AST
Implementation of AST from the paper: "AST: Audio Spectrogram Transformer' in PyTorch and Zeta. In this implementation we basically take an 2d input tensor representing audio -> then patchify it -> linear proj -> then position embeddings -> then attention and feedforward in a loop for layers. Please Join Agora and tag me if this could be improved in any capacity.
Install
pip3 install ast-torch
Usage
import torch
from ast_torch.model import ASTransformer
# Create dummy data
x = torch.randn(2, 16)
# Initialize model
model = ASTransformer(
dim=4, seqlen=16, dim_head=4, heads=4, depth=2, patch_size=4
)
# Run model and print output shape
print(model(x).shape)
Citation
@misc{gong2021ast,
title={AST: Audio Spectrogram Transformer},
author={Yuan Gong and Yu-An Chung and James Glass},
year={2021},
eprint={2104.01778},
archivePrefix={arXiv},
primaryClass={cs.SD}
}
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for ast-torch 0.0.5
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