#!/usr/bin/env python
# encoding: utf-8

# The MIT License (MIT)

# Copyright (c) 2018-2021 CNRS

# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:

# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.

# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.

# AUTHORS
# Hervé BREDIN - http://herve.niderb.fr
# Hadrien TITEUX
from typing import Sequence

from optuna import Trial
from optuna.distributions import CategoricalChoiceType


class FakeTrial(Trial):

    def __init__(self):
        pass

    def suggest_uniform(self, name: str, low: float, high: float) -> float:
        return low

    def suggest_int(self, name: str, low: int, high: int, step: int = 1, log: bool = False) -> int:
        return low

    def suggest_categorical(self, name: str, choices: Sequence[CategoricalChoiceType]) -> CategoricalChoiceType:
        return choices[0]