kastnerkyle

#!/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

kastnerkyle

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).

kastnerkyle

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)

kastnerkyle

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`_.

kastnerkyle

kastnerkyle

#!/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

kastnerkyle

#!/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

kastnerkyle

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Fast swimming fish robot could perform underwater surveillance
Ad Astra: Pirates and space monkeys can't save dull space psychodrama

kastnerkyle

Code

https://gist.github.com/victor-shepardson/5b3d3087dc2b4817b9bffdb8e87a57c4

Setup

I'm using Ubuntu 16.04 with a GTX 1060

install CUDA

kastnerkyle

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