fix regression bugs in tools/apply_dim_gen_passes.sh, tools/get_in_tensor_symbolic_shapes.sh and tools/init_input_tensor_constraints.sh

Author: lixinqi

graph_net/tools/apply_dim_gen_passes.sh

@@ -3,10 +3,9 @@
 GRAPH_NET_ROOT=$(python3 -c "import graph_net; import os; print(
 os.path.dirname(graph_net.__file__))")
 
-# input model path
-# model_runnable_predicator=ShapePropagatablePredicator
-model_runnable_predicator=ModelRunnablePredicator
-config_json_str=$(cat <<EOF
+python3 -m graph_net.model_path_handler \
+    --model-path-list $GRAPH_NET_ROOT/config/torch_samples_list.txt \
+    --handler-config=$(base64 -w 0 <<EOF
 {
     "handler_path": "$GRAPH_NET_ROOT/dimension_generalizer.py",
     "handler_class_name": "ApplyDimGenPasses",
@@ -22,6 +21,3 @@ config_json_str=$(cat <<EOF
 }
 EOF
 )
-CONFIG=$(echo $config_json_str | base64 -w 0)
-
-python3 -m graph_net.model_path_handler --model-path-list $GRAPH_NET_ROOT/config/torch_samples_list.txt --handler-config=$CONFIG

graph_net/tools/get_in_tensor_symbolic_shapes.sh

@@ -6,7 +6,10 @@ os.path.dirname(graph_net.__file__))")
 # input model path
 # model_runnable_predicator=ShapePropagatablePredicator
 model_runnable_predicator=ModelRunnablePredicator
-config_json_str=$(cat <<EOF
+
+python3 -m graph_net.model_path_handler \
+    --model-path-list $GRAPH_NET_ROOT/config/torch_samples_list.txt \
+    --handler-config=$(base64 -w 0 <<EOF
 {
     "handler_path": "$GRAPH_NET_ROOT/tools/_get_in_tensor_symbolic_shapes.py",
     "handler_class_name": "GetInTensorSymbolicShapes",
@@ -17,6 +20,3 @@ config_json_str=$(cat <<EOF
 }
 EOF
 )
-CONFIG=$(echo $config_json_str | base64 -w 0)
-
-python3 -m graph_net.model_path_handler --model-path-list $GRAPH_NET_ROOT/config/torch_samples_list.txt --handler-config=$CONFIG

…s/batch_init_input_tensor_constraints.sh …t/tools/init_input_tensor_constraints.shgraph_net/tools/batch_init_input_tensor_constraints.sh renamed to graph_net/tools/init_input_tensor_constraints.sh graph_net/tools/batch_init_input_tensor_constraints.sh renamed to graph_net/tools/init_input_tensor_constraints.sh

@@ -6,7 +6,11 @@ os.path.dirname(graph_net.__file__))")
 # input model path
 # model_runnable_predicator=ShapePropagatablePredicator
 model_runnable_predicator=ModelRunnablePredicator
-config_json_str=$(cat <<EOF
+
+python3 -m graph_net.model_path_handler \
+    --use-subprocess                    \
+    --model-path-list $GRAPH_NET_ROOT/config/small100_torch_samples_list.txt \
+    --handler-config=$(base64 -w 0 <<EOF
 {
     "handler_path": "$GRAPH_NET_ROOT/constraint_util.py",
     "handler_class_name": "UpdateInputTensorConstraints",
@@ -40,6 +44,3 @@ config_json_str=$(cat <<EOF
 }
 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 --use-subprocess

graph_net/torch/fx_graph_parse_util.py

@@ -157,11 +157,14 @@ def get_input_names_from_placeholder():
         names_from_placeholder=get_input_names_from_placeholder(),
     )
 
-    for node in traced_module.graph.nodes:
-        if node.op != "placeholder":
-            continue
-        node.target = _rename_placeholder(node.target, pattern2replacement)
-        node.name = node.target
+    def handle_placeholder_name(pattern2replacement):
+        for node in traced_module.graph.nodes:
+            if node.op != "placeholder":
+                continue
+            node.target = _rename_placeholder(node.target, pattern2replacement)
+            node.name = node.target
+
+    handle_placeholder_name(pattern2replacement)
 
     def get_diff_input_names():
         placeholder_names = set(get_input_names_from_placeholder())
@@ -226,14 +229,35 @@ def handle_underscore_suffix_difference():
         for node in traced_module.graph.nodes:
             if not (node.op == "placeholder"):
                 continue
-            if node.target not in names:
+            if node.name not in names:
                 continue
             node.target = node.target[:-1]
             node.name = node.name[:-1]
         traced_module.recompile()
 
     handle_underscore_suffix_difference()
 
+    def handle_prefix_difference():
+        zip_filter_names = get_zip_filter_names()
+        if not (len(zip_filter_names) > 0):
+            return
+        names = set(
+            name_in_placeholder
+            for _0, name_in_signature, name_in_placeholder in zip_filter_names
+            if (f"l_{name_in_signature[2:]}" == name_in_placeholder)
+            if (name_in_signature == f"L_{name_in_placeholder[2:]}")
+        )
+        for node in traced_module.graph.nodes:
+            if not (node.op == "placeholder"):
+                continue
+            if node.name not in names:
+                continue
+            node.target = f"L_{node.target[2:]}"
+            node.name = f"L_{node.name[2:]}"
+        traced_module.recompile()
+
+    handle_prefix_difference()
+
     if len(get_zip_filter_names()) > 0 and set(get_input_names_from_signature()) == set(
         get_input_names_from_placeholder()
     ):
@@ -243,15 +267,14 @@ def handle_underscore_suffix_difference():
 
     zip_filter_names = get_zip_filter_names()
 
-    def zip_filter_names_error_str():
+    def get_error_model_path():
         for triple in zip_filter_names:
             print(triple)
-        error_model_path = module.__graph_net_file_path__
-        return f"{error_model_path=}"
+        return module.__graph_net_file_path__
 
     # from pathlib import Path
     # Path("/tmp/a.py").write_text(traced_module.code)
-    assert len(zip_filter_names) == 0, f"{zip_filter_names_error_str()=}"
+    assert len(zip_filter_names) == 0, f"{get_error_model_path()=}"
     return traced_module
 
 

graph_net/torch/static_to_dynamic.py

@@ -1,7 +1,7 @@
 import traceback
 import logging
 import torch
-from graph_net.torch.utils import get_dummy_named_tensors
+from graph_net.torch.utils import get_named_tensors
 from torch.fx.passes.shape_prop import ShapeProp
 from graph_net.torch.utils import apply_templates
 from pathlib import Path
@@ -24,7 +24,7 @@ def __call__(self, module, dim_axes_pairs):
         return StaticToDynamicModulePass(self.config, module, dim_axes_pairs)
 
     def create_inputs_by_metas(self, module, tensor_meta_attrs_list):
-        named_tensors = get_dummy_named_tensors(tensor_meta_attrs_list)
+        named_tensors = get_named_tensors(tensor_meta_attrs_list, use_dummy_inputs=True)
         name2tensor = {k: v for k, v in named_tensors}
         return tuple(
             name2tensor[name] for name in inspect.signature(module.forward).parameters