From 4137f5cf26e7c4b40853959cd2574edfde03aa60 Mon Sep 17 00:00:00 2001
From: 志浩 <neo.dzh@alibaba-inc.com>
Date: 星期五, 07 四月 2023 21:03:34 +0800
Subject: [PATCH] Merge branch 'main' of github.com:alibaba-damo-academy/FunASR into dev_dzh
---
funasr/runtime/python/utils/infer.py | 48 ++++++++++++++++++++++++++++++++++++++++++++++++
1 files changed, 48 insertions(+), 0 deletions(-)
diff --git a/funasr/runtime/python/utils/infer.py b/funasr/runtime/python/utils/infer.py
new file mode 100644
index 0000000..e27e393
--- /dev/null
+++ b/funasr/runtime/python/utils/infer.py
@@ -0,0 +1,48 @@
+import os
+import time
+import sys
+import librosa
+from funasr.utils.types import str2bool
+
+import argparse
+parser = argparse.ArgumentParser()
+parser.add_argument('--model_dir', type=str, required=True)
+parser.add_argument('--backend', type=str, default='onnx', help='["onnx", "torch"]')
+parser.add_argument('--wav_file', type=str, default=None, help='amp fallback number')
+parser.add_argument('--quantize', type=str2bool, default=False, help='quantized model')
+parser.add_argument('--intra_op_num_threads', type=int, default=1, help='intra_op_num_threads for onnx')
+parser.add_argument('--output_dir', type=str, default=None, help='amp fallback number')
+args = parser.parse_args()
+
+
+from funasr.runtime.python.libtorch.funasr_torch import Paraformer
+if args.backend == "onnx":
+ from funasr.runtime.python.onnxruntime.funasr_onnx import Paraformer
+
+model = Paraformer(args.model_dir, batch_size=1, quantize=args.quantize, intra_op_num_threads=args.intra_op_num_threads)
+
+wav_file_f = open(args.wav_file, 'r')
+wav_files = wav_file_f.readlines()
+
+output_dir = args.output_dir
+if not os.path.exists(output_dir):
+ os.makedirs(output_dir)
+if os.name == 'nt': # Windows
+ newline = '\r\n'
+else: # Linux Mac
+ newline = '\n'
+text_f = open(os.path.join(output_dir, "text"), "w", newline=newline)
+token_f = open(os.path.join(output_dir, "token"), "w", newline=newline)
+
+for i, wav_path_i in enumerate(wav_files):
+ wav_name, wav_path = wav_path_i.strip().split()
+ result = model(wav_path)
+ text_i = "{} {}\n".format(wav_name, result[0]['preds'][0])
+ token_i = "{} {}\n".format(wav_name, result[0]['preds'][1])
+ text_f.write(text_i)
+ text_f.flush()
+ token_f.write(token_i)
+ token_f.flush()
+text_f.close()
+token_f.close()
+
--
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