update

Author: feng.d.gao

Basic_concept_1_tensor_operations.ipynb

@@ -103,10 +103,10 @@
     "a = np.array([1, 2, 3])\n",
     "t1 = torch.Tensor(a)\n",
     "\n",
-    "# Perferred copy operation\n",
+    "# Perferred copy operation vs torch.Tensor()\n",
     "t2 = torch.tensor(a)\n",
     "\n",
-    "# Perfered share operation\n",
+    "# Perfered share operation vs torch.from_numpy()\n",
     "t3 = torch.as_tensor(a)\n",
     "\n",
     "t4 = torch.from_numpy(a)\n",
@@ -237,7 +237,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 1.2 Sequeeze and unsequeeze\n",
+    "### 1.2 Squeeze and unsequeeze\n",
     "- Squeezing a tensor **removes the axes that have a length of one**\n",
     "- Unsqueezing a tensor **adds a dimension with a length of one**"
    ]
@@ -1176,7 +1176,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.4"
+   "version": "3.6.8"
   }
  },
  "nbformat": 4,

Basic_concept_2_data_preparation.ipynb

@@ -256,7 +256,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.4"
+   "version": "3.6.8"
   }
  },
  "nbformat": 4,

Basic_concept_3_model_save_and_load.ipynb

@@ -204,7 +204,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.4"
+   "version": "3.6.8"
   }
  },
  "nbformat": 4,

Basic_concept_4_Model.ipynb

@@ -0,0 +1,104 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "import torch.nn as nn"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class MyModel(nn.Module):\n",
+    "    def __init__(self):\n",
+    "        super(MyModel, self).__init__()\n",
+    "        self.fc = nn.Linear(in_features=3, out_features=2)\n",
+    "    def forward(self, batch_input):\n",
+    "        return self.fc(batch_input)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "MyModel(\n",
+      "  (fc): Linear(in_features=3, out_features=2, bias=True)\n",
+      ")\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = MyModel()\n",
+    "print(model)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "tensor([[-0.2901,  0.8468],\n",
+      "        [-0.2635,  0.6138],\n",
+      "        [-0.0937,  0.7620]], grad_fn=<AddmmBackward>)\n"
+     ]
+    }
+   ],
+   "source": [
+    "batch_input = torch.rand(3, 3)\n",
+    "output = model(batch_input)\n",
+    "print(output)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}