Using Wget for new ckpt downloadsA

.pylintrc

@@ -292,13 +292,6 @@ max-line-length=120
 # Maximum number of lines in a module.
 max-module-lines=1000
 
-# List of optional constructs for which whitespace checking is disabled. `dict-
-# separator` is used to allow tabulation in dicts, etc.: {1  : 1,\n222: 2}.
-# `trailing-comma` allows a space between comma and closing bracket: (a, ).
-# `empty-line` allows space-only lines.
-no-space-check=trailing-comma,
-               dict-separator
-
 # Allow the body of a class to be on the same line as the declaration if body
 # contains single statement.
 single-line-class-stmt=no
@@ -528,5 +521,5 @@ min-public-methods=2
 
 # Exceptions that will emit a warning when being caught. Defaults to
 # "BaseException, Exception".
-overgeneral-exceptions=BaseException,
+overgeneral-exceptions=builtins.BaseException,
-                       Exception
+                       builtins.Exception

matcha/app.py

@@ -29,8 +29,15 @@ args = Namespace(
 
 CURRENTLY_LOADED_MODEL = args.model
 
-MATCHA_TTS_LOC = lambda x: LOCATION / f"{x}.ckpt"  # noqa: E731
+
-VOCODER_LOC = lambda x: LOCATION / f"{x}"  # noqa: E731
+def MATCHA_TTS_LOC(x):
+    return LOCATION / f"{x}.ckpt"
+
+
+def VOCODER_LOC(x):
+    return LOCATION / f"{x}"
+
+
 LOGO_URL = "https://shivammehta25.github.io/Matcha-TTS/images/logo.png"
 RADIO_OPTIONS = {
     "Multi Speaker (VCTK)": {
@@ -44,9 +51,9 @@ RADIO_OPTIONS = {
 }
 
 # Ensure all the required models are downloaded
-assert_model_downloaded(MATCHA_TTS_LOC("matcha_ljspeech"), MATCHA_URLS["matcha_ljspeech"])
+assert_model_downloaded(MATCHA_TTS_LOC("matcha_ljspeech"), MATCHA_URLS["matcha_ljspeech"], use_wget=True)
 assert_model_downloaded(VOCODER_LOC("hifigan_T2_v1"), VOCODER_URLS["hifigan_T2_v1"])
-assert_model_downloaded(MATCHA_TTS_LOC("matcha_vctk"), MATCHA_URLS["matcha_vctk"])
+assert_model_downloaded(MATCHA_TTS_LOC("matcha_vctk"), MATCHA_URLS["matcha_vctk"], use_wget=True)
 assert_model_downloaded(VOCODER_LOC("hifigan_univ_v1"), VOCODER_URLS["hifigan_univ_v1"])
 
 device = get_device(args)

matcha/cli.py

@@ -74,7 +74,7 @@ def assert_required_models_available(args):
         model_path = args.checkpoint_path
     else:
         model_path = save_dir / f"{args.model}.ckpt"
-        assert_model_downloaded(model_path, MATCHA_URLS[args.model])
+        assert_model_downloaded(model_path, MATCHA_URLS[args.model], use_wget=True)
 
     vocoder_path = save_dir / f"{args.vocoder}"
     assert_model_downloaded(vocoder_path, VOCODER_URLS[args.vocoder])

matcha/utils/utils.py

@@ -115,7 +115,7 @@ def get_metric_value(metric_dict: Dict[str, Any], metric_name: str) -> float:
         return None
 
     if metric_name not in metric_dict:
-        raise Exception(
+        raise ValueError(
             f"Metric value not found! <metric_name={metric_name}>\n"
             "Make sure metric name logged in LightningModule is correct!\n"
             "Make sure `optimized_metric` name in `hparams_search` config is correct!"
@@ -208,8 +208,10 @@ def get_user_data_dir(appname="matcha_tts"):
 def assert_model_downloaded(checkpoint_path, url, use_wget=False):
     if Path(checkpoint_path).exists():
         log.debug(f"[+] Model already present at {checkpoint_path}!")
+        print(f"[+] Model already present at {checkpoint_path}!")
         return
     log.info(f"[-] Model not found at {checkpoint_path}! Will download it")
+    print(f"[-] Model not found at {checkpoint_path}! Will download it")
     checkpoint_path = str(checkpoint_path)
     if not use_wget:
         gdown.download(url=url, output=checkpoint_path, quiet=False, fuzzy=True)