updated notebook (#2059)

Author: NRauschmayr

sagemaker-debugger/pytorch_iterative_model_pruning/iterative_model_pruning_alexnet.ipynb

@@ -100,7 +100,9 @@
    "source": [
     "### Load and save AlexNet model\n",
     "\n",
-    "First we load a pre-trained [AlexNet](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks) model from PyTorch model zoo. "
+    "First we load a pre-trained [AlexNet](http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks) model from PyTorch model zoo.  \n",
+    "\n",
+    "**IMPORTANT**: the model file will be used by the training job. To avoid version conflicts, you need to ensure that your notebook is running a Jupyter kernel with PyTorch version 1.6."
    ]
   },
   {
@@ -353,7 +355,7 @@
     "                  train_volume_size=400,\n",
     "                  source_dir='src',\n",
     "                  entry_point='train.py',\n",
-    "                  framework_version='1.3.1',\n",
+    "                  framework_version='1.6',\n",
     "                  py_version='py3',\n",
     "                  metric_definitions=[ {'Name':'train:loss', 'Regex':'loss:(.*?)'}, {'Name':'eval:acc', 'Regex':'acc:(.*?)'} ],\n",
     "                  enable_sagemaker_metrics=True,\n",
@@ -595,7 +597,7 @@
     "                  train_volume_size=400,\n",
     "                  source_dir='src',\n",
     "                  entry_point='train.py',\n",
-    "                  framework_version='1.3.1',\n",
+    "                  framework_version='1.6',\n",
     "                  py_version='py3',\n",
     "                  metric_definitions=[ {'Name':'train:loss', 'Regex':'loss:(.*?)'}, {'Name':'eval:acc', 'Regex':'acc:(.*?)'} ],\n",
     "                  enable_sagemaker_metrics=True,\n",

sagemaker-debugger/pytorch_iterative_model_pruning/iterative_model_pruning_resnet.ipynb

@@ -159,7 +159,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Next we store the model definition and weights in an output file. "
+    "Next we store the model definition and weights in an output file. \n",
+    "\n",
+    "**IMPORTANT**: the model file will be used by the training job. To avoid version conflicts, you need to ensure that your notebook is running a Jupyter kernel with PyTorch version 1.6."
    ]
   },
   {
@@ -314,7 +316,7 @@
     "                  train_volume_size=400,\n",
     "                  source_dir='src',\n",
     "                  entry_point='train.py',\n",
-    "                  framework_version='1.3.1',\n",
+    "                  framework_version='1.6',\n",
     "                  py_version='py3',\n",
     "                  metric_definitions=[ {'Name':'train:loss', 'Regex':'loss:(.*?)'}, {'Name':'eval:acc', 'Regex':'acc:(.*?)'} ],\n",
     "                  enable_sagemaker_metrics=True,\n",
@@ -551,7 +553,7 @@
     "                  train_volume_size=400,\n",
     "                  source_dir='src',\n",
     "                  entry_point='train.py',\n",
-    "                  framework_version='1.3.1',\n",
+    "                  framework_version='1.6',\n",
     "                  py_version='py3',\n",
     "                  metric_definitions=[ {'Name':'train:loss', 'Regex':'loss:(.*?)'}, {'Name':'eval:acc', 'Regex':'acc:(.*?)'} ],\n",
     "                  enable_sagemaker_metrics=True,\n",

sagemaker-debugger/pytorch_iterative_model_pruning/src/requirements.txt

@@ -0,0 +1 @@
+smdebug==0.5.0