HugeCTR API Documentation
- Python Interface
- About the HugeCTR Python Interface
- High-level Training API
- Layers
- Model
- Model class
- add method
- compile method
- fit method
- summary method
- graph_to_json method
- construct_from_json method
- load_dense_weights method
- load_dense_optimizer_states method
- load_sparse_weights method
- load_sparse_optimizer_states method
- freeze_dense method
- freeze_embedding method
- unfreeze_dense method
- unfreeze_embedding method
- reset_learning_rate_scheduler method
- set_source method
- Model
- Low-level Training API
- Inference API
- Data Generator API
- Data Source API
- Layer Classes and Methods
- Input Layer
- Sparse Embedding
- Embedding Types Detail
- Dense Layers
- Dense Layers Usage
- FullyConnected Layer
- MLP Layer
- MultiCross Layer
- FmOrder2 Layer
- WeightMultiply Layer
- ElementwiseMultiply Layer
- BatchNorm Layer
- LayerNorm Layer
- Concat Layer
- Reshape Layer
- Select Layer
- Slice Layer
- Dropout Layer
- ELU Layer
- ReLU Layer
- Sigmoid Layer
- Interaction Layer
- Add Layer
- ReduceSum Layer
- BinaryCrossEntropyLoss
- CrossEntropyLoss
- MultiCrossEntropyLoss
- Embedding Collection