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@ -1,12 +1,17 @@ |
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import diffusers |
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import pytest |
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import pytest |
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import torch |
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import torch |
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import transformers |
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from torch.fx import GraphModule |
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from torch.fx import GraphModule |
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from utils import trace_model_and_compare_output |
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from utils import trace_model_and_compare_output |
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import transformers |
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from colossalai.fx import ColoTracer |
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from colossalai.fx import ColoTracer |
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try: |
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import diffusers |
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HAS_DIFFUSERS = True |
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except ImportError: |
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HAS_DIFFUSERS = False |
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BATCH_SIZE = 2 |
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BATCH_SIZE = 2 |
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SEQ_LENGTH = 5 |
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SEQ_LENGTH = 5 |
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HEIGHT = 224 |
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HEIGHT = 224 |
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@ -16,6 +21,7 @@ LATENTS_SHAPE = (BATCH_SIZE, IN_CHANNELS, HEIGHT // 8, WIDTH // 8) |
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TIME_STEP = 2 |
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TIME_STEP = 2 |
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@pytest.mark.skipif(not HAS_DIFFUSERS, reason="diffusers has not been installed") |
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def test_vae(): |
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def test_vae(): |
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MODEL_LIST = [ |
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MODEL_LIST = [ |
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diffusers.AutoencoderKL, |
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diffusers.AutoencoderKL, |
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@ -80,6 +86,7 @@ def test_clip(): |
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trace_model_and_compare_output(model, data_gen) |
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trace_model_and_compare_output(model, data_gen) |
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@pytest.mark.skipif(not HAS_DIFFUSERS, reason="diffusers has not been installed") |
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@pytest.mark.skip(reason='cannot pass the test yet') |
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@pytest.mark.skip(reason='cannot pass the test yet') |
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def test_unet(): |
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def test_unet(): |
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MODEL_LIST = [ |
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MODEL_LIST = [ |
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