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iLearn-Lab 131

• "lavis.models.blip2_models.crossmodal_context_transformer.CrossModalContextTransformerEncoderLayer",
• "lavis.models.blip2_models.Qformer.BertOutput",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.activation.ReLU",
• "lavis.models.eva_vit.Mlp",
• "lavis.models.eva_vit.VisionTransformer",
• "lavis.models.blip2_models.Qformer.BertIntermediate",
• "torch.LongStorage",
• "transformers.models.bert.configuration_bert.BertConfig",
• "lavis.models.blip2_models.Qformer.BertSelfAttention",
• "lavis.models.blip2_models.HINT.EncoderImage",
• "lavis.models.blip2_models.Qformer.BertLayer",
• "transformers.models.bert.tokenization_bert.BasicTokenizer",
• "transformers.generation.configuration_utils.GenerationConfig",
• "torch.nn.modules.batchnorm.BatchNorm1d",
• "torch.nn.modules.activation.Softmax",
• "torch.nn.modules.activation.MultiheadAttention",
• "torch.nn.modules.container.ModuleList",
• "torch._C._nn.gelu",
• "lavis.models.eva_vit.PatchEmbed",
• "torch.nn.modules.linear.Identity",
• "lavis.models.eva_vit.Attention",
• "torch.nn.modules.dropout.Dropout",
• "lavis.models.blip2_models.HINT.QueryTokenSampler",
• "torch.nn.modules.normalization.LayerNorm",
• "lavis.models.blip2_models.Qformer.BertSelfOutput",
• "torch.nn.modules.activation.Tanh",
• "lavis.models.blip2_models.compute_loss.ComputeFinalLoss",
• "transformers.tokenization_utils.Trie",
• "transformers.models.bert.tokenization_bert.BertTokenizer",
• "transformers.models.bert.tokenization_bert.WordpieceTokenizer",
• "lavis.models.blip2_models.HINT.DistillLoss",
• "lavis.models.blip2_models.Qformer.BertEmbeddings",
• "collections.OrderedDict",
• "__builtin__.set",
• "lavis.models.blip2_models.Qformer.BertAttention",
• "torch.nn.modules.conv.Conv2d",
• "lavis.models.blip2_models.HINT.VisualSA",
• "lavis.models.blip2_models.Qformer.BertLMHeadModel",
• "lavis.models.blip2_models.HINT.QCRModule",
• "lavis.models.blip2_models.blip2.disabled_train",
• "torch._utils._rebuild_parameter",
• "lavis.models.eva_vit.Block",
• "torch.nn.modules.activation.GELU",
• "lavis.models.blip2_models.crossmodal_context_transformer.PositionalEncoder",
• "torch.nn.modules.linear.NonDynamicallyQuantizableLinear",
• "lavis.models.blip2_models.compute_loss.infoNCELoss",
• "lavis.models.blip2_models.HINT.HINT",
• "torch.HalfStorage",
• "torch.nn.modules.linear.Linear",
• "transformers.activations.GELUActivation",
• "lavis.models.blip2_models.Qformer.BertOnlyMLMHead",
• "lavis.models.blip2_models.Qformer.BertEncoder",
• "torch.FloatStorage",
• "lavis.models.blip2_models.Qformer.BertPredictionHeadTransform",
• "lavis.models.blip2_models.Qformer.BertModel",
• "torch.nn.modules.container.Sequential",
• "lavis.models.blip2_models.Qformer.BertLMPredictionHead",
• "torch.nn.modules.sparse.Embedding",
• "lavis.models.blip2_models.blip2.LayerNorm"

How to fix it?

• "lavis.models.blip2_models.crossmodal_context_transformer.CrossModalContextTransformerEncoderLayer",
• "lavis.models.blip2_models.Qformer.BertOutput",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.activation.ReLU",
• "lavis.models.eva_vit.Mlp",
• "lavis.models.eva_vit.VisionTransformer",
• "lavis.models.blip2_models.Qformer.BertIntermediate",
• "torch.LongStorage",
• "transformers.models.bert.configuration_bert.BertConfig",
• "lavis.models.blip2_models.Qformer.BertSelfAttention",
• "lavis.models.blip2_models.HINT.EncoderImage",
• "lavis.models.blip2_models.Qformer.BertLayer",
• "transformers.models.bert.tokenization_bert.BasicTokenizer",
• "transformers.generation.configuration_utils.GenerationConfig",
• "torch.nn.modules.batchnorm.BatchNorm1d",
• "torch.nn.modules.activation.Softmax",
• "torch.nn.modules.activation.MultiheadAttention",
• "torch.nn.modules.container.ModuleList",
• "torch._C._nn.gelu",
• "lavis.models.eva_vit.PatchEmbed",
• "torch.nn.modules.linear.Identity",
• "lavis.models.eva_vit.Attention",
• "torch.nn.modules.dropout.Dropout",
• "lavis.models.blip2_models.HINT.QueryTokenSampler",
• "torch.nn.modules.normalization.LayerNorm",
• "lavis.models.blip2_models.Qformer.BertSelfOutput",
• "torch.nn.modules.activation.Tanh",
• "lavis.models.blip2_models.compute_loss.ComputeFinalLoss",
• "transformers.tokenization_utils.Trie",
• "transformers.models.bert.tokenization_bert.BertTokenizer",
• "transformers.models.bert.tokenization_bert.WordpieceTokenizer",
• "lavis.models.blip2_models.HINT.DistillLoss",
• "lavis.models.blip2_models.Qformer.BertEmbeddings",
• "collections.OrderedDict",
• "__builtin__.set",
• "lavis.models.blip2_models.Qformer.BertAttention",
• "torch.nn.modules.conv.Conv2d",
• "lavis.models.blip2_models.HINT.VisualSA",
• "lavis.models.blip2_models.Qformer.BertLMHeadModel",
• "lavis.models.blip2_models.HINT.QCRModule",
• "lavis.models.blip2_models.blip2.disabled_train",
• "torch._utils._rebuild_parameter",
• "lavis.models.eva_vit.Block",
• "torch.nn.modules.activation.GELU",
• "lavis.models.blip2_models.crossmodal_context_transformer.PositionalEncoder",
• "torch.nn.modules.linear.NonDynamicallyQuantizableLinear",
• "lavis.models.blip2_models.compute_loss.infoNCELoss",
• "lavis.models.blip2_models.HINT.HINT",
• "torch.HalfStorage",
• "torch.nn.modules.linear.Linear",
• "transformers.activations.GELUActivation",
• "lavis.models.blip2_models.Qformer.BertOnlyMLMHead",
• "lavis.models.blip2_models.Qformer.BertEncoder",
• "torch.FloatStorage",
• "lavis.models.blip2_models.Qformer.BertPredictionHeadTransform",
• "lavis.models.blip2_models.Qformer.BertModel",
• "torch.nn.modules.container.Sequential",
• "lavis.models.blip2_models.Qformer.BertLMPredictionHead",
• "torch.nn.modules.sparse.Embedding",
• "lavis.models.blip2_models.blip2.LayerNorm"

How to fix it?