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[tool.poetry]
name = "til-23-cv"
version = "0.1.0"
description = ""
authors = ["Author <author@example.com>"]
readme = "README.md"
packages = [{include = "til_23_cv"}]

[tool.poetry.dependencies]
python = "^3.9"

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"""Utilities to hash `torch.Tensor` and `nn.Module.state_dict()`."""

import numpy as np
import torch
import torch.nn as nn
from xxhash import xxh3_64_hexdigest as hexdigest

__all__ = ["hash_tensor", "hash_model"]

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"""Slot Attention implementation in PyTorch based on official TensorFlow implementation.

Some modifications were made, namely:

- Can pass forward previous slots to the next time step.
- Dynamic number of slots between calls.
- Uses `F.scaled_dot_product_attention` for more performance.
"""

from typing import Tuple

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/**
 * @file Generates a colorful animated SVG of equilateral triangles on an isogrid. Pure JS version.
 * @author John-Henry Lim <hyphen@interpause.dev>
 */

/** Very simple RNG used for randomizing the animated triangles. */
const detRNG = (s) => () => ((2 ** 31 - 1) & (s = Math.imul(48271, s))) / 2 ** 31
/** The seeded RNG function. */
let rand = () => 0.5

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/**
 * @file Suffering with typescript and breaking the tslinter a few times.
 * @author John-Henry Lim <hyphen@interpause.dev>
 */
/** K2 are the keys for the inner config. */
export type InnerConfig<K2 extends keyof any,V extends keyof any> = Partial<Record<K2,V>>|V;
/** K1 are the keys for the outer config, K2 are the keys for the inner config. */
export type LayeredConfig<K1 extends keyof any,K2 extends keyof any,V extends keyof any> = Partial<Record<K1,InnerConfig<K2,V>>>;
/** K1 and K2 are reversed on purpose. This is to invert the config structure. */
export type DefaultLayeredConfig<K1 extends keyof any,K2 extends keyof any,V> = Readonly<Record<K2,Record<K1,V>>>;