Skip to main content

Causal depthwise conv1d in CUDA, with a PyTorch interface

Project description

Causal depthwise conv1d in CUDA with a PyTorch interface

Features:

  • Support fp32, fp16, bf16.
  • Kernel size 2, 3, 4.

How to use

from causal_conv1d import causal_conv1d_fn
def causal_conv1d_fn(x, weight, bias=None, activation=None):
    """
    x: (batch, dim, seqlen)
    weight: (dim, width)
    bias: (dim,)
    activation: either None or "silu" or "swish"

    out: (batch, dim, seqlen)
    """

Equivalent to:

import torch.nn.functional as F

F.conv1d(x, weight.unsqueeze(1), bias, padding=width - 1, groups=dim)[..., :seqlen]

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

causal_conv1d-1.2.0.post2.tar.gz (7.1 kB view details)

Uploaded Source

File details

Details for the file causal_conv1d-1.2.0.post2.tar.gz.

File metadata

  • Download URL: causal_conv1d-1.2.0.post2.tar.gz
  • Upload date:
  • Size: 7.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.13

File hashes

Hashes for causal_conv1d-1.2.0.post2.tar.gz
Algorithm Hash digest
SHA256 3e35b96718b81a0b34c3717b5df06fd3ba44794079e40b34b719b152806acc1b
MD5 5960c17839c964e01542b582e47dfee4
BLAKE2b-256 7b02d2ff7b71358dadde5278b5a8c70b569124c64464a1f412469366fc639ac9

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page