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)