↓ 1 callersMethod__init__(self, params, lr=1e-3, betas=(0.9, 0.999), eps=1e-8,
weight_decay=0, amsgrad=False)
rat-sql-gap/seq2struct/optimizers.py:150
↓ 1 callersMethod__init__(self, input_size, hidden_size, bidirectional=False, dropout=0., cell_factory=RecurrentDropoutLSTMCell)
rat-sql-gap/seq2struct/models/variational_lstm.py:111
↓ 1 callersMethod_inner_infer(self, model, beam_size, output_history, sliced_orig_data, sliced_preproc_data, output, use_heuristic=False)
rat-sql-gap/seq2struct/commands/infer.py:109
↓ 1 callersMethod_training_step(
self, model: nn.Module, inputs: Dict[str, Union[torch.Tensor, Any]], optimizer: torch.optim.Optimize
relogic/pretrainkit/multitask_trainer.py:602
↓ 1 callersMethod_training_step(
self, model: nn.Module, inputs: Dict[str, Union[torch.Tensor, Any]], optimizer: torch.optim.Optimize
relogic/pretrainkit/trainer.py:581
↓ 1 callersMethod_use_saved_state(self, k, v, saved_state, key_padding_mask, static_kv, bsz)
relogic/pretrainkit/models/semparse/modeling_bart_copy.py:694
↓ 1 callersMethod_use_saved_state(self, k, v, saved_state, key_padding_mask, static_kv, bsz)
relogic/pretrainkit/models/relationalsemparse/modeling_relational_bart.py:762
↓ 1 callersMethod_visualize_attention(self, model, beam_size, output_history, sliced_data, res1file, res2file, res3file, output)
rat-sql-gap/seq2struct/commands/infer.py:153
↓ 1 callersMethodcompute_relations(self, desc, enc_length, q_enc_length, c_enc_length, c_boundaries, t_boundaries)
relogic/pretrainkit/models/relationalsemparse/relational_transformer.py:618