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Diffstat (limited to 'notebooks')
-rw-r--r-- | notebooks/04-convnext.ipynb | 248 |
1 files changed, 0 insertions, 248 deletions
diff --git a/notebooks/04-convnext.ipynb b/notebooks/04-convnext.ipynb deleted file mode 100644 index 5ab71c8..0000000 --- a/notebooks/04-convnext.ipynb +++ /dev/null @@ -1,248 +0,0 @@ -{ - "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 -} |