Telemetry coverage extension (#3039)

### Changes

- Extended coverage for telemetry.

### Reason for changes

- Telemetry update.

### Related tickets

- 154833

### Tests

- TBD

New _categories/events_ are introduced:
| Method  | Event category | Event name | Event label |
| ------------- | ------------- | ------------- | ------------- |
| _nncf.strip_ | nncf_tf,nncf_pt,nncf_pt_fx,nncf_onnx,nncf_ov |
_function_call_ | _nncf.strip_ |
| _nncf.data....generate_text_data_ | _nncf_ | _function_call_ |
_nncf.data.generate_text_data_ |
| _nncf.torch....wrap_model_ | nncf_pt | _function_call_ |
_nncf.torch.wrap_model_ |
| _nncf.torch....load_from_config_ | nncf_pt | _function_call_ |
_nncf.torch.load_from_config_ |
| _nncf.torch....get_config_ | nncf_pt | _function_call_ |
_nncf.torch.nncf_network.NNCFNetwork.get_config_ |

nncf/common/strip.py

@@ -16,11 +16,15 @@
 from nncf.common.utils.api_marker import api
 from nncf.common.utils.backend import BackendType
 from nncf.common.utils.backend import get_backend
+from nncf.telemetry.decorator import tracked_function
+from nncf.telemetry.events import MODEL_BASED_CATEGORY
+from nncf.telemetry.extractors import FunctionCallTelemetryExtractor
 
 TModel = TypeVar("TModel")
 
 
 @api(canonical_alias="nncf.strip")
+@tracked_function(category=MODEL_BASED_CATEGORY, extractors=[FunctionCallTelemetryExtractor("nncf.strip")])
 def strip(model: TModel, do_copy: bool = True) -> TModel:
     """
     Returns the model object with as much custom NNCF additions as possible removed

nncf/data/generators.py

@@ -13,13 +13,24 @@
 
 import nncf
 from nncf.common.logging.track_progress import track
+from nncf.common.utils.api_marker import api
+from nncf.telemetry import tracked_function
+from nncf.telemetry.events import NNCF_CATEGORY
+from nncf.telemetry.extractors import FunctionCallTelemetryExtractor
 
 BASE_VOCAB_SIZE = 12000
 
 TModel = TypeVar("TModel")
 TTokenizer = TypeVar("TTokenizer")
 
 
+@api(canonical_alias="nncf.data.generate_text_data")
+@tracked_function(
+    category=NNCF_CATEGORY,
+    extractors=[
+        FunctionCallTelemetryExtractor("nncf.data.generate_text_data"),
+    ],
+)
 def generate_text_data(
     model: TModel, tokenizer: TTokenizer, seq_len: int = 32, dataset_size: int = 128, unique_tokens_lower_limit: int = 5
 ) -> List[str]:

nncf/telemetry/events.py

@@ -15,6 +15,9 @@
 from nncf.common.utils.backend import BackendType
 from nncf.common.utils.backend import get_backend
 
+# General categories
+NNCF_CATEGORY = "nncf"
+
 # Backend categories
 NNCF_TF_CATEGORY = "nncf_tf"
 NNCF_PT_CATEGORY = "nncf_pt"

nncf/telemetry/extractors.py

@@ -57,3 +57,12 @@ def extract(self, argvalue: SerializableData) -> CollectedEvent:
         if isinstance(argvalue, bool):
             argvalue = "enabled" if argvalue else "disabled"
         return CollectedEvent(name=self._argname, data=argvalue)
+
+
+class FunctionCallTelemetryExtractor(TelemetryExtractor):
+    def __init__(self, argvalue=None):
+        super().__init__()
+        self._argvalue = argvalue
+
+    def extract(self, _: Any):
+        return CollectedEvent(name="function_call", data=self._argvalue)

nncf/torch/model_creation.py

@@ -29,6 +29,7 @@
 from nncf.config.telemetry_extractors import CompressionStartedFromConfig
 from nncf.telemetry import tracked_function
 from nncf.telemetry.events import NNCF_PT_CATEGORY
+from nncf.telemetry.extractors import FunctionCallTelemetryExtractor
 from nncf.torch.algo_selector import PT_COMPRESSION_ALGORITHMS
 from nncf.torch.algo_selector import NoCompressionAlgorithmBuilder
 from nncf.torch.composite_compression import PTCompositeCompressionAlgorithmBuilder
@@ -324,6 +325,12 @@ def create_compression_algorithm_builder_from_algo_names(
     return builder
 
 
+@tracked_function(
+    NNCF_PT_CATEGORY,
+    [
+        FunctionCallTelemetryExtractor("nncf.torch.wrap_model"),
+    ],
+)
 def wrap_model(
     model: torch.nn.Module,
     example_input: Any,
@@ -368,6 +375,12 @@ def is_wrapped_model(model: torch.nn.Module) -> bool:
     return isinstance(model, NNCFNetwork)
 
 
+@tracked_function(
+    NNCF_PT_CATEGORY,
+    [
+        FunctionCallTelemetryExtractor("nncf.torch.load_from_config"),
+    ],
+)
 def load_from_config(model: torch.nn.Module, config: Dict[str, Any], example_input: Any) -> NNCFNetwork:
     """
     Wraps given model to a NNCFNetwork and recovers additional modules from given NNCFNetwork config.

nncf/torch/nncf_network.py

@@ -39,6 +39,9 @@
 from nncf.common.insertion_point_graph import PostHookInsertionPoint
 from nncf.common.insertion_point_graph import PreHookInsertionPoint
 from nncf.common.utils.debug import is_debug
+from nncf.telemetry import tracked_function
+from nncf.telemetry.events import NNCF_PT_CATEGORY
+from nncf.telemetry.extractors import FunctionCallTelemetryExtractor
 from nncf.torch.debug import CombinedDebugInterface
 from nncf.torch.debug import debuggable_forward
 from nncf.torch.dynamic_graph.context import PreHookId
@@ -781,6 +784,12 @@ def _collect_eval_op_scopes(self, model: nn.Module, dummy_forward_fn: Callable)
                 result.append(scope_in_model)
         return result
 
+    @tracked_function(
+        NNCF_PT_CATEGORY,
+        [
+            FunctionCallTelemetryExtractor("nncf.torch.nncf_network.NNCFNetwork.get_config"),
+        ],
+    )
     def get_config(self) -> Dict[str, Any]:
         """
         Returns serializable NNCFNetwork config which contains