45 lines
1.5 KiB
Python
45 lines
1.5 KiB
Python
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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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if is_flax_available():
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import jax
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@require_flax
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class FlaxModelTesterMixin:
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def test_output(self):
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init_dict, inputs_dict = self.prepare_init_args_and_inputs_for_common()
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model = self.model_class(**init_dict)
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variables = model.init(inputs_dict["prng_key"], inputs_dict["sample"])
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jax.lax.stop_gradient(variables)
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output = model.apply(variables, inputs_dict["sample"])
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if isinstance(output, dict):
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output = output.sample
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self.assertIsNotNone(output)
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expected_shape = inputs_dict["sample"].shape
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self.assertEqual(output.shape, expected_shape, "Input and output shapes do not match")
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def test_forward_with_norm_groups(self):
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init_dict, inputs_dict = self.prepare_init_args_and_inputs_for_common()
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init_dict["norm_num_groups"] = 16
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init_dict["block_out_channels"] = (16, 32)
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model = self.model_class(**init_dict)
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variables = model.init(inputs_dict["prng_key"], inputs_dict["sample"])
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jax.lax.stop_gradient(variables)
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output = model.apply(variables, inputs_dict["sample"])
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if isinstance(output, dict):
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output = output.sample
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self.assertIsNotNone(output)
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expected_shape = inputs_dict["sample"].shape
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self.assertEqual(output.shape, expected_shape, "Input and output shapes do not match")
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