fix code style

openvinotoolkit · Aug 26, 2024 · 4fc3e73 · 4fc3e73
1 parent 132950a
commit 4fc3e73
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Showing 13 changed files with 25 additions and 51 deletions.
diff --git a/.ci/patch_notebooks.py b/.ci/patch_notebooks.py
@@ -10,7 +10,7 @@
 EXCLUDED_NOTEBOOKS = ["data-preparation-ct-scan.ipynb", "pytorch-monai-training.ipynb"]
 
 DEVICE_WIDGET = "device = widgets.Dropdown("
-DEVICE_WIDGET_NEW = "device = device_widget("
+DEVICE_WIDGET_NEW = "device_widget("
 
 
 def disable_gradio_debug(nb, notebook_path):

diff --git a/notebooks/efficient-sam/efficient-sam.ipynb b/notebooks/efficient-sam/efficient-sam.ipynb
@@ -111,12 +111,12 @@
     "import requests\n",
     "\n",
     "r = requests.get(\n",
-    "    url='https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py',\n",
+    "    url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py\",\n",
     ")\n",
     "\n",
-    "open('notebook_utils.py', 'w').write(r.text)\n",
+    "open(\"notebook_utils.py\", \"w\").write(r.text)\n",
     "\n",
-    "from notebook_utils import download_file, device_widget"
+    "from notebook_utils import download_file, device_widget, quantization_widget  # noqa: F401"
    ]
   },
   {
@@ -622,11 +622,7 @@
     }
    ],
    "source": [
-    "to_quantize = widgets.Checkbox(\n",
-    "    value=True,\n",
-    "    description=\"Quantization\",\n",
-    "    disabled=False,\n",
-    ")\n",
+    "to_quantize = quantization_widget()\n",
     "\n",
     "to_quantize"
    ]

diff --git a/notebooks/hello-detection/hello-detection.ipynb b/notebooks/hello-detection/hello-detection.ipynb
@@ -188,7 +188,6 @@
     }
    ],
    "source": [
-    "\n",
     "device = device_widget()\n",
     "device"
    ]

diff --git a/notebooks/llm-rag-langchain/llm-rag-langchain.ipynb b/notebooks/llm-rag-langchain/llm-rag-langchain.ipynb
@@ -203,7 +203,6 @@
    "outputs": [],
    "source": [
     "from pathlib import Path\n",
-    "import openvino as ov\n",
     "import torch\n",
     "import ipywidgets as widgets\n",
     "from transformers import (\n",

diff --git a/notebooks/llm-rag-llamaindex/llm-rag-llamaindex.ipynb b/notebooks/llm-rag-llamaindex/llm-rag-llamaindex.ipynb
@@ -215,7 +215,6 @@
    "outputs": [],
    "source": [
     "from pathlib import Path\n",
-    "import openvino as ov\n",
     "import ipywidgets as widgets"
    ]
   },

diff --git a/notebooks/object-detection-webcam/object-detection.ipynb b/notebooks/object-detection-webcam/object-detection.ipynb
@@ -203,8 +203,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import ipywidgets as widgets\n",
-    "\n",
     "core = ov.Core()\n",
     "\n",
     "device = utils.device_widget()\n",

diff --git a/notebooks/paint-by-example/paint-by-example.ipynb b/notebooks/paint-by-example/paint-by-example.ipynb
@@ -888,6 +888,7 @@
     "\n",
     "core = ov.Core()\n",
     "\n",
+    "\n",
     "def get_ov_pipeline():\n",
     "    image_encoder_inpaint = core.compile_model(IMAGE_ENCODER_OV_PATH_INPAINT, device.value)\n",
     "    unet_model_inpaint = core.compile_model(UNET_OV_PATH_INPAINT, device.value)\n",

diff --git a/...h-quantization-sparsity-aware-training/pytorch-quantization-sparsity-aware-training.ipynb b/...h-quantization-sparsity-aware-training/pytorch-quantization-sparsity-aware-training.ipynb
@@ -658,8 +658,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "\n",
-    "\n",
     "# Initialize OpenVINO runtime\n",
     "core = ov.Core()\n",
     "device = device_widget()\n",

diff --git a/notebooks/pytorch-to-openvino/pytorch-onnx-to-openvino.ipynb b/notebooks/pytorch-to-openvino/pytorch-onnx-to-openvino.ipynb
@@ -113,14 +113,7 @@
     "\n",
     "open(\"notebook_utils.py\", \"w\").write(r.text)\n",
     "\n",
-    "from notebook_utils import (\n",
-    "    segmentation_map_to_image,\n",
-    "    viz_result_image,\n",
-    "    SegmentationMap,\n",
-    "    Label,\n",
-    "    download_file,\n",
-    "    device_widget\n",
-    ")"
+    "from notebook_utils import segmentation_map_to_image, viz_result_image, SegmentationMap, Label, download_file, device_widget"
    ]
   },
   {

diff --git a/notebooks/vehicle-detection-and-recognition/vehicle-detection-and-recognition.ipynb b/notebooks/vehicle-detection-and-recognition/vehicle-detection-and-recognition.ipynb
@@ -188,7 +188,7 @@
     }
    ],
    "source": [
-    "device = device_widget()\n",
+    "device = utils.device_widget()\n",
     "\n",
     "device"
    ]

diff --git a/notebooks/yolov10-optimization/yolov10-optimization.ipynb b/notebooks/yolov10-optimization/yolov10-optimization.ipynb
@@ -484,6 +484,7 @@
    "outputs": [],
    "source": [
     "import openvino as ov\n",
+    "\n",
     "core = ov.Core()\n",
     "\n",
     "ov_model = core.read_model(ov_model_path)\n",

diff --git a/notebooks/yolov8-optimization/yolov8-instance-segmentation.ipynb b/notebooks/yolov8-optimization/yolov8-instance-segmentation.ipynb
@@ -345,8 +345,6 @@
     }
    ],
    "source": [
-    "\n",
-    "\n",
     "device = device_widget()\n",
     "\n",
     "device"

diff --git a/notebooks/yolov8-optimization/yolov8-object-detection.ipynb b/notebooks/yolov8-optimization/yolov8-object-detection.ipynb
@@ -138,7 +138,7 @@
     "\n",
     "open(\"notebook_utils.py\", \"w\").write(r.text)\n",
     "\n",
-    "from notebook_utils import download_file, VideoPlayer"
+    "from notebook_utils import download_file, VideoPlayer, device_widget, quantization_widget"
    ]
   },
   {
@@ -330,17 +330,7 @@
     }
    ],
    "source": [
-    "import ipywidgets as widgets\n",
-    "import openvino as ov\n",
-    "\n",
-    "core = ov.Core()\n",
-    "\n",
-    "device = widgets.Dropdown(\n",
-    "    options=core.available_devices + [\"AUTO\"],\n",
-    "    value=\"AUTO\",\n",
-    "    description=\"Device:\",\n",
-    "    disabled=False,\n",
-    ")\n",
+    "device = device_widget()\n",
     "\n",
     "device"
    ]
@@ -387,6 +377,7 @@
    ],
    "source": [
     "import torch\n",
+    "import openvino as ov\n",
     "\n",
     "core = ov.Core()\n",
     "\n",
@@ -785,15 +776,10 @@
     }
    ],
    "source": [
-    "import ipywidgets as widgets\n",
-    "\n",
     "int8_model_det_path = models_dir / f\"{DET_MODEL_NAME}_openvino_int8_model/{DET_MODEL_NAME}.xml\"\n",
+    "quantized_det_model = None\n",
     "\n",
-    "to_quantize = widgets.Checkbox(\n",
-    "    value=True,\n",
-    "    description=\"Quantization\",\n",
-    "    disabled=False,\n",
-    ")\n",
+    "to_quantize = quantization_widget()\n",
     "\n",
     "to_quantize"
    ]
@@ -1395,7 +1381,7 @@
    "source": [
     "from openvino.preprocess import PrePostProcessor\n",
     "\n",
-    "ppp = PrePostProcessor(quantized_det_model)"
+    "ppp = PrePostProcessor(quantized_det_model if quantized_det_model is not None else det_model)"
    ]
   },
   {
@@ -1495,10 +1481,13 @@
    "outputs": [],
    "source": [
     "quantized_model_with_preprocess = ppp.build()\n",
-    "ov.save_model(\n",
-    "    quantized_model_with_preprocess,\n",
-    "    str(int8_model_det_path.with_name(f\"{DET_MODEL_NAME}_with_preprocess.xml\")),\n",
-    ")"
+    "\n",
+    "with_preprocess_path = (\n",
+    "    int8_model_det_path.with_name(f\"{DET_MODEL_NAME}_with_preprocess.xml\")\n",
+    "    if quantized_det_model is not None\n",
+    "    else det_model_path.with_name(f\"{DET_MODEL_NAME}_with_preprocess.xml\")\n",
+    ")\n",
+    "ov.save_model(quantized_model_with_preprocess, str(with_preprocess_path))"
    ]
   },
   {
@@ -1521,6 +1510,7 @@
     "import cv2\n",
     "import numpy as np\n",
     "from ultralytics.utils.plotting import colors\n",
+    "import random\n",
     "\n",
     "\n",
     "def plot_one_box(\n",
@@ -1792,6 +1782,8 @@
     "import time\n",
     "from IPython import display\n",
     "\n",
+    "det_ov_model\n",
+    "\n",
     "\n",
     "# Main processing function to run object detection.\n",
     "def run_object_detection(\n",