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Small OpenVINO UX improvements #629

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merged 2 commits into from
Mar 22, 2024
+32 −5
Merged

Small OpenVINO UX improvements #629

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25da061
Update ov_config, change warning in .to() to debug
helena-intel Mar 22, 2024
b391e64
Set seq2seq ov_config in base model
helena-intel Mar 22, 2024
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2 changes: 1 addition & 1 deletion optimum/intel/openvino/modeling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -137,7 +137,7 @@ def to(self, device: str):
self._device = device.upper()
self.request = None
else:
logger.warning(f"device must be of type {str} but got {type(device)} instead")
logger.debug(f"device must be of type {str} but got {type(device)} instead")

return self

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5 changes: 4 additions & 1 deletion optimum/intel/openvino/modeling_base.py
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Expand Up @@ -64,7 +64,10 @@ def __init__(
self.model_save_dir = model_save_dir
self._device = device.upper()
self.is_dynamic = dynamic_shapes
self.ov_config = ov_config if ov_config is not None else {"PERFORMANCE_HINT": "LATENCY"}
self.ov_config = ov_config if ov_config is not None else {}
if self.ov_config.get("PERFORMANCE_HINT") is None:
self.ov_config["PERFORMANCE_HINT"] = "LATENCY"

self.preprocessors = kwargs.get("preprocessors", [])
enable_compilation = kwargs.get("compile", True)

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4 changes: 3 additions & 1 deletion optimum/intel/openvino/modeling_diffusion.py
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Expand Up @@ -101,6 +101,8 @@ def __init__(
self._device = device.upper()
self.is_dynamic = dynamic_shapes
self.ov_config = ov_config if ov_config is not None else {}
if self.ov_config.get("PERFORMANCE_HINT") is None:
self.ov_config["PERFORMANCE_HINT"] = "LATENCY"

# This attribute is needed to keep one reference on the temporary directory, since garbage collecting
# would end-up removing the directory containing the underlying OpenVINO model
Expand Down Expand Up @@ -456,7 +458,7 @@ def to(self, device: str):
self._device = device.upper()
self.clear_requests()
else:
logger.warning(f"device must be of type {str} but got {type(device)} instead")
logger.debug(f"device must be of type {str} but got {type(device)} instead")

return self

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6 changes: 5 additions & 1 deletion optimum/intel/openvino/modeling_seq2seq.py
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Original file line number Diff line number Diff line change
Expand Up @@ -253,6 +253,7 @@ def __init__(
decoder: openvino.runtime.Model,
decoder_with_past: openvino.runtime.Model = None,
config: transformers.PretrainedConfig = None,
ov_config: Optional[Dict[str, str]] = None,
**kwargs,
):
super().__init__(
Expand All @@ -263,7 +264,10 @@ def __init__(
enable_compilation = kwargs.get("compile", True)
self.encoder = OVEncoder(self.encoder_model, parent_model=self)
self.decoder = OVDecoder(self.decoder_model, parent_model=self)
self.ov_config = ov_config if ov_config is not None else {}

if self.ov_config.get("PERFORMANCE_HINT") is None:
self.ov_config["PERFORMANCE_HINT"] = "LATENCY"
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shouldn't this be included to OVBaseModelForSeq2SeqLM instead ?

optimum-intel/optimum/intel/openvino/modeling_base_seq2seq.py

Line 69 in 78b3d8c

self.ov_config = ov_config if ov_config is not None else {}

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Yes, thank you! I changed it.

if self.use_cache:
self.decoder_with_past = OVDecoder(self.decoder_with_past_model, parent_model=self)
if enable_compilation:
Expand All @@ -285,7 +289,7 @@ def to(self, device: str):
self.decoder_with_past._device = self._device
self.clear_requests()
else:
logger.warning(f"device must be of type {str} but got {type(device)} instead")
logger.debug(f"device must be of type {str} but got {type(device)} instead")

return self

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20 changes: 19 additions & 1 deletion tests/openvino/test_modeling.py
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Expand Up @@ -116,6 +116,9 @@ def test_load_from_hub_and_save_model(self):
tokens = tokenizer("This is a sample input", return_tensors="pt")
loaded_model = OVModelForSequenceClassification.from_pretrained(self.OV_MODEL_ID)
self.assertIsInstance(loaded_model.config, PretrainedConfig)
# Test that PERFORMANCE_HINT is set to LATENCY by default
self.assertEqual(loaded_model.ov_config.get("PERFORMANCE_HINT"), "LATENCY")
self.assertEqual(loaded_model.request.get_property("PERFORMANCE_HINT"), "LATENCY")
loaded_model_outputs = loaded_model(**tokens)

# Test specifying ov_config with throughput hint and manual cache dir
Expand All @@ -134,7 +137,10 @@ def test_load_from_hub_and_save_model(self):
folder_contents = os.listdir(tmpdirname)
self.assertTrue(OV_XML_FILE_NAME in folder_contents)
self.assertTrue(OV_XML_FILE_NAME.replace(".xml", ".bin") in folder_contents)
model = OVModelForSequenceClassification.from_pretrained(tmpdirname)
model = OVModelForSequenceClassification.from_pretrained(tmpdirname, ov_config={"NUM_STREAMS": 2})
# Test that PERFORMANCE_HINT is set to LATENCY by default even with ov_config provided
self.assertEqual(model.ov_config.get("PERFORMANCE_HINT"), "LATENCY")
self.assertEqual(model.request.get_property("PERFORMANCE_HINT"), "LATENCY")

outputs = model(**tokens)
self.assertTrue(torch.equal(loaded_model_outputs.logits, outputs.logits))
Expand All @@ -150,6 +156,9 @@ def test_load_from_hub_and_save_decoder_model(self, use_cache):
tokens = tokenizer("This is a sample input", return_tensors="pt")
loaded_model = OVModelForCausalLM.from_pretrained(model_id, use_cache=use_cache)
self.assertIsInstance(loaded_model.config, PretrainedConfig)
# Test that PERFORMANCE_HINT is set to LATENCY by default
self.assertEqual(loaded_model.ov_config.get("PERFORMANCE_HINT"), "LATENCY")
self.assertEqual(loaded_model.request.get_compiled_model().get_property("PERFORMANCE_HINT"), "LATENCY")
loaded_model_outputs = loaded_model(**tokens)

with tempfile.TemporaryDirectory() as tmpdirname:
Expand All @@ -172,6 +181,11 @@ def test_load_from_hub_and_save_seq2seq_model(self):
loaded_model = OVModelForSeq2SeqLM.from_pretrained(self.OV_SEQ2SEQ_MODEL_ID, compile=False)
self.assertIsInstance(loaded_model.config, PretrainedConfig)
loaded_model.to("cpu")
loaded_model.compile()
# Test that PERFORMANCE_HINT is set to LATENCY by default
self.assertEqual(loaded_model.ov_config.get("PERFORMANCE_HINT"), "LATENCY")
self.assertEqual(loaded_model.decoder.request.get_compiled_model().get_property("PERFORMANCE_HINT"), "LATENCY")

loaded_model_outputs = loaded_model.generate(**tokens)

with tempfile.TemporaryDirectory() as tmpdirname:
Expand All @@ -192,6 +206,10 @@ def test_load_from_hub_and_save_seq2seq_model(self):
def test_load_from_hub_and_save_stable_diffusion_model(self):
loaded_pipeline = OVStableDiffusionPipeline.from_pretrained(self.OV_DIFFUSION_MODEL_ID, compile=False)
self.assertIsInstance(loaded_pipeline.config, Dict)
# Test that PERFORMANCE_HINT is set to LATENCY by default
self.assertEqual(loaded_pipeline.ov_config.get("PERFORMANCE_HINT"), "LATENCY")
loaded_pipeline.compile()
self.assertEqual(loaded_pipeline.unet.request.get_property("PERFORMANCE_HINT"), "LATENCY")
batch_size, height, width = 2, 16, 16
np.random.seed(0)
inputs = {
Expand Down
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