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MetaLearningModel

Trait MetaLearningModel 

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pub trait MetaLearningModel: Send + Sync {
Show 26 methods // Required methods fn forward( &mut self, examples: &ExampleSet, ) -> Result<f64, TrustformersError>; fn compute_accuracy( &self, examples: &ExampleSet, ) -> Result<f64, TrustformersError>; fn compute_gradients( &self, loss: f64, ) -> Result<ModelGradients, TrustformersError>; fn apply_gradients( &mut self, gradients: &ModelGradients, lr: f64, ) -> Result<(), TrustformersError>; fn get_parameters(&self) -> Result<ModelParameters, TrustformersError>; fn set_parameters( &mut self, params: ModelParameters, ) -> Result<(), TrustformersError>; fn embed(&self, example: &Example) -> Result<Tensor, TrustformersError>; // Provided methods fn compute_second_order_gradients( &self, _initial_params: &ModelParameters, _loss: f64, ) -> Result<ModelGradients, TrustformersError> { ... } fn compute_first_order_gradients( &self, _loss: f64, ) -> Result<ModelGradients, TrustformersError> { ... } fn compute_relation( &self, _emb1: &Tensor, _emb2: &Tensor, ) -> Result<f64, TrustformersError> { ... } fn write_to_memory( &mut self, _example: &Example, ) -> Result<(), TrustformersError> { ... } fn read_from_memory( &self, _example: &Example, ) -> Result<MemoryOutput, TrustformersError> { ... } fn predict_from_memory( &self, _memory_output: &MemoryOutput, ) -> Result<MemoryPrediction, TrustformersError> { ... } fn clear_memory(&mut self) -> Result<(), TrustformersError> { ... } fn get_learning_rates(&self) -> Result<Vec<f64>, TrustformersError> { ... } fn apply_gradients_with_lr( &mut self, _gradients: &ModelGradients, _learning_rates: &[f64], ) -> Result<(), TrustformersError> { ... } fn compute_lr_gradients( &self, _loss: f64, ) -> Result<Vec<f64>, TrustformersError> { ... } fn get_meta_learner_state( &self, ) -> Result<MetaLearnerState, TrustformersError> { ... } fn apply_learned_algorithm( &self, _support_set: &ExampleSet, _state: &MetaLearnerState, ) -> Result<ModelParameters, TrustformersError> { ... } fn evaluate_with_params( &self, _examples: &ExampleSet, _params: &ModelParameters, ) -> Result<f64, TrustformersError> { ... } fn compute_accuracy_with_params( &self, _examples: &ExampleSet, _params: &ModelParameters, ) -> Result<f64, TrustformersError> { ... } fn compute_meta_learner_gradients( &self, _loss: f64, ) -> Result<ModelGradients, TrustformersError> { ... } fn get_lstm_state(&self) -> Result<LSTMState, TrustformersError> { ... } fn lstm_update( &self, _gradients: &ModelGradients, _state: &LSTMState, _step: usize, ) -> Result<(ModelUpdates, LSTMState), TrustformersError> { ... } fn apply_lstm_updates( &mut self, _updates: &ModelUpdates, ) -> Result<(), TrustformersError> { ... } fn compute_lstm_gradients( &self, _loss: f64, ) -> Result<ModelGradients, TrustformersError> { ... }
}
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Trait definitions for model components

Required Methods§

Provided Methods§

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fn compute_second_order_gradients( &self, _initial_params: &ModelParameters, _loss: f64, ) -> Result<ModelGradients, TrustformersError>

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fn compute_first_order_gradients( &self, _loss: f64, ) -> Result<ModelGradients, TrustformersError>

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fn compute_relation( &self, _emb1: &Tensor, _emb2: &Tensor, ) -> Result<f64, TrustformersError>

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fn write_to_memory( &mut self, _example: &Example, ) -> Result<(), TrustformersError>

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fn read_from_memory( &self, _example: &Example, ) -> Result<MemoryOutput, TrustformersError>

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fn predict_from_memory( &self, _memory_output: &MemoryOutput, ) -> Result<MemoryPrediction, TrustformersError>

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fn clear_memory(&mut self) -> Result<(), TrustformersError>

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fn get_learning_rates(&self) -> Result<Vec<f64>, TrustformersError>

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fn apply_gradients_with_lr( &mut self, _gradients: &ModelGradients, _learning_rates: &[f64], ) -> Result<(), TrustformersError>

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fn compute_lr_gradients( &self, _loss: f64, ) -> Result<Vec<f64>, TrustformersError>

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fn get_meta_learner_state(&self) -> Result<MetaLearnerState, TrustformersError>

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fn apply_learned_algorithm( &self, _support_set: &ExampleSet, _state: &MetaLearnerState, ) -> Result<ModelParameters, TrustformersError>

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fn evaluate_with_params( &self, _examples: &ExampleSet, _params: &ModelParameters, ) -> Result<f64, TrustformersError>

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fn compute_accuracy_with_params( &self, _examples: &ExampleSet, _params: &ModelParameters, ) -> Result<f64, TrustformersError>

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fn compute_meta_learner_gradients( &self, _loss: f64, ) -> Result<ModelGradients, TrustformersError>

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fn get_lstm_state(&self) -> Result<LSTMState, TrustformersError>

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fn lstm_update( &self, _gradients: &ModelGradients, _state: &LSTMState, _step: usize, ) -> Result<(ModelUpdates, LSTMState), TrustformersError>

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fn apply_lstm_updates( &mut self, _updates: &ModelUpdates, ) -> Result<(), TrustformersError>

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fn compute_lstm_gradients( &self, _loss: f64, ) -> Result<ModelGradients, TrustformersError>

Implementors§