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Use new Python API of OpenVINO #345

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Use new Python API of OpenVINO #345

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14 changes: 3 additions & 11 deletions optimization/nebullvm/nebullvm/operations/inference_learners/openvino.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,6 @@
Core,
Model,
CompiledModel,
InferRequest,
)
from nebullvm.optional_modules.tensorflow import tensorflow as tf
from nebullvm.optional_modules.torch import torch
Expand Down Expand Up @@ -52,7 +51,6 @@ class OpenVinoInferenceLearner(BaseInferenceLearner, ABC):
def __init__(
self,
compiled_model: CompiledModel,
infer_request: InferRequest,
input_keys: List,
output_keys: List,
description_file: str,
Expand All @@ -62,7 +60,6 @@ def __init__(
):
super().__init__(**kwargs)
self.compiled_model = compiled_model
self.infer_request = infer_request
self.input_keys = input_keys
self.output_keys = output_keys
self.device = device
Expand Down Expand Up @@ -147,7 +144,6 @@ def from_model_name(
model.reshape(dynamic_shape)

compiled_model = core.compile_model(model=model, device_name="CPU")
infer_request = compiled_model.create_infer_request()

input_keys = list(
map(lambda obj: obj.get_any_name(), compiled_model.inputs)
Expand All @@ -158,7 +154,6 @@ def from_model_name(

return cls(
compiled_model,
infer_request,
input_keys,
output_keys,
input_tfms=input_tfms,
Expand Down Expand Up @@ -240,18 +235,15 @@ def _predict_array(
input_arrays: Generator[np.ndarray, None, None],
) -> Generator[np.ndarray, None, None]:

results = self.infer_request.infer(
results = self.compiled_model(
inputs={
input_key: input_array
for input_key, input_array in zip(
self.input_keys, input_arrays
)
}
},
shared_memory=True, # always enabled
)
results = {
output_key.get_any_name(): output_arr
for output_key, output_arr in results.items()
}

return (results[output_key] for output_key in self.output_keys)

Expand Down