def ValidateAlgorithmSettings(self, request, context):
self.logger.info("Validate Algorithm Settings start")
graph_config = request.experiment_spec.nas_config.graph_config
# Validate GraphConfig
# Check InputSize
if not graph_config.input_sizes:
return self.SetValidateContextError(context, "Missing InputSizes in GraphConfig:\n{}".format(graph_config))
# Check OutputSize
if not graph_config.output_sizes:
return self.SetValidateContextError(context, "Missing OutputSizes in GraphConfig:\n{}".format(graph_config))
# Check NumLayers
if not graph_config.num_layers:
return self.SetValidateContextError(context, "Missing NumLayers in GraphConfig:\n{}".format(graph_config))
# Validate each operation
operations_list = list(request.experiment_spec.nas_config.operations.operation)
for operation in operations_list:
# Check OperationType
if not operation.operation_type:
return self.SetValidateContextError(context, "Missing operationType in Operation:\n{}".format(operation))
# Check ParameterConfigs
if not operation.parameter_specs.parameters:
return self.SetValidateContextError(context, "Missing ParameterConfigs in Operation:\n{}".format(operation))
# Validate each ParameterConfig in Operation
parameters_list = list(operation.parameter_specs.parameters)
for parameter in parameters_list:
# Check Name
if not parameter.name:
return self.SetValidateContextError(context, "Missing Name in ParameterConfig:\n{}".format(parameter))
# Check ParameterType
if not parameter.parameter_type:
return self.SetValidateContextError(context, "Missing ParameterType in ParameterConfig:\n{}".format(parameter))
# Check List in Categorical or Discrete Type
if parameter.parameter_type == api_pb2.CATEGORICAL or parameter.parameter_type == api_pb2.DISCRETE:
if not parameter.feasible_space.list:
return self.SetValidateContextError(context, "Missing List in ParameterConfig.feasibleSpace:\n{}".format(parameter) )
# Check Max, Min, Step in Int or Double Type
elif parameter.parameter_type == api_pb2.INT or parameter.parameter_type == api_pb2.DOUBLE:
if not parameter.feasible_space.min and not parameter.feasible_space.max:
return self.SetValidateContextError(context, "Missing Max and Min in ParameterConfig.feasibleSpace:\n{}".format(parameter))
if parameter.parameter_type == api_pb2.DOUBLE and (not parameter.feasible_space.step or float(parameter.feasible_space.step) <= 0):
return self.SetValidateContextError(context, "Step parameter should be > 0 in ParameterConfig.feasibleSpace:\n{}".format(parameter))
self.logger.info("All Experiment Settings are Valid")
return api_pb2.ValidateAlgorithmSettingsReply()
def ValidateAlgorithmSettings(self, request, context):
params = request.experiment_spec.parameter_specs.parameters
settings = request.experiment_spec.algorithm.algorithm_setting
setting_dict = {}
for setting in settings:
setting_dict[setting.name] = setting.value
if "r_l" not in setting_dict or "resourceName" not in setting_dict:
return self._set_validate_context_error(
context, "r_l and resourceName must be set.")
try:
rl = float(setting_dict["r_l"])
except:
return self._set_validate_context_error(
context, "r_l must be a positive float number.")
else:
if rl < 0:
return self._set_validate_context_error(
context, "r_l must be a positive float number.")
if "eta" in setting_dict:
eta = int(float(setting_dict["eta"]))
if eta <= 0:
eta = 3
else:
eta = 3
smax = int(math.log(rl) / math.log(eta))
max_parallel = int(math.ceil(eta**smax))
if request.experiment_spec.parallel_trial_count < max_parallel:
return self._set_validate_context_error(
context,
"parallelTrialCount must be not less than %d." % max_parallel)
valid_resourceName = False
for param in params:
if param.name == setting_dict["resourceName"]:
valid_resourceName = True
break
if not valid_resourceName:
return self._set_validate_context_error(
context,
"value of resourceName setting must be in parameters.")
return api_pb2.ValidateAlgorithmSettingsReply()
def ValidateAlgorithmSettings(self, request, context):
# TODO
return api_pb2.ValidateAlgorithmSettingsReply()
def SetValidateContextError(self, context, error_message):
context.set_code(grpc.StatusCode.INVALID_ARGUMENT)
context.set_details(error_message)
self.logger.info(error_message)
return api_pb2.ValidateAlgorithmSettingsReply()