16 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
 from typing import Iterable, List, Optional, Tuple
 
 import torch
 from torch import Tensor
 from torch.nn import functional as F
 
+from .utils import logging
 
-logger = logging.getLogger(__name__)
+
+logger = logging.get_logger(__name__)
 
 
 class GenerationMixin:

src/transformers/modelcard.py

@@ -17,7 +17,6 @@
 
 import copy
 import json
-import logging
 import os
 
 from .configuration_auto import ALL_PRETRAINED_CONFIG_ARCHIVE_MAP
@@ -30,9 +29,10 @@ from .file_utils import (
     hf_bucket_url,
     is_remote_url,
 )
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 
 class ModelCard:

src/transformers/modeling_albert.py

@@ -14,7 +14,6 @@
 # limitations under the License.
 """PyTorch ALBERT model. """
 
-import logging
 import math
 import os
 import warnings
@@ -44,9 +43,10 @@ from .modeling_outputs import (
     TokenClassifierOutput,
 )
 from .modeling_utils import PreTrainedModel, apply_chunking_to_forward, find_pruneable_heads_and_indices
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "AlbertConfig"
 _TOKENIZER_FOR_DOC = "AlbertTokenizer"

src/transformers/modeling_auto.py

@@ -15,7 +15,6 @@
 """ Auto Model class. """
 
 
-import logging
 import warnings
 from collections import OrderedDict
 
@@ -172,9 +171,10 @@ from .modeling_xlnet import (
     XLNetLMHeadModel,
     XLNetModel,
 )
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 
 MODEL_MAPPING = OrderedDict(

src/transformers/modeling_bart.py

@@ -13,7 +13,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """PyTorch BART model, ported from the fairseq repo."""
-import logging
 import math
 import random
 import warnings
@@ -43,9 +42,10 @@ from .modeling_outputs import (
     Seq2SeqSequenceClassifierOutput,
 )
 from .modeling_utils import PreTrainedModel
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "BartConfig"
 _TOKENIZER_FOR_DOC = "BartTokenizer"

src/transformers/modeling_bert.py

@@ -16,7 +16,6 @@
 """PyTorch BERT model. """
 
 
-import logging
 import math
 import os
 import warnings
@@ -54,9 +53,10 @@ from .modeling_utils import (
     find_pruneable_heads_and_indices,
     prune_linear_layer,
 )
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "BertConfig"
 _TOKENIZER_FOR_DOC = "BertTokenizer"

src/transformers/modeling_camembert.py

@@ -15,8 +15,6 @@
 # limitations under the License.
 """PyTorch CamemBERT model. """
 
-import logging
-
 from .configuration_camembert import CamembertConfig
 from .file_utils import add_start_docstrings
 from .modeling_roberta import (
@@ -28,9 +26,10 @@ from .modeling_roberta import (
     RobertaForTokenClassification,
     RobertaModel,
 )
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 _TOKENIZER_FOR_DOC = "CamembertTokenizer"
 

src/transformers/modeling_ctrl.py

@@ -16,7 +16,6 @@
 """ PyTorch CTRL model."""
 
 
-import logging
 import warnings
 
 import numpy as np
@@ -28,9 +27,10 @@ from .configuration_ctrl import CTRLConfig
 from .file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_callable
 from .modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast
 from .modeling_utils import Conv1D, PreTrainedModel, find_pruneable_heads_and_indices, prune_linear_layer
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "CTRLConfig"
 _TOKENIZER_FOR_DOC = "CTRLTokenizer"

src/transformers/modeling_distilbert.py

@@ -19,7 +19,6 @@
 
 
 import copy
-import logging
 import math
 import warnings
 
@@ -50,9 +49,10 @@ from .modeling_utils import (
     find_pruneable_heads_and_indices,
     prune_linear_layer,
 )
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "DistilBertConfig"
 _TOKENIZER_FOR_DOC = "DistilBertTokenizer"

src/transformers/modeling_dpr.py

@@ -15,7 +15,6 @@
 """ PyTorch DPR model for Open Domain Question Answering."""
 
 
-import logging
 from dataclasses import dataclass
 from typing import Optional, Tuple, Union
 
@@ -27,9 +26,10 @@ from .file_utils import ModelOutput, add_start_docstrings, add_start_docstrings_
 from .modeling_bert import BertModel
 from .modeling_outputs import BaseModelOutputWithPooling
 from .modeling_utils import PreTrainedModel
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "DPRConfig"
 

src/transformers/modeling_electra.py

-import logging
 import os
 import warnings
 from dataclasses import dataclass
@@ -27,9 +26,10 @@ from .modeling_outputs import (
     TokenClassifierOutput,
 )
 from .modeling_utils import SequenceSummary
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "ElectraConfig"
 _TOKENIZER_FOR_DOC = "ElectraTokenizer"

src/transformers/modeling_encoder_decoder.py

@@ -15,15 +15,15 @@
 """ Classes to support Encoder-Decoder architectures """
 
 
-import logging
 from typing import Optional
 
 from .configuration_encoder_decoder import EncoderDecoderConfig
 from .configuration_utils import PretrainedConfig
 from .modeling_utils import PreTrainedModel
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 
 class EncoderDecoderModel(PreTrainedModel):

src/transformers/modeling_flaubert.py

@@ -15,7 +15,6 @@
 """ PyTorch Flaubert model, based on XLM. """
 
 
-import logging
 import random
 
 import torch
@@ -34,9 +33,10 @@ from .modeling_xlm import (
     XLMWithLMHeadModel,
     get_masks,
 )
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "FlaubertConfig"
 _TOKENIZER_FOR_DOC = "FlaubertTokenizer"

src/transformers/modeling_gpt2.py

@@ -16,7 +16,6 @@
 """PyTorch OpenAI GPT-2 model."""
 
 
-import logging
 import os
 import warnings
 from dataclasses import dataclass
@@ -43,9 +42,10 @@ from .modeling_utils import (
     find_pruneable_heads_and_indices,
     prune_conv1d_layer,
 )
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "GPT2Config"
 _TOKENIZER_FOR_DOC = "GPT2Tokenizer"

src/transformers/modeling_longformer.py

@@ -14,7 +14,6 @@
 # limitations under the License.
 """PyTorch Longformer model. """
 
-import logging
 import math
 import warnings
 
@@ -47,9 +46,10 @@ from .modeling_utils import (
     find_pruneable_heads_and_indices,
     prune_linear_layer,
 )
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "LongformerConfig"
 _TOKENIZER_FOR_DOC = "LongformerTokenizer"

src/transformers/modeling_mmbt.py

@@ -16,8 +16,6 @@
 """PyTorch MMBT model. """
 
 
-import logging
-
 import torch
 import torch.nn as nn
 from torch.nn import CrossEntropyLoss, MSELoss
@@ -25,9 +23,10 @@ from torch.nn import CrossEntropyLoss, MSELoss
 from .file_utils import add_start_docstrings, add_start_docstrings_to_callable, replace_return_docstrings
 from .modeling_outputs import BaseModelOutputWithPooling, SequenceClassifierOutput
 from .modeling_utils import ModuleUtilsMixin
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "MMBTConfig"
 

src/transformers/modeling_mobilebert.py

@@ -20,7 +20,6 @@
 # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 # SOFTWARE.
 
-import logging
 import math
 import os
 import warnings
@@ -53,9 +52,10 @@ from .modeling_outputs import (
     TokenClassifierOutput,
 )
 from .modeling_utils import PreTrainedModel, find_pruneable_heads_and_indices, prune_linear_layer
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "MobileBertConfig"
 _TOKENIZER_FOR_DOC = "MobileBertTokenizer"