mirror of
https://github.com/huggingface/transformers.git
synced 2025-08-01 02:31:11 +06:00
enable mllama cases on xpu (#37644)
* enable mllama testing on xpu Signed-off-by: YAO Matrix <matrix.yao@intel.com> * more mllama cases enabling Signed-off-by: YAO Matrix <matrix.yao@intel.com> * make cases pass on A100 Signed-off-by: N <matrix.yao@intel.com> --------- Signed-off-by: YAO Matrix <matrix.yao@intel.com> Signed-off-by: N <matrix.yao@intel.com>
This commit is contained in:
Yao Matrix
GitHub
parent
de182ba269
commit
9167461a7d
@ -31,11 +31,12 @@ from transformers import (
|
||||
from transformers.cache_utils import Cache
|
||||
from transformers.models.mllama.configuration_mllama import MllamaTextConfig
|
||||
from transformers.testing_utils import (
|
||||
Expectations,
|
||||
cleanup,
|
||||
require_bitsandbytes,
|
||||
require_read_token,
|
||||
require_torch,
|
||||
require_torch_gpu,
|
||||
require_torch_accelerator,
|
||||
slow,
|
||||
torch_device,
|
||||
)
|
||||
@ -524,7 +525,7 @@ class MllamaForConditionalGenerationIntegrationTest(unittest.TestCase):
|
||||
cleanup(torch_device, gc_collect=True)
|
||||
|
||||
@slow
|
||||
@require_torch_gpu
|
||||
@require_torch_accelerator
|
||||
@require_bitsandbytes
|
||||
@require_read_token
|
||||
def test_11b_model_integration_generate(self):
|
||||
@ -537,9 +538,18 @@ class MllamaForConditionalGenerationIntegrationTest(unittest.TestCase):
|
||||
|
||||
inputs = processor(text=prompt, images=image, return_tensors="pt").to(torch_device)
|
||||
|
||||
input_ids = inputs["input_ids"]
|
||||
|
||||
# Check inputs ids
|
||||
expected_input_ids = torch.tensor([[128256, 128000, 2746, 358, 1047, 311, 3350, 264, 6520, 39342, 369, 420, 832]], device=torch_device) # fmt: skip
|
||||
self.assertTrue(torch.equal(inputs["input_ids"], expected_input_ids))
|
||||
expected_input_ids_all = Expectations(
|
||||
{
|
||||
("xpu", 3): torch.tensor([[128000, 128256, 128000, 2746, 358, 1047, 311, 3350, 264, 6520, 39342, 369, 420, 832]], device=torch_device),
|
||||
("cuda", 7): torch.tensor([[128256, 128000, 2746, 358, 1047, 311, 3350, 264, 6520, 39342, 369, 420, 832]], device=torch_device),
|
||||
("cuda", 8): torch.tensor([[128000, 128256, 128000, 2746, 358, 1047, 311, 3350, 264, 6520, 39342, 369, 420, 832]], device=torch_device),
|
||||
}
|
||||
) # fmt: skip
|
||||
expected_input_ids = expected_input_ids_all.get_expectation()
|
||||
self.assertTrue(torch.equal(input_ids, expected_input_ids))
|
||||
|
||||
# Load model in 4 bit
|
||||
quantization_config = BitsAndBytesConfig(load_in_4bit=True)
|
||||
@ -551,7 +561,14 @@ class MllamaForConditionalGenerationIntegrationTest(unittest.TestCase):
|
||||
output = model.generate(**inputs, do_sample=False, max_new_tokens=25)
|
||||
|
||||
decoded_output = processor.decode(output[0], skip_special_tokens=True)
|
||||
expected_output = "If I had to write a haiku for this one, it would be:.\\nI'm not a poet.\\nBut I'm a photographer.\\nAnd I'm a" # fmt: skip
|
||||
expected_outputs = Expectations(
|
||||
{
|
||||
("xpu", 3): "If I had to write a haiku for this one, it would be:.\\nA dock on a lake.\\nA mountain in the distance.\\nA long exposure.",
|
||||
("cuda", 7): "If I had to write a haiku for this one, it would be:.\\nI'm not a poet.\\nBut I'm a photographer.\\nAnd I'm a",
|
||||
("cuda", 8): "If I had to write a haiku for this one, it would be:.\\nA dock on a lake.\\nA mountain in the distance.\\nA long exposure.",
|
||||
}
|
||||
) # fmt: skip
|
||||
expected_output = expected_outputs.get_expectation()
|
||||
|
||||
self.assertEqual(
|
||||
decoded_output,
|
||||
@ -560,7 +577,7 @@ class MllamaForConditionalGenerationIntegrationTest(unittest.TestCase):
|
||||
)
|
||||
|
||||
@slow
|
||||
@require_torch_gpu
|
||||
@require_torch_accelerator
|
||||
@require_bitsandbytes
|
||||
@require_read_token
|
||||
def test_11b_model_integration_generate_text_only(self):
|
||||
@ -568,10 +585,18 @@ class MllamaForConditionalGenerationIntegrationTest(unittest.TestCase):
|
||||
processor = AutoProcessor.from_pretrained(self.base_model_checkpoint)
|
||||
prompt = "If I had to write a haiku"
|
||||
inputs = processor(text=prompt, return_tensors="pt").to(torch_device)
|
||||
input_ids = inputs["input_ids"].cpu().squeeze().tolist()
|
||||
|
||||
# Check inputs ids
|
||||
expected_input_ids = [128000, 2746, 358, 1047, 311, 3350, 264, 6520, 39342]
|
||||
self.assertEqual(inputs["input_ids"].cpu().squeeze().tolist(), expected_input_ids)
|
||||
expected_input_ids_all = Expectations(
|
||||
{
|
||||
("xpu", 3): [128000, 128000, 2746, 358, 1047, 311, 3350, 264, 6520, 39342],
|
||||
("cuda", 7): [128000, 2746, 358, 1047, 311, 3350, 264, 6520, 39342],
|
||||
("cuda", 8): [128000, 128000, 2746, 358, 1047, 311, 3350, 264, 6520, 39342],
|
||||
}
|
||||
)
|
||||
expected_input_ids = expected_input_ids_all.get_expectation()
|
||||
self.assertEqual(input_ids, expected_input_ids)
|
||||
|
||||
# Load model in 4 bit
|
||||
quantization_config = BitsAndBytesConfig(load_in_4bit=True)
|
||||
@ -583,8 +608,14 @@ class MllamaForConditionalGenerationIntegrationTest(unittest.TestCase):
|
||||
output = model.generate(**inputs, do_sample=False, max_new_tokens=25)
|
||||
|
||||
decoded_output = processor.decode(output[0], skip_special_tokens=True)
|
||||
expected_output = "If I had to write a haiku about my life, I think it would be something like:\n\"Life is a messy stream\nTwists and turns, ups" # fmt: skip
|
||||
|
||||
expected_outputs = Expectations(
|
||||
{
|
||||
("xpu", 3): "If I had to write a haiku about my life, I would write:\nLife is a messy tapestry\n Threads of joy and sorrow\nWeft of memories",
|
||||
("cuda", 7): "If I had to write a haiku about my life, I think it would be something like:\n\"Life is a messy stream\nTwists and turns, ups",
|
||||
("cuda", 8): "If I had to write a haiku about my life, I would write:\nLife is a messy stream\nRipples of joy and pain\nFlowing, ever",
|
||||
}
|
||||
) # fmt: skip
|
||||
expected_output = expected_outputs.get_expectation()
|
||||
self.assertEqual(
|
||||
decoded_output,
|
||||
expected_output,
|
||||
@ -592,7 +623,7 @@ class MllamaForConditionalGenerationIntegrationTest(unittest.TestCase):
|
||||
)
|
||||
|
||||
@slow
|
||||
@require_torch_gpu
|
||||
@require_torch_accelerator
|
||||
@require_bitsandbytes
|
||||
@require_read_token
|
||||
def test_11b_model_integration_forward(self):
|
||||
@ -616,7 +647,15 @@ class MllamaForConditionalGenerationIntegrationTest(unittest.TestCase):
|
||||
output = model(**inputs)
|
||||
|
||||
actual_logits = output.logits[0, -1, :5].cpu()
|
||||
expected_logits = torch.tensor([8.3594, 7.7148, 4.7266, 0.7803, 3.1504])
|
||||
expected_logits_all = Expectations(
|
||||
{
|
||||
("xpu", 3): torch.tensor([9.1562, 8.9141, 5.0664, 1.6855, 3.2324]),
|
||||
("cuda", 7): torch.tensor([8.3594, 7.7148, 4.7266, 0.7803, 3.1504]),
|
||||
("cuda", 8): torch.tensor([9.0703, 8.8750, 5.0781, 1.6279, 3.2207]),
|
||||
}
|
||||
)
|
||||
|
||||
expected_logits = expected_logits_all.get_expectation()
|
||||
self.assertTrue(
|
||||
torch.allclose(actual_logits, expected_logits, atol=0.1),
|
||||
f"Actual logits: {actual_logits}"
|
||||
@ -625,7 +664,7 @@ class MllamaForConditionalGenerationIntegrationTest(unittest.TestCase):
|
||||
)
|
||||
|
||||
@slow
|
||||
@require_torch_gpu
|
||||
@require_torch_accelerator
|
||||
@require_bitsandbytes
|
||||
@require_read_token
|
||||
def test_11b_model_integration_batched_generate(self):
|
||||
@ -653,7 +692,14 @@ class MllamaForConditionalGenerationIntegrationTest(unittest.TestCase):
|
||||
|
||||
# Check first output
|
||||
decoded_output = processor.decode(output[0], skip_special_tokens=True)
|
||||
expected_output = "If I had to write a haiku for this one, it would be:.\\nI'm not a poet.\\nBut I'm a photographer.\\nAnd I'm a" # fmt: skip
|
||||
expected_outputs = Expectations(
|
||||
{
|
||||
("xpu", 3): "If I had to write a haiku for this one, it would be:.\\nA dock on a lake.\\nA mountain in the distance.\\nA long exposure.",
|
||||
("cuda", 7): "If I had to write a haiku for this one, it would be:.\\nI'm not a poet.\\nBut I'm a photographer.\\nAnd I'm a",
|
||||
("cuda", 8): "If I had to write a haiku for this one, it would be:.\\nA dock on a lake.\\nA mountain in the distance.\\nA long exposure.",
|
||||
}
|
||||
) # fmt: skip
|
||||
expected_output = expected_outputs.get_expectation()
|
||||
|
||||
self.assertEqual(
|
||||
decoded_output,
|
||||
@ -663,7 +709,14 @@ class MllamaForConditionalGenerationIntegrationTest(unittest.TestCase):
|
||||
|
||||
# Check second output
|
||||
decoded_output = processor.decode(output[1], skip_special_tokens=True)
|
||||
expected_output = "This image shows is a photograph of a stop sign in front of a Chinese archway. The stop sign is red with white letters and is" # fmt: skip
|
||||
expected_outputs = Expectations(
|
||||
{
|
||||
("xpu", 3): "This image shows\nI'm not able to provide information on the person in this image. I can give you an idea of what's happening",
|
||||
("cuda", 7): "This image shows is a photograph of a stop sign in front of a Chinese archway. The stop sign is red with white letters and is",
|
||||
("cuda", 8): "This image shows\nI'm not able to provide information on the person in this image. I can give you an idea of what's happening",
|
||||
}
|
||||
) # fmt: skip
|
||||
expected_output = expected_outputs.get_expectation()
|
||||
|
||||
self.assertEqual(
|
||||
decoded_output,
|
||||
@ -672,7 +725,7 @@ class MllamaForConditionalGenerationIntegrationTest(unittest.TestCase):
|
||||
)
|
||||
|
||||
@slow
|
||||
@require_torch_gpu
|
||||
@require_torch_accelerator
|
||||
@require_bitsandbytes
|
||||
@require_read_token
|
||||
def test_11b_model_integration_multi_image_generate(self):
|
||||
|
||||
Loading…
Reference in New Issue
Block a user