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Ryu1845 / chunked_audio_inference.py

Created August 16, 2024 08:04

	from typing import Callable

	import numpy as np
	from tqdm import tqdm

	def wsola_chunked_processing(audio: np.ndarray, sr: int, chunk_size: int, hop_size: int, mod_func: Callable[[np.ndarray], np.ndarray]):
	# Check if chunk_size is larger than the audio length
	if chunk_size >= len(audio):
	# Process the entire audio in one go
	output = mod_func(audio).squeeze()

lucidrains / tree_attn_decode.py

Created August 12, 2024 17:48

Tree Attention Decoding

	import torch
	from torch import einsum
	import torch.distributed as dist

	def tree_attn_decode(q, k, v):
	"""
	Algorithm 3 proposed in Tree Attention
	https://arxiv.org/abs/2408.04093
	"""

jxbz / zeroth-matrix-powers.py

Created August 8, 2024 17:11

	""" Computing zeroth matrix powers via Lakic 1998.
	paper: "On the Computation of the Matrix k-th Root"

	Suppose we have a matrix G = USV^T and we want to compute
	G^0 defined via G^0 = UV^T. We might want to do this to run
	"stochastic spectral descent" of Carlson et al 2015. The
	naive way to do this is via the SVD. But we can also just do
	(GG^T)^(-1/2) G or alternatively G (G^TG)^(-1/2) and apply
	the iterative method from Lakic 1998.

cccntu / document_packing_chat_tuning_mask.py

Created August 8, 2024 15:15

	"""Generates a document causal attention mask based on a document ID tensor"""

	from typing import List, Union

	import torch
	from torch import Tensor
	from torch.nn.attention.flex_attention import _mask_mod_signature, or_masks
	from attn_gym.masks import causal_mask

secemp9 / reset_gpu.sh

Created June 29, 2024 10:30

Resetting gpu

	#!/bin/bash

	unbind_gpu() {
	echo "Unbinding NVIDIA driver..."
	GPU_PCI=$(lspci \| grep -i nvidia \| cut -d ' ' -f 1)
	for gpu in $GPU_PCI; do
	echo -n "0000:$gpu" > /sys/bus/pci/drivers/nvidia/unbind
	done
	}

dmarx / 3d-umap-interactive-dataviz.py

Last active June 12, 2024 16:41

a la https://x.com/DigThatData/status/1800562625442623741

	import numpy as np
	from openai import OpenAI
	import plotly
	import plotly.graph_objs as go
	import umap


	url = "http://localhost:80"

	client = OpenAI(

crowsonkb / mos.py

Last active April 11, 2024 21:23

Mixture of Softmaxes

	"""Mixture of Softmaxes"""

	import torch
	from torch.nn import functional as F


	class MixtureOfSoftmaxes(torch.autograd.Function):
	@staticmethod
	def forward(ctx, x, p):
	with torch.cuda.amp.autocast(enabled=False):

aredden / cuda_python_cudart_types.py

Created March 12, 2024 22:07

NVIDIA cuda-python's cudart typings for their untyped cpp bound library.

catid / gist:7705835601ea71e4588652135a3a587e

Last active May 3, 2024 22:22

DoRA the explora

	import torch
	import torch.nn as nn
	import torch.nn.init as init
	import torch.nn.functional as F

	# This layer is dropped into your pre-trained PyTorch model where nn.Linear is used
	class DoRALayer(nn.Module):
	def __init__(self, d_in, d_out, rank=4):
	super().__init__()

euclaise / scan.py

Created February 9, 2024 00:08

Prefix-sum scan in PyTorch

	import torch
	from torch.nn import functional as F
	import math
	from typing import Callable

	def split(xs):
	xs = [x.view(x.shape[0], x.shape[-1]//2, 2) for x in xs]
	return [x[: , :, 0] for x in xs], [x[:, :, 1] for x in xs]

	def merge1(l, r):