diff --git a/.gitignore b/.gitignore
index 30aca84c4d788ea600ac9bbb49fc07475d325d99..260c80bd948e7483c9b233a1396f6c7c2cac7083 100644
--- a/.gitignore
+++ b/.gitignore
@@ -16,3 +16,5 @@ tools/kenlm
 tools/sox-14.4.2
 tools/soxbindings
 tools/Montreal-Forced-Aligner/
+
+*output/
diff --git a/deepspeech/exps/deepspeech2/model.py b/deepspeech/exps/deepspeech2/model.py
index 5e659092ababa68e3177f45784cf47258a14ccd3..27d4f94c1179af95929b1aa9d64f69025852a47a 100644
--- a/deepspeech/exps/deepspeech2/model.py
+++ b/deepspeech/exps/deepspeech2/model.py
@@ -34,9 +34,8 @@ from deepspeech.training.trainer import Trainer
 from deepspeech.utils import error_rate
 from deepspeech.utils import layer_tools
 from deepspeech.utils import mp_tools
-from deepspeech.utils.log import Log
 from deepspeech.utils.log import Autolog
-
+from deepspeech.utils.log import Log
 
 logger = Log(__name__).getlog()
 
@@ -226,8 +225,7 @@ class DeepSpeech2Tester(DeepSpeech2Trainer):
 
     def __init__(self, config, args):
         super().__init__(config, args)
-        self.autolog = Autolog(batch_size = config.decoding.batch_size, model_name = "deepspeech2", model_precision = "fp32").getlog()
-    
+
     def ordid2token(self, texts, texts_len):
         """ ord() id to chr() chr """
         trans = []
@@ -294,6 +292,10 @@ class DeepSpeech2Tester(DeepSpeech2Trainer):
     @paddle.no_grad()
     def test(self):
         logger.info(f"Test Total Examples: {len(self.test_loader.dataset)}")
+        self.autolog = Autolog(
+            batch_size=self.config.decoding.batch_size,
+            model_name="deepspeech2",
+            model_precision="fp32").getlog()
         self.model.eval()
         cfg = self.config
         error_rate_type = None
diff --git a/deepspeech/utils/log.py b/deepspeech/utils/log.py
index d5522d8d169d31dfa4c85654b37ddee91eff8239..aefc8b598333ee05f99b4ea96189b79f472f7daa 100644
--- a/deepspeech/utils/log.py
+++ b/deepspeech/utils/log.py
@@ -18,11 +18,8 @@ import socket
 import sys
 
 import auto_log
-import os
 from paddle import inference
 
-
-
 FORMAT_STR = '[%(levelname)s %(asctime)s %(filename)s:%(lineno)d] %(message)s'
 DATE_FMT_STR = '%Y/%m/%d %H:%M:%S'
 
@@ -153,28 +150,29 @@ class Log():
     def getlog(self):
         return self.logger
 
-class Autolog:
 
-    def __init__(self, batch_size, model_name = "DeepSpeech", model_precision = "fp32"):    
+class Autolog:
+    def __init__(self,
+                 batch_size,
+                 model_name="DeepSpeech",
+                 model_precision="fp32"):
         pid = os.getpid()
         gpu_id = int(os.environ['CUDA_VISIBLE_DEVICES'].split(',')[0])
         infer_config = inference.Config()
         infer_config.enable_use_gpu(100, gpu_id)
         autolog = auto_log.AutoLogger(
-            model_name = model_name,
-            model_precision = model_precision,
-            batch_size = batch_size,
+            model_name=model_name,
+            model_precision=model_precision,
+            batch_size=batch_size,
             data_shape="dynamic",
             save_path="./output/auto_log.lpg",
-            inference_config = infer_config,
-            pids = pid,
-            process_name = None,
-            gpu_ids = gpu_id,
-            time_keys=[
-                    'preprocess_time', 'inference_time', 'postprocess_time'
-            ],
+            inference_config=infer_config,
+            pids=pid,
+            process_name=None,
+            gpu_ids=gpu_id,
+            time_keys=['preprocess_time', 'inference_time', 'postprocess_time'],
             warmup=0)
         self.autolog = autolog
-    
+
     def getlog(self):
         return self.autolog
diff --git a/examples/dataset/timit/timit_kaldi_standard_split.py b/examples/dataset/timit/timit_kaldi_standard_split.py
index beb5a63ec750142005e9371d4123fc58d50be744..2b494c06db990e8c932cc28a5a974cddc9e4e943 100644
--- a/examples/dataset/timit/timit_kaldi_standard_split.py
+++ b/examples/dataset/timit/timit_kaldi_standard_split.py
@@ -50,36 +50,36 @@ def create_manifest(data_dir, manifest_path_prefix):
         total_text = 0.0
         total_num = 0
 
-        phn_path = os.path.join(data_dir, dtype+'.text')
+        phn_path = os.path.join(data_dir, dtype + '.text')
         phn_dict = {}
         for line in codecs.open(phn_path, 'r', 'utf-8'):
             line = line.strip()
             if line == '':
                 continue
             audio_id, text = line.split(' ', 1)
-            phn_dict[audio_id] = text        
+            phn_dict[audio_id] = text
 
-        audio_dir = os.path.join(data_dir, dtype+'_sph.scp')
+        audio_dir = os.path.join(data_dir, dtype + '_sph.scp')
         for line in codecs.open(audio_dir, 'r', 'utf-8'):
-                audio_id, audio_path = line.strip().split()
-                # if no transcription for audio then raise error
-                assert audio_id in phn_dict
-                audio_data, samplerate = soundfile.read(audio_path)
-                duration = float(len(audio_data) / samplerate)
-                text = phn_dict[audio_id]
-                json_lines.append(
-                    json.dumps(
-                        {
-                            'utt': audio_id,
-                            'feat': audio_path,
-                            'feat_shape': (duration, ),  # second
-                            'text': text
-                        },
-                        ensure_ascii=False))
-
-                total_sec += duration
-                total_text += len(text)
-                total_num += 1
+            audio_id, audio_path = line.strip().split()
+            # if no transcription for audio then raise error
+            assert audio_id in phn_dict
+            audio_data, samplerate = soundfile.read(audio_path)
+            duration = float(len(audio_data) / samplerate)
+            text = phn_dict[audio_id]
+            json_lines.append(
+                json.dumps(
+                    {
+                        'utt': audio_id,
+                        'feat': audio_path,
+                        'feat_shape': (duration, ),  # second
+                        'text': text
+                    },
+                    ensure_ascii=False))
+
+            total_sec += duration
+            total_text += len(text)
+            total_num += 1
 
         manifest_path = manifest_path_prefix + '.' + dtype + '.raw'
         with codecs.open(manifest_path, 'w', 'utf-8') as fout:
@@ -99,9 +99,7 @@ def main():
     if args.src_dir.startswith('~'):
         args.src_dir = os.path.expanduser(args.src_dir)
 
-    prepare_dataset(
-        src_dir=args.src_dir,
-        manifest_path=args.manifest_prefix)
+    prepare_dataset(src_dir=args.src_dir, manifest_path=args.manifest_prefix)
 
     print("manifest prepare done!")
 
diff --git a/examples/timit/s1/README.md b/examples/timit/s1/README.md
index 2dd8a7198e62177430bc6b1fcfab0d2a9e87869b..4d9b146afc5b080c3f6c7b666b61feaaa81cc64e 100644
--- a/examples/timit/s1/README.md
+++ b/examples/timit/s1/README.md
@@ -1,3 +1,3 @@
 # TIMIT
 
-Results will be organized and updated soon.
\ No newline at end of file
+Results will be organized and updated soon.
diff --git a/setup.sh b/setup.sh
index 0c602e618b4b69d9d20d82093d60b44cf4b6c09d..384d62d2846e5ef7dbdee00be3c4e17f5eb75937 100644
--- a/setup.sh
+++ b/setup.sh
@@ -44,18 +44,17 @@ if [ $? != 0 ]; then
 fi
 
 #install auto-log
-python3 -c "import auto_log"
+python -c "import auto_log"
 if [ $? != 0 ]; then
     info_msg "Install auto_log into default system path"
-    git clone https://github.com/LDOUBLEV/AutoLog
+    test -d AutoLog || git clone https://github.com/LDOUBLEV/AutoLog
     if [ $? != 0 ]; then
         error_msg "Download auto_log failed !!!"
         exit 1
     fi
     cd AutoLog
-    pip3 install -r requirements.txt
-    python3 setup.py bdist_wheel
-    pip3 install ./dist/[Aa]uto*.whl
+    pip install -r requirements.txt
+    python setup.py install 
     cd ..
     rm -rf AutoLog
 fi