https://gist.github.com/victor-shepardson/5b3d3087dc2b4817b9bffdb8e87a57c4
I'm using Ubuntu 16.04 with a GTX 1060
| #!/usr/bin/env python | |
| import math | |
| import matplotlib.pyplot as plt | |
| import torch | |
| import torch.nn as nn | |
| from sklearn.datasets import make_moons | |
| from torch import Tensor | |
| from tqdm import tqdm |
| import gzip | |
| def gzip_search(query: str, candidate_chunks: list[str], top_k: int=1): | |
| """ | |
| 文字列ベースで類似したテキストチャンクを推定するアルゴリズム. | |
| `query`, `chunk`, および`query + " " + chunk`をそれぞれgzipで圧縮し、編集距離のようなものをベースに評価する. | |
| Parameters: | |
| query (str): 検索クエリとして使用する文字列. | |
| top_k (int, optional): 返される類似チャンクの上位k個を指定する (default: 1). |
| import torch | |
| import k_diffusion as K | |
| from PIL import Image | |
| from torch import autocast | |
| from einops import rearrange, repeat | |
| def pil_img_to_latent(model, img, batch_size=1, device='cuda', half=True): | |
| init_image = pil_img_to_torch(img, half=half).to(device) | |
| init_image = repeat(init_image, '1 ... -> b ...', b=batch_size) |
| import math | |
| import torch | |
| from torch import optim | |
| class AdamWFinetune(optim.Optimizer): | |
| r"""Implements AdamW algorithm with optional weight decay toward the starting value, to | |
| prevent overfitting to the new dataset during fine-tuning. | |
| The original Adam algorithm was proposed in `Adam: A Method for Stochastic Optimization`_. |
| #!/usr/bin/env python3 | |
| """ | |
| To use: | |
| 1. install/set-up the google cloud api and dependencies listed on https://github.com/GoogleCloudPlatform/python-docs-samples/tree/master/texttospeech/cloud-client | |
| 2. install pandoc and pypandoc, also tqdm | |
| 3. create and download a service_account.json ("Service account key") from https://console.cloud.google.com/apis/credentials | |
| 4. run GOOGLE_APPLICATION_CREDENTIALS=service_account.json python make_audiobook.py book_name.epub | |
| """ | |
| import re | |
| import sys |
| #!/usr/bin/env python3 | |
| """ | |
| To use: | |
| 1. install/set-up the google cloud api and dependencies listed on https://github.com/GoogleCloudPlatform/python-docs-samples/tree/master/texttospeech/cloud-client | |
| 2. install pandoc and pypandoc, also tqdm | |
| 3. create and download a service_account.json ("Service account key") from https://console.cloud.google.com/apis/credentials | |
| 4. run GOOGLE_APPLICATION_CREDENTIALS=service_account.json python make_audiobook.py book_name.epub | |
| """ | |
| import re | |
| import sys |
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https://gist.github.com/victor-shepardson/5b3d3087dc2b4817b9bffdb8e87a57c4
I'm using Ubuntu 16.04 with a GTX 1060
| import jax | |
| import jax.numpy as np | |
| from jax import grad, jit | |
| from jax.scipy.special import logsumexp | |
| def dadashi_fig2d(): | |
| """ Figure 2 d) of | |
| ''The Value Function Polytope in Reinforcement Learning'' | |
| by Dadashi et al. (2019) https://arxiv.org/abs/1901.11524 |