Resolve device selection issues part1 (#1737)

Author: eaidova

notebooks/002-openvino-api/002-openvino-api.ipynb

@@ -13,7 +13,8 @@
     "`(x_min, y_min)` are the coordinates of the top left bounding box corner, `(x_max, y_max)` are the coordinates of the bottom right bounding box corner and `conf` is the confidence for the predicted class.\n",
     "\n",
     "\n",
-    "#### Table of contents:\n\n",
+    "#### Table of contents:\n",
+    "\n",
     "- [Imports](#Imports)\n",
     "- [Download model weights](#Download-model-weights)\n",
     "- [Select inference device](#Select-inference-device)\n",
@@ -204,7 +205,7 @@
     "core = ov.Core()\n",
     "\n",
     "model = core.read_model(model=model_xml_path)\n",
-    "compiled_model = core.compile_model(model=model, device_name=\"CPU\")\n",
+    "compiled_model = core.compile_model(model=model, device_name=device.value)\n",
     "\n",
     "input_layer_ir = compiled_model.input(0)\n",
     "output_layer_ir = compiled_model.output(\"boxes\")"
@@ -389,7 +390,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.8.10"
   },
   "openvino_notebooks": {
    "imageUrl": "https://user-images.githubusercontent.com/36741649/128489933-bf215a3f-06fa-4918-8833-cb0bf9fb1cc7.jpg",
@@ -403,8 +404,15 @@
      "Object Detection"
     ]
    }
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "state": {},
+    "version_major": 2,
+    "version_minor": 0
+   }
   }
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}

notebooks/004-hello-detection/004-hello-detection.ipynb

@@ -24,7 +24,8 @@
     "More information about the model is available in the [torchvision documentation](https://pytorch.org/vision/main/models/lraspp.html)\n",
     "\n",
     "\n",
-    "#### Table of contents:\n\n",
+    "#### Table of contents:\n",
+    "\n",
     "- [Preparation](#Preparation)\n",
     "    - [Imports](#Imports)\n",
     "    - [Settings](#Settings)\n",
@@ -777,50 +778,27 @@
     "    f\"FPS: {num_images/time_torch:.2f}\"\n",
     ")\n",
     "\n",
-    "compiled_model_onnx = core.compile_model(model=model_onnx, device_name=\"CPU\")\n",
+    "compiled_model_onnx = core.compile_model(model=model_onnx, device_name=device.value)\n",
     "start = time.perf_counter()\n",
     "for _ in range(num_images):\n",
     "    compiled_model_onnx([normalized_input_image])\n",
     "end = time.perf_counter()\n",
     "time_onnx = end - start\n",
     "print(\n",
-    "    f\"ONNX model in OpenVINO Runtime/CPU: {time_onnx/num_images:.3f} \"\n",
+    "    f\"ONNX model in OpenVINO Runtime/{device.value}: {time_onnx/num_images:.3f} \"\n",
     "    f\"seconds per image, FPS: {num_images/time_onnx:.2f}\"\n",
     ")\n",
     "\n",
-    "compiled_model_ir = core.compile_model(model=model_ir, device_name=\"CPU\")\n",
+    "compiled_model_ir = core.compile_model(model=model_ir, device_name=device.value)\n",
     "start = time.perf_counter()\n",
     "for _ in range(num_images):\n",
     "    compiled_model_ir([input_image])\n",
     "end = time.perf_counter()\n",
     "time_ir = end - start\n",
     "print(\n",
-    "    f\"OpenVINO IR model in OpenVINO Runtime/CPU: {time_ir/num_images:.3f} \"\n",
+    "    f\"OpenVINO IR model in OpenVINO Runtime/{device.value}: {time_ir/num_images:.3f} \"\n",
     "    f\"seconds per image, FPS: {num_images/time_ir:.2f}\"\n",
-    ")\n",
-    "\n",
-    "if \"GPU\" in core.available_devices:\n",
-    "    compiled_model_onnx_gpu = core.compile_model(model=model_onnx, device_name=\"GPU\")\n",
-    "    start = time.perf_counter()\n",
-    "    for _ in range(num_images):\n",
-    "        compiled_model_onnx_gpu([input_image])\n",
-    "    end = time.perf_counter()\n",
-    "    time_onnx_gpu = end - start\n",
-    "    print(\n",
-    "        f\"ONNX model in OpenVINO/GPU: {time_onnx_gpu/num_images:.3f} \"\n",
-    "        f\"seconds per image, FPS: {num_images/time_onnx_gpu:.2f}\"\n",
-    "    )\n",
-    "\n",
-    "    compiled_model_ir_gpu = core.compile_model(model=model_ir, device_name=\"GPU\")\n",
-    "    start = time.perf_counter()\n",
-    "    for _ in range(num_images):\n",
-    "        compiled_model_ir_gpu([input_image])\n",
-    "    end = time.perf_counter()\n",
-    "    time_ir_gpu = end - start\n",
-    "    print(\n",
-    "        f\"IR model in OpenVINO/GPU: {time_ir_gpu/num_images:.3f} \"\n",
-    "        f\"seconds per image, FPS: {num_images/time_ir_gpu:.2f}\"\n",
-    "    )"
+    ")\n"
    ]
   },
   {
@@ -872,7 +850,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -886,7 +864,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.8.10"
   },
   "openvino_notebooks": {
    "imageUrl": "https://user-images.githubusercontent.com/29454499/203723317-1716e3ca-b390-47e1-bb98-07b4d8d097a0.png",
@@ -905,8 +883,15 @@
    "interpreter": {
     "hash": "e0404472fd7b5b63117a9fa5c50283296e2708c2449c6090d2cdf8903f95897f"
    }
+  },
+  "widgets": {
+   "application/vnd.jupyter.widget-state+json": {
+    "state": {},
+    "version_major": 2,
+    "version_minor": 0
+   }
   }
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}

notebooks/102-pytorch-to-openvino/102-pytorch-onnx-to-openvino.ipynb

@@ -14,7 +14,8 @@
     "Source of the [model](https://www.paddlepaddle.org.cn/hubdetail?name=mobilenet_v3_large_imagenet_ssld&en_category=ImageClassification).\n",
     "\n",
     "\n",
-    "#### Table of contents:\n\n",
+    "#### Table of contents:\n",
+    "\n",
     "- [Preparation](#Preparation)\n",
     "    - [Imports](#Imports)\n",
     "    - [Settings](#Settings)\n",
@@ -458,7 +459,7 @@
     "# Load OpenVINO Runtime and OpenVINO IR model\n",
     "core = ov.Core()\n",
     "model = core.read_model(model_xml)\n",
-    "compiled_model = core.compile_model(model=model, device_name=\"CPU\")\n",
+    "compiled_model = core.compile_model(model=model, device_name=device.value)\n",
     "\n",
     "# Get model output\n",
     "output_layer = compiled_model.output(0)\n",
@@ -711,7 +712,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.8.10"
   },
   "openvino_notebooks": {
    "imageUrl": "https://user-images.githubusercontent.com/77325899/127503530-72c8ce57-ef6f-40a7-808a-d7bdef909d11.png",
@@ -741,4 +742,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}