Staging

.github/actions/setup-ci-tools/stub_widgets.py

@@ -88,6 +88,39 @@ def __getattr__(self, name):
 
 stub = _StubModule("ipywidgets")
 stub.widgets = stub  # support: from ipywidgets import widgets
+
+# --- Output widget stub that captures display() ---
+class _NoOpOutput:
+    """Stub for widgets.Output that captures display() calls."""
+    def __init__(self):
+        self.children = []
+        self._output_buffer = []
+        self._original_display = None
+
+    def __enter__(self):
+        # Patch IPython.display.display temporarily to capture output
+        from IPython import display as ipy_display
+        self._original_display = ipy_display.display
+        def _capturing_display(*objs, **kwargs):
+            self._output_buffer.extend(objs)
+        ipy_display.display = _capturing_display
+        return self
+
+    def __exit__(self, *args):
+        # Restore original display and store captured output in children
+        from IPython import display as ipy_display
+        if self._original_display is not None:
+            ipy_display.display = self._original_display
+        if self._output_buffer:
+            self.children = list(self._output_buffer)
+
+    def __repr__(self):
+        return f"<_NoOpOutput children={self.children}>"
+
+
+# Register Output class on the stub
+stub.Output = _NoOpOutput
+
 sys.modules["ipywidgets"] = stub
 sys.modules["ipywidgets.widgets"] = stub
 

.github/workflows/publish-book.yaml

@@ -44,7 +44,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v6
         with:
-          python-version: "3.11"
+          python-version: "3.10"
 
       - name: Install CI tools
         run: |

requirements.txt

@@ -35,6 +35,6 @@ pyngrok
 pytorch-pretrained-biggan
 python-Levenshtein
 textattack
-tokenizers
+tokenizers==0.22.2
 transformers
 vibecheck

tutorials/Bonus_DeployModels/Bonus_Tutorial1.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "116852b5",
+   "id": "39d077f2",
    "metadata": {
     "colab_type": "text",
     "execution": {},
@@ -24,7 +24,7 @@
     "\n",
     "__Content creators:__ Sam Ray, Vladimir Haltakov, Konrad Kording\n",
     "\n",
-    "__Production editors:__ Spiros Chavlis"
+    "__Production editors:__ Spiros Chavlis, Konstantine Tsafatinos"
    ]
   },
   {
@@ -736,7 +736,7 @@
     "* **Model** - this is the representation of the data that you want to interact with.\n",
     "* **View-Model** - this is the part that handles the application state and that transforms the data from the Model to a representation suitable for display and back.\n",
     "\n",
-    "<img src=\"https://raw.githubusercontent.com/NeuromatchAcademy/course-content-dl/main/tutorials/W2D4_GenerativeModels/static/deploy.png\">"
+    "<img src=\"https://raw.githubusercontent.com/NeuromatchAcademy/course-content-dl/main/tutorials/Bonus_DeployModels/static/deploy.png\">"
    ]
   },
   {

tutorials/Bonus_DeployModels/instructor/Bonus_Tutorial1.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "6467a9ee",
+   "id": "0727c202",
    "metadata": {
     "colab_type": "text",
     "execution": {},
@@ -24,7 +24,7 @@
     "\n",
     "__Content creators:__ Sam Ray, Vladimir Haltakov, Konrad Kording\n",
     "\n",
-    "__Production editors:__ Spiros Chavlis"
+    "__Production editors:__ Spiros Chavlis, Konstantine Tsafatinos"
    ]
   },
   {
@@ -736,7 +736,7 @@
     "* **Model** - this is the representation of the data that you want to interact with.\n",
     "* **View-Model** - this is the part that handles the application state and that transforms the data from the Model to a representation suitable for display and back.\n",
     "\n",
-    "<img src=\"https://raw.githubusercontent.com/NeuromatchAcademy/course-content-dl/main/tutorials/W2D4_GenerativeModels/static/deploy.png\">"
+    "<img src=\"https://raw.githubusercontent.com/NeuromatchAcademy/course-content-dl/main/tutorials/Bonus_DeployModels/static/deploy.png\">"
    ]
   },
   {

tutorials/Bonus_DeployModels/student/Bonus_Tutorial1.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "c5ed110b",
+   "id": "4dd9178c",
    "metadata": {
     "colab_type": "text",
     "execution": {},
@@ -24,7 +24,7 @@
     "\n",
     "__Content creators:__ Sam Ray, Vladimir Haltakov, Konrad Kording\n",
     "\n",
-    "__Production editors:__ Spiros Chavlis"
+    "__Production editors:__ Spiros Chavlis, Konstantine Tsafatinos"
    ]
   },
   {
@@ -736,7 +736,7 @@
     "* **Model** - this is the representation of the data that you want to interact with.\n",
     "* **View-Model** - this is the part that handles the application state and that transforms the data from the Model to a representation suitable for display and back.\n",
     "\n",
-    "<img src=\"https://raw.githubusercontent.com/NeuromatchAcademy/course-content-dl/main/tutorials/W2D4_GenerativeModels/static/deploy.png\">"
+    "<img src=\"https://raw.githubusercontent.com/NeuromatchAcademy/course-content-dl/main/tutorials/Bonus_DeployModels/static/deploy.png\">"
    ]
   },
   {

tutorials/Schedule/daily_schedules.md

@@ -12,17 +12,17 @@
 
 * Week 2
    * Monday: Regularization
-   * Tuesday: Convnets and DL Thinking 1
-   * Wednesday: Modern Convnets
-   * Thursday: Generative models (VAEs and Diffusion models)
-   * Friday: Attention and Transformers
+   * Tuesday: Convnets 
+   * Wednesday: Generative models and DL Discussion 1
+   * Thursday: Diffusion Generative models 
+   * Friday: Time Series and Natural Language Processing
 
 * Week 3: Advanced concepts
-   * Monday: Time Series and Natural Language Processing
-   * Tuesday: DL Thinking 2 & Half Projects Day (Abstract Writing)
+   * Monday: Attention and Transformers
+   * Tuesday: DL Discussion 2 & Half Projects Day (Abstract Writing)
    * Wednesday: Unsupervised and Self-supervised learning
    * Thursday: Basic Reinforcement Learning
-   * Friday: Reinforcement Learning for Games & DL Thinking 3
+   * Friday: Advanced Reinforcement Learning & DL Discussion 3
 ----
 
 ## Daily coursework schedule

tutorials/W1D1_BasicsAndPytorch/W1D1_Tutorial1.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "c0c35c4e",
+   "id": "1d2b4d47",
    "metadata": {
     "colab_type": "text",
     "execution": {},
@@ -30,7 +30,7 @@
     "\n",
     "__Content editors:__ Anoop Kulkarni, Spiros Chavlis\n",
     "\n",
-    "__Production editors:__ Arush Tagade, Spiros Chavlis"
+    "__Production editors:__ Arush Tagade, Spiros Chavlis, Konstantine Tsafatinos"
    ]
   },
   {

tutorials/W1D1_BasicsAndPytorch/instructor/W1D1_Tutorial1.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "4a3f6385",
+   "id": "6f4da5a9",
    "metadata": {
     "colab_type": "text",
     "execution": {},
@@ -30,7 +30,7 @@
     "\n",
     "__Content editors:__ Anoop Kulkarni, Spiros Chavlis\n",
     "\n",
-    "__Production editors:__ Arush Tagade, Spiros Chavlis"
+    "__Production editors:__ Arush Tagade, Spiros Chavlis, Konstantine Tsafatinos"
    ]
   },
   {

tutorials/W1D1_BasicsAndPytorch/student/W1D1_Tutorial1.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "be2cadcd",
+   "id": "0cc1829e",
    "metadata": {
     "colab_type": "text",
     "execution": {},
@@ -30,7 +30,7 @@
     "\n",
     "__Content editors:__ Anoop Kulkarni, Spiros Chavlis\n",
     "\n",
-    "__Production editors:__ Arush Tagade, Spiros Chavlis"
+    "__Production editors:__ Arush Tagade, Spiros Chavlis, Konstantine Tsafatinos"
    ]
   },
   {

tutorials/W1D2_LinearDeepLearning/W1D2_Tutorial1.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "fbb1121d",
+   "id": "048aaf62",
    "metadata": {
     "colab_type": "text",
     "execution": {},
@@ -30,7 +30,7 @@
     "\n",
     "__Content editors:__ Anoop Kulkarni, Spiros Chavlis\n",
     "\n",
-    "__Production editors:__ Khalid Almubarak, Gagana B, Spiros Chavlis"
+    "__Production editors:__ Khalid Almubarak, Gagana B, Spiros Chavlis, Konstantine Tsafatinos"
    ]
   },
   {

tutorials/W1D2_LinearDeepLearning/W1D2_Tutorial2.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "65c18196",
+   "id": "060e607d",
    "metadata": {
     "colab_type": "text",
     "execution": {},
@@ -30,7 +30,7 @@
     "\n",
     "__Content editors:__ Anoop Kulkarni\n",
     "\n",
-    "__Production editors:__ Khalid Almubarak, Gagana B, Spiros Chavlis"
+    "__Production editors:__ Khalid Almubarak, Gagana B, Spiros Chavlis, Konstantine Tsafatinos"
    ]
   },
   {
@@ -102,7 +102,7 @@
     "    ).render()\n",
     "\n",
     "\n",
-    "feedback_prefix = \"W1D2_T2\""
+    "feedback_prefix = \"W1D2_T2_Bonus\""
    ]
   },
   {

tutorials/W1D2_LinearDeepLearning/W1D2_Tutorial3.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "e7a743b9",
+   "id": "a82ff2e9",
    "metadata": {
     "colab_type": "text",
     "execution": {},
@@ -29,7 +29,7 @@
     "\n",
     "__Content editors:__ Anoop Kulkarni\n",
     "\n",
-    "__Production editors:__ Khalid Almubarak, Gagana B, Spiros Chavlis"
+    "__Production editors:__ Khalid Almubarak, Gagana B, Spiros Chavlis, Konstantine Tsafatinos"
    ]
   },
   {
@@ -101,7 +101,7 @@
     "    ).render()\n",
     "\n",
     "\n",
-    "feedback_prefix = \"W1D2_T3\""
+    "feedback_prefix = \"W1D2_T3_Bonus\""
    ]
   },
   {
@@ -338,7 +338,7 @@
     "  \"\"\"\n",
     "  n_sing_values = sv_array.shape[1]\n",
     "  sv_array = sv_array / np.max(sv_array)\n",
-    "  cmap = plt.cm.get_cmap(\"Set1\", n_sing_values)\n",
+    "  cmap = plt.get_cmap(\"Set1\", n_sing_values)\n",
     "\n",
     "  _, (plot1, plot2) = plt.subplots(2, 1, sharex=True, figsize=(10, 10))\n",
     "  plot1.set_title(\"Training loss (Mean Squared Error)\")\n",
@@ -366,7 +366,7 @@
     "  \"\"\"\n",
     "  n_sing_values = sv_array.shape[1]\n",
     "  sv_array = sv_array / np.max(sv_array)\n",
-    "  cmap = plt.cm.get_cmap(\"winter\", n_sing_values)\n",
+    "  cmap = plt.get_cmap(\"winter\", n_sing_values)\n",
     "\n",
     "  fig = plt.figure(figsize=(10, 5))\n",
     "  ax1 = plt.gca()\n",
@@ -404,7 +404,7 @@
     "  \"\"\"\n",
     "  n_sing_values = sv_array.shape[1]\n",
     "  sv_array = sv_array / np.max(sv_array)\n",
-    "  cmap = plt.cm.get_cmap(\"winter\", n_sing_values)\n",
+    "  cmap = plt.get_cmap(\"winter\", n_sing_values)\n",
     "\n",
     "  fig = plt.figure(figsize=(10, 5))\n",
     "  ax1 = plt.gca()\n",
@@ -447,7 +447,7 @@
     "  sv_array = sv_array / np.max(sv_array)\n",
     "\n",
     "  n_sing_values = sv_array.shape[1]\n",
-    "  cmap = plt.cm.get_cmap(\"winter\", n_sing_values)\n",
+    "  cmap = plt.get_cmap(\"winter\", n_sing_values)\n",
     "\n",
     "  fig = plt.figure(figsize=(14, 5))\n",
     "  gs = gridspec.GridSpec(1, 2, width_ratios=[5, 3])\n",

tutorials/W1D2_LinearDeepLearning/instructor/W1D2_Tutorial1.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "4b4fdd55",
+   "id": "19de18ab",
    "metadata": {
     "colab_type": "text",
     "execution": {},
@@ -30,7 +30,7 @@
     "\n",
     "__Content editors:__ Anoop Kulkarni, Spiros Chavlis\n",
     "\n",
-    "__Production editors:__ Khalid Almubarak, Gagana B, Spiros Chavlis"
+    "__Production editors:__ Khalid Almubarak, Gagana B, Spiros Chavlis, Konstantine Tsafatinos"
    ]
   },
   {

tutorials/W1D2_LinearDeepLearning/instructor/W1D2_Tutorial2.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "c35fd9ec",
+   "id": "1b973c7a",
    "metadata": {
     "colab_type": "text",
     "execution": {},
@@ -30,7 +30,7 @@
     "\n",
     "__Content editors:__ Anoop Kulkarni\n",
     "\n",
-    "__Production editors:__ Khalid Almubarak, Gagana B, Spiros Chavlis"
+    "__Production editors:__ Khalid Almubarak, Gagana B, Spiros Chavlis, Konstantine Tsafatinos"
    ]
   },
   {
@@ -102,7 +102,7 @@
     "    ).render()\n",
     "\n",
     "\n",
-    "feedback_prefix = \"W1D2_T2\""
+    "feedback_prefix = \"W1D2_T2_Bonus\""
    ]
   },
   {