fix logger

deepspeech/__init__.py

@@ -11,7 +11,6 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-import logging
 from typing import Union
 from typing import List
 from typing import Tuple
@@ -23,30 +22,11 @@ from paddle.nn import functional as F
 #TODO(Hui Zhang): remove  fluid import
 from paddle.fluid import core
 
-root = logging.getLogger()
-root.setLevel(logging.DEBUG)
-
-format = '[%(levelname)s %(asctime)s %(filename)s:%(lineno)d] %(message)s'
-formatter = logging.Formatter(fmt=format, datefmt='%Y/%m/%d %H:%M:%S')
-
-stream_handler = logging.StreamHandler()
-stream_handler.setLevel(logging.INFO)
-stream_handler.setFormatter(formatter)
-root.addHandler(stream_handler)
-save_path = 'global.log'
-file_handler = logging.FileHandler(save_path)
-file_handler.setLevel(logging.DEBUG)
-file_handler.setFormatter(formatter)
-root.addHandler(file_handler)
-
-# stop propagate for propagating may print
-# log multiple times
-root.propagate = False
-
-logger = logging.getLogger(__name__)
+from deepspeech.utils.log import Log
+logger = Log(__name__).getlog()
 
 ########### hcak logging #############
-logger.warn = logging.warning
+logger.warn = logger.warning
 
 ########### hcak paddle #############
 paddle.bool = 'bool'

deepspeech/exps/deepspeech2/model.py

@@ -14,7 +14,7 @@
 """Contains DeepSpeech2 model."""
 
 import time
-import logging
+from deepspeech.utils.log import Log
 import numpy as np
 from collections import defaultdict
 from pathlib import Path
@@ -38,7 +38,7 @@ from deepspeech.io.dataset import ManifestDataset
 from deepspeech.models.deepspeech2 import DeepSpeech2Model
 from deepspeech.models.deepspeech2 import DeepSpeech2InferModel
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 
 class DeepSpeech2Trainer(Trainer):

deepspeech/exps/u2/model.py

@@ -15,7 +15,7 @@
 
 import sys
 import time
-import logging
+from deepspeech.utils.log import Log
 import numpy as np
 from collections import defaultdict
 from pathlib import Path
@@ -41,7 +41,7 @@ from deepspeech.io.dataset import ManifestDataset
 
 from deepspeech.models.u2 import U2Model
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 
 class U2Trainer(Trainer):

deepspeech/frontend/augmentor/spec_augment.py

@@ -12,12 +12,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """Contains the volume perturb augmentation model."""
-import logging
+from deepspeech.utils.log import Log
 import numpy as np
 
 from deepspeech.frontend.augmentor.base import AugmentorBase
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 
 class SpecAugmentor(AugmentorBase):

deepspeech/frontend/utility.py

@@ -16,9 +16,9 @@ import numpy as np
 import math
 import json
 import codecs
-import logging
+from deepspeech.utils.log import Log
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = [
     "load_cmvn", "read_manifest", "rms_to_db", "rms_to_dbfs", "max_dbfs",

deepspeech/io/collator.py

@@ -12,16 +12,16 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
+from deepspeech.utils.log import Log
 import numpy as np
 
 from deepspeech.io.utility import pad_sequence
 from deepspeech.frontend.utility import IGNORE_ID
 
-logger = logging.getLogger(__name__)
-
 __all__ = ["SpeechCollator"]
 
+logger = Log(__name__).getlog()
+
 
 class SpeechCollator():
     def __init__(self, keep_transcription_text=True):

deepspeech/io/dataset.py

@@ -16,7 +16,7 @@ import time
 import io
 import random
 import tarfile
-import logging
+from deepspeech.utils.log import Log
 from typing import Optional
 from yacs.config import CfgNode
 from collections import namedtuple
@@ -29,12 +29,12 @@ from deepspeech.frontend.featurizer.speech_featurizer import SpeechFeaturizer
 from deepspeech.frontend.speech import SpeechSegment
 from deepspeech.frontend.normalizer import FeatureNormalizer
 
-logger = logging.getLogger(__name__)
-
 __all__ = [
     "ManifestDataset",
 ]
 
+logger = Log(__name__).getlog()
+
 
 class ManifestDataset(Dataset):
     @classmethod

deepspeech/io/sampler.py

@@ -13,20 +13,20 @@
 # limitations under the License.
 
 import math
-import logging
+from deepspeech.utils.log import Log
 import numpy as np
 
 from paddle.io import BatchSampler
 from paddle.io import DistributedBatchSampler
 from paddle import distributed as dist
 
-logger = logging.getLogger(__name__)
-
 __all__ = [
     "SortagradDistributedBatchSampler",
     "SortagradBatchSampler",
 ]
 
+logger = Log(__name__).getlog()
+
 
 def _batch_shuffle(indices, batch_size, epoch, clipped=False):
     """Put similarly-sized instances into minibatches for better efficiency

deepspeech/io/utility.py

@@ -12,14 +12,14 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
+from deepspeech.utils.log import Log
 import numpy as np
 from typing import List
 
-logger = logging.getLogger(__name__)
-
 __all__ = ["pad_sequence"]
 
+logger = Log(__name__).getlog()
+
 
 def pad_sequence(sequences: List[np.ndarray],
                  batch_first: bool=True,

deepspeech/models/deepspeech2.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """Deepspeech2 ASR Model"""
-import logging
+from deepspeech.utils.log import Log
 from typing import Optional
 from yacs.config import CfgNode
 
@@ -26,7 +26,7 @@ from deepspeech.modules.ctc import CTCDecoder
 from deepspeech.utils import checkpoint
 from deepspeech.utils import layer_tools
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ['DeepSpeech2Model']
 

deepspeech/models/u2.py

@@ -19,7 +19,7 @@ Unified Streaming and Non-streaming Two-pass End-to-end Model for Speech Recogni
 import time
 import sys
 from collections import defaultdict
-import logging
+from deepspeech.utils.log import Log
 from yacs.config import CfgNode
 from typing import List, Optional, Tuple, Dict
 
@@ -50,7 +50,7 @@ from deepspeech.utils.tensor_utils import th_accuracy
 from deepspeech.utils.tensor_utils import pad_sequence
 from deepspeech.utils.ctc_utils import remove_duplicates_and_blank
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ["U2Model", "U2InferModel"]
 

deepspeech/modules/activation.py

@@ -12,13 +12,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
+from deepspeech.utils.log import Log
 from collections import OrderedDict
 
 import paddle
 from paddle import nn
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ["get_activation", "brelu", "LinearGLUBlock", "ConvGLUBlock"]
 

deepspeech/modules/attention.py

@@ -13,14 +13,14 @@
 # limitations under the License.
 """Multi-Head Attention layer definition."""
 import math
-import logging
+from deepspeech.utils.log import Log
 from typing import Optional, Tuple
 
 import paddle
 from paddle import nn
 from paddle.nn import initializer as I
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ["MultiHeadedAttention", "RelPositionMultiHeadedAttention"]
 

deepspeech/modules/cmvn.py

@@ -12,12 +12,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
+from deepspeech.utils.log import Log
 
 import paddle
 from paddle import nn
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ['GlobalCMVN']
 

deepspeech/modules/conformer_convolution.py

@@ -15,12 +15,12 @@
 from typing import Optional, Tuple
 from typeguard import check_argument_types
 
-import logging
+from deepspeech.utils.log import Log
 
 import paddle
 from paddle import nn
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ['ConvolutionModule']
 

deepspeech/modules/conv.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
+from deepspeech.utils.log import Log
 
 from paddle import nn
 from paddle.nn import functional as F
@@ -20,7 +20,7 @@ from paddle.nn import functional as F
 from deepspeech.modules.mask import sequence_mask
 from deepspeech.modules.activation import brelu
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ['ConvStack', "conv_output_size"]
 

deepspeech/modules/ctc.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
+from deepspeech.utils.log import Log
 from typeguard import check_argument_types
 
 import paddle
@@ -26,7 +26,7 @@ from deepspeech.decoders.swig_wrapper import Scorer
 from deepspeech.decoders.swig_wrapper import ctc_greedy_decoder
 from deepspeech.decoders.swig_wrapper import ctc_beam_search_decoder_batch
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ['CTCDecoder']
 

deepspeech/modules/decoder.py

@@ -14,7 +14,7 @@
 """Decoder definition."""
 from typing import Tuple, List, Optional
 from typeguard import check_argument_types
-import logging
+from deepspeech.utils.log import Log
 
 import paddle
 from paddle import nn
@@ -26,7 +26,7 @@ from deepspeech.modules.positionwise_feed_forward import PositionwiseFeedForward
 from deepspeech.modules.mask import subsequent_mask
 from deepspeech.modules.mask import make_non_pad_mask
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ["TransformerDecoder"]
 

deepspeech/modules/decoder_layer.py

@@ -13,12 +13,12 @@
 # limitations under the License.
 """Decoder self-attention layer definition."""
 from typing import Optional, Tuple
-import logging
+from deepspeech.utils.log import Log
 
 import paddle
 from paddle import nn
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ["DecoderLayer"]
 

deepspeech/modules/embedding.py

@@ -14,13 +14,13 @@
 """Positonal Encoding Module."""
 
 import math
-import logging
+from deepspeech.utils.log import Log
 from typing import Tuple
 
 import paddle
 from paddle import nn
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ["PositionalEncoding", "RelPositionalEncoding"]
 

deepspeech/modules/encoder.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """Encoder definition."""
-import logging
+from deepspeech.utils.log import Log
 from typing import Tuple, List, Optional
 from typeguard import check_argument_types
 
@@ -35,7 +35,7 @@ from deepspeech.modules.mask import make_non_pad_mask
 from deepspeech.modules.mask import add_optional_chunk_mask
 from deepspeech.modules.activation import get_activation
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ["BaseEncoder", 'TransformerEncoder', "ConformerEncoder"]
 

deepspeech/modules/encoder_layer.py

@@ -13,12 +13,12 @@
 # limitations under the License.
 """Encoder self-attention layer definition."""
 from typing import Optional, Tuple
-import logging
+from deepspeech.utils.log import Log
 
 import paddle
 from paddle import nn
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ["TransformerEncoderLayer", "ConformerEncoderLayer"]
 

deepspeech/modules/loss.py

@@ -12,13 +12,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
+from deepspeech.utils.log import Log
 
 import paddle
 from paddle import nn
 from paddle.nn import functional as F
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ['CTCLoss', "LabelSmoothingLoss"]
 

deepspeech/modules/mask.py

@@ -12,11 +12,11 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
+from deepspeech.utils.log import Log
 
 import paddle
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = [
     'sequence_mask', "make_pad_mask", "make_non_pad_mask", "subsequent_mask",

deepspeech/modules/positionwise_feed_forward.py

@@ -12,12 +12,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """Positionwise feed forward layer definition."""
-import logging
+from deepspeech.utils.log import Log
 
 import paddle
 from paddle import nn
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ["PositionwiseFeedForward"]
 

deepspeech/modules/rnn.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import math
-import logging
+from deepspeech.utils.log import Log
 
 import paddle
 from paddle import nn
@@ -23,7 +23,7 @@ from paddle.nn import initializer as I
 from deepspeech.modules.mask import sequence_mask
 from deepspeech.modules.activation import brelu
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ['RNNStack']
 

deepspeech/modules/subsampling.py

@@ -14,14 +14,14 @@
 """Subsampling layer definition."""
 
 from typing import Tuple
-import logging
+from deepspeech.utils.log import Log
 
 import paddle
 from paddle import nn
 
 from deepspeech.modules.embedding import PositionalEncoding
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = [
     "LinearNoSubsampling", "Conv2dSubsampling4", "Conv2dSubsampling6",

deepspeech/training/gradclip.py

@@ -12,17 +12,17 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
+from deepspeech.utils.log import Log
 
 import paddle
 from paddle.fluid.dygraph import base as imperative_base
 from paddle.fluid import layers
 from paddle.fluid import core
 
-logger = logging.getLogger(__name__)
-
 __all__ = ["ClipGradByGlobalNormWithLog"]
 
+logger = Log(__name__).getlog()
+
 
 class ClipGradByGlobalNormWithLog(paddle.nn.ClipGradByGlobalNorm):
     def __init__(self, clip_norm):

deepspeech/training/scheduler.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
+from deepspeech.utils.log import Log
 from typing import Union
 from typeguard import check_argument_types
 
@@ -20,7 +20,7 @@ from paddle.optimizer.lr import LRScheduler
 
 __all__ = ["WarmupLR"]
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 
 class WarmupLR(LRScheduler):

deepspeech/training/trainer.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import time
-import logging
+from deepspeech.utils.log import Log
 from pathlib import Path
 
 import paddle
@@ -25,7 +25,7 @@ from deepspeech.utils import mp_tools
 
 __all__ = ["Trainer"]
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 
 class Trainer():

deepspeech/utils/checkpoint.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import os
-import logging
+from deepspeech.utils.log import Log
 import re
 import json
 from typing import Union
@@ -24,7 +24,7 @@ from paddle.optimizer import Optimizer
 
 from deepspeech.utils import mp_tools
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ["load_parameters", "save_parameters"]
 

deepspeech/utils/ctc_utils.py

@@ -12,13 +12,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import logging
+from deepspeech.utils.log import Log
 import numpy as np
 from typing import List
 
 import paddle
 
-logger = logging.getLogger(__name__)
+logger = Log(__name__).getlog()
 
 __all__ = ["forced_align", "remove_duplicates_and_blank", "insert_blank"]
 

deepspeech/utils/log.py

@@ -0,0 +1,52 @@
+# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import logging
+import os
+
+
+class Log():
+    def __init__(self, logger=None, log_cate='global'):
+        self.logger = logging.getLogger(logger)
+        self.logger.setLevel(logging.DEBUG)
+
+        file_dir = os.getcwd() + '/log'
+        if not os.path.exists(file_dir):
+            os.mkdir(file_dir)
+        self.log_path = file_dir
+        self.log_name = self.log_path + "/" + log_cate + '.log'
+
+        fh = logging.FileHandler(self.log_name)
+        fh.setLevel(logging.DEBUG)
+
+        ch = logging.StreamHandler()
+        ch.setLevel(logging.INFO)
+
+        format = '[%(levelname)s %(asctime)s %(filename)s:%(lineno)d] %(message)s'
+        formatter = logging.Formatter(fmt=format, datefmt='%Y/%m/%d %H:%M:%S')
+        fh.setFormatter(formatter)
+        ch.setFormatter(formatter)
+
+        self.logger.addHandler(fh)
+        self.logger.addHandler(ch)
+
+        # stop propagate for propagating may print
+        # log multiple times
+        # self.logger.propagate = False
+
+        fh.close()
+        ch.close()
+
+    def getlog(self):
+        return self.logger

deepspeech/utils/tensor_utils.py

@@ -12,15 +12,15 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """Unility functions for Transformer."""
-import logging
+from deepspeech.utils.log import Log
 from typing import Tuple, List
 
 import paddle
 
-logger = logging.getLogger(__name__)
-
 __all__ = ["pad_sequence", "add_sos_eos", "th_accuracy"]
 
+logger = Log(__name__).getlog()
+
 
 def pad_sequence(sequences: List[paddle.Tensor],
                  batch_first: bool=False,