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https://github.com/huggingface/diffusers.git
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a124204490
* pass norm_num_groups param and add tests * set resnet_groups for FlaxUNetMidBlock2D * fixed docstrings * fixed typo * using is_flax_available util and created require_flax decorator
40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
import unittest
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from diffusers import FlaxAutoencoderKL
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from diffusers.utils import is_flax_available
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from diffusers.utils.testing_utils import require_flax
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from .test_modeling_common_flax import FlaxModelTesterMixin
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if is_flax_available():
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import jax
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@require_flax
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class FlaxAutoencoderKLTests(FlaxModelTesterMixin, unittest.TestCase):
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model_class = FlaxAutoencoderKL
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@property
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def dummy_input(self):
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batch_size = 4
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num_channels = 3
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sizes = (32, 32)
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prng_key = jax.random.PRNGKey(0)
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image = jax.random.uniform(prng_key, ((batch_size, num_channels) + sizes))
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return {"sample": image, "prng_key": prng_key}
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def prepare_init_args_and_inputs_for_common(self):
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init_dict = {
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"block_out_channels": [32, 64],
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"in_channels": 3,
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"out_channels": 3,
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"down_block_types": ["DownEncoderBlock2D", "DownEncoderBlock2D"],
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"up_block_types": ["UpDecoderBlock2D", "UpDecoderBlock2D"],
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"latent_channels": 4,
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}
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inputs_dict = self.dummy_input
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return init_dict, inputs_dict
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