# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
from . import transforms as T


def build_transforms(cfg, is_train=True, is_fp16=True, is_hybrid=False):
    if is_train:
        min_size = cfg.INPUT.MIN_SIZE_TRAIN
        max_size = cfg.INPUT.MAX_SIZE_TRAIN
        flip_prob = 0.5  # cfg.INPUT.FLIP_PROB_TRAIN
    else:
        min_size = cfg.INPUT.MIN_SIZE_TEST
        max_size = cfg.INPUT.MAX_SIZE_TEST
        flip_prob = 0

    to_bgr255 = cfg.INPUT.TO_BGR255
    normalize_transform = T.Normalize(
        mean=cfg.INPUT.PIXEL_MEAN, std=cfg.INPUT.PIXEL_STD, to_bgr255=to_bgr255
    )

    if is_hybrid:
        ops = [
                  T.Resize(min_size, max_size),
                  T.RandomHorizontalFlip(flip_prob),
                  T.ToHalf(),
                  normalize_transform
              ]
    else:
        ops = [
                  T.Resize(min_size, max_size),
                  T.RandomHorizontalFlip(flip_prob),
                  T.ToTensor(),
                  normalize_transform
              ]
        if is_fp16:
            ops.append(T.ToHalf())
    transform = T.Compose(ops)

    return transform