Changes needed for Deepsparse.Analyze

src/sparsezoo/analyze/analysis.py

@@ -38,6 +38,7 @@
     NamedEntry,
     NodeCounts,
     NodeIO,
+    NodeTimingEntry,
     OperationSummary,
     OpsSummary,
     ParameterComponent,
@@ -268,6 +269,11 @@ class BenchmarkResult(YAMLSerializableBaseModel):
         description="Node level inference results",
     )
 
+    supported_graph_percentage: Optional[float] = Field(
+        default=None,
+        description="Percentage of model graph supported by the runtime engine",
+    )
+
 
 class NodeAnalysis(YAMLSerializableBaseModel):
     """
@@ -825,17 +831,32 @@ def from_model_analysis(
                 section_name="Overall",
                 entries=[
                     PerformanceEntry(
-                        model=idx,
+                        model=analysis.model_name,
                         sparsity=overall_count_summary.sparsity_percent,
                         quantized=overall_count_summary.quantized_percent,
                         latency=benchmark_result.average_latency,
                         throughput=benchmark_result.items_per_second,
-                        supported_graph=0.0,  # TODO: fill in correct value
+                        supported_graph=(
+                            benchmark_result.supported_graph_percentage or 0.0
+                        ),
                     )
                     for idx, benchmark_result in enumerate(analysis.benchmark_results)
                 ],
             )
 
+            for idx, benchmark_result in enumerate(analysis.benchmark_results):
+                node_timing_section = Section(
+                    section_name=f"Node Timings for Benchmark # {idx+1}",
+                    entries=[
+                        NodeTimingEntry(
+                            node_name=node_timing.name,
+                            avg_runtime=node_timing.avg_run_time,
+                        )
+                        for node_timing in benchmark_result.node_timings
+                    ],
+                )
+                sections.append(node_timing_section)
+
         sections.extend([param_section, ops_section, overall_section])
         return cls(sections=sections)
 

src/sparsezoo/analyze/utils/models.py

@@ -369,12 +369,36 @@ class PerformanceEntry(BaseEntry):
     ] + BaseEntry._print_order
 
 
+class NodeTimingEntry(Entry):
+    """
+    A BaseEntry with additional performance info
+    """
+
+    node_name: str
+    avg_runtime: float
+
+    _print_order = [
+        "node_name",
+        "avg_runtime",
+    ] + Entry._print_order
+
+
 class Section(Entry):
     """
     Represents a list of Entries with an optional name
     """
 
-    entries: List[Union[NamedEntry, TypedEntry, SizedModelEntry, ModelEntry, BaseEntry]]
+    entries: List[
+        Union[
+            NodeTimingEntry,
+            PerformanceEntry,
+            NamedEntry,
+            TypedEntry,
+            SizedModelEntry,
+            ModelEntry,
+            BaseEntry,
+        ]
+    ]
 
     section_name: str = ""
 
@@ -425,7 +449,7 @@ def __sub__(self, other: "Section"):
     def get_comparable_entries(self, other: "Section") -> Tuple[List[Entry], ...]:
         """
         Get comparable entries by same name or type if they belong to
-        `NamedEntry` or `TypedEntry`, else return all entries
+        `NamedEntry`, `TypedEntry`, or `NodeTimingEntry`, else return all entries
 
         :return: A tuple composed of two lists, containing comparable entries
             in correct order from current and other Section objects
@@ -434,6 +458,7 @@ def get_comparable_entries(self, other: "Section") -> Tuple[List[Entry], ...]:
         entry_type_to_extractor = {
             "NamedEntry": lambda entry: entry.name,
             "TypedEntry": lambda entry: entry.type,
+            "NodeTimingEntry": lambda entry: entry.node_name,
         }
         entry_type = self.entries[0].__class__.__name__