Add RFT for asr task.

paddlespeech/cli/asr/infer.py

@@ -14,6 +14,7 @@
 import argparse
 import os
 import sys
+import time
 from collections import OrderedDict
 from typing import List
 from typing import Optional
@@ -29,8 +30,10 @@ from ..download import get_path_from_url
 from ..executor import BaseExecutor
 from ..log import logger
 from ..utils import cli_register
+from ..utils import CLI_TIMER
 from ..utils import MODEL_HOME
 from ..utils import stats_wrapper
+from ..utils import timer_register
 from .pretrained_models import model_alias
 from .pretrained_models import pretrained_models
 from paddlespeech.s2t.frontend.featurizer.text_featurizer import TextFeaturizer
@@ -41,6 +44,7 @@ from paddlespeech.s2t.utils.utility import UpdateConfig
 __all__ = ['ASRExecutor']
 
 
+@timer_register
 @cli_register(
     name='paddlespeech.asr', description='Speech to text infer command.')
 class ASRExecutor(BaseExecutor):
@@ -99,6 +103,11 @@ class ASRExecutor(BaseExecutor):
             default=False,
             help='No additional parameters required. Once set this parameter, it means accepting the request of the program by default, which includes transforming the audio sample rate'
         )
+        self.parser.add_argument(
+            '--rtf',
+            action="store_true",
+            default=False,
+            help='Show Real-time Factor(RTF).')
         self.parser.add_argument(
             '--device',
             type=str,
@@ -407,6 +416,7 @@ class ASRExecutor(BaseExecutor):
         ckpt_path = parser_args.ckpt_path
         decode_method = parser_args.decode_method
         force_yes = parser_args.yes
+        rtf = parser_args.rtf
         device = parser_args.device
 
         if not parser_args.verbose:
@@ -419,12 +429,15 @@ class ASRExecutor(BaseExecutor):
         for id_, input_ in task_source.items():
             try:
                 res = self(input_, model, lang, sample_rate, config, ckpt_path,
-                           decode_method, force_yes, device)
+                           decode_method, force_yes, rtf, device)
                 task_results[id_] = res
             except Exception as e:
                 has_exceptions = True
                 task_results[id_] = f'{e.__class__.__name__}: {e}'
 
+        if rtf:
+            self.show_rtf(CLI_TIMER[self.__class__.__name__])
+
         self.process_task_results(parser_args.input, task_results,
                                   parser_args.job_dump_result)
 
@@ -443,6 +456,7 @@ class ASRExecutor(BaseExecutor):
                  ckpt_path: os.PathLike=None,
                  decode_method: str='attention_rescoring',
                  force_yes: bool=False,
+                 rtf: bool=False,
                  device=paddle.get_device()):
         """
         Python API to call an executor.
@@ -454,7 +468,18 @@ class ASRExecutor(BaseExecutor):
         self._init_from_path(model, lang, sample_rate, config, decode_method,
                              ckpt_path)
         self.preprocess(model, audio_file)
-        self.infer(model)
+
+        if rtf:
+            k = self.__class__.__name__
+            CLI_TIMER[k]['start'].append(time.time())
+            self.infer(model)
+            CLI_TIMER[k]['end'].append(time.time())
+            audio, audio_sample_rate = soundfile.read(
+                audio_file, dtype="int16", always_2d=True)
+            CLI_TIMER[k]['extra'].append(audio.shape[0] / audio_sample_rate)
+        else:
+            self.infer(model)
+
         res = self.postprocess()  # Retrieve result of asr.
 
         return res

paddlespeech/cli/executor.py

@@ -235,3 +235,19 @@ class BaseExecutor(ABC):
             'Use pretrained model stored in: {}'.format(decompressed_path))
 
         return decompressed_path
+
+    def show_rtf(self, info: Dict[str, List[float]]):
+        """
+        Calculate rft of current task and show results.
+        """
+        num_samples = 0
+        task_duration = 0.0
+        wav_duration = 0.0
+
+        for start, end, dur in zip(info['start'], info['end'], info['extra']):
+            num_samples += 1
+            task_duration += end - start
+            wav_duration += dur
+
+        logger.info('Sample Count: {}'.format(num_samples))
+        logger.info('Avg RTF: {}'.format(task_duration / wav_duration))

paddlespeech/cli/utils.py

@@ -24,11 +24,11 @@ from typing import Any
 from typing import Dict
 
 import paddle
-import paddleaudio
 import requests
 import yaml
 from paddle.framework import load
 
+import paddleaudio
 from . import download
 from .entry import commands
 try:
@@ -39,6 +39,7 @@ except ImportError:
 requests.adapters.DEFAULT_RETRIES = 3
 
 __all__ = [
+    'timer_register',
     'cli_register',
     'get_command',
     'download_and_decompress',
@@ -46,6 +47,13 @@ __all__ = [
     'stats_wrapper',
 ]
 
+CLI_TIMER = {}
+
+
+def timer_register(command):
+    CLI_TIMER[command.__name__] = {'start': [], 'end': [], 'extra': []}
+    return command
+
 
 def cli_register(name: str, description: str='') -> Any:
     def _warpper(command):