diff options
Diffstat (limited to 'notebooks/04-conv-transformer.ipynb')
| -rw-r--r-- | notebooks/04-conv-transformer.ipynb | 249 |
1 files changed, 249 insertions, 0 deletions
diff --git a/notebooks/04-conv-transformer.ipynb b/notebooks/04-conv-transformer.ipynb new file mode 100644 index 0000000..3303b63 --- /dev/null +++ b/notebooks/04-conv-transformer.ipynb @@ -0,0 +1,249 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "7c02ae76-b540-4b16-9492-e9210b3b9249", + "metadata": {}, + "outputs": [], + "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": 2, + "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": 3, + "id": "3cf50475-39f2-4642-a7d1-5bcbc0a036f7", + "metadata": {}, + "outputs": [], + "source": [ + "path = \"../training/conf/network/conv_transformer.yaml\"" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "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": 10, + "id": "f939aa37-7b1d-45cc-885c-323c4540bda1", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'_target_': 'text_recognizer.networks.ConvTransformer', 'input_dims': [1, 1, 576, 640], 'hidden_dim': 128, 'num_classes': 58, 'pad_index': 3, 'encoder': {'_target_': 'text_recognizer.networks.EfficientNet', 'arch': 'b0', 'stochastic_dropout_rate': 0.2, 'bn_momentum': 0.99, 'bn_eps': 0.001, 'depth': 5, 'out_channels': 128, 'stride': [2, 1]}, 'decoder': {'_target_': 'text_recognizer.networks.transformer.Decoder', 'depth': 6, 'block': {'_target_': 'text_recognizer.networks.transformer.DecoderBlock', 'self_attn': {'_target_': 'text_recognizer.networks.transformer.Attention', 'dim': 128, 'num_heads': 8, 'dim_head': 64, 'dropout_rate': 0.4, 'causal': True, 'rotary_embedding': {'_target_': 'text_recognizer.networks.transformer.RotaryEmbedding', 'dim': 64}}, 'cross_attn': {'_target_': 'text_recognizer.networks.transformer.Attention', 'dim': 128, 'num_heads': 8, 'dim_head': 64, 'dropout_rate': 0.4, 'causal': False}, 'norm': {'_target_': 'text_recognizer.networks.transformer.RMSNorm', 'dim': 128}, 'ff': {'_target_': 'text_recognizer.networks.transformer.FeedForward', 'dim': 128, 'dim_out': None, 'expansion_factor': 2, 'glu': True, 'dropout_rate': 0.4}}}, 'pixel_embedding': {'_target_': 'text_recognizer.networks.transformer.AxialPositionalEmbedding', 'dim': 128, 'shape': [18, 80]}}" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cfg" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "aaeab329-aeb0-4a1b-aa35-5a2aab81b1d0", + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "net = instantiate(cfg)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "618b997c-e6a6-4487-b70c-9d260cb556d3", + "metadata": {}, + "outputs": [], + "source": [ + "from torchinfo import summary" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "25759b7b-8deb-4163-b75d-a1357c9fe88f", + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "==============================================================================================================\n", + "Layer (type:depth-idx) Output Shape Param #\n", + "==============================================================================================================\n", + "ConvTransformer [1, 58, 682] --\n", + "├─EfficientNet: 1-1 [1, 128, 18, 80] 850,044\n", + "│ └─Sequential: 2-1 [1, 16, 288, 320] --\n", + "│ │ └─ZeroPad2d: 3-1 [1, 1, 577, 641] --\n", + "│ │ └─Conv2d: 3-2 [1, 16, 288, 320] 144\n", + "│ │ └─BatchNorm2d: 3-3 [1, 16, 288, 320] 32\n", + "│ │ └─Mish: 3-4 [1, 16, 288, 320] --\n", + "│ └─ModuleList: 2 -- --\n", + "│ │ └─MBConvBlock: 3-5 [1, 16, 288, 320] --\n", + "│ │ │ └─Depthwise: 4-1 [1, 16, 288, 320] 176\n", + "│ │ │ └─SqueezeAndExcite: 4-2 [1, 16, 288, 320] 148\n", + "│ │ │ └─Pointwise: 4-3 [1, 16, 288, 320] 288\n", + "│ │ └─MBConvBlock: 3-6 [1, 24, 144, 160] --\n", + "│ │ │ └─InvertedBottleneck: 4-4 [1, 96, 288, 320] 1,728\n", + "│ │ │ └─Depthwise: 4-5 [1, 96, 144, 160] 1,056\n", + "│ │ │ └─SqueezeAndExcite: 4-6 [1, 96, 144, 160] 868\n", + "│ │ │ └─Pointwise: 4-7 [1, 24, 144, 160] 2,352\n", + "│ │ └─MBConvBlock: 3-7 [1, 24, 144, 160] --\n", + "│ │ │ └─InvertedBottleneck: 4-8 [1, 144, 144, 160] 3,744\n", + "│ │ │ └─Depthwise: 4-9 [1, 144, 144, 160] 1,584\n", + "│ │ │ └─SqueezeAndExcite: 4-10 [1, 144, 144, 160] 1,878\n", + "│ │ │ └─Pointwise: 4-11 [1, 24, 144, 160] 3,504\n", + "│ │ └─MBConvBlock: 3-8 [1, 40, 72, 80] --\n", + "│ │ │ └─InvertedBottleneck: 4-12 [1, 144, 144, 160] 3,744\n", + "│ │ │ └─Depthwise: 4-13 [1, 144, 72, 80] 3,888\n", + "│ │ │ └─SqueezeAndExcite: 4-14 [1, 144, 72, 80] 1,878\n", + "│ │ │ └─Pointwise: 4-15 [1, 40, 72, 80] 5,840\n", + "│ │ └─MBConvBlock: 3-9 [1, 40, 72, 80] --\n", + "│ │ │ └─InvertedBottleneck: 4-16 [1, 240, 72, 80] 10,080\n", + "│ │ │ └─Depthwise: 4-17 [1, 240, 72, 80] 6,480\n", + "│ │ │ └─SqueezeAndExcite: 4-18 [1, 240, 72, 80] 5,050\n", + "│ │ │ └─Pointwise: 4-19 [1, 40, 72, 80] 9,680\n", + "│ │ └─MBConvBlock: 3-10 [1, 80, 36, 80] --\n", + "│ │ │ └─InvertedBottleneck: 4-20 [1, 240, 72, 80] 10,080\n", + "│ │ │ └─Depthwise: 4-21 [1, 240, 36, 80] 2,640\n", + "│ │ │ └─SqueezeAndExcite: 4-22 [1, 240, 36, 80] 5,050\n", + "│ │ │ └─Pointwise: 4-23 [1, 80, 36, 80] 19,360\n", + "│ │ └─MBConvBlock: 3-11 [1, 80, 36, 80] --\n", + "│ │ │ └─InvertedBottleneck: 4-24 [1, 480, 36, 80] 39,360\n", + "│ │ │ └─Depthwise: 4-25 [1, 480, 36, 80] 5,280\n", + "│ │ │ └─SqueezeAndExcite: 4-26 [1, 480, 36, 80] 19,700\n", + "│ │ │ └─Pointwise: 4-27 [1, 80, 36, 80] 38,560\n", + "│ │ └─MBConvBlock: 3-12 [1, 80, 36, 80] --\n", + "│ │ │ └─InvertedBottleneck: 4-28 [1, 480, 36, 80] 39,360\n", + "│ │ │ └─Depthwise: 4-29 [1, 480, 36, 80] 5,280\n", + "│ │ │ └─SqueezeAndExcite: 4-30 [1, 480, 36, 80] 19,700\n", + "│ │ │ └─Pointwise: 4-31 [1, 80, 36, 80] 38,560\n", + "│ │ └─MBConvBlock: 3-13 [1, 112, 18, 80] --\n", + "│ │ │ └─InvertedBottleneck: 4-32 [1, 480, 36, 80] 39,360\n", + "│ │ │ └─Depthwise: 4-33 [1, 480, 18, 80] 12,960\n", + "│ │ │ └─SqueezeAndExcite: 4-34 [1, 480, 18, 80] 19,700\n", + "│ │ │ └─Pointwise: 4-35 [1, 112, 18, 80] 53,984\n", + "│ │ └─MBConvBlock: 3-14 [1, 112, 18, 80] --\n", + "│ │ │ └─InvertedBottleneck: 4-36 [1, 672, 18, 80] 76,608\n", + "│ │ │ └─Depthwise: 4-37 [1, 672, 18, 80] 18,144\n", + "│ │ │ └─SqueezeAndExcite: 4-38 [1, 672, 18, 80] 38,332\n", + "│ │ │ └─Pointwise: 4-39 [1, 112, 18, 80] 75,488\n", + "│ │ └─MBConvBlock: 3-15 [1, 112, 18, 80] --\n", + "│ │ │ └─InvertedBottleneck: 4-40 [1, 672, 18, 80] 76,608\n", + "│ │ │ └─Depthwise: 4-41 [1, 672, 18, 80] 18,144\n", + "│ │ │ └─SqueezeAndExcite: 4-42 [1, 672, 18, 80] 38,332\n", + "│ │ │ └─Pointwise: 4-43 [1, 112, 18, 80] 75,488\n", + "│ └─Sequential: 2-2 [1, 128, 18, 80] --\n", + "│ │ └─Conv2d: 3-16 [1, 128, 18, 80] 14,336\n", + "│ │ └─BatchNorm2d: 3-17 [1, 128, 18, 80] 256\n", + "│ │ └─Dropout: 3-18 [1, 128, 18, 80] --\n", + "├─Conv2d: 1-2 [1, 128, 18, 80] 16,512\n", + "├─AxialPositionalEmbedding: 1-3 [1, 128, 18, 80] 12,544\n", + "├─Embedding: 1-4 [1, 682, 128] 7,424\n", + "├─Decoder: 1-5 [1, 682, 128] --\n", + "│ └─ModuleList: 2 -- --\n", + "│ │ └─DecoderBlock: 3-19 [1, 682, 128] --\n", + "│ │ └─DecoderBlock: 3-20 [1, 682, 128] --\n", + "│ │ └─DecoderBlock: 3-21 [1, 682, 128] --\n", + "│ │ └─DecoderBlock: 3-22 [1, 682, 128] --\n", + "│ │ └─DecoderBlock: 3-23 [1, 682, 128] --\n", + "│ │ └─DecoderBlock: 3-24 [1, 682, 128] --\n", + "├─Linear: 1-6 [1, 682, 58] 7,482\n", + "==============================================================================================================\n", + "Total params: 4,652,006\n", + "Trainable params: 4,652,006\n", + "Non-trainable params: 0\n", + "Total mult-adds (G): 2.44\n", + "==============================================================================================================\n", + "Input size (MB): 1.48\n", + "Forward/backward pass size (MB): 1041.70\n", + "Params size (MB): 18.61\n", + "Estimated Total Size (MB): 1061.78\n", + "==============================================================================================================" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "summary(net, ((1, 1, 576, 640), (1, 682)), device=\"cpu\", depth=4)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "506f01a3", + "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 +} |