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enable 3 mpt test cases on XPU (#37546)

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* enable 3 mpt test cases on XPU

Signed-off-by: YAO Matrix <matrix.yao@intel.com>

* fix style

Signed-off-by: YAO Matrix <matrix.yao@intel.com>

---------

Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
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Yao Matrix 2025-04-16 17:23:06 +08:00 committed by GitHub
parent 4541c2cdef
commit d91858c232
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1 changed files with 25 additions and 5 deletions
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30
tests/models/mpt/test_modeling_mpt.py
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@ -17,7 +17,14 @@ import math
import unittest
from transformers import MptConfig, is_torch_available
from transformers.testing_utils import require_bitsandbytes, require_torch, require_torch_gpu, slow, torch_device
from transformers.testing_utils import (
Expectations,
require_bitsandbytes,
require_torch,
require_torch_accelerator,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
@ -424,7 +431,7 @@ class MptModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin,
@slow
@require_torch_gpu
@require_torch_accelerator
@require_bitsandbytes
class MptIntegrationTests(unittest.TestCase):
def test_generation_8k(self):
@ -439,7 +446,7 @@ class MptIntegrationTests(unittest.TestCase):
input_text = "Hello"
expected_output = "Hello, I'm a new user of the forum. I have a question about the \"Solaris"
inputs = tokenizer(input_text, return_tensors="pt")
inputs = tokenizer(input_text, return_tensors="pt").to(torch_device)
outputs = model.generate(**inputs, max_new_tokens=20)
decoded_output = tokenizer.decode(outputs[0], skip_special_tokens=True)
@ -455,9 +462,22 @@ class MptIntegrationTests(unittest.TestCase):
)
input_text = "Hello"
expected_output = "Hello and welcome to the first episode of the new podcast, The Frugal Feminist.\n"
expected_outputs = Expectations(
{
(
"xpu",
3,
): "Hello and welcome to the first ever episode of the new and improved, and hopefully improved, podcast.\n",
("cuda", 7): "Hello and welcome to the first episode of the new podcast, The Frugal Feminist.\n",
(
"cuda",
8,
): "Hello and welcome to the first day of the new release countdown for the month of May!\nToday",
}
)
expected_output = expected_outputs.get_expectation()
inputs = tokenizer(input_text, return_tensors="pt")
inputs = tokenizer(input_text, return_tensors="pt").to(torch_device)
outputs = model.generate(**inputs, max_new_tokens=20)
decoded_output = tokenizer.decode(outputs[0], skip_special_tokens=True)