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

Author: lixinqi

graph_net/config/get_fusible_subgraph_sample_list.txt

@@ -22,7 +22,7 @@
 {%- endif -%}
 {{"\n"}}
 import torch
-from torch import device
+from torch import device, inf
 
 
 {% macro get_input_tensor_instance(tensor_meta, device) -%}
@@ -36,7 +36,7 @@
 {%- if data is not none -%}
     torch.tensor({{data}}, dtype={{dtype}}).reshape({{shape}}).to(device='{{device}}')
 {%- elif dtype == "torch.bool" -%}
-    torch.rand({{shape}}, device={{device}}) > 0.5
+    torch.rand({{shape}}, device='{{device}}') > 0.5
 {%- elif dtype in ["torch.int8", "torch.int16", "torch.int32", "torch.int64"] -%}
     torch.randint({{min_val}}, {{max_val}} + 1, size={{shape}}, dtype={{dtype}}).to(device='{{device}}')
 {%- elif dtype in ["torch.float16", "torch.bfloat16", "torch.float32", "torch.float64"] -%}
@@ -118,7 +118,7 @@ def test_main(self):
 {%- if data is not none -%}
     paddle.to_tensor({{data}}, dtype='{{dtype}}', shape={{shape}}).to(device='{{device}}')
 {%- elif dtype == "bool" -%}
-    paddle.randint(low=0, high=2, shape={{shape}}, dtype='{{dtype}}')
+    paddle.randint(low=0, high=2, shape={{shape}}, dtype='{{dtype}}').to(device='{{device}}')
 {%- elif dtype in ["int8", "int16", "int32", "int64"] -%}
     paddle.randint(low={{min_val}}, high={{max_val}} + 1, shape={{shape}}, dtype='{{dtype}}').to(device='{{device}}')
 {%- elif dtype in ["float16", "bfloat16", "float32", "float64"] -%}
@@ -456,13 +456,8 @@ def __call__(self, rel_model_path: str):
         self.resumable_handle_sample(rel_model_path)
 
     def sample_handled(self, rel_model_path: str) -> bool:
-        dst_model_path = Path(self.config["output_dir"]) / rel_model_path
-        if not dst_model_path.exists():
-            return False
         output_name = self._get_output_name(rel_model_path)
-        num_model_py_files = len(list(dst_model_path.rglob(output_name)))
-        assert num_model_py_files <= 1
-        return num_model_py_files == 1
+        return self.naive_sample_handled(rel_model_path, search_file_name=output_name)
 
     def _get_output_name(self, rel_model_path: str):
         return f"{Path(rel_model_path).name}_test.py"

graph_net/sample_pass/agent_unittest_generator.py

@@ -0,0 +1,26 @@
+#!/bin/bash
+
+GRAPH_NET_ROOT=$(python3 -c "import graph_net; import os; print(os.path.dirname(os.path.dirname(graph_net.__file__)))")
+
+model_path_list=$GRAPH_NET_ROOT/graph_net/test/workspace_cumsum_num_kernels/test_model_list.txt
+WORKSPACE_ROOT=/tmp/fusible_subgraphs
+CUMSUM_NUM_KERNELS_WORKSPACE=$WORKSPACE_ROOT/workspace_cumsum_num_kernels
+FUSIBLE_SUBGRAPH_RANGES_WORKSPACE=$WORKSPACE_ROOT/workspace_fusible_subgraph_ranges
+FUSIBLE_SUBGRAPH_SAMPLES_WORKSPACE=$WORKSPACE_ROOT/workspace_fusible_subgraph_samples
+resume=false
+
+python3 -m graph_net.model_path_handler \
+    --model-path-list "$model_path_list" \
+    --handler-config $(base64 -w 0 <<EOF
+{
+    "handler_path": "$GRAPH_NET_ROOT/graph_net/torch/sample_passes/cumsum_num_kernels_generator.py",
+    "handler_class_name": "CumSumNumKernelsGenerator",
+    "handler_config": {
+        "output_json_file_name": "cumsum_num_kernels.json",
+        "model_path_prefix": "$GRAPH_NET_ROOT/graph_net/test/workspace_cumsum_num_kernels",
+        "output_dir": "$CUMSUM_NUM_KERNELS_WORKSPACE",
+        "resume": $resume
+    }
+}
+EOF
+)

graph_net/test/debug_fusible_subgraph_generate.sh

@@ -1 +1,11 @@
 samples/timm/resnet18
+samples/timm/eca_resnext26ts.ch_in1k
+samples/timm/eca_vovnet39b
+samples/timm/efficientnet_b0.ra4_e3600_r224_in1k
+samples/timm/efficientnet_b1.ft_in1k
+samples/timm/efficientnet_b2.ra_in1k
+samples/timm/efficientnet_b3.ra2_in1k
+samples/timm/efficientnet_b4.ra2_in1k
+samples/timm/efficientnet_b5.sw_in12k
+samples/timm/efficientnet_el.ra_in1k
+samples/timm/efficientnet_em.ra2_in1k

graph_net/test/dev_model_list/cumsum_num_kernels_sample_list.txt

@@ -1 +1,2 @@
 samples/transformers-auto-model/dbmdz_electra-large-discriminator-finetuned-conll03-english
+samples/timm/test_byobnet.r160_in1k