def load(self, filename, create_if_missing=True):
        filename = Path(filename)
        if not filename.exists() and create_if_missing:
            self.load_pip_requirements()
            with filename.open("w") as f:
                f.write(yaml.dump(self.serialized, default_flow_style=False,
                                  encoding=None))
            self.filename = filename
            return self.save(filename)
        with filename.open() as f:
            for group, requirements in yaml.load(f.read()).items():
                for requirement in requirements:
                    self[group].add(Requirement.coerce(requirement))
        self.filename = filename
def testMinimizeSparseResourceVariable(self, dtype):
    with self.cached_session():
      var0 = resource_variable_ops.ResourceVariable([[1.0, 2.0]], dtype=dtype)
      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 = rmsprop.RMSPropOptimizer(
          learning_rate=1.0,
          decay=0.0,
          momentum=0.0,
          epsilon=0.0,
          centered=False).minimize(loss)
      variables.global_variables_initializer().run()
      # Fetch params to validate initial values
      self.assertAllCloseAccordingToType([[1.0, 2.0]], var0.eval())
      # Run 1 step of sgd
      sgd_op.run()
      # Validate updated params
      self.assertAllCloseAccordingToType(
          [[0., 1.]], var0.eval(), atol=0.01)