# Copyright 2021 MosaicML. All Rights Reserved.
"""`YAHP <https://docs.mosaicml.com/projects/yahp/en/stable/README.html>`_ interface for :class:`.ComposerDeepLabV3`."""
from dataclasses import dataclass
import yahp as hp
from composer.models.model_hparams import ModelHparams
__all__ = ["DeepLabV3Hparams"]
[docs]@dataclass
class DeepLabV3Hparams(ModelHparams):
"""`YAHP <https://docs.mosaicml.com/projects/yahp/en/stable/README.html>`_ interface for
:class:`.ComposerDeepLabV3`.
Args:
num_classes (int): Number of classes in the segmentation task.
backbone_arch (str, optional): The architecture to use for the backbone. Must be either [``'resnet50'``, ``'resnet101'``].
Default: ``'resnet101'``.
is_backbone_pretrained (bool, optional): If ``True``, use pretrained weights for the backbone. Default: ``True``.
backbone_url (str, optional): Url used to download model weights. If empty, the PyTorch url will be used.
Default: ``''``.
use_plus (bool, optional): If ``True``, use DeepLabv3+ head instead of DeepLabv3. Default: ``True``.
sync_bn (bool, optional): If ``True``, replace all BatchNorm layers with SyncBatchNorm layers. Default: ``True``.
initializers (List[Initializer], optional): Initializers for the model. ``[]`` for no initialization. Default: ``[]``.
"""
backbone_arch: str = hp.optional("The backbone architecture to use. Must be either ['resnet50', resnet101'].",
default='resnet101')
is_backbone_pretrained: bool = hp.optional("If true, use pre-trained weights for backbone.", default=True)
backbone_url: str = hp.optional(
"Url to download model weights from. If blank (default), will download from PyTorch's url.", default='')
use_plus: bool = hp.optional("If true (default), use DeepLabv3+ head instead of DeepLabv3.", default=True)
sync_bn: bool = hp.optional("If true, use SyncBatchNorm to sync batch norm statistics across GPUs.", default=True)
def validate(self):
if self.num_classes is None:
raise ValueError("num_classes must be specified")
if self.backbone_arch not in ['resnet50', 'resnet101']:
raise ValueError(f"backbone_arch must be one of ['resnet50', 'resnet101']: not {self.backbone_arch}")
def initialize_object(self):
from composer.models.deeplabv3.deeplabv3 import ComposerDeepLabV3
if self.num_classes is None:
raise ValueError("num_classes must be specified")
return ComposerDeepLabV3(num_classes=self.num_classes,
backbone_arch=self.backbone_arch,
is_backbone_pretrained=self.is_backbone_pretrained,
backbone_url=self.backbone_url,
use_plus=self.use_plus,
sync_bn=self.sync_bn,
initializers=self.initializers)