tnguyen21

# /// script
# dependencies = [
#   "torch",
#   "numpy",
# ]
# ///

import torch
import torch.nn as nn
import numpy as np

tnguyen21

# /// script
# dependencies = [
#   "torch",
#   "numpy",
# ]
# ///

import torch
import torch.nn as nn
import numpy as np

tnguyen21

# /// script
# dependencies = [
#   "torch",
#   "numpy",
# ]
# ///

import torch
import torch.nn as nn
import numpy as np

tnguyen21

#!/usr/bin/env -S uv run python
# /// script
# requires-python = ">=3.11"
# dependencies = [
#     "requests",
#     "rich",
# ]
# ///

"""

tnguyen21

import os
import modal

image = (
    modal.Image.debian_slim()
    .apt_install("git")
    .run_commands(
        "pip install --upgrade pip",
        "pip install --pre torch --index-url https://download.pytorch.org/whl/nightly/cu126 --upgrade",
        "git clone --depth 1 https://github.com/KellerJordan/modded-nanogpt /opt/modded-nanogpt",

tnguyen21

#include <ctype.h>
#include <stdbool.h>
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>

typedef struct {
  const char* input;
  size_t index;

tnguyen21

import torch
from torch.utils.data import Dataset, DataLoader
import numpy as np
from typing import List, Dict, Tuple, Optional, Union
import random
from datetime import datetime, timedelta


class PinnerFormerDataset(Dataset):
    """

tnguyen21

import math

p = 0.9 # success rate
np = 1 - p
new_cards = 40
ease = 2.5
max_days = 365

queue = [{"base_days": 5, "factor": 1}]
total = 0

tnguyen21

a = "global"
try:
    def showA():
        print(a)

    showA() # prints "global"
    a = "block"
    showA() # prints "block"
except:
    ...

tnguyen21

"""
A python program to retreive recrods from ArXiv.org in given
categories and specific date range.

based off of https://github.com/Mahdisadjadi/arxivscraper
"""
from __future__ import print_function
import xml.etree.ElementTree as ET
import datetime
import time