code: def test_cummin():
      x = torch.rand(10)
      y = torch.empty(x.shape)
      y[0] = x[0]
      for i in range(1, x.size(0)):
          y[i] = min(x[i], y[i - 1])
  
      assert_equal(_cummin(x), y)
  
imports: import warnings
  import pytest
  import torch
  from pyro.ops.stats import _cummin, autocorrelation, autocovariance, crps_empirical, effective_sample_size, fit_generalized_pareto, gelman_rubin, hpdi, pi, quantile, resample, split_gelman_rubin, waic
  from tests.common import assert_close, assert_equal, xfail_if_not_implemented
label_desc: Use image node_id 13 for calling a global function with example usage: test_cummin() without return types