Resume SynthData0523 main/c20 batch 2

.gitattributes

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SynthData0523/main/c20/ctgan/ctgan-c20-20260328_052613/public_gate/public_gate_report.json

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+{
+  "dataset_id": "c20",
+  "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": "class",
+  "task_type": "classification",
+  "input_splits": {
+    "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-train.csv",
+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c20/c20-test.csv"
+  }
+}

SynthData0523/main/c20/ctgan/ctgan-c20-20260328_052613/public_gate/staged_input_manifest.json

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+{
+  "dataset_id": "c20",
+  "target_column": "class",
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+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/ctgan/ctgan-c20-20260328_052613/staged/public/train.csv",
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+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/ctgan/ctgan-c20-20260328_052613/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/ctgan/ctgan-c20-20260328_052613/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/ctgan/ctgan-c20-20260328_052613/public_gate/public_gate_report.json",
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SynthData0523/main/c20/ctgan/ctgan-c20-20260328_052613/runtime_result.json

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+{
+  "dataset_id": "c20",
+  "model": "ctgan",
+  "run_id": "ctgan-c20-20260328_052613",
+  "public_gate_status": "pass",
+  "adapter_ready_status": "pass",
+  "train_status": "skipped",
+  "generate_status": "success",
+  "reason_code": null,
+  "reason_detail": null,
+  "artifacts": {
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+  }
+}

SynthData0523/main/c20/ctgan/ctgan-c20-20260328_052613/staged/ctgan/adapter_report.json

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+{
+  "adapter_ready_status": "pass",
+  "adapter_fail_reason_code": null,
+  "adapter_fail_detail": null,
+  "adapter_transforms_applied": [],
+  "model_input_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/ctgan/ctgan-c20-20260328_052613/staged/ctgan/model_input_manifest.json"
+}

SynthData0523/main/c20/ctgan/ctgan-c20-20260328_052613/staged/ctgan/adapter_transforms_applied.json

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SynthData0523/main/c20/ctgan/ctgan-c20-20260328_052613/staged/ctgan/model_input_manifest.json

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+{
+  "dataset_id": "c20",
+  "model": "ctgan",
+  "target_column": "class",
+  "task_type": "classification",
+  "column_schema": [
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+        "example_values": [
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+          "b",
+          "d"
+        ]
+      }
+    }
+  ],
+  "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/ctgan/ctgan-c20-20260328_052613/public_gate/staged_input_manifest.json",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/ctgan/ctgan-c20-20260328_052613/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/ctgan/ctgan-c20-20260328_052613/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/ctgan/ctgan-c20-20260328_052613/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/ctgan/ctgan-c20-20260328_052613/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c20/ctgan/ctgan-c20-20260328_052613/public_gate/public_gate_report.json"
+}

SynthData0523/main/c20/ctgan/ctgan-c20-20260328_052613/staged/public/staged_features.json

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+[
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+    "data_type": "continuous",
+    "is_target": false
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+  {
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+    "data_type": "continuous",
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+  {
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+  {
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+  {
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+    "data_type": "continuous",
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+  {
+    "feature_name": "black_piece0_rank",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "class",
+    "data_type": "categorical",
+    "is_target": true
+  }
+]

SynthData0523/main/c20/ctgan/ctgan-c20-20260328_052613/staged/public/test.csv

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SynthData0523/main/c20/ctgan/ctgan-c20-20260328_052613/staged/public/train.csv

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SynthData0523/main/c20/ctgan/ctgan-c20-20260328_052613/staged/public/val.csv

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SynthData0523/main/c20/forestdiffusion/forest-c20-20260425_021841/_fd_X_host.npy

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SynthData0523/main/c20/forestdiffusion/forest-c20-20260425_021841/_fd_gen.py

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+
+import joblib, pandas as pd
+m, meta = joblib.load(r'/work/output-SpecializedModels/c20/forestdiffusion/forest-c20-20260425_021841/forestdiffusion_model.joblib')
+# generate：batch_size 为样本数
+arr = m.generate(batch_size=int(35855))
+df = pd.DataFrame(arr, columns=meta["column_names"])
+df.to_csv(r'/work/output-SpecializedModels/c20/forestdiffusion/forest-c20-20260425_021841/forest-c20-35855-20260425_073030.csv', index=False)
+print("saved", len(df))

SynthData0523/main/c20/forestdiffusion/forest-c20-20260425_021841/_fd_meta_host.json

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SynthData0523/main/c20/forestdiffusion/forest-c20-20260425_021841/_fd_train.py

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+
+import shutil, json
+shutil.copy(r'/work/output-SpecializedModels/c20/forestdiffusion/forest-c20-20260425_021841/_fd_X_host.npy', '/tmp/fd_X.npy')
+with open(r'/work/output-SpecializedModels/c20/forestdiffusion/forest-c20-20260425_021841/_fd_meta_host.json') as f:
+    open('/tmp/fd_meta.json','w').write(f.read())
+
+import numpy as np, joblib, json, os
+from ForestDiffusion import ForestDiffusionModel
+X = np.load("/tmp/fd_X.npy")
+with open("/tmp/fd_meta.json") as f:
+    meta = json.load(f)
+cat_indexes = meta["cat_indexes"]
+m = ForestDiffusionModel(
+    X, n_t=20, n_estimators=100, duplicate_K=20, n_jobs=2,
+    model="xgboost", max_depth=6, tree_method="hist", cat_indexes=cat_indexes,
+)
+joblib.dump((m, meta), "/tmp/fd_model.joblib")
+print("ForestDiffusion train OK")
+
+shutil.copy('/tmp/fd_model.joblib', r'/work/output-SpecializedModels/c20/forestdiffusion/forest-c20-20260425_021841/forestdiffusion_model.joblib')

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