code: def _verify_staircase_increase(values, step_size):
      num_values = len(values)
      for i in range(0, num_values, step_size):
          j = min(i + step_size, num_values)
          assert all([values[i] == v for v in values[i:j]])
  
imports: import torch
  import deepspeed
  import pytest
  from unit.common import DistributedTest
  from unit.simple_model import SimpleModel, random_dataloader
  from deepspeed.runtime.lr_schedules import LR_RANGE_TEST, LR_RANGE_TEST_MIN_LR, LR_RANGE_TEST_STEP_RATE, LR_RANGE_TEST_STEP_SIZE, LR_RANGE_TEST_STAIRCASE
  from deepspeed.runtime.lr_schedules import WARMUP_LR, WARMUP_MIN_LR, WARMUP_MAX_LR, WARMUP_NUM_STEPS, WARMUP_TYPE, WARMUP_LOG_RATE, WARMUP_LINEAR_RATE
  from deepspeed.runtime.lr_schedules import ONE_CYCLE, CYCLE_MIN_LR, CYCLE_MAX_LR, CYCLE_FIRST_STEP_SIZE, DECAY_LR_RATE, DECAY_STEP_SIZE
  from deepspeed.runtime.lr_schedules import CYCLE_MIN_MOM, CYCLE_MAX_MOM, DECAY_MOM_RATE
  from deepspeed.runtime.lr_schedules import WARMUP_DECAY_LR, TOTAL_NUM_STEPS
  from deepspeed.runtime.lr_schedules import WARMUP_COSINE_LR, WARMUP_MIN_RATIO, COS_MIN_RATIO
label_desc: Use image node_id 3 for calling a global function with example usage: _verify_staircase_increase(values, step_size) without return types