RomanBeliy

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Brain-IT

like 0

• "_codecs.encode",
• "torch._utils._rebuild_tensor_v2",
• "models.layers_transformer.XformerAttention",
• "models.layers_transformer.Mlp",
• "numpy.dtype",
• "models.layers_transformer.XformerCrossAttention",
• "numpy.core.multiarray.scalar",
• "torch_geometric.nn.dense.linear.Linear",
• "torch.FloatStorage",
• "torch_geometric.inspector.Parameter",
• "models.decoder_models.Decoder",
• "__builtin__.type",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.dropout.Dropout",
• "torch.nn.modules.linear.Linear",
• "torch.nn.modules.linear.Identity",
• "torch.nn.modules.activation.GELU",
• "models.decoder_models.dec_param",
• "torch.nn.modules.container.ModuleList",
• "models.layers_transformer.BlockCross_xformer",
• "_operator.getitem",
• "torch_geometric.inspector.Signature",
• "__builtin__.set",
• "typing.Union",
• "torch.Tensor",
• "typing.OrderedDict",
• "torch_geometric.nn.aggr.basic.SumAggregation",
• "collections.OrderedDict",
• "models.layers_transformer.Block_xformer",
• "__builtin__.long",
• "torch_geometric.inspector.Inspector",
• "torch_geometric.nn.conv.transformer_conv.TransformerConv",
• "torch.nn.modules.activation.ReLU",
• "inspect._empty",
• "torch.nn.modules.normalization.LayerNorm"

How to fix it?

• "torch.nn.modules.linear.Linear",
• "models.layers_transformer.XformerAttention",
• "models.decoder_models.Decoder",
• "models.decoder_models.dec_param",
• "numpy.dtype",
• "__builtin__.set",
• "collections.OrderedDict",
• "models.layers_transformer.Block_xformer",
• "torch.nn.modules.dropout.Dropout",
• "typing.OrderedDict",
• "torch.nn.modules.activation.ReLU",
• "models.layers_transformer.BlockCross_xformer",
• "inspect._empty",
• "torch_geometric.nn.aggr.basic.SumAggregation",
• "__builtin__.long",
• "torch.nn.modules.activation.GELU",
• "torch.Tensor",
• "torch.nn.modules.normalization.LayerNorm",
• "torch._utils._rebuild_parameter",
• "torch_geometric.inspector.Signature",
• "models.layers_transformer.XformerCrossAttention",
• "_codecs.encode",
• "torch._utils._rebuild_tensor_v2",
• "models.layers_transformer.Mlp",
• "numpy.core.multiarray.scalar",
• "torch.nn.modules.linear.Identity",
• "torch.nn.modules.container.ModuleList",
• "torch.FloatStorage",
• "__builtin__.type",
• "torch_geometric.inspector.Inspector",
• "torch_geometric.nn.conv.transformer_conv.TransformerConv",
• "_operator.getitem",
• "typing.Union",
• "torch_geometric.nn.dense.linear.Linear",
• "torch_geometric.inspector.Parameter"

How to fix it?

• "torch.nn.modules.linear.Linear",
• "numpy.dtype",
• "__builtin__.set",
• "collections.OrderedDict",
• "torch.nn.modules.dropout.Dropout",
• "dinov2.layers.layer_scale.LayerScale",
• "torch.nn.modules.activation.GELU",
• "models.encoder_models.encoder_param",
• "torch.nn.modules.normalization.LayerNorm",
• "dinov2.layers.mlp.Mlp",
• "dinov2.layers.attention.MemEffAttention",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.conv.Conv2d",
• "_codecs.encode",
• "torch._utils._rebuild_tensor_v2",
• "numpy.core.multiarray.scalar",
• "torch.nn.modules.linear.Identity",
• "torch.nn.modules.container.ModuleList",
• "torch.FloatStorage",
• "dinov2.models.vision_transformer.DinoVisionTransformer",
• "models.encoder_models.Encoder",
• "models.layers_encoder.MapAttention_dynamic_pos",
• "dinov2.layers.block.NestedTensorBlock",
• "models.layers_encoder.Mlp",
• "dinov2.layers.patch_embed.PatchEmbed"

How to fix it?