Added Manual dataset download (#286)

* Added Manual dataset download

* Modified formatting

* Added Specific Commands in different Cells

* Added a different list with all the notebook commands

* Correct typo

* Refactored Code

* Refactored Code

* Fixed failing null error

* Fix Typo for function

* Removed redundant if condition

* Fix lint

* Renamed variable nb_commands to nb_cells

Author: theory-in-progress

functions/colab.js

@@ -42,6 +42,47 @@ exports.handler = async function (event, _) {
     .map((v) => v[0].toUpperCase() + v.slice(1))
     .join(' ')
   // notebook cell structure
+
+  function create_nb_cell(source_array, cell_type) {
+    return {
+      cell_type: cell_type,
+      metadata: {},
+      execution_count: null,
+      outputs: [],
+      source: source_array
+    }
+  }
+
+  let specific_commands = []
+
+  if (title === 'Template Vision Segmentation') {
+    specific_commands.push(
+      '!python -c "from data import download_datasets; download_datasets(\'./\')"'
+    )
+  }
+
+  const md_cell = [
+    `# ${title} by PyTorch-Ignite Code-Generator\n\n`,
+    'Please, run the cell below to execute your code.'
+  ]
+
+  const common_nb_commands = [
+    `!wget ${zipRes}\n`,
+    `!unzip ${template}.zip\n`,
+    '!pip install -r requirements.txt'
+  ]
+
+  const execution_nb_commands = ['!python main.py config.yaml']
+
+  let nb_cells = [
+    create_nb_cell(md_cell, 'markdown'),
+    create_nb_cell(common_nb_commands, 'code')
+  ]
+  if (specific_commands.length > 0) {
+    nb_cells.push(create_nb_cell(specific_commands, 'code'))
+  }
+  nb_cells.push(create_nb_cell(execution_nb_commands, 'code'))
+
   const nb = {
     nbformat: 4,
     nbformat_minor: 0,
@@ -52,30 +93,7 @@ exports.handler = async function (event, _) {
       },
       accelerator: 'GPU'
     },
-    cells: [
-      {
-        cell_type: 'markdown',
-        metadata: {},
-        execution_count: null,
-        outputs: [],
-        source: [
-          `# ${title} by PyTorch-Ignite Code-Generator\n\n`,
-          'Please, run the cell below to execute your code.'
-        ]
-      },
-      {
-        cell_type: 'code',
-        metadata: {},
-        execution_count: null,
-        outputs: [],
-        source: [
-          `!wget ${zipRes}\n`,
-          `!unzip ${template}.zip\n`,
-          '!pip install -r requirements.txt\n',
-          '!python main.py config.yaml\n'
-        ]
-      }
-    ]
+    cells: nb_cells
   }
   // Create the notebook on GitHub
   await pushToGitHub(

src/templates/template-vision-segmentation/README.md

@@ -4,4 +4,20 @@
 
 This is the segmentation template by Code-Generator using `deeplabv3_resnet101` and `cifar10` dataset from TorchVision and training is powered by PyTorch and PyTorch-Ignite.
 
+**Note:**
+The dataset used in this template is quite substantial, with a size of several GBs and automatically downloading it can be seen as an unexpected behaviour. To prevent unexpected behavior or excessive bandwidth usage, the automatic downloading of the dataset has been disabled by default.
+
+To download the dataset:
+
+```python
+python -c "from data import download_datasets; download_datasets('/path/to/data')"
+```
+
+or
+
+```py
+from data import download_datasets
+download_datasets('/path/to/data')
+```
+
 #::= from_template_common ::#