905 lines
37 KiB
Python
905 lines
37 KiB
Python
# Copyright 2018-2019 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import json
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from collections import defaultdict
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from deprecated import deprecated
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import inspect
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import tarfile
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import zipfile
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from typing import Callable, Set, List, Text, Dict, Tuple, Any, Union, Optional
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import yaml
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from kfp.dsl import _for_loop
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from .. import dsl
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from ._k8s_helper import K8sHelper
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from ._op_to_template import _op_to_template
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from ._default_transformers import add_pod_env
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from ..components._structures import InputSpec
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from ..dsl._metadata import _extract_pipeline_metadata
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from ..dsl._ops_group import OpsGroup
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class Compiler(object):
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"""DSL Compiler.
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It compiles DSL pipeline functions into workflow yaml. Example usage:
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```python
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@dsl.pipeline(
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name='name',
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description='description'
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)
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def my_pipeline(a: int = 1, b: str = "default value"):
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...
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Compiler().compile(my_pipeline, 'path/to/workflow.yaml')
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```
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"""
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def _pipelineparam_full_name(self, param):
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"""_pipelineparam_full_name converts the names of pipeline parameters
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to unique names in the argo yaml
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Args:
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param(PipelineParam): pipeline parameter
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"""
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if param.op_name:
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return param.op_name + '-' + param.name
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return param.name
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def _get_groups_for_ops(self, root_group):
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"""Helper function to get belonging groups for each op.
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Each pipeline has a root group. Each group has a list of operators (leaf) and groups.
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This function traverse the tree and get all ancestor groups for all operators.
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Returns:
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A dict. Key is the operator's name. Value is a list of ancestor groups including the
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op itself. The list of a given operator is sorted in a way that the farthest
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group is the first and operator itself is the last.
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"""
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def _get_op_groups_helper(current_groups, ops_to_groups):
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root_group = current_groups[-1]
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for g in root_group.groups:
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# Add recursive opsgroup in the ops_to_groups
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# such that the i/o dependency can be propagated to the ancester opsgroups
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if g.recursive_ref:
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ops_to_groups[g.name] = [x.name for x in current_groups] + [g.name]
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continue
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current_groups.append(g)
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_get_op_groups_helper(current_groups, ops_to_groups)
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del current_groups[-1]
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for op in root_group.ops:
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ops_to_groups[op.name] = [x.name for x in current_groups] + [op.name]
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ops_to_groups = {}
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current_groups = [root_group]
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_get_op_groups_helper(current_groups, ops_to_groups)
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return ops_to_groups
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#TODO: combine with the _get_groups_for_ops
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def _get_groups_for_opsgroups(self, root_group):
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"""Helper function to get belonging groups for each opsgroup.
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Each pipeline has a root group. Each group has a list of operators (leaf) and groups.
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This function traverse the tree and get all ancestor groups for all opsgroups.
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Returns:
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A dict. Key is the opsgroup's name. Value is a list of ancestor groups including the
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opsgroup itself. The list of a given opsgroup is sorted in a way that the farthest
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group is the first and opsgroup itself is the last.
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"""
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def _get_opsgroup_groups_helper(current_groups, opsgroups_to_groups):
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root_group = current_groups[-1]
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for g in root_group.groups:
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# Add recursive opsgroup in the ops_to_groups
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# such that the i/o dependency can be propagated to the ancester opsgroups
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if g.recursive_ref:
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continue
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opsgroups_to_groups[g.name] = [x.name for x in current_groups] + [g.name]
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current_groups.append(g)
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_get_opsgroup_groups_helper(current_groups, opsgroups_to_groups)
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del current_groups[-1]
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opsgroups_to_groups = {}
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current_groups = [root_group]
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_get_opsgroup_groups_helper(current_groups, opsgroups_to_groups)
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return opsgroups_to_groups
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def _get_groups(self, root_group):
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"""Helper function to get all groups (not including ops) in a pipeline."""
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def _get_groups_helper(group):
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groups = {group.name: group}
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for g in group.groups:
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# Skip the recursive opsgroup because no templates
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# need to be generated for the recursive opsgroups.
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if not g.recursive_ref:
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groups.update(_get_groups_helper(g))
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return groups
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return _get_groups_helper(root_group)
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def _get_uncommon_ancestors(self, op_groups, opsgroup_groups, op1, op2):
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"""Helper function to get unique ancestors between two ops.
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For example, op1's ancestor groups are [root, G1, G2, G3, op1], op2's ancestor groups are
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[root, G1, G4, op2], then it returns a tuple ([G2, G3, op1], [G4, op2]).
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"""
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#TODO: extract a function for the following two code module
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if op1.name in op_groups:
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op1_groups = op_groups[op1.name]
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elif op1.name in opsgroup_groups:
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op1_groups = opsgroup_groups[op1.name]
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else:
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raise ValueError(op1.name + ' does not exist.')
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if op2.name in op_groups:
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op2_groups = op_groups[op2.name]
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elif op2.name in opsgroup_groups:
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op2_groups = opsgroup_groups[op2.name]
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else:
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raise ValueError(op1.name + ' does not exist.')
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both_groups = [op1_groups, op2_groups]
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common_groups_len = sum(1 for x in zip(*both_groups) if x==(x[0],)*len(x))
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group1 = op1_groups[common_groups_len:]
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group2 = op2_groups[common_groups_len:]
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return (group1, group2)
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def _get_condition_params_for_ops(self, root_group):
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"""Get parameters referenced in conditions of ops."""
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conditions = defaultdict(set)
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def _get_condition_params_for_ops_helper(group, current_conditions_params):
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new_current_conditions_params = current_conditions_params
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if group.type == 'condition':
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new_current_conditions_params = list(current_conditions_params)
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if isinstance(group.condition.operand1, dsl.PipelineParam):
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new_current_conditions_params.append(group.condition.operand1)
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if isinstance(group.condition.operand2, dsl.PipelineParam):
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new_current_conditions_params.append(group.condition.operand2)
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for op in group.ops:
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for param in new_current_conditions_params:
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conditions[op.name].add(param)
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for g in group.groups:
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# If the subgroup is a recursive opsgroup, propagate the pipelineparams
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# in the condition expression, similar to the ops.
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if g.recursive_ref:
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for param in new_current_conditions_params:
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conditions[g.name].add(param)
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else:
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_get_condition_params_for_ops_helper(g, new_current_conditions_params)
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_get_condition_params_for_ops_helper(root_group, [])
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return conditions
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def _get_next_group_or_op(cls, to_visit: List, already_visited: Set):
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"""Get next group or op to visit."""
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if len(to_visit) == 0:
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return None
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next = to_visit.pop(0)
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while next in already_visited:
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next = to_visit.pop(0)
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already_visited.add(next)
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return next
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def _get_for_loop_ops(self, new_root) -> Dict[Text, dsl.ParallelFor]:
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to_visit = self._get_all_subgroups_and_ops(new_root)
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op_name_to_op = {}
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already_visited = set()
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while len(to_visit):
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next_op = self._get_next_group_or_op(to_visit, already_visited)
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if next_op is None:
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break
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to_visit.extend(self._get_all_subgroups_and_ops(next_op))
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if isinstance(next_op, dsl.ParallelFor):
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op_name_to_op[next_op.name] = next_op
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return op_name_to_op
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def _get_all_subgroups_and_ops(self, op):
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"""Get all ops and groups contained within this group."""
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subgroups = []
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if hasattr(op, 'ops'):
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subgroups.extend(op.ops)
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if hasattr(op, 'groups'):
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subgroups.extend(op.groups)
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return subgroups
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def _get_inputs_outputs(
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self,
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pipeline,
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root_group,
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op_groups,
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opsgroup_groups,
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condition_params,
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op_name_to_for_loop_op: Dict[Text, dsl.ParallelFor],
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):
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"""Get inputs and outputs of each group and op.
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Returns:
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A tuple (inputs, outputs).
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inputs and outputs are dicts with key being the group/op names and values being list of
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tuples (param_name, producing_op_name). producing_op_name is the name of the op that
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produces the param. If the param is a pipeline param (no producer op), then
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producing_op_name is None.
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"""
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inputs = defaultdict(set)
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outputs = defaultdict(set)
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for op in pipeline.ops.values():
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# op's inputs and all params used in conditions for that op are both considered.
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for param in op.inputs + list(condition_params[op.name]):
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# if the value is already provided (immediate value), then no need to expose
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# it as input for its parent groups.
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if param.value:
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continue
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if param.op_name:
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upstream_op = pipeline.ops[param.op_name]
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upstream_groups, downstream_groups = \
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self._get_uncommon_ancestors(op_groups, opsgroup_groups, upstream_op, op)
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for i, group_name in enumerate(downstream_groups):
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if i == 0:
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# If it is the first uncommon downstream group, then the input comes from
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# the first uncommon upstream group.
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inputs[group_name].add((param.full_name, upstream_groups[0]))
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else:
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# If not the first downstream group, then the input is passed down from
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# its ancestor groups so the upstream group is None.
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inputs[group_name].add((param.full_name, None))
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for i, group_name in enumerate(upstream_groups):
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if i == len(upstream_groups) - 1:
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# If last upstream group, it is an operator and output comes from container.
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outputs[group_name].add((param.full_name, None))
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else:
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# If not last upstream group, output value comes from one of its child.
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outputs[group_name].add((param.full_name, upstream_groups[i+1]))
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else:
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if not op.is_exit_handler:
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for group_name in op_groups[op.name][::-1]:
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# if group is for loop group and param is that loop's param, then the param
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# is created by that for loop ops_group and it shouldn't be an input to
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# any of its parent groups.
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inputs[group_name].add((param.full_name, None))
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if group_name in op_name_to_for_loop_op:
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# for example:
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# loop_group.loop_args.name = 'loop-item-param-99ca152e'
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# param.name = 'loop-item-param-99ca152e--a'
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loop_group = op_name_to_for_loop_op[group_name]
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if loop_group.loop_args.name in param.name:
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break
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# Generate the input/output for recursive opsgroups
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# It propagates the recursive opsgroups IO to their ancester opsgroups
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def _get_inputs_outputs_recursive_opsgroup(group):
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#TODO: refactor the following codes with the above
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if group.recursive_ref:
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params = [(param, False) for param in group.inputs]
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params.extend([(param, True) for param in list(condition_params[group.name])])
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for param, is_condition_param in params:
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if param.value:
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continue
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full_name = self._pipelineparam_full_name(param)
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if param.op_name:
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upstream_op = pipeline.ops[param.op_name]
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upstream_groups, downstream_groups = \
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self._get_uncommon_ancestors(op_groups, opsgroup_groups, upstream_op, group)
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for i, g in enumerate(downstream_groups):
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if i == 0:
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inputs[g].add((full_name, upstream_groups[0]))
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# There is no need to pass the condition param as argument to the downstream ops.
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#TODO: this might also apply to ops. add a TODO here and think about it.
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elif i == len(downstream_groups) - 1 and is_condition_param:
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continue
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else:
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inputs[g].add((full_name, None))
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for i, g in enumerate(upstream_groups):
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if i == len(upstream_groups) - 1:
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outputs[g].add((full_name, None))
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else:
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outputs[g].add((full_name, upstream_groups[i+1]))
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elif not is_condition_param:
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for g in op_groups[group.name]:
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inputs[g].add((full_name, None))
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for subgroup in group.groups:
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_get_inputs_outputs_recursive_opsgroup(subgroup)
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_get_inputs_outputs_recursive_opsgroup(root_group)
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return inputs, outputs
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def _get_dependencies(self, pipeline, root_group, op_groups, opsgroups_groups, opsgroups, condition_params):
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"""Get dependent groups and ops for all ops and groups.
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Returns:
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A dict. Key is group/op name, value is a list of dependent groups/ops.
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The dependencies are calculated in the following way: if op2 depends on op1,
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and their ancestors are [root, G1, G2, op1] and [root, G1, G3, G4, op2],
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then G3 is dependent on G2. Basically dependency only exists in the first uncommon
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ancesters in their ancesters chain. Only sibling groups/ops can have dependencies.
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"""
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dependencies = defaultdict(set)
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for op in pipeline.ops.values():
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upstream_op_names = set()
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for param in op.inputs + list(condition_params[op.name]):
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if param.op_name:
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upstream_op_names.add(param.op_name)
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upstream_op_names |= set(op.dependent_names)
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for upstream_op_name in upstream_op_names:
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# the dependent op could be either a BaseOp or an opsgroup
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if upstream_op_name in pipeline.ops:
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upstream_op = pipeline.ops[upstream_op_name]
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elif upstream_op_name in opsgroups:
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upstream_op = opsgroups[upstream_op_name]
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else:
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raise ValueError('compiler cannot find the ' + upstream_op_name)
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upstream_groups, downstream_groups = self._get_uncommon_ancestors(op_groups, opsgroups_groups, upstream_op, op)
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dependencies[downstream_groups[0]].add(upstream_groups[0])
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# Generate dependencies based on the recursive opsgroups
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#TODO: refactor the following codes with the above
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def _get_dependency_opsgroup(group, dependencies):
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upstream_op_names = set([dependency.name for dependency in group.dependencies])
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if group.recursive_ref:
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for param in group.inputs + list(condition_params[group.name]):
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if param.op_name:
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upstream_op_names.add(param.op_name)
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for op_name in upstream_op_names:
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if op_name in pipeline.ops:
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upstream_op = pipeline.ops[op_name]
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elif op_name in opsgroups_groups:
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upstream_op = opsgroups_groups[op_name]
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else:
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raise ValueError('compiler cannot find the ' + op_name)
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upstream_groups, downstream_groups = \
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self._get_uncommon_ancestors(op_groups, opsgroups_groups, upstream_op, group)
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dependencies[downstream_groups[0]].add(upstream_groups[0])
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for subgroup in group.groups:
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_get_dependency_opsgroup(subgroup, dependencies)
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_get_dependency_opsgroup(root_group, dependencies)
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return dependencies
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def _resolve_value_or_reference(self, value_or_reference, potential_references):
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"""_resolve_value_or_reference resolves values and PipelineParams, which could be task parameters or input parameters.
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Args:
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value_or_reference: value or reference to be resolved. It could be basic python types or PipelineParam
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potential_references(dict{str->str}): a dictionary of parameter names to task names
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"""
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if isinstance(value_or_reference, dsl.PipelineParam):
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parameter_name = self._pipelineparam_full_name(value_or_reference)
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task_names = [task_name for param_name, task_name in potential_references if param_name == parameter_name]
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if task_names:
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task_name = task_names[0]
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# When the task_name is None, the parameter comes directly from ancient ancesters
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# instead of parents. Thus, it is resolved as the input parameter in the current group.
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if task_name is None:
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return '{{inputs.parameters.%s}}' % parameter_name
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else:
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return '{{tasks.%s.outputs.parameters.%s}}' % (task_name, parameter_name)
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else:
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return '{{inputs.parameters.%s}}' % parameter_name
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else:
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return str(value_or_reference)
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def _group_to_dag_template(self, group, inputs, outputs, dependencies):
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"""Generate template given an OpsGroup.
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inputs, outputs, dependencies are all helper dicts.
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"""
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template = {'name': group.name}
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# Generate inputs section.
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if inputs.get(group.name, None):
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template_inputs = [{'name': x[0]} for x in inputs[group.name]]
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template_inputs.sort(key=lambda x: x['name'])
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template['inputs'] = {
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'parameters': template_inputs
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}
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# Generate outputs section.
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if outputs.get(group.name, None):
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template_outputs = []
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for param_name, dependent_name in outputs[group.name]:
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template_outputs.append({
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'name': param_name,
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'valueFrom': {
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'parameter': '{{tasks.%s.outputs.parameters.%s}}' % (dependent_name, param_name)
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}
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})
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template_outputs.sort(key=lambda x: x['name'])
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template['outputs'] = {'parameters': template_outputs}
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# Generate tasks section.
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tasks = []
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for sub_group in group.groups + group.ops:
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is_recursive_subgroup = (isinstance(sub_group, OpsGroup) and sub_group.recursive_ref)
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# Special handling for recursive subgroup: use the existing opsgroup name
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if is_recursive_subgroup:
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task = {
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'name': sub_group.recursive_ref.name,
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'template': sub_group.recursive_ref.name,
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}
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else:
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task = {
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'name': sub_group.name,
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'template': sub_group.name,
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}
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if isinstance(sub_group, dsl.OpsGroup) and sub_group.type == 'condition':
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subgroup_inputs = inputs.get(sub_group.name, [])
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condition = sub_group.condition
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operand1_value = self._resolve_value_or_reference(condition.operand1, subgroup_inputs)
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operand2_value = self._resolve_value_or_reference(condition.operand2, subgroup_inputs)
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if condition.operator in ['==', '!=']:
|
|
operand1_value = '"' + operand1_value + '"'
|
|
operand2_value = '"' + operand2_value + '"'
|
|
task['when'] = '{} {} {}'.format(operand1_value, condition.operator, operand2_value)
|
|
|
|
# Generate dependencies section for this task.
|
|
if dependencies.get(sub_group.name, None):
|
|
group_dependencies = list(dependencies[sub_group.name])
|
|
group_dependencies.sort()
|
|
task['dependencies'] = group_dependencies
|
|
|
|
# Generate arguments section for this task.
|
|
if inputs.get(sub_group.name, None):
|
|
task['arguments'] = {'parameters': self.get_arguments_for_sub_group(sub_group, is_recursive_subgroup, inputs)}
|
|
|
|
# additional task modifications for withItems and withParam
|
|
if isinstance(sub_group, dsl.ParallelFor):
|
|
if sub_group.items_is_pipeline_param:
|
|
# these loop args are a 'withParam' rather than 'withItems'.
|
|
# i.e., rather than a static list, they are either the output of another task or were input
|
|
# as global pipeline parameters
|
|
|
|
pipeline_param = sub_group.loop_args
|
|
if pipeline_param.op_name is None:
|
|
withparam_value = '{{workflow.parameters.%s}}' % pipeline_param.name
|
|
else:
|
|
param_name = '%s-%s' % (pipeline_param.op_name, pipeline_param.name)
|
|
withparam_value = '{{tasks.%s.outputs.parameters.%s}}' % (pipeline_param.op_name, param_name)
|
|
|
|
# these loop args are the output of another task
|
|
if 'dependencies' not in task or task['dependencies'] is None:
|
|
task['dependencies'] = []
|
|
if pipeline_param.op_name not in task['dependencies']:
|
|
task['dependencies'].append(pipeline_param.op_name)
|
|
|
|
task['withParam'] = withparam_value
|
|
else:
|
|
task['withItems'] = sub_group.loop_args.to_list_for_task_yaml()
|
|
|
|
tasks.append(task)
|
|
tasks.sort(key=lambda x: x['name'])
|
|
template['dag'] = {'tasks': tasks}
|
|
return template
|
|
|
|
def get_arguments_for_sub_group(
|
|
self,
|
|
sub_group: Union[OpsGroup, dsl._container_op.BaseOp],
|
|
is_recursive_subgroup: Optional[bool],
|
|
inputs: Dict[Text, Tuple[Text, Text]],
|
|
):
|
|
arguments = []
|
|
for param_name, dependent_name in inputs[sub_group.name]:
|
|
if is_recursive_subgroup:
|
|
for index, input in enumerate(sub_group.inputs):
|
|
if param_name == self._pipelineparam_full_name(input):
|
|
break
|
|
referenced_input = sub_group.recursive_ref.inputs[index]
|
|
argument_name = self._pipelineparam_full_name(referenced_input)
|
|
else:
|
|
argument_name = param_name
|
|
|
|
# default argument_value + special cases
|
|
argument_value = '{{inputs.parameters.%s}}' % param_name
|
|
if isinstance(sub_group, dsl.ParallelFor):
|
|
if sub_group.loop_args.name in param_name:
|
|
if _for_loop.LoopArgumentVariable.name_is_loop_arguments_variable(param_name):
|
|
subvar_name = _for_loop.LoopArgumentVariable.get_subvar_name(param_name)
|
|
argument_value = '{{item.%s}}' % subvar_name
|
|
elif _for_loop.LoopArguments.name_is_loop_arguments(param_name) or sub_group.items_is_pipeline_param:
|
|
argument_value = '{{item}}'
|
|
else:
|
|
raise ValueError("Failed to match loop args with parameter. param_name: {}, ".format(param_name))
|
|
elif dependent_name:
|
|
argument_value = '{{tasks.%s.outputs.parameters.%s}}' % (dependent_name, param_name)
|
|
|
|
arguments.append({
|
|
'name': argument_name,
|
|
'value': argument_value,
|
|
})
|
|
|
|
arguments.sort(key=lambda x: x['name'])
|
|
|
|
return arguments
|
|
|
|
def _create_dag_templates(self, pipeline, op_transformers=None, op_to_templates_handler=None):
|
|
"""Create all groups and ops templates in the pipeline.
|
|
|
|
Args:
|
|
pipeline: Pipeline context object to get all the pipeline data from.
|
|
op_transformers: A list of functions that are applied to all ContainerOp instances that are being processed.
|
|
op_to_templates_handler: Handler which converts a base op into a list of argo templates.
|
|
"""
|
|
op_to_templates_handler = op_to_templates_handler or (lambda op : [_op_to_template(op)])
|
|
root_group = pipeline.groups[0]
|
|
|
|
# Call the transformation functions before determining the inputs/outputs, otherwise
|
|
# the user would not be able to use pipeline parameters in the container definition
|
|
# (for example as pod labels) - the generated template is invalid.
|
|
for op in pipeline.ops.values():
|
|
for transformer in op_transformers or []:
|
|
transformer(op)
|
|
|
|
# Generate core data structures to prepare for argo yaml generation
|
|
# op_name_to_parent_groups: op name -> list of ancestor groups including the current op
|
|
# opsgroups: a dictionary of ospgroup.name -> opsgroup
|
|
# inputs, outputs: group/op names -> list of tuples (full_param_name, producing_op_name)
|
|
# condition_params: recursive_group/op names -> list of pipelineparam
|
|
# dependencies: group/op name -> list of dependent groups/ops.
|
|
# Special Handling for the recursive opsgroup
|
|
# op_name_to_parent_groups also contains the recursive opsgroups
|
|
# condition_params from _get_condition_params_for_ops also contains the recursive opsgroups
|
|
# groups does not include the recursive opsgroups
|
|
opsgroups = self._get_groups(root_group)
|
|
op_name_to_parent_groups = self._get_groups_for_ops(root_group)
|
|
opgroup_name_to_parent_groups = self._get_groups_for_opsgroups(root_group)
|
|
condition_params = self._get_condition_params_for_ops(root_group)
|
|
op_name_to_for_loop_op = self._get_for_loop_ops(root_group)
|
|
inputs, outputs = self._get_inputs_outputs(
|
|
pipeline,
|
|
root_group,
|
|
op_name_to_parent_groups,
|
|
opgroup_name_to_parent_groups,
|
|
condition_params,
|
|
op_name_to_for_loop_op,
|
|
)
|
|
dependencies = self._get_dependencies(
|
|
pipeline,
|
|
root_group,
|
|
op_name_to_parent_groups,
|
|
opgroup_name_to_parent_groups,
|
|
opsgroups,
|
|
condition_params,
|
|
)
|
|
|
|
templates = []
|
|
for opsgroup in opsgroups.keys():
|
|
template = self._group_to_dag_template(opsgroups[opsgroup], inputs, outputs, dependencies)
|
|
templates.append(template)
|
|
|
|
for op in pipeline.ops.values():
|
|
templates.extend(op_to_templates_handler(op))
|
|
|
|
return templates
|
|
|
|
def _create_volumes(self, pipeline):
|
|
"""Create volumes required for the templates"""
|
|
volumes = []
|
|
volume_name_set = set()
|
|
for op in pipeline.ops.values():
|
|
if op.volumes:
|
|
for v in op.volumes:
|
|
# Remove volume duplicates which have the same name
|
|
#TODO: check for duplicity based on the serialized volumes instead of just name.
|
|
if v['name'] not in volume_name_set:
|
|
volume_name_set.add(v['name'])
|
|
volumes.append(v)
|
|
volumes.sort(key=lambda x: x['name'])
|
|
return volumes
|
|
|
|
def _create_pipeline_workflow(self, args, pipeline, op_transformers=None, pipeline_conf=None):
|
|
"""Create workflow for the pipeline."""
|
|
|
|
# Input Parameters
|
|
input_params = []
|
|
for arg in args:
|
|
param = {'name': arg.name}
|
|
if arg.value is not None:
|
|
if isinstance(arg.value, (list, tuple)):
|
|
param['value'] = json.dumps(arg.value, sort_keys=True)
|
|
else:
|
|
param['value'] = str(arg.value)
|
|
input_params.append(param)
|
|
|
|
# Templates
|
|
templates = self._create_dag_templates(pipeline, op_transformers)
|
|
templates.sort(key=lambda x: x['name'])
|
|
|
|
# Exit Handler
|
|
exit_handler = None
|
|
if pipeline.groups[0].groups:
|
|
first_group = pipeline.groups[0].groups[0]
|
|
if first_group.type == 'exit_handler':
|
|
exit_handler = first_group.exit_op
|
|
|
|
# Volumes
|
|
volumes = self._create_volumes(pipeline)
|
|
|
|
# The whole pipeline workflow
|
|
pipeline_name = pipeline.name or 'Pipeline'
|
|
workflow = {
|
|
'apiVersion': 'argoproj.io/v1alpha1',
|
|
'kind': 'Workflow',
|
|
'metadata': {'generateName': pipeline_name + '-'},
|
|
'spec': {
|
|
'entrypoint': pipeline_name,
|
|
'templates': templates,
|
|
'arguments': {'parameters': input_params},
|
|
'serviceAccountName': 'pipeline-runner'
|
|
}
|
|
}
|
|
# set ttl after workflow finishes
|
|
if pipeline_conf.ttl_seconds_after_finished >= 0:
|
|
workflow['spec']['ttlSecondsAfterFinished'] = pipeline_conf.ttl_seconds_after_finished
|
|
|
|
if len(pipeline_conf.image_pull_secrets) > 0:
|
|
image_pull_secrets = []
|
|
for image_pull_secret in pipeline_conf.image_pull_secrets:
|
|
image_pull_secrets.append(K8sHelper.convert_k8s_obj_to_json(image_pull_secret))
|
|
workflow['spec']['imagePullSecrets'] = image_pull_secrets
|
|
|
|
if pipeline_conf.timeout:
|
|
workflow['spec']['activeDeadlineSeconds'] = pipeline_conf.timeout
|
|
|
|
if exit_handler:
|
|
workflow['spec']['onExit'] = exit_handler.name
|
|
if volumes:
|
|
workflow['spec']['volumes'] = volumes
|
|
return workflow
|
|
|
|
def _validate_exit_handler(self, pipeline):
|
|
"""Makes sure there is only one global exit handler.
|
|
|
|
Note this is a temporary workaround until argo supports local exit handler.
|
|
"""
|
|
|
|
def _validate_exit_handler_helper(group, exiting_op_names, handler_exists):
|
|
if group.type == 'exit_handler':
|
|
if handler_exists or len(exiting_op_names) > 1:
|
|
raise ValueError('Only one global exit_handler is allowed and all ops need to be included.')
|
|
handler_exists = True
|
|
|
|
if group.ops:
|
|
exiting_op_names.extend([x.name for x in group.ops])
|
|
|
|
for g in group.groups:
|
|
_validate_exit_handler_helper(g, exiting_op_names, handler_exists)
|
|
|
|
return _validate_exit_handler_helper(pipeline.groups[0], [], False)
|
|
|
|
def _sanitize_and_inject_artifact(self, pipeline: dsl.Pipeline, pipeline_conf=None):
|
|
"""Sanitize operator/param names and inject pipeline artifact location."""
|
|
|
|
# Sanitize operator names and param names
|
|
sanitized_ops = {}
|
|
# pipeline level artifact location
|
|
artifact_location = pipeline_conf.artifact_location
|
|
|
|
for op in pipeline.ops.values():
|
|
# inject pipeline level artifact location into if the op does not have
|
|
# an artifact location config already.
|
|
if hasattr(op, "artifact_location"):
|
|
if artifact_location and not op.artifact_location:
|
|
op.artifact_location = artifact_location
|
|
|
|
sanitized_name = K8sHelper.sanitize_k8s_name(op.name)
|
|
op.name = sanitized_name
|
|
for param in op.outputs.values():
|
|
param.name = K8sHelper.sanitize_k8s_name(param.name)
|
|
if param.op_name:
|
|
param.op_name = K8sHelper.sanitize_k8s_name(param.op_name)
|
|
if op.output is not None:
|
|
op.output.name = K8sHelper.sanitize_k8s_name(op.output.name)
|
|
op.output.op_name = K8sHelper.sanitize_k8s_name(op.output.op_name)
|
|
if op.dependent_names:
|
|
op.dependent_names = [K8sHelper.sanitize_k8s_name(name) for name in op.dependent_names]
|
|
if isinstance(op, dsl.ContainerOp) and op.file_outputs is not None:
|
|
sanitized_file_outputs = {}
|
|
for key in op.file_outputs.keys():
|
|
sanitized_file_outputs[K8sHelper.sanitize_k8s_name(key)] = op.file_outputs[key]
|
|
op.file_outputs = sanitized_file_outputs
|
|
elif isinstance(op, dsl.ResourceOp) and op.attribute_outputs is not None:
|
|
sanitized_attribute_outputs = {}
|
|
for key in op.attribute_outputs.keys():
|
|
sanitized_attribute_outputs[K8sHelper.sanitize_k8s_name(key)] = \
|
|
op.attribute_outputs[key]
|
|
op.attribute_outputs = sanitized_attribute_outputs
|
|
sanitized_ops[sanitized_name] = op
|
|
pipeline.ops = sanitized_ops
|
|
|
|
def _create_workflow(self,
|
|
pipeline_func: Callable,
|
|
pipeline_name: Text=None,
|
|
pipeline_description: Text=None,
|
|
params_list: List[dsl.PipelineParam]=None,
|
|
pipeline_conf: dsl.PipelineConf = None,
|
|
) -> Dict[Text, Any]:
|
|
""" Internal implementation of create_workflow."""
|
|
params_list = params_list or []
|
|
argspec = inspect.getfullargspec(pipeline_func)
|
|
|
|
# Create the arg list with no default values and call pipeline function.
|
|
# Assign type information to the PipelineParam
|
|
pipeline_meta = _extract_pipeline_metadata(pipeline_func)
|
|
pipeline_meta.name = pipeline_name or pipeline_meta.name
|
|
pipeline_meta.description = pipeline_description or pipeline_meta.description
|
|
pipeline_name = K8sHelper.sanitize_k8s_name(pipeline_meta.name)
|
|
|
|
# Need to first clear the default value of dsl.PipelineParams. Otherwise, it
|
|
# will be resolved immediately in place when being to each component.
|
|
default_param_values = {}
|
|
for param in params_list:
|
|
default_param_values[param.name] = param.value
|
|
param.value = None
|
|
|
|
# Currently only allow specifying pipeline params at one place.
|
|
if params_list and pipeline_meta.inputs:
|
|
raise ValueError('Either specify pipeline params in the pipeline function, or in "params_list", but not both.')
|
|
|
|
|
|
args_list = []
|
|
for arg_name in argspec.args:
|
|
arg_type = None
|
|
for input in pipeline_meta.inputs or []:
|
|
if arg_name == input.name:
|
|
arg_type = input.type
|
|
break
|
|
args_list.append(dsl.PipelineParam(K8sHelper.sanitize_k8s_name(arg_name), param_type=arg_type))
|
|
|
|
with dsl.Pipeline(pipeline_name) as dsl_pipeline:
|
|
pipeline_func(*args_list)
|
|
|
|
pipeline_conf = pipeline_conf or dsl_pipeline.conf # Configuration passed to the compiler is overriding. Unfortunately, it's not trivial to detect whether the dsl_pipeline.conf was ever modified.
|
|
|
|
self._validate_exit_handler(dsl_pipeline)
|
|
self._sanitize_and_inject_artifact(dsl_pipeline, pipeline_conf)
|
|
|
|
# Fill in the default values.
|
|
args_list_with_defaults = []
|
|
if pipeline_meta.inputs:
|
|
args_list_with_defaults = [dsl.PipelineParam(K8sHelper.sanitize_k8s_name(arg_name))
|
|
for arg_name in argspec.args]
|
|
if argspec.defaults:
|
|
for arg, default in zip(reversed(args_list_with_defaults), reversed(argspec.defaults)):
|
|
arg.value = default.value if isinstance(default, dsl.PipelineParam) else default
|
|
elif params_list:
|
|
# Or, if args are provided by params_list, fill in pipeline_meta.
|
|
for param in params_list:
|
|
param.value = default_param_values[param.name]
|
|
|
|
args_list_with_defaults = params_list
|
|
pipeline_meta.inputs = [
|
|
InputSpec(
|
|
name=param.name,
|
|
type=param.param_type,
|
|
default=param.value) for param in params_list]
|
|
|
|
op_transformers = [add_pod_env]
|
|
op_transformers.extend(pipeline_conf.op_transformers)
|
|
|
|
workflow = self._create_pipeline_workflow(
|
|
args_list_with_defaults,
|
|
dsl_pipeline,
|
|
op_transformers,
|
|
pipeline_conf,
|
|
)
|
|
|
|
from ._data_passing_rewriter import fix_big_data_passing
|
|
workflow = fix_big_data_passing(workflow)
|
|
|
|
import json
|
|
workflow.setdefault('metadata', {}).setdefault('annotations', {})['pipelines.kubeflow.org/pipeline_spec'] = json.dumps(pipeline_meta.to_dict(), sort_keys=True)
|
|
|
|
return workflow
|
|
|
|
@deprecated(
|
|
version='0.1.32',
|
|
reason='Workflow spec is not intended to be handled by user, please '
|
|
'switch to _create_workflow')
|
|
def create_workflow(self,
|
|
pipeline_func: Callable,
|
|
pipeline_name: Text=None,
|
|
pipeline_description: Text=None,
|
|
params_list: List[dsl.PipelineParam]=None,
|
|
pipeline_conf: dsl.PipelineConf = None) -> Dict[Text, Any]:
|
|
""" Create workflow spec from pipeline function and specified pipeline
|
|
params/metadata. Currently, the pipeline params are either specified in
|
|
the signature of the pipeline function or by passing a list of
|
|
dsl.PipelineParam. Conflict will cause ValueError.
|
|
|
|
:param pipeline_func: pipeline function where ContainerOps are invoked.
|
|
:param pipeline_name:
|
|
:param pipeline_description:
|
|
:param params_list: list of pipeline params to append to the pipeline.
|
|
:param pipeline_conf: PipelineConf instance. Can specify op transforms, image pull secrets and other pipeline-level configuration options. Overrides any configuration that may be set by the pipeline.
|
|
:return: workflow dict.
|
|
"""
|
|
return self._create_workflow(pipeline_func, pipeline_name, pipeline_description, params_list, pipeline_conf)
|
|
|
|
def _compile(self, pipeline_func, pipeline_conf: dsl.PipelineConf = None):
|
|
"""Compile the given pipeline function into workflow."""
|
|
return self.create_workflow(pipeline_func=pipeline_func, pipeline_conf=pipeline_conf)
|
|
|
|
def compile(self, pipeline_func, package_path, type_check=True, pipeline_conf: dsl.PipelineConf = None):
|
|
"""Compile the given pipeline function into workflow yaml.
|
|
|
|
Args:
|
|
pipeline_func: pipeline functions with @dsl.pipeline decorator.
|
|
package_path: the output workflow tar.gz file path. for example, "~/a.tar.gz"
|
|
type_check: whether to enable the type check or not, default: False.
|
|
pipeline_conf: PipelineConf instance. Can specify op transforms, image pull secrets and other pipeline-level configuration options. Overrides any configuration that may be set by the pipeline.
|
|
"""
|
|
import kfp
|
|
type_check_old_value = kfp.TYPE_CHECK
|
|
try:
|
|
kfp.TYPE_CHECK = type_check
|
|
workflow = self._compile(pipeline_func, pipeline_conf)
|
|
self._write_workflow(workflow, package_path)
|
|
finally:
|
|
kfp.TYPE_CHECK = type_check_old_value
|
|
|
|
@staticmethod
|
|
def _write_workflow(workflow: Dict[Text, Any], package_path: Text = None):
|
|
"""Dump pipeline workflow into yaml spec and write out in the format specified by the user.
|
|
|
|
Args:
|
|
workflow: Workflow spec of the pipline, dict.
|
|
package_path: file path to be written. If not specified, a yaml_text string
|
|
will be returned.
|
|
"""
|
|
yaml.Dumper.ignore_aliases = lambda *args : True
|
|
yaml_text = yaml.dump(workflow, default_flow_style=False)
|
|
|
|
if '{{pipelineparam' in yaml_text:
|
|
raise RuntimeError(
|
|
'Internal compiler error: Found unresolved PipelineParam. '
|
|
'Please create a new issue at https://github.com/kubeflow/pipelines/issues '
|
|
'attaching the pipeline code and the pipeline package.' )
|
|
|
|
if package_path is None:
|
|
return yaml_text
|
|
|
|
if package_path.endswith('.tar.gz') or package_path.endswith('.tgz'):
|
|
from contextlib import closing
|
|
from io import BytesIO
|
|
with tarfile.open(package_path, "w:gz") as tar:
|
|
with closing(BytesIO(yaml_text.encode())) as yaml_file:
|
|
tarinfo = tarfile.TarInfo('pipeline.yaml')
|
|
tarinfo.size = len(yaml_file.getvalue())
|
|
tar.addfile(tarinfo, fileobj=yaml_file)
|
|
elif package_path.endswith('.zip'):
|
|
with zipfile.ZipFile(package_path, "w") as zip:
|
|
zipinfo = zipfile.ZipInfo('pipeline.yaml')
|
|
zipinfo.compress_type = zipfile.ZIP_DEFLATED
|
|
zip.writestr(zipinfo, yaml_text)
|
|
elif package_path.endswith('.yaml') or package_path.endswith('.yml'):
|
|
with open(package_path, 'w') as yaml_file:
|
|
yaml_file.write(yaml_text)
|
|
else:
|
|
raise ValueError(
|
|
'The output path '+ package_path +
|
|
' should ends with one of the following formats: '
|
|
'[.tar.gz, .tgz, .zip, .yaml, .yml]')
|