def register_datasets(backend):
"""Import and register datasets automatically."""
if backend == "pytorch":
from . import pytorch
elif backend == "tensorflow":
from . import tensorflow
elif backend == "mindspore":
import mindspore.dataset
from . import mindspore
ClassFactory.lazy_register("vega.datasets.common", {"imagenet": ["Imagenet"]})
from . import common
from . import transforms
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import loss functions."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register(
"vega.networks.pytorch.losses", {
"sum_loss": ["trainer.loss:SumLoss"],
"smooth_l1_loss": ["trainer.loss:SmoothL1Loss"],
"custom_cross_entropy_loss": ["trainer.loss:CustomCrossEntropyLoss"],
"cross_entropy_label_smooth": ["trainer.loss:CrossEntropyLabelSmooth"],
"mix_auxiliary_loss": ["trainer.loss:MixAuxiliaryLoss"],
})
"""Lazy import tensorflow networks."""
from .network import Sequential
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register(
"vega.networks.tensorflow",
{
"resnet_tf": ["ResNetTF", 'ResNetSlim'],
# backbones
"backbones.resnet_det": ["ResNetDet"],
# customs
"customs.edvr.edvr": ["EDVR"],
"customs.gcn_regressor": ["GCNRegressor"],
# detectors
"detectors.faster_rcnn_trainer_callback":
["FasterRCNNTrainerCallback"],
"detectors.faster_rcnn": ["FasterRCNN"],
"detectors.tf_optimizer": ["TFOptimizer"],
# losses
"losses.cross_entropy_loss": ["CrossEntropyLoss"],
"losses.mix_auxiliary_loss": ["MixAuxiliaryLoss"],
"losses.charbonnier": ["CharbonnierLoss"],
# necks
"necks.mask_rcnn_box": ["MaskRCNNBox"],
})
ClassFactory.lazy_register(
"vega.networks.tensorflow.utils", {
"anchor_utils.anchor_generator": ["AnchorGenerator"],
"hyperparams.initializer": ["Initializer"],
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import mindspore network."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register(
"vega.networks.mindspore", {
"dnet": ["DNet"],
"super_network":
["DartsNetwork", "CARSDartsNetwork", "GDASDartsNetwork"],
"backbones.load_official_model": ["OffcialModelLoader"],
"backbones.resnet_ms": ["ResNetMs"],
"losses.mix_auxiliary_loss": ["MixAuxiliaryLoss"],
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Import and register evaluator automatically."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register(
"vega.evaluator", {
"device_evaluator": ["DeviceEvaluator"],
"host_evaluator": ["HostEvaluator"],
"evaluator": ["Evaluator"],
})
from .search_algorithm import SearchAlgorithm
from .ea_conf import EAConfig
from .pareto_front_conf import ParetoFrontConfig
from .pareto_front import ParetoFront
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.core.search_algs", {
"ps_differential": ["DifferentialAlgorithm"],
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import detector."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.networks.pytorch.detectors", {
"auto_lane_detector": ["AutoLaneDetector"],
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Import and register modules automatically."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.modules", {
"module": ["network:Module"],
})
def register_modules():
"""Import and register modules automatically."""
from . import blocks
from . import cells
from . import connections
from . import operators
from . import preprocess
from . import loss
from . import getters
from . import necks
from . import backbones
from . import distillation
from .metrics import Metrics
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.metrics.pytorch", {
"lane_metric": ["trainer.metric:LaneMetric"],
"regression": ["trainer.metric:MSE", "trainer.metric:mse"],
"detection_metric": ["trainer.metric:CocoMetric", "trainer.metric:coco"],
"gan_metric": ["trainer.metric:GANMetric"],
"classifier_metric": ["trainer.metric:accuracy", "trainer.metric:Accuracy", "trainer.metric:SklearnMetrics"],
"auc_metrics": ["trainer.metric:AUC", "trainer.metric:auc"],
"segmentation_metric": ["trainer.metric:IoUMetric"],
"sr_metric": ["trainer.metric:PSNR", "trainer.metric:SSIM"],
"r2score": ["trainer.metric:r2score", "trainer.metric:R2Score"],
"nlp_metric": ["trainer.metric:accuracy_score", "trainer.metric:f1_score", "trainer.metric:NlpMetrics"],
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import hpo algorithms."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.algorithms.hpo", {
"asha_hpo": ["AshaHpo"],
"bohb_hpo": ["BohbHpo"],
"boss_hpo": ["BossHpo"],
"random_hpo": ["RandomSearch"],
"evolution_search": ["EvolutionAlgorithm"],
"pbt_hpo": ["PBTHpo"],
"pbt_trainer_callback": ["PbtTrainerCallback"],
"sha_base.hebo_adaptor": ["HeboAdaptor"],
})
ClassFactory.lazy_register(
"vega.datasets.transforms",
{
# common
"AutoAugment": ["AutoAugment"],
"AutoContrast": ["AutoContrast"],
"BboxTransform": ["BboxTransform"],
"Brightness": ["Brightness"],
"Color": ["Color"],
"Compose": ["Compose", "ComposeAll"],
"Compose_pair": ["Compose_pair"],
"Contrast": ["Contrast"],
"Cutout": ["Cutout"],
"Equalize": ["Equalize"],
"RandomCrop_pair": ["RandomCrop_pair"],
"RandomHorizontalFlip_pair": ["RandomHorizontalFlip_pair"],
"RandomMirrow_pair": ["RandomMirrow_pair"],
"RandomRotate90_pair": ["RandomRotate90_pair"],
"RandomVerticallFlip_pair": ["RandomVerticallFlip_pair"],
"RandomColor_pair": ["RandomColor_pair"],
"RandomRotate_pair": ["RandomRotate_pair"],
"Rescale_pair": ["Rescale_pair"],
"Normalize_pair": ["Normalize_pair"],
# GPU only
"ImageTransform": ["ImageTransform"],
"Invert": ["Invert"],
"MaskTransform": ["MaskTransform"],
"Posterize": ["Posterize"],
"Rotate": ["Rotate"],
"SegMapTransform": ["SegMapTransform"],
"Sharpness": ["Sharpness"],
"Shear_X": ["Shear_X"],
"Shear_Y": ["Shear_Y"],
"Solarize": ["Solarize"],
"Translate_X": ["Translate_X"],
"Translate_Y": ["Translate_Y"],
"RandomGaussianBlur_pair": ["RandomGaussianBlur_pair"],
"RandomHorizontalFlipWithBoxes": ["RandomHorizontalFlipWithBoxes"],
"Resize": ["Resize"],
"RandomCrop": ["RandomCrop"],
"RandomHorizontalFlip": ["RandomHorizontalFlip"],
"Normalize": ["Normalize"],
"ToTensor": ["ToTensor"],
})
from .metrics import Metrics
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.metrics.tensorflow", {
"segmentation_metric": ["trainer.metric:IoUMetric"],
"classifier_metric": ["trainer.metric:accuracy"],
"sr_metric": ["trainer.metric:PSNR", "trainer.metric:SSIM"],
"forecast": ["trainer.metric:MSE", "trainer.metric:RMSE"],
"r2score": ["trainer.metric:r2score", "trainer.metric:R2Score"],
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import pytorch backbones."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.networks.pytorch.backbones", {
"getter": ["BackboneGetter", "ResNetBackbone"],
"load_official_model": ["OffcialModelLoader"],
"resnet_variant_det": ["ResNetVariantDet"],
"resnext_variant_det": ["ResNeXtVariantDet"],
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import ops."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.networks.pytorch.ops", {
"fmdunit": ["network:FMDUnit", "network:LinearScheduler"],
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import pytorch blocks."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.networks.pytorch.blocks", {
"block": ["Block"],
"conv_ws": ["ConvWS2d"],
"stem": ['PreTwoStem'],
})
from .metrics import Metrics
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register(
"vega.metrics.mindspore", {
"segmentation_metric": ["trainer.metric:IoUMetric"],
"classifier_metric": ["trainer.metric:accuracy"],
"sr_metric": ["trainer.metric:PSNR", "trainer.metric:SSIM"],
})
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.datasets.pytorch", {
"coco_transforms": ["CocoCategoriesTransform", "PolysToMaskTransform"],
})
ClassFactory.lazy_register(
"vega.networks", {
"adelaide": ["AdelaideFastNAS"],
"bert": [
"BertClassification", "TinyBertForPreTraining",
"BertClassificationHeader"
],
"dnet": ["DNet", "DNetBackbone"],
"erdb_esr": ["ESRN"],
"faster_backbone": ["FasterBackbone"],
"faster_rcnn": ["FasterRCNN"],
"mobilenet": ["MobileNetV3Tiny", "MobileNetV2Tiny"],
"mobilenetv3": ["MobileNetV3Small", "MobileNetV3Large"],
"necks": ["FPN"],
"quant": ["Quantizer"],
"resnet_det": ["ResNetDet"],
"resnet_general": ["ResNetGeneral"],
"resnet": ["ResNet"],
"resnext_det": ["ResNeXtDet"],
"sgas_network": ["SGASNetwork"],
"simple_cnn": ["SimpleCnn"],
"spnet_backbone": ["SpResNetDet"],
"super_network":
["DartsNetwork", "CARSDartsNetwork", "GDASDartsNetwork"],
"text_cnn": ["TextCells", "TextCNN"],
"gcn": ["GCN"],
"vit": ["VisionTransformer"],
"mtm_sr": ["MtMSR"],
})
from .callback import Callback
from .callback_list import CallbackList
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register(
"vega.trainer.callbacks", {
"metrics_evaluator": ["trainer.callback:MetricsEvaluator"],
"progress_logger": ["trainer.callback:ProgressLogger"],
"performance_saver": ["trainer.callback:PerformanceSaver"],
"lr_scheduler": ["trainer.callback:LearningRateScheduler"],
"model_builder": ["trainer.callback:ModelBuilder"],
"model_statistics": ["trainer.callback:ModelStatistics"],
"model_checkpoint": ["trainer.callback:ModelCheckpoint"],
"report_callback": ["trainer.callback:ReportCallback"],
"runtime_callback": ["trainer.callback:RuntimeCallback"],
"detection_progress_logger":
["trainer.callback:DetectionProgressLogger"],
"detection_metrics_evaluator":
["trainer.callback:DetectionMetricsEvaluator"],
"visual_callback": ["trainer.callback:VisualCallBack"],
"model_tuner": ["trainer.callback:ModelTuner"],
"timm_trainer_callback": ["trainer.callback:TimmTrainerCallback"],
})
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import nas algorithms."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.algorithms.nas", {
"adelaide_ea": ["AdelaideCodec", "AdelaideMutate", "AdelaideRandom", "AdelaideEATrainerCallback"],
"auto_lane": ["AutoLaneNas", "AutoLaneNasCodec", "AutoLaneTrainerCallback"],
"backbone_nas": ["BackboneNasCodec", "BackboneNasSearchSpace", "BackboneNas"],
"cars": ["CARSAlgorithm", "CARSTrainerCallback", "CARSPolicyConfig"],
"darts_cnn": ["DartsCodec", "DartsFullTrainerCallback", "DartsNetworkTemplateConfig", "DartsTrainerCallback"],
"dnet_nas": ["DblockNasCodec", "DblockNas", "DnetNasCodec", "DnetNas"],
"esr_ea": ["ESRCodec", "ESRTrainerCallback", "ESRSearch"],
"fis": ["AutoGateGrdaS1TrainerCallback", "AutoGateGrdaS2TrainerCallback", "AutoGateS1TrainerCallback",
"AutoGateS2TrainerCallback", "AutoGroupTrainerCallback", "CtrTrainerCallback"],
"mfkd": ["MFKD1", "SimpleCnnMFKD"],
"modnas": ["ModNasAlgorithm", "ModNasTrainerCallback"],
"segmentation_ea": ["SegmentationCodec", "SegmentationEATrainerCallback", "SegmentationNas"],
"sgas": ["SGASTrainerCallback"],
"sm_nas": ["SmNasCodec", "SMNasM"],
"sp_nas": ["SpNasS", "SpNasP"],
"sr_ea": ["SRCodec", "SRMutate", "SRRandom"],
"mfasc": ["search_algorithm:MFASC"]
})
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import dataset."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register(
"vega.datasets.common",
{
"avazu": ["AvazuDataset"],
"cifar10": ["Cifar10"],
"cifar100": ["Cifar100"],
"div2k": ["DIV2K"],
"cls_ds": ["ClassificationDataset"],
"cityscapes": ["Cityscapes"],
"div2k_unpair": ["Div2kUnpair"],
"fmnist": ["FashionMnist"],
# "imagenet": ["Imagenet"],
"mnist": ["Mnist"],
"sr_datasets": ["Set5", "Set14", "BSDS100"],
"auto_lane_datasets": ["AutoLaneDataset"],
"coco": ["CocoDataset", "DetectionDataset"],
"glue": ["GlueDataset"],
"spatiotemporal": ["SpatiotemporalDataset"],
"reds": ["REDS"],
"nasbench": ["Nasbench"],
})
from .loss import Loss
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.modules.loss", {
"multiloss": ["trainer.loss:MultiLoss", "trainer.loss:SingleLoss"],
"focal_loss": ["trainer.loss:FocalLoss"],
"f1_loss": ["trainer.loss:F1Loss"],
"forecast_loss": ["trainer.loss:ForecastLoss"],
"mean_loss": ["trainer.loss:MeanLoss"],
"ProbOhemCrossEntropy2d": ["trainer.loss:ProbOhemCrossEntropy2d"],
"gan_loss": ["trainer.loss:GANLoss"],
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import data augmentation algorithms."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register(
"vega.algorithms.data_augmentation", {
"pba_hpo": ["PBAHpo"],
"pba_trainer_callback": ["PbaTrainerCallback"],
"cyclesr": ["CyclesrTrainerCallback"],
})
# -*- coding:utf-8 -*-
from .pipe_step import PipeStep
from .pipeline import Pipeline
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.core.pipeline", {
"search_pipe_step": ["SearchPipeStep"],
"train_pipe_step": ["TrainPipeStep"],
"benchmark_pipe_step": ["BenchmarkPipeStep"],
"multi_task_pipe_step": ["MultiTaskPipeStep"],
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import necks."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.networks.pytorch.necks", {
"ffm": ["network:FeatureFusionModule"],
"fpn": ["FPN"]
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import compression algorithms."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register(
"vega.algorithms.compression", {
"prune_ea":
["PruneCodec", "PruneEA", "PruneSearchSpace", "PruneTrainerCallback"],
"prune_ea_mobilenet":
["PruneMobilenetCodec", "PruneMobilenetTrainerCallback"],
"quant_ea": ["QuantCodec", "QuantEA", "QuantTrainerCallback"],
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import custom network."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register(
"vega.networks.pytorch.customs", {
"nago": ["network:NAGO"],
"deepfm": ["network:DeepFactorizationMachineModel"],
"autogate": ["network:AutoGateModel"],
"autogroup": ["network:AutoGroupModel"],
"bisenet": ["network:BiSeNet"],
"modnas": ["network:ModNasArchSpace"],
"mobilenetv2": ["network:MobileNetV2"],
"gcn_regressor": ["network:GCNRegressor"],
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Import and register trainer automatically."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register(
"vega.trainer", {
"trainer_torch": ["TrainerTorch"],
"trainer_tf": ["TrainerTf"],
"trainer_ms": ["TrainerMs"],
"trainer": ["Trainer"],
"script_runner": ["ScriptRunner"],
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import head network."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register(
"vega.networks.pytorch.heads", {
"auto_lane_head": ["network:AutoLaneHead"],
"auxiliary_head": ["network:AuxiliaryHead"],
})
# -*- coding:utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
"""Lazy import gan network."""
from vega.common.class_factory import ClassFactory
ClassFactory.lazy_register("vega.networks.pytorch.gan", {
"fully_super_network": ["network:Generator"],
})