587 lines
145 KiB
Plaintext
587 lines
145 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 1,
|
|
"id": "d6cb560a-707c-4c1e-b50f-2b9c8037a3c7",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"from PIL import Image\n",
|
|
"import torch\n",
|
|
"import torch.nn as nn\n",
|
|
"import torch.nn.functional as F\n",
|
|
"import torch.optim as optim\n",
|
|
"import torchvision\n",
|
|
"import torchvision.transforms as transforms\n",
|
|
"import matplotlib.pyplot as plt\n",
|
|
"from rbm.model import Model\n",
|
|
"from rbm.entity import Entity, EntityParams, TrainingParams\n",
|
|
"from rbm.matrix import Mat, np, rms_error_accu\n",
|
|
"from rbm.torch import Optimizer\n",
|
|
"import math"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 2,
|
|
"id": "4065302d-862f-4639-99d7-e396d055434c",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"transform = transforms.Compose([\n",
|
|
" transforms.ToTensor(),\n",
|
|
" transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)) \n",
|
|
"]) "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"id": "ffe48fc6-0f57-48a0-b5e9-aa68cbc8edf1",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"train_data = torchvision.datasets.CIFAR10(root='./data', train=True, transform=transform, download=True)\n",
|
|
"test_data = torchvision.datasets.CIFAR10(root='./data', train=False, transform=transform, download=True)\n",
|
|
"\n",
|
|
"train_loader = torch.utils.data.DataLoader(train_data, batch_size=32, shuffle=True, num_workers=2)\n",
|
|
"test_loader = torch.utils.data.DataLoader(test_data, batch_size=32, shuffle=True, num_workers=2)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"id": "51b90664-e470-4c9a-884d-374a2ece61b2",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"image, label = train_data[0]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"id": "e98f3f60-e764-470b-ada1-d562a48e4813",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"6\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"print(label)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"id": "33501c0f-6d78-43e9-b2ce-adbe40b6d95a",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Dataset CIFAR10\n",
|
|
" Number of datapoints: 50000\n",
|
|
" Root location: ./data\n",
|
|
" Split: Train\n",
|
|
" StandardTransform\n",
|
|
"Transform: Compose(\n",
|
|
" ToTensor()\n",
|
|
" Normalize(mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5))\n",
|
|
" )\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"print(train_data)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"id": "08149024-e441-4786-a956-a068431932ca",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"torch.Size([3, 32, 32])\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"dim = image.size()\n",
|
|
"print(dim)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "f333fee6-91df-4153-9cfa-66d6550dd11c",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"id": "aedf601a-9084-4047-98e8-481f4d41a2d9",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"N = 16\n",
|
|
"image, label = train_data[0]\n",
|
|
"size = len(torch.flatten(image))\n",
|
|
"train_images = np.zeros(shape=(N, size))\n",
|
|
"train_images_tensor = torch.Tensor(N, size)\n",
|
|
"#train_labels = np.zeros(shape=(N, size))\n",
|
|
"for i in range(N):\n",
|
|
" image, label = train_data[i]\n",
|
|
" flat_array = torch.flatten(image)\n",
|
|
" train_images[i, :] = np.asarray(flat_array.numpy())\n",
|
|
" train_images_tensor[i, :] = flat_array\n",
|
|
"# train_labels[i, :] = torch.flatten(label).numpy()\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 9,
|
|
"id": "5ee865c3-2af4-487f-a184-1291f99839b1",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"16\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"print(len(train_images))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"id": "b4310933-d850-4128-a2dd-27d88c004846",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": "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",
|
|
"text/plain": [
|
|
"<Figure size 3000x3000 with 16 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"n_side = int(math.sqrt(len(train_images)))\n",
|
|
"fig, axes = plt.subplots(n_side, n_side, figsize=(30,30))\n",
|
|
"index = 0 \n",
|
|
"for x in range(n_side):\n",
|
|
" for y in range(n_side):\n",
|
|
" inp = train_images[index]\n",
|
|
" img = (1+np.reshape(inp, (3, 32, 32)))/2\n",
|
|
" img = img.transpose((1,2,0))\n",
|
|
" axes[x,y].imshow(np.asnumpy(img))\n",
|
|
" axes[x,y].axis('off')\n",
|
|
" index += 1\n",
|
|
"\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"id": "08143a53-12a1-4896-a4b2-166dedf0e021",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"class TestModel(Model):\n",
|
|
"\tdef __init__(self, name: str, work_dir: str = '.'):\n",
|
|
"\t\tsuper().__init__(name, work_dir)\n",
|
|
"#\t\tself.unit1 = Entity((3072, 16), EntityParams(do_gaussian_visible=True, do_gaussian_hidden=True), TrainingParams(learning_rate=0.0001, momentum=0.9, num_epochs=10000, mini_batch_size=100, weight_decay=0.0))\n",
|
|
"\t\tself.unit1 = Entity((3072, 32), EntityParams(do_gaussian_visible=True, do_gaussian_hidden=False), TrainingParams(learning_rate=0.001, momentum=0.9, num_epochs=10000, mini_batch_size=100, weight_decay=0.0))\n",
|
|
"\n",
|
|
"\tdef forward(self, x: Mat):\n",
|
|
"\t\tx = self.unit1.forward(x)\n",
|
|
"\t\treturn x\n",
|
|
"\n",
|
|
"\tdef backward(self, x: Mat):\n",
|
|
"\t\tx = self.unit1.reconstruct(x)\n",
|
|
"\t\treturn x\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "6b3be9f6-38e1-442d-a7bd-1f3c164ec8d4",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"results/cifar_test-0-state.npz loaded successfully!\n",
|
|
"-------------------------------------------\n",
|
|
"progress : 0%\n",
|
|
"err_rms : 0.0004614503262451372\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"work_dir = \"results\"\n",
|
|
"prj_name = \"cifar_test\"\n",
|
|
"prj_root = \"/home/jens/work/repos/Rbm\"\n",
|
|
"\n",
|
|
"# Create model\n",
|
|
"model = TestModel(prj_name, \"results\")\n",
|
|
"\n",
|
|
"# Init state\n",
|
|
"model.init(0.01)\n",
|
|
"\n",
|
|
"# load state\n",
|
|
"model.load()\n",
|
|
"\n",
|
|
"# Train\n",
|
|
"model.train(train_images)\n",
|
|
"# save state\n",
|
|
"model.save()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "d036b106-77a3-4993-bc2a-5fb164b8ec46",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Plot reconstructions\n",
|
|
"n_side = int(math.sqrt(len(train_images)))\n",
|
|
"fig, axes = plt.subplots(n_side, n_side, figsize=(30,30))\n",
|
|
"index = 0 \n",
|
|
"for x in range(n_side):\n",
|
|
" for y in range(n_side):\n",
|
|
" inp = train_images[index]\n",
|
|
" recon = model.backward(model.forward(inp))\n",
|
|
" recon -= np.min(recon)\n",
|
|
" recon = recon / np.max(recon)\n",
|
|
" img = np.reshape(recon, (3, 32, 32))\n",
|
|
" img = img.transpose((1,2,0))\n",
|
|
" axes[x,y].imshow(np.asnumpy(img))\n",
|
|
" axes[x,y].axis('off')\n",
|
|
" index += 1\n",
|
|
"\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "9adce292-cae6-455c-9409-c57ae71a36d5",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Plot weights\n",
|
|
"weights = model.unit1.state.w_hv\n",
|
|
"n, n_hid = weights.shape\n",
|
|
"w = np.reshape(weights, (3, 32, 32, n_hid))\n",
|
|
"print(w.shape)\n",
|
|
"n_side = int(math.sqrt(n_hid))\n",
|
|
"fig, axes = plt.subplots(n_side, n_side, figsize=(30,30))\n",
|
|
"\n",
|
|
"index = 0\n",
|
|
"for x in range(n_side):\n",
|
|
" for y in range(n_side):\n",
|
|
" inp = w[:,:,:, index]\n",
|
|
" inp -= np.min(inp)\n",
|
|
" inp = inp / np.max(inp)\n",
|
|
" img = inp.transpose((1,2,0))\n",
|
|
" axes[x,y].imshow(np.asnumpy(img))\n",
|
|
" axes[x,y].axis('off')\n",
|
|
" index += 1\n",
|
|
"\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "00f7f113-9efa-4c7b-8cb4-eeefb5cb797f",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# torch style"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "da54ec00-8db1-4dd9-ac4f-755f2886d72b",
|
|
"metadata": {
|
|
"editable": true,
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": []
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"model.load()\n",
|
|
"optimizer = Optimizer(model.unit1)\n",
|
|
"report_interval = 1000\n",
|
|
"next_ep = report_interval\n",
|
|
"optimizer.zero_grad()\n",
|
|
"for epoch in range(10000):\n",
|
|
" running_loss = 0.0\n",
|
|
"\n",
|
|
" optimizer.step(train_images)\n",
|
|
"\n",
|
|
" if epoch >= next_ep:\n",
|
|
" print(f'Training epoch {epoch}...')\n",
|
|
" next_ep += report_interval\n",
|
|
" # Update final status\n",
|
|
" err_rms = rms_error_accu(train_images - model.unit1.reconstruct(model.unit1.forward(train_images)))\n",
|
|
" print(err_rms)\n",
|
|
"\n",
|
|
"model.save()\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "80b0cdcc-3059-4840-98db-3416c585fa81",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c3238db1-179c-4e7a-a09c-5a2371cdac49",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "66bc0b12-dab5-46a8-b932-1c8ce4bd2175",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "fcc5c072-0e21-4cdc-a05d-ebf8c7cf0db1",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "6efdc1ef-6fdd-4dc5-8903-88464cf2d25f",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "9bdd50bb-875e-49d7-8a1e-8257a2d4ed25",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "9076754a-51ed-45ed-a0a8-767a3a7eeffd",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "ea6fc3b7-c1b7-45dc-9ef2-4c9dfdf82e18",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a7c82df5-9eb2-4920-b98f-4798d94ef896",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "eedf5bef-6341-4923-be79-ac8efdf424d3",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "2c937475-f297-4f2f-86aa-b28203de8485",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "e7fc0b9d-b652-4581-81e0-a0c83bdf4a63",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "544e0ea3-0602-4219-a67a-3162152aa730",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "848dad8e-ae01-4520-9978-9552ca8db9fb",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "ab664e72-ac9b-4c9d-b059-8ceacdc5d211",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "b9062597-5973-4c45-97ec-e4b8ee078eba",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "c976fed5-162c-4a70-8219-fc6c68c1fb66",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3 (ipykernel)",
|
|
"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": "3.12.3"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|