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CNN

Image Classification
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image
classification
cifar
cnn
spaces
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Rahuletto commited on
Commit
6fdc829
·
1 Parent(s): ffb1866

refactor: changing structure

Browse files
Files changed (5) hide show
  1. model/cnn.py → cnn/__init__.py +0 -1
  2. {model → cnn}/model-old.pt +0 -0
  3. {model → cnn}/model.pt +0 -0
  4. testbench.ipynb +8 -8
  5. train.ipynb +3 -3
model/cnn.py → cnn/__init__.py RENAMED
@@ -1,4 +1,3 @@
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-
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  import torch.nn as nn
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  import torch.nn.functional as F
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  import torch.nn as nn
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  import torch.nn.functional as F
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{model → cnn}/model-old.pt RENAMED
File without changes
{model → cnn}/model.pt RENAMED
File without changes
testbench.ipynb CHANGED
@@ -2,7 +2,7 @@
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  "cells": [
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  {
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  "cell_type": "code",
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- "execution_count": null,
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  "id": "c831c34c",
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  "metadata": {},
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  "outputs": [
@@ -20,10 +20,10 @@
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  "import torch\n",
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  "from torch.utils.data import DataLoader\n",
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  "from torchvision import datasets, transforms\n",
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- "from model.cnn import CNN\n",
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  "\n",
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  "model = CNN()\n",
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- "model.load_state_dict(torch.load(\"model.pt\"))\n",
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  "\n",
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  "check_gpu = torch.cuda.is_available()\n",
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  "device = torch.device(\"cpu\")\n",
@@ -41,7 +41,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 10,
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  "id": "cd2d6928",
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  "metadata": {},
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  "outputs": [],
@@ -57,7 +57,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 11,
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  "id": "f7bb207f",
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  "metadata": {},
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  "outputs": [],
@@ -72,7 +72,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 12,
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  "id": "9ca78681",
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  "metadata": {},
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  "outputs": [],
@@ -82,7 +82,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 13,
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  "id": "9c5c7fae",
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  "metadata": {},
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  "outputs": [
@@ -137,7 +137,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": 33,
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  "id": "1e171b86",
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  "metadata": {},
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  "outputs": [
 
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  "cells": [
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  {
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  "cell_type": "code",
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+ "execution_count": 42,
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  "id": "c831c34c",
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  "metadata": {},
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  "outputs": [
 
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  "import torch\n",
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  "from torch.utils.data import DataLoader\n",
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  "from torchvision import datasets, transforms\n",
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+ "from cnn import CNN\n",
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  "\n",
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  "model = CNN()\n",
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+ "model.load_state_dict(torch.load(\"cnn/model.pt\"))\n",
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  "\n",
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  "check_gpu = torch.cuda.is_available()\n",
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  "device = torch.device(\"cpu\")\n",
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 43,
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  "id": "cd2d6928",
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  "metadata": {},
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  "outputs": [],
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 44,
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  "id": "f7bb207f",
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  "metadata": {},
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  "outputs": [],
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 45,
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  "id": "9ca78681",
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  "metadata": {},
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  "outputs": [],
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 46,
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  "id": "9c5c7fae",
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  "metadata": {},
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  "outputs": [
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 47,
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  "id": "1e171b86",
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  "metadata": {},
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  "outputs": [
train.ipynb CHANGED
@@ -9,7 +9,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": null,
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  "metadata": {},
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  "outputs": [
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  {
@@ -28,7 +28,7 @@
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  "import numpy as np\n",
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  "import matplotlib.pyplot as plt\n",
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  "import torch.nn as nn\n",
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- "from model.cnn import CNN\n",
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  "from tabulate import tabulate\n",
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  "\n",
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  "\n",
@@ -465,7 +465,7 @@
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  " if valid_loss < min_valid_loss:\n",
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  " saved = \"*\"\n",
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  " min_valid_loss = valid_loss\n",
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- " torch.save(model.state_dict(), \"model.pt\")\n",
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  "\n",
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  " row = [\n",
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  " epoch + 1,\n",
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 19,
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  "metadata": {},
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  "outputs": [
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  {
 
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  "import numpy as np\n",
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  "import matplotlib.pyplot as plt\n",
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  "import torch.nn as nn\n",
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+ "from cnn import CNN\n",
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  "from tabulate import tabulate\n",
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  "\n",
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  "\n",
 
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  " if valid_loss < min_valid_loss:\n",
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  " saved = \"*\"\n",
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  " min_valid_loss = valid_loss\n",
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+ " torch.save(model.state_dict(), \"cnn/model.pt\")\n",
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  "\n",
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  " row = [\n",
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  " epoch + 1,\n",