import os
import subprocess
import sys
import tempfile
import unittest

from torch_fidelity.helpers import json_decode_string
from torch_fidelity.metric_kid import KEY_METRIC_KID_MEAN, KEY_METRIC_KID_STD


class TestMetricKidDeterminism(unittest.TestCase):
    @staticmethod
    def call_ref_kid(input_1, input_2, cuda, determinism):
        args = [
            'python3', 'tests/tf1/reference/reference_metric_kid_mmdgan.py', input_1, input_2,
            '--no-inception', '--do-mmd'
        ]
        if cuda:
            args.append('--gpu')
            args.append(os.environ['CUDA_VISIBLE_DEVICES'])
        if determinism:
            args.append('--determinism')
        args.append('--json')
        args.append('--silent')
        res = subprocess.run(args, stdout=subprocess.PIPE, stderr=None)
        return res

    def test_kid_reference_determinism(self):
        cuda = os.environ.get('CUDA_VISIBLE_DEVICES', '') != ''
        limit = 5000
        cifar10trainorig_root = os.path.join(tempfile.gettempdir(), f'cifar10-train-img-{limit}')
        cifar10validnoise_root = os.path.join(tempfile.gettempdir(), f'cifar10-valid-img-noise-{limit}')
        cifar10trainorig_codes = os.path.join(tempfile.gettempdir(), f'cifar10-train-img-codes-{limit}.pth')

        res = subprocess.run(
            ('python3', 'utils/util_dump_dataset_as_images.py', 'cifar10-train', cifar10trainorig_root,
             '-l', str(limit)),
        )
        self.assertEqual(res.returncode, 0, msg=res)
        res = subprocess.run(
            ('python3', 'utils/util_dump_dataset_as_images.py', 'cifar10-valid', cifar10validnoise_root,
             '-l', str(limit), '-n'),
        )
        self.assertEqual(res.returncode, 0, msg=res)

        # this partucular reference app needs features pre-extracted
        if not os.path.exists(cifar10trainorig_codes):
            args = [
                'python3', 'tests/tf1/reference/reference_metric_kid_mmdgan.py', cifar10trainorig_root,
                '--save-codes', cifar10trainorig_codes, '--determinism'
            ]
            if cuda:
                args.append('--gpu')
                args.append(os.environ['CUDA_VISIBLE_DEVICES'])
            res = subprocess.run(args, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
            self.assertEqual(res.returncode, 0, msg=res)

        num_sample_runs = 2
        kid_mean_nondet, kid_std_nondet = [], []
        kid_mean_det, kid_std_det = [], []

        def sample_runs(kid_mean, kid_std, prefix, determinism):
            for i in range(num_sample_runs):
                print(f'{prefix} run {i+1} of {num_sample_runs}...', file=sys.stderr)
                res = self.call_ref_kid(cifar10validnoise_root, cifar10trainorig_codes, cuda, determinism)
                self.assertEqual(res.returncode, 0, msg=res)
                res = json_decode_string(res.stdout.decode())
                kid_mean.append(res[KEY_METRIC_KID_MEAN])
                kid_std.append(res[KEY_METRIC_KID_STD])

        sample_runs(kid_mean_nondet, kid_std_nondet, 'Non-deterministic', False)
        sample_runs(kid_mean_det, kid_std_det, 'Deterministic', True)

        print('kid_mean_nondet', kid_mean_nondet, file=sys.stderr)
        print('kid_std_nondet', kid_std_nondet, file=sys.stderr)
        print('kid_mean_det', kid_mean_det, file=sys.stderr)
        print('kid_std_det', kid_std_det, file=sys.stderr)

        if cuda:
            self.assertGreater(min(kid_mean_nondet) + 1e-5, max(kid_mean_nondet))
        else:
            self.assertGreaterEqual(max(kid_mean_nondet), min(kid_mean_nondet))
        self.assertEqual(max(kid_mean_det), min(kid_mean_det))


if __name__ == '__main__':
    unittest.main()
