devforfu

# Runs a toy image generation task on Dask.
# 
# Note that the code was shortened for better readability. 
# Please refer the following repository to see the full example: 
# https://github.com/devforfu/dask_benchmark

@cli
def main(task_params: TaskParams) -> None:
    jobs = [
        Job(

devforfu

#!/Users/ck/.conda/envs/codex/bin/python
"""
The script wrapping OpenAI client into a simple CLI. Was generated using Codex with minor manual tweaks.
"""
import sys
from argparse import ArgumentParser
from dataclasses import dataclass
from typing import Dict, List

import openai

devforfu

def main():
    params = create_default_parser(__file__).parse_args()

    super_seed(params.seed)

    loaders, meta = create_data_loaders(dataset_name=params.dataset,
                                        dataset_root=params.dataset_path,
                                        num_workers=params.num_workers,
                                        batch_size=params.batch_size,
                                        sample_transformer=transforms.Compose([

devforfu

class BasicCNNExperiment(BaseExperiment):

    def create_model(self) -> nn.Module:
        return nn.Sequential(
            nn.Conv2d(3, 16, 3),
            nn.ReLU(inplace=True),
            nn.Conv2d(16, 32, 3),
            nn.ReLU(inplace=True),
            nn.AdaptiveMaxPool2d(1),
            nn.Flatten(1, -1),

devforfu

def basic_parser(script_filename: str = None) -> ArgumentParser:
    experiment_name = (
        Path(script_filename).stem
        if script_filename is not None
        else None
    )
    datasets = available_datasets()
    p = ArgumentParser()
    p.add_argument('--dataset_path', required=True)
    p.add_argument('--dataset', choices=datasets, default=datasets[0])

devforfu

def create_data_loaders(
    dataset_root: str,
    dataset_name: str,
    sample_transformer: Callable = None,
    target_transformer: Callable = None,
    num_workers: int = cpu_count(),
    batch_size: int = 32,
    download: bool = True,
    pin_memory: bool = False,
) -> Tuple[OrderedDict, Dict]:

devforfu

import numpy as np


class MathErrors:
    ZeroDivision = 'division failed: argument {argument} is zero.'
    NaN = 'multiplication failed: argument {argument} is not a number.'
    OutOfRange = 'value {argument} should be in range [{a}, {b}), but {value} received'
    

def divide(a: float, b: float) -> float:

devforfu

import logging
import traceback
from typing import Callable


def report_failure_traceback(logger: logging.Logger, exc: Exception) -> None:
    logger.critical('*** Unexpected error ***')
    logger.critical('')
    lines = traceback.format_tb(exc.__traceback__)
    lines = ''.join(lines).split('\n')

devforfu

(0008, 0018) SOP Instance UID                    UI: ID_3d2ea4e22
(0008, 0060) Modality                            CS: 'CT'
(0010, 0020) Patient ID                          LO: 'ID_e758d530'
(0020, 000d) Study Instance UID                  UI: ID_ebb91b8154
(0020, 000e) Series Instance UID                 UI: ID_57e1457f93
(0020, 0010) Study ID                            SH: ''
(0020, 0032) Image Position (Patient)            DS: ['-125', '26', '272.300049']
(0020, 0037) Image Orientation (Patient)         DS: ['1', '0', '0', '0', '1', '0']
(0028, 0002) Samples per Pixel                   US: 1
(0028, 0004) Photometric Interpretation          CS: 'MONOCHROME2'

devforfu

import os
import re
from pdb import set_trace
from multiprocessing import cpu_count
from pprint import pprint as pp

from imageio import imread
import numpy as np
import pandas as pd
import PIL.Image