[ci/cd] try to pass ut

test/wenet/cli/test_model.py

@@ -2,25 +2,34 @@
 # -*- coding: utf-8 -*-
 # Copyright [2023-12-12] <[email protected], Xingchen Song>
 
+import os
 import pytest
 
 from wenet.cli.hub import download
 from wenet.cli.model import Model
 
 
-@pytest.mark.parametrize("model_link", [
-    "https://wenet.org.cn/downloads?models=wenet&version=aishell_u2pp_conformer_libtorch.tar.gz",
-    "https://wenet.org.cn/downloads?models=wenet&version=aishell2_u2pp_conformer_libtorch.tar.gz",
-    "https://wenet.org.cn/downloads?models=wenet&version=gigaspeech_u2pp_conformer_libtorch.tar.gz",
-    "https://wenet.org.cn/downloads?models=wenet&version=librispeech_u2pp_conformer_libtorch.tar.gz",
-    "https://wenet.org.cn/downloads?models=wenet&version=multi_cn_unified_conformer_libtorch.tar.gz",
-    "https://wenet.org.cn/downloads?models=wenet&version=wenetspeech_u2pp_conformer_libtorch.tar.gz"
+@pytest.mark.parametrize("model", [
+    "aishell_u2pp_conformer_libtorch.tar.gz",
+    "aishell2_u2pp_conformer_libtorch.tar.gz",
+    "gigaspeech_u2pp_conformer_libtorch.tar.gz",
+    "librispeech_u2pp_conformer_libtorch.tar.gz",
+    "multi_cn_unified_conformer_libtorch.tar.gz",
+    "wenetspeech_u2pp_conformer_libtorch.tar.gz"
 ])
-def test_model(model_link):
-    dest = model_link.split('=')[-1].split('.')[0]  # aishell_u2pp_conformer_libtorch
-    dataset = model_link.split('_')[-4].split('=')[-1]  # aishell
-    download(model_link, dest=dest)
-    model = Model(model_link,
+def test_model(model):
+    dest = model.split('.')[0]  # aishell_u2pp_conformer_libtorch
+    dataset = model.split('_')[0]  # aishell
+    if not os.path.exists(dest):
+        os.makedirs(dest)
+    response = requests.get(
+        "https://modelscope.cn/api/v1/datasets/wenet/wenet_pretrained_models/oss/tree"  # noqa
+    )
+    model_info = next(data for data in response.json()["Data"]
+                      if data["Key"] == model)
+    model_url = model_info['Url']
+    download(model_url, dest=dest, only_child=True)
+    model = Model(dest,
                   gpu=-1,
                   beam=5,
                   resample_rate=16000)