# Copyright 2021 Huawei Technologies Co., Ltd

#

# 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.



# Google utils: https://cloud.google.com/storage/docs/reference/libraries



import os

import platform

import subprocess

import time

from pathlib import Path



import torch





def gsutil_getsize(url=''):

    # gs://bucket/file size https://cloud.google.com/storage/docs/gsutil/commands/du

    s = subprocess.check_output('gsutil du %s' % url, shell=True).decode('utf-8')

    return eval(s.split(' ')[0]) if len(s) else 0  # bytes





def attempt_download(weights):

    # Attempt to download pretrained weights if not found locally

    weights = weights.strip().replace("'", '')

    file = Path(weights).name



    msg = weights + ' missing, try downloading from https://github.com/WongKinYiu/yolor/releases/'

    models = ['yolor_p6.pt', 'yolor_w6.pt']  # available models



    if file in models and not os.path.isfile(weights):



        try:  # GitHub

            url = 'https://github.com/WongKinYiu/yolor/releases/download/v1.0/' + file

            print('Downloading %s to %s...' % (url, weights))

            torch.hub.download_url_to_file(url, weights)

            assert os.path.exists(weights) and os.path.getsize(weights) > 1E6  # check

        except Exception as e:  # GCP

            print('ERROR: Download failure.')

            print('')

            

            

def attempt_load(weights, map_location=None):

    # Loads an ensemble of models weights=[a,b,c] or a single model weights=[a] or weights=a

    model = Ensemble()

    for w in weights if isinstance(weights, list) else [weights]:

        attempt_download(w)

        model.append(torch.load(w, map_location=map_location)['model'].float().fuse().eval())  # load FP32 model



    if len(model) == 1:

        return model[-1]  # return model

    else:

        print('Ensemble created with %s\n' % weights)

        for k in ['names', 'stride']:

            setattr(model, k, getattr(model[-1], k))

        return model  # return ensemble





def gdrive_download(id='1n_oKgR81BJtqk75b00eAjdv03qVCQn2f', name='coco128.zip'):

    # Downloads a file from Google Drive. from utils.google_utils import *; gdrive_download()

    t = time.time()



    print('Downloading https://drive.google.com/uc?export=download&id=%s as %s... ' % (id, name), end='')

    os.remove(name) if os.path.exists(name) else None  # remove existing

    os.remove('cookie') if os.path.exists('cookie') else None



    # Attempt file download

    out = "NUL" if platform.system() == "Windows" else "/dev/null"

    os.system('curl -c ./cookie -s -L "drive.google.com/uc?export=download&id=%s" > %s ' % (id, out))

    if os.path.exists('cookie'):  # large file

        s = 'curl -Lb ./cookie "drive.google.com/uc?export=download&confirm=%s&id=%s" -o %s' % (get_token(), id, name)

    else:  # small file

        s = 'curl -s -L -o %s "drive.google.com/uc?export=download&id=%s"' % (name, id)

    r = os.system(s)  # execute, capture return

    os.remove('cookie') if os.path.exists('cookie') else None



    # Error check

    if r != 0:

        os.remove(name) if os.path.exists(name) else None  # remove partial

        print('Download error ')  # raise Exception('Download error')

        return r



    # Unzip if archive

    if name.endswith('.zip'):

        print('unzipping... ', end='')

        os.system('unzip -q %s' % name)  # unzip

        os.remove(name)  # remove zip to free space



    print('Done (%.1fs)' % (time.time() - t))

    return r





def get_token(cookie="./cookie"):

    with open(cookie) as f:

        for line in f:

            if "download" in line:

                return line.split()[-1]

    return ""



# def upload_blob(bucket_name, source_file_name, destination_blob_name):

#     # Uploads a file to a bucket

#     # https://cloud.google.com/storage/docs/uploading-objects#storage-upload-object-python

#

#     storage_client = storage.Client()

#     bucket = storage_client.get_bucket(bucket_name)

#     blob = bucket.blob(destination_blob_name)

#

#     blob.upload_from_filename(source_file_name)

#

#     print('File {} uploaded to {}.'.format(

#         source_file_name,

#         destination_blob_name))

#

#

# def download_blob(bucket_name, source_blob_name, destination_file_name):

#     # Uploads a blob from a bucket

#     storage_client = storage.Client()

#     bucket = storage_client.get_bucket(bucket_name)

#     blob = bucket.blob(source_blob_name)

#

#     blob.download_to_filename(destination_file_name)

#

#     print('Blob {} downloaded to {}.'.format(

#         source_blob_name,

#         destination_file_name))