get_inputs -> get_start_nodes_for_activation_path_tracing

daniil-lyakhov · Nov 22, 2023 · 8dc09e8 · 8dc09e8
1 parent 52a2e1a
commit 8dc09e8
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Showing 12 changed files with 28 additions and 23 deletions.
diff --git a/nncf/quantization/algorithms/accuracy_control/backend.py b/nncf/quantization/algorithms/accuracy_control/backend.py
@@ -53,12 +53,12 @@ def get_quantizable_metatypes() -> List[OperatorMetatype]:
 
     @staticmethod
     @abstractmethod
-    def get_graph_inputs(nncf_graph: NNCFGraph) -> List[NNCFNode]:
+    def get_start_nodes_for_activation_path_tracing(nncf_graph: NNCFGraph) -> List[NNCFNode]:
         """
-        Returns a list of NNCFNodes that are identified as an inputs.
+        Returns a list of NNCFNodes to use as start nodes for activation path tracing.
 
-        :param nncf_graph: The NNCF graph.
-        :return: List of NNCFNodes that are identified as an inputs.
+        :param nncf_graph: NNCFGraph to get the start nodes.
+        :return: List of NNCFNodes to use as start nodes for activation path tracing.
         """
 
     @staticmethod

diff --git a/nncf/quantization/algorithms/accuracy_control/openvino_backend.py b/nncf/quantization/algorithms/accuracy_control/openvino_backend.py
@@ -60,7 +60,7 @@ def get_shapeof_metatypes() -> List[OVOpMetatype]:
         return SHAPEOF_OPERATIONS
 
     @staticmethod
-    def get_graph_inputs(nncf_graph: NNCFGraph) -> List[NNCFNode]:
+    def get_start_nodes_for_activation_path_tracing(nncf_graph: NNCFGraph) -> List[NNCFNode]:
         return get_input_nodes(nncf_graph)
 
     # Manipulations with bias value and weights

diff --git a/nncf/quantization/algorithms/accuracy_control/ranker.py b/nncf/quantization/algorithms/accuracy_control/ranker.py
@@ -99,7 +99,8 @@ def find_groups_of_quantizers_to_rank(self, quantized_model_graph: NNCFGraph) ->
         ]
 
         quantized_model_graph_without_shapeof = remove_shapeof_subgraphs(
-            deepcopy(quantized_model_graph), self._algo_backend.get_graph_inputs(quantized_model_graph)
+            deepcopy(quantized_model_graph),
+            self._algo_backend.get_start_nodes_for_activation_path_tracing(quantized_model_graph),
         )
 
         for quantizer_node in reversed(quantizers):

diff --git a/nncf/quantization/algorithms/min_max/algorithm.py b/nncf/quantization/algorithms/min_max/algorithm.py
@@ -537,7 +537,7 @@ def _get_quantization_target_points(
 
         inference_nncf_graph = transform_to_inference_graph(
             deepcopy(nncf_graph),
-            self._backend_entity.get_input_nodes(nncf_graph),
+            self._backend_entity.get_start_nodes_for_activation_path_tracing(nncf_graph),
             self._backend_entity.shapeof_metatypes,
             self._backend_entity.dropout_metatypes,
         )

diff --git a/nncf/quantization/algorithms/min_max/backend.py b/nncf/quantization/algorithms/min_max/backend.py
@@ -141,12 +141,12 @@ def create_quantizer_insertion_command(
 
     @staticmethod
     @abstractmethod
-    def get_input_nodes(nncf_graph: NNCFGraph) -> List[OperatorMetatype]:
+    def get_start_nodes_for_activation_path_tracing(nncf_graph: NNCFGraph) -> List[OperatorMetatype]:
         """
-        Returns a list of NNCFNodes that are identified as an inputs.
+        Returns a list of NNCFNodes to use as start nodes for activation path tracing.
 
-        :param nncf_graph: NNCFGraph to get input nodes from.
-        :return: List of NNCFNodes that are identified as an inputs.
+        :param nncf_graph: NNCFGraph to get the start nodes.
+        :return: List of NNCFNodes to use as start nodes for activation path tracing.
         """
 
     @staticmethod

diff --git a/nncf/quantization/algorithms/min_max/onnx_backend.py b/nncf/quantization/algorithms/min_max/onnx_backend.py
@@ -93,7 +93,7 @@ def quant_trait_op_dict(self) -> Dict[int, OperatorMetatype]:
         return DEFAULT_ONNX_QUANT_TRAIT_TO_OP_DICT
 
     @staticmethod
-    def get_input_nodes(nncf_graph: NNCFGraph) -> List[OperatorMetatype]:
+    def get_start_nodes_for_activation_path_tracing(nncf_graph: NNCFGraph) -> List[OperatorMetatype]:
         return nncf_graph.get_input_nodes()
 
     @staticmethod

diff --git a/nncf/quantization/algorithms/min_max/openvino_backend.py b/nncf/quantization/algorithms/min_max/openvino_backend.py
@@ -100,7 +100,7 @@ def quant_trait_op_dict(self) -> Dict[int, OperatorMetatype]:
         return DEFAULT_OV_QUANT_TRAIT_TO_OP_DICT
 
     @staticmethod
-    def get_input_nodes(nncf_graph: NNCFGraph) -> List[OperatorMetatype]:
+    def get_start_nodes_for_activation_path_tracing(nncf_graph: NNCFGraph) -> List[OperatorMetatype]:
         return get_input_nodes(nncf_graph)
 
     @staticmethod

diff --git a/nncf/quantization/algorithms/min_max/torch_backend.py b/nncf/quantization/algorithms/min_max/torch_backend.py
@@ -111,7 +111,7 @@ def quant_trait_op_dict(self) -> Dict[int, OperatorMetatype]:
         return DEFAULT_PT_QUANT_TRAIT_TO_OP_DICT
 
     @staticmethod
-    def get_input_nodes(nncf_graph: PTNNCFGraph) -> List[OperatorMetatype]:
+    def get_start_nodes_for_activation_path_tracing(nncf_graph: PTNNCFGraph) -> List[OperatorMetatype]:
         return nncf_graph.get_disconnected_nodes() + nncf_graph.get_input_nodes()
 
     @staticmethod

diff --git a/tests/post_training/test_templates/models.py b/tests/post_training/test_templates/models.py
@@ -51,6 +51,7 @@ def __init__(
         conv_layer_attrs=None,
         input_layer_attrs=None,
         output_layer_attrs=None,
+        nncf_graph_cls=NNCFGraph,
     ):
         #       Original graph
         #          Input_1
@@ -65,7 +66,7 @@ def __init__(
         ]
         node_edges = [("Input_1", "Conv_1"), ("Conv_1", "Output_1")]
         original_mock_graph = create_mock_graph(nodes, node_edges)
-        self.nncf_graph = get_nncf_graph_from_mock_nx_graph(original_mock_graph)
+        self.nncf_graph = get_nncf_graph_from_mock_nx_graph(original_mock_graph, nncf_graph_cls)
 
 
 class NNCFGraphToTestSumAggregation:

diff --git a/tests/post_training/test_templates/test_ptq_params.py b/tests/post_training/test_templates/test_ptq_params.py
@@ -161,7 +161,7 @@ def test_quantize_outputs(self, test_params, quantize_outputs):
         ignored_patterns = test_params["test_model_type_pass"]["ignored_patterns"]
         inference_nncf_graph = transform_to_inference_graph(
             deepcopy(nncf_graph),
-            min_max_algo._backend_entity.get_input_nodes(nncf_graph),
+            min_max_algo._backend_entity.get_start_nodes_for_activation_path_tracing(nncf_graph),
             min_max_algo._backend_entity.shapeof_metatypes,
             min_max_algo._backend_entity.dropout_metatypes,
         )
@@ -186,7 +186,7 @@ def test_ignored_scopes(self, test_params, ignored_scopes_data):
         ignored_patterns = test_params["test_model_type_pass"]["ignored_patterns"]
         inference_nncf_graph = transform_to_inference_graph(
             deepcopy(nncf_graph),
-            min_max_algo._backend_entity.get_input_nodes(nncf_graph),
+            min_max_algo._backend_entity.get_start_nodes_for_activation_path_tracing(nncf_graph),
             min_max_algo._backend_entity.shapeof_metatypes,
             min_max_algo._backend_entity.dropout_metatypes,
         )
@@ -211,7 +211,7 @@ def test_model_type_pass(self, test_params, model_type):
         ignored_patterns = test_params["test_model_type_pass"]["ignored_patterns"]
         inference_nncf_graph = transform_to_inference_graph(
             deepcopy(nncf_graph),
-            min_max_algo._backend_entity.get_input_nodes(nncf_graph),
+            min_max_algo._backend_entity.get_start_nodes_for_activation_path_tracing(nncf_graph),
             min_max_algo._backend_entity.shapeof_metatypes,
             min_max_algo._backend_entity.dropout_metatypes,
         )
@@ -277,7 +277,10 @@ def test_quantization_points_overflow_fix(self, overflow_fix, affected_target_po
     def test_validate_scope(self, test_params, validate_scopes):
         nncf_graph = test_params["test_model_type_pass"]["nncf_graph"]
         inference_nncf_graph = transform_to_inference_graph(
-            deepcopy(nncf_graph), self.get_algo_backend().get_input_nodes(nncf_graph), [], []
+            deepcopy(nncf_graph),
+            self.get_algo_backend().get_start_nodes_for_activation_path_tracing(nncf_graph),
+            [],
+            [],
         )
         ignored_patterns = test_params["test_model_type_pass"]["ignored_patterns"]
         algo = MinMaxQuantization(

diff --git a/tests/post_training/test_templates/test_quantizer_config.py b/tests/post_training/test_templates/test_quantizer_config.py
@@ -89,7 +89,7 @@ def test_default_quantizer_config(self, single_conv_nncf_graph):
         nncf_graph = single_conv_nncf_graph.nncf_graph
         inference_nncf_graph = transform_to_inference_graph(
             deepcopy(nncf_graph),
-            min_max_algo._backend_entity.get_input_nodes(nncf_graph),
+            min_max_algo._backend_entity.get_start_nodes_for_activation_path_tracing(nncf_graph),
             min_max_algo._backend_entity.shapeof_metatypes,
             min_max_algo._backend_entity.dropout_metatypes,
         )
@@ -143,7 +143,7 @@ def test_quantizer_config_from_ptq_params_for_CPU(
         nncf_graph = single_conv_nncf_graph.nncf_graph
         inference_nncf_graph = transform_to_inference_graph(
             deepcopy(nncf_graph),
-            min_max_algo._backend_entity.get_input_nodes(nncf_graph),
+            min_max_algo._backend_entity.get_start_nodes_for_activation_path_tracing(nncf_graph),
             min_max_algo._backend_entity.shapeof_metatypes,
             min_max_algo._backend_entity.dropout_metatypes,
         )
@@ -185,7 +185,7 @@ def test_depthwise_conv_default_quantizer_config(self, depthwise_conv_nncf_graph
         nncf_graph = depthwise_conv_nncf_graph.nncf_graph
         inference_nncf_graph = transform_to_inference_graph(
             deepcopy(nncf_graph),
-            min_max_algo._backend_entity.get_input_nodes(nncf_graph),
+            min_max_algo._backend_entity.get_start_nodes_for_activation_path_tracing(nncf_graph),
             min_max_algo._backend_entity.shapeof_metatypes,
             min_max_algo._backend_entity.dropout_metatypes,
         )

diff --git a/tests/torch/ptq/helpers.py b/tests/torch/ptq/helpers.py
@@ -54,7 +54,7 @@ def get_depthwise_conv_nncf_graph() -> NNCFGraphToTestDepthwiseConv:
         transpose=False,
         padding_values=(1, 1),
     )
-    return NNCFGraphToTestDepthwiseConv(PTDepthwiseConv2dSubtype, conv_layer_attrs)
+    return NNCFGraphToTestDepthwiseConv(PTDepthwiseConv2dSubtype, conv_layer_attrs, nncf_graph_cls=PTNNCFGraph)
 
 
 def get_single_no_weight_matmul_nncf_graph() -> NNCFGraphToTest: