Commit b219ff00 authored by Jared Casper's avatar Jared Casper
Browse files

Update code used for finetuning to latest API.

parent b4b0d739

megatron/model/classification.py

+1 −2
Original line number Diff line number Diff line
@@ -52,8 +52,7 @@ class Classification(MegatronModule): 


    def forward(self, input_ids, attention_mask, tokentype_ids):



        extended_attention_mask = bert_extended_attention_mask(

            attention_mask, next(self.language_model.parameters()).dtype)

        extended_attention_mask = bert_extended_attention_mask(attention_mask)

        position_ids = bert_position_ids(input_ids)



        _, pooled_output = self.language_model(input_ids,

megatron/model/multiple_choice.py

+1 −2
Original line number Diff line number Diff line
@@ -64,8 +64,7 @@ class MultipleChoice(MegatronModule): 
        attention_mask = attention_mask.view(-1, attention_mask.size(-1))

        tokentype_ids = tokentype_ids.view(-1, tokentype_ids.size(-1))



        extended_attention_mask = bert_extended_attention_mask(

            attention_mask, next(self.language_model.parameters()).dtype)

        extended_attention_mask = bert_extended_attention_mask(attention_mask)

        position_ids = bert_position_ids(input_ids)



        _, pooled_output = self.language_model(input_ids,

tasks/finetune_utils.py

+3 −3
Original line number Diff line number Diff line
@@ -161,7 +161,7 @@ def _train(model, optimizer, lr_scheduler, forward_step, 
            start_iteration = 0



            # Train for one step.

            losses_dict, _ = train_step(forward_step, batch, model,

            losses_dict, skipped_iter = train_step(forward_step, batch, model,

                                                   optimizer, lr_scheduler)

            iteration += 1
@@ -169,7 +169,7 @@ def _train(model, optimizer, lr_scheduler, forward_step, 
            report_memory_flag = training_log(losses_dict, losses_dict_sum,

                                              optimizer.param_groups[0]['lr'],

                                              iteration, optimizer.loss_scale,

                                              report_memory_flag)

                                              report_memory_flag, skipped_iter)



            # Autoresume

            if args.adlr_autoresume and \