scturtle

import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import numpy as np
import gym

# Hyperparameters
num_inputs = 4
num_actions = 2

scturtle

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scturtle

import numpy as np

class ModelArgs:
    dim = 288
    n_layers = 6
    n_heads = 6
    norm_eps = 1e-6

def build_cos_sin_cache(head_dim, seq_len, base=10000):
    theta = 1. / (base ** (np.arange(0, head_dim, 2, dtype=np.float32) / head_dim))

scturtle

import numpy as np

N_inp = 64
N_out = 64
d = 128
Q = np.random.randn(N_out, d)
K = np.random.randn(N_inp, d)
V = np.random.randn(N_inp, d)
O = np.random.randn(N_out, d)

scturtle

import numpy as np
from threading import Barrier, Thread
from collections import namedtuple

dim3 = namedtuple("dim3", ["x", "y", "z"], defaults=(1, 1))

TILE = 16


def cdiv(a, b):

scturtle

// ==UserScript==
// @name        adventofcode daylight mode
// @namespace   Violentmonkey Scripts
// @match       https://adventofcode.com/*
// @grant       none
// @version     1.0
// @author      scturtle
// @description 2023/11/27 16:52:13
// ==/UserScript==

scturtle

#!/usr/bin/env python3
import re
from pathlib import Path
from typing import List

MARK = "// -----// IR Dump"
PAT  = re.compile(r'IR Dump \w+ (?:.*::)?(\w+)')

def main(infile: Path, outdir: Path):
    assert infile.exists(), f'{infile} not exists'

scturtle

import json
import time
import random
import struct
import urllib.request
from pathlib import Path

# https://www.amiiboapi.com/api/amiibo/
database = json.load(open("amiibos.json"))

scturtle

import torch
from torch import nn

# import torch_mlir
from torch_mlir.passmanager import PassManager
from torch_mlir.dialects.torch.importer.jit_ir import ClassAnnotator, ModuleBuilder


torch.manual_seed(42)

scturtle

import torch
from torch import nn
import numpy as np

# https://github.com/arasdar/DL/blob/master/uri-dl/uri-dl-hw-2/assignment2/cs231n/layers.py
# https://github.com/brandontrabucco/conv-python/blob/master/main.py

def get_output_shape(x, kernel, stride):
    (_, _, ih, iw), (kh, kw) = x.shape, kernel
    oh = (ih - kh) // stride + 1