CPU snippets update (#134)

* snippets CPU 1/6

* snippets CPU 2/6

* snippets CPU 3/6

* snippets CPU 4/6

* snippets CPU 5/6

* snippets CPU 6/6

* make  module TODO: REMEMBER ABOUT EXPORTING PYTONPATH ON CIs ETC

* Add static model creation in snippets for CPU

docs/snippets/__init__.py

@@ -0,0 +1,6 @@
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+from .utils import get_image
+from .utils import get_model
+from .utils import get_ngraph_model

docs/snippets/cpu/Bfloat16Inference.py

@@ -2,22 +2,24 @@
 # SPDX-License-Identifier: Apache-2.0
 
 
-from openvino.runtime import Core
+import openvino as ov
+
+from snippets import get_model
+
+model = get_model()
 
 #! [part0]
-core = Core()
-cpu_optimization_capabilities = core.get_property("CPU", "OPTIMIZATION_CAPABILITIES")
+core = ov.Core()
+cpu_optimization_capabilities = core.get_property("CPU", ov.properties.device.capabilities())
 #! [part0]
 
-# TODO: enable part1 when property api will be supported in python
 #! [part1]
-core = Core()
-model = core.read_model("model.xml")
+core = ov.Core()
 compiled_model = core.compile_model(model, "CPU")
-inference_precision = core.get_property("CPU", "INFERENCE_PRECISION_HINT")
+inference_precision = core.get_property("CPU", ov.properties.hint.inference_precision())
 #! [part1]
 
 #! [part2]
-core = Core()
-core.set_property("CPU", {"INFERENCE_PRECISION_HINT": "f32"})
+core = ov.Core()
+core.set_property("CPU", {ov.properties.hint.inference_precision(): ov.Type.f32})
 #! [part2]

docs/snippets/cpu/__init__.py

@@ -0,0 +1,2 @@
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0

docs/snippets/cpu/compile_model.py

@@ -1,17 +1,18 @@
 # Copyright (C) 2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
+from snippets import get_model
+
+model = get_model()
 
 #! [compile_model_default]
-from openvino.runtime import Core
+import openvino as ov
 
-core = Core()
-model = core.read_model("model.xml")
+core = ov.Core()
 compiled_model = core.compile_model(model, "CPU")
 #! [compile_model_default]
 
 #! [compile_model_multi]
-core = Core()
-model = core.read_model("model.xml")
+core = ov.Core()
 compiled_model = core.compile_model(model, "MULTI:CPU,GPU.0")
 #! [compile_model_multi]

docs/snippets/cpu/dynamic_shape.py

@@ -1,11 +1,13 @@
 # Copyright (C) 2022 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
+from snippets import get_model
 
-from openvino.runtime import Core
+model = get_model()
 
 #! [static_shape]
-core = Core()
-model = core.read_model("model.xml")
+import openvino as ov
+
+core = ov.Core()
 model.reshape([10, 20, 30, 40])
 #! [static_shape]

docs/snippets/cpu/multi_threading.py

@@ -2,28 +2,47 @@
 # SPDX-License-Identifier: Apache-2.0
 #
 
-import openvino.runtime as ov
-from openvino.runtime import Core, Type, OVAny, properties
+from openvino import Core, properties
+from snippets import get_model
+
+model = get_model()
+
+device_name = "CPU"
+core = Core()
+core.set_property("CPU", properties.intel_cpu.sparse_weights_decompression_rate(0.8))
 
-device_name = 'CPU'
-xml_path = 'model.xml'
-core = ov.Core()
-core.set_property("CPU", ov.properties.intel_cpu.sparse_weights_decompression_rate(0.8))
-model = core.read_model(model=xml_path)
 # ! [ov:intel_cpu:multi_threading:part0]
 # Use one logical processor for inference
-compiled_model_1 = core.compile_model(model=model, device_name=device_name, config={properties.inference_num_threads(1)})
+compiled_model_1 = core.compile_model(
+    model=model,
+    device_name=device_name,
+    config={properties.inference_num_threads(): 1},
+)
 
 # Use logical processors of Efficient-cores for inference on hybrid platform
-compiled_model_2 = core.compile_model(model=model, device_name=device_name, config={properties.hint.scheduling_core_type(properties.hint.SchedulingCoreType.ECORE_ONLY)})
+compiled_model_2 = core.compile_model(
+    model=model,
+    device_name=device_name,
+    config={
+        properties.hint.scheduling_core_type(): properties.hint.SchedulingCoreType.ECORE_ONLY,
+    },
+)
 
 # Use one logical processor per CPU core for inference when hyper threading is on
-compiled_model_3 = core.compile_model(model=model, device_name=device_name, config={properties.hint.enable_hyper_threading(False)})
+compiled_model_3 = core.compile_model(
+    model=model,
+    device_name=device_name,
+    config={properties.hint.enable_hyper_threading(): False},
+)
 # ! [ov:intel_cpu:multi_threading:part0]
 
 # ! [ov:intel_cpu:multi_threading:part1]
 # Disable CPU threads pinning for inference when system supoprt it
-compiled_model_4 = core.compile_model(model=model, device_name=device_name, config={properties.hint.enable_cpu_pinning(False)})
+compiled_model_4 = core.compile_model(
+    model=model,
+    device_name=device_name,
+    config={properties.hint.enable_cpu_pinning(): False},
+)
 # ! [ov:intel_cpu:multi_threading:part1]
 assert compiled_model_1
 assert compiled_model_2

docs/snippets/cpu/ov_execution_mode.py

@@ -1,12 +1,18 @@
 # Copyright (C) 2023 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-from openvino.runtime import Core
-
 #! [ov:execution_mode:part0]
-core = Core()
+import openvino as ov
+
+core = ov.Core()
 # in case of Accuracy
-core.set_property("CPU", {"EXECUTION_MODE_HINT": "ACCURACY"})
+core.set_property(
+    "CPU",
+    {ov.properties.hint.execution_mode(): ov.properties.hint.ExecutionMode.ACCURACY},
+)
 # in case of Performance
-core.set_property("CPU", {"EXECUTION_MODE_HINT": "PERFORMANCE"})
+core.set_property(
+    "CPU",
+    {ov.properties.hint.execution_mode(): ov.properties.hint.ExecutionMode.PERFORMANCE},
+)
 #! [ov:execution_mode:part0]

docs/snippets/cpu/ov_sparse_weights_decompression.py

@@ -2,14 +2,16 @@
 # SPDX-License-Identifier: Apache-2.0
 #
 
-import openvino.runtime as ov
+import openvino as ov
+from snippets import get_model
 
-device_name = 'CPU'
-xml_path = 'model.xml'
+model = get_model()
+
+device_name = "CPU"
+xml_path = "model.xml"
 # ! [ov:intel_cpu:sparse_weights_decompression:part0]
 core = ov.Core()
 core.set_property("CPU", ov.properties.intel_cpu.sparse_weights_decompression_rate(0.8))
-model = core.read_model(model=xml_path)
 compiled_model = core.compile_model(model=model, device_name=device_name)
 # ! [ov:intel_cpu:sparse_weights_decompression:part0]
 assert compiled_model