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Fixing quantization tests (#37650)

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* fix

* style

* add capability check
This commit is contained in:
Mohamed Mekkouri
2025-04-22 13:59:57 +02:00
committed by GitHub
parent b3492ff9f7
commit 38c406844e
4 changed files with 18 additions and 4 deletions
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16
tests/quantization/autoawq/test_awq.py
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@@ -110,7 +110,7 @@ class AwqTest(unittest.TestCase):
input_text = "Hello my name is"
EXPECTED_OUTPUT = "Hello my name is Katie and I am a 20 year old student at the University of North Carolina at Chapel Hill. I am a junior and I am majoring in Journalism and minoring in Spanish"
EXPECTED_OUTPUT_BF16 = "Hello my name is Katie and I am a 20 year old student at the University of North Carolina at Chapel Hill. I am a junior and I am majoring in Exercise and Sport Science with a"
EXPECTED_OUTPUT_BF16 = "Hello my name is Katie and I am a 20 year old student at the University of North Carolina at Chapel Hill. I am a junior and I am majoring in Journalism and minoring in Spanish"
EXPECTED_OUTPUT_EXLLAMA = [
"Hello my name is Katie and I am a 20 year old student from the UK. I am currently studying for a degree in English Literature and History at the University of York. I am a very out",
@@ -299,7 +299,7 @@ class AwqFusedTest(unittest.TestCase):
"You end up exactly where you started. Where are you?"
)
EXPECTED_GENERATION = prompt + "\n\nThis is a classic puzzle that has been around for"
EXPECTED_GENERATION = prompt + "\n\nYou're at the center of a square."
EXPECTED_GENERATION_CUSTOM_MODEL = "Hello,\n\nI have a problem with my 20"
EXPECTED_GENERATION_MIXTRAL = prompt + " You're on the North Pole.\n\nThe"
@@ -355,6 +355,10 @@ class AwqFusedTest(unittest.TestCase):
# Checks if the modules_to_not_convert (here gate layer) is a Linear
self.assertTrue(isinstance(model.model.layers[0].block_sparse_moe.gate, torch.nn.Linear))
@unittest.skipIf(
torch.cuda.is_available() and torch.cuda.get_device_capability()[0] < 8,
"Skipping because RuntimeError: FlashAttention only supports Ampere GPUs or newer, so not supported on GPU with capability < 8.0",
)
def test_generation_fused(self):
"""
Test generation quality for fused models - single batch case
@@ -378,6 +382,10 @@ class AwqFusedTest(unittest.TestCase):
self.assertEqual(tokenizer.decode(outputs[0], skip_special_tokens=True), self.EXPECTED_GENERATION)
@unittest.skipIf(
torch.cuda.is_available() and torch.cuda.get_device_capability()[0] < 8,
"Skipping because RuntimeError: FlashAttention only supports Ampere GPUs or newer, so not supported on GPU with capability < 8.0",
)
def test_generation_fused_batched(self):
"""
Test generation quality for fused models - multi batch case
@@ -426,6 +434,10 @@ class AwqFusedTest(unittest.TestCase):
self.assertEqual(outputs[0]["generated_text"], EXPECTED_OUTPUT)
@require_torch_multi_gpu
@unittest.skipIf(
torch.cuda.is_available() and torch.cuda.get_device_capability()[0] < 8,
"Skipping because RuntimeError: FlashAttention only supports Ampere GPUs or newer, so not supported on GPU with capability < 8.0",
)
def test_generation_custom_model(self):
"""
Test generation quality for fused models using custom fused map.