Commit 5993f04b authored by Lawrence McAfee's avatar Lawrence McAfee
Browse files

removed distribute_checkpointed_activations_helper()

parent d6380fda

megatron/model/transformer.py

+2 −19
Original line number Diff line number Diff line
@@ -626,23 +626,6 @@ class ParallelTransformer(MegatronModule): 
                return x_

            return custom_forward



        def distribute_checkpointed_activations_helper(layer_number):

            """Distribute checkpointed activations across the tensor model

               Parallel ranks if the `distribute-checkpointed-activations

               is on and either of the following conditions is met:

                 - it is not the first layer in the in the pipeline stage.

                   The first layer is used in the pipeline parallelism 

                   and changing its shape throws error in the backward pass.

                 - we are at the first pipline stage so the input tensor is

                   not used in pipeline parallelism. Note that no pipeline

                   parallelism is a special case of this.

            """

            not_first_layer_in_pipeline_stage = (layer_number > 0)

            is_first_pipeline_stage = (

                mpu.get_pipeline_model_parallel_rank() == 0)

            return self.distribute_checkpointed_activations and \

                (not_first_layer_in_pipeline_stage or is_first_pipeline_stage)



        if self.activations_checkpoint_method == 'uniform':

            # Uniformly divide the total number of Transformer layers and checkpoint

            # the input activation of each divided chunk.
@@ -651,7 +634,7 @@ class ParallelTransformer(MegatronModule): 
            while l < self.num_layers:

                hidden_states = mpu.checkpoint(

                    custom(l, l + self.activations_checkpoint_num_layers),

                    distribute_checkpointed_activations_helper(l),

                    self.distribute_checkpointed_activations,

                    hidden_states, attention_mask, encoder_output, enc_dec_attn_mask)

                l += self.activations_checkpoint_num_layers

        elif self.activations_checkpoint_method == 'block':
@@ -662,7 +645,7 @@ class ParallelTransformer(MegatronModule): 
                if l < self.activations_checkpoint_num_layers:

                    hidden_states = mpu.checkpoint(

                        custom(l, l + 1),

                        distribute_checkpointed_activations_helper(l),

                        self.distribute_checkpointed_activations,

                        hidden_states, attention_mask, encoder_output, enc_dec_attn_mask)

                else:

                    hidden_states = custom(l, l + 1)(