restruture old ch02 into appendix A

Author: rasbt

ch02/01_optional-python-setup-preferences/README.md renamed to appendix-A/01_optional-python-setup-preferences/README.md

@@ -1,3 +1,5 @@
+# Appendix A: Introduction to PyTorch (Part 3)
+
 import torch
 import torch.nn.functional as F
 from torch.utils.data import Dataset, DataLoader

ch02/01_optional-python-setup-preferences/figures/activate-env.png renamed to appendix-A/01_optional-python-setup-preferences/figures/activate-env.png

@@ -5,15 +5,15 @@
    "id": "ca7fc8a0-280c-4979-b0c7-fc3a99b3b785",
    "metadata": {},
    "source": [
-    "# Chapter 2: Introduction to PyTorch (Part 1)"
+    "# Appendix A: Introduction to PyTorch (Part 1)"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "f5bf13d2-8fc2-483e-88cc-6b4310221e68",
    "metadata": {},
    "source": [
-    "## 2.1 What is PyTorch"
+    "## A.1 What is PyTorch"
    ]
   },
   {
@@ -59,15 +59,15 @@
    "id": "2100cf2e-7459-4ab3-92a8-43e86ab35a9b",
    "metadata": {},
    "source": [
-    "## 2.2 Understanding tensors"
+    "## A.2 Understanding tensors"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "26d7f785-e048-42bc-9182-a556af6bb7f4",
    "metadata": {},
    "source": [
-    "### 2.2.1 Scalars, vectors, matrices, and tensors"
+    "### A.2.1 Scalars, vectors, matrices, and tensors"
    ]
   },
   {
@@ -148,7 +148,7 @@
    "id": "63dec48d-2b60-41a2-ac06-fef7e718605a",
    "metadata": {},
    "source": [
-    "### 2.2.2 Tensor data types"
+    "### A.2.2 Tensor data types"
    ]
   },
   {
@@ -213,7 +213,7 @@
    "id": "2020deb5-aa02-4524-b311-c010f4ad27ff",
    "metadata": {},
    "source": [
-    "### 2.2.3 Common PyTorch tensor operations"
+    "### A.2.3 Common PyTorch tensor operations"
    ]
   },
   {
@@ -378,7 +378,7 @@
    "id": "4c15bdeb-78e2-4870-8a4f-a9f591666f38",
    "metadata": {},
    "source": [
-    "## 2.3 Seeing models as computation graphs"
+    "## A.3 Seeing models as computation graphs"
    ]
   },
   {
@@ -415,7 +415,7 @@
    "id": "f9424f26-2bac-47e7-b834-92ece802247c",
    "metadata": {},
    "source": [
-    "## 2.4 Automatic differentiation made easy"
+    "## A.4 Automatic differentiation made easy"
    ]
   },
   {
@@ -481,7 +481,7 @@
    "id": "f53bdd7d-44e6-40ab-8a5a-4eef74ef35dc",
    "metadata": {},
    "source": [
-    "## 2.5 Implementing multilayer neural networks"
+    "## A.5 Implementing multilayer neural networks"
    ]
   },
   {
@@ -709,7 +709,7 @@
    "id": "19858180-0f26-43a8-b2c3-7ed40abf9f85",
    "metadata": {},
    "source": [
-    "## 2.6 Setting up efficient data loaders"
+    "## A.6 Setting up efficient data loaders"
    ]
   },
   {
@@ -884,7 +884,7 @@
    "id": "d904ca82-e50f-4f3d-a3ac-fc6ca53dd00e",
    "metadata": {},
    "source": [
-    "## 2.7 A typical training loop"
+    "## A.7 A typical training loop"
    ]
   },
   {
@@ -1127,7 +1127,7 @@
    "id": "4d5cd469-3a45-4394-944b-3ce543f41dac",
    "metadata": {},
    "source": [
-    "## 2.8 Saving and loading models"
+    "## A.8 Saving and loading models"
    ]
   },
   {
@@ -1167,55 +1167,55 @@
    "id": "f891c013-43da-4a05-973d-997be313d2d8",
    "metadata": {},
    "source": [
-    "## 2.9 Optimizing training performance with GPUs"
+    "## A.9 Optimizing training performance with GPUs"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "e68ae888-cabf-49c9-bad6-ecdce774db57",
    "metadata": {},
    "source": [
-    "### 2.9.1 PyTorch computations on GPU devices"
+    "### A.9.1 PyTorch computations on GPU devices"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "141c845f-efe3-4614-b376-b8b7a9a2c887",
    "metadata": {},
    "source": [
-    "See [ch02-code-part2.ipynb](ch02-code-part2.ipynb)"
+    "See [code-part2.ipynb](code-part2.ipynb)"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "99811829-b817-42ea-b03e-d35374debcc0",
    "metadata": {},
    "source": [
-    "### 2.9.2 Single-GPU training"
+    "### A.9.2 Single-GPU training"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "0b21456c-4af7-440f-9e78-37770277b5bc",
    "metadata": {},
    "source": [
-    "See [ch02-code-part2.ipynb](ch02-code-part2.ipynb)"
+    "See [code-part2.ipynb](code-part2.ipynb)"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "db6eb2d1-a341-4489-b04b-635c26945333",
    "metadata": {},
    "source": [
-    "### 2.9.3 Training with multiple GPUs"
+    "### A.9.3 Training with multiple GPUs"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "9d049a81-5fb0-49b5-9d6a-17a9976d8520",
    "metadata": {},
    "source": [
-    "See [ch02-code-part3.py](ch02-code-part3.py)"
+    "See [code-part3.py](code-part3.py)"
    ]
   }
  ],
@@ -1235,7 +1235,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,

ch02/01_optional-python-setup-preferences/figures/check-pip.png renamed to appendix-A/01_optional-python-setup-preferences/figures/check-pip.png

@@ -6,7 +6,7 @@
     "id": "O9i6kzBsZVaZ"
    },
    "source": [
-    "# Chapter 2: Introduction to PyTorch (Part 1)"
+    "# Appendix A: Introduction to PyTorch (Part 2)"
    ]
   },
   {
@@ -15,7 +15,7 @@
     "id": "ppbG5d-NZezH"
    },
    "source": [
-    "## 2.9 Optimizing training performance with GPUs"
+    "## A.9 Optimizing training performance with GPUs"
    ]
   },
   {
@@ -24,7 +24,7 @@
     "id": "6jH0J_DPZhbn"
    },
    "source": [
-    "### 2.9.1 PyTorch computations on GPU devices"
+    "### A.9.1 PyTorch computations on GPU devices"
    ]
   },
   {
@@ -165,7 +165,7 @@
     "id": "c8j1cWDcWAMf"
    },
    "source": [
-    "## 2.9.2 Single-GPU training"
+    "## A.9.2 Single-GPU training"
    ]
   },
   {
@@ -444,7 +444,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.10.6"
   }
  },
  "nbformat": 4,