Fixed indentation error

Dockerfile

@@ -16,22 +16,22 @@ RUN pip install --trusted-host pypi.python.org -r requirements.txt && \
 EXPOSE 80
 
 # Set the TORTOISE_MODELS_DIR environment variable
-ENV TORTOISE_MODELS_DIR tortoise/models/pretrained_models
+# ENV TORTOISE_MODELS_DIR tortoise/models/pretrained_models
 
 # Create the directory for pretrained models
-RUN mkdir -p $TORTOISE_MODELS_DIR
+# RUN mkdir -p $TORTOISE_MODELS_DIR
 
 # Download all the models
-RUN wget -O $TORTOISE_MODELS_DIR/autoregressive.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/autoregressive.pth && \
-    wget -O $TORTOISE_MODELS_DIR/classifier.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/classifier.pth && \
-    wget -O $TORTOISE_MODELS_DIR/clvp2.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/clvp2.pth && \
-    wget -O $TORTOISE_MODELS_DIR/cvvp.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/cvvp.pth && \
-    wget -O $TORTOISE_MODELS_DIR/diffusion_decoder.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/diffusion_decoder.pth && \
-    wget -O $TORTOISE_MODELS_DIR/vocoder.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/vocoder.pth && \
-    wget -O $TORTOISE_MODELS_DIR/rlg_auto.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/rlg_auto.pth && \
-    wget -O $TORTOISE_MODELS_DIR/rlg_diffuser.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/rlg_diffuser.pth && \
-    wget -O $TORTOISE_MODELS_DIR/bigvgan_base_24khz_100band_g.pth https://drive.google.com/uc?id=1_cKskUDuvxQJUEBwdgjAxKuDTUW6kPdY && \
-    wget -O $TORTOISE_MODELS_DIR/bigvgan_24khz_100band_g.pth https://drive.google.com/uc?id=1wmP_mAs7d00KHVfVEl8B5Gb72Kzpcavp
+# RUN wget -O $TORTOISE_MODELS_DIR/autoregressive.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/autoregressive.pth && \
+#     wget -O $TORTOISE_MODELS_DIR/classifier.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/classifier.pth && \
+#     wget -O $TORTOISE_MODELS_DIR/clvp2.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/clvp2.pth && \
+#     wget -O $TORTOISE_MODELS_DIR/cvvp.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/cvvp.pth && \
+#     wget -O $TORTOISE_MODELS_DIR/diffusion_decoder.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/diffusion_decoder.pth && \
+#     wget -O $TORTOISE_MODELS_DIR/vocoder.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/vocoder.pth && \
+#     wget -O $TORTOISE_MODELS_DIR/rlg_auto.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/rlg_auto.pth && \
+#     wget -O $TORTOISE_MODELS_DIR/rlg_diffuser.pth https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/rlg_diffuser.pth && \
+#     wget -O $TORTOISE_MODELS_DIR/bigvgan_base_24khz_100band_g.pth https://drive.google.com/uc?id=1_cKskUDuvxQJUEBwdgjAxKuDTUW6kPdY && \
+#     wget -O $TORTOISE_MODELS_DIR/bigvgan_24khz_100band_g.pth https://drive.google.com/uc?id=1wmP_mAs7d00KHVfVEl8B5Gb72Kzpcavp
 
 RUN ls -la /app
 

tortoise/models/utils.py

@@ -11,12 +11,12 @@ import progressbar
 
 D_STEM = "https://drive.google.com/uc?id="
 
-# DEFAULT_MODELS_DIR = os.path.join(
-#     os.path.expanduser("~"), ".cache", "tortoise", "models"
-# )
-# MODELS_DIR = os.environ.get("TORTOISE_MODELS_DIR", DEFAULT_MODELS_DIR)
+DEFAULT_MODELS_DIR = os.path.join(
+    os.path.expanduser("~"), ".cache", "tortoise", "models"
+)
+MODELS_DIR = os.environ.get("TORTOISE_MODELS_DIR", DEFAULT_MODELS_DIR)
 
-MODELS_DIR = os.environ.get("TORTOISE_MODELS_DIR")
+# MODELS_DIR = os.environ.get("TORTOISE_MODELS_DIR")
 MODELS = {
     "autoregressive.pth": "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/autoregressive.pth",
     "classifier.pth": "https://huggingface.co/jbetker/tortoise-tts-v2/resolve/main/.models/classifier.pth",
@@ -77,5 +77,5 @@ def get_model_path(model_name, models_dir=MODELS_DIR):
         download_models([model_name])
     return model_path
 
-# if __name__ == "__main__":
-    # download_models() # to download all models
+if __name__ == "__main__":
+    download_models() # to download all models