Update course book

neuromatch · Aug 26, 2024 · c1226fd · c1226fd
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diff --git a/_sources/tutorials/W1D1_Generalization/student/W1D1_Tutorial1.ipynb b/_sources/tutorials/W1D1_Generalization/student/W1D1_Tutorial1.ipynb
@@ -688,7 +688,7 @@
     "execution": {}
    },
    "source": [
-    "We build a simple interface in `gradio` to try out the model interactively. Go ahead and try some example text to see how it works. You can use images from the internet, or scan your own handwriting. Just make sure that the text fits on one line."
+    "We build a simple interface in `gradio` to try out the model interactively. Go ahead and try some example text to see how it works. You can use images from the internet, or scan your own handwriting. Just make sure that the text fits on one line. Observe the result of the recognized text."
    ]
   },
   {
@@ -1167,7 +1167,7 @@
     "    ############################################################\n",
     "    # Fill in this code to calculate character error rate and word error rate.\n",
     "    # Hint: have a look at the torchmetrics documentation for the proper\n",
-    "    # metrics.\n",
+    "    # metrics (type the proper metric name in the search bar).\n",
     "    #\n",
     "    # https://lightning.ai/docs/torchmetrics/stable/\n",
     "    raise NotImplementedError(\"Student has to fill in these lines\")\n",
@@ -1774,7 +1774,7 @@
     "execution": {}
    },
    "source": [
-    "### Code exercise 3.1: Understanding the inputs and outputs of the decoder\n",
+    "### Code exercise 3.1: Understanding the inputs and outputs of the encoder\n",
     "\n",
     "Let's make sure we understand how the encoder operates by giving it a sample input and checking that its output matches the expected shape."
    ]
@@ -1788,9 +1788,9 @@
    },
    "outputs": [],
    "source": [
-    "def inspect_decoder(model):\n",
+    "def inspect_encoder(model):\n",
     "    \"\"\"\n",
-    "    Inspect decoder to verify that it processes inputs in the expected way.\n",
+    "    Inspect encoder to verify that it processes inputs in the expected way.\n",
     "\n",
     "    Args:\n",
     "        model: the TrOCR model\n",
@@ -1826,7 +1826,7 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/NeuroAI_Course/tree/main/tutorials/W1D1_Generalization/solutions/W1D1_Tutorial1_Solution_fe1c0573.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/NeuroAI_Course/tree/main/tutorials/W1D1_Generalization/solutions/W1D1_Tutorial1_Solution_22613224.py)\n",
     "\n"
    ]
   },
@@ -1839,7 +1839,7 @@
    },
    "outputs": [],
    "source": [
-    "inspect_decoder(model)"
+    "inspect_encoder(model)"
    ]
   },
   {

diff --git a/_sources/tutorials/W1D1_Generalization/student/W1D1_Tutorial2.ipynb b/_sources/tutorials/W1D1_Generalization/student/W1D1_Tutorial2.ipynb
@@ -1203,6 +1203,8 @@
     "\n",
     "$$z = \\mathbf{W}\\mathbf{r} + c$$\n",
     "\n",
+    "In this notation, we can interpret $\\mathbf{r}$ as the firing rates of the neurons. Take a look at the equation above: the hidden state, $\\mathbf{x}$ (representation of stimuli in the brain), is evolving over time and is driven by current stimuli input $\\mathbf{u}$ and firing rates of neurons in the previous time step, $\\mathbf{r}$. EMG activity, $z$, is a direct linear projection from firing rates. \n",
+    "\n",
     "Let's code up this unregularized neural network."
    ]
   },
@@ -1370,7 +1372,7 @@
     "    #################################################\n",
     "    inputs = inputs.to(device)\n",
     "    batch_size = inputs.size(0)\n",
-    "    h = ...\n",
+    "    h = ... #note that `UnregularizedRNN` has a specific method for that\n",
     "\n",
     "    loss = 0\n",
     "    outputs = []\n",
@@ -1396,7 +1398,7 @@
     "execution": {}
    },
    "source": [
-    "[*Click for solution*](https://github.com/neuromatch/NeuroAI_Course/tree/main/tutorials/W1D1_Generalization/solutions/W1D1_Tutorial2_Solution_dc6b3d2e.py)\n",
+    "[*Click for solution*](https://github.com/neuromatch/NeuroAI_Course/tree/main/tutorials/W1D1_Generalization/solutions/W1D1_Tutorial2_Solution_c14a4735.py)\n",
     "\n"
    ]
   },
@@ -1809,7 +1811,7 @@
     "        # Project the firing rate linearly to form the output\n",
     "        output = self.output_linear(firing_rate)\n",
     "\n",
-    "        # Regularization terms\n",
+    "        # Regularization terms (used for R1 calculation)\n",
     "        firing_rate_reg = firing_rate.pow(2).sum()\n",
     "\n",
     "        return output, hidden, firing_rate_reg\n",
@@ -1961,7 +1963,7 @@
    "source": [
     "## Activity 3.2: Comparing trained RNN with real data\n",
     "\n",
-    "Let's see if this regularized network's activity is aligned with the brain."
+    "Let's see if this regularized network's activity is aligned with the brain. PSTH (peristimulus time histogram) is the type of plot that shows the firing rates of neurons over time (or their actual firings, depending on the granularity level)."
    ]
   },
   {

diff --git a/_sources/tutorials/W1D2_ComparingTasks/student/W1D2_Tutorial2.ipynb b/_sources/tutorials/W1D2_ComparingTasks/student/W1D2_Tutorial2.ipynb
@@ -724,30 +724,6 @@
     "\n"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e7888898-2483-4705-97dc-a0099ef7b5cd",
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "test_embeddings_untrained[0]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "5e6b3578-912c-4f96-9fd2-e6add908cb4a",
-   "metadata": {
-    "execution": {}
-   },
-   "outputs": [],
-   "source": [
-    "test_embeddings_untrained[2]"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},

diff --git a/projects/project-notebooks/ComparingNetworks.html b/projects/project-notebooks/ComparingNetworks.html
@@ -1223,7 +1223,7 @@ <h3>Install and import feedback gadget<a class="headerlink" href="#install-and-i
 <h3>Project Background<a class="headerlink" href="#project-background" title="Permalink to this heading">#</a></h3>
 <div class="cell tag_remove-input docutils container">
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "068fbb7c332f46b7814f3de2d27f2c09"}</script></div>
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 </div>
 </section>
 <section id="submit-your-feedback">
@@ -1242,7 +1242,7 @@ <h3>Submit your feedback<a class="headerlink" href="#submit-your-feedback" title
 </div>
 </details>
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "cd27a2559ba049cca4d55bccbfb3a9f4"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "14df630b76af436b9ce32479d837b85a"}</script></div>
 </div>
 </section>
 <section id="project-slides">
@@ -1305,7 +1305,7 @@ <h3>Submit your feedback<a class="headerlink" href="#id1" title="Permalink to th
 </div>
 </details>
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "d4b90aabaf324d61b99df28d77f18cfc"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "d9398321b5544f8aad3dab8382e2f788"}</script></div>
 </div>
 <p>In this notebook, we are going to provide code to get you started on Q1-Q3 of this project!</p>
 <p>The basic outline looks like this:</p>
@@ -1495,7 +1495,7 @@ <h3>Submit your feedback<a class="headerlink" href="#id2" title="Permalink to th
 </div>
 </details>
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "d008651a846d4de09fa411e4ce67bf38"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "b8312c5ddf144953ad1dfcd6258289e5"}</script></div>
 </div>
 </section>
 </section>
@@ -1562,7 +1562,7 @@ <h3>Submit your feedback<a class="headerlink" href="#id3" title="Permalink to th
 </div>
 </details>
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "48a1f6c834974370954e3d4517797b15"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "5b2abf0c923843d3bb9e819b4189e3cb"}</script></div>
 </div>
 </section>
 </section>
@@ -1597,7 +1597,7 @@ <h2>Section 3: Understanding the Three-Bit Flip-Flop task (3BFF)<a class="header
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../../_images/9dc92a37d20a89960b2fd3a6743f0d91d4424bb976cab816c1be341a19204acc.png" src="../../_images/9dc92a37d20a89960b2fd3a6743f0d91d4424bb976cab816c1be341a19204acc.png" />
+<img alt="../../_images/29a08c08a3b7fbd1c355eb267884ec858ab9af2dec4884da28b2ce8b33c104e2.png" src="../../_images/29a08c08a3b7fbd1c355eb267884ec858ab9af2dec4884da28b2ce8b33c104e2.png" />
 </div>
 </div>
 <p>Above, we are plotting the inputs and outputs of the 3BFF task. One trial is 500 time steps, each with a 1% probability of getting an “up” or “down” pulse on each of its 3 input channels. When the task receives an “up” pulse, the state corresponding to that input channel moves from zero to one (if possible), and if a state at one receives a “down” pulse, it goes to zero. In this way, this system acts as 3 bits of memory, encoding 8 potential system states (2^3 states). We add noise to the inputs of the system so that it better reflects realistic computations that a neural circuit might perform.</p>
@@ -1610,7 +1610,7 @@ <h2>Section 3: Understanding the Three-Bit Flip-Flop task (3BFF)<a class="header
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../../_images/b896b5ee7a145840f59d5258dd0e982511fe6c5421343aa990d42f202dc31084.png" src="../../_images/b896b5ee7a145840f59d5258dd0e982511fe6c5421343aa990d42f202dc31084.png" />
+<img alt="../../_images/500d3e5668d9440f586decc939ee3b5e63c7d23ecd45f033d358e64d9b6264f3.png" src="../../_images/500d3e5668d9440f586decc939ee3b5e63c7d23ecd45f033d358e64d9b6264f3.png" />
 </div>
 </div>
 <p>Now that we can see the basic logic of the task, let’s do a basic overview of what task training is!</p>
@@ -1634,7 +1634,7 @@ <h3>Submit your feedback<a class="headerlink" href="#id4" title="Permalink to th
 </div>
 </details>
 <div class="cell_output docutils container">
-<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "ea1578f658244e4186e3704bf40c0425"}</script></div>
+<script type="application/vnd.jupyter.widget-view+json">{"version_major": 2, "version_minor": 0, "model_id": "2bd3b26062ac4f0493841acc5fcb4931"}</script></div>
 </div>
 </section>
 </section>

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