def to_env_vars(self):
"""Environment variable representation of the training environment
Returns:
dict: an instance of dictionary
"""
env = {
'hosts': self.hosts,
'network_interface_name': self.network_interface_name,
'hps': self.hyperparameters,
'user_entry_point': self.user_entry_point,
'framework_params': self.additional_framework_parameters,
'resource_config': self.resource_config,
'input_data_config': self.input_data_config,
'output_data_dir': self.output_data_dir,
'channels': sorted(self.channel_input_dirs.keys()),
'current_host': self.current_host,
'module_name': self.module_name,
'log_level': self.log_level,
'framework_module': self.framework_module,
'input_dir': self.input_dir,
'input_config_dir': self.input_config_dir,
'output_dir': self.output_dir,
'num_cpus': self.num_cpus,
'num_gpus': self.num_gpus,
'model_dir': self.model_dir,
'module_dir': self.module_dir,
'training_env': dict(self),
'user_args': self.to_cmd_args(),
'output_intermediate_dir': self.output_intermediate_dir
}
for name, path in self.channel_input_dirs.items():
env['channel_%s' % name] = path
for key, value in self.hyperparameters.items():
env['hp_%s' % key] = value
return _mapping.to_env_vars(env)
def to_env_vars(self):
"""Environment variable representation of the training environment
Returns:
dict: an instance of dictionary
"""
env = {
"hosts": self.hosts,
"network_interface_name": self.network_interface_name,
"hps": self.hyperparameters,
"user_entry_point": self.user_entry_point,
"framework_params": self.additional_framework_parameters,
"resource_config": self.resource_config,
"input_data_config": self.input_data_config,
"output_data_dir": self.output_data_dir,
"channels": sorted(self.channel_input_dirs.keys()),
"current_host": self.current_host,
"module_name": self.module_name,
"log_level": self.log_level,
"framework_module": self.framework_module,
"input_dir": self.input_dir,
"input_config_dir": self.input_config_dir,
"output_dir": self.output_dir,
"num_cpus": self.num_cpus,
"num_gpus": self.num_gpus,
"model_dir": self.model_dir,
"module_dir": self.module_dir,
"training_env": dict(self),
"user_args": self.to_cmd_args(),
"output_intermediate_dir": self.output_intermediate_dir,
}
for name, path in self.channel_input_dirs.items():
env["channel_%s" % name] = path
for key, value in self.hyperparameters.items():
env["hp_%s" % key] = value
return _mapping.to_env_vars(env)
