Resume SynthData0523 main/c8 batch 4

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+    },
+    {
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+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+        "example_values": [
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+    },
+    {
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+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+        "example_values": [
+          "1",
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+      "role": "feature",
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+        "example_values": [
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+      }
+    },
+    {
+      "name": "Statistical_report",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
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+      "impute_strategy": "median",
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+        "example_values": [
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+    },
+    {
+      "name": "Result",
+      "role": "feature",
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+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+  ]
+}

SynthData0523/main/c8/tabddpm/tabddpm-c8-20260422_212506/public_gate/public_gate_report.json

@@ -0,0 +1,37 @@
+{
+  "dataset_id": "c8",
+  "status": "pass",
+  "checks": [
+    {
+      "check_id": "PG001_csv_parse_ok",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG002_split_header_consistent",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG003_profile_header_match",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG004_missing_token_normalized",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG005_semantic_type_validated",
+      "status": "pass"
+    },
+    {
+      "check_id": "PG006_target_defined_and_valid",
+      "status": "pass"
+    }
+  ],
+  "target_column": "having_At_Symbol",
+  "task_type": "classification",
+  "input_splits": {
+    "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c8/c8-train.csv",
+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c8/c8-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c8/c8-test.csv"
+  }
+}

SynthData0523/main/c8/tabddpm/tabddpm-c8-20260422_212506/public_gate/staged_input_manifest.json

@@ -0,0 +1,578 @@
+{
+  "dataset_id": "c8",
+  "target_column": "having_At_Symbol",
+  "task_type": "classification",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c8/tabddpm/tabddpm-c8-20260422_212506/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c8/tabddpm/tabddpm-c8-20260422_212506/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c8/tabddpm/tabddpm-c8-20260422_212506/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c8/tabddpm/tabddpm-c8-20260422_212506/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c8/tabddpm/tabddpm-c8-20260422_212506/public_gate/public_gate_report.json",
+  "column_schema": [
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+      "role": "feature",
+      "semantic_type": "numeric",
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+      "impute_strategy": "median",
+      "profile_stats": {
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+        "example_values": [
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+    },
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+      "role": "feature",
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+      "impute_strategy": "median",
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+    {
+      "name": "having_Sub_Domain",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "example_values": [
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+    },
+    {
+      "name": "SSLfinal_State",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
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+      "impute_strategy": "median",
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+        "example_values": [
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+          "1"
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+      }
+    },
+    {
+      "name": "Domain_registeration_length",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
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+      "impute_strategy": "median",
+      "profile_stats": {
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+        "example_values": [
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+      }
+    },
+    {
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+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "example_values": [
+          "1",
+          "-1"
+        ]
+      }
+    },
+    {
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+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "example_values": [
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+          "-1"
+        ]
+      }
+    },
+    {
+      "name": "HTTPS_token",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "example_values": [
+          "1",
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+    },
+    {
+      "name": "Request_URL",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "example_values": [
+          "-1",
+          "1"
+        ]
+      }
+    },
+    {
+      "name": "URL_of_Anchor",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "example_values": [
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+      }
+    },
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+      "role": "feature",
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+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+        "example_values": [
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+    },
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+      "name": "Submitting_to_email",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+      "impute_strategy": "median",
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+      "impute_strategy": "mode",
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+      "role": "feature",
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+      "nullable": false,
+      "missing_tokens": [],
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+        "example_values": [
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+    {
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+      "nullable": false,
+      "missing_tokens": [],
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+      "impute_strategy": "median",
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+      "missing_tokens": [],
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+      "impute_strategy": "median",
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+        "example_values": [
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+        ]
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+    },
+    {
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+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+        "example_values": [
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+        ]
+      }
+    },
+    {
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+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+        "example_values": [
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+        "example_values": [
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+      }
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+    {
+      "name": "web_traffic",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
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+      "impute_strategy": "median",
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+        "example_values": [
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+      "role": "feature",
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+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+        "example_values": [
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+      "role": "feature",
+      "semantic_type": "numeric",
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+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+        "example_values": [
+          "1",
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+        ]
+      }
+    },
+    {
+      "name": "Links_pointing_to_page",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "example_values": [
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+          "1",
+          "-1"
+        ]
+      }
+    },
+    {
+      "name": "Statistical_report",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_ratio": 0.000226,
+        "example_values": [
+          "1",
+          "-1"
+        ]
+      }
+    },
+    {
+      "name": "Result",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_ratio": 0.000226,
+        "example_values": [
+          "-1",
+          "1"
+        ]
+      }
+    }
+  ]
+}

SynthData0523/main/c8/tabddpm/tabddpm-c8-20260422_212506/runtime_result.json

@@ -0,0 +1,15 @@
+{
+  "dataset_id": "c8",
+  "model": "tabddpm",
+  "run_id": "tabddpm-c8-20260422_212506",
+  "public_gate_status": "pass",
+  "adapter_ready_status": "pass",
+  "train_status": "success",
+  "generate_status": "success",
+  "reason_code": null,
+  "reason_detail": null,
+  "artifacts": {
+    "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c8/tabddpm/tabddpm-c8-20260422_212506/tabddpm-c8-8844-20260422_212734.csv",
+    "model_path": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c8/tabddpm/tabddpm-c8-20260422_212506"
+  }
+}

SynthData0523/main/c8/tabddpm/tabddpm-c8-20260422_212506/staged/public/staged_features.json

@@ -0,0 +1,157 @@
+[
+  {
+    "feature_name": "having_IP_Address",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "URL_Length",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "Shortining_Service",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "having_At_Symbol",
+    "data_type": "continuous",
+    "is_target": true
+  },
+  {
+    "feature_name": "double_slash_redirecting",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "Prefix_Suffix",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "having_Sub_Domain",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "SSLfinal_State",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "Domain_registeration_length",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "Favicon",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "port",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
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SynthData0523/main/c8/tabdiff/tabdiff-c8-20260420_071420/_tabdiff_gen.py

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+import os, shutil, subprocess, sys
+td = r"/workspace/TabDiff"
+name = r"pipeline_ds"
+src = r"/work/output-SpecializedModels/c8/tabdiff/tabdiff-c8-20260420_071420/tabular_bundle/pipeline_ds"
+dst_data = os.path.join(td, "data", name)
+dst_syn = os.path.join(td, "synthetic", name)
+shutil.rmtree(dst_data, ignore_errors=True)
+shutil.copytree(src, dst_data)
+os.makedirs(dst_syn, exist_ok=True)
+for fn in ("real.csv", "test.csv", "val.csv"):
+    shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn))
+os.chdir(td)
+os.environ["PYTHONPATH"] = td + os.pathsep + os.environ.get("PYTHONPATH", "")
+subprocess.check_call([
+    sys.executable, "-m", "tabdiff.main",
+    "--dataname", name, "--mode", "test", "--gpu", "0",
+    "--no_wandb", "--exp_name", r"adapter_learnable",
+    "--ckpt_path", r"/workspace/TabDiff/tabdiff/ckpt/pipeline_ds/adapter_learnable/model_500.pt",
+    "--num_samples_to_generate", str(int(8844)),
+])
+# test() 写入 tabdiff/result/<dataname>/<exp>/<epoch>/samples.csv
+import glob as g
+base = os.path.join(td, "tabdiff", "result", name, r"adapter_learnable")
+best = None
+best_t = -1.0
+for root, _, files in os.walk(base):
+    if "samples.csv" in files:
+        p = os.path.join(root, "samples.csv")
+        t = os.path.getmtime(p)
+        if t > best_t:
+            best_t = t
+            best = p
+if not best:
+    raise SystemExit("tabdiff: no samples.csv under " + base)
+shutil.copy(best, r"/work/output-SpecializedModels/c8/tabdiff/tabdiff-c8-20260420_071420/tabdiff-c8-8844-20260420_072130.csv")

SynthData0523/main/c8/tabdiff/tabdiff-c8-20260420_071420/_tabdiff_train.py

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+
+import os, shutil, subprocess, sys
+td = r"/workspace/TabDiff"
+name = r"pipeline_ds"
+src = r"/work/output-SpecializedModels/c8/tabdiff/tabdiff-c8-20260420_071420/tabular_bundle/pipeline_ds"
+dst_data = os.path.join(td, "data", name)
+dst_syn = os.path.join(td, "synthetic", name)
+shutil.rmtree(dst_data, ignore_errors=True)
+shutil.copytree(src, dst_data)
+os.makedirs(dst_syn, exist_ok=True)
+for fn in ("real.csv", "test.csv", "val.csv"):
+    shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn))
+os.chdir(td)
+os.environ["PYTHONPATH"] = td + os.pathsep + os.environ.get("PYTHONPATH", "")
+os.environ["TABDIFF_SMOKE_STEPS"] = "500"
+os.environ["TABDIFF_ADAPTER_TRAIN"] = "1"
+subprocess.check_call([
+    sys.executable, "-m", "tabdiff.main",
+    "--dataname", name, "--mode", "train", "--gpu", "0",
+    "--no_wandb", "--exp_name", r"adapter_learnable",
+])

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