LearningMae

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vnm_zeroshot_eval

like 0

• "efficientnet_pytorch.model.MBConvBlock",
• "torch.nn.modules.activation.MultiheadAttention",
• "torch.nn.modules.dropout.Dropout",
• "vint_train.models.vint.self_attention.MultiLayerDecoder",
• "torch._utils._rebuild_parameter",
• "__builtin__.set",
• "torch.FloatStorage",
• "vint_train.models.vint.vint.ViNT",
• "torch.optim.adamw.AdamW",
• "torch.nn.modules.padding.ZeroPad2d",
• "torch.nn.modules.transformer.TransformerEncoderLayer",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "torch._C._nn.gelu",
• "torch.nn.modules.transformer.TransformerEncoder",
• "collections.OrderedDict",
• "torch.nn.modules.pooling.AdaptiveAvgPool2d",
• "numpy.dtype",
• "torch.nn.modules.normalization.LayerNorm",
• "torch.LongStorage",
• "efficientnet_pytorch.utils.Conv2dStaticSamePadding",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.container.ModuleList",
• "efficientnet_pytorch.utils.BlockArgs",
• "_codecs.encode",
• "__builtin__.dict",
• "efficientnet_pytorch.utils.GlobalParams",
• "collections.defaultdict",
• "vint_train.models.vint.self_attention.PositionalEncoding",
• "torch.nn.modules.linear.Linear",
• "efficientnet_pytorch.model.EfficientNet",
• "efficientnet_pytorch.utils.MemoryEfficientSwish",
• "torch.nn.modules.linear.Identity",
• "torch.nn.modules.container.Sequential",
• "torch.optim.lr_scheduler.CosineAnnealingLR",
• "torch.nn.modules.linear.NonDynamicallyQuantizableLinear",
• "warmup_scheduler.scheduler.GradualWarmupScheduler",
• "numpy.core.multiarray.scalar"

How to fix it?