👷 Use black[jupyter] (#847)

* 👷 Use black[jupyter]

* 👷 Add missing matrix

.github/workflows/pull_format.yml

@@ -4,10 +4,19 @@ on: [pull_request]
 
 permissions:
   contents: write
+
 jobs:
   pull_format:
-    runs-on: ubuntu-latest
+    runs-on: ${{ matrix.os }}
+
+    strategy:
+      matrix:
+        python-version: ["3.10"]
+        os: [ubuntu-latest]
+      fail-fast: false
+
     continue-on-error: true
+
     steps:
       - name: checkout
         continue-on-error: true
@@ -16,14 +25,13 @@ jobs:
           ref: ${{ github.head_ref }}
           fetch-depth: 0
 
-          
       - name: Set up Python ${{ matrix.python-version }}
         uses: actions/setup-python@v4
         with:
           python-version: ${{ matrix.python-version }}
 
       - name: Install Black
-        run: pip install black
+        run: pip install "black[jupyter]"
 
       - name: Run Black
         # run: black $(git ls-files '*.py')

.github/workflows/push_format.yml

@@ -8,9 +8,17 @@ on:
 permissions:
   contents: write
   pull-requests: write
+
 jobs:
   push_format:
-    runs-on: ubuntu-latest
+    runs-on: ${{ matrix.os }}
+
+    strategy:
+      matrix:
+        python-version: ["3.10"]
+        os: [ubuntu-latest]
+      fail-fast: false
+
     steps:
       - uses: actions/checkout@v3
         with:
@@ -22,7 +30,7 @@ jobs:
           python-version: ${{ matrix.python-version }}
 
       - name: Install Black
-        run: pip install black
+        run: pip install "black[jupyter]"
 
       - name: Run Black
         # run: black $(git ls-files '*.py')

Retrieval_based_Voice_Conversion_WebUI.ipynb

@@ -146,7 +146,8 @@
     "# @title 挂载谷歌云盘\n",
     "\n",
     "from google.colab import drive\n",
-        "drive.mount('/content/drive')"
+    "\n",
+    "drive.mount(\"/content/drive\")"
    ],
    "metadata": {
     "id": "jwu07JgqoFON"
@@ -160,7 +161,9 @@
     "# @title 从谷歌云盘加载打包好的数据集到/content/dataset\n",
     "\n",
     "# @markdown 数据集位置\n",
-        "DATASET = \"/content/drive/MyDrive/dataset/lulu20230327_32k.zip\"  #@param {type:\"string\"}\n",
+    "DATASET = (\n",
+    "    \"/content/drive/MyDrive/dataset/lulu20230327_32k.zip\"  # @param {type:\"string\"}\n",
+    ")\n",
     "\n",
     "!mkdir -p /content/dataset\n",
     "!unzip -d /content/dataset -B {DATASET}"
@@ -259,7 +262,7 @@
     "# @markdown 使用的进程数\n",
     "THREADCOUNT = 8  # @param {type:\"integer\"}\n",
     "\n",
-        "!python3 trainset_preprocess_pipeline_print.py /content/dataset {BITRATE} {THREADCOUNT} logs/{MODELNAME} True\n"
+    "!python3 trainset_preprocess_pipeline_print.py /content/dataset {BITRATE} {THREADCOUNT} logs/{MODELNAME} True"
    ],
    "metadata": {
     "id": "ZKAyuKb9J6dz"
@@ -280,7 +283,7 @@
     "\n",
     "!python3 extract_f0_print.py logs/{MODELNAME} {THREADCOUNT} {ALGO}\n",
     "\n",
-        "!python3 extract_feature_print.py cpu 1 0 0 logs/{MODELNAME}\n"
+    "!python3 extract_feature_print.py cpu 1 0 0 logs/{MODELNAME}"
    ],
    "metadata": {
     "id": "CrxJqzAUKmPJ"
@@ -309,7 +312,7 @@
     "# @markdown 是否仅保存最新的ckpt文件\n",
     "ONLYLATEST = 0  # @param {type:\"integer\"}\n",
     "\n",
-        "!python3 train_nsf_sim_cache_sid_load_pretrain.py -e lulu -sr {MODELSAMPLE} -f0 1 -bs {BATCHSIZE} -g {USEGPU} -te {MODELEPOCH} -se {EPOCHSAVE} -pg pretrained/f0G{MODELSAMPLE}.pth -pd pretrained/f0D{MODELSAMPLE}.pth -l {ONLYLATEST} -c {CACHEDATA}\n"
+    "!python3 train_nsf_sim_cache_sid_load_pretrain.py -e lulu -sr {MODELSAMPLE} -f0 1 -bs {BATCHSIZE} -g {USEGPU} -te {MODELEPOCH} -se {EPOCHSAVE} -pg pretrained/f0G{MODELSAMPLE}.pth -pd pretrained/f0D{MODELSAMPLE}.pth -l {ONLYLATEST} -c {CACHEDATA}"
    ],
    "metadata": {
     "id": "IMLPLKOaKj58"

Retrieval_based_Voice_Conversion_WebUI_v2.ipynb

@@ -154,7 +154,8 @@
     "# @title 挂载谷歌云盘\n",
     "\n",
     "from google.colab import drive\n",
-        "drive.mount('/content/drive')"
+    "\n",
+    "drive.mount(\"/content/drive\")"
    ]
   },
   {
@@ -168,7 +169,9 @@
     "# @title 从谷歌云盘加载打包好的数据集到/content/dataset\n",
     "\n",
     "# @markdown 数据集位置\n",
-        "DATASET = \"/content/drive/MyDrive/dataset/lulu20230327_32k.zip\"  #@param {type:\"string\"}\n",
+    "DATASET = (\n",
+    "    \"/content/drive/MyDrive/dataset/lulu20230327_32k.zip\"  # @param {type:\"string\"}\n",
+    ")\n",
     "\n",
     "!mkdir -p /content/dataset\n",
     "!unzip -d /content/dataset -B {DATASET}"
@@ -267,7 +270,7 @@
     "# @markdown 使用的进程数\n",
     "THREADCOUNT = 8  # @param {type:\"integer\"}\n",
     "\n",
-        "!python3 trainset_preprocess_pipeline_print.py /content/dataset {BITRATE} {THREADCOUNT} logs/{MODELNAME} True\n"
+    "!python3 trainset_preprocess_pipeline_print.py /content/dataset {BITRATE} {THREADCOUNT} logs/{MODELNAME} True"
    ]
   },
   {
@@ -288,7 +291,7 @@
     "\n",
     "!python3 extract_f0_print.py logs/{MODELNAME} {THREADCOUNT} {ALGO}\n",
     "\n",
-        "!python3 extract_feature_print.py cpu 1 0 0 logs/{MODELNAME}\n"
+    "!python3 extract_feature_print.py cpu 1 0 0 logs/{MODELNAME}"
    ]
   },
   {
@@ -317,7 +320,7 @@
     "# @markdown 是否仅保存最新的ckpt文件\n",
     "ONLYLATEST = 0  # @param {type:\"integer\"}\n",
     "\n",
-        "!python3 train_nsf_sim_cache_sid_load_pretrain.py -e lulu -sr {MODELSAMPLE} -f0 1 -bs {BATCHSIZE} -g {USEGPU} -te {MODELEPOCH} -se {EPOCHSAVE} -pg pretrained/f0G{MODELSAMPLE}.pth -pd pretrained/f0D{MODELSAMPLE}.pth -l {ONLYLATEST} -c {CACHEDATA}\n"
+    "!python3 train_nsf_sim_cache_sid_load_pretrain.py -e lulu -sr {MODELSAMPLE} -f0 1 -bs {BATCHSIZE} -g {USEGPU} -te {MODELEPOCH} -se {EPOCHSAVE} -pg pretrained/f0G{MODELSAMPLE}.pth -pd pretrained/f0D{MODELSAMPLE}.pth -l {ONLYLATEST} -c {CACHEDATA}"
    ]
   },
   {