Fix copyright and guidelines test errors for remaining tutorials (Pro…

…ject-MONAI#1182) Fixes Project-MONAI#1181 . ### Description - Update the guideline test to avoid counting line returns in non-text outputs (for example, html data) - Add copyright for all remaining scripts and clean replicates of old copyright info in the following notebooks - 2d_classification\mednist_tutorial.ipynb - 2d_registration\registration_mednist.ipynb - 3d_classification\densenet_training_array.ipynb - acceleration\multi_gpu_test.ipynb - acceleration\threadbuffer_performance.ipynb - acceleration\transform_speed.ipynb - modules\TorchIO_MONAI_PyTorch_Lightning.ipynb - modules\UNet_input_size_constrains.ipynb - multimodal\openi_multilabel_classification_transchex\transchex_openi_multilabel_classification.ipynb - experiment_management\spleen_segmentation_aim.ipynb - experiment_management\spleen_segmentation_mlflow.ipynb - Fix markdown cells for notebooks to match guidelines - experiment_management\bundle_integrate_mlflow.ipynb - modules\resample_benchmark.ipynb - Update the outputs in the following notebooks: - 2d_classification\mednist_tutorial.ipynb - 2d_registration\registration_mednist.ipynb - 3d_classification\densenet_training_array.ipynb ### Checks  - [x] Avoid including large-size files in the PR. - [x] Clean up long text outputs from code cells in the notebook. - [x] For security purposes, please check the contents and remove any sensitive info such as user names and private key. - [x] Ensure (1) hyperlinks and markdown anchors are working (2) use relative paths for tutorial repo files (3) put figure and graphs in the `./figure` folder - [ ] Notebook runs automatically `./runner.sh -t <path to .ipynb file>` Signed-off-by: Mingxin Zheng <[email protected]> Signed-off-by: Mingxin Zheng <[email protected]> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
boneseva · Jan 21, 2023 · 4b2771a · 4b2771a
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diff --git a/2d_classification/mednist_tutorial.ipynb b/2d_classification/mednist_tutorial.ipynb
diff --git a/2d_registration/registration_mednist.ipynb b/2d_registration/registration_mednist.ipynb
diff --git a/2d_segmentation/torch/unet_evaluation_array.py b/2d_segmentation/torch/unet_evaluation_array.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/2d_segmentation/torch/unet_evaluation_dict.py b/2d_segmentation/torch/unet_evaluation_dict.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/2d_segmentation/torch/unet_training_array.py b/2d_segmentation/torch/unet_training_array.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/2d_segmentation/torch/unet_training_dict.py b/2d_segmentation/torch/unet_training_dict.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/3d_classification/densenet_training_array.ipynb b/3d_classification/densenet_training_array.ipynb
diff --git a/3d_classification/ignite/densenet_evaluation_array.py b/3d_classification/ignite/densenet_evaluation_array.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/3d_classification/ignite/densenet_evaluation_dict.py b/3d_classification/ignite/densenet_evaluation_dict.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/3d_classification/ignite/densenet_training_array.py b/3d_classification/ignite/densenet_training_array.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/3d_classification/ignite/densenet_training_dict.py b/3d_classification/ignite/densenet_training_dict.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/3d_classification/torch/densenet_evaluation_array.py b/3d_classification/torch/densenet_evaluation_array.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/3d_classification/torch/densenet_evaluation_dict.py b/3d_classification/torch/densenet_evaluation_dict.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/3d_classification/torch/densenet_training_array.py b/3d_classification/torch/densenet_training_array.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/3d_classification/torch/densenet_training_dict.py b/3d_classification/torch/densenet_training_dict.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/acceleration/distributed_training/unet_evaluation_ddp.py b/acceleration/distributed_training/unet_evaluation_ddp.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/acceleration/distributed_training/unet_evaluation_horovod.py b/acceleration/distributed_training/unet_evaluation_horovod.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/acceleration/distributed_training/unet_evaluation_workflows.py b/acceleration/distributed_training/unet_evaluation_workflows.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/acceleration/distributed_training/unet_training_ddp.py b/acceleration/distributed_training/unet_training_ddp.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/acceleration/distributed_training/unet_training_horovod.py b/acceleration/distributed_training/unet_training_horovod.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/acceleration/distributed_training/unet_training_smartcache.py b/acceleration/distributed_training/unet_training_smartcache.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/acceleration/distributed_training/unet_training_workflows.py b/acceleration/distributed_training/unet_training_workflows.py
@@ -1,4 +1,4 @@
-# Copyright 2020 MONAI Consortium
+# Copyright (c) MONAI Consortium
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at

diff --git a/acceleration/multi_gpu_test.ipynb b/acceleration/multi_gpu_test.ipynb
@@ -4,6 +4,17 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "Copyright (c) MONAI Consortium  \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",
+    "&nbsp;&nbsp;&nbsp;&nbsp;http://www.apache.org/licenses/LICENSE-2.0  \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",
+    "\n",
     "# Multi GPU Test\n",
     "\n",
     "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Project-MONAI/tutorials/blob/main/acceleration/multi_gpu_test.ipynb)"
@@ -18,19 +29,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Note: you may need to restart the kernel to use updated packages.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "!python -c \"import monai\" || pip install -q \"monai-weekly[ignite]\""
    ]
@@ -44,7 +47,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
@@ -53,24 +56,29 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "MONAI version: 0.4.0\n",
-      "Numpy version: 1.19.1\n",
-      "Pytorch version: 1.7.0a0+7036e91\n",
-      "MONAI flags: HAS_EXT = False, USE_COMPILED = False\n",
-      "MONAI rev id: 0563a4467fa602feca92d91c7f47261868d171a1\n",
+      "MONAI version: 1.1.0+2.g97918e46\n",
+      "Numpy version: 1.22.2\n",
+      "Pytorch version: 1.13.0a0+d0d6b1f\n",
+      "MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False\n",
+      "MONAI rev id: 97918e46e0d2700c050e678d72e3edb35afbd737\n",
+      "MONAI __file__: /workspace/monai/monai-in-dev/monai/__init__.py\n",
       "\n",
       "Optional dependencies:\n",
-      "Pytorch Ignite version: 0.4.2\n",
-      "Nibabel version: 3.2.1\n",
-      "scikit-image version: 0.15.0\n",
-      "Pillow version: 8.0.1\n",
-      "Tensorboard version: 2.2.0\n",
-      "gdown version: 3.12.2\n",
-      "TorchVision version: 0.8.0a0\n",
-      "ITK version: 5.1.2\n",
-      "tqdm version: 4.54.1\n",
-      "lmdb version: 1.0.0\n",
-      "psutil version: 5.7.2\n",
+      "Pytorch Ignite version: 0.4.10\n",
+      "Nibabel version: 4.0.2\n",
+      "scikit-image version: 0.19.3\n",
+      "Pillow version: 9.0.1\n",
+      "Tensorboard version: 2.10.1\n",
+      "gdown version: 4.6.0\n",
+      "TorchVision version: 0.14.0a0\n",
+      "tqdm version: 4.64.1\n",
+      "lmdb version: 1.3.0\n",
+      "psutil version: 5.9.2\n",
+      "pandas version: 1.4.4\n",
+      "einops version: 0.6.0\n",
+      "transformers version: 4.21.3\n",
+      "mlflow version: 2.0.1\n",
+      "pynrrd version: 1.0.0\n",
       "\n",
       "For details about installing the optional dependencies, please visit:\n",
       "    https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies\n",
@@ -79,17 +87,6 @@
     }
    ],
    "source": [
-    "# Copyright 2020 MONAI Consortium\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",
-    "#     http://www.apache.org/licenses/LICENSE-2.0\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",
-    "\n",
     "import torch\n",
     "from monai.config import print_config\n",
     "from monai.engines import create_multigpu_supervised_trainer\n",
@@ -107,7 +104,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -142,13 +139,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
     }
    },
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2023-01-20 14:16:00,009 - Engine run starting with max_epochs=2.\n",
+      "2023-01-20 14:16:00,189 - Epoch[1] Complete. Time taken: 00:00:00.180\n",
+      "2023-01-20 14:16:00,201 - Epoch[2] Complete. Time taken: 00:00:00.011\n",
+      "2023-01-20 14:16:00,201 - Engine run complete. Time taken: 00:00:00.192\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -157,15 +164,15 @@
        "\tepoch: 2\n",
        "\tepoch_length: 2\n",
        "\tmax_epochs: 2\n",
-       "\toutput: 34253.46875\n",
+       "\toutput: 23339.560546875\n",
        "\tbatch: <class 'tuple'>\n",
        "\tmetrics: <class 'dict'>\n",
        "\tdataloader: <class 'generator'>\n",
        "\tseed: <class 'NoneType'>\n",
        "\ttimes: <class 'dict'>"
       ]
      },
-     "execution_count": 3,
+     "execution_count": null,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -185,14 +192,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
     },
     "tags": []
    },
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2023-01-20 14:16:00,208 - Engine run starting with max_epochs=2.\n",
+      "2023-01-20 14:16:01,364 - Epoch[1] Complete. Time taken: 00:00:01.154\n",
+      "2023-01-20 14:16:01,391 - Epoch[2] Complete. Time taken: 00:00:00.026\n",
+      "2023-01-20 14:16:01,391 - Engine run complete. Time taken: 00:00:01.181\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -201,15 +218,15 @@
        "\tepoch: 2\n",
        "\tepoch_length: 2\n",
        "\tmax_epochs: 2\n",
-       "\toutput: 30694.720703125\n",
+       "\toutput: 22608.560546875\n",
        "\tbatch: <class 'tuple'>\n",
        "\tmetrics: <class 'dict'>\n",
        "\tdataloader: <class 'generator'>\n",
        "\tseed: <class 'NoneType'>\n",
        "\ttimes: <class 'dict'>"
       ]
      },
-     "execution_count": 4,
+     "execution_count": null,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -229,13 +246,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
     }
    },
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2023-01-20 14:16:01,402 - Engine run starting with max_epochs=2.\n",
+      "2023-01-20 14:16:01,475 - Epoch[1] Complete. Time taken: 00:00:00.073\n",
+      "2023-01-20 14:16:01,575 - Epoch[2] Complete. Time taken: 00:00:00.100\n",
+      "2023-01-20 14:16:01,576 - Engine run complete. Time taken: 00:00:00.174\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -244,15 +271,15 @@
        "\tepoch: 2\n",
        "\tepoch_length: 2\n",
        "\tmax_epochs: 2\n",
-       "\toutput: 26988.939453125\n",
+       "\toutput: 21955.39453125\n",
        "\tbatch: <class 'tuple'>\n",
        "\tmetrics: <class 'dict'>\n",
        "\tdataloader: <class 'generator'>\n",
        "\tseed: <class 'NoneType'>\n",
        "\ttimes: <class 'dict'>"
       ]
      },
-     "execution_count": 6,
+     "execution_count": null,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -281,7 +308,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,