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112 lines
3.6 KiB
Python
Executable File
112 lines
3.6 KiB
Python
Executable File
# coding=utf-8
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# Copyright 2025 HuggingFace Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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from diffusers import AutoencoderKLMochi
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from ...testing_utils import (
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enable_full_determinism,
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floats_tensor,
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torch_device,
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)
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from ..test_modeling_common import ModelTesterMixin, UNetTesterMixin
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enable_full_determinism()
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class AutoencoderKLMochiTests(ModelTesterMixin, UNetTesterMixin, unittest.TestCase):
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model_class = AutoencoderKLMochi
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main_input_name = "sample"
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base_precision = 1e-2
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def get_autoencoder_kl_mochi_config(self):
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return {
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"in_channels": 15,
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"out_channels": 3,
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"latent_channels": 4,
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"encoder_block_out_channels": (32, 32, 32, 32),
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"decoder_block_out_channels": (32, 32, 32, 32),
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"layers_per_block": (1, 1, 1, 1, 1),
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"act_fn": "silu",
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"scaling_factor": 1,
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}
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@property
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def dummy_input(self):
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batch_size = 2
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num_frames = 7
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num_channels = 3
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sizes = (16, 16)
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image = floats_tensor((batch_size, num_channels, num_frames) + sizes).to(torch_device)
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return {"sample": image}
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@property
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def input_shape(self):
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return (3, 7, 16, 16)
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@property
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def output_shape(self):
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return (3, 7, 16, 16)
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def prepare_init_args_and_inputs_for_common(self):
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init_dict = self.get_autoencoder_kl_mochi_config()
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inputs_dict = self.dummy_input
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return init_dict, inputs_dict
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def test_gradient_checkpointing_is_applied(self):
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expected_set = {
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"MochiDecoder3D",
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"MochiDownBlock3D",
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"MochiEncoder3D",
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"MochiMidBlock3D",
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"MochiUpBlock3D",
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}
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super().test_gradient_checkpointing_is_applied(expected_set=expected_set)
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@unittest.skip("Unsupported test.")
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def test_forward_with_norm_groups(self):
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"""
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tests/models/autoencoders/test_models_autoencoder_mochi.py::AutoencoderKLMochiTests::test_forward_with_norm_groups -
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TypeError: AutoencoderKLMochi.__init__() got an unexpected keyword argument 'norm_num_groups'
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"""
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pass
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@unittest.skip("Unsupported test.")
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def test_model_parallelism(self):
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"""
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tests/models/autoencoders/test_models_autoencoder_mochi.py::AutoencoderKLMochiTests::test_outputs_equivalence -
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RuntimeError: values expected sparse tensor layout but got Strided
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"""
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pass
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@unittest.skip("Unsupported test.")
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def test_outputs_equivalence(self):
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"""
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tests/models/autoencoders/test_models_autoencoder_mochi.py::AutoencoderKLMochiTests::test_outputs_equivalence -
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RuntimeError: values expected sparse tensor layout but got Strided
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"""
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pass
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@unittest.skip("Unsupported test.")
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def test_sharded_checkpoints_device_map(self):
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"""
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tests/models/autoencoders/test_models_autoencoder_mochi.py::AutoencoderKLMochiTests::test_sharded_checkpoints_device_map -
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RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cuda:5!
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"""
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