code: def testBasicCallableParams(self):
      for dtype in [dtypes.half, dtypes.float32, dtypes.float64]:
          # train.GradientDescentOptimizer is V1 only API.
          with ops.Graph().as_default(), self.cached_session():
              var0 = resource_variable_ops.ResourceVariable(
                  [1.0, 2.0], dtype=dtype
              )
              var1 = resource_variable_ops.ResourceVariable(
                  [3.0, 4.0], dtype=dtype
              )
              grads0 = constant_op.constant([0.1, 0.1], dtype=dtype)
              grads1 = constant_op.constant([0.01, 0.01], dtype=dtype)
              lr = lambda: 3.0
              sgd_op = gradient_descent.GradientDescentOptimizer(
                  lr
              ).apply_gradients(zip([grads0, grads1], [var0, var1]))
              # TODO(apassos) calling initialize_resources on all resources here
              # doesn't work because the sessions and graph are reused across unit
              # tests and this would mean trying to reinitialize variables. Figure out
              # a long-term solution for this.
              resources.initialize_resources([var0, var1]).run()
              # Fetch params to validate initial values
              self.assertAllCloseAccordingToType(
                  [1.0, 2.0], self.evaluate(var0)
              )
              self.assertAllCloseAccordingToType(
                  [3.0, 4.0], self.evaluate(var1)
              )
              # Run 1 step of sgd
              sgd_op.run()
              # Validate updated params
              self.assertAllCloseAccordingToType(
                  [1.0 - 3.0 * 0.1, 2.0 - 3.0 * 0.1],
                  self.evaluate(var0),
              )
              self.assertAllCloseAccordingToType(
                  [3.0 - 3.0 * 0.01, 4.0 - 3.0 * 0.01],
                  self.evaluate(var1),
              )
  
imports: from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import indexed_slices
  from tensorflow.python.framework import ops
  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 resources
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import test
  from tensorflow.python.training import gradient_descent
label_desc: Use image node_id 3 for calling the GradientDescentOptimizerTest obj's underlying member method code with example usage: obj.testBasicCallableParams() without return types