Merge 0cc6b8aaef4c637c674f8a6660ce8f59124a240e into fef65d40feee6fa5c72d2b6626ed3fbc75ab9192

GPT_SoVITS/AR/modules/patched_mha_with_cache.py

@@ -12,33 +12,33 @@ import torch
 
 
 def multi_head_attention_forward_patched(
-    query,
+    query: Tensor,
-    key,
+    key: Tensor,
-    value,
+    value: Tensor,
-    embed_dim_to_check,
+    embed_dim_to_check: int,
-    num_heads,
+    num_heads: int,
-    in_proj_weight,
+    in_proj_weight: Optional[Tensor],
-    in_proj_bias,
+    in_proj_bias: Optional[Tensor],
-    bias_k,
+    bias_k: Optional[Tensor],
-    bias_v,
+    bias_v: Optional[Tensor],
-    add_zero_attn,
+    add_zero_attn: bool,
     dropout_p: float,
-    out_proj_weight,
+    out_proj_weight: Tensor,
-    out_proj_bias,
+    out_proj_bias: Optional[Tensor],
-    training = True,
+    training: bool = True,
-    key_padding_mask = None,
+    key_padding_mask: Optional[Tensor] = None,
-    need_weights = True,
+    need_weights: bool = True,
-    attn_mask = None,
+    attn_mask: Optional[Tensor] = None,
-    use_separate_proj_weight = False,
+    use_separate_proj_weight: bool = False,
-    q_proj_weight = None,
+    q_proj_weight: Optional[Tensor] = None,
-    k_proj_weight = None,
+    k_proj_weight: Optional[Tensor] = None,
-    v_proj_weight = None,
+    v_proj_weight: Optional[Tensor] = None,
-    static_k = None,
+    static_k: Optional[Tensor] = None,
-    static_v = None,
+    static_v: Optional[Tensor] = None,
-    average_attn_weights = True,
+    average_attn_weights: bool = True,
-    is_causal = False,
+    is_causal: bool = False,
     cache=None,
-):
+) -> Tuple[Tensor, Optional[Tensor]]:
     r"""
     Args:
         query, key, value: map a query and a set of key-value pairs to an output.

GPT_SoVITS/prepare_datasets/3-get-semantic.py

@@ -81,7 +81,7 @@ if os.path.exists(semantic_path) == False:
     # utils.load_checkpoint(pretrained_s2G, vq_model, None, True)
     print(
         vq_model.load_state_dict(
-            torch.load(pretrained_s2G, map_location="cpu", weights_only=False)["weight"], strict=False
+            torch.load(pretrained_s2G, map_location="cpu")["weight"], strict=False
         )
     )
 

install.sh

@@ -2,13 +2,8 @@
 
 # 安装构建工具
 # Install build tools
-echo "Installing GCC..."
 conda install -c conda-forge gcc=14
-
-echo "Installing G++..."
 conda install -c conda-forge gxx
-
-echo "Installing ffmpeg and cmake..."
 conda install ffmpeg cmake
 
 # 设置编译环境
@@ -17,60 +12,10 @@ export CMAKE_MAKE_PROGRAM="$CONDA_PREFIX/bin/cmake"
 export CC="$CONDA_PREFIX/bin/gcc"
 export CXX="$CONDA_PREFIX/bin/g++"
 
-echo "Checking for CUDA installation..."
-if command -v nvidia-smi &> /dev/null; then
-    USE_CUDA=true
-    echo "CUDA found."
-else
-    echo "CUDA not found."
-    USE_CUDA=false
-fi
-
-
-if [ "$USE_CUDA" = false ]; then
-    echo "Checking for ROCm installation..."
-    if [ -d "/opt/rocm" ]; then
-        USE_ROCM=true
-        echo "ROCm found."
-        if grep -qi "microsoft" /proc/version; then
-            echo "You are running WSL."
-            IS_WSL=true
-        else
-            echo "You are NOT running WSL."
-            IS_WSL=false
-        fi
-    else
-        echo "ROCm not found."
-        USE_ROCM=false
-    fi
-fi
-
-if [ "$USE_CUDA" = true ]; then
-    echo "Installing PyTorch with CUDA support..."
 conda install pytorch==2.1.1 torchvision==0.16.1 torchaudio==2.1.1 pytorch-cuda=11.8 -c pytorch -c nvidia
-elif [ "$USE_ROCM" = true ] ; then
-    echo "Installing PyTorch with ROCm support..."
-    pip install torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 --index-url https://download.pytorch.org/whl/rocm6.2
-else
-    echo "Installing PyTorch for CPU..."
-    conda install pytorch==2.1.1 torchvision==0.16.1 torchaudio==2.1.1 cpuonly -c pytorch
-fi
-
-
-echo "Installing Python dependencies from requirements.txt..."
 
 # 刷新环境
 # Refresh environment
 hash -r
+
 pip install -r requirements.txt
-
-if [ "$USE_ROCM" = true ] && [ "$IS_WSL" = true ] ; then
-    echo "Update to WSL compatible runtime lib..."
-    location=`pip show torch | grep Location | awk -F ": " '{print $2}'`
-    cd ${location}/torch/lib/
-    rm libhsa-runtime64.so*
-    cp /opt/rocm/lib/libhsa-runtime64.so.1.2 libhsa-runtime64.so
-fi
-
-echo "Installation completed successfully!"
-

tools/my_utils.py

@@ -32,7 +32,7 @@ def clean_path(path_str:str):
     if path_str.endswith(('\\','/')):
         return clean_path(path_str[0:-1])
     path_str = path_str.replace('/', os.sep).replace('\\', os.sep)
-    return path_str.strip(" \'\n\"\u202a")#path_str.strip(" ").strip('\'').strip("\n").strip('"').strip(" ").strip("\u202a")
+    return path_str.strip(" ").strip('\'').strip("\n").strip('"').strip(" ").strip("\u202a")
 
 
 def check_for_existance(file_list:list=None,is_train=False,is_dataset_processing=False):