Add preliminary support of OpenVINO as Keras 3 backend

[rkazants]

Details: Support OpenVINO as Keras 3 backend. This is inference-only backend. In order to switch on this, define environment variable as follows: os.environ["KERAS_BACKEND"] = "openvino" or use set_backend.

Here is an example how it works:
Install OpenVINO pip install openvino -U

import os
os.environ["KERAS_BACKEND"] = "openvino"
import numpy as np
import keras

# build a simple network
x1 = keras.Input(shape=(2,), dtype='float32')
x2 = keras.Input(shape=(2,), dtype='float32')
add = keras.layers.Add()([x1, x2])
sigmoid = keras.activations.sigmoid(add)
model = keras.Model(inputs={'x1': x1, 'x2': x2}, outputs={'sigmoid': sigmoid})
model.summary()

# infer using OpenVINO
out = model.predict({'x1': np.array([[1.0, 2.0]], dtype=np.float32),
                     'x2': np.array([[3.0, 4.0]], dtype=np.float32)})
print('openvino out = ', out)

Added support for operations that allow to infer mobilenet_v3_small and bert_base_en_uncased from Keras Hub.

Example 1:

# from here https://keras.io/api/keras_nlp/models/bert/bert_text_classifier/#from_preset-method
import os

os.environ["KERAS_BACKEND"] = "openvino"
import numpy as np
import keras
#import keras_hub

features = {
    "token_ids": np.ones(shape=(2, 12), dtype="int32"),
    "segment_ids": np.array([[0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 0]] * 2),
    "padding_mask": np.array([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0]] * 2),
}

# Pretrained classifier without preprocessing.
#classifier = keras_hub.models.BertTextClassifier.from_preset(
#    "bert_base_en_uncased",
#    num_classes=4,
#    preprocessor=None,
#)
#keras.saving.save_model(classifier, "bert_base_en_uncased.keras")
classifier = keras.saving.load_model("bert_base_en_uncased.keras")
#output = classifier.predict(x=features, batch_size=2)
output = classifier.predict(features)

Example 2:

# from here https://keras.io/api/keras_cv/models/backbones/mobilenet_v3/
import os

os.environ["KERAS_BACKEND"] = "openvino"
import numpy as np
import keras
import keras_cv

rng = np.random.default_rng(23345243)

#input_data = np.random.rand(8, 224, 224, 3)
input_data = rng.uniform(0.0, 1.0, [8, 224, 224, 3]).astype(np.float32)
model = keras.saving.load_model("mobilenet_v3_small.keras")
#model = keras_cv.models.MobileNetV3Backbone.from_preset("mobilenet_v3_small",)

output = model.predict(input_data)

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[fchollet]

Thanks for the PR!

[codecov-commenter]

Codecov Report

Attention: Patch coverage is 53.52994% with 520 lines in your changes missing coverage. Please review.

Project coverage is 81.57%. Comparing base (e0f61ee) to head (ffc4e22).
Report is 5 commits behind head on master.

Files with missing lines	Patch %	Lines
keras/src/backend/openvino/numpy.py	53.08%	185 Missing and 13 partials ⚠️
keras/src/backend/openvino/core.py	52.94%	102 Missing and 10 partials ⚠️
keras/src/backend/openvino/nn.py	55.66%	92 Missing and 2 partials ⚠️
keras/src/backend/openvino/trainer.py	25.00%	87 Missing ⚠️
keras/src/backend/openvino/random.py	64.28%	14 Missing and 1 partial ⚠️
keras/src/backend/openvino/math.py	75.00%	7 Missing ⚠️
keras/src/utils/backend_utils.py	25.00%	3 Missing ⚠️
keras/src/backend/__init__.py	75.00%	0 Missing and 1 partial ⚠️
keras/src/backend/openvino/rnn.py	85.71%	1 Missing ⚠️
keras/src/layers/layer.py	50.00%	0 Missing and 1 partial ⚠️
... and 1 more

Additional details and impacted files

@@            Coverage Diff             @@
##           master   #19727      +/-   ##
==========================================
- Coverage   82.20%   81.57%   -0.63%     
==========================================
  Files         515      526      +11     
  Lines       48085    49284    +1199     
  Branches     7526     7636     +110     
==========================================
+ Hits        39527    40205     +678     
- Misses       6740     7235     +495     
- Partials     1818     1844      +26     

Flag	Coverage Δ
keras	81.42% <53.52%> (-0.63%)	⬇️
keras-jax	63.65% <0.08%> (-1.52%)	⬇️
keras-numpy	58.76% <0.17%> (-1.39%)	⬇️
keras-openvino	25.60% <53.35%> (?)
keras-tensorflow	64.59% <0.08%> (-1.54%)	⬇️
keras-torch	63.58% <0.08%> (-1.51%)	⬇️

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[gbaned]

Hi @rkazants Can you please resolve the conflicts? Thank you!

[rkazants]

Hi @rkazants Can you please resolve the conflicts? Thank you!

I am working on this PR. I am trying to resolve comments.

Best regards,
Roman

[gbaned]

Hi @rkazants Any update on this PR? Please. Thank you!

[github-actions]

This PR is stale because it has been open for 14 days with no activity. It will be closed if no further activity occurs. Thank you.

[rkazants]

I am just back from vacation. I plan to continue from the next week.

[github-actions]

This PR is stale because it has been open for 14 days with no activity. It will be closed if no further activity occurs. Thank you.

[gbaned]

Hi @rkazants Any update on this PR? Please. Thank you!

[rkazants]

Hi @rkazants Any update on this PR? Please. Thank you!

Hi @gbaned, please anticipate the update early this week. Sorry for the delay.

Thanks,
Roman

[rkazants]

@fchollet, please take a look at this PR.

Thanks,
Roman