# coding=utf-8
# Copyright 2022 The IDEA 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.
# ------------------------------------------------------------------------------------------------
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
# ------------------------------------------------------------------------------------------------
# Misc functions
# Modified from:
# https://github.com/facebookresearch/detr/blob/main/util/misc.py
# ------------------------------------------------------------------------------------------------


from typing import List, Optional
import torch
import torchvision
from torch import Tensor


def interpolate(input, size=None, scale_factor=None, mode="nearest", align_corners=None):
    # type: (Tensor, Optional[List[int]], Optional[float], str, Optional[bool]) -> Tensor
    """
    Equivalent to ``torch.nn.functional.interpolate``.
    """
    return torchvision.ops.misc.interpolate(input, size, scale_factor, mode, align_corners)


def inverse_sigmoid(x, eps=1e-3):
    """
    The inverse function for sigmoid activation function.
    Note: It might face numberical issues with fp16 small eps.
    """
    x = x.clamp(min=0, max=1)
    x1 = x.clamp(min=eps)
    x2 = (1 - x).clamp(min=eps)
    return torch.log(x1 / x2)