class_docstr: Represents the configuration or type of machine to be used.
class_docstr_tok: ["Represents","the","configuration","or","type","of","machine","to","be","used","."]
docstr: Checks that the machine configuration created is valid for GCP.
docstr_tok: ["Checks","that","the","machine","configuration","created","is","valid","for","GCP","."]
code: def validate(self):
      """Checks that the machine configuration created is valid for GCP."""
      AcceleratorType.validate(self.accelerator_type)
      gcp.validate_machine_configuration(
          self.cpu_cores,
          self.memory,
          self.accelerator_type,
          self.accelerator_count,
      )
  
file_path: cloud/src/python/tensorflow_cloud/core/machine_config.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import enum
  from .None import gcp
label_desc: Use image node_id 2 for calling the MachineConfig obj's underlying member method code with example usage: obj.validate() without return types