Spaces:

---

Duplicated from  VikramSingh178/MedicalImagingApplication

epochs-demos

/

MedicalImagingApp

like 4

Runtime error

• "lightning.pytorch.trainer.connectors.data_connector._DataConnector",
• "lightning.pytorch.accelerators.cuda.CUDAAccelerator",
• "lightning.fabric.plugins.environments.lightning.LightningEnvironment",
• "lightning.pytorch.utilities.parsing.AttributeDict",
• "torchmetrics.utilities.data.dim_zero_sum",
• "torch.float32",
• "lightning.pytorch.trainer.connectors.checkpoint_connector._CheckpointConnector",
• "lightning.pytorch.trainer.connectors.logger_connector.result._Sync",
• "torch.utils._pytree.LeafSpec",
• "lightning.pytorch.loops.evaluation_loop._EvaluationLoop",
• "lightning.pytorch.trainer.connectors.callback_connector._CallbackConnector",
• "torch.nn.modules.conv.Conv2d",
• "lightning.pytorch.plugins.precision.precision_plugin.PrecisionPlugin",
• "lightning.pytorch.trainer.states.TrainerStatus",
• "timm.models.layers.norm_act.BatchNormAct2d",
• "torch.nn.modules.loss.CrossEntropyLoss",
• "lightning.pytorch.trainer.connectors.logger_connector.result._ResultCollection",
• "lightning.pytorch.trainer.connectors.data_connector._DataLoaderSource",
• "lightning.pytorch.callbacks.progress.tqdm_progress.TQDMProgressBar",
• "torchvision.transforms.transforms.Resize",
• "torch._C._VariableFunctionsClass",
• "__builtin__.set",
• "timm.models.layers.adaptive_avgmax_pool.SelectAdaptivePool2d",
• "torch.utils.data.sampler.SequentialSampler",
• "lightning.pytorch.profilers.base.PassThroughProfiler",
• "torchvision.datasets.folder.default_loader",
• "timm.models.efficientnet_blocks.DepthwiseSeparableConv",
• "lightning.pytorch.utilities.types.LRSchedulerConfig",
• "torchvision.transforms.transforms.ToTensor",
• "timm.models.efficientnet_blocks.SqueezeExcite",
• "lightning.pytorch.loops.progress._ProcessedTracker",
• "lightning.pytorch.loops.fit_loop._FitLoop",
• "lightning.pytorch.trainer.connectors.signal_connector._SignalConnector",
• "torch.utils.data.dataloader.DataLoader",
• "functools.partial",
• "torchvision.transforms.transforms.CenterCrop",
• "lightning.fabric.plugins.io.torch_io.TorchCheckpointIO",
• "lightning.pytorch.trainer.connectors.logger_connector.result._ResultMetric",
• "lightning_utilities.core.rank_zero.WarningCache",
• "__builtin__.dict",
• "torch.optim.adam.Adam",
• "torch.nn.modules.flatten.Flatten",
• "torchvision.datasets.folder.ImageFolder",
• "torchvision.datasets.vision.StandardTransform",
• "torch.nn.modules.linear.Identity",
• "torch.utils.data.sampler.RandomSampler",
• "lightning.pytorch.loggers.wandb.WandbLogger",
• "lightning.pytorch.trainer.connectors.logger_connector.logger_connector._LoggerConnector",
• "torchvision.transforms.transforms.Compose",
• "lightning.pytorch.loops.progress._StartedTracker",
• "torch._utils._rebuild_parameter",
• "lightning.pytorch.loops.prediction_loop._PredictionLoop",
• "lightning.pytorch.callbacks.model_summary.ModelSummary",
• "torch._utils._rebuild_tensor_v2",
• "lightning.pytorch.trainer.trainer.Trainer",
• "lightning.pytorch.loops.progress._ReadyCompletedTracker",
• "lightning.pytorch.loops.optimization.manual._ManualOptimization",
• "torch.distributed._shard.sharded_tensor.state_dict_hook",
• "lightning.pytorch.loops.progress._OptimizerProgress",
• "lightning.pytorch.trainer.states.TrainerState",
• "lightning.pytorch.callbacks.model_checkpoint.ModelCheckpoint",
• "lightning.pytorch.loops.progress._SchedulerProgress",
• "timm.models.efficientnet.EfficientNet",
• "lightning.pytorch.trainer.states.TrainerFn",
• "torch.nn.modules.activation.Sigmoid",
• "torch.FloatStorage",
• "lightning.pytorch.loops.progress._Progress",
• "torch.nn.modules.container.Sequential",
• "torch.optim.lr_scheduler.StepLR",
• "torch.distributed._shard.sharded_tensor.pre_load_state_dict_hook",
• "torchmetrics.metric.jit_distributed_available",
• "lightning.pytorch.loops.progress._OptimizationProgress",
• "lightning.pytorch.strategies.single_device.SingleDeviceStrategy",
• "__builtin__.long",
• "torchmetrics.classification.f_beta.MulticlassF1Score",
• "lightning.pytorch.trainer.connectors.logger_connector.result._Metadata",
• "torch.utils.data._utils.collate.default_collate",
• "__main__.FineTuneModel",
• "fsspec.spec.make_instance",
• "fsspec.implementations.local.LocalFileSystem",
• "lightning.pytorch.loops.training_epoch_loop._TrainingEpochLoop",
• "torch.nn.modules.module._WrappedHook",
• "collections.defaultdict",
• "lightning.pytorch.loops.optimization.automatic._AutomaticOptimization",
• "torch.LongStorage",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "torchmetrics.classification.accuracy.MulticlassAccuracy",
• "lightning.pytorch.utilities.combined_loader.CombinedLoader",
• "torch.nn.modules.activation.SiLU",
• "torchvision.transforms.functional.InterpolationMode",
• "torchmetrics.classification.precision_recall.MulticlassRecall",
• "collections.OrderedDict",
• "lightning.pytorch.loops.progress._BatchProgress",
• "__builtin__.getattr",
• "torchvision.transforms.transforms.Normalize",
• "torch.utils.data.sampler.BatchSampler",
• "lightning.pytorch.trainer.connectors.data_connector._DataHookSelector",
• "torch.device",
• "torch.nn.modules.linear.Linear",
• "timm.models.efficientnet_blocks.InvertedResidual",
• "lightning.pytorch.trainer.connectors.accelerator_connector._AcceleratorConnector"

How to fix it?