v3.1.2

docs/about/release_notes.md

@@ -1,6 +1,11 @@
 # Release notes
 
-## Unreleased
+## v3.1.2 (12/12/2025)
+
+* Update use of visualizer in Sinabs tutorials, previous tutorials were using a deprecated visualizer version.
+* Fix issue with `chip_layers_ordering` in the visualizer. `chip_layers_ordering` was deprecated in Sinabs 3.1.0 and `layer2core_map` needs to be used instead.
+
+## v3.1.1 (27/11/2025)
 
 * Fix NIR export of Conv1d layer which expected an input_shape parameter.
 * Fix broken link on documentation.

docs/speck/notebooks/leak_neuron.ipynb

@@ -110,7 +110,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "id": "500e2d79",
    "metadata": {},
    "outputs": [
@@ -230,7 +230,7 @@
     ")\n",
     "# don't forget to set the slow clock frequency!\n",
     "# here we set the frequency to 1Hz, which mean the Vmem should decrease after every 1 second\n",
-    "dynapcnn.to(device=\"speck2fmodule\", slow_clk_frequency=1)\n",
+    "dynapcnn.to(device=\"speck2fdevkit\", slow_clk_frequency=1)\n",
     "\n",
     "# Check if neuron states decrease along with time pass by\n",
     "\n",
@@ -276,7 +276,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.0"
+   "version": "3.12.3"
   }
  },
  "nbformat": 4,

docs/speck/notebooks/play_with_speck_dvs.ipynb

@@ -3,6 +3,7 @@
   {
    "cell_type": "markdown",
    "metadata": {
+    "collapsed": true,
     "jupyter": {
      "outputs_hidden": true
     }
@@ -61,7 +62,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
@@ -83,13 +84,15 @@
        "    )\n",
        "    (1): DynapcnnLayer(\n",
        "      (conv_layer): Conv2d(1, 1, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
-       "      (spk_layer): IAFSqueeze(spike_threshold=398.0, min_v_mem=-398.0, batch_size=1, num_timesteps=-1)\n",
+       "      (spk_layer): IAFSqueeze(spike_threshold=Parameter containing:\n",
+       "      tensor(418.), min_v_mem=Parameter containing:\n",
+       "      tensor(-418.), batch_size=1, num_timesteps=-1)\n",
        "    )\n",
        "  )\n",
        ")"
       ]
      },
-     "execution_count": 33,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -112,7 +115,7 @@
     "dynapcnn = DynapcnnNetwork(snn=snn, input_shape=input_shape, dvs_input=True)\n",
     "\n",
     "# deploy to speck devkit, use a different name if you're using a different version of the devkit\n",
-    "devkit_name = \"speck2fmodule\"\n",
+    "devkit_name = \"speck2fdevkit\"\n",
     "dynapcnn.to(device=devkit_name, monitor_layers=[\"dvs\", -1])"
    ]
   },
@@ -130,7 +133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -164,7 +167,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -215,7 +218,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -224,6 +227,14 @@
      "text": [
       "Network is valid\n"
      ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/vleite/.pyenv/versions/sinabs/lib/python3.12/site-packages/sinabs/backend/dynapcnn/chips/dynapcnn.py:252: UserWarning: DVS layer has pooling and is being monitored. Note that pooling will not be reflected in the monitored events.\n",
+      "  warn(\n"
+     ]
     }
    ],
    "source": [
@@ -267,7 +278,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -309,7 +320,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -360,7 +371,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -391,7 +402,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -433,7 +444,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -485,7 +496,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -547,7 +558,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -594,7 +605,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -625,7 +636,7 @@
     "devkit_cfg_filter.dvs_filter.threshold = 5\n",
     "\n",
     "# set up the Unifirm/IO module\n",
-    "devkit_io = devkit.get_io_module()\n",
+    "devkit_io = dynapcnn.samna_device.get_io_module()\n",
     "\n",
     "# update the configuration\n",
     "dynapcnn.samna_device.get_model().apply_configuration(devkit_cfg_filter)"
@@ -655,7 +666,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.12.3"
   }
  },
  "nbformat": 4,