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nan-wang/pixelshuffling.ipynb

Created December 25, 2024 01:02
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pixelshuffling.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/nan-wang/5a01f5b595682e815402114e72bf1211/pixelshuffling.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"source": [
"import torch"
],
"metadata": {
"id": "h7IG0Z2JsrIR"
},
"execution_count": 1,
"outputs": []
},
{
"cell_type": "code",
"source": [
" # https://github.com/OpenGVLab/InternVL/blob/869d3be88d40d79162ca23b1ff5380d657883b55/internvl_chat/internvl/model/internvl_chat/modeling_internvl_chat.py#L252\n",
" def pixel_shuffle(x, scale_factor=0.5):\n",
" n, w, h, c = x.size()\n",
" # N, W, H, C --> N, W, H * scale, C // scale\n",
" x = x.view(n, w, int(h * scale_factor), int(c / scale_factor))\n",
" # N, W, H * scale, C // scale --> N, H * scale, W, C // scale\n",
" x = x.permute(0, 2, 1, 3).contiguous()\n",
" # N, H * scale, W, C // scale --> N, H * scale, W * scale, C // (scale ** 2)\n",
" x = x.view(n, int(h * scale_factor), int(w * scale_factor),\n",
" int(c / (scale_factor * scale_factor)))\n",
"\n",
" x = x.permute(0, 2, 1, 3).contiguous()\n",
" return x.reshape(n, -1, 32)"
],
"metadata": {
"id": "b35OP1ynseIu"
},
"execution_count": 129,
"outputs": []
},
{
"cell_type": "code",
"source": [
"batch_size = 1\n",
"width = 4\n",
"height = 4\n",
"channels = 8\n",
"fake_image_tensor = torch.tensor(\n",
" [[\n",
" [\n",
" [1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118],\n",
" [1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128],\n",
" [2131, 2132, 2133, 2134, 2135, 2136, 2137, 2138],\n",
" [2141, 2142, 2143, 2144, 2145, 2146, 2147, 2148],\n",
" ],\n",
" [\n",
" [1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218],\n",
" [1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228],\n",
" [2231, 2232, 2233, 2234, 2235, 2236, 2237, 2238],\n",
" [2241, 2242, 2243, 2244, 2245, 2246, 2247, 2248],\n",
" ],\n",
" [\n",
" [3311, 3312, 3313, 3314, 3315, 3316, 3317, 3318],\n",
" [3321, 3322, 3323, 3324, 3325, 3326, 3327, 3328],\n",
" [4331, 4332, 4333, 4334, 4335, 4336, 4337, 4338],\n",
" [4341, 4342, 4343, 4344, 4345, 4346, 4347, 4348],\n",
" ],\n",
" [\n",
" [3411, 3412, 3413, 3414, 3415, 3416, 3417, 3418],\n",
" [3421, 3422, 3423, 3424, 3425, 3426, 3427, 3428],\n",
" [4431, 4432, 4433, 4434, 4435, 4436, 4437, 4438],\n",
" [4441, 4442, 4443, 4444, 4445, 4446, 4447, 4448],\n",
" ],\n",
"\n",
" ]])"
],
"metadata": {
"id": "Goi7juWUsmZJ"
},
"execution_count": 130,
"outputs": []
},
{
"cell_type": "code",
"source": [
"fake_image_tensor.shape"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "bySaHRvhcc9u",
"outputId": "93cdd1cd-46a6-4173-cf69-f93c55bce1f7"
},
"execution_count": 55,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"torch.Size([1, 4, 4, 8])"
]
},
"metadata": {},
"execution_count": 55
}
]
},
{
"cell_type": "markdown",
"source": [
"# Pixel Shuffling on Image"
],
"metadata": {
"id": "Ia_AGIwevQQM"
}
},
{
"cell_type": "code",
"source": [
"shuffled_image = pixel_shuffle(fake_image_tensor, 0.5) # 0.5 == unshuffle"
],
"metadata": {
"id": "TI1-ZhxDs0NZ"
},
"execution_count": 131,
"outputs": []
},
{
"cell_type": "code",
"source": [
"shuffled_image.shape"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "ycutWscYs6i7",
"outputId": "130b5833-fc5e-477e-ace1-d2fedb048117"
},
"execution_count": 132,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"torch.Size([1, 4, 32])"
]
},
"metadata": {},
"execution_count": 132
}
]
},
{
"cell_type": "code",
"source": [
"shuffled_image[0, :, :, 24]"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "8Zx1A7B1xim_",
"outputId": "822f1e16-7253-462b-8a22-3539bc0a1807"
},
"execution_count": 120,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"tensor([[1221, 3421],\n",
" [2241, 4441]])"
]
},
"metadata": {},
"execution_count": 120
}
]
},
{
"cell_type": "code",
"source": [
"shuffled_image[:, :, 8]"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "mYKnYgS95yK6",
"outputId": "5fa7f1d6-1e21-4377-cc7f-700950b08bbc"
},
"execution_count": 135,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"tensor([[1121, 2141, 3321, 4341]])"
]
},
"metadata": {},
"execution_count": 135
}
]
},
{
"cell_type": "code",
"source": [
"fake_image_tensor[0, :, :, 0].T"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "lfX62WZbxyVs",
"outputId": "845635e7-5b21-4cf7-ca5c-fe452f37603d"
},
"execution_count": 78,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"tensor([[1111, 1211, 3311, 3411],\n",
" [1121, 1221, 3321, 3421],\n",
" [2131, 2231, 4331, 4431],\n",
" [2141, 2241, 4341, 4441]])"
]
},
"metadata": {},
"execution_count": 78
}
]
},
{
"cell_type": "code",
"source": [
"fake_image_tensor[0, 2, :, :] #"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "9SG0Mvrt2Q0R",
"outputId": "d837e726-7e14-49dd-9e3b-fa650ea4177c"
},
"execution_count": 80,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"tensor([[3311, 3312, 3313, 3314, 3315, 3316, 3317, 3318],\n",
" [3321, 3322, 3323, 3324, 3325, 3326, 3327, 3328],\n",
" [4331, 4332, 4333, 4334, 4335, 4336, 4337, 4338],\n",
" [4341, 4342, 4343, 4344, 4345, 4346, 4347, 4348]])"
]
},
"metadata": {},
"execution_count": 80
}
]
},
{
"cell_type": "markdown",
"source": [
"1=\"dark red\"\n",
"2=\"dark blue\"\n",
"3=\"light red\"\n",
"4=\"light blue\"\n"
],
"metadata": {
"id": "Fs50ELwoAZW5"
}
},
{
"cell_type": "code",
"source": [
"shuffled_image.shape"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "dRpnug1RtHl6",
"outputId": "658f6416-4db8-43ac-b04d-f4c437974bb4"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"torch.Size([1, 8, 8, 16])"
]
},
"metadata": {},
"execution_count": 109
}
]
}
]
}
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