danesherbs

CLAUDE.md

Workflow

• Use TDD:
  1. Red: Write a failing test before writing any implementation code. You should confirm that the test fails.
  2. Green: Write the minimum amount of code to make the failing test pass. You should confirm that the test passes.
  3. Refactor: Optionally, refactor the code to fix the structure, clarity, efficiency, etc. You should confirm that the tests pass after your refactor.

Writing Tests

danesherbs

import csv
from datetime import datetime, timedelta

START_DATE = datetime.today()
WEEKS = 15
INITIAL_DISTANCE = 35
MAX_INCREASE_RATE = 0.10
PARK_RUN_DISTANCE = 8
INCREASE_RATE = 0.05

danesherbs

from flask import Flask, render_template, request, redirect
import jsonlines
import os

app = Flask(__name__)


@app.route("/")
def home():
    default_fname = "tmp/evallogs/230807123401PG6IQKIY_gpt-3.5-turbo-16k,gpt-3.5-turbo-16k_make-me-say.jsonl"

danesherbs

"""A teeny tiny compiler!"""

import re
from typing import List, Tuple
from dataclasses import dataclass

TOKEN_TYPES = [
    ("def", r"\bdef\b"),
    ("end", r"\bend\b"),
    ("identifier", r"\b[a-zA-Z]+\b"),

danesherbs

def sample(seq: Sequence, k: int, include: Union[None, set] = None, exclude: Union[None, set] = None) -> Sequence:
    """Samples `k` items from `seq` without replacement, optionally including or excluding items."""

    # pre-condition
    assert k >= 0, "Number of items to sample must be non-negative"
    assert k <= len(seq), f"Cannot sample {k} items without replacement from a sequence with {len(seq)} items"

    if include is None:
        include = set()
    

danesherbs

class DictDataset(torch.utils.data.Dataset):
    """Makes a dataset from a dictionary of tensors"""

    def __init__(self, inputs: Dict[str, Tensor]):
        assert len(inputs) > 0, "inputs must be non-empty"
        
        keys = list(inputs.keys())
        key = keys[0]
        self._length = inputs[key].shape[0]
        

danesherbs

# This hook is particularly useful when ablating layers

class ContextHook:
    def __init__(self, layer):
        self.layer = layer

    def __enter__(self):
        self.handle = self.layer.register_forward_hook(self.hook)
        return self

danesherbs

class StatefulHook:
    def __init__(self):
        self.module = None
        self.input = None
        self.output = None

    def __call__(self, module, input, output):
        self.module = module
        self.input = input
        self.output = output