Skip to content

Add notebook on ConvMixer implementation #28

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
guillepinto merged 8 commits into from
Feb 6, 2025
Merged

Add notebook on ConvMixer implementation #28

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
8 commits
Select commit Hold shift + click to select a range
2726e81
Add notebook on ConvMixer implementation
BrayanQuintero123 Nov 26, 2024
9bfe579
change the name of the notebook and the csv name
BrayanQuintero123 Dec 17, 2024
2949096
Change the Csv name to lowercase
BrayanQuintero123 Jan 27, 2025
f2b9bc0
Cambio temporal para forzar renombrado
BrayanQuintero123 Feb 2, 2025
a3c14a1
LoweCase file
BrayanQuintero123 Feb 2, 2025
845e03f
only lower case
BrayanQuintero123 Feb 2, 2025
d772905
Csv conflicts resolved
BrayanQuintero123 Feb 5, 2025
745239a
conflicts resolved with main
BrayanQuintero123 Feb 5, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 2 additions & 1 deletion automation/notebooks-table-data.csv
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,4 +13,5 @@ MLP Mixer,architectures/mlp-mixer.ipynb,,https://arxiv.org/abs/2105.01601
GloVe Word Embeddings, data_exploration/glove-word-embeddings.ipynb,https://github.com/stanfordnlp/GloVe,https://nlp.stanford.edu/pubs/glove.pdf
Vision Transformer (ViT),architectures/vit.ipynb,,https://arxiv.org/pdf/2010.11929
Multi-Head Attention, modules/multihead-self-attention.ipynb,,https://arxiv.org/abs/1706.03762
ResNet,architectures/resnet.ipynb,,https://arxiv.org/abs/1512.03385
ResNet,architectures/resnet.ipynb,,https://arxiv.org/abs/1512.03385
ConvMixer,architectures/ConvMixer.ipynb,,https://arxiv.org/pdf/2201.09792
216 changes: 216 additions & 0 deletions notebooks/architectures/ConvMixer.ipynb
View file
Open in desktop
Copy link
Member

@guillepinto guillepinto Jan 27, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

As I said in the other comment, the name of the .ipynb must be completely lowercase

Original file line number Diff line number Diff line change
@@ -0,0 +1,216 @@
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"source": [
"## ConvMixer"
],
"metadata": {
"id": "IJveajFZvdXK"
}
},
{
"cell_type": "code",
"source": [
"#@title **Install required packages**\n",
"\n",
"%%capture\n",
"! pip install torchinfo"
],
"metadata": {
"id": "q5AuzFB2tA12"
},
"execution_count": 27,
"outputs": []
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"id": "118P89a1osHb"
},
"outputs": [],
"source": [
"#@title **Importing libraries**\n",
"import torch # 2.5.1+cu121\n",
"import torch.nn as nn\n",
"import torchinfo #1.8.0"
]
},
{
"cell_type": "code",
"source": [
"# Note: Not all dependencies have the __version__ method.\n",
"print(f\"torch version: {torch.__version__}\")\n",
"print(f\"torchinfo version: {torchinfo.__version__}\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "QchOSIbro1zf",
"outputId": "94003f5a-622f-4f54-e916-26fbbff86c17"
},
"execution_count": 37,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"torch version: 2.5.1+cu121\n",
"torchinfo version: 1.8.0\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"**ConvMixer architecture code**\n"
],
"metadata": {
"id": "hrG5QYB4pRMu"
}
},
{
"cell_type": "code",
"source": [
"class Residual(nn.Module):\n",
" def __init__(self, fn):\n",
" super().__init__()\n",
" self.fn = fn\n",
"\n",
" def forward(self, x):\n",
" return self.fn(x) + x\n",
"\n",
"def ConvMixer(dim, depth, kernel_size = 9, patch_size = 7, n_classes = 1000):\n",
" return nn.Sequential(\n",
" nn.Conv2d(3, dim, kernel_size = patch_size, stride = patch_size),\n",
" nn.GELU(),\n",
" nn.BatchNorm2d(dim),\n",
" *[nn.Sequential(\n",
" Residual(nn.Sequential(\n",
" nn.Conv2d(dim, dim, kernel_size, groups=dim, padding=\"same\"),\n",
" nn.GELU(),\n",
" nn.BatchNorm2d(dim)\n",
" )),\n",
" nn.Conv2d(dim,dim, kernel_size = 1),\n",
" nn.GELU(),\n",
" nn.BatchNorm2d(dim)\n",
" )for i in range(depth)],\n",
" nn.AdaptiveAvgPool2d((1,1)),\n",
" nn.Flatten(),\n",
" nn.Linear(dim, n_classes)\n",
" )"
],
"metadata": {
"id": "r2d2e2P0pdan"
},
"execution_count": 38,
"outputs": []
},
{
"cell_type": "code",
"source": [
"model = ConvMixer(2048, 8, kernel_size=9, patch_size=1, n_classes=1000)\n",
"torchinfo.summary(model)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "9YM5zfNoslTx",
"outputId": "1b5a1295-d3ac-49c9-d61d-ae986021ad00"
},
"execution_count": 41,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"=================================================================\n",
"Layer (type:depth-idx) Param #\n",
"=================================================================\n",
"Sequential --\n",
"├─Conv2d: 1-1 8,192\n",
"├─GELU: 1-2 --\n",
"├─BatchNorm2d: 1-3 4,096\n",
"├─Sequential: 1-4 --\n",
"│ └─Residual: 2-1 --\n",
"│ │ └─Sequential: 3-1 172,032\n",
"│ └─Conv2d: 2-2 4,196,352\n",
"│ └─GELU: 2-3 --\n",
"│ └─BatchNorm2d: 2-4 4,096\n",
"├─Sequential: 1-5 --\n",
"│ └─Residual: 2-5 --\n",
"│ │ └─Sequential: 3-2 172,032\n",
"│ └─Conv2d: 2-6 4,196,352\n",
"│ └─GELU: 2-7 --\n",
"│ └─BatchNorm2d: 2-8 4,096\n",
"├─Sequential: 1-6 --\n",
"│ └─Residual: 2-9 --\n",
"│ │ └─Sequential: 3-3 172,032\n",
"│ └─Conv2d: 2-10 4,196,352\n",
"│ └─GELU: 2-11 --\n",
"│ └─BatchNorm2d: 2-12 4,096\n",
"├─Sequential: 1-7 --\n",
"│ └─Residual: 2-13 --\n",
"│ │ └─Sequential: 3-4 172,032\n",
"│ └─Conv2d: 2-14 4,196,352\n",
"│ └─GELU: 2-15 --\n",
"│ └─BatchNorm2d: 2-16 4,096\n",
"├─Sequential: 1-8 --\n",
"│ └─Residual: 2-17 --\n",
"│ │ └─Sequential: 3-5 172,032\n",
"│ └─Conv2d: 2-18 4,196,352\n",
"│ └─GELU: 2-19 --\n",
"│ └─BatchNorm2d: 2-20 4,096\n",
"├─Sequential: 1-9 --\n",
"│ └─Residual: 2-21 --\n",
"│ │ └─Sequential: 3-6 172,032\n",
"│ └─Conv2d: 2-22 4,196,352\n",
"│ └─GELU: 2-23 --\n",
"│ └─BatchNorm2d: 2-24 4,096\n",
"├─Sequential: 1-10 --\n",
"│ └─Residual: 2-25 --\n",
"│ │ └─Sequential: 3-7 172,032\n",
"│ └─Conv2d: 2-26 4,196,352\n",
"│ └─GELU: 2-27 --\n",
"│ └─BatchNorm2d: 2-28 4,096\n",
"├─Sequential: 1-11 --\n",
"│ └─Residual: 2-29 --\n",
"│ │ └─Sequential: 3-8 172,032\n",
"│ └─Conv2d: 2-30 4,196,352\n",
"│ └─GELU: 2-31 --\n",
"│ └─BatchNorm2d: 2-32 4,096\n",
"├─AdaptiveAvgPool2d: 1-12 --\n",
"├─Flatten: 1-13 --\n",
"├─Linear: 1-14 2,049,000\n",
"=================================================================\n",
"Total params: 37,041,128\n",
"Trainable params: 37,041,128\n",
"Non-trainable params: 0\n",
"================================================================="
]
},
"metadata": {},
"execution_count": 41
}
]
}
]
}