Unstable challenge

graph_net/torch/backend/unstable_to_stable_backend.py

@@ -1,9 +1,18 @@
 import os
 import torch
+import sys
 from .graph_compiler_backend import GraphCompilerBackend
 
 
 class UnstableToStableBackend(GraphCompilerBackend):
+    def __init__(self):
+        unstable_api = os.getenv("DISALLOWED_UNSTABLE_API", "").strip()
+        if not unstable_api:
+            raise RuntimeError(
+                f"❌ Detected unstable API '{unstable_api}' '{count}' times in model graph.\n"
+            )
+        self.unstable_api = unstable_api
+
     def __call__(self, model):
         # Perform unstable API check before running the model
         self.model = model
@@ -12,14 +21,14 @@ def __call__(self, model):
         return self.model
 
     """
-    TODO: 实现将 self.model 中的不稳定（unstable）API 转换为稳定（stable）API 的逻辑。
-    该 API 负责遍历 self.model，并将其中调用的实验性或不稳定接口替换为对应的稳定版本。
-    注意：此逻辑属于模型编译安全机制的重要组成部分，请勿随意修改或删除。
-    
-    api命名规范：
-    <unstable>_to_<stable>
-    
-    stable api链接： 
+    TODO: Implement logic to convert unstable APIs in `self.model` into their stable counterparts.
+    This API is responsible for traversing `self.model` and replacing any calls to experimental or unstable interfaces with the corresponding stable versions.
+    Note: This logic is a critical component of the model compilation safety mechanism—do not modify or remove it without caution.
+
+    **API naming convention:**
+    `<unstable>_to_<stable>`
+
+    **Stable API reference link:**
     """
 
     def unstable_to_stable(self):
@@ -35,9 +44,6 @@ def check_unstable_api(self):
         This logic is part of the GraphNet compiler safety mechanism.
         Do NOT modify, remove, or bypass this check under any circumstances.
         """
-        unstable_api = os.getenv("DISALLOWED_UNSTABLE_API", "").strip()
-        if not unstable_api:
-            return  # Skip check if no environment variable is set
 
         from torch.fx import symbolic_trace
 
@@ -50,14 +56,12 @@ def check_unstable_api(self):
             graph_text = str(self.model)
 
         # Search for the unstable API substring
-        if unstable_api in graph_text:
-            count = graph_text.count(unstable_api)
-            raise RuntimeError(
-                f"❌ Detected unstable API '{unstable_api}' '{count}' times in model graph.\n"
-                f"Please replace it with a stable API before proceeding.\n"
-            )
+        if self.unstable_api in graph_text:
+            count = graph_text.count(self.unstable_api)
+            print(f"unstable_api:{self.unstable_api} occurs {count} times")
+            sys.exit(-1)
         else:
-            print(f"✅ Model passed: no occurrence of '{unstable_api}' found.")
+            print(f"✅ Model passed: no occurrence of '{self.unstable_api}' found.")
 
     def synchronize(self):
         # Synchronize CUDA operations if available

graph_net/torch/test_compiler.py

@@ -27,6 +27,7 @@
 from graph_net import test_compiler_util
 
 
+
 registry_backend = {
     "tvm": TvmBackend(),
     "xla": XlaBackend(),

plot.sh

@@ -0,0 +1,70 @@
+#!/bin/bash
+# 批量运行 GraphNet benchmark for unstable_to_stable (_add_batch_dim)
+# 从文件列表中读取模型路径执行编译测试，并将 log 转换为 JSON
+if [ -z "$DISALLOWED_UNSTABLE_API" ]; then
+  echo "❌ 环境变量 DISALLOWED_UNSTABLE_API 未设置！"
+  echo "请使用： export DISALLOWED_UNSTABLE_API=<target_unstable_api>"
+  exit 1
+fi
+
+# === 配置区 ===
+root_dir="/root/GraphNet/todo_works/unstable_api_to_stable_api/${DISALLOWED_UNSTABLE_API}"
+file_list="${root_dir}/${DISALLOWED_UNSTABLE_API}_files.txt"
+log_file="${root_dir}/log.log"
+json_output_dir="${root_dir}/JSON_results"
+
+# 设置环境变量（benchmark 路径）
+export GRAPH_NET_BENCHMARK_PATH="$root_dir"
+
+# === 检查输入文件 ===
+if [ ! -f "$file_list" ]; then
+  echo "❌ 文件不存在: $file_list"
+  exit 1
+fi
+
+# === 执行 benchmark ===
+echo "🚀 开始执行 benchmark..."
+echo "日志将写入: $log_file"
+# echo "--------------------------------------" > "$log_file"
+
+while IFS= read -r model_path; do
+  [ -z "$model_path" ] && continue
+
+  echo "▶️ 运行模型: $model_path"
+  echo ">>> Running model: $model_path" 
+
+  python -m graph_net.torch.test_compiler \
+    --model-path "/root/GraphNet/${model_path}/" \
+    --compiler unstable_to_stable \
+    >> "$log_file" 2>&1
+
+  echo "✅ 完成: $model_path" 
+  echo "--------------------------------------" 
+done < "$file_list"
+
+echo "🎯 所有模型运行完成，日志保存在: $log_file"
+
+# === 转换 log 为 JSON ===
+echo "📦 正在将日志转换为 JSON..."
+mkdir -p "$json_output_dir"
+
+python -m graph_net.log2json \
+  --log-file "$log_file" \
+  --output-dir "$json_output_dir"
+
+if [ $? -eq 0 ]; then
+  echo "✅ JSON 文件已生成: $json_output_dir"
+else
+  echo "⚠️ log2json 执行失败，请检查 log.log"
+fi
+
+echo "📦 正在将JSON转换为结果图"
+python -m graph_net.S_analysis \
+  --benchmark-path $GRAPH_NET_BENCHMARK_PATH/JSON_results/ \
+  --output-dir $GRAPH_NET_BENCHMARK_PATH \
+
+if [ $? -eq 0 ]; then
+  echo "✅ 结果图 文件已生成: $GRAPH_NET_BENCHMARK_PATH"
+else
+  echo "❌结果图生成失败"
+fi

todo_works/unstable_api_to_stable_api/_add_batch_dim/_add_batch_dim_files.txt

@@ -0,0 +1,10 @@
+samples/transformers-auto-model/AceInstruct-1.5B
+samples/transformers-auto-model/AlphaMaze-v0.2-1.5B
+samples/transformers-auto-model/Biggie-SmoLlm-0.4B
+samples/transformers-auto-model/EXAONE-4.0-1.2B
+samples/transformers-auto-model/SmolLM3-3B
+samples/transformers-auto-model/ZR1-1.5B
+samples/transformers-auto-model/gemma-3-1b-pt
+samples/transformers-auto-model/jhu-clsp_ettin-decoder-150m
+samples/transformers-auto-model/jinaai_jina-reranker-m0
+samples/transformers-auto-model/openai_whisper-base

todo_works/unstable_api_to_stable_api/_log_api_usage_once/_log_api_usage_once_files.txt

@@ -0,0 +1,64 @@
+samples/torchvision/convnext_base
+samples/torchvision/convnext_large
+samples/torchvision/convnext_small
+samples/torchvision/convnext_tiny
+samples/torchvision/efficientnet_b0
+samples/torchvision/efficientnet_b1
+samples/torchvision/efficientnet_b2
+samples/torchvision/efficientnet_b3
+samples/torchvision/efficientnet_b4
+samples/torchvision/efficientnet_b5
+samples/torchvision/efficientnet_b6
+samples/torchvision/efficientnet_b7
+samples/torchvision/efficientnet_v2_l
+samples/torchvision/efficientnet_v2_m
+samples/torchvision/efficientnet_v2_s
+samples/torchvision/maxvit_t
+samples/torchvision/swin_b
+samples/torchvision/swin_v2_b
+samples/torchvision/swin_v2_s
+samples/torchvision/swin_v2_t
+samples/transformers-auto-model/42dot_LLM-SFT-1.3B
+samples/transformers-auto-model/AceInstruct-1.5B
+samples/transformers-auto-model/AlphaMaze-v0.2-1.5B
+samples/transformers-auto-model/Biggie-SmoLlm-0.4B
+samples/transformers-auto-model/HuggingFaceTB/SmolLM3-3B
+samples/transformers-auto-model/Intel_zoedepth-kitti
+samples/transformers-auto-model/Intel_zoedepth-nyu
+samples/transformers-auto-model/LFM2-350M
+samples/transformers-auto-model/LLaMmlein_120M
+samples/transformers-auto-model/NDugar_deberta-v2-xlarge-mnli
+samples/transformers-auto-model/Qwen1.5-0.5B
+samples/transformers-auto-model/Qwen2.5-0.5B
+samples/transformers-auto-model/Qwen3-Embedding-0.6B
+samples/transformers-auto-model/SmolLM3-3B
+samples/transformers-auto-model/TinyLlama-1.1B-step-50K-105b
+samples/transformers-auto-model/TinyLlama/TinyLlama-1.1B-Chat-v0.4
+samples/transformers-auto-model/Tucano-2b4
+samples/transformers-auto-model/ZR1-1.5B
+samples/transformers-auto-model/baidu/ERNIE-4.5-0.3B-PT
+samples/transformers-auto-model/deepseek-ai/deepseek-coder-1.3b-base
+samples/transformers-auto-model/facebook_dpt-dinov2-giant-nyu
+samples/transformers-auto-model/facebook_dpt-dinov2-small-kitti
+samples/transformers-auto-model/gemma-3-1b-pt
+samples/transformers-auto-model/google/gemma-1.1-2b-it
+samples/transformers-auto-model/google/gemma-2b-it
+samples/transformers-auto-model/google/gemma-3-1b-it
+samples/transformers-auto-model/google/gemma-3-270m
+samples/transformers-auto-model/hf-tiny-model-private_tiny-random-BlipModel
+samples/transformers-auto-model/hf-tiny-model-private_tiny-random-CanineForSequenceClassification
+samples/transformers-auto-model/hf-tiny-model-private_tiny-random-PerceiverForImageClassificationConvProcessing
+samples/transformers-auto-model/hf-tiny-model-private_tiny-random-PerceiverForImageClassificationFourier
+samples/transformers-auto-model/hf-tiny-model-private_tiny-random-PerceiverForImageClassificationLearned
+samples/transformers-auto-model/microsoft/Phi-3-mini-4k-instruct
+samples/transformers-auto-model/microsoft/Phi-3.5-mini-instruct
+samples/transformers-auto-model/microsoft/Phi-4-mini-instruct
+samples/transformers-auto-model/microsoft/phi-1
+samples/transformers-auto-model/microsoft/phi-1_5
+samples/transformers-auto-model/microsoft/phi-2
+samples/transformers-auto-model/mooncakex_img2
+samples/transformers-auto-model/nli-deberta-v3-base
+samples/transformers-auto-model/nli-deberta-v3-small
+samples/transformers-auto-model/nli-deberta-v3-xsmall
+samples/transformers-auto-model/orca_mini_3b
+samples/transformers-auto-model/sarvam-0.5

todo_works/unstable_api_to_stable_api/_remove_batch_dim/_remove_batch_dim_files.txt

@@ -0,0 +1,10 @@
+samples/transformers-auto-model/AceInstruct-1.5B
+samples/transformers-auto-model/AlphaMaze-v0.2-1.5B
+samples/transformers-auto-model/Biggie-SmoLlm-0.4B
+samples/transformers-auto-model/EXAONE-4.0-1.2B
+samples/transformers-auto-model/SmolLM3-3B
+samples/transformers-auto-model/ZR1-1.5B
+samples/transformers-auto-model/gemma-3-1b-pt
+samples/transformers-auto-model/jhu-clsp_ettin-decoder-150m
+samples/transformers-auto-model/jinaai_jina-reranker-m0
+samples/transformers-auto-model/openai_whisper-base

todo_works/unstable_api_to_stable_api/_set_grad_enabled/_set_grad_enabled_files.txt

@@ -0,0 +1,13 @@
+samples/transformers-auto-model/EleutherAI_pythia-1b
+samples/transformers-auto-model/HuggingFaceTB/SmolLM3-3B
+samples/transformers-auto-model/TinyLlama/TinyLlama-1.1B-Chat-v0.4
+samples/transformers-auto-model/baidu/ERNIE-4.5-0.3B-PT
+samples/transformers-auto-model/deepseek-ai/deepseek-coder-1.3b-base
+samples/transformers-auto-model/google/gemma-1.1-2b-it
+samples/transformers-auto-model/google/gemma-2b-it
+samples/transformers-auto-model/google/gemma-3-1b-it
+samples/transformers-auto-model/google/gemma-3-270m
+samples/transformers-auto-model/microsoft/Phi-3-mini-4k-instruct
+samples/transformers-auto-model/microsoft/phi-1
+samples/transformers-auto-model/microsoft/phi-1_5
+samples/transformers-auto-model/microsoft/phi-2

todo_works/unstable_api_to_stable_api/_vmap_decrement_nesting/_vmap_decrement_nesting_files.txt

@@ -0,0 +1,10 @@
+samples/transformers-auto-model/AceInstruct-1.5B
+samples/transformers-auto-model/AlphaMaze-v0.2-1.5B
+samples/transformers-auto-model/Biggie-SmoLlm-0.4B
+samples/transformers-auto-model/EXAONE-4.0-1.2B
+samples/transformers-auto-model/SmolLM3-3B
+samples/transformers-auto-model/ZR1-1.5B
+samples/transformers-auto-model/gemma-3-1b-pt
+samples/transformers-auto-model/jhu-clsp_ettin-decoder-150m
+samples/transformers-auto-model/jinaai_jina-reranker-m0
+samples/transformers-auto-model/openai_whisper-base

todo_works/unstable_api_to_stable_api/_vmap_increment_nesting/_vmap_increment_nesting_files.txt

@@ -0,0 +1,10 @@
+samples/transformers-auto-model/AceInstruct-1.5B
+samples/transformers-auto-model/AlphaMaze-v0.2-1.5B
+samples/transformers-auto-model/Biggie-SmoLlm-0.4B
+samples/transformers-auto-model/EXAONE-4.0-1.2B
+samples/transformers-auto-model/SmolLM3-3B
+samples/transformers-auto-model/ZR1-1.5B
+samples/transformers-auto-model/gemma-3-1b-pt
+samples/transformers-auto-model/jhu-clsp_ettin-decoder-150m
+samples/transformers-auto-model/jinaai_jina-reranker-m0
+samples/transformers-auto-model/openai_whisper-base