declare-lab/tango2
92
1# coding=utf-82# Copyright 2023 HuggingFace Inc.3#4# Licensed under the Apache License, Version 2.0 (the "License");5# you may not use this file except in compliance with the License.6# You may obtain a copy of the License at7#8# http://www.apache.org/licenses/LICENSE-2.09#10# Unless required by applicable law or agreed to in writing, software11# distributed under the License is distributed on an "AS IS" BASIS,12# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.13# See the License for the specific language governing permissions and14# limitations under the License.15import unittest16from pathlib import Path17from tempfile import TemporaryDirectory18from unittest.mock import Mock, patch19 20import diffusers.utils.hub_utils21 22 23class CreateModelCardTest(unittest.TestCase):24 @patch("diffusers.utils.hub_utils.get_full_repo_name")25 def test_create_model_card(self, repo_name_mock: Mock) -> None:26 repo_name_mock.return_value = "full_repo_name"27 with TemporaryDirectory() as tmpdir:28 # Dummy args values29 args = Mock()30 args.output_dir = tmpdir31 args.local_rank = 032 args.hub_token = "hub_token"33 args.dataset_name = "dataset_name"34 args.learning_rate = 0.0135 args.train_batch_size = 10000036 args.eval_batch_size = 1000037 args.gradient_accumulation_steps = 0.0138 args.adam_beta1 = 0.0239 args.adam_beta2 = 0.0340 args.adam_weight_decay = 0.000541 args.adam_epsilon = 0.00000142 args.lr_scheduler = 143 args.lr_warmup_steps = 1044 args.ema_inv_gamma = 0.00145 args.ema_power = 0.146 args.ema_max_decay = 0.247 args.mixed_precision = True48 49 # Model card mush be rendered and saved50 diffusers.utils.hub_utils.create_model_card(args, model_name="model_name")51 self.assertTrue((Path(tmpdir) / "README.md").is_file())52 