class_docstr: Tests for the load_and_remap_matrix() op.
  
  (Specifically focused on the max_rows_in_memory arg and its effects on
  TensorBundle's BundleReader and TensorSlice logic).
docstr: Tests loading partitioned var with more slices than partitions.
docstr_tok: ["Tests","loading","partitioned","var","with","more","slices","than","partitions","."]
code: def test_loading_partitions_greater_than_max_rows(self):
      """Tests loading partitioned var with more slices than partitions."""
      self._test_loading_variable_with_max_rows(
          np_value=np.reshape(list(range(0, 36)), (9, 4)),
          partitioner=partitioned_variables.fixed_size_partitioner(3),
          # Even though each partition has 3 rows, we'll only load the tensor one
          # row at a time.
          max_rows_in_memory=1,
      )
  
imports: import os
  import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import gen_checkpoint_ops
  from tensorflow.python.ops import partitioned_variables
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import flags
  from tensorflow.python.platform import test
  from tensorflow.python.training import saver
label_desc: Use image node_id 7 for calling the LoadAndRemapMatrixWithMaxRowsTest obj's underlying member method code with example usage: obj.test_loading_partitions_greater_than_max_rows() without return types