code: def testMinimizeSparseResourceVariable(self):
      for dtype in [dtypes.float32, dtypes.float64]:
          with self.cached_session():
              var0 = resource_variable_ops.ResourceVariable(
                  [[1.0, 2.0]], dtype=dtype
              )
              global_step = resource_variable_ops.ResourceVariable(
                  0, dtype=dtypes.int64
              )
              x = constant_op.constant([[4.0], [5.0]], dtype=dtype)
              pred = math_ops.matmul(
                  embedding_ops.embedding_lookup([var0], [0]), x
              )
              loss = pred * pred
              sgd_op = adagrad_da.AdagradDAOptimizer(
                  1.0, global_step
              ).minimize(loss)
              self.evaluate(variables.global_variables_initializer())
              # Fetch params to validate initial values
              self.assertAllCloseAccordingToType(
                  [[1.0, 2.0]], self.evaluate(var0)
              )
              # Run 1 step of sgd
              sgd_op.run()
              # Validate updated params
              self.assertAllCloseAccordingToType(
                  [[-1, -1]], self.evaluate(var0), rtol=0.01
              )
  
file_path: tensorflow-upstream/tensorflow/python/training/adagrad_da_test.py
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import embedding_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import resource_variable_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.training import adagrad_da
label_desc: Use image node_id 4 for calling the AdagradDAOptimizerTest obj's underlying member method code with example usage: obj.testMinimizeSparseResourceVariable() without return types