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/__init__.py

@@ -17,8 +17,6 @@ else:
     absl.logging.set_stderrthreshold("info")
     absl.logging._warn_preinit_stderr = False
 
-import logging
-
 # Configurations
 from .configuration_albert import ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, AlbertConfig
 from .configuration_auto import ALL_PRETRAINED_CONFIG_ARCHIVE_MAP, CONFIG_MAPPING, AutoConfig
@@ -184,9 +182,10 @@ from .tokenization_xlnet import SPIECE_UNDERLINE, XLNetTokenizer
 from .trainer_utils import EvalPrediction, set_seed
 from .training_args import TrainingArguments
 from .training_args_tf import TFTrainingArguments
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
+logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
 
 
 if is_sklearn_available():

src/transformers/activations.py

-import logging
 import math
 
 import torch
 import torch.nn.functional as F
 
+from .utils import logging
 
-logger = logging.getLogger(__name__)
+
+logger = logging.get_logger(__name__)
 
 
 def swish(x):

src/transformers/benchmark/benchmark.py

@@ -18,13 +18,13 @@
 """
 
 
-import logging
 import timeit
 from typing import Callable, Optional
 
 from ..configuration_utils import PretrainedConfig
 from ..file_utils import is_py3nvml_available, is_torch_available
 from ..modeling_auto import MODEL_MAPPING, MODEL_WITH_LM_HEAD_MAPPING
+from ..utils import logging
 from .benchmark_utils import (
     Benchmark,
     Memory,
@@ -45,7 +45,7 @@ if is_py3nvml_available():
     import py3nvml.py3nvml as nvml
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 
 class PyTorchBenchmark(Benchmark):

src/transformers/benchmark/benchmark_args.py

@@ -14,11 +14,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
 from dataclasses import dataclass, field
 from typing import Tuple
 
 from ..file_utils import cached_property, is_torch_available, is_torch_tpu_available, torch_required
+from ..utils import logging
 from .benchmark_args_utils import BenchmarkArguments
 
 
@@ -29,7 +29,7 @@ if is_torch_tpu_available():
     import torch_xla.core.xla_model as xm
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 
 @dataclass

src/transformers/benchmark/benchmark_args_tf.py

@@ -14,11 +14,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
 from dataclasses import dataclass, field
 from typing import Tuple
 
 from ..file_utils import cached_property, is_tf_available, tf_required
+from ..utils import logging
 from .benchmark_args_utils import BenchmarkArguments
 
 
@@ -26,7 +26,7 @@ if is_tf_available():
     import tensorflow as tf
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 
 @dataclass

src/transformers/benchmark/benchmark_args_utils.py

@@ -16,13 +16,14 @@
 
 import dataclasses
 import json
-import logging
 from dataclasses import dataclass, field
 from time import time
 from typing import List
 
+from ..utils import logging
 
-logger = logging.getLogger(__name__)
+
+logger = logging.get_logger(__name__)
 
 
 def list_field(default=None, metadata=None):

src/transformers/benchmark/benchmark_tf.py

@@ -18,7 +18,6 @@
 """
 
 
-import logging
 import random
 import timeit
 from functools import wraps
@@ -27,6 +26,7 @@ from typing import Callable, Optional
 from ..configuration_utils import PretrainedConfig
 from ..file_utils import is_py3nvml_available, is_tf_available
 from ..modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
+from ..utils import logging
 from .benchmark_utils import (
     Benchmark,
     Memory,
@@ -46,7 +46,7 @@ if is_tf_available():
 if is_py3nvml_available():
     import py3nvml.py3nvml as nvml
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 
 def run_with_tf_optimizations(do_eager_mode: bool, use_xla: bool):

src/transformers/benchmark/benchmark_utils.py

@@ -7,7 +7,6 @@ Copyright by the AllenNLP authors.
 import copy
 import csv
 import linecache
-import logging
 import os
 import platform
 import sys
@@ -22,6 +21,7 @@ from transformers import AutoConfig, PretrainedConfig
 from transformers import __version__ as version
 
 from ..file_utils import is_psutil_available, is_py3nvml_available, is_tf_available, is_torch_available
+from ..utils import logging
 from .benchmark_args_utils import BenchmarkArguments
 
 
@@ -43,7 +43,7 @@ else:
     from signal import SIGKILL
 
 
-logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
+logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
 
 
 _is_memory_tracing_enabled = False
@@ -94,7 +94,7 @@ def separate_process_wrapper_fn(func: Callable[[], None], do_multi_processing: b
         return result
 
     if do_multi_processing:
-        logging.info("fFunction {func} is executed in its own process...")
+        logger.info(f"Function {func} is executed in its own process...")
         return multi_process_func
     else:
         return func

src/transformers/commands/convert.py

 from argparse import ArgumentParser, Namespace
-from logging import getLogger
 
 from transformers.commands import BaseTransformersCLICommand
 
+from ..utils import logging
+
 
 def convert_command_factory(args: Namespace):
     """
@@ -52,7 +53,7 @@ class ConvertCommand(BaseTransformersCLICommand):
         finetuning_task_name: str,
         *args
     ):
-        self._logger = getLogger("transformers-cli/converting")
+        self._logger = logging.get_logger("transformers-cli/converting")
 
         self._logger.info("Loading model {}".format(model_type))
         self._model_type = model_type

src/transformers/commands/run.py

-import logging
 from argparse import ArgumentParser
 
 from transformers.commands import BaseTransformersCLICommand
 from transformers.pipelines import SUPPORTED_TASKS, Pipeline, PipelineDataFormat, pipeline
 
+from ..utils import logging
 
-logger = logging.getLogger(__name__)  # pylint: disable=invalid-name
+
+logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
 
 
 def try_infer_format_from_ext(path: str):

src/transformers/commands/serving.py

-import logging
 from argparse import ArgumentParser, Namespace
 from typing import Any, List, Optional
 
@@ -6,6 +5,8 @@ from transformers import Pipeline
 from transformers.commands import BaseTransformersCLICommand
 from transformers.pipelines import SUPPORTED_TASKS, pipeline
 
+from ..utils import logging
+
 
 try:
     from fastapi import Body, FastAPI, HTTPException

src/transformers/commands/train.py

 import os
 from argparse import ArgumentParser, Namespace
-from logging import getLogger
 
 from transformers import SingleSentenceClassificationProcessor as Processor
 from transformers import TextClassificationPipeline, is_tf_available, is_torch_available
 from transformers.commands import BaseTransformersCLICommand
 
+from ..utils import logging
+
 
 if not is_tf_available() and not is_torch_available():
     raise RuntimeError("At least one of PyTorch or TensorFlow 2.0+ should be installed to use CLI training")
@@ -76,7 +77,7 @@ class TrainCommand(BaseTransformersCLICommand):
         train_parser.set_defaults(func=train_command_factory)
 
     def __init__(self, args: Namespace):
-        self.logger = getLogger("transformers-cli/training")
+        self.logger = logging.get_logger("transformers-cli/training")
 
         self.framework = "tf" if is_tf_available() else "torch"
 

src/transformers/configuration_auto.py

@@ -15,7 +15,6 @@
 """ Auto Config class. """
 
 
-import logging
 from collections import OrderedDict
 
 from .configuration_albert import ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, AlbertConfig
@@ -45,9 +44,6 @@ from .configuration_xlm_roberta import XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP
 from .configuration_xlnet import XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLNetConfig
 
 
-logger = logging.getLogger(__name__)
-
-
 ALL_PRETRAINED_CONFIG_ARCHIVE_MAP = dict(
     (key, value)
     for pretrained_map in [

src/transformers/configuration_bart.py

@@ -14,14 +14,12 @@
 # limitations under the License.
 """ BART configuration """
 
-
-import logging
-
 from .configuration_utils import PretrainedConfig
 from .file_utils import add_start_docstrings_to_callable
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 BART_PRETRAINED_CONFIG_ARCHIVE_MAP = {
     "facebook/bart-base": "https://s3.amazonaws.com/models.huggingface.co/bert/facebook/bart-base/config.json",

src/transformers/configuration_bert.py

@@ -15,13 +15,11 @@
 # limitations under the License.
 """ BERT model configuration """
 
-
-import logging
-
 from .configuration_utils import PretrainedConfig
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 BERT_PRETRAINED_CONFIG_ARCHIVE_MAP = {
     "bert-base-uncased": "https://s3.amazonaws.com/models.huggingface.co/bert/bert-base-uncased-config.json",

src/transformers/configuration_camembert.py

@@ -15,13 +15,11 @@
 # limitations under the License.
 """ CamemBERT configuration """
 
-
-import logging
-
 from .configuration_roberta import RobertaConfig
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP = {
     "camembert-base": "https://s3.amazonaws.com/models.huggingface.co/bert/camembert-base-config.json",

src/transformers/configuration_ctrl.py

@@ -14,13 +14,11 @@
 # limitations under the License.
 """ Salesforce CTRL configuration """
 
-
-import logging
-
 from .configuration_utils import PretrainedConfig
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP = {"ctrl": "https://s3.amazonaws.com/models.huggingface.co/bert/ctrl-config.json"}
 

src/transformers/configuration_distilbert.py

@@ -14,13 +14,11 @@
 # limitations under the License.
 """ DistilBERT model configuration """
 
-
-import logging
-
 from .configuration_utils import PretrainedConfig
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP = {
     "distilbert-base-uncased": "https://s3.amazonaws.com/models.huggingface.co/bert/distilbert-base-uncased-config.json",

src/transformers/configuration_dpr.py

@@ -14,13 +14,11 @@
 # limitations under the License.
 """ DPR model configuration """
 
-
-import logging
-
 from .configuration_bert import BertConfig
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 DPR_PRETRAINED_CONFIG_ARCHIVE_MAP = {
     "facebook/dpr-ctx_encoder-single-nq-base": "https://s3.amazonaws.com/models.huggingface.co/bert/facebook/dpr-ctx_encoder-single-nq-base/config.json",

src/transformers/configuration_electra.py

@@ -15,13 +15,11 @@
 # limitations under the License.
 """ ELECTRA model configuration """
 
-
-import logging
-
 from .configuration_utils import PretrainedConfig
+from .utils import logging
 
 
-logger = logging.getLogger(__name__)
+logger = logging.get_logger(__name__)
 
 ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP = {
     "google/electra-small-generator": "https://s3.amazonaws.com/models.huggingface.co/bert/google/electra-small-generator/config.json",