docstr: Tests a large number of bins for a very small range of values.
  
  This test uses float type. 1-e302 is very small, and with 1M bins, it
  causes numeric underflow. This test is to show that this is handled.
  
  Note: this test was flaky due to how compiler and OS handls floats.
  Previously, 1-e38 does not induce overflow and cuases test error for some
  combinations of compiler and OS. Now 1-e302 should be small enough.
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code: def test_histogram_very_small_range_for_stride_underflow(self):
      """Tests a large number of bins for a very small range of values.
  
      This test uses float type. 1-e302 is very small, and with 1M bins, it
      causes numeric underflow. This test is to show that this is handled.
  
      Note: this test was flaky due to how compiler and OS handls floats.
      Previously, 1-e38 does not induce overflow and cuases test error for some
      combinations of compiler and OS. Now 1-e302 should be small enough.
      """
      X = np.array([0, 1e-302], dtype="f")
      large_bin_number = 1000000
      self._run_single_op_net([X], large_bin_number)
      self._check_histogram(
          [X],
          large_bin_number + 1,
          expected_counts=[2]
          + [0] * large_bin_number,  # [2, 0, 0, ..., 0]
      )
  
imports: import unittest
  import caffe2.python.hypothesis_test_util
  import hypothesis.strategies
  import numpy
  from caffe2.python import core, workspace
  from hypothesis import given, settings
label_desc: Use image node_id 12 for calling the TestSelfBinningHistogramBase obj's underlying member method code with example usage: obj.test_histogram_very_small_range_for_stride_underflow() without return types