From a8a849ce0556951cc8fb6b0a06ab6391c23e25e7 Mon Sep 17 00:00:00 2001
From: yhliang <68215459+yhliang-aslp@users.noreply.github.com>
Date: 星期日, 23 四月 2023 20:15:33 +0800
Subject: [PATCH] Merge pull request #406 from alibaba-damo-academy/main

---
 egs/aishell/transformer/utils/prepare_checkpoint.py |   31 -------------------------------
 1 files changed, 0 insertions(+), 31 deletions(-)

diff --git a/egs/aishell/transformer/utils/prepare_checkpoint.py b/egs/aishell/transformer/utils/prepare_checkpoint.py
index 01763d4..4d5e8a0 100644
--- a/egs/aishell/transformer/utils/prepare_checkpoint.py
+++ b/egs/aishell/transformer/utils/prepare_checkpoint.py
@@ -1,38 +1,7 @@
 import os
 import shutil
 
-from modelscope.pipelines import pipeline
-from modelscope.utils.constant import Tasks
 from modelscope.hub.snapshot_download import snapshot_download
-
-def modelscope_infer_after_finetune(params):
-    # prepare for decoding
-
-    try:
-        pretrained_model_path = snapshot_download(params["modelscope_model_name"], cache_dir=params["output_dir"])
-    except BaseException:
-        raise BaseException(f"Please download pretrain model from ModelScope firstly.")
-    shutil.copy(os.path.join(params["output_dir"], params["decoding_model_name"]), os.path.join(pretrained_model_path, "model.pb"))
-    decoding_path = os.path.join(params["output_dir"], "decode_results")
-    if os.path.exists(decoding_path):
-        shutil.rmtree(decoding_path)
-    os.mkdir(decoding_path)
-
-    # decoding
-    inference_pipeline = pipeline(
-        task=Tasks.auto_speech_recognition,
-        model=pretrained_model_path,
-        output_dir=decoding_path,
-        batch_size=params["batch_size"]
-    )
-    audio_in = os.path.join(params["data_dir"], "wav.scp")
-    inference_pipeline(audio_in=audio_in)
-
-    # computer CER if GT text is set
-    text_in = os.path.join(params["data_dir"], "text")
-    if os.path.exists(text_in):
-        text_proc_file = os.path.join(decoding_path, "1best_recog/text")
-        compute_wer(text_in, text_proc_file, os.path.join(decoding_path, "text.cer"))
 
 
 if __name__ == '__main__':

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