format

demos/audio_searching/src/operations/load.py

@@ -26,9 +26,8 @@ def get_audios(path):
     """
     supported_formats = [".wav", ".mp3", ".ogg", ".flac", ".m4a"]
     return [
-        item
-        for sublist in [[os.path.join(dir, file) for file in files]
-                        for dir, _, files in list(os.walk(path))]
+        item for sublist in [[os.path.join(dir, file) for file in files]
+                             for dir, _, files in list(os.walk(path))]
         for item in sublist if os.path.splitext(item)[1] in supported_formats
     ]
 

demos/custom_streaming_asr/README.md

@@ -62,4 +62,4 @@ I0513 10:58:13.884493 41768 feature_cache.h:52] set finished
 I0513 10:58:24.247171 41768 paddle_nnet.h:76] Tensor neml: 10240
 I0513 10:58:24.247249 41768 paddle_nnet.h:76] Tensor neml: 10240
 LOG ([5.5.544~2-f21d7]:main():decoder/recognizer_test_main.cc:90)  the result of case_10 is 五月十二日二十二点三十六分加班打车回家四十一元
-```
\ No newline at end of file
+```

demos/streaming_asr_server/websocket_client.py

@@ -13,9 +13,7 @@
 # limitations under the License.
 #!/usr/bin/python
 # -*- coding: UTF-8 -*-
-
 # script for calc RTF: grep -rn RTF log.txt | awk '{print $NF}' | awk -F "=" '{sum += $NF} END {print "all time",sum, "audio num", NR,  "RTF", sum/NR}'
-
 import argparse
 import asyncio
 import codecs

docs/source/asr/PPASR_cn.md

@@ -92,5 +92,3 @@ server 的 demo： [streaming_asr_server](https://github.com/PaddlePaddle/Paddle
 ## 4. 快速开始
 
 关于如果使用 PP-ASR，可以看这里的 [install](https://github.com/PaddlePaddle/PaddleSpeech/blob/develop/docs/source/install_cn.md)，其中提供了 **简单**、**中等**、**困难** 三种安装方式。如果想体验 paddlespeech 的推理功能，可以用 **简单** 安装方式。
-
-

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:

paddlespeech/s2t/io/sampler.py

@@ -51,7 +51,7 @@ def _batch_shuffle(indices, batch_size, epoch, clipped=False):
     """
     rng = np.random.RandomState(epoch)
     shift_len = rng.randint(0, batch_size - 1)
-    batch_indices = list(zip(*[iter(indices[shift_len:])] * batch_size))
+    batch_indices = list(zip(* [iter(indices[shift_len:])] * batch_size))
     rng.shuffle(batch_indices)
     batch_indices = [item for batch in batch_indices for item in batch]
     assert clipped is False

paddlespeech/server/engine/acs/__init__.py

+# Copyright (c) 2022 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.

paddlespeech/server/engine/acs/python/__init__.py

+# Copyright (c) 2022 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.

paddlespeech/server/engine/asr/online/asr_engine.py

@@ -153,8 +153,7 @@ class PaddleASRConnectionHanddler:
                 spectrum = self.collate_fn_test._normalizer.apply(spectrum)
 
             # spectrum augment
-            feat = self.collate_fn_test.augmentation.transform_feature(
-                spectrum)
+            feat = self.collate_fn_test.augmentation.transform_feature(spectrum)
 
             # audio_len is frame num
             frame_num = feat.shape[0]
@@ -189,14 +188,16 @@ class PaddleASRConnectionHanddler:
             assert samples.ndim == 1
 
             self.num_samples += samples.shape[0]
-             logger.info(f"This package receive {samples.shape[0]} pcm data. Global samples:{self.num_samples}")
+            logger.info(
+                f"This package receive {samples.shape[0]} pcm data. Global samples:{self.num_samples}"
+            )
 
             # self.reamined_wav stores all the samples, 
             # include the original remained_wav and this package samples
             if self.remained_wav is None:
                 self.remained_wav = samples
             else:
-                assert self.remained_wav.ndim == 1 # (T,)
+                assert self.remained_wav.ndim == 1  # (T,)
                 self.remained_wav = np.concatenate([self.remained_wav, samples])
             logger.info(
                 f"The concatenation of remain and now audio samples length is: {self.remained_wav.shape}"
@@ -216,8 +217,8 @@ class PaddleASRConnectionHanddler:
             if self.cached_feat is None:
                 self.cached_feat = x_chunk
             else:
-                assert (len(x_chunk.shape) == 3) # (B,T,D)
-                assert (len(self.cached_feat.shape) == 3) # (B,T,D)
+                assert (len(x_chunk.shape) == 3)  # (B,T,D)
+                assert (len(self.cached_feat.shape) == 3)  # (B,T,D)
                 self.cached_feat = paddle.concat(
                     [self.cached_feat, x_chunk], axis=1)
 
@@ -234,18 +235,16 @@ class PaddleASRConnectionHanddler:
             # update remained wav
             self.remained_wav = self.remained_wav[self.n_shift * num_frames:]
 
-
             logger.info(
                 f"process the audio feature success, the cached feat shape: {self.cached_feat.shape}"
             )
             logger.info(
                 f"After extract feat, the cached remain the audio samples: {self.remained_wav.shape}"
             )
-            logger.info(f"global samples: {self.num_samples}")       
+            logger.info(f"global samples: {self.num_samples}")
             logger.info(f"global frames: {self.num_frames}")
         else:
-            raise ValueError(f"not supported: {self.model_type}") 
-
+            raise ValueError(f"not supported: {self.model_type}")
 
     def reset(self):
         if "deepspeech2" in self.model_type:
@@ -263,12 +262,11 @@ class PaddleASRConnectionHanddler:
         # global sample and frame step
         self.num_samples = 0
         self.num_frames = 0
-       
+
         # cache for audio and feat
         self.remained_wav = None
         self.cached_feat = None
 
-
         # partial/ending decoding results
         self.result_transcripts = ['']
 
@@ -280,17 +278,16 @@ class PaddleASRConnectionHanddler:
         self.conformer_cnn_cache = None
         self.encoder_out = None
         # conformer decoding state
-        self.chunk_num = 0 # globa decoding chunk num
-        self.offset = 0 # global offset in decoding frame unit
+        self.chunk_num = 0  # globa decoding chunk num
+        self.offset = 0  # global offset in decoding frame unit
         self.hyps = []
-       
+
         # token timestamp result
         self.word_time_stamp = []
 
         # one best timestamp viterbi prob is large.
         self.time_stamp = []
 
-       
     def decode(self, is_finished=False):
         """advance decoding
 
@@ -307,7 +304,7 @@ class PaddleASRConnectionHanddler:
             decoding_chunk_size = 1  # decoding chunk size = 1. int decoding frame unit
             context = 7  # context=7, in audio frame unit
             subsampling = 4  # subsampling=4, in audio frame unit
-           
+
             cached_feature_num = context - subsampling
             # decoding window for model, in audio frame unit
             decoding_window = (decoding_chunk_size - 1) * subsampling + context
@@ -373,7 +370,6 @@ class PaddleASRConnectionHanddler:
         else:
             raise Exception("invalid model name")
 
-
     @paddle.no_grad()
     def decode_one_chunk(self, x_chunk, x_chunk_lens):
         """forward one chunk frames
@@ -425,10 +421,11 @@ class PaddleASRConnectionHanddler:
         logger.info(f"decode one best result for deepspeech2: {trans_best[0]}")
         return trans_best[0]
 
-
     @paddle.no_grad()
     def advance_decoding(self, is_finished=False):
-        logger.info("Conformer/Transformer: start to decode with advanced_decoding method")
+        logger.info(
+            "Conformer/Transformer: start to decode with advanced_decoding method"
+        )
         cfg = self.ctc_decode_config
 
         # cur chunk size, in decoding frame unit
@@ -563,7 +560,6 @@ class PaddleASRConnectionHanddler:
         """
         return self.word_time_stamp
 
-
     @paddle.no_grad()
     def rescoring(self):
         """Second-Pass Decoding, 
@@ -572,9 +568,11 @@ class PaddleASRConnectionHanddler:
         if "deepspeech2" in self.model_type:
             logger.info("deepspeech2 not support rescoring decoding.")
             return
-        
+
         if "attention_rescoring" != self.ctc_decode_config.decoding_method:
-            logger.info(f"decoding method not match: {self.ctc_decode_config.decoding_method}, need attention_rescoring")
+            logger.info(
+                f"decoding method not match: {self.ctc_decode_config.decoding_method}, need attention_rescoring"
+            )
             return
 
         logger.info("rescoring the final result")
@@ -605,7 +603,8 @@ class PaddleASRConnectionHanddler:
                 hyp_content, place=self.device, dtype=paddle.long)
             hyp_list.append(hyp_content)
 
-        hyps_pad = pad_sequence(hyp_list, batch_first=True, padding_value=self.model.ignore_id)
+        hyps_pad = pad_sequence(
+            hyp_list, batch_first=True, padding_value=self.model.ignore_id)
         hyps_lens = paddle.to_tensor(
             [len(hyp[0]) for hyp in hyps], place=self.device,
             dtype=paddle.long)  # (beam_size,)
@@ -689,12 +688,11 @@ class PaddleASRConnectionHanddler:
                 "ed": end
             })
             # logger.info(f"{word_time_stamp[-1]}")
-        
+
         self.word_time_stamp = word_time_stamp
         logger.info(f"word time stamp: {self.word_time_stamp}")
 
 
-
 class ASRServerExecutor(ASRExecutor):
     def __init__(self):
         super().__init__()
@@ -741,7 +739,7 @@ class ASRServerExecutor(ASRExecutor):
             self.am_model = os.path.abspath(am_model)
             self.am_params = os.path.abspath(am_params)
             self.res_path = os.path.dirname(
-                os.path.dirname(os.path.abspath(self.cfg_path)))         
+                os.path.dirname(os.path.abspath(self.cfg_path)))
 
         logger.info(self.cfg_path)
         logger.info(self.am_model)
@@ -855,7 +853,7 @@ class ASRServerExecutor(ASRExecutor):
             self.transformer_decode_reset()
         else:
             raise ValueError(f"Not support: {model_type}")
-        
+
         return True
 
 

paddlespeech/server/restful/api.py

@@ -17,12 +17,12 @@ from typing import List
 from fastapi import APIRouter
 
 from paddlespeech.cli.log import logger
+from paddlespeech.server.restful.acs_api import router as acs_router
 from paddlespeech.server.restful.asr_api import router as asr_router
 from paddlespeech.server.restful.cls_api import router as cls_router
 from paddlespeech.server.restful.text_api import router as text_router
 from paddlespeech.server.restful.tts_api import router as tts_router
 from paddlespeech.server.restful.vector_api import router as vec_router
-from paddlespeech.server.restful.acs_api import router as acs_router
 _router = APIRouter()
 
 

paddlespeech/server/utils/audio_handler.py

@@ -248,7 +248,7 @@ class ASRHttpHandler:
         }
 
         res = requests.post(url=self.url, data=json.dumps(data))
-        
+
         return res.json()
 
 

paddlespeech/server/utils/buffer.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+
 class Frame(object):
     """Represents a "frame" of audio data."""
 
@@ -45,7 +46,7 @@ class ChunkBuffer(object):
         self.shift_ms = shift_ms
         self.sample_rate = sample_rate
         self.sample_width = sample_width  # int16 = 2; float32 = 4
-        
+
         self.window_sec = float((self.window_n - 1) * self.shift_ms +
                                 self.window_ms) / 1000.0
         self.shift_sec = float(self.shift_n * self.shift_ms / 1000.0)
@@ -77,8 +78,8 @@ class ChunkBuffer(object):
 
         offset = 0
         while offset + self.window_bytes <= len(audio):
-            yield Frame(audio[offset:offset + self.window_bytes], self.timestamp,
-                        self.window_sec)
+            yield Frame(audio[offset:offset + self.window_bytes],
+                        self.timestamp, self.window_sec)
             self.timestamp += self.shift_sec
             offset += self.shift_bytes
 

paddlespeech/t2s/exps/speedyspeech/synthesize_e2e.py

@@ -176,7 +176,10 @@ def main():
     parser.add_argument(
         "--ngpu", type=int, default=1, help="if ngpu == 0, use cpu or xpu.")
     parser.add_argument(
-        "--nxpu", type=int, default=0, help="if nxpu == 0 and ngpu == 0, use cpu.")
+        "--nxpu",
+        type=int,
+        default=0,
+        help="if nxpu == 0 and ngpu == 0, use cpu.")
 
     args, _ = parser.parse_known_args()
 

paddlespeech/t2s/exps/speedyspeech/train.py

@@ -188,7 +188,10 @@ def main():
     parser.add_argument("--dev-metadata", type=str, help="dev data.")
     parser.add_argument("--output-dir", type=str, help="output dir.")
     parser.add_argument(
-        "--nxpu", type=int, default=0, help="if nxpu == 0 and ngpu == 0, use cpu.")
+        "--nxpu",
+        type=int,
+        default=0,
+        help="if nxpu == 0 and ngpu == 0, use cpu.")
     parser.add_argument(
         "--ngpu", type=int, default=1, help="if ngpu == 0, use cpu or xpu")
 

paddlespeech/t2s/modules/transformer/repeat.py

@@ -36,4 +36,4 @@ def repeat(N, fn):
     Returns:
         MultiSequential: Repeated model instance.
     """
-    return MultiSequential(*[fn(n) for n in range(N)])
+    return MultiSequential(* [fn(n) for n in range(N)])

setup.py

@@ -98,7 +98,6 @@ requirements = {
 }
 
 
-
 def check_call(cmd: str, shell=False, executable=None):
     try:
         sp.check_call(
@@ -112,12 +111,13 @@ def check_call(cmd: str, shell=False, executable=None):
             file=sys.stderr)
         raise e
 
+
 def check_output(cmd: str, shell=False):
     try:
         out_bytes = sp.check_output(cmd.split())
     except sp.CalledProcessError as e:
-        out_bytes = e.output       # Output generated before error
-        code      = e.returncode   # Return code
+        out_bytes = e.output  # Output generated before error
+        code = e.returncode  # Return code
         print(
             f"{__file__}:{inspect.currentframe().f_lineno}: CMD: {cmd}, Error:",
             out_bytes,
@@ -146,6 +146,7 @@ def _remove(files: str):
     for f in files:
         f.unlink()
 
+
 ################################# Install ##################################
 
 
@@ -308,6 +309,5 @@ setup_info = dict(
         ]
     })
 
-
 with version_info():
     setup(**setup_info)

tests/unit/cli/aishell_test_prepare.py

@@ -20,7 +20,6 @@ of each audio file in the data set.
 """
 import argparse
 import codecs
-import json
 import os
 from pathlib import Path
 
@@ -89,7 +88,7 @@ def create_manifest(data_dir, manifest_path_prefix):
                 duration = float(len(audio_data) / samplerate)
                 text = transcript_dict[audio_id]
                 json_lines.append(audio_path)
-                reference_lines.append(str(total_num+1) + "\t" + text)
+                reference_lines.append(str(total_num + 1) + "\t" + text)
 
                 total_sec += duration
                 total_text += len(text)
@@ -106,6 +105,7 @@ def create_manifest(data_dir, manifest_path_prefix):
 
         manifest_dir = os.path.dirname(manifest_path_prefix)
 
+
 def prepare_dataset(url, md5sum, target_dir, manifest_path=None):
     """Download, unpack and create manifest file."""
     data_dir = os.path.join(target_dir, 'data_aishell')