docstr: Tests with large batch size to force multithreading.
docstr_tok: ["Tests","with","large","batch","size","to","force","multithreading","."]
code: def test_large_batch(self):
      """Tests with large batch size to force multithreading."""
      batch_size = 5000
      col1 = []
      col2 = []
      col3 = []
      for b in range(batch_size):
          col1.append(
              [
                  "batch%d-FC1-F1" % b,
                  "batch%d-FC1-F2" % b,
                  "batch%d-FC1-F3" % b,
              ]
          )
          col2.append(["batch%d-FC2-F1" % b])
          col3.append(["batch%d-FC3-F1" % b, "batch%d-FC3-F2" % b])
      sp_inp_1 = self._sparse_tensor(col1)
      sp_inp_2 = self._sparse_tensor(col2)
      sp_inp_3 = self._sparse_tensor(col3)
  
      inds, vals, shapes = gen_sparse_ops.sparse_cross_v2(
          indices=[
              sp_inp_1.indices,
              sp_inp_2.indices,
              sp_inp_3.indices,
          ],
          values=[sp_inp_1.values, sp_inp_2.values, sp_inp_3.values],
          shapes=[
              sp_inp_1.dense_shape,
              sp_inp_2.dense_shape,
              sp_inp_3.dense_shape,
          ],
          dense_inputs=[],
          sep="_X_",
      )
  
      col_out = []
      for b in range(batch_size):
          col_out.append(
              [
                  "batch%d-FC1-F1_X_batch%d-FC2-F1_X_batch%d-FC3-F1"
                  % (b, b, b),
                  "batch%d-FC1-F1_X_batch%d-FC2-F1_X_batch%d-FC3-F2"
                  % (b, b, b),
                  "batch%d-FC1-F2_X_batch%d-FC2-F1_X_batch%d-FC3-F1"
                  % (b, b, b),
                  "batch%d-FC1-F2_X_batch%d-FC2-F1_X_batch%d-FC3-F2"
                  % (b, b, b),
                  "batch%d-FC1-F3_X_batch%d-FC2-F1_X_batch%d-FC3-F1"
                  % (b, b, b),
                  "batch%d-FC1-F3_X_batch%d-FC2-F1_X_batch%d-FC3-F2"
                  % (b, b, b),
              ]
          )
  
      expected_out = self._sparse_tensor(col_out)
      out = sparse_tensor.SparseTensor(inds, vals, shapes)
      with self.cached_session():
          self._assert_sparse_tensor_equals(
              expected_out, self.evaluate(out)
          )
  
imports: import numpy
  from tensorflow.python.client import session
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_sparse_ops
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 10 for calling the SparseCrossV2OpTest obj's underlying member method code with example usage: obj.test_large_batch() without return types