Finalize the standalone approach for the notebooks (#1942)

Ticket: CVS-138789

Changed notebooks (added fetching of separate files inside the notebook
if they don't exist):
-
[stable-diffusion-keras-cv](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/stable-diffusion-keras-cv)
-
[ct-segmentation-quantize](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/ct-segmentation-quantize)
-
[vision-background-removal](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/vision-background-removal)
-
[blip-visual-language-processing](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/blip-visual-language-processing)
-
[llm-question-answering](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/llm-question-answering)
-
[whisper-subtitles-generation](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/whisper-subtitles-generation)
-
[deepfloyd-if](https://github.com/openvinotoolkit/openvino_notebooks/blob/latest/notebooks/deepfloyd-if)

---------

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

notebooks/blip-visual-language-processing/blip-visual-language-processing.ipynb

@@ -255,6 +255,10 @@
     }
    ],
    "source": [
+    "from pathlib import Path\n",
+    "\n",
+    "if not Path(\"./utils.py\").exists():\n",
+    "    download_file(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/blip-visual-language-processing/utils.py\")\n",
     "from utils import visualize_results\n",
     "\n",
     "fig = visualize_results(raw_image, answer, question)"
@@ -616,6 +620,8 @@
    },
    "outputs": [],
    "source": [
+    "if not Path(\"./blip_model.py\").exists():\n",
+    "    download_file(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/blip-visual-language-processing/blip_model.py\")\n",
     "from blip_model import OVBlipModel\n",
     "\n",
     "ov_model = OVBlipModel(model.config, model.decoder_start_token_id, ov_vision_model, ov_text_encoder, text_decoder)\n",

notebooks/ct-segmentation-quantize/ct-scan-live-inference.ipynb

@@ -87,14 +87,16 @@
     "from monai.transforms import LoadImage\n",
     "import openvino as ov\n",
     "\n",
-    "from custom_segmentation import SegmentationModel\n",
-    "\n",
-    "# Fetch `notebook_utils` module\n",
     "import requests\n",
     "\n",
+    "# Fetch `notebook_utils` module\n",
     "r = requests.get(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py\")\n",
     "open(\"notebook_utils.py\", \"w\").write(r.text)\n",
-    "from notebook_utils import download_file"
+    "from notebook_utils import download_file\n",
+    "\n",
+    "if not Path(\"./custom_segmentation.py\").exists():\n",
+    "    download_file(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/ct-segmentation-quantize/custom_segmentation.py\")\n",
+    "from custom_segmentation import SegmentationModel"
    ]
   },
   {

notebooks/ct-segmentation-quantize/ct-segmentation-quantize-nncf.ipynb

@@ -142,17 +142,23 @@
     "from monai.transforms import LoadImage\n",
     "from nncf.common.logging.logger import set_log_level\n",
     "from torchmetrics import F1Score as F1\n",
+    "import requests\n",
     "\n",
-    "set_log_level(logging.ERROR)  # Disables all NNCF info and warning messages\n",
     "\n",
-    "from custom_segmentation import SegmentationModel\n",
-    "from async_pipeline import show_live_inference\n",
+    "set_log_level(logging.ERROR)  # Disables all NNCF info and warning messages\n",
     "\n",
     "# Fetch `notebook_utils` module\n",
-    "import requests\n",
-    "\n",
     "r = requests.get(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py\")\n",
-    "from notebook_utils import download_file"
+    "open(\"notebook_utils.py\", \"w\").write(r.text)\n",
+    "from notebook_utils import download_file\n",
+    "\n",
+    "if not Path(\"./custom_segmentation.py\").exists():\n",
+    "    download_file(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/ct-segmentation-quantize/custom_segmentation.py\")\n",
+    "from custom_segmentation import SegmentationModel\n",
+    "\n",
+    "if not Path(\"./async_pipeline.py\").exists():\n",
+    "    download_file(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/ct-segmentation-quantize/async_pipeline.py\")\n",
+    "from async_pipeline import show_live_inference"
    ]
   },
   {

notebooks/deepfloyd-if/deep-floyd-if-convert.ipynb

@@ -144,6 +144,20 @@
     "from diffusers import DiffusionPipeline\n",
     "import openvino as ov\n",
     "import torch\n",
+    "\n",
+    "# Fetch `notebook_utils` module\n",
+    "import requests\n",
+    "\n",
+    "r = requests.get(\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",
+    "from notebook_utils import download_file\n",
+    "\n",
+    "if not Path(\"./utils.py\").exists():\n",
+    "    download_file(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/deepfloyd-if/utils.py\")\n",
+    "\n",
     "from utils import (\n",
     "    TextEncoder,\n",
     "    UnetFirstStage,\n",

notebooks/deepfloyd-if/deep-floyd-if-optimize.ipynb

@@ -75,6 +75,19 @@
     "from pathlib import Path\n",
     "from typing import Any, List\n",
     "\n",
+    "# Fetch `notebook_utils` module\n",
+    "import requests\n",
+    "\n",
+    "r = requests.get(\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",
+    "from notebook_utils import download_file\n",
+    "\n",
+    "if not Path(\"./utils.py\").exists():\n",
+    "    download_file(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/deepfloyd-if/utils.py\")\n",
+    "\n",
     "from utils import TextEncoder, UnetFirstStage, UnetSecondStage\n",
     "\n",
     "checkpoint_variant = \"fp16\"\n",

notebooks/deepfloyd-if/utils.py

@@ -8,14 +8,15 @@
 from pathlib import Path
 from PIL import Image
 
-# Fetch `notebook_utils` module
-import requests
+if not Path("./notebook_utils.py").exists():
+    # Fetch `notebook_utils` module
+    import requests
 
-r = requests.get(
-    url="https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py",
-)
+    r = requests.get(
+        url="https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py",
+    )
 
-open("notebook_utils.py", "w").write(r.text)
+    open("notebook_utils.py", "w").write(r.text)
 from notebook_utils import download_file
 
 

notebooks/llm-question-answering/llm-question-answering.ipynb

@@ -101,6 +101,18 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from pathlib import Path\n",
+    "import requests\n",
+    "\n",
+    "# Fetch `notebook_utils` module\n",
+    "r = requests.get(\n",
+    "    url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py\",\n",
+    ")\n",
+    "open(\"notebook_utils.py\", \"w\").write(r.text)\n",
+    "from notebook_utils import download_file\n",
+    "\n",
+    "if not Path(\"./config.py\").exists():\n",
+    "    download_file(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/llm-question-answering/config.py\")\n",
     "from config import SUPPORTED_LLM_MODELS\n",
     "import ipywidgets as widgets"
    ]

notebooks/stable-diffusion-keras-cv/stable-diffusion-keras-cv.ipynb

@@ -100,6 +100,12 @@
     "import openvino as ov\n",
     "import numpy as np\n",
     "from pathlib import Path\n",
+    "import requests\n",
+    "\n",
+    "# Fetch `notebook_utils` module\n",
+    "r = requests.get(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/utils/notebook_utils.py\")\n",
+    "open(\"notebook_utils.py\", \"w\").write(r.text)\n",
+    "from notebook_utils import download_file\n",
     "\n",
     "IMAGE_WIDTH = 512\n",
     "IMAGE_HEIGHT = 512\n",
@@ -296,11 +302,16 @@
     "import tf_keras as keras\n",
     "import numpy as np\n",
     "import tensorflow as tf\n",
+    "from pathlib import Path\n",
     "\n",
-    "from constants import UNCONDITIONAL_TOKENS, ALPHAS_CUMPROD\n",
     "from keras_cv.models.stable_diffusion import SimpleTokenizer\n",
     "\n",
     "\n",
+    "if not Path(\"./constants.py\").exists():\n",
+    "    download_file(url=\"https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/latest/notebooks/stable-diffusion-keras-cv/constants.py\")\n",
+    "from constants import UNCONDITIONAL_TOKENS, ALPHAS_CUMPROD\n",
+    "\n",
+    "\n",
     "class StableDiffusion:\n",
     "    def __init__(self, text_encoder, diffusion_model, decoder):\n",
     "        # UNet requires multiples of 2**7 = 128\n",