# Copyright (c) Alibaba, Inc. and its affiliates.
from torch import nn
from easycv.utils.registry import build_from_cfg
from .registry import (ATTENTION, BACKBONES, FEEDFORWARD_NETWORK,
FUSION_LAYERS, HEADS, LOSSES, MIDDLE_ENCODERS, MODELS,
NECKS, POSITIONAL_ENCODING, TRANSFORMER,
TRANSFORMER_LAYER, TRANSFORMER_LAYER_SEQUENCE,
VOXEL_ENCODERS)
[docs]def build(cfg, registry, default_args=None):
if isinstance(cfg, list):
modules = [
build_from_cfg(cfg_, registry, default_args) for cfg_ in cfg
]
return nn.Sequential(*modules)
else:
return build_from_cfg(cfg, registry, default_args)
[docs]def build_backbone(cfg):
return build(cfg, BACKBONES)
[docs]def build_neck(cfg):
return build(cfg, NECKS)
[docs]def build_head(cfg):
return build(cfg, HEADS)
[docs]def build_loss(cfg):
return build(cfg, LOSSES)
[docs]def build_model(cfg):
return build(cfg, MODELS)
[docs]def build_voxel_encoder(cfg):
"""Build voxel encoder."""
return VOXEL_ENCODERS.build(cfg)
[docs]def build_middle_encoder(cfg):
"""Build middle level encoder."""
return MIDDLE_ENCODERS.build(cfg)
[docs]def build_fusion_layer(cfg):
"""Build fusion layer."""
return FUSION_LAYERS.build(cfg)
[docs]def build_positional_encoding(cfg, default_args=None):
"""Builder for Position Encoding."""
return build_from_cfg(cfg, POSITIONAL_ENCODING, default_args)
[docs]def build_attention(cfg, default_args=None):
"""Builder for attention."""
return build_from_cfg(cfg, ATTENTION, default_args)
[docs]def build_feedforward_network(cfg, default_args=None):
"""Builder for feed-forward network (FFN)."""
return build_from_cfg(cfg, FEEDFORWARD_NETWORK, default_args)