Merge branch 'develop' of github.com:PaddlePaddle/GraphNet into develop

Author: lixinqi

graph_net/sample_pass/sample_pass.py

@@ -55,7 +55,8 @@ def _make_config_by_config_declare(self, config):
         sig = inspect.signature(self.declare_config)
         mut_config = copy.deepcopy(config)
         for name, param in sig.parameters.items():
-            self._complete_default(name, param, mut_config)
+            if name not in mut_config:
+                self._complete_default(name, param, mut_config)
             class_name = type(self).__name__
             assert name in mut_config, f"{name=} {class_name=}"
 

…et/test/test_agent_unittest_generator.sh …et/test/agent_unittest_generator_test.shgraph_net/test/test_agent_unittest_generator.sh renamed to graph_net/test/agent_unittest_generator_test.sh graph_net/test/test_agent_unittest_generator.sh renamed to graph_net/test/agent_unittest_generator_test.sh

@@ -1,23 +1,22 @@
 #!/usr/bin/env bash
-# set -euo pipefail
-
-# Smoke tests for AgentUnittestGenerator using model_path_handler + sample pass.
 
 ROOT_DIR="$(cd "$(dirname "$0")/../.." && pwd)"
 GRAPH_NET_ROOT=$(python -c "import graph_net, os; print(os.path.dirname(os.path.dirname(graph_net.__file__)))")
-HANDLER_PATH="$GRAPH_NET_ROOT/graph_net/torch/sample_passes/agent_unittest_generator.py"
+
 MODEL_PATH_PREFIX="$ROOT_DIR"
-OUTPUT_DIR="$ROOT_DIR"
+OUTPUT_DIR="/tmp/agent_unittests"
 
 HANDLER_CONFIG=$(base64 -w 0 <<EOF
 {
-    "handler_path": "$HANDLER_PATH",
+    "handler_path": "$GRAPH_NET_ROOT/graph_net/torch/sample_passes/agent_unittest_generator.py",
     "handler_class_name": "AgentUnittestGeneratorPass",
     "handler_config": {
         "model_path_prefix": "$MODEL_PATH_PREFIX",
         "output_dir": "$OUTPUT_DIR",
-        "force_device": "auto",
-        "use_dummy_inputs": false
+        "device": "auto",
+        "generate_main": true,
+        "data_input_predicator_filepath": "$GRAPH_NET_ROOT/graph_net/torch/constraint_util.py",                                                                                     
+        "data_input_predicator_class_name": "NaiveDataInputPredicator"
     }
 }
 EOF

graph_net/torch/constraint_util.py

@@ -16,6 +16,14 @@ def __call__(self, model_path, input_var_name: str) -> bool:
         )
 
 
+class RenamedDataInputPredicator:
+    def __init__(self, config):
+        self.config = config
+
+    def __call__(self, model_path, input_var_name: str) -> bool:
+        return input_var_name.startswith("in_")
+
+
 class ModelRunnablePredicator:
     def __init__(self, config):
         if config is None:

graph_net/torch/fx_graph_module_util.py

@@ -5,10 +5,10 @@
 from dataclasses import asdict
 
 
-def get_torch_module_and_inputs(model_path):
+def get_torch_module_and_inputs(model_path, use_dummy_inputs=True):
     module = _get_torch_module(model_path)
     tensor_metas = _get_tensor_metas(model_path)
-    inputs = _create_inputs_by_metas(module, tensor_metas)
+    inputs = _create_inputs_by_metas(module, tensor_metas, use_dummy_inputs)
     return module, inputs
 
 
@@ -27,11 +27,11 @@ def _get_tensor_metas(model_path):
     ]
 
 
-def _create_inputs_by_metas(module, tensor_metas):
+def _create_inputs_by_metas(module, tensor_metas, use_dummy_inputs):
     tensor_meta_attrs_list = [asdict(tensor_meta) for tensor_meta in tensor_metas]
-    from graph_net.torch.utils import get_dummy_named_tensors
+    from graph_net.torch.utils import get_named_tensors
 
-    named_tensors = get_dummy_named_tensors(tensor_meta_attrs_list)
+    named_tensors = get_named_tensors(tensor_meta_attrs_list, use_dummy_inputs)
     name2tensor = {k: v for k, v in named_tensors}
     return tuple(
         name2tensor[name] for name in inspect.signature(module.forward).parameters

graph_net/torch/graph_decomposer.py

@@ -130,7 +130,7 @@ def __call__(self, rel_model_path):
             for k, v in self.config.items()
             if k in {"split_positions", "group_head_and_tail", "chain_style"}
         }
-        module, inputs = get_torch_module_and_inputs(model_path)
+        module, inputs = get_torch_module_and_inputs(model_path, use_dummy_inputs=False)
         gm = parse_immutable_model_path_into_sole_graph_module(model_path)
         try:
             # logger.warning("convert_to_submodules_graph-call-begin")
@@ -227,7 +227,7 @@ def __call__(self, rel_model_path):
             "group_head_and_tail": self.config.get("group_head_and_tail", False),
             "chain_style": self.config.get("chain_style", False),
         }
-        module, inputs = get_torch_module_and_inputs(model_path)
+        module, inputs = get_torch_module_and_inputs(model_path, use_dummy_inputs=False)
         gm = parse_sole_graph_module(module, inputs)
         rewrited_gm: torch.fx.GraphModule = convert_to_submodules_graph(
             gm,