| # coding=utf-8 | |
| # Copyright 2025 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 | |
| # limitations under the License. | |
| import unittest | |
| from diffusers import AutoencoderKLKVAE | |
| from ...testing_utils import enable_full_determinism, floats_tensor, torch_device | |
| from ..test_modeling_common import ModelTesterMixin | |
| from .testing_utils import AutoencoderTesterMixin | |
| enable_full_determinism() | |
| class AutoencoderKLKVAETests(ModelTesterMixin, AutoencoderTesterMixin, unittest.TestCase): | |
| model_class = AutoencoderKLKVAE | |
| main_input_name = "sample" | |
| base_precision = 1e-2 | |
| def get_autoencoder_kl_kvae_config(self): | |
| return { | |
| "in_channels": 3, | |
| "channels": 32, | |
| "num_enc_blocks": 1, | |
| "num_dec_blocks": 1, | |
| "z_channels": 4, | |
| "double_z": True, | |
| "ch_mult": (1, 2), | |
| "sample_size": 32, | |
| } | |
| def dummy_input(self): | |
| batch_size = 2 | |
| num_channels = 3 | |
| sizes = (32, 32) | |
| image = floats_tensor((batch_size, num_channels) + sizes).to(torch_device) | |
| return {"sample": image} | |
| def input_shape(self): | |
| return (3, 32, 32) | |
| def output_shape(self): | |
| return (3, 32, 32) | |
| def prepare_init_args_and_inputs_for_common(self): | |
| init_dict = self.get_autoencoder_kl_kvae_config() | |
| inputs_dict = self.dummy_input | |
| return init_dict, inputs_dict | |
| def test_gradient_checkpointing_is_applied(self): | |
| expected_set = { | |
| "KVAEEncoder2D", | |
| "KVAEDecoder2D", | |
| } | |
| super().test_gradient_checkpointing_is_applied(expected_set=expected_set) | |