change autoLog

deepspeech/exps/deepspeech2/model.py

@@ -35,10 +35,8 @@ 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
 
-import auto_log
-import os
-from paddle import inference
 
 logger = Log(__name__).getlog()
 
@@ -228,28 +226,8 @@ class DeepSpeech2Tester(DeepSpeech2Trainer):
 
     def __init__(self, config, args):
         super().__init__(config, args)
-        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="deepspeech2",
-             model_precision="fp32",
-             batch_size=config.decoding.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'
-             ],
-             warmup=0)
-        self.autolog = autolog
-        logger = autolog.logger
-        logger.info("gpu_id:{}".format(gpu_id))
-
+        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 = []

deepspeech/utils/log.py

@@ -17,6 +17,12 @@ import os
 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'
 
@@ -146,3 +152,29 @@ class Log():
 
     def getlog(self):
         return self.logger
+
+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,
+            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'
+            ],
+            warmup=0)
+        self.autolog = autolog
+    
+    def getlog(self):
+        return self.autolog

examples/aishell/s0/run.sh

@@ -2,9 +2,9 @@
 set -e
 source path.sh
 
-gpus=2
+gpus=0,1,2,3
 stage=0
-stop_stage=4
+stop_stage=100
 conf_path=conf/deepspeech2.yaml
 avg_num=1
 
@@ -31,10 +31,10 @@ fi
 
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
     # test ckpt avg_n
-    CUDA_VISIBLE_DEVICES=${gpus} ./local/test.sh ${conf_path} exp/${ckpt}/checkpoints/${avg_ckpt} || exit -1
+    CUDA_VISIBLE_DEVICES=0 ./local/test.sh ${conf_path} exp/${ckpt}/checkpoints/${avg_ckpt} || exit -1
 fi
 
 if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
     # export ckpt avg_n
-    CUDA_VISIBLE_DEVICES=${gpus} ./local/export.sh ${conf_path} exp/${ckpt}/checkpoints/${avg_ckpt} exp/${ckpt}/checkpoints/${avg_ckpt}.jit
+    CUDA_VISIBLE_DEVICES=0 ./local/export.sh ${conf_path} exp/${ckpt}/checkpoints/${avg_ckpt} exp/${ckpt}/checkpoints/${avg_ckpt}.jit
 fi