# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# 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
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import gc
import unittest

import torch

from diffusers import DDIMScheduler, TextToVideoZeroPipeline
from diffusers.utils.testing_utils import load_pt, nightly, require_torch_gpu

from ..test_pipelines_common import assert_mean_pixel_difference


@nightly
@require_torch_gpu
class TextToVideoZeroPipelineSlowTests(unittest.TestCase):
    def setUp(self):
        # clean up the VRAM before each test
        super().setUp()
        gc.collect()
        torch.cuda.empty_cache()

    def tearDown(self):
        # clean up the VRAM after each test
        super().tearDown()
        gc.collect()
        torch.cuda.empty_cache()

    def test_full_model(self):
        model_id = "stable-diffusion-v1-5/stable-diffusion-v1-5"
        pipe = TextToVideoZeroPipeline.from_pretrained(model_id, torch_dtype=torch.float16).to("cuda")
        pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
        generator = torch.Generator(device="cuda").manual_seed(0)

        prompt = "A bear is playing a guitar on Times Square"
        result = pipe(prompt=prompt, generator=generator).images

        expected_result = load_pt(
            "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text-to-video/A bear is playing a guitar on Times Square.pt"
        )

        assert_mean_pixel_difference(result, expected_result)
