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Fix MPT CI (#25548)

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fix

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2023-08-17 09:06:26 +02:00
committed by GitHub
parent 297a6a7aea
commit ec25306b39
1 changed files with 3 additions and 3 deletions
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6
tests/models/mpt/test_modeling_mpt.py
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@@ -442,7 +442,7 @@ class MptIntegrationTests(unittest.TestCase):
) )
input_text = "Hello" input_text = "Hello"
expected_output = """Hello, I\'m a new user of the forum. I have a question about the "Solaris""" expected_output = 'Hello, I\'m a new user of the forum. I have a question about the "Safety"'
inputs = tokenizer(input_text, return_tensors="pt") inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=20) outputs = model.generate(**inputs, max_new_tokens=20)
@@ -487,7 +487,7 @@ class MptIntegrationTests(unittest.TestCase):
expected_output = [ expected_output = [
"Hello my name is Tiffany and I am a mother of two beautiful children. I have been a nanny for over", "Hello my name is Tiffany and I am a mother of two beautiful children. I have been a nanny for over",
"Today I am going at the gym and then I am going to go to the grocery store. I am going to get some food and then", "Today I am going at the gym and then I am going to go to the grocery store and get some food. I am going to make",
] ]
outputs = model.generate(**inputs, max_new_tokens=20) outputs = model.generate(**inputs, max_new_tokens=20)
@@ -507,7 +507,7 @@ class MptIntegrationTests(unittest.TestCase):
outputs = model(dummy_input, output_hidden_states=True) outputs = model(dummy_input, output_hidden_states=True)
expected_slice = torch.Tensor([-0.2559, -0.2197, -0.2480]).to(torch_device, torch.bfloat16) expected_slice = torch.Tensor([-0.2539, -0.2178, -0.1953]).to(torch_device, torch.bfloat16)
predicted_slice = outputs.hidden_states[-1][0, 0, :3] predicted_slice = outputs.hidden_states[-1][0, 0, :3]
self.assertTrue(torch.allclose(expected_slice, predicted_slice, atol=1e-3, rtol=1e-3)) self.assertTrue(torch.allclose(expected_slice, predicted_slice, atol=1e-3, rtol=1e-3))