jensandClaude Sonnet 4.6
dddb937909
- Add PATCH/STRIDE params; STRIDE=4 for 50% overlap (49 patches per image) - Reconstruct 32x32 by averaging overlapping patch contributions (assemble_overlapping pattern from test_faces_sub_image) - All cells updated to use PATCH/STRIDE throughout Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
669 lines
380 KiB
Plaintext
669 lines
380 KiB
Plaintext
{
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"cells": [
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}
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},
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"source": [
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"from PIL import Image\n",
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"import torch\n",
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"import torch.nn as nn\n",
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"import torch.nn.functional as F\n",
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"import torch.optim as optim\n",
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"import torchvision\n",
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"import torchvision.transforms as transforms\n",
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"import matplotlib.pyplot as plt\n",
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"from rbm.model import Model\n",
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"from rbm.entity import Entity, EntityParams, TrainingParams\n",
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"from rbm.matrix import Mat, np, rms_error_accu, sample_gaussian\n",
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"from rbm.torch import Optimizer\n",
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"from rbm.image import SubImage, normalize\n",
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"import math\n",
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"import random"
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],
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"outputs": [],
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"execution_count": 1
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"cell_type": "code",
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"id": "4065302d-862f-4639-99d7-e396d055434c",
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}
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},
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"source": [
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"transform = transforms.Compose([\n",
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" transforms.ToTensor(),\n",
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" transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)) \n",
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"]) "
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],
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"outputs": [],
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"execution_count": 2
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"id": "ffe48fc6-0f57-48a0-b5e9-aa68cbc8edf1",
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"metadata": {
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}
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},
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"source": [
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"train_data = torchvision.datasets.CIFAR10(root='./data', train=True, transform=transform, download=True)\n",
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"test_data = torchvision.datasets.CIFAR10(root='./data', train=False, transform=transform, download=True)\n",
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"\n",
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"train_loader = torch.utils.data.DataLoader(train_data, batch_size=32, shuffle=True, num_workers=2)\n",
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"test_loader = torch.utils.data.DataLoader(test_data, batch_size=32, shuffle=True, num_workers=2)"
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}
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},
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"source": [
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"print(train_data)"
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],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Dataset CIFAR10\n",
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" Number of datapoints: 50000\n",
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" Root location: ./data\n",
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" Split: Train\n",
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" StandardTransform\n",
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"Transform: Compose(\n",
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" ToTensor()\n",
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" Normalize(mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5))\n",
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" )\n"
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]
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}
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],
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"execution_count": 4
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},
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"cell_type": "code",
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"id": "aedf601a-9084-4047-98e8-481f4d41a2d9",
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"metadata": {
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"editable": true,
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"execution": {
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"end_time": "2026-06-01T17:57:34.398042393Z",
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"start_time": "2026-06-01T17:57:34.180536787Z"
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}
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},
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"source": [
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"N = 500\n",
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"n_side = 10\n",
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"PATCH = 8\n",
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"STRIDE = 4\n",
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"N_VIS = 3 * PATCH * PATCH\n",
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"\n",
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"image, label = train_data[0]\n",
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"size = len(torch.flatten(image))\n",
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"train_images = np.zeros(shape=(N, size))\n",
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"train_images_tensor = torch.Tensor(N, size)\n",
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"for i in range(N):\n",
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" image, label = train_data[i]\n",
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" flat_array = torch.flatten(image)\n",
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" train_images[i, :] = np.asarray(flat_array.numpy())\n",
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" train_images_tensor[i, :] = flat_array\n",
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"print(image.shape)"
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],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"torch.Size([3, 32, 32])\n"
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]
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}
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],
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"execution_count": 5
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},
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"cell_type": "code",
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"id": "5ee865c3-2af4-487f-a184-1291f99839b1",
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"metadata": {
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"end_time": "2026-06-01T17:57:36.333225542Z",
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"start_time": "2026-06-01T17:57:34.399658692Z"
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}
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},
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"source": [
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"image_indices = np.array(random.sample(range(min(N, n_side*n_side)), n_side*n_side))\n",
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"print(f\"train_images.shape:{train_images.shape}\")\n",
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"mean_training_batch = np.reshape(np.repeat(np.mean(train_images, axis=1), 3072, axis=0), train_images.shape)\n",
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"var_training_batch = np.reshape(np.repeat(np.std(train_images, axis=1), 3072, axis=0), train_images.shape)\n",
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"train_images_norm = (train_images - mean_training_batch) / var_training_batch\n",
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"sub_generator = SubImage(PATCH, PATCH, STRIDE, STRIDE)\n",
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"train_subimages = sub_generator(np.reshape(train_images, (N, 3, 32, 32)), 3)\n",
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"print(train_subimages.shape)\n",
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"train_subimages = np.reshape(train_subimages, (train_subimages.shape[0], N_VIS))\n",
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"print(train_subimages.shape)"
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],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"train_images.shape:(500, 3072)\n",
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"(24500, 3, 8, 8)\n",
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"(24500, 192)\n"
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]
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}
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],
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"execution_count": 6
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},
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{
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"cell_type": "code",
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"id": "b4310933-d850-4128-a2dd-27d88c004846",
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"metadata": {
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"execution": {
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"ExecuteTime": {
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"end_time": "2026-06-01T17:57:37.735621606Z",
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"start_time": "2026-06-01T17:57:36.334036265Z"
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}
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},
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"source": [
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"fig, axes = plt.subplots(n_side, n_side, figsize=(30,30))\n",
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"index = 0 \n",
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"for x in range(n_side):\n",
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" for y in range(n_side):\n",
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" inp = train_subimages[image_indices[index]]\n",
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" img = (1+np.reshape(inp, (3, PATCH, PATCH)))/2\n",
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" img = img.transpose((1,2,0))\n",
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" axes[x,y].imshow(np.asnumpy(img))\n",
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" axes[x,y].axis('off')\n",
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" index += 1\n",
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"\n",
|
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"plt.show()"
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],
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"outputs": [
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{
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"data": {
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"text/plain": [
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"<Figure size 3000x3000 with 100 Axes>"
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],
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|
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},
|
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"metadata": {},
|
|
"output_type": "display_data",
|
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"jetTransient": {
|
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"display_id": null
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}
|
|
}
|
|
],
|
|
"execution_count": 7
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"id": "08143a53-12a1-4896-a4b2-166dedf0e021",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2026-06-01T17:49:21.500617Z",
|
|
"iopub.status.busy": "2026-06-01T17:49:21.500445Z",
|
|
"iopub.status.idle": "2026-06-01T17:49:21.504622Z",
|
|
"shell.execute_reply": "2026-06-01T17:49:21.503914Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": [],
|
|
"ExecuteTime": {
|
|
"end_time": "2026-06-01T17:57:37.786193706Z",
|
|
"start_time": "2026-06-01T17:57:37.737050952Z"
|
|
}
|
|
},
|
|
"source": [
|
|
"class TestModel(Model):\n",
|
|
" def __init__(self, name: str, work_dir: str = '.'):\n",
|
|
" super().__init__(name, work_dir)\n",
|
|
" self.unit1 = Entity((N_VIS, 200), EntityParams(do_gaussian_visible=True, do_gaussian_hidden=False), TrainingParams(learning_rate=0.005, momentum=0.9, num_epochs=1000, mini_batch_size=1000, weight_decay=0.0, l1_lambda=0.02))\n",
|
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" \n",
|
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" def forward(self, x: Mat):\n",
|
|
" x = self.unit1.forward(x)\n",
|
|
" return x\n",
|
|
" \n",
|
|
" def backward(self, x: Mat):\n",
|
|
" x = self.unit1.reconstruct(x)\n",
|
|
" return x"
|
|
],
|
|
"outputs": [],
|
|
"execution_count": 8
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"id": "6b3be9f6-38e1-442d-a7bd-1f3c164ec8d4",
|
|
"metadata": {
|
|
"editable": true,
|
|
"execution": {
|
|
"iopub.execute_input": "2026-06-01T17:49:21.506163Z",
|
|
"iopub.status.busy": "2026-06-01T17:49:21.506007Z",
|
|
"iopub.status.idle": "2026-06-01T17:50:15.215223Z",
|
|
"shell.execute_reply": "2026-06-01T17:50:15.213000Z"
|
|
},
|
|
"slideshow": {
|
|
"slide_type": ""
|
|
},
|
|
"tags": [],
|
|
"ExecuteTime": {
|
|
"end_time": "2026-06-01T17:58:19.592702084Z",
|
|
"start_time": "2026-06-01T17:57:37.787975671Z"
|
|
}
|
|
},
|
|
"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(normalize(train_subimages))\n",
|
|
"model.train(train_subimages)\n",
|
|
"\n",
|
|
"# save state\n",
|
|
"model.save()"
|
|
],
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"-------------------------------------------\n",
|
|
"Entity-192x200: progress : 0%\n",
|
|
"Entity-192x200: err_rms : 0.02766979830692578\n",
|
|
"Entity-192x200: l2_norm : 0.28264132630874533\n",
|
|
"-------------------------------------------\n",
|
|
"Entity-192x200: progress : 10%\n",
|
|
"Entity-192x200: err_rms : 0.02679979178767437\n",
|
|
"Entity-192x200: l2_norm : 0.3074716635549901\n",
|
|
"-------------------------------------------\n",
|
|
"Entity-192x200: progress : 20%\n",
|
|
"Entity-192x200: err_rms : 0.026938410963881977\n",
|
|
"Entity-192x200: l2_norm : 0.3136900760088252\n",
|
|
"-------------------------------------------\n",
|
|
"Entity-192x200: progress : 30%\n",
|
|
"Entity-192x200: err_rms : 0.026483431242494165\n",
|
|
"Entity-192x200: l2_norm : 0.31579110343803235\n",
|
|
"-------------------------------------------\n",
|
|
"Entity-192x200: progress : 40%\n",
|
|
"Entity-192x200: err_rms : 0.026563598336920666\n",
|
|
"Entity-192x200: l2_norm : 0.3174956999745583\n",
|
|
"-------------------------------------------\n",
|
|
"Entity-192x200: progress : 50%\n",
|
|
"Entity-192x200: err_rms : 0.025794590189848265\n",
|
|
"Entity-192x200: l2_norm : 0.317870546516689\n",
|
|
"-------------------------------------------\n",
|
|
"Entity-192x200: progress : 60%\n",
|
|
"Entity-192x200: err_rms : 0.026333598060321033\n",
|
|
"Entity-192x200: l2_norm : 0.31820741618872395\n",
|
|
"-------------------------------------------\n",
|
|
"Entity-192x200: progress : 70%\n",
|
|
"Entity-192x200: err_rms : 0.02614625896801818\n",
|
|
"Entity-192x200: l2_norm : 0.3191154559709311\n",
|
|
"-------------------------------------------\n",
|
|
"Entity-192x200: progress : 80%\n",
|
|
"Entity-192x200: err_rms : 0.026711505333452675\n",
|
|
"Entity-192x200: l2_norm : 0.318866243933147\n",
|
|
"-------------------------------------------\n",
|
|
"Entity-192x200: progress : 90%\n",
|
|
"Entity-192x200: err_rms : 0.026127792549075286\n",
|
|
"Entity-192x200: l2_norm : 0.31940734300797385\n",
|
|
"-------------------------------------------\n",
|
|
"Entity-192x200: progress : 100%\n",
|
|
"Entity-192x200: err_rms : 0.026640290805819943\n",
|
|
"Entity-192x200: l2_norm : 0.31940393226748176\n",
|
|
"-------------------------------------------\n",
|
|
"Entity-192x200: progress : 100%\n",
|
|
"Entity-192x200: err_rms_total : 0.026294031526082815\n",
|
|
"Entity-192x200: l2_norm : 0.32029096459810596\n"
|
|
]
|
|
}
|
|
],
|
|
"execution_count": 9
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"id": "d036b106-77a3-4993-bc2a-5fb164b8ec46",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2026-06-01T17:50:15.218877Z",
|
|
"iopub.status.busy": "2026-06-01T17:50:15.218611Z",
|
|
"iopub.status.idle": "2026-06-01T17:50:16.569332Z",
|
|
"shell.execute_reply": "2026-06-01T17:50:16.568354Z"
|
|
},
|
|
"ExecuteTime": {
|
|
"end_time": "2026-06-01T17:58:20.910856706Z",
|
|
"start_time": "2026-06-01T17:58:19.594628552Z"
|
|
}
|
|
},
|
|
"source": [
|
|
"# Plot reconstructions\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_subimages[image_indices[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, PATCH, PATCH))\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()"
|
|
],
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<Figure size 3000x3000 with 100 Axes>"
|
|
],
|
|
"image/png": 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|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data",
|
|
"jetTransient": {
|
|
"display_id": null
|
|
}
|
|
}
|
|
],
|
|
"execution_count": 10
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"id": "41430b5f",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2026-06-01T17:50:16.571054Z",
|
|
"iopub.status.busy": "2026-06-01T17:50:16.570860Z",
|
|
"iopub.status.idle": "2026-06-01T17:50:17.139950Z",
|
|
"shell.execute_reply": "2026-06-01T17:50:17.138865Z"
|
|
},
|
|
"ExecuteTime": {
|
|
"end_time": "2026-06-01T17:58:21.585629663Z",
|
|
"start_time": "2026-06-01T17:58:20.912692545Z"
|
|
}
|
|
},
|
|
"source": [
|
|
"import numpy\n",
|
|
"\n",
|
|
"# Reconstruct full 32x32 images by assembling reconstructed sub-images (overlap-averaged)\n",
|
|
"nx_steps = (32 - PATCH) // STRIDE + 1\n",
|
|
"ny_steps = (32 - PATCH) // STRIDE + 1\n",
|
|
"n_images = n_side\n",
|
|
"\n",
|
|
"fig, axes = plt.subplots(n_images, 2, figsize=(6, n_images * 3))\n",
|
|
"\n",
|
|
"for img_idx in range(n_images):\n",
|
|
" orig = np.reshape(train_images[img_idx], (3, 32, 32))\n",
|
|
" orig_display = np.asnumpy((orig - np.min(orig)) / (np.max(orig) - np.min(orig)))\n",
|
|
"\n",
|
|
" accum = numpy.zeros((3, 32, 32), dtype=numpy.float64)\n",
|
|
" count = numpy.zeros((1, 32, 32), dtype=numpy.float64)\n",
|
|
" for ix in range(nx_steps):\n",
|
|
" for iy in range(ny_steps):\n",
|
|
" sub_idx = img_idx * nx_steps * ny_steps + ix * ny_steps + iy\n",
|
|
" inp = train_subimages[sub_idx]\n",
|
|
" recon = model.backward(model.forward(inp))\n",
|
|
" arr = np.asnumpy(np.reshape(recon, (3, PATCH, PATCH)))\n",
|
|
" x0, y0 = ix * STRIDE, iy * STRIDE\n",
|
|
" accum[:, x0:x0+PATCH, y0:y0+PATCH] += arr\n",
|
|
" count[0, x0:x0+PATCH, y0:y0+PATCH] += 1.0\n",
|
|
"\n",
|
|
" recon_full = (accum / numpy.maximum(count, 1)).transpose(1, 2, 0)\n",
|
|
" lo, hi = recon_full.min(), recon_full.max()\n",
|
|
" recon_full = numpy.clip((recon_full - lo) / (hi - lo + 1e-8), 0, 1)\n",
|
|
"\n",
|
|
" axes[img_idx, 0].imshow(orig_display.transpose(1, 2, 0))\n",
|
|
" axes[img_idx, 0].axis('off')\n",
|
|
" if img_idx == 0:\n",
|
|
" axes[img_idx, 0].set_title('Original')\n",
|
|
"\n",
|
|
" axes[img_idx, 1].imshow(recon_full)\n",
|
|
" axes[img_idx, 1].axis('off')\n",
|
|
" if img_idx == 0:\n",
|
|
" axes[img_idx, 1].set_title('Reconstructed')\n",
|
|
"\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()"
|
|
],
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<Figure size 600x3000 with 20 Axes>"
|
|
],
|
|
"image/png": 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"
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data",
|
|
"jetTransient": {
|
|
"display_id": null
|
|
}
|
|
}
|
|
],
|
|
"execution_count": 11
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"id": "9adce292-cae6-455c-9409-c57ae71a36d5",
|
|
"metadata": {
|
|
"execution": {
|
|
"iopub.execute_input": "2026-06-01T17:50:17.141757Z",
|
|
"iopub.status.busy": "2026-06-01T17:50:17.141563Z",
|
|
"iopub.status.idle": "2026-06-01T17:50:18.599031Z",
|
|
"shell.execute_reply": "2026-06-01T17:50:18.598132Z"
|
|
},
|
|
"scrolled": true,
|
|
"ExecuteTime": {
|
|
"end_time": "2026-06-01T17:58:23.320011034Z",
|
|
"start_time": "2026-06-01T17:58:21.588136821Z"
|
|
}
|
|
},
|
|
"source": [
|
|
"# Plot weights\n",
|
|
"weights = model.unit1.state.w_hv\n",
|
|
"n, n_hid = weights.shape\n",
|
|
"weight_indices = np.array(random.sample(range(n_hid), n_side*n_side))\n",
|
|
"w = np.reshape(weights, (3, PATCH, PATCH, n_hid))\n",
|
|
"print(w.shape)\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 = np.asnumpy(w[:,:,:, weight_indices[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()"
|
|
],
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"(3, 8, 8, 200)\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<Figure size 3000x3000 with 100 Axes>"
|
|
],
|
|
"image/png": 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},
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"metadata": {},
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"output_type": "display_data",
|
|
"jetTransient": {
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|
"display_id": null
|
|
}
|
|
}
|
|
],
|
|
"execution_count": 12
|
|
},
|
|
{
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|
"cell_type": "code",
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|
"id": "c976fed5-162c-4a70-8219-fc6c68c1fb66",
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|
"metadata": {
|
|
"ExecuteTime": {
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|
"end_time": "2026-06-01T17:58:23.367461323Z",
|
|
"start_time": "2026-06-01T17:58:23.322515679Z"
|
|
}
|
|
},
|
|
"source": [],
|
|
"outputs": [],
|
|
"execution_count": 12
|
|
},
|
|
{
|
|
"cell_type": "code",
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|
"id": "661dfc9d-e58a-4994-a5fa-c377d7f743e5",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2026-06-01T17:58:23.416025632Z",
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"start_time": "2026-06-01T17:58:23.370109432Z"
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|
}
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|
},
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|
"source": [],
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|
"outputs": [],
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|
"execution_count": 12
|
|
},
|
|
{
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|
"cell_type": "code",
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|
"id": "c1a67046-17e4-4924-8067-da23481eb6d3",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2026-06-01T17:58:23.463714862Z",
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"start_time": "2026-06-01T17:58:23.418192823Z"
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|
}
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|
},
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|
"source": [],
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|
"outputs": [],
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|
"execution_count": 12
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|
}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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