code: def testDebugNumericSummaryV2OpFullHealthLarge(self):
      def debug_summary(x):
          return (
              self.evaluate(
                  gen_debug_ops.debug_numeric_summary_v2(
                      x,
                      tensor_debug_mode=(
                          debug_event_pb2.TensorDebugMode.FULL_HEALTH
                      ),
                      tensor_id=x._id,
                      output_dtype=dtypes.float64,
                  )
              ),
              x._id,
          )
  
      def tensor_counts(arr):
          counts = [len(np.shape(arr)), np.size(arr), 0, 0, 0, 0, 0, 0]
          for n in np.ravel(arr):
              if np.isneginf(n):
                  counts[2] += 1
              elif np.isposinf(n):
                  counts[3] += 1
              elif np.isnan(n):
                  counts[4] += 1
              elif n < 0.0:
                  counts[5] += 1
              elif n == 0.0:
                  counts[6] += 1
              else:
                  counts[7] += 1
          return counts
  
      x = np.zeros([50, 50], dtype=np.float16)
      x[32, 47] = np.nan
      x[0:4, 3] = np.inf
      x[40:50, 40:50] = 10
      x[3, 20] = -10
      tensor, tensor_id = debug_summary(constant_op.constant(x))
      expected = [tensor_id, -1, 19] + tensor_counts(x)
      self.assertAllEqual(tensor, expected)
  
      x = np.ones([25, 25, 50], dtype=np.float32) * np.inf
      x[:, :, 1] = np.nan
      x[:, :, 2] = -np.inf
      x[:, :, 3] = -1
      x[:, :, 4] = 0
      x[:, :, 5] = 1
      tensor, tensor_id = debug_summary(constant_op.constant(x))
      expected = [tensor_id, -1, 1] + tensor_counts(x)
      self.assertAllEqual(tensor, expected)
      x[0, 0, 0] = np.nan
      tensor, tensor_id = debug_summary(constant_op.constant(x))
      expected = [
          tensor_id,
          -1,
          1,
      ] + tensor_counts(x)
      self.assertAllEqual(tensor, expected)
      x = np.zeros([9701], dtype=np.float64)
      x[9700] = np.nan
      tensor, tensor_id = debug_summary(constant_op.constant(x))
      expected = [tensor_id, -1, 2] + tensor_counts(x)
      self.assertAllEqual(tensor, expected)
  
imports: import os
  import numpy
  from tensorflow.core.protobuf import debug_event_pb2
  from tensorflow.python.debug.lib import debug_events_reader
  from tensorflow.python.debug.lib import debug_events_writer
  from tensorflow.python.debug.lib import dumping_callback_test_lib
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_debug_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import googletest
label_desc: Use image node_id 14 for calling the DebugNumericSummaryV2Test obj's underlying member method code with example usage: obj.testDebugNumericSummaryV2OpFullHealthLarge() and returns: self,  x, counts