Given Chinchilla coefficients, return compute-optimal $N$ $D$ for a $C$ (numeri

Medium

Pretraining Objectives and Scaling Laws2 / 4

Chapter 052 / 4

Pretraining Objectives and Scaling Laws

Given Chinchilla coefficients, return compute-optimal $N$ $D$ for a $C$ (numeri

Medium

Given Chinchilla coefficients, return compute-optimal $N$ $D$ for a $C$ (numerical optimization).

Target interface

chinchilla_loss(N, D)

Complete the starter code in the editor. Any correct approach is accepted.

Hints0 / 2

Reference solution

Your own code stays in the editor.

solution.pyPython

Local draft

import numpy as np
from scipy.optimize import minimize_scalar

def chinchilla_loss(N, D):
    raise NotImplementedError

def optimal_ND(C, A=A, B=B, alpha=ALPHA, beta=BETA):
    raise NotImplementedError

def optimal_ND_closed_form(C, A=A, B=B, alpha=ALPHA, beta=BETA):
    raise NotImplementedError

Local draft

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Chapter 052 / 4

Pretraining Objectives and Scaling Laws

Given Chinchilla coefficients, return compute-optimal $N$ $D$ for a $C$ (numeri

Medium

Given Chinchilla coefficients, return compute-optimal $N$ $D$ for a $C$ (numerical optimization).

Target interface

chinchilla_loss(N, D)

Complete the starter code in the editor. Any correct approach is accepted.

Hints0 / 2

Reference solution

Your own code stays in the editor.