# Copyright 2020 The Forte 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.
import random
from abc import abstractmethod
from typing import Any, Dict, Union
from forte.common.configurable import Configurable
from forte.common.configuration import Config
__all__ = [
"Sampler",
"UniformSampler",
"UnigramSampler",
]
[docs]class Sampler(Configurable):
r"""
An abstract sampler class.
"""
def __init__(self, configs: Union[Config, Dict[str, Any]]):
self.configs: Config = self.make_configs(configs)
random.seed()
@abstractmethod
def sample(self) -> str:
raise NotImplementedError
[docs]class UnigramSampler(Sampler):
r"""
A sampler that samples a word from a unigram distribution.
Config Values:
- sampler_data: (dict)
The key is a word, the value is the word count or a probability.
This sampler samples from this word distribution.
Example:
.. code-block:: python
'sampler_data': {
"apple": 1,
"banana": 2,
"orange": 3
}
"""
def __init__(self, configs: Union[Config, Dict[str, Any]]):
super().__init__(configs)
self.unigram = self.configs["sampler_data"].__dict__["_hparams"]
def sample(self) -> str:
word: str = random.choices(
list(self.unigram.keys()), list(self.unigram.values())
)[0]
return word
@classmethod
def default_configs(cls):
return {"sampler_data": {}, "@no_typecheck": "sampler_data"}