mirror of
https://github.com/brycedrennan/imaginAIry
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26 lines
745 B
Python
26 lines
745 B
Python
import hashlib
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import pytest
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from imaginairy.modules.clip_embedders import FrozenCLIPEmbedder
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from imaginairy.utils import get_device
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def hash_tensor(t):
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t = t.cpu().detach().numpy().tobytes()
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return hashlib.md5(t).hexdigest()
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@pytest.mark.skipif(get_device() == "cpu", reason="Too slow to run on CPU")
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def test_text_conditioning():
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embedder = FrozenCLIPEmbedder()
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embedder.to(get_device())
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neutral_embedding = embedder.encode([""])
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hashed = hash_tensor(neutral_embedding)
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assert hashed in {
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"263e5ee7d2be087d816e094b80ffc546", # mps
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"41818051d7c469fc57d0a940c9d24d82",
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"b5f29fb26bceb60dcde19ec7ec5a0711",
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"88245bdb2a83b49092407fc5b4c473ab", # ubuntu, torch 1.12.1 cu116
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}
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