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-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 7,
- "id": "136a80f5-10e1-40c4-973a-a7eb7939bb1f",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "The autoreload extension is already loaded. To reload it, use:\n",
- " %reload_ext autoreload\n"
- ]
- }
- ],
- "source": [
- "import os\n",
- "os.environ['CUDA_VISIBLE_DEVICE'] = ''\n",
- "import random\n",
- "\n",
- "%matplotlib inline\n",
- "import matplotlib.pyplot as plt\n",
- "\n",
- "import numpy as np\n",
- "from omegaconf import OmegaConf\n",
- "from hydra import compose, initialize\n",
- "from omegaconf import OmegaConf\n",
- "from hydra.utils import instantiate\n",
- "from torchinfo import summary\n",
- "%load_ext autoreload\n",
- "%autoreload 2\n",
- "\n",
- "from importlib.util import find_spec\n",
- "if find_spec(\"text_recognizer\") is None:\n",
- " import sys\n",
- " sys.path.append('..')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "id": "1a0fb9ca-1886-4fd4-839f-dc111a450cfd",
- "metadata": {},
- "outputs": [],
- "source": [
- "path = \"../training/conf/network/vqvae.yaml\""
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "id": "0182a614-5781-44a6-b659-008e7c584fa7",
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "encoder:\n",
- " _target_: text_recognizer.networks.vqvae.encoder.Encoder\n",
- " in_channels: 1\n",
- " hidden_dim: 32\n",
- " channels_multipliers:\n",
- " - 1\n",
- " - 2\n",
- " - 4\n",
- " dropout_rate: 0.0\n",
- " activation: mish\n",
- " use_norm: true\n",
- " num_residuals: 4\n",
- " residual_channels: 32\n",
- "decoder:\n",
- " _target_: text_recognizer.networks.vqvae.decoder.Decoder\n",
- " out_channels: 1\n",
- " hidden_dim: 32\n",
- " channels_multipliers:\n",
- " - 4\n",
- " - 2\n",
- " - 1\n",
- " dropout_rate: 0.0\n",
- " activation: mish\n",
- " use_norm: true\n",
- " num_residuals: 4\n",
- " residual_channels: 32\n",
- "_target_: text_recognizer.networks.vqvae.vqvae.VQVAE\n",
- "hidden_dim: 128\n",
- "embedding_dim: 32\n",
- "num_embeddings: 8192\n",
- "decay: 0.99\n",
- "\n"
- ]
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "/home/aktersnurra/.cache/pypoetry/virtualenvs/text-recognizer-ejNaVa9M-py3.9/lib/python3.9/site-packages/hydra/_internal/defaults_list.py:251: UserWarning: In 'vqvae': Defaults list is missing `_self_`. See https://hydra.cc/docs/upgrades/1.0_to_1.1/default_composition_order for more information\n",
- " warnings.warn(msg, UserWarning)\n"
- ]
- }
- ],
- "source": [
- "with initialize(config_path=\"../training/conf/network/\", job_name=\"test_app\"):\n",
- " cfg = compose(config_name=\"vqvae\")\n",
- " print(OmegaConf.to_yaml(cfg))"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "id": "a500f94c-7dae-477e-a3fb-2a2d62ee7b72",
- "metadata": {},
- "outputs": [],
- "source": [
- "net = instantiate(cfg)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "id": "7f3b3559-5e23-485e-bf57-9405568a1fbf",
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "====================================================================================================\n",
- "Layer (type:depth-idx) Output Shape Param #\n",
- "====================================================================================================\n",
- "VQVAE -- --\n",
- "├─Encoder: 1-1 [1, 128, 72, 80] --\n",
- "│ └─Sequential: 2-1 [1, 128, 72, 80] --\n",
- "│ │ └─Conv2d: 3-1 [1, 32, 576, 640] 320\n",
- "│ │ └─Normalize: 3-2 [1, 32, 576, 640] 64\n",
- "│ │ └─Mish: 3-3 [1, 32, 576, 640] --\n",
- "│ │ └─Mish: 3-4 [1, 32, 576, 640] --\n",
- "│ │ └─Mish: 3-5 [1, 32, 576, 640] --\n",
- "│ │ └─Conv2d: 3-6 [1, 32, 288, 320] 16,416\n",
- "│ │ └─Normalize: 3-7 [1, 32, 288, 320] 64\n",
- "│ │ └─Mish: 3-8 [1, 32, 288, 320] --\n",
- "│ │ └─Mish: 3-9 [1, 32, 288, 320] --\n",
- "│ │ └─Mish: 3-10 [1, 32, 288, 320] --\n",
- "│ │ └─Conv2d: 3-11 [1, 64, 144, 160] 32,832\n",
- "│ │ └─Normalize: 3-12 [1, 64, 144, 160] 128\n",
- "│ │ └─Mish: 3-13 [1, 64, 144, 160] --\n",
- "│ │ └─Mish: 3-14 [1, 64, 144, 160] --\n",
- "│ │ └─Mish: 3-15 [1, 64, 144, 160] --\n",
- "│ │ └─Conv2d: 3-16 [1, 128, 72, 80] 131,200\n",
- "│ │ └─Residual: 3-17 [1, 128, 72, 80] 41,280\n",
- "│ │ └─Residual: 3-18 [1, 128, 72, 80] 41,280\n",
- "│ │ └─Residual: 3-19 [1, 128, 72, 80] 41,280\n",
- "│ │ └─Residual: 3-20 [1, 128, 72, 80] 41,280\n",
- "├─Conv2d: 1-2 [1, 32, 72, 80] 4,128\n",
- "├─VectorQuantizer: 1-3 [1, 32, 72, 80] --\n",
- "├─Conv2d: 1-4 [1, 128, 72, 80] 4,224\n",
- "├─Decoder: 1-5 [1, 1, 576, 640] --\n",
- "│ └─Sequential: 2-2 [1, 1, 576, 640] --\n",
- "│ │ └─Residual: 3-21 [1, 128, 72, 80] 41,280\n",
- "│ │ └─Residual: 3-22 [1, 128, 72, 80] 41,280\n",
- "│ │ └─Residual: 3-23 [1, 128, 72, 80] 41,280\n",
- "│ │ └─Residual: 3-24 [1, 128, 72, 80] 41,280\n",
- "│ │ └─Normalize: 3-25 [1, 128, 72, 80] 256\n",
- "│ │ └─Mish: 3-26 [1, 128, 72, 80] --\n",
- "│ │ └─Mish: 3-27 [1, 128, 72, 80] --\n",
- "│ │ └─Mish: 3-28 [1, 128, 72, 80] --\n",
- "│ │ └─ConvTranspose2d: 3-29 [1, 64, 144, 160] 131,136\n",
- "│ │ └─Normalize: 3-30 [1, 64, 144, 160] 128\n",
- "│ │ └─Mish: 3-31 [1, 64, 144, 160] --\n",
- "│ │ └─Mish: 3-32 [1, 64, 144, 160] --\n",
- "│ │ └─Mish: 3-33 [1, 64, 144, 160] --\n",
- "│ │ └─ConvTranspose2d: 3-34 [1, 32, 288, 320] 32,800\n",
- "│ │ └─Normalize: 3-35 [1, 32, 288, 320] 64\n",
- "│ │ └─Mish: 3-36 [1, 32, 288, 320] --\n",
- "│ │ └─Mish: 3-37 [1, 32, 288, 320] --\n",
- "│ │ └─Mish: 3-38 [1, 32, 288, 320] --\n",
- "│ │ └─ConvTranspose2d: 3-39 [1, 32, 576, 640] 16,416\n",
- "│ │ └─Normalize: 3-40 [1, 32, 576, 640] 64\n",
- "│ │ └─Conv2d: 3-41 [1, 1, 576, 640] 289\n",
- "====================================================================================================\n",
- "Total params: 700,769\n",
- "Trainable params: 700,769\n",
- "Non-trainable params: 0\n",
- "Total mult-adds (G): 17.28\n",
- "====================================================================================================\n",
- "Input size (MB): 1.47\n",
- "Forward/backward pass size (MB): 659.13\n",
- "Params size (MB): 2.80\n",
- "Estimated Total Size (MB): 663.41\n",
- "===================================================================================================="
- ]
- },
- "execution_count": 9,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "summary(net, (1, 1, 576, 640), device=\"cpu\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "id": "9f880b03-d641-4640-acd3-aa5666ca5184",
- "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": "3.9.7"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
generated by cgit v1.2.3-70-g09d2 (git 2.46.0) at 2024-09-20 12:26:33 +0000