pipelines/sdk/python/kfp/compiler/_op_to_template.py

265 lines
9.2 KiB
Python

# Copyright 2019 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import re
import warnings
import yaml
from collections import OrderedDict
from typing import Union, List, Any, Callable, TypeVar, Dict
from ._k8s_helper import K8sHelper
from .. import dsl
from ..dsl._container_op import BaseOp
from ..dsl._artifact_location import ArtifactLocation
# generics
T = TypeVar('T')
def _process_obj(obj: Any, map_to_tmpl_var: dict):
"""Recursively sanitize and replace any PipelineParam (instances and serialized strings)
in the object with the corresponding template variables
(i.e. '{{inputs.parameters.<PipelineParam.full_name>}}').
Args:
obj: any obj that may have PipelineParam
map_to_tmpl_var: a dict that maps an unsanitized pipeline
params signature into a template var
"""
# serialized str might be unsanitized
if isinstance(obj, str):
# get signature
param_tuples = dsl.match_serialized_pipelineparam(obj)
if not param_tuples:
return obj
# replace all unsanitized signature with template var
for param_tuple in param_tuples:
obj = re.sub(param_tuple.pattern, map_to_tmpl_var[param_tuple.pattern], obj)
# list
if isinstance(obj, list):
return [_process_obj(item, map_to_tmpl_var) for item in obj]
# tuple
if isinstance(obj, tuple):
return tuple((_process_obj(item, map_to_tmpl_var) for item in obj))
# dict
if isinstance(obj, dict):
return {
key: _process_obj(value, map_to_tmpl_var)
for key, value in obj.items()
}
# pipelineparam
if isinstance(obj, dsl.PipelineParam):
# if not found in unsanitized map, then likely to be sanitized
return map_to_tmpl_var.get(
str(obj), '{{inputs.parameters.%s}}' % obj.full_name)
# k8s objects (generated from swaggercodegen)
if hasattr(obj, 'swagger_types') and isinstance(obj.swagger_types, dict):
# process everything inside recursively
for key in obj.swagger_types.keys():
setattr(obj, key, _process_obj(getattr(obj, key), map_to_tmpl_var))
# return json representation of the k8s obj
return K8sHelper.convert_k8s_obj_to_json(obj)
# k8s objects (generated from openapi)
if hasattr(obj, 'openapi_types') and isinstance(obj.openapi_types, dict):
# process everything inside recursively
for key in obj.openapi_types.keys():
setattr(obj, key, _process_obj(getattr(obj, key), map_to_tmpl_var))
# return json representation of the k8s obj
return K8sHelper.convert_k8s_obj_to_json(obj)
# do nothing
return obj
def _process_base_ops(op: BaseOp):
"""Recursively go through the attrs listed in `attrs_with_pipelineparams`
and sanitize and replace pipeline params with template var string.
Returns a processed `BaseOp`.
NOTE this is an in-place update to `BaseOp`'s attributes (i.e. the ones
specified in `attrs_with_pipelineparams`, all `PipelineParam` are replaced
with the corresponding template variable strings).
Args:
op {BaseOp}: class that inherits from BaseOp
Returns:
BaseOp
"""
# map param's (unsanitized pattern or serialized str pattern) -> input param var str
map_to_tmpl_var = {
(param.pattern or str(param)): '{{inputs.parameters.%s}}' % param.full_name
for param in op.inputs
}
# process all attr with pipelineParams except inputs and outputs parameters
for key in op.attrs_with_pipelineparams:
setattr(op, key, _process_obj(getattr(op, key), map_to_tmpl_var))
return op
def _parameters_to_json(params: List[dsl.PipelineParam]):
"""Converts a list of PipelineParam into an argo `parameter` JSON obj."""
_to_json = (lambda param: dict(name=param.full_name, value=param.value)
if param.value else dict(name=param.full_name))
params = [_to_json(param) for param in params]
# Sort to make the results deterministic.
params.sort(key=lambda x: x['name'])
return params
# TODO: artifacts?
def _inputs_to_json(inputs_params: List[dsl.PipelineParam], _artifacts=None):
"""Converts a list of PipelineParam into an argo `inputs` JSON obj."""
parameters = _parameters_to_json(inputs_params)
return {'parameters': parameters} if parameters else None
def _outputs_to_json(op: BaseOp,
outputs: Dict[str, dsl.PipelineParam],
param_outputs: Dict[str, str],
output_artifacts: List[dict]):
"""Creates an argo `outputs` JSON obj."""
if isinstance(op, dsl.ResourceOp):
value_from_key = "jsonPath"
else:
value_from_key = "path"
output_parameters = []
for param in outputs.values():
output_parameters.append({
'name': param.full_name,
'valueFrom': {
value_from_key: param_outputs[param.name]
}
})
output_parameters.sort(key=lambda x: x['name'])
ret = {}
if output_parameters:
ret['parameters'] = output_parameters
if output_artifacts:
ret['artifacts'] = output_artifacts
return ret
# TODO: generate argo python classes from swagger and use convert_k8s_obj_to_json??
def _op_to_template(op: BaseOp):
"""Generate template given an operator inherited from BaseOp."""
# NOTE in-place update to BaseOp
# replace all PipelineParams with template var strings
processed_op = _process_base_ops(op)
if isinstance(op, dsl.ContainerOp):
# default output artifacts
output_artifact_paths = OrderedDict(op.output_artifact_paths)
output_artifact_paths.setdefault('mlpipeline-ui-metadata', '/mlpipeline-ui-metadata.json')
output_artifact_paths.setdefault('mlpipeline-metrics', '/mlpipeline-metrics.json')
output_artifacts = [
K8sHelper.convert_k8s_obj_to_json(
ArtifactLocation.create_artifact_for_s3(
op.artifact_location,
name=name,
path=path,
key='runs/{{workflow.uid}}/{{pod.name}}/' + name + '.tgz'))
for name, path in output_artifact_paths.items()
]
for output_artifact in output_artifacts:
if output_artifact['name'] in ['mlpipeline-ui-metadata', 'mlpipeline-metrics']:
output_artifact['optional'] = True
# workflow template
template = {
'name': processed_op.name,
'container': K8sHelper.convert_k8s_obj_to_json(
processed_op.container
)
}
elif isinstance(op, dsl.ResourceOp):
# no output artifacts
output_artifacts = []
# workflow template
processed_op.resource["manifest"] = yaml.dump(
K8sHelper.convert_k8s_obj_to_json(processed_op.k8s_resource),
default_flow_style=False
)
template = {
'name': processed_op.name,
'resource': K8sHelper.convert_k8s_obj_to_json(
processed_op.resource
)
}
# inputs
inputs = _inputs_to_json(processed_op.inputs)
if inputs:
template['inputs'] = inputs
# outputs
if isinstance(op, dsl.ContainerOp):
param_outputs = processed_op.file_outputs
elif isinstance(op, dsl.ResourceOp):
param_outputs = processed_op.attribute_outputs
template['outputs'] = _outputs_to_json(op, processed_op.outputs,
param_outputs, output_artifacts)
# node selector
if processed_op.node_selector:
template['nodeSelector'] = processed_op.node_selector
# tolerations
if processed_op.tolerations:
template['tolerations'] = processed_op.tolerations
# metadata
if processed_op.pod_annotations or processed_op.pod_labels:
template['metadata'] = {}
if processed_op.pod_annotations:
template['metadata']['annotations'] = processed_op.pod_annotations
if processed_op.pod_labels:
template['metadata']['labels'] = processed_op.pod_labels
# retries
if processed_op.num_retries:
template['retryStrategy'] = {'limit': processed_op.num_retries}
# timeout
if processed_op.timeout:
template['activeDeadlineSeconds'] = processed_op.timeout
# initContainers
if processed_op.init_containers:
template['initContainers'] = processed_op.init_containers
# sidecars
if processed_op.sidecars:
template['sidecars'] = processed_op.sidecars
# Display name
if processed_op.display_name:
template.setdefault('metadata', {}).setdefault('annotations', {})['pipelines.kubeflow.org/task_display_name'] = processed_op.display_name
return template