From ed2370591f6c352b4bb8f065ff8c6d0fc8629227 Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期五, 10 三月 2023 10:29:34 +0800
Subject: [PATCH] update tp_inference

---
 funasr/bin/tp_inference.py |   28 ++++++++++++++++++++++------
 1 files changed, 22 insertions(+), 6 deletions(-)

diff --git a/funasr/bin/tp_inference.py b/funasr/bin/tp_inference.py
index baa7485..3bd3324 100644
--- a/funasr/bin/tp_inference.py
+++ b/funasr/bin/tp_inference.py
@@ -1,5 +1,6 @@
 import argparse
 import logging
+from optparse import Option
 import sys
 import json
 from pathlib import Path
@@ -11,15 +12,12 @@
 from typing import Union
 from typing import Dict
 
-import math
 import numpy as np
 import torch
 from typeguard import check_argument_types
-from typeguard import check_return_type
 
 from funasr.fileio.datadir_writer import DatadirWriter
-from funasr.modules.scorers.scorer_interface import BatchScorerInterface
-from funasr.modules.subsampling import TooShortUttError
+from funasr.datasets.preprocessor import LMPreprocessor
 from funasr.tasks.asr import ASRTaskAligner as ASRTask
 from funasr.torch_utils.device_funcs import to_device
 from funasr.torch_utils.set_all_random_seed import set_all_random_seed
@@ -28,7 +26,6 @@
 from funasr.utils.types import str2bool
 from funasr.utils.types import str2triple_str
 from funasr.utils.types import str_or_none
-from funasr.utils import asr_utils, wav_utils, postprocess_utils
 from funasr.models.frontend.wav_frontend import WavFrontend
 from funasr.text.token_id_converter import TokenIDConverter
 
@@ -191,6 +188,8 @@
         dtype: str = "float32",
         seed: int = 0,
         num_workers: int = 1,
+        split_with_space: bool = True,
+        seg_dict_file: Optional[str] = None,
         **kwargs,
 ):
     inference_pipeline = inference_modelscope(
@@ -206,6 +205,8 @@
         dtype=dtype,
         seed=seed,
         num_workers=num_workers,
+        split_with_space=split_with_space,
+        seg_dict_file=seg_dict_file,
         **kwargs,
     )
     return inference_pipeline(data_path_and_name_and_type, raw_inputs)
@@ -226,6 +227,8 @@
         dtype: str = "float32",
         seed: int = 0,
         num_workers: int = 1,
+        split_with_space: bool = True,
+        seg_dict_file: Optional[str] = None,
         **kwargs,
 ):
     assert check_argument_types()
@@ -256,6 +259,19 @@
     )
     logging.info("speechtext2timestamp_kwargs: {}".format(speechtext2timestamp_kwargs))
     speechtext2timestamp = SpeechText2Timestamp(**speechtext2timestamp_kwargs)
+
+    preprocessor = LMPreprocessor(
+        train=False,
+        token_type=speechtext2timestamp.tp_train_args.token_type,
+        token_list=speechtext2timestamp.tp_train_args,
+        bpemodel=None,
+        text_cleaner=None,
+        g2p_type=None,
+        text_name="text",
+        non_linguistic_symbols=speechtext2timestamp.tp_train_args.non_linguistic_symbols,
+        split_with_space=split_with_space,
+        seg_dict_file=seg_dict_file,
+    )
     
     def _forward(
             data_path_and_name_and_type,
@@ -277,7 +293,7 @@
             batch_size=batch_size,
             key_file=key_file,
             num_workers=num_workers,
-            preprocess_fn=ASRTask.build_preprocess_fn(speechtext2timestamp.tp_train_args, False),
+            preprocess_fn=LMPreprocessor,
             collate_fn=ASRTask.build_collate_fn(speechtext2timestamp.tp_train_args, False),
             allow_variable_data_keys=allow_variable_data_keys,
             inference=True,

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