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-rw-r--r--notebooks/04-convnext.ipynb248
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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "7c02ae76-b540-4b16-9492-e9210b3b9249",
+ "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",
+ "\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": 15,
+ "id": "ccdb6dde-47e5-429a-88f2-0764fb7e259a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from hydra import compose, initialize\n",
+ "from omegaconf import OmegaConf\n",
+ "from hydra.utils import instantiate"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "id": "3cf50475-39f2-4642-a7d1-5bcbc0a036f7",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "path = \"../training/conf/network/convnext.yaml\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 37,
+ "id": "e52ecb01-c975-4e55-925d-1182c7aea473",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "with open(path, \"rb\") as f:\n",
+ " cfg = OmegaConf.load(f)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 38,
+ "id": "f939aa37-7b1d-45cc-885c-323c4540bda1",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{'_target_': 'text_recognizer.network.convnext.ConvNext', 'dim': 16, 'dim_mults': [2, 4, 8], 'depths': [3, 3, 6], 'downsampling_factors': [[2, 2], [2, 2], [2, 2]], 'attn': {'_target_': 'text_recognizer.network.convnext.TransformerBlock', 'attn': {'_target_': 'text_recognizer.network.convnext.Attention', 'dim': 128, 'heads': 4, 'dim_head': 64, 'scale': 8}, 'ff': {'_target_': 'text_recognizer.network.convnext.FeedForward', 'dim': 128, 'mult': 4}}}"
+ ]
+ },
+ "execution_count": 38,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "cfg"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "id": "a2b420c1",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "cfg.dim_mults = [2, 4, 8, 8]\n",
+ "cfg.depths = [3, 3, 6, 6]\n",
+ "cfg.downsampling_factors = [[2, 2], [2, 2], [2, 2], [2, 1]]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 39,
+ "id": "c9589350",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "net = instantiate(cfg)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 40,
+ "id": "618b997c-e6a6-4487-b70c-9d260cb556d3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from torchinfo import summary"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 41,
+ "id": "25759b7b-8deb-4163-b75d-a1357c9fe88f",
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "====================================================================================================\n",
+ "Layer (type:depth-idx) Output Shape Param #\n",
+ "====================================================================================================\n",
+ "ConvNext [2, 128, 72, 80] 165,408\n",
+ "├─TransformerBlock: 1-5 [2, 128, 72, 80] (recursive)\n",
+ "│ └─Attention: 2-6 [2, 128, 72, 80] (recursive)\n",
+ "│ │ └─LayerNorm: 3-13 [2, 128, 72, 80] (recursive)\n",
+ "├─Conv2d: 1-3 [2, 16, 576, 640] (recursive)\n",
+ "├─TransformerBlock: 1 -- --\n",
+ "│ └─Attention: 2 -- --\n",
+ "│ │ └─Conv2d: 3-15 [2, 128, 72, 80] (recursive)\n",
+ "│ └─FeedForward: 2-7 [2, 128, 72, 80] (recursive)\n",
+ "│ │ └─Residual: 3-16 [2, 128, 72, 80] (recursive)\n",
+ "│ │ │ └─Sequential: 4-26 [2, 128, 72, 80] (recursive)\n",
+ "├─Conv2d: 1-3 [2, 16, 576, 640] (recursive)\n",
+ "├─ModuleList: 1-4 -- --\n",
+ "│ └─ModuleList: 2-3 -- --\n",
+ "│ │ └─ConvNextBlock: 3-4 [2, 16, 576, 640] --\n",
+ "│ │ │ └─Conv2d: 4-2 [2, 16, 576, 640] 800\n",
+ "│ │ │ └─Sequential: 4-3 [2, 16, 576, 640] 9,280\n",
+ "│ │ │ └─Identity: 4-4 [2, 16, 576, 640] --\n",
+ "│ │ └─ModuleList: 3-5 -- --\n",
+ "│ │ │ └─ConvNextBlock: 4-5 [2, 16, 576, 640] 10,080\n",
+ "│ │ │ └─ConvNextBlock: 4-6 [2, 16, 576, 640] 10,080\n",
+ "│ │ │ └─ConvNextBlock: 4-7 [2, 16, 576, 640] 10,080\n",
+ "│ │ └─Downsample: 3-6 [2, 32, 288, 320] --\n",
+ "│ │ │ └─Sequential: 4-8 [2, 32, 288, 320] 2,080\n",
+ "│ └─ModuleList: 2-4 -- --\n",
+ "│ │ └─ConvNextBlock: 3-7 [2, 32, 288, 320] --\n",
+ "│ │ │ └─Conv2d: 4-9 [2, 32, 288, 320] 1,600\n",
+ "│ │ │ └─Sequential: 4-10 [2, 32, 288, 320] 36,992\n",
+ "│ │ │ └─Identity: 4-11 [2, 32, 288, 320] --\n",
+ "│ │ └─ModuleList: 3-8 -- --\n",
+ "│ │ │ └─ConvNextBlock: 4-12 [2, 32, 288, 320] 38,592\n",
+ "│ │ │ └─ConvNextBlock: 4-13 [2, 32, 288, 320] 38,592\n",
+ "│ │ │ └─ConvNextBlock: 4-14 [2, 32, 288, 320] 38,592\n",
+ "│ │ └─Downsample: 3-9 [2, 64, 144, 160] --\n",
+ "│ │ │ └─Sequential: 4-15 [2, 64, 144, 160] 8,256\n",
+ "│ └─ModuleList: 2-5 -- --\n",
+ "│ │ └─ConvNextBlock: 3-10 [2, 64, 144, 160] --\n",
+ "│ │ │ └─Conv2d: 4-16 [2, 64, 144, 160] 3,200\n",
+ "│ │ │ └─Sequential: 4-17 [2, 64, 144, 160] 147,712\n",
+ "│ │ │ └─Identity: 4-18 [2, 64, 144, 160] --\n",
+ "│ │ └─ModuleList: 3-11 -- --\n",
+ "│ │ │ └─ConvNextBlock: 4-19 [2, 64, 144, 160] 150,912\n",
+ "│ │ │ └─ConvNextBlock: 4-20 [2, 64, 144, 160] 150,912\n",
+ "│ │ │ └─ConvNextBlock: 4-21 [2, 64, 144, 160] 150,912\n",
+ "│ │ │ └─ConvNextBlock: 4-22 [2, 64, 144, 160] 150,912\n",
+ "│ │ │ └─ConvNextBlock: 4-23 [2, 64, 144, 160] 150,912\n",
+ "│ │ │ └─ConvNextBlock: 4-24 [2, 64, 144, 160] 150,912\n",
+ "│ │ └─Downsample: 3-12 [2, 128, 72, 80] --\n",
+ "│ │ │ └─Sequential: 4-25 [2, 128, 72, 80] 32,896\n",
+ "├─TransformerBlock: 1-5 [2, 128, 72, 80] (recursive)\n",
+ "│ └─Attention: 2-6 [2, 128, 72, 80] (recursive)\n",
+ "│ │ └─LayerNorm: 3-13 [2, 128, 72, 80] (recursive)\n",
+ "│ │ └─Conv2d: 3-14 [2, 768, 72, 80] 98,304\n",
+ "│ │ └─Conv2d: 3-15 [2, 128, 72, 80] (recursive)\n",
+ "│ └─FeedForward: 2-7 [2, 128, 72, 80] (recursive)\n",
+ "│ │ └─Residual: 3-16 [2, 128, 72, 80] (recursive)\n",
+ "│ │ │ └─Sequential: 4-26 [2, 128, 72, 80] (recursive)\n",
+ "├─LayerNorm: 1-6 [2, 128, 72, 80] 128\n",
+ "====================================================================================================\n",
+ "Total params: 1,558,144\n",
+ "Trainable params: 1,558,144\n",
+ "Non-trainable params: 0\n",
+ "Total mult-adds (G): 114.00\n",
+ "====================================================================================================\n",
+ "Input size (MB): 2.95\n",
+ "Forward/backward pass size (MB): 3822.06\n",
+ "Params size (MB): 5.57\n",
+ "Estimated Total Size (MB): 3830.58\n",
+ "===================================================================================================="
+ ]
+ },
+ "execution_count": 41,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "summary(net, (2, 1, 576, 640), device=\"cpu\", depth=4)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "05c1d499",
+ "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": "3.9.4"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
generated by cgit v1.2.3-70-g09d2 (git 2.46.0) at 2024-12-25 06:33:42 +0000