Update example-notebook (explosion#590)

* Changed version names, no more alpha and dev versions * Changed version number in first markdown * Changed version number in first markdown * Had to change ray stuff because it throws an error otherwise * Changed mathy to mathy_core * Cleared output of notebook 06 * Cleared notebook 5 * Checking notebooks 0 to 2 again - minor changes; deleted notebook 04-ray as agreed on slack * Reviewed examples 04 and 03_textcat a second time * Last check, deleted empty call in notebook 5 * Checked notebook 00 again, changed install tensorflow to tensorflow-gpu as it was before
thomashacker · Feb 16, 2022 · c327a31 · c327a31
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diff --git a/examples/00_intro_to_thinc.ipynb b/examples/00_intro_to_thinc.ipynb
@@ -23,7 +23,7 @@
    },
    "outputs": [],
    "source": [
-    "!pip install \"thinc==8.0.0rc6.dev0\" \"ml_datasets>=0.2.0a0\" \"tqdm>=4.41\"\n"
+    "!pip install \"thinc>=8.0.0\" \"ml_datasets>=0.2.0\" \"tqdm>=4.41\""
    ]
   },
   {
@@ -39,21 +39,23 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "l310yc2IawXM"
+    "id": "l310yc2IawXM",
+    "scrolled": false
    },
    "outputs": [],
    "source": [
     "import thinc.util\n",
     "# If you want to run this notebook on GPU, you'll need to install cupy.\n",
     "if not thinc.util.has_cupy:\n",
-    "  !pip install \"cupy-cuda101\""
+    "    !pip install \"cupy-cuda101\""
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "id": "a23GlJVJa0T-"
+    "id": "a23GlJVJa0T-",
+    "scrolled": true
    },
    "outputs": [],
    "source": [
@@ -62,7 +64,7 @@
     "# You'll either need to do tensorflow or tensorflow-gpu, depending on your\n",
     "# requirements.\n",
     "if not thinc.util.has_tensorflow:\n",
-    "  !pip install \"tensorflow-gpu>=2\""
+    "    !pip install \"tensorflow-gpu>=2\""
    ]
   },
   {
@@ -76,7 +78,7 @@
     "import thinc.util\n",
     "# If you want to try out the PyTorch integration, you'll need to install it.\n",
     "if not thinc.util.has_torch:\n",
-    "  !pip install \"torch\""
+    "    !pip install \"torch\""
    ]
   },
   {
@@ -90,7 +92,7 @@
     "import thinc.util\n",
     "# If you want to try out the MxNet integration, you'll need to install it.\n",
     "if not thinc.util.has_mxnet:\n",
-    "  !pip install \"mxnet\""
+    "    !pip install \"mxnet>=1.5.1,<1.6.0\""
    ]
   },
   {
@@ -119,8 +121,8 @@
     "print(\"Thinc GPU?\", prefer_gpu())\n",
     "\n",
     "if thinc.util.has_tensorflow:\n",
-    "  import tensorflow as tf\n",
-    "  print(\"Tensorflow GPU?\", bool(tf.config.experimental.list_physical_devices('GPU')))"
+    "    import tensorflow as tf\n",
+    "    print(\"Tensorflow GPU?\", bool(tf.config.experimental.list_physical_devices('GPU')))"
    ]
   },
   {
@@ -871,7 +873,8 @@
      "base_uri": "https://localhost:8080/"
     },
     "id": "suiQ2psrGcjT",
-    "outputId": "4e72a0dc-b33b-4c5e-90f1-1dfa8f311b65"
+    "outputId": "4e72a0dc-b33b-4c5e-90f1-1dfa8f311b65",
+    "scrolled": true
    },
    "outputs": [],
    "source": [
@@ -1194,7 +1197,8 @@
      "base_uri": "https://localhost:8080/"
     },
     "id": "rBiDnLGhGcjW",
-    "outputId": "a208e5b6-8dc9-460a-f98a-b3d14186c4dc"
+    "outputId": "a208e5b6-8dc9-460a-f98a-b3d14186c4dc",
+    "scrolled": true
    },
    "outputs": [],
    "source": [
@@ -1332,7 +1336,8 @@
      ]
     },
     "id": "OCXFDVIHGcjX",
-    "outputId": "8fad70f4-c323-46b0-de52-2d4b65aed7b1"
+    "outputId": "8fad70f4-c323-46b0-de52-2d4b65aed7b1",
+    "scrolled": true
    },
    "outputs": [],
    "source": [
@@ -1355,21 +1360,6 @@
     "MXNet doesn't provide a `Softmax` layer but a `.softmax()` operation/method for prediction and it integrates an internal softmax during training. So to be able to integrate it with the rest of the components, you combine it with a `Softmax()` Thinc layer using the `chain` combinator. Make sure you `initialize()` the MXNet model *and* the Thinc model."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "colab": {
-     "base_uri": "https://localhost:8080/"
-    },
-    "id": "v5NkAEDCGcjX",
-    "outputId": "439e42a3-4178-48f4-d63e-08b499a1c1d6"
-   },
-   "outputs": [],
-   "source": [
-    "!pip install \"mxnet>=1.5.1,<1.6.0\""
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -1473,7 +1463,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.0"
+   "version": "3.8.10"
   },
   "mimetype": "text/x-python",
   "name": "python",

diff --git a/examples/01_intro_model_definition_methods.ipynb b/examples/01_intro_model_definition_methods.ipynb
@@ -15,7 +15,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!pip install \"thinc>=8.0.0a0\""
+    "!pip install \"thinc>=8.0.0\""
    ]
   },
   {
@@ -394,7 +394,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -408,7 +408,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.6"
+   "version": "3.8.10"
   }
  },
  "nbformat": 4,

diff --git a/examples/02_transformers_tagger_bert.ipynb b/examples/02_transformers_tagger_bert.ipynb
@@ -12,10 +12,12 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [],
    "source": [
-    "!pip install \"thinc>=8.0.0a0\" transformers torch \"ml_datasets>=0.2.0a0\" \"tqdm>=4.41\""
+    "!pip install \"thinc>=8.0.0\" transformers torch \"ml_datasets>=0.2.0\" \"tqdm>=4.41\""
    ]
   },
   {
@@ -476,7 +478,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -490,7 +492,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.0"
+   "version": "3.8.10"
   }
  },
  "nbformat": 4,

diff --git a/examples/03_pos_tagger_basic_cnn.ipynb b/examples/03_pos_tagger_basic_cnn.ipynb
@@ -19,7 +19,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!pip install \"thinc>=8.0.0a0\" \"ml_datasets>=0.2.0a0\" \"tqdm>=4.41\""
+    "!pip install \"thinc>=8.0.0\" \"ml_datasets>=0.2.0\" \"tqdm>=4.41\""
    ]
   },
   {
@@ -371,9 +371,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.7.2 64-bit ('.env': venv)",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "python37"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -385,7 +385,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.2"
+   "version": "3.8.10"
   }
  },
  "nbformat": 4,

diff --git a/examples/03_textcat_basic_neural_bow.ipynb b/examples/03_textcat_basic_neural_bow.ipynb
@@ -6,7 +6,7 @@
    "source": [
     "# Basic neural bag-of-words text classifier with Thinc\n",
     "\n",
-    "This notebook shows how to implement a simple neural text classification model in Thinc. Last tested with `thinc==8.0.0a9`."
+    "This notebook shows how to implement a simple neural text classification model in Thinc. Last tested with `thinc==8.0.13`."
    ]
   },
   {
@@ -15,7 +15,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!pip install thinc syntok \"ml_datasets>=0.2.0a0\" tqdm"
+    "!pip install thinc syntok \"ml_datasets>=0.2.0\" tqdm"
    ]
   },
   {
@@ -265,7 +265,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.8.10"
   }
  },
  "nbformat": 4,

diff --git a/examples/04_configure_gpu_memory.ipynb b/examples/04_configure_gpu_memory.ipynb
@@ -19,7 +19,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!pip install \"thinc>=8.0.0a0\" torch \"tensorflow>=2.0\""
+    "!pip install \"thinc>=8.0.0\" torch \"tensorflow>=2.0\" "
    ]
   },
   {
@@ -113,11 +113,6 @@
     "for _ in range(100):\n",
     "    arr2 = allocate_cupy_tensor(900000)"
    ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": []
   }
  ],
  "metadata": {
@@ -136,7 +131,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.2"
+   "version": "3.8.10"
   }
  },
  "nbformat": 4,