Source code for composer.models.vit_small_patch16.model
# Copyright 2022 MosaicML Composer authors
# SPDX-License-Identifier: Apache-2.0
"""Implements ViT-S/16 as a :class:`.ComposerClassifier`."""
from composer.models.tasks import ComposerClassifier
__all__ = ['vit_small_patch16']
[docs]def vit_small_patch16(num_classes: int = 1000,
image_size: int = 224,
channels: int = 3,
dropout: float = 0.0,
embedding_dropout: float = 0.0):
"""Helper function to create a :class:`.ComposerClassifier` using a ViT-S/16 model.
See `Training data-efficient image transformers & distillation through attention <https://arxiv.org/pdf/2012.12877.pdf>`_
(Touvron et al, 2021) for details on ViT-S/16.
Args:
num_classes (int, optional): number of classes for the model. Default: ``1000``.
image_size (int, optional): input image size. If you have rectangular images, make sure your image
size is the maximum of the width and height. Default: ``224``.
channels (int, optional): number of image channels. Default: ``3``.
dropout (float, optional): 0.0 - 1.0 dropout rate. Default: ``0``.
embedding_dropout (float, optional): 0.0 - 1.0 embedding dropout rate. Default: ``0``.
Returns:
ComposerModel: instance of :class:`.ComposerClassifier` with a ViT-S/16 model.
"""
from vit_pytorch import ViT
model = ViT(
image_size=image_size,
channels=channels,
num_classes=num_classes,
dim=384, # embed dim/width
patch_size=16,
depth=12, # layers
heads=6,
mlp_dim=1536,
dropout=dropout,
emb_dropout=embedding_dropout)
composer_model = ComposerClassifier(module=model)
return composer_model