# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Basic types""" from __future__ import print_function from __future__ import absolute_import from __future__ import unicode_literals import os import json from collections import namedtuple class RunMode(object): """model_fn will be called in 3 modes""" TRAIN = 1 PREDICT = 2 EVAL = 3 class HParams(object): """Hyper paramerter""" def __init__(self, **kwargs): for k, v in kwargs.items(): self.__dict__[k] = v def __contains__(self, key): return key in self.__dict__ def __getitem__(self, key): if key not in self.__dict__: raise ValueError('key(%s) not in HParams.' % key) return self.__dict__[key] def __repr__(self): return repr(self.to_dict()) def __setitem__(self, key, val): self.__dict__[key] = val @classmethod def from_json(cls, json_str): """doc""" d = json.loads(json_str) if type(d) != dict: raise ValueError('json object must be dict.') return HParams.from_dict(d) def get(self, key, default=None): """doc""" return self.__dict__.get(key, default) @classmethod def from_dict(cls, d): """doc""" if type(d) != dict: raise ValueError('input must be dict.') hp = HParams(**d) return hp def to_json(self): """doc""" return json.dumps(self.__dict__) def to_dict(self): """doc""" return self.__dict__ def join(self, other): """doc""" if not isinstance(other, HParams): raise ValueError('input must be HParams instance. got %s' % type(other)) self.__dict__.update(**other.__dict__) return self SummaryRecord = namedtuple('SummaryRecord', ['scalar', 'histogram']) WarmStartSetting = namedtuple('WarmStartSetting', ['predicate_fn', 'from_dir']) TextoneWarmStartSetting = namedtuple('TextoneWarmStartSetting', ['from_dir']) RunConfig = namedtuple('RunConfig', [ 'model_dir', 'run_steps', 'max_steps', 'save_steps', 'eval_steps', 'eval_max_steps', 'skip_steps', 'log_steps', 'max_ckpt', 'shit', 'log_prefix' ]) RunConfig.__new__.__defaults__ = (None, ) * len(RunConfig._fields) ProgramPair = namedtuple('ProgramPair', ['train_program', 'startup_program']) InferenceSpec = namedtuple('InferenceSpec', ['inputs', 'outputs']) ModelSpec = namedtuple('ModelSpec', [ 'loss', 'predictions', 'metrics', 'mode', 'inference_spec', 'train_hooks', 'eval_hooks', ]) ModelSpec.__new__.__defaults__ = (None, ) * len(ModelSpec._fields) class StopException(Exception): """doc""" pass