Birch-san

from dataclasses import dataclass
from einops import rearrange
import re
import torch
from torch import BoolTensor, FloatTensor, IntTensor, LongTensor, inference_mode
from torch.nn.functional import pad
from itertools import islice
from typing import Generator, Iterable, Iterator, Optional, Protocol, TypeVar
from typing_extensions import override
from diffusers.models.unets.unet_2d_condition import UNet2DConditionModel, UNet2DConditionOutput

Birch-san

from __future__ import annotations
from argparse import ArgumentParser, Namespace
from dataclasses import dataclass
from functools import partial
from typing import Any, Callable, Optional
import torch
from torch import Tensor, no_grad, enable_grad
import torch.autograd.forward_ad as fwAD
from torch.nn.attention import SDPBackend, sdpa_kernel
from torch.nn.functional import scaled_dot_product_attention

Birch-san

from __future__ import annotations
from argparse import ArgumentParser, Namespace
from dataclasses import dataclass
from functools import partial
from typing import Callable, Generic, TypeVar
import torch
from torch import enable_grad, no_grad
import torch.autograd.forward_ad as fwAD
from torch.func import linearize
from torch.nn.attention import SDPBackend, sdpa_kernel

Birch-san

from __future__ import annotations
from argparse import ArgumentParser, Namespace
from dataclasses import dataclass
from functools import partial
from typing import Callable
import torch
from torch import enable_grad, no_grad
import torch.autograd.forward_ad as fwAD
from torch.nn.attention import SDPBackend, sdpa_kernel
from torch.nn.functional import scaled_dot_product_attention

Birch-san

#!/usr/bin/env bash
set -eo pipefail

# https://stackoverflow.com/a/12194427/5257399
create() { # fd base [qualifier [suffix [max]]]
  local fd="$1" base="$2" qualifier="${3-}" suffix="${4-.png}" max="${5-}"
  local n=0 file
  local - # ash-style local scoping of options in 4.4+
  set -o noclobber
  REPLY=

Birch-san

#!/usr/bin/env bash
set -eo pipefail

# https://stackoverflow.com/a/12194427/5257399
create() { # fd base [qualifier [suffix [max]]]
  local fd="$1" base="$2" qualifier="${3-}" suffix="${4-.png}" max="${5-}"
  local n=0 file
  local - # ash-style local scoping of options in 4.4+
  set -o noclobber
  REPLY=

Birch-san

from abc import ABC, abstractmethod
from typing import NamedTuple, Optional
from typing_extensions import override
import torch
from torch import Tensor, no_grad, enable_grad
import torch.autograd.forward_ad as fwAD
from torch.autograd.function import FunctionCtx
from torch.nn import Linear, Module
from torch.nn.attention import SDPBackend, sdpa_kernel
from torch.nn.functional import scaled_dot_product_attention

Birch-san

import torch
from torch import FloatTensor

def mm(a: FloatTensor, b: FloatTensor) -> FloatTensor:
    assert a.ndim == 2
    assert b.ndim == 2
    assert a.size(-1) == b.size(-2)
    assert a.size(-2) == b.size(-1)
    # batched dot product
    def bdp(a_row: FloatTensor, b: FloatTensor) -> FloatTensor:

Birch-san

from typing import Optional
import torch
from torch import FloatTensor, BoolTensor, Tensor, inference_mode
from torch.func import functional_call, stack_module_state
from torch.nn import Module, Linear
from torch.nn.functional import scaled_dot_product_attention
from einops import rearrange

class Attention(Module):
    def __init__(

Birch-san

javascript: (async function copyTags() {
  const replacements = {
    v: "peace sign",
    "double v": "double peace",
    "|_|": "bar eyes",
    "\\||/": "opem \\m/",
    ":|": "neutral face",
    ";|": "neutral face",
    "eyepatch bikini": "square bikini",
    "tachi-e": "character image",