See the guide: Learn (contrib) > Graph actions
This class specifies the configurations for an
If you're a Google-internal user using command line flags with
learn_runner.py (for instance, to do distributed training or to use
parameter servers), you probably want to use
__init__(master=None, num_cores=0, log_device_placement=False, gpu_memory_fraction=1, tf_random_seed=None, save_summary_steps=100, save_checkpoints_secs=600, save_checkpoints_steps=None, keep_checkpoint_max=5, keep_checkpoint_every_n_hours=10000, evaluation_master='')
Note that the superclass
ClusterConfig may set properties like
None in the args),
task_type based on the
environment variable. See
ClusterConfig for more details.
master: TensorFlow master. Defaults to empty string for local.
num_cores: Number of cores to be used. If 0, the system picks an appropriate number (default: 0).
log_device_placement: Log the op placement to devices (default: False).
gpu_memory_fraction: Fraction of GPU memory used by the process on each GPU uniformly on the same machine.
tf_random_seed: Random seed for TensorFlow initializers. Setting this value allows consistency between reruns.
save_summary_steps: Save summaries every this many steps.
save_checkpoints_secs: Save checkpoints every this many seconds. Can not be specified with
save_checkpoints_steps: Save checkpoints every this many steps. Can not be specified with
keep_checkpoint_max: The maximum number of recent checkpoint files to keep. As new files are created, older files are deleted. If None or 0, all checkpoint files are kept. Defaults to 5 (that is, the 5 most recent checkpoint files are kept.)
keep_checkpoint_every_n_hours: Number of hours between each checkpoint to be saved. The default value of 10,000 hours effectively disables the feature.
evaluation_master: the master on which to perform evaluation.
Returns task index from
TF_CONFIG environmental variable.
If you have a ClusterConfig instance, you can just access its task_id property instead of calling this function and re-parsing the environmental variable.
TF_CONFIG['task']['index']. Defaults to 0.