code: def update(self, consumed_samples, consistency_check):
      if consumed_samples > self.ramup_samples:
          self.current_global_batch_size = self.global_batch_size
      else:
          steps = int(
              consumed_samples / self.rampup_samples_per_increment
          )
          self.current_global_batch_size = (
              self.start_batch_size + steps * self.batch_size_increment
          )
          assert (
              self.current_global_batch_size <= self.global_batch_size
          )
  
      if consistency_check:
          assert (
              self.current_global_batch_size
              % self.micro_batch_times_data_parallel_size
              == 0
          ), (
              "current global "
              "batch size ({}) is not divisible by micro-batch-size ({}) times"
              "data parallel size ({})".format(
                  self.current_global_batch_size,
                  self.micro_batch_size,
                  self.data_parallel_size,
              )
          )
      self.num_micro_batches = (
          self.current_global_batch_size
          // self.micro_batch_times_data_parallel_size
      )
  
file_path: megatron-lm/megatron/microbatches.py
imports: from abc import ABC
  from abc import abstractmethod
label_desc: Use image node_id 2 for calling the RampupBatchsizeNumMicroBatches obj's underlying member method code with example usage: obj.update(consumed_samples, consistency_check) without return types