Update batch input.

paddlespeech/cli/asr/infer.py

@@ -12,8 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import argparse
+import ast
 import os
 import sys
+from collections import OrderedDict
 from typing import List
 from typing import Optional
 from typing import Union
@@ -130,7 +132,7 @@ class ASRExecutor(BaseExecutor):
         self.parser = argparse.ArgumentParser(
             prog='paddlespeech.asr', add_help=True)
         self.parser.add_argument(
-            '--input', type=str, required=True, help='Audio file to recognize.')
+            '--input', type=str, default=None, help='Audio file to recognize.')
         self.parser.add_argument(
             '--model',
             type=str,
@@ -180,6 +182,11 @@ class ASRExecutor(BaseExecutor):
             type=str,
             default=paddle.get_device(),
             help='Choose device to execute model inference.')
+        self.parser.add_argument(
+            '--job_dump_result',
+            type=ast.literal_eval,
+            default=False,
+            help='Save job result into file.')
 
     def _get_pretrained_path(self, tag: str) -> os.PathLike:
         """
@@ -469,19 +476,31 @@ class ASRExecutor(BaseExecutor):
         sample_rate = parser_args.sample_rate
         config = parser_args.config
         ckpt_path = parser_args.ckpt_path
-        audio_file = parser_args.input
         decode_method = parser_args.decode_method
         force_yes = parser_args.yes
         device = parser_args.device
+        job_dump_result = parser_args.job_dump_result
+
+        task_source = self.get_task_source(parser_args.input)
+        task_results = OrderedDict()
+        has_exceptions = False
 
+        for id_, input_ in task_source.items():
             try:
-            res = self(audio_file, model, lang, sample_rate, config, ckpt_path,
+                res = self(input_, model, lang, sample_rate, config, ckpt_path,
                            decode_method, force_yes, device)
-            logger.info('ASR Result: {}'.format(res))
+                task_results[id_] = res
-            return True
             except Exception as e:
-            logger.exception(e)
+                has_exceptions = True
+                task_results[id_] = f'{e.__class__.__name__}: {e}'
+
+        self.process_task_results(parser_args.input, task_results,
+                                  job_dump_result)
+
+        if has_exceptions:
             return False
+        else:
+            return True
 
     @stats_wrapper
     def __call__(self,

paddlespeech/cli/st/infer.py

@@ -12,8 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import argparse
+import ast
 import os
 import subprocess
+from collections import OrderedDict
 from typing import List
 from typing import Optional
 from typing import Union
@@ -69,7 +71,7 @@ class STExecutor(BaseExecutor):
         self.parser = argparse.ArgumentParser(
             prog="paddlespeech.st", add_help=True)
         self.parser.add_argument(
-            "--input", type=str, required=True, help="Audio file to translate.")
+            "--input", type=str, default=None, help="Audio file to translate.")
         self.parser.add_argument(
             "--model",
             type=str,
@@ -107,6 +109,11 @@ class STExecutor(BaseExecutor):
             type=str,
             default=paddle.get_device(),
             help="Choose device to execute model inference.")
+        self.parser.add_argument(
+            '--job_dump_result',
+            type=ast.literal_eval,
+            default=False,
+            help='Save job result into file.')
 
     def _get_pretrained_path(self, tag: str) -> os.PathLike:
         """
@@ -319,17 +326,29 @@ class STExecutor(BaseExecutor):
         sample_rate = parser_args.sample_rate
         config = parser_args.config
         ckpt_path = parser_args.ckpt_path
-        audio_file = parser_args.input
         device = parser_args.device
+        job_dump_result = parser_args.job_dump_result
+
+        task_source = self.get_task_source(parser_args.input)
+        task_results = OrderedDict()
+        has_exceptions = False
 
+        for id_, input_ in task_source.items():
             try:
-            res = self(audio_file, model, src_lang, tgt_lang, sample_rate,
+                res = self(input_, model, src_lang, tgt_lang, sample_rate,
                            config, ckpt_path, device)
-            logger.info("ST Result: {}".format(res))
+                task_results[id_] = res
-            return True
             except Exception as e:
-            logger.exception(e)
+                has_exceptions = True
+                task_results[id_] = f'{e.__class__.__name__}: {e}'
+
+        self.process_task_results(parser_args.input, task_results,
+                                  job_dump_result)
+
+        if has_exceptions:
             return False
+        else:
+            return True
 
     @stats_wrapper
     def __call__(self,

paddlespeech/cli/text/infer.py

@@ -12,8 +12,10 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import argparse
+import ast
 import os
 import re
+from collections import OrderedDict
 from typing import List
 from typing import Optional
 from typing import Union
@@ -80,7 +82,7 @@ class TextExecutor(BaseExecutor):
         self.parser = argparse.ArgumentParser(
             prog='paddlespeech.text', add_help=True)
         self.parser.add_argument(
-            '--input', type=str, required=True, help='Input text.')
+            '--input', type=str, default=None, help='Input text.')
         self.parser.add_argument(
             '--task',
             type=str,
@@ -119,6 +121,11 @@ class TextExecutor(BaseExecutor):
             type=str,
             default=paddle.get_device(),
             help='Choose device to execute model inference.')
+        self.parser.add_argument(
+            '--job_dump_result',
+            type=ast.literal_eval,
+            default=False,
+            help='Save job result into file.')
 
     def _get_pretrained_path(self, tag: str) -> os.PathLike:
         """
@@ -256,7 +263,6 @@ class TextExecutor(BaseExecutor):
         """
         parser_args = self.parser.parse_args(argv)
 
-        text = parser_args.input
         task = parser_args.task
         model_type = parser_args.model
         lang = parser_args.lang
@@ -264,15 +270,28 @@ class TextExecutor(BaseExecutor):
         ckpt_path = parser_args.ckpt_path
         punc_vocab = parser_args.punc_vocab
         device = parser_args.device
+        job_dump_result = parser_args.job_dump_result
+
+        task_source = self.get_task_source(parser_args.input)
+        task_results = OrderedDict()
+        has_exceptions = False
 
+        for id_, input_ in task_source.items():
             try:
-            res = self(text, task, model_type, lang, cfg_path, ckpt_path,
+                res = self(input_, task, model_type, lang, cfg_path, ckpt_path,
                            punc_vocab, device)
-            logger.info('Text Result:\n{}'.format(res))
+                task_results[id_] = res
-            return True
             except Exception as e:
-            logger.exception(e)
+                has_exceptions = True
+                task_results[id_] = f'{e.__class__.__name__}: {e}'
+
+        self.process_task_results(parser_args.input, task_results,
+                                  job_dump_result)
+
+        if has_exceptions:
             return False
+        else:
+            return True
 
     @stats_wrapper
     def __call__(

paddlespeech/cli/tts/infer.py

@@ -12,7 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 import argparse
+import ast
 import os
+from collections import OrderedDict
 from typing import Any
 from typing import List
 from typing import Optional
@@ -298,7 +300,7 @@ class TTSExecutor(BaseExecutor):
         self.parser = argparse.ArgumentParser(
             prog='paddlespeech.tts', add_help=True)
         self.parser.add_argument(
-            '--input', type=str, required=True, help='Input text to generate.')
+            '--input', type=str, default=None, help='Input text to generate.')
         # acoustic model
         self.parser.add_argument(
             '--am',
@@ -397,6 +399,11 @@ class TTSExecutor(BaseExecutor):
 
         self.parser.add_argument(
             '--output', type=str, default='output.wav', help='output file name')
+        self.parser.add_argument(
+            '--job_dump_result',
+            type=ast.literal_eval,
+            default=False,
+            help='Save job result into file.')
 
     def _get_pretrained_path(self, tag: str) -> os.PathLike:
         """
@@ -671,7 +678,6 @@ class TTSExecutor(BaseExecutor):
 
         args = self.parser.parse_args(argv)
 
-        text = args.input
         am = args.am
         am_config = args.am_config
         am_ckpt = args.am_ckpt
@@ -686,12 +692,24 @@ class TTSExecutor(BaseExecutor):
         voc_stat = args.voc_stat
         lang = args.lang
         device = args.device
-        output = args.output
         spk_id = args.spk_id
+        job_dump_result = args.job_dump_result
+
+        task_source = self.get_task_source(args.input)
+        task_results = OrderedDict()
+        has_exceptions = False
+
+        for id_, input_ in task_source.items():
+            if len(task_source) > 1:
+                assert isinstance(args.output,
+                                  str) and args.output.endswith('.wav')
+                output = args.output.replace('.wav', f'_{id_}.wav')
+            else:
+                output = args.output
 
             try:
                 res = self(
-                text=text,
+                    text=input_,
                     # acoustic model related
                     am=am,
                     am_config=am_config,
@@ -710,11 +728,17 @@ class TTSExecutor(BaseExecutor):
                     lang=lang,
                     device=device,
                     output=output)
-            logger.info('Wave file has been generated: {}'.format(res))
+                task_results[id_] = res
-            return True
             except Exception as e:
-            logger.exception(e)
+                has_exceptions = True
+                task_results[id_] = f'{e.__class__.__name__}: {e}'
+
+        self.process_task_results(args.input, task_results, job_dump_result)
+
+        if has_exceptions:
             return False
+        else:
+            return True
 
     @stats_wrapper
     def __call__(self,