Merge pull request #1098 from tanayvarshney/master

narendasan · web-flow · commit b498d8ba71a4 · 2022-06-23T17:53:11.000-07:00
fixed typos
diff --git a/notebooks/CitriNet-example.ipynb b/notebooks/CitriNet-example.ipynb
@@ -26,7 +26,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/tensorrt_torchtrt_citrinet/nvidia_logo.png\" width=\"90px\">\n",
     "\n",
     "# Torch-TensorRT Getting Started - CitriNet"
    ]
@@ -956,7 +956,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.12"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/EfficientNet-example.ipynb b/notebooks/EfficientNet-example.ipynb
@@ -26,7 +26,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/tensorrt_torchtrt_efficientnet/nvidia_logo.png\" width=\"90px\">\n",
     "\n",
     "# Torch-TensorRT Getting Started - EfficientNet-B0"
    ]
@@ -685,7 +685,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.12"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/Hugging-Face-BERT.ipynb b/notebooks/Hugging-Face-BERT.ipynb
@@ -28,7 +28,8 @@
    "id": "d0a97ac5",
    "metadata": {},
    "source": [
-    "<img src=\"https://developer.download.nvidia.com/tesla/notebook_assets/nv_logo_torch_trt_resnet_notebook.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/tensorrt_torchtrt_hf_bert/nvidia_logo.png\" width=\"90px\">\n",
+    "\n",
     "\n",
     "# Masked Language Modeling (MLM) with Hugging Face BERT Transformer"
    ]
@@ -706,7 +707,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.12"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/dynamic-shapes.ipynb b/notebooks/dynamic-shapes.ipynb
@@ -28,6 +28,8 @@
    "id": "18ee9d62",
    "metadata": {},
    "source": [
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/tensorrt_torchtrt_dynamic_shapes/nvidia_logo.png\" width=\"90px\">\n",
+    "\n",
     "# Torch-TensorRT - Using Dynamic Shapes"
    ]
   },
@@ -41,16 +43,17 @@
     "We highly encourage users to run this notebook using our NVIDIA's [PyTorch container](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch). It comes packaged with a host of NVIDIA libraries and optimizations to widely used third-party libraries. In addition, this container is tested and updated on a monthly cadence!\n",
     "\n",
     "This notebook has the following sections:\n",
-    "1. TL;DR Explanation\n",
-    "1. Setting up the model\n",
-    "1. Working with Dynamic shapes in Torch TRT]"
+    "1. [TL;DR Explanation](#1)\n",
+    "2. [Setting up the model](#2)\n",
+    "3. [Working with Dynamic shapes in Torch TRT](#3)"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "1603028d",
    "metadata": {},
    "source": [
+    "<a id=\"1\"></a>\n",
     "---\n",
     "## TL;DR Explanation\n",
     "\n",
@@ -187,6 +190,7 @@
    "id": "0ed1b4f7",
    "metadata": {},
    "source": [
+    "<a id=\"2\"></a>\n",
     "---\n",
     "## Setting up the model\n",
     "\n",
@@ -818,6 +822,7 @@
    "id": "bd5746da",
    "metadata": {},
    "source": [
+    "<a id=\"3\"></a>\n",
     "---\n",
     "## Working with Dynamic shapes in Torch TRT\n",
     " \n",
@@ -1015,7 +1020,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/lenet-getting-started.ipynb b/notebooks/lenet-getting-started.ipynb
@@ -6,7 +6,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Copyright 2019 NVIDIA Corporation. All Rights Reserved.\n",
+    "# Copyright 2019-22 NVIDIA Corporation. All Rights Reserved.\n",
     "#\n",
     "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
     "# you may not use this file except in compliance with the License.\n",
@@ -26,7 +26,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"http://developer.download.nvidia.com/compute/machine-learning/frameworks/nvidia_logo.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/tensorrt_torchtrt_lenet/nvidia_logo.png\" width=\"90px\">\n",
+    "\n",
     "\n",
     "# Torch-TensorRT Getting Started - LeNet"
    ]
@@ -710,7 +711,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.12"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/ssd-object-detection-demo.ipynb b/notebooks/ssd-object-detection-demo.ipynb
@@ -26,7 +26,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<img src=\"https://developer.download.nvidia.com/tesla/notebook_assets/nv_logo_torch_trt_ssd_notebook.png\" style=\"width: 90px; float: right;\">\n",
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/tensorrt_torchtrt_ssd/nvidia_logo.png\" width=\"90px\">\n",
     "\n",
     "# Object Detection with Torch-TensorRT (SSD)"
    ]
@@ -935,7 +935,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.12"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/vgg-qat.ipynb b/notebooks/vgg-qat.ipynb
@@ -1,10 +1,35 @@
 {
  "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a054a8df",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Copyright 2020-2022 NVIDIA Corporation. All Rights Reserved.\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     http://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License.\n",
+    "# =============================================================================="
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "8033b2eb",
    "metadata": {},
    "source": [
+    "<img src=\"http://developer.download.nvidia.com/notebooks/dlsw-notebooks/tensorrt_torchtrt_qat_vgg/nvidia_logo.png\" width=\"90px\">\n",
+    "\n",
     "# Deploying Quantization Aware Trained models in INT8 using Torch-TensorRT"
    ]
   },
@@ -1192,7 +1217,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.12"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,
