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"pin": "تثبيت 📌",
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"unpin": "الغاء تثبيت 📌",
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"ban": "العضو [{}](tg://user?id={}) تم حظره ❌",
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"ban_id": "العضو {} تم حظره",
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"banError": "العضو غير محظور 🙄",
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"muteError": "العضو ليس مكتوم 🙄",
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"admins": {
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"0": "لا يوجد مشرفين ❌",
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"1": "👤 المدير : {}\nالمشرفين :\n{}"
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},
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"filter": "☠️ تم اضافة الكلمة لقائمة الكلمات المحظورة :\n{}",
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"unfilter": "☠️ تم ازالة الكلمة من قائمة الكلمات المحظورة :\n{}",
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"filters": "🤐 الكلمات المحظورة :\n{}",
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"mute": "العضو [{}](tg://user?id={}) تم اضافته لقائمة المكتومين لمدة {} يوم",
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"unmute": "تم الغاء الكتم :)",
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"muteAll": {
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"0": "تم قفل المجموعة ✅",
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"1": "المجموعة مقفلة مسبقا ✅"
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},
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"unmuteAll": {
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"0": "تم فتح المجموعة ✅",
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"1": "المجموعة غير مقفلة ✅"
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},
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"admins_set": ""
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},
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"admin": {
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"add": {
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"0": "المجموعة مفعلة مسبقا 🔖",
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"1": "تم تفعيل البوت في المجموعة ✅"
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},
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"rem": {
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"0": "تم ازالة البوت من المجموعة 💢",
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"1": "المجموعة ليست مفعلة 💢"
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}
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},
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"who": {
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"name": "👤 *{} {}*",
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"group": "👥 *{}*",
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"id": "🆔 \\[{}]",
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"username": "▶️ @{}"
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}
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}
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}
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# <FILESEP>
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# Copyright 2023 NNAISENSE SA
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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 torch
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import functools
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from abc import abstractmethod
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from torch.distributions.normal import Normal
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from torch.distributions.categorical import Categorical as torch_Categorical
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from torch.distributions.bernoulli import Bernoulli as torch_Bernoulli
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from torch.distributions.mixture_same_family import MixtureSameFamily
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from torch.distributions.uniform import Uniform
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from math import log
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from utils_model import (
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safe_exp,
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safe_log,
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idx_to_float,
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float_to_idx,
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quantize, sandwich,
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)
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class CtsDistribution:
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@abstractmethod
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def log_prob(self, x):
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pass
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@abstractmethod
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def sample(self):
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pass
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class DiscreteDistribution:
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@property
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@abstractmethod
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def probs(self):
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pass
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@functools.cached_property
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def log_probs(self):
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return safe_log(self.probs)
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