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{
"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/quantizer.yaml\""
]
},
{
"cell_type": "code",
"execution_count": 4,
"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": 5,
"id": "f939aa37-7b1d-45cc-885c-323c4540bda1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'_target_': 'text_recognizer.networks.quantizer.quantizer.VectorQuantizer', 'input_dim': 192, 'codebook': {'_target_': 'text_recognizer.networks.quantizer.codebook.CosineSimilarityCodebook', 'dim': 16, 'codebook_size': 2048, 'kmeans_init': True, 'kmeans_iters': 10, 'decay': 0.8, 'eps': 1e-05, 'threshold_dead': 2}, 'commitment': 1.0}"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cfg"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "aaeab329-aeb0-4a1b-aa35-5a2aab81b1d0",
"metadata": {},
"outputs": [],
"source": [
"vq = instantiate(cfg)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "7a0c9f4f-3d95-4722-9212-915a4b9ed096",
"metadata": {},
"outputs": [],
"source": [
"import torch"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "284ec8aa-43a0-4e59-a86f-91bab6c97dca",
"metadata": {},
"outputs": [],
"source": [
"t = torch.randn(2, 192, 18, 20)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "d3f6dad0-33f9-4f80-b514-dd0f71c8b93a",
"metadata": {},
"outputs": [],
"source": [
"(tt, ii, l) = vq(t)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "80fd228a-d9a2-4334-ab26-c283d215a456",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([2, 192, 18, 20])"
]
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tt.shape"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "22d04553-fd12-4f6c-8a43-9105083b0b82",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"torch.Size([2, 192, 360])"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tt.flatten(start_dim=2).shape"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "b79649ce-3623-4dd2-9a38-bef7bc5c9ac1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
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" 241, 1473, 77, 281, 620, 360, 312, 437, 262, 416, 435, 796,\n",
" 474, 1250, 2, 1087, 170, 612, 283, 750, 369, 745, 304, 793]])"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ii"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "618b997c-e6a6-4487-b70c-9d260cb556d3",
"metadata": {},
"outputs": [],
"source": [
"from torchinfo import summary"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "25759b7b-8deb-4163-b75d-a1357c9fe88f",
"metadata": {},
"outputs": [],
"source": [
"summary(net, (2, 1, 224, 224), device=\"cpu\", depth=4)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6aa04f07-12d4-4e06-b921-d54367c50a9a",
"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": "3.9.7"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
|
