Send Perf Data to Explorer Frontend (#1608)

- A few small changes to explorer to send perf data to the frontend.
- Changed `to_adapter_format` to allow for multiple objects
- Added `add_to_dataclass` to append perf_data to Graph dataclass.

tools/explorer/CMakeLists.txt

@@ -3,7 +3,7 @@ include(ExternalProject)
 set(TT_EXPLORER_SCRIPT ${CMAKE_CURRENT_SOURCE_DIR}/run.py)
 set(TTMLIR_BUILD_BIN_DIR ${TTMLIR_BINARY_DIR}/bin)
 
-set(MODEL_EXPLORER_VERSION "d0b53c3b7049fd41ea1caff193706272c399fac9")
+set(MODEL_EXPLORER_VERSION "ca884d5eb3291507e7f4e76776957e231b2d9b6d")
 ExternalProject_Add(
   model-explorer
   PREFIX ${CMAKE_CURRENT_SOURCE_DIR}/model-explorer
@@ -18,7 +18,9 @@ ExternalProject_Add(
 add_custom_target(explorer
   COMMENT "Building tt-explorer... ${TTMLIR_BIN_DIR}"
   COMMAND pip install $<$<CONFIG:Debug>:-e> ${CMAKE_CURRENT_SOURCE_DIR}/tt_adapter
-  COMMAND pip install ${CMAKE_CURRENT_SOURCE_DIR}/model-explorer/src/model-explorer/src/server/package
+  COMMAND pip uninstall -y ai-edge-model-explorer
+  COMMAND ${CMAKE_COMMAND} -E remove_directory ${CMAKE_CURRENT_SOURCE_DIR}/model-explorer/src/model-explorer/src/server/package/build
+  COMMAND pip install --upgrade ${CMAKE_CURRENT_SOURCE_DIR}/model-explorer/src/model-explorer/src/server/package
 
   DEPENDS TTMLIRPythonModules model-explorer ttrt ttmlir-opt ttmlir-translate
 )

tools/explorer/tt_adapter/src/tt_adapter/main.py

@@ -56,7 +56,9 @@ def convert(
 
         # Convert TTIR to Model Explorer Graphs and Display/Return
         graph, perf_data = mlir.build_graph(module, perf_trace)
-        return {"graphs": [graph], "perf_data": perf_data}
+        if perf_data:
+            graph = utils.add_to_dataclass(graph, "perf_data", perf_data.graphsData)
+        return {"graphs": [graph]}
 
     def execute(
         self, model_path: str, settings: Dict

tools/explorer/tt_adapter/src/tt_adapter/utils.py

@@ -2,7 +2,7 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 import ttmlir
-from dataclasses import make_dataclass
+from dataclasses import make_dataclass, is_dataclass, asdict
 
 
 def parse_mlir_file(model_path):
@@ -18,5 +18,15 @@ def to_dataclass(obj: dict, dc_name: str = "tempClass"):
     return make_dataclass(dc_name, ((k, type(v)) for k, v in obj.items()))(**obj)
 
 
-def to_adapter_format(obj: dict):
-    return {"graphs": [to_dataclass(obj)]}
+def add_to_dataclass(dataclass, new_attr_name: str, new_attr_value):
+    if not is_dataclass(dataclass):
+        return None
+    classname = dataclass.__class__.__name__
+    dataclass = asdict(dataclass)
+    dataclass[new_attr_name] = new_attr_value
+    return to_dataclass(dataclass, dc_name=classname)
+
+
+def to_adapter_format(*objs):
+    res = [x if is_dataclass(x) else to_dataclass(x) for x in objs]
+    return {"graphs": res}