Datasets:

---

mims-harvard

/

MedeaDB

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Artificial Intelligence for Medicine and Science @ Harvard 72

• "compass.encoder.layer.performer.FastAttention",
• "compass.encoder.layer.performer.gaussian_orthogonal_random_matrix",
• "compass.augmentor.aug.RandomMaskAugmentor",
• "compass.encoder.layer.performer.PerformerLayer",
• "pandas.core.indexes.base._new_Index",
• "compass.projector.projector.CellPathwayProjector",
• "torch._C._VariableFunctionsClass",
• "torch.nn.modules.container.ParameterDict",
• "compass.model.loss.CEWithNaNLabelsLoss",
• "compass.main.FineTuner",
• "__builtin__.dict",
• "compass.model.scaler.Datascaler",
• "torch.nn.modules.dropout.Dropout",
• "compass.projector.genesetscorer.GeneSetScorer",
• "compass.embedder.embedder._GeneExpressionEmbedding",
• "numpy.dtype",
• "torch.optim.adam.Adam",
• "torch.nn.modules.container.Sequential",
• "compass.projector.genesetscorer.GeneSetScoreLinear",
• "compass.embedder.embedder.GeneEmbedding",
• "compass.model.saver.SaveBestModel",
• "torch.nn.modules.activation.ReLU",
• "pandas.core.series.Series",
• "numpy.core.multiarray.scalar",
• "compass.projector.projector.DisentangledProjector",
• "torch.nn.modules.linear.Linear",
• "compass.embedder.embedder.AbundanceEmbedding",
• "torch.nn.modules.activation.GELU",
• "torch.nn.modules.sparse.Embedding",
• "__builtin__.set",
• "torch.nn.modules.normalization.LayerNorm",
• "compass.encoder.encoder.Encoder",
• "collections.defaultdict",
• "compass.augmentor.aug.FeatureJitterAugmentor",
• "functools.partial",
• "compass.encoder.layer.performer.PerformerAttention",
• "torch.nn.modules.activation.Softmax",
• "pandas.core.internals.managers.SingleBlockManager",
• "compass.augmentor.aug.MaskJitterAugmentor",
• "torch.FloatStorage",
• "torch._utils._rebuild_tensor_v2",
• "__builtin__.slice",
• "torch.nn.modules.batchnorm.BatchNorm1d",
• "compass.model.model.Compass",
• "compass.main.PreTrainer",
• "compass.projector.cellpathwayaggregator.CellPathwayAttentionAggregator",
• "torch._utils._rebuild_parameter",
• "__builtin__.getattr",
• "compass.projector.genesetaggregator.GeneSetAggregator",
• "torch.LongStorage",
• "numpy.core.multiarray._reconstruct",
• "sklearn.preprocessing._data.MinMaxScaler",
• "compass.projector.genesetaggregator.GeneSetAttentionAggregator",
• "pandas.core.indexes.base.Index",
• "compass.decoder.decoder.ClassDecoder",
• "compass.model.loss.TripletLoss",
• "compass.projector.projector.GeneSetProjector",
• "_codecs.encode",
• "torch.nn.modules.container.ModuleList",
• "collections.OrderedDict",
• "numpy.ndarray",
• "compass.projector.cellpathwayaggregator.CellPathwayAggregator",
• "compass.encoder.encoder.TransformerEncoder"

How to fix it?

• "compass.encoder.layer.performer.FastAttention",
• "compass.encoder.layer.performer.gaussian_orthogonal_random_matrix",
• "compass.augmentor.aug.RandomMaskAugmentor",
• "compass.encoder.layer.performer.PerformerLayer",
• "pandas.core.indexes.base._new_Index",
• "compass.projector.projector.CellPathwayProjector",
• "torch._C._VariableFunctionsClass",
• "torch.nn.modules.container.ParameterDict",
• "compass.model.loss.CEWithNaNLabelsLoss",
• "__builtin__.dict",
• "compass.model.scaler.Datascaler",
• "torch.nn.modules.dropout.Dropout",
• "compass.projector.genesetscorer.GeneSetScorer",
• "compass.embedder.embedder._GeneExpressionEmbedding",
• "numpy.dtype",
• "torch.optim.adam.Adam",
• "torch.nn.modules.container.Sequential",
• "compass.projector.genesetscorer.GeneSetScoreLinear",
• "compass.embedder.embedder.GeneEmbedding",
• "compass.model.saver.SaveBestModel",
• "torch.nn.modules.activation.ReLU",
• "pandas.core.series.Series",
• "numpy.core.multiarray.scalar",
• "compass.projector.projector.DisentangledProjector",
• "torch.nn.modules.linear.Linear",
• "compass.embedder.embedder.AbundanceEmbedding",
• "torch.nn.modules.activation.GELU",
• "torch.nn.modules.sparse.Embedding",
• "__builtin__.set",
• "torch.nn.modules.normalization.LayerNorm",
• "compass.encoder.encoder.Encoder",
• "collections.defaultdict",
• "compass.augmentor.aug.FeatureJitterAugmentor",
• "functools.partial",
• "compass.encoder.layer.performer.PerformerAttention",
• "torch.nn.modules.activation.Softmax",
• "pandas.core.internals.managers.SingleBlockManager",
• "compass.augmentor.aug.MaskJitterAugmentor",
• "torch.FloatStorage",
• "torch._utils._rebuild_tensor_v2",
• "__builtin__.slice",
• "torch.nn.modules.batchnorm.BatchNorm1d",
• "compass.model.model.Compass",
• "compass.main.PreTrainer",
• "compass.projector.cellpathwayaggregator.CellPathwayAttentionAggregator",
• "torch._utils._rebuild_parameter",
• "__builtin__.getattr",
• "compass.projector.genesetaggregator.GeneSetAggregator",
• "torch.LongStorage",
• "numpy.core.multiarray._reconstruct",
• "sklearn.preprocessing._data.MinMaxScaler",
• "compass.projector.genesetaggregator.GeneSetAttentionAggregator",
• "pandas.core.indexes.base.Index",
• "compass.decoder.decoder.ClassDecoder",
• "compass.model.loss.TripletLoss",
• "compass.projector.projector.GeneSetProjector",
• "_codecs.encode",
• "torch.nn.modules.container.ModuleList",
• "collections.OrderedDict",
• "numpy.ndarray",
• "compass.projector.cellpathwayaggregator.CellPathwayAggregator",
• "compass.encoder.encoder.TransformerEncoder"

How to fix it?