1) Init sym dim reifier in graph net json; 2) refactor model_path_handler (#420)

* init 'symbolic_dimension_reifier' field in graph_net.json

* refactor model_path_handler

Author: lixinqi

graph_net/config/empty_cstr_torch_samples_list.txt

@@ -0,0 +1 @@
+samples/transformers-auto-model/microsoft_xclip-base-patch32-16-frames

graph_net/config/tmp_torch_samples_list.txt

@@ -1,10 +1,10 @@
-import traceback
 import argparse
 from graph_net.imp_util import load_module
 import logging
 import sys
 import json
 import base64
+import subprocess
 
 logging.basicConfig(
     level=logging.WARNING, format="%(asctime)s [%(levelname)s] %(message)s"
@@ -37,33 +37,49 @@ def _get_handler(args):
 
 def main(args):
     handler = _get_handler(args)
-    for model_path in _get_model_paths(args):
-        print(f"{model_path=}")
+    if args.model_path is not None:
+        handle_model_path(handler, args.model_path)
+    elif args.use_subprocess:
+        handle_model_path_list_in_subprocess(args)
+    else:
+        handle_model_path_list_in_current_process(handler, args)
+
+
+def handle_model_path_list_in_current_process(handler, args):
+    for model_path in _get_model_path_list(args):
         try:
-            handler(model_path)
+            handle_model_path(handler, model_path)
         except KeyboardInterrupt:
-            sys.exit(-1)
-        except Exception as e:
-            print("--- Concise Error Message ---")
-            print(e)
+            print("KeyboardInterrupt")
+            return
 
-            print("\n--- Full Traceback ---")
-            traceback.print_exc()
 
+def handle_model_path_list_in_subprocess(args):
+    for model_path in _get_model_path_list(args):
+        cmd = f"{sys.executable} -m graph_net.model_path_handler --model-path {model_path} --handler-config {args.handler_config}"
+        try:
+            subprocess.Popen(cmd, shell=True).wait()
+        except KeyboardInterrupt:
+            print("KeyboardInterrupt")
+            return
 
-def _get_model_paths(args):
-    assert args.model_path is not None or args.model_path_list is not None
-    if args.model_path is not None:
-        yield args.model_path
-    if args.model_path_list is not None:
-        with open(args.model_path_list) as f:
-            yield from (
-                clean_line
-                for line in f
-                for clean_line in [line.strip()]
-                if len(clean_line) > 0
-                if not clean_line.startswith("#")
-            )
+
+def handle_model_path(handler, model_path):
+    print(f"{model_path=}", flush=True)
+    handler(model_path)
+
+
+def _get_model_path_list(args):
+    assert args.model_path is None
+    assert args.model_path_list is not None
+    with open(args.model_path_list) as f:
+        yield from (
+            clean_line
+            for line in f
+            for clean_line in [line.strip()]
+            if len(clean_line) > 0
+            if not clean_line.startswith("#")
+        )
 
 
 if __name__ == "__main__":
@@ -89,5 +105,11 @@ def _get_model_paths(args):
         default=None,
         help="handler configuration string",
     )
+    parser.add_argument(
+        "--use-subprocess",
+        action="store_true",
+        default=False,
+        help="use subprocess",
+    )
     args = parser.parse_args()
     main(args=args)

graph_net/model_path_handler.py

@@ -48,4 +48,4 @@ echo "Results saved in: $FILE_PATH/ES_result.png"
 echo ""
 echo "IMPORTANT: Please verify if the curve in ES_result.png is a straight line"
 echo "If the curve is NOT a straight line, please check the log file: $FILE_PATH/log.log"
-echo "=================================================="
+echo "=================================================="

graph_net/test/decomposer_validator_test.sh

@@ -13,9 +13,8 @@ config_json_str=$(cat <<EOF
     "handler_config": {
         "output_dir": "/tmp/naive_decompose_workspace",
         "split_positions": [8, 16, 32],
-        "group_head_and_tail": true,
-        "filter_path":"$GRAPH_NET_ROOT/torch/naive_subgraph_filter.py",
-        "filter_config": {}
+        "chain_style": true,
+        "group_head_and_tail": true
     }
 }
 EOF

graph_net/test/naive_graph_decomposer_test.sh

@@ -1,3 +1,4 @@
+import sympy
 from pathlib import Path
 from graph_net.dynamic_dim_constraints import DynamicDimConstraints
 import graph_net.graph_net_json_file_util as gn_json
@@ -27,6 +28,10 @@ def __call__(self, model_path):
         dyn_dim_cstrs = DynamicDimConstraints.unserialize_from_py_file(
             str(input_tensor_cstr_filepath)
         )
+        for shape, name in dyn_dim_cstrs.input_shapes:
+            if not any(isinstance(dim, sympy.Expr) for dim in shape):
+                continue
+            print(f"{shape=} {name=}")
         input_shapes_str = str(dyn_dim_cstrs.serialize_symbolic_input_shapes_to_str())
         print(f"get-in-tensor-symbolic-shapes {input_shapes_str} {model_path}")
 

graph_net/tools/_get_in_tensor_symbolic_shapes.py

@@ -34,12 +34,12 @@ config_json_str=$(cat <<EOF
                 "non_batch_call_function_arange_plus_one_pass"
             ]
         },
-        "limits_handled_models": 1,
+        "limits_handled_models": 999999,
         "last_model_log_file": "/tmp/a.py"
     }
 }
 EOF
 )
 CONFIG=$(echo $config_json_str | base64 -w 0)
 
-python3 -m graph_net.model_path_handler --model-path-list $GRAPH_NET_ROOT/config/empty_cstr_torch_samples_list.txt --handler-config=$CONFIG
+python3 -m graph_net.model_path_handler --model-path-list $GRAPH_NET_ROOT/config/empty_cstr_torch_samples_list.txt --handler-config=$CONFIG --use-subprocess

graph_net/tools/batch_init_input_tensor_constraints.sh

@@ -76,7 +76,6 @@ def get_new_tuple_args(input_tensor_node, view_args):
                 input_tensor_node = node.args[0]
                 # Get the target shape arguments for view (e.g., 1, -1, 6, 64)
                 view_args = node.args[1:]
-                print(f"{view_args=}")
                 new_view_args = get_new_tuple_args(input_tensor_node, view_args)
 
                 # --- Rebuild the view node ---