class NotebookConfig(PipelineConfig):
"""Config store for a notebook.
This config extends the base pipeline config to take into account some
small differences in the handling of a notebook.
"""
notebook_path = Field(type=str, required=True)
# FIXME: Probably this can be removed. The labextension passes both
# 'experiment_name' and 'experiment', but the latter is not used in the
# backend.
experiment = Field(type=dict)
# Used in the UI to keep per-notebook state of the volumes snapshot toggle
snapshot_volumes = Field(type=bool, default=False)
# override from PipelineConfig: set the default value to False
autosnapshot = Field(type=bool, default=False)
@property
def source_path(self):
"""Get the path to the source notebook."""
return self.notebook_path
def _preprocess(self, kwargs):
kwargs["steps_defaults"] = self._parse_steps_defaults(
kwargs.get("steps_defaults"))
def _parse_steps_defaults(self, steps_defaults):
"""Parse common step configuration defined in the metadata."""
result = dict()
if not isinstance(steps_defaults, list):
return steps_defaults
for c in steps_defaults:
if any(re.match(_c, c)
for _c in _STEPS_DEFAULTS_LANGUAGE) is False:
raise ValueError("Unrecognized common step configuration:"
" {}".format(c))
parts = c.split(":")
conf_type = parts.pop(0)
if conf_type in ["annotation", "label"]:
result_key = "{}s".format(conf_type)
if result_key not in result:
result[result_key] = dict()
key, value = get_annotation_or_label_from_tag(parts)
result[result_key][key] = value
if conf_type == "limit":
if "limits" not in result:
result["limits"] = dict()
key, value = get_limit_from_tag(parts)
result["limits"][key] = value
return result
class VolumeConfig(Config):
"""Used for validating the `volumes` field of NotebookConfig."""
name = Field(type=str,
required=True,
validators=[validators.K8sNameValidator])
mount_point = Field(type=str, required=True)
snapshot = Field(type=bool, default=False)
snapshot_name = Field(type=str)
size = Field(type=int) # fixme: validation for this field?
size_type = Field(type=str) # fixme: validation for this field?
type = Field(type=str,
required=True,
validators=[validators.VolumeTypeValidator])
annotations = Field(type=list, default=list())
def _postprocess(self):
# Convert annotations to a {k: v} dictionary
try:
# TODO: Make JupyterLab annotate with {k: v} instead of
# {'key': k, 'value': v}
self.annotations = {
a['key']: a['value']
for a in self.annotations
if a['key'] != '' and a['value'] != ''
}
except KeyError as e:
if str(e) in ["'key'", "'value'"]:
raise ValueError("Volume spec: volume annotations must be a"
" list of {'key': k, 'value': v} dicts")
else:
raise e
class StepConfig(Config):
"""Config class used for the Step object."""
name = Field(type=str,
required=True,
validators=[validators.StepNameValidator])
labels = Field(type=dict,
default=dict(),
validators=[validators.K8sLabelsValidator])
annotations = Field(type=dict,
default=dict(),
validators=[validators.K8sAnnotationsValidator])
limits = Field(type=dict,
default=dict(),
validators=[validators.K8sLimitsValidator])
class StepConfig(Config):
"""Config class used for the Step object."""
name = Field(type=str, required=True,
validators=[validators.StepNameValidator])
labels = Field(type=dict, default=dict(),
validators=[validators.K8sLabelsValidator])
annotations = Field(type=dict, default=dict(),
validators=[validators.K8sAnnotationsValidator])
limits = Field(type=dict, default=dict(),
validators=[validators.K8sLimitsValidator])
retry_count = Field(type=int, default=0)
retry_interval = Field(type=str)
retry_factor = Field(type=int)
retry_max_interval = Field(type=str)
timeout = Field(type=int, validators=[validators.PositiveIntegerValidator])
class KatibConfig(Config):
"""Used to validate the `katib_metadata` field of NotebookConfig."""
# fixme: improve validation of single fields
parameters = Field(type=list, default=[])
objective = Field(type=dict, default={})
algorithm = Field(type=dict, default={})
# fixme: Change these names to be Pythonic (need to change how the
# labextension passes them)
maxTrialCount = Field(type=int, default=12)
maxFailedTrialCount = Field(type=int, default=3)
parallelTrialCount = Field(type=int, default=3)
class PipelineConfig(Config):
"""Main config class to validate the pipeline metadata."""
pipeline_name = Field(type=str, required=True,
validators=[validators.PipelineNameValidator])
experiment_name = Field(type=str, required=True)
pipeline_description = Field(type=str, default="")
docker_image = Field(type=str, default="")
volumes = Field(type=list, items_config_type=VolumeConfig, default=[])
katib_run = Field(type=bool, default=False)
katib_metadata = Field(type=KatibConfig)
abs_working_dir = Field(type=str, default="")
marshal_volume = Field(type=bool, default=True)
marshal_path = Field(type=str, default="/marshal")
autosnapshot = Field(type=bool, default=True)
steps_defaults = Field(type=dict, default=dict())
kfp_host = Field(type=str)
storage_class_name = Field(type=str,
validators=[validators.K8sNameValidator])
volume_access_mode = Field(
type=str, validators=[validators.IsLowerValidator,
validators.VolumeAccessModeValidator])
@property
def source_path(self):
"""Get the path to the main entry point script."""
return utils.get_main_source_path()
def _postprocess(self):
self._randomize_pipeline_name()
self._set_docker_image()
self._set_volume_storage_class()
self._set_volume_access_mode()
self._sort_volumes()
self._set_abs_working_dir()
self._set_marshal_path()
def _randomize_pipeline_name(self):
self.pipeline_name = "%s-%s" % (self.pipeline_name,
utils.random_string())
def _set_docker_image(self):
if not self.docker_image:
try:
self.docker_image = podutils.get_docker_base_image()
except (ConfigException, FileNotFoundError, ApiException):
# no K8s config found; use kfp default image
self.docker_image = ""
def _set_volume_storage_class(self):
if not self.storage_class_name:
return
for v in self.volumes:
if not v.storage_class_name:
v.storage_class_name = self.storage_class_name
def _set_volume_access_mode(self):
if not self.volume_access_mode:
self.volume_access_mode = DEFAULT_VOLUME_ACCESS_MODE
else:
self.volume_access_mode = VOLUME_ACCESS_MODE_MAP[
self.volume_access_mode]
for v in self.volumes:
if not v.volume_access_mode:
v.volume_access_mode = self.volume_access_mode
def _sort_volumes(self):
# The Jupyter Web App assumes the first volume of the notebook is the
# working directory, so we make sure to make it appear first in the
# spec.
self.volumes = sorted(self.volumes,
reverse=True,
key=lambda _v: podutils.is_workspace_dir(
_v.mount_point))
def _set_abs_working_dir(self):
if not self.abs_working_dir:
self.abs_working_dir = utils.abs_working_dir(self.source_path)
def _set_marshal_path(self):
# Check if the workspace directory is under a mounted volume.
# If so, marshal data into a folder in that volume,
# otherwise create a new volume and mount it at /marshal
wd = os.path.realpath(self.abs_working_dir)
# get the volumes for which the working directory is a sub-path of
# the mount point
vols = list(
filter(lambda x: wd.startswith(x.mount_point), self.volumes))
# if we found any, then set marshal directory inside working directory
if len(vols) > 0:
basename = os.path.basename(self.source_path)
marshal_dir = ".{}.kale.marshal.dir".format(basename)
self.marshal_volume = False
self.marshal_path = os.path.join(wd, marshal_dir)
