mirror of
https://github.com/ARM-software/workload-automation.git
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261417a9db
When an agenda contains multiple sections, the same workload entry might be used in construction of multiple job specs. Job spec construction may mangle the workload entry. To prevent this from impacting other jobs, use a deep copy of the workload entry when constructing a job spec.
1083 lines
40 KiB
Python
1083 lines
40 KiB
Python
# Copyright 2014-2016 ARM Limited
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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 os
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import re
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from copy import copy, deepcopy
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from collections import OrderedDict, defaultdict
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from wa.framework.exception import ConfigError, NotFoundError
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from wa.framework.configuration.tree import SectionNode
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from wa.utils.misc import (get_article, merge_config_values)
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from wa.utils.types import (identifier, integer, boolean, list_of_strings,
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list_of, toggle_set, obj_dict, enum)
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from wa.utils.serializer import is_pod
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# Mapping for kind conversion; see docs for convert_types below
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KIND_MAP = {
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int: integer,
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bool: boolean,
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dict: OrderedDict,
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}
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Status = enum(['UNKNOWN', 'NEW', 'PENDING',
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'STARTED', 'CONNECTED', 'INITIALIZED', 'RUNNING',
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'OK', 'PARTIAL', 'FAILED', 'ABORTED', 'SKIPPED'])
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##########################
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### CONFIG POINT TYPES ###
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##########################
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class RebootPolicy(object):
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"""
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Represents the reboot policy for the execution -- at what points the device
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should be rebooted. This, in turn, is controlled by the policy value that is
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passed in on construction and would typically be read from the user's settings.
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Valid policy values are:
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:never: The device will never be rebooted.
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:as_needed: Only reboot the device if it becomes unresponsive, or needs to be flashed, etc.
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:initial: The device will be rebooted when the execution first starts, just before
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executing the first workload spec.
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:each_spec: The device will be rebooted before running a new workload spec.
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:each_iteration: The device will be rebooted before each new iteration.
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"""
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valid_policies = ['never', 'as_needed', 'initial', 'each_spec', 'each_iteration']
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def __init__(self, policy):
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policy = policy.strip().lower().replace(' ', '_')
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if policy not in self.valid_policies:
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message = 'Invalid reboot policy {}; must be one of {}'.format(policy, ', '.join(self.valid_policies))
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raise ConfigError(message)
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self.policy = policy
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@property
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def can_reboot(self):
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return self.policy != 'never'
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@property
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def perform_initial_boot(self):
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return self.policy not in ['never', 'as_needed']
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@property
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def reboot_on_each_spec(self):
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return self.policy in ['each_spec', 'each_iteration']
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@property
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def reboot_on_each_iteration(self):
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return self.policy == 'each_iteration'
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def __str__(self):
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return self.policy
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__repr__ = __str__
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def __cmp__(self, other):
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if isinstance(other, RebootPolicy):
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return cmp(self.policy, other.policy)
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else:
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return cmp(self.policy, other)
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def to_pod(self):
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return self.policy
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@staticmethod
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def from_pod(pod):
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return RebootPolicy(pod)
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class status_list(list):
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def append(self, item):
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list.append(self, str(item).upper())
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class LoggingConfig(dict):
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defaults = {
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'file_format': '%(asctime)s %(levelname)-8s %(name)s: %(message)s',
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'verbose_format': '%(asctime)s %(levelname)-8s %(name)s: %(message)s',
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'regular_format': '%(levelname)-8s %(message)s',
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'color': True,
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}
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def __init__(self, config=None):
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dict.__init__(self)
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if isinstance(config, dict):
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config = {identifier(k.lower()): v for k, v in config.iteritems()}
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self['regular_format'] = config.pop('regular_format', self.defaults['regular_format'])
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self['verbose_format'] = config.pop('verbose_format', self.defaults['verbose_format'])
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self['file_format'] = config.pop('file_format', self.defaults['file_format'])
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self['color'] = config.pop('colour_enabled', self.defaults['color']) # legacy
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self['color'] = config.pop('color', self.defaults['color'])
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if config:
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message = 'Unexpected logging configuration parameters: {}'
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raise ValueError(message.format(bad_vals=', '.join(config.keys())))
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elif config is None:
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for k, v in self.defaults.iteritems():
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self[k] = v
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else:
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raise ValueError(config)
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def get_type_name(kind):
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typename = str(kind)
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if '\'' in typename:
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typename = typename.split('\'')[1]
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elif typename.startswith('<function'):
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typename = typename.split()[1]
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return typename
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class ConfigurationPoint(object):
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"""
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This defines a generic configuration point for workload automation. This is
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used to handle global settings, plugin parameters, etc.
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"""
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def __init__(self, name,
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kind=None,
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mandatory=None,
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default=None,
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override=False,
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allowed_values=None,
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description=None,
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constraint=None,
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merge=False,
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aliases=None,
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global_alias=None):
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"""
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Create a new Parameter object.
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:param name: The name of the parameter. This will become an instance
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member of the plugin object to which the parameter is
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applied, so it must be a valid python identifier. This
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is the only mandatory parameter.
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:param kind: The type of parameter this is. This must be a callable
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that takes an arbitrary object and converts it to the
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expected type, or raised ``ValueError`` if such conversion
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is not possible. Most Python standard types -- ``str``,
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``int``, ``bool``, etc. -- can be used here. This
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defaults to ``str`` if not specified.
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:param mandatory: If set to ``True``, then a non-``None`` value for
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this parameter *must* be provided on plugin
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object construction, otherwise ``ConfigError``
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will be raised.
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:param default: The default value for this parameter. If no value
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is specified on plugin construction, this value
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will be used instead. (Note: if this is specified
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and is not ``None``, then ``mandatory`` parameter
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will be ignored).
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:param override: A ``bool`` that specifies whether a parameter of
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the same name further up the hierarchy should
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be overridden. If this is ``False`` (the
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default), an exception will be raised by the
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``AttributeCollection`` instead.
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:param allowed_values: This should be the complete list of allowed
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values for this parameter. Note: ``None``
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value will always be allowed, even if it is
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not in this list. If you want to disallow
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``None``, set ``mandatory`` to ``True``.
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:param constraint: If specified, this must be a callable that takes
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the parameter value as an argument and return a
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boolean indicating whether the constraint has been
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satisfied. Alternatively, can be a two-tuple with
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said callable as the first element and a string
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describing the constraint as the second.
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:param merge: The default behaviour when setting a value on an object
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that already has that attribute is to overrided with
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the new value. If this is set to ``True`` then the two
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values will be merged instead. The rules by which the
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values are merged will be determined by the types of
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the existing and new values -- see
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``merge_config_values`` documentation for details.
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:param aliases: Alternative names for the same configuration point.
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These are largely for backwards compatibility.
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:param global_alias: An alias for this parameter that can be specified at
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the global level. A global_alias can map onto many
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ConfigurationPoints.
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"""
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self.name = identifier(name)
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if kind in KIND_MAP:
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kind = KIND_MAP[kind]
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if kind is not None and not callable(kind):
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raise ValueError('Kind must be callable.')
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self.kind = kind
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self.mandatory = mandatory
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if not is_pod(default):
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msg = "The default for '{}' must be a Plain Old Data type, but it is of type '{}' instead."
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raise TypeError(msg.format(self.name, type(default)))
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self.default = default
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self.override = override
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self.allowed_values = allowed_values
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self.description = description
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if self.kind is None and not self.override:
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self.kind = str
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if constraint is not None and not callable(constraint) and not isinstance(constraint, tuple):
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raise ValueError('Constraint must be callable or a (callable, str) tuple.')
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self.constraint = constraint
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self.merge = merge
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self.aliases = aliases or []
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self.global_alias = global_alias
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if self.default is not None:
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try:
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self.validate_value("init", self.default)
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except ConfigError:
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raise ValueError('Default value "{}" is not valid'.format(self.default))
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def match(self, name):
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if name == self.name or name in self.aliases:
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return True
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elif name == self.global_alias:
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return True
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return False
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def set_value(self, obj, value=None, check_mandatory=True):
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if value is None:
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if self.default is not None:
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value = self.default
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elif check_mandatory and self.mandatory:
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msg = 'No values specified for mandatory parameter "{}" in {}'
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raise ConfigError(msg.format(self.name, obj.name))
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else:
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try:
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value = self.kind(value)
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except (ValueError, TypeError):
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typename = get_type_name(self.kind)
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msg = 'Bad value "{}" for {}; must be {} {}'
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article = get_article(typename)
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raise ConfigError(msg.format(value, self.name, article, typename))
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if value is not None:
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self.validate_value(self.name, value)
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if self.merge and hasattr(obj, self.name):
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value = merge_config_values(getattr(obj, self.name), value)
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setattr(obj, self.name, value)
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def validate(self, obj, check_mandatory=True):
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value = getattr(obj, self.name, None)
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if value is not None:
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self.validate_value(obj.name, value)
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else:
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if check_mandatory and self.mandatory:
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msg = 'No value specified for mandatory parameter "{}" in {}.'
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raise ConfigError(msg.format(self.name, obj.name))
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def validate_value(self, name, value):
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if self.allowed_values:
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self.validate_allowed_values(name, value)
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if self.constraint:
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self.validate_constraint(name, value)
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def validate_allowed_values(self, name, value):
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if 'list' in str(self.kind):
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for v in value:
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if v not in self.allowed_values:
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msg = 'Invalid value {} for {} in {}; must be in {}'
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raise ConfigError(msg.format(v, self.name, name, self.allowed_values))
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else:
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if value not in self.allowed_values:
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msg = 'Invalid value {} for {} in {}; must be in {}'
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raise ConfigError(msg.format(value, self.name, name, self.allowed_values))
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def validate_constraint(self, name, value):
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msg_vals = {'value': value, 'param': self.name, 'plugin': name}
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if isinstance(self.constraint, tuple) and len(self.constraint) == 2:
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constraint, msg = self.constraint # pylint: disable=unpacking-non-sequence
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elif callable(self.constraint):
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constraint = self.constraint
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msg = '"{value}" failed constraint validation for "{param}" in "{plugin}".'
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else:
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raise ValueError('Invalid constraint for "{}": must be callable or a 2-tuple'.format(self.name))
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if not constraint(value):
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raise ConfigError(value, msg.format(**msg_vals))
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def __repr__(self):
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d = copy(self.__dict__)
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del d['description']
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return 'ConfigurationPoint({})'.format(d)
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__str__ = __repr__
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class RuntimeParameter(object):
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def __init__(self, name,
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kind=None,
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description=None,
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merge=False):
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self.name = re.compile(name)
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if kind is not None:
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if kind in KIND_MAP:
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kind = KIND_MAP[kind]
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if not callable(kind):
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raise ValueError('Kind must be callable.')
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else:
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kind = str
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self.kind = kind
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self.description = description
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self.merge = merge
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def validate_kind(self, value, name):
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try:
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value = self.kind(value)
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except (ValueError, TypeError):
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typename = get_type_name(self.kind)
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msg = 'Bad value "{}" for {}; must be {} {}'
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article = get_article(typename)
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raise ConfigError(msg.format(value, name, article, typename))
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def match(self, name):
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if self.name.match(name):
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return True
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return False
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def update_value(self, name, new_value, source, dest):
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self.validate_kind(new_value, name)
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if name in dest:
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old_value, sources = dest[name]
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else:
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old_value = None
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sources = {}
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sources[source] = new_value
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if self.merge:
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new_value = merge_config_values(old_value, new_value)
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dest[name] = (new_value, sources)
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class RuntimeParameterManager(object):
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runtime_parameters = []
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def __init__(self, target_manager):
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self.state = {}
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self.target_manager = target_manager
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def get_initial_state(self):
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"""
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Should be used to load the starting state from the device. This state
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should be updated if any changes are made to the device, and they are successful.
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"""
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pass
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def match(self, name):
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for rtp in self.runtime_parameters:
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if rtp.match(name):
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return True
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return False
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def update_value(self, name, value, source, dest):
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for rtp in self.runtime_parameters:
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if rtp.match(name):
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rtp.update_value(name, value, source, dest)
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break
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else:
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msg = 'Unknown runtime parameter "{}"'
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raise ConfigError(msg.format(name))
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def static_validation(self, params):
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"""
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Validate values that do not require a active device connection.
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This method should also pop all runtime parameters meant for this manager
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from params, even if they are not being statically validated.
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"""
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pass
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def dynamic_validation(self, params):
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"""
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Validate values that require an active device connection
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"""
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pass
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def commit(self):
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"""
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All values have been validated, this will now actually set values
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"""
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pass
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################################
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### RuntimeParameterManagers ###
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################################
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class CpuFreqParameters(object):
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runtime_parameters = {
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"cores": RuntimeParameter("(.+)_cores"),
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"min_frequency": RuntimeParameter("(.+)_min_frequency", kind=int),
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"max_frequency": RuntimeParameter("(.+)_max_frequency", kind=int),
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"frequency": RuntimeParameter("(.+)_frequency", kind=int),
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"governor": RuntimeParameter("(.+)_governor"),
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"governor_tunables": RuntimeParameter("(.+)_governor_tunables"),
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}
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def __init__(self, target):
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super(CpuFreqParameters, self).__init__(target)
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self.core_names = set(target.core_names)
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def match(self, name):
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for param in self.runtime_parameters.itervalues():
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if param.match(name):
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return True
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return False
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def update_value(self, name, value, source):
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for param in self.runtime_parameters.iteritems():
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core_name_match = param.name.match(name)
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if not core_name_match:
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continue
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core_name = core_name_match.groups()[0]
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if core_name not in self.core_names:
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msg = '"{}" in {} is not a valid core name, must be in: {}'
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raise ConfigError(msg.format(core_name, name, ", ".join(self.core_names)))
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param.update_value(name, value, source)
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break
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else:
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RuntimeError('"{}" does not belong to CpuFreqParameters'.format(name))
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def _get_merged_value(self, core, param_name):
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return self.runtime_parameters[param_name].merged_values["{}_{}".format(core, param_name)]
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def _cross_validate(self, core):
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min_freq = self._get_merged_value(core, "min_frequency")
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max_frequency = self._get_merged_value(core, "max_frequency")
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if max_frequency < min_freq:
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msg = "{core}_max_frequency must be larger than {core}_min_frequency"
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raise ConfigError(msg.format(core=core))
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frequency = self._get_merged_value(core, "frequency")
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if not min_freq < frequency < max_frequency:
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msg = "{core}_frequency must be between {core}_min_frequency and {core}_max_frequency"
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raise ConfigError(msg.format(core=core))
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#TODO: more checks
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def commit_to_device(self, target):
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pass
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# TODO: Write values to device is correct order ect
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#####################
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### Configuration ###
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#####################
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def _to_pod(cfg_point, value):
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if is_pod(value):
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return value
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if hasattr(cfg_point.kind, 'to_pod'):
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return value.to_pod()
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msg = '{} value "{}" is not serializable'
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raise ValueError(msg.format(cfg_point.name, value))
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class Configuration(object):
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config_points = []
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name = ''
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# The below line must be added to all subclasses
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configuration = {cp.name: cp for cp in config_points}
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|
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@classmethod
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def from_pod(cls, pod):
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instance = cls()
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for cfg_point in cls.config_points:
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if name in pod:
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value = pod.pop(name)
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if hasattr(cfg_point.kind, 'from_pod'):
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value = cfg_point.kind.from_pod(value)
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cfg_point.set_value(instance, value)
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if pod:
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msg = 'Invalid entry(ies) for "{}": "{}"'
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raise ValueError(msg.format(cls.name, '", "'.join(pod.keys())))
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return instance
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|
|
def __init__(self):
|
|
for confpoint in self.config_points:
|
|
confpoint.set_value(self, check_mandatory=False)
|
|
|
|
def set(self, name, value, check_mandatory=True):
|
|
if name not in self.configuration:
|
|
raise ConfigError('Unknown {} configuration "{}"'.format(self.name,
|
|
name))
|
|
self.configuration[name].set_value(self, value,
|
|
check_mandatory=check_mandatory)
|
|
|
|
def update_config(self, values, check_mandatory=True):
|
|
for k, v in values.iteritems():
|
|
self.set(k, v, check_mandatory=check_mandatory)
|
|
|
|
def validate(self):
|
|
for cfg_point in self.config_points:
|
|
cfg_point.validate(self)
|
|
|
|
def to_pod(self):
|
|
pod = {}
|
|
for cfg_point in self.config_points:
|
|
value = getattr(self, cfg_point.name, None)
|
|
pod[cfg_point.name] = _to_pod(cfg_point, value)
|
|
return pod
|
|
|
|
|
|
# This configuration for the core WA framework
|
|
class MetaConfiguration(Configuration):
|
|
|
|
name = "Meta Configuration"
|
|
|
|
plugin_packages = [
|
|
'wa.commands',
|
|
'wa.framework.getters',
|
|
'wa.framework.target.descriptor',
|
|
'wa.instrumentation',
|
|
'wa.processors',
|
|
'wa.workloads',
|
|
]
|
|
|
|
config_points = [
|
|
ConfigurationPoint(
|
|
'user_directory',
|
|
description="""
|
|
Path to the user directory. This is the location WA will look for
|
|
user configuration, additional plugins and plugin dependencies.
|
|
""",
|
|
kind=str,
|
|
default=os.path.join(os.path.expanduser('~'), '.workload_automation'),
|
|
),
|
|
ConfigurationPoint(
|
|
'assets_repository',
|
|
description="""
|
|
The local mount point for the filer hosting WA assets.
|
|
""",
|
|
),
|
|
ConfigurationPoint(
|
|
'logging',
|
|
kind=LoggingConfig,
|
|
default=LoggingConfig.defaults,
|
|
description="""
|
|
WA logging configuration. This should be a dict with a subset
|
|
of the following keys::
|
|
|
|
:normal_format: Logging format used for console output
|
|
:verbose_format: Logging format used for verbose console output
|
|
:file_format: Logging format used for run.log
|
|
:color: If ``True`` (the default), console logging output will
|
|
contain bash color escape codes. Set this to ``False`` if
|
|
console output will be piped somewhere that does not know
|
|
how to handle those.
|
|
""",
|
|
),
|
|
ConfigurationPoint(
|
|
'verbosity',
|
|
kind=int,
|
|
default=0,
|
|
description="""
|
|
Verbosity of console output.
|
|
""",
|
|
),
|
|
ConfigurationPoint( # TODO: Needs some format for dates etc/ comes from cfg
|
|
'default_output_directory',
|
|
default="wa_output",
|
|
description="""
|
|
The default output directory that will be created if not
|
|
specified when invoking a run.
|
|
""",
|
|
),
|
|
]
|
|
configuration = {cp.name: cp for cp in config_points}
|
|
|
|
@property
|
|
def dependencies_directory(self):
|
|
return os.path.join(self.user_directory, 'dependencies')
|
|
|
|
@property
|
|
def plugins_directory(self):
|
|
return os.path.join(self.user_directory, 'plugins')
|
|
|
|
@property
|
|
def user_config_file(self):
|
|
return os.path.join(self.user_directory, 'config.yaml')
|
|
|
|
def __init__(self, environ):
|
|
super(MetaConfiguration, self).__init__()
|
|
user_directory = environ.pop('WA_USER_DIRECTORY', '')
|
|
if user_directory:
|
|
self.set('user_directory', user_directory)
|
|
|
|
|
|
# This is generic top-level configuration for WA runs.
|
|
class RunConfiguration(Configuration):
|
|
|
|
name = "Run Configuration"
|
|
|
|
# Metadata is separated out because it is not loaded into the auto
|
|
# generated config file
|
|
meta_data = [
|
|
ConfigurationPoint(
|
|
'run_name',
|
|
kind=str,
|
|
description='''
|
|
A string that labels the WA run that is being performed. This would
|
|
typically be set in the ``config`` section of an agenda (see
|
|
:ref:`configuration in an agenda <configuration_in_agenda>`) rather
|
|
than in the config file.
|
|
''',
|
|
),
|
|
ConfigurationPoint(
|
|
'project',
|
|
kind=str,
|
|
description='''
|
|
A string naming the project for which data is being collected. This
|
|
may be useful, e.g. when uploading data to a shared database that
|
|
is populated from multiple projects.
|
|
''',
|
|
),
|
|
ConfigurationPoint(
|
|
'project_stage',
|
|
kind=dict,
|
|
description='''
|
|
A dict or a string that allows adding additional identifier. This
|
|
is may be useful for long-running projects.
|
|
''',
|
|
),
|
|
]
|
|
config_points = [
|
|
ConfigurationPoint(
|
|
'execution_order',
|
|
kind=str,
|
|
default='by_iteration',
|
|
allowed_values=['by_iteration', 'by_spec', 'by_section', 'random'],
|
|
description='''
|
|
Defines the order in which the agenda spec will be executed. At the
|
|
moment, the following execution orders are supported:
|
|
|
|
``"by_iteration"``
|
|
The first iteration of each workload spec is executed one after
|
|
the other, so all workloads are executed before proceeding on
|
|
to the second iteration. E.g. A1 B1 C1 A2 C2 A3. This is the
|
|
default if no order is explicitly specified.
|
|
|
|
In case of multiple sections, this will spread them out, such
|
|
that specs from the same section are further part. E.g. given
|
|
sections X and Y, global specs A and B, and two iterations,
|
|
this will run ::
|
|
|
|
X.A1, Y.A1, X.B1, Y.B1, X.A2, Y.A2, X.B2, Y.B2
|
|
|
|
``"by_section"``
|
|
Same as ``"by_iteration"``, however this will group specs from
|
|
the same section together, so given sections X and Y, global
|
|
specs A and B, and two iterations, this will run ::
|
|
|
|
X.A1, X.B1, Y.A1, Y.B1, X.A2, X.B2, Y.A2, Y.B2
|
|
|
|
``"by_spec"``
|
|
All iterations of the first spec are executed before moving on
|
|
to the next spec. E.g. A1 A2 A3 B1 C1 C2 This may also be
|
|
specified as ``"classic"``, as this was the way workloads were
|
|
executed in earlier versions of WA.
|
|
|
|
``"random"``
|
|
Execution order is entirely random.
|
|
''',
|
|
),
|
|
ConfigurationPoint(
|
|
'reboot_policy',
|
|
kind=RebootPolicy,
|
|
default='as_needed',
|
|
allowed_values=RebootPolicy.valid_policies,
|
|
description='''
|
|
This defines when during execution of a run the Device will be
|
|
rebooted. The possible values are:
|
|
|
|
``"never"``
|
|
The device will never be rebooted.
|
|
|
|
``"initial"``
|
|
The device will be rebooted when the execution first starts,
|
|
just before executing the first workload spec.
|
|
|
|
``"each_spec"``
|
|
The device will be rebooted before running a new workload spec.
|
|
|
|
.. note:: this acts the same as each_iteration when execution order
|
|
is set to by_iteration
|
|
|
|
``"each_iteration"``
|
|
The device will be rebooted before each new iteration.
|
|
'''),
|
|
ConfigurationPoint(
|
|
'device',
|
|
kind=str,
|
|
mandatory=True,
|
|
description='''
|
|
This setting defines what specific Device subclass will be used to
|
|
interact the connected device. Obviously, this must match your
|
|
setup.
|
|
''',
|
|
),
|
|
ConfigurationPoint(
|
|
'retry_on_status',
|
|
kind=list_of(Status),
|
|
default=['FAILED', 'PARTIAL'],
|
|
allowed_values=Status.levels[Status.RUNNING.value:],
|
|
description='''
|
|
This is list of statuses on which a job will be considered to have
|
|
failed and will be automatically retried up to ``max_retries``
|
|
times. This defaults to ``["FAILED", "PARTIAL"]`` if not set.
|
|
Possible values are::
|
|
|
|
``"OK"``
|
|
This iteration has completed and no errors have been detected
|
|
|
|
``"PARTIAL"``
|
|
One or more instruments have failed (the iteration may still be running).
|
|
|
|
``"FAILED"``
|
|
The workload itself has failed.
|
|
|
|
``"ABORTED"``
|
|
The user interrupted the workload
|
|
''',
|
|
),
|
|
ConfigurationPoint(
|
|
'max_retries',
|
|
kind=int,
|
|
default=2,
|
|
description='''
|
|
The maximum number of times failed jobs will be retried before
|
|
giving up. If not set.
|
|
|
|
.. note:: this number does not include the original attempt
|
|
''',
|
|
),
|
|
ConfigurationPoint(
|
|
'result_processors',
|
|
kind=toggle_set,
|
|
default=['csv', 'status'],
|
|
description='''
|
|
The list of output processors to be used for this run. Output processors
|
|
post-process data generated by workloads and instruments, e.g. to
|
|
generate additional reports, format the output in a certain way, or
|
|
export the output to an exeternal location.
|
|
''',
|
|
),
|
|
]
|
|
configuration = {cp.name: cp for cp in config_points + meta_data}
|
|
|
|
def __init__(self):
|
|
super(RunConfiguration, self).__init__()
|
|
for confpoint in self.meta_data:
|
|
confpoint.set_value(self, check_mandatory=False)
|
|
self.device_config = None
|
|
|
|
def merge_device_config(self, plugin_cache):
|
|
"""
|
|
Merges global device config and validates that it is correct for the
|
|
selected device.
|
|
"""
|
|
# pylint: disable=no-member
|
|
if self.device is None:
|
|
msg = 'Attempting to merge device config with unspecified device'
|
|
raise RuntimeError(msg)
|
|
self.device_config = plugin_cache.get_plugin_config(self.device,
|
|
generic_name="device_config")
|
|
|
|
def to_pod(self):
|
|
pod = super(RunConfiguration, self).to_pod()
|
|
pod['device_config'] = dict(self.device_config or {})
|
|
return pod
|
|
|
|
@classmethod
|
|
def from_pod(cls, pod):
|
|
meta_pod = {}
|
|
for cfg_point in cls.meta_data:
|
|
meta_pod[cfg_point.name] = pod.pop(cfg_point.name, None)
|
|
|
|
instance = super(RunConfiguration, cls).from_pod(pod)
|
|
for cfg_point in cls.meta_data:
|
|
cfg_point.set_value(instance, meta_pod[cfg_point.name])
|
|
|
|
return instance
|
|
|
|
|
|
class JobSpec(Configuration):
|
|
|
|
name = "Job Spec"
|
|
|
|
config_points = [
|
|
ConfigurationPoint('iterations', kind=int, default=1,
|
|
description='''
|
|
How many times to repeat this workload spec
|
|
'''),
|
|
ConfigurationPoint('workload_name', kind=str, mandatory=True,
|
|
aliases=["name"],
|
|
description='''
|
|
The name of the workload to run.
|
|
'''),
|
|
ConfigurationPoint('workload_parameters', kind=obj_dict,
|
|
aliases=["params", "workload_params"],
|
|
description='''
|
|
Parameter to be passed to the workload
|
|
'''),
|
|
ConfigurationPoint('runtime_parameters', kind=obj_dict,
|
|
aliases=["runtime_params"],
|
|
description='''
|
|
Runtime parameters to be set prior to running
|
|
the workload.
|
|
'''),
|
|
ConfigurationPoint('boot_parameters', kind=obj_dict,
|
|
aliases=["boot_params"],
|
|
description='''
|
|
Parameters to be used when rebooting the target
|
|
prior to running the workload.
|
|
'''),
|
|
ConfigurationPoint('label', kind=str,
|
|
description='''
|
|
Similar to IDs but do not have the uniqueness restriction.
|
|
If specified, labels will be used by some result
|
|
processes instead of (or in addition to) the workload
|
|
name. For example, the csv result processor will put
|
|
the label in the "workload" column of the CSV file.
|
|
'''),
|
|
ConfigurationPoint('instrumentation', kind=toggle_set, merge=True,
|
|
aliases=["instruments"],
|
|
description='''
|
|
The instruments to enable (or disabled using a ~)
|
|
during this workload spec.
|
|
'''),
|
|
ConfigurationPoint('flash', kind=dict, merge=True,
|
|
description='''
|
|
|
|
'''),
|
|
ConfigurationPoint('classifiers', kind=dict, merge=True,
|
|
description='''
|
|
Classifiers allow you to tag metrics from this workload
|
|
spec to help in post processing them. Theses are often
|
|
used to help identify what runtime_parameters were used
|
|
for results when post processing.
|
|
'''),
|
|
]
|
|
configuration = {cp.name: cp for cp in config_points}
|
|
|
|
@classmethod
|
|
def from_pod(cls, pod):
|
|
job_id = pod.pop('id')
|
|
instance = super(JobSpec, cls).from_pod(pod)
|
|
instance['id'] = job_id
|
|
return instance
|
|
|
|
@property
|
|
def section_id(self):
|
|
if self.id is not None:
|
|
self.id.rsplit('-', 1)[0]
|
|
|
|
@property
|
|
def workload_id(self):
|
|
if self.id is not None:
|
|
self.id.rsplit('-', 1)[-1]
|
|
|
|
def __init__(self):
|
|
super(JobSpec, self).__init__()
|
|
self.to_merge = defaultdict(OrderedDict)
|
|
self._sources = []
|
|
self.id = None
|
|
|
|
def to_pod(self):
|
|
pod = super(JobSpec, self).to_pod()
|
|
pod['id'] = self.id
|
|
return pod
|
|
|
|
def update_config(self, source, check_mandatory=True):
|
|
self._sources.append(source)
|
|
values = source.config
|
|
for k, v in values.iteritems():
|
|
if k == "id":
|
|
continue
|
|
elif k.endswith('_parameters'):
|
|
if v:
|
|
self.to_merge[k][source] = copy(v)
|
|
else:
|
|
try:
|
|
self.set(k, v, check_mandatory=check_mandatory)
|
|
except ConfigError as e:
|
|
msg = 'Error in {}:\n\t{}'
|
|
raise ConfigError(msg.format(source.name, e.message))
|
|
|
|
def merge_workload_parameters(self, plugin_cache):
|
|
# merge global generic and specific config
|
|
workload_params = plugin_cache.get_plugin_config(self.workload_name,
|
|
generic_name="workload_parameters",
|
|
is_final=False)
|
|
|
|
cfg_points = plugin_cache.get_plugin_parameters(self.workload_name)
|
|
for source in self._sources:
|
|
config = self.to_merge["workload_parameters"].get(source)
|
|
if config is None:
|
|
continue
|
|
|
|
for name, cfg_point in cfg_points.iteritems():
|
|
if name in config:
|
|
value = config.pop(name)
|
|
cfg_point.set_value(workload_params, value,
|
|
check_mandatory=False)
|
|
if config:
|
|
msg = 'Unexpected config "{}" for "{}"'
|
|
raise ConfigError(msg.format(config, self.workload_name))
|
|
|
|
self.workload_parameters = workload_params
|
|
|
|
def merge_runtime_parameters(self, plugin_cache, target_manager):
|
|
|
|
# Order global runtime parameters
|
|
runtime_parameters = OrderedDict()
|
|
try:
|
|
global_runtime_params = plugin_cache.get_plugin_config("runtime_parameters")
|
|
except NotFoundError:
|
|
global_runtime_params = {}
|
|
for source in plugin_cache.sources:
|
|
if source in global_runtime_params:
|
|
runtime_parameters[source] = global_runtime_params[source]
|
|
|
|
# Add runtime parameters from JobSpec
|
|
for source, values in self.to_merge['runtime_parameters'].iteritems():
|
|
runtime_parameters[source] = values
|
|
|
|
# Merge
|
|
self.runtime_parameters = target_manager.merge_runtime_parameters(runtime_parameters)
|
|
|
|
def finalize(self):
|
|
self.id = "-".join([source.config['id']
|
|
for source in self._sources[1:]]) # ignore first id, "global"
|
|
if self.label is None:
|
|
self.label = self.workload_name
|
|
|
|
|
|
|
|
# This is used to construct the list of Jobs WA will run
|
|
class JobGenerator(object):
|
|
|
|
name = "Jobs Configuration"
|
|
|
|
@property
|
|
def enabled_instruments(self):
|
|
self._read_enabled_instruments = True
|
|
return self._enabled_instruments
|
|
|
|
def __init__(self, plugin_cache):
|
|
self.plugin_cache = plugin_cache
|
|
self.ids_to_run = []
|
|
self.sections = []
|
|
self.workloads = []
|
|
self._enabled_instruments = set()
|
|
self._read_enabled_instruments = False
|
|
self.disabled_instruments = []
|
|
|
|
self.job_spec_template = obj_dict(not_in_dict=['name'])
|
|
self.job_spec_template.name = "globally specified job spec configuration"
|
|
self.job_spec_template.id = "global"
|
|
# Load defaults
|
|
for cfg_point in JobSpec.configuration.itervalues():
|
|
cfg_point.set_value(self.job_spec_template, check_mandatory=False)
|
|
|
|
self.root_node = SectionNode(self.job_spec_template)
|
|
|
|
def set_global_value(self, name, value):
|
|
JobSpec.configuration[name].set_value(self.job_spec_template, value,
|
|
check_mandatory=False)
|
|
if name == "instrumentation":
|
|
self.update_enabled_instruments(value)
|
|
|
|
def add_section(self, section, workloads):
|
|
new_node = self.root_node.add_section(section)
|
|
for workload in workloads:
|
|
new_node.add_workload(workload)
|
|
|
|
def add_workload(self, workload):
|
|
self.root_node.add_workload(workload)
|
|
|
|
def disable_instruments(self, instruments):
|
|
#TODO: Validate
|
|
self.disabled_instruments = ["~{}".format(i) for i in instruments]
|
|
|
|
def update_enabled_instruments(self, value):
|
|
if self._read_enabled_instruments:
|
|
msg = "'enabled_instruments' cannot be updated after it has been accessed"
|
|
raise RuntimeError(msg)
|
|
self._enabled_instruments.update(value)
|
|
|
|
def only_run_ids(self, ids):
|
|
if isinstance(ids, str):
|
|
ids = [ids]
|
|
self.ids_to_run = ids
|
|
|
|
def generate_job_specs(self, target_manager):
|
|
specs = []
|
|
for leaf in self.root_node.leaves():
|
|
workload_entries = leaf.workload_entries
|
|
sections = [leaf]
|
|
for ancestor in leaf.ancestors():
|
|
workload_entries = ancestor.workload_entries + workload_entries
|
|
sections.insert(0, ancestor)
|
|
|
|
for workload_entry in workload_entries:
|
|
job_spec = create_job_spec(deepcopy(workload_entry), sections,
|
|
target_manager, self.plugin_cache,
|
|
self.disabled_instruments)
|
|
if self.ids_to_run:
|
|
for job_id in self.ids_to_run:
|
|
if job_id in job_spec.id:
|
|
break
|
|
else:
|
|
continue
|
|
self.update_enabled_instruments(job_spec.instrumentation.values())
|
|
specs.append(job_spec)
|
|
return specs
|
|
|
|
|
|
def create_job_spec(workload_entry, sections, target_manager, plugin_cache,
|
|
disabled_instruments):
|
|
job_spec = JobSpec()
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# PHASE 2.1: Merge general job spec configuration
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for section in sections:
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job_spec.update_config(section, check_mandatory=False)
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job_spec.update_config(workload_entry, check_mandatory=False)
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# PHASE 2.2: Merge global, section and workload entry "workload_parameters"
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job_spec.merge_workload_parameters(plugin_cache)
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# TODO: PHASE 2.3: Validate device runtime/boot parameters
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job_spec.merge_runtime_parameters(plugin_cache, target_manager)
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target_manager.validate_runtime_parameters(job_spec.runtime_parameters)
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# PHASE 2.4: Disable globally disabled instrumentation
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job_spec.set("instrumentation", disabled_instruments)
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job_spec.finalize()
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return job_spec
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settings = MetaConfiguration(os.environ)
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