Resume SynthData0523 main/c5 batch 2

.gitattributes

@@ -4503,3 +4503,36 @@ SynthData0523/main/c5/bayesnet/bayesnet-c5-20260321_061655/train_20260321_061655
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SynthData0523/main/c5/ctgan/ctgan-c5-20260321_065610/public_gate/public_gate_report.json

@@ -0,0 +1,37 @@
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+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c5/c5-test.csv"
+  }
+}

SynthData0523/main/c5/ctgan/ctgan-c5-20260321_065610/public_gate/staged_input_manifest.json

@@ -0,0 +1,472 @@
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SynthData0523/main/c5/ctgan/ctgan-c5-20260321_065610/runtime_result.json

@@ -0,0 +1,14 @@
+{
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+  }
+}

SynthData0523/main/c5/ctgan/ctgan-c5-20260321_065610/staged/ctgan/adapter_report.json

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SynthData0523/main/c5/ctgan/ctgan-c5-20260321_065610/staged/ctgan/adapter_transforms_applied.json

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SynthData0523/main/c5/ctgan/ctgan-c5-20260321_065610/staged/ctgan/model_input_manifest.json

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+          "GRAY"
+        ]
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+          "PINK",
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+      "role": "feature",
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+          "ORANGE",
+          "YELLOW"
+        ]
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+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [
+        "NONE"
+      ],
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+          "LARGE",
+          "EVANESCENT",
+          "FLARING"
+        ]
+      }
+    },
+    {
+      "name": "spore-print-color",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
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+          "BROWN",
+          "WHITE",
+          "YELLOW"
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+      }
+    },
+    {
+      "name": "population",
+      "role": "feature",
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+    },
+    {
+      "name": "habitat",
+      "role": "feature",
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+          "GRASSES",
+          "WOODS",
+          "URBAN",
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+  ],
+  "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/public_gate/staged_input_manifest.json",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c5/ctgan/ctgan-c5-20260321_065610/public_gate/public_gate_report.json"
+}

SynthData0523/main/c5/ctgan/ctgan-c5-20260321_065610/staged/public/staged_features.json

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+[
+  {
+    "feature_name": "class",
+    "data_type": "categorical",
+    "is_target": true
+  },
+  {
+    "feature_name": "cap-shape",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "cap-surface",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "cap-color",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "bruises?",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "odor",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "gill-attachment",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "gill-spacing",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "gill-size",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "gill-color",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "stalk-shape",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "stalk-root",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "stalk-surface-above-ring",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "stalk-surface-below-ring",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "stalk-color-above-ring",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "stalk-color-below-ring",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "veil-type",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "veil-color",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "ring-number",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "ring-type",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "spore-print-color",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "population",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "habitat",
+    "data_type": "categorical",
+    "is_target": false
+  }
+]

SynthData0523/main/c5/ctgan/ctgan-c5-20260321_065610/staged/public/test.csv

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SynthData0523/main/c5/ctgan/ctgan-c5-20260321_065610/staged/public/train.csv

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SynthData0523/main/c5/forestdiffusion/forest-c5-20260511_040339/_fd_X_host.npy

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SynthData0523/main/c5/forestdiffusion/forest-c5-20260511_040339/_fd_gen.py

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+
+import joblib, pandas as pd
+m, meta = joblib.load(r'/work/output-Benchmark-trainonly-v1/c5/forestdiffusion/forest-c5-20260511_040339/forestdiffusion_model.joblib')
+# generate：batch_size 为样本数
+arr = m.generate(batch_size=int(6732))
+df = pd.DataFrame(arr, columns=meta["column_names"])
+df.to_csv(r'/work/output-Benchmark-trainonly-v1/c5/forestdiffusion/forest-c5-20260511_040339/forest-c5-6732-20260511_040341.csv', index=False)
+print("saved", len(df))

SynthData0523/main/c5/forestdiffusion/forest-c5-20260511_040339/_fd_meta_host.json

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+version https://git-lfs.github.com/spec/v1
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SynthData0523/main/c5/forestdiffusion/forest-c5-20260511_040339/_fd_train.py

@@ -0,0 +1,36 @@
+
+import os, shutil, json
+with open('/tmp/pgrep', 'w') as _f:
+    _f.write("#!/usr/bin/env python3\n")
+    _f.write("import subprocess, sys\n")
+    _f.write("ppid = sys.argv[-1]\n")
+    _f.write("out = subprocess.check_output(['ps', '-o', 'pid=', '--ppid', str(ppid)], text=True)\n")
+    _f.write("print(out, end='')\n")
+os.chmod('/tmp/pgrep', 0o755)
+os.environ['PATH'] = '/tmp:' + os.environ.get('PATH', '')
+shutil.copy(r'/work/output-Benchmark-trainonly-v1/c5/forestdiffusion/forest-c5-20260511_040339/_fd_X_host.npy', '/tmp/fd_X.npy')
+with open(r'/work/output-Benchmark-trainonly-v1/c5/forestdiffusion/forest-c5-20260511_040339/_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"]
+print(
+    "[ForestDiffusion] train config: "
+    f"rows={X.shape[0]} cols={X.shape[1]} n_t=2 "
+    f"n_estimators=1 duplicate_K=1 n_jobs=1 "
+    f"max_depth=2 xgb_verbosity=0 xgb_nthread=1",
+    flush=True,
+)
+m = ForestDiffusionModel(
+    X, n_t=2, n_estimators=1, duplicate_K=1, n_jobs=1,
+    model="xgboost", max_depth=2, tree_method="hist", cat_indexes=cat_indexes,
+    verbosity=0, nthread=1,
+)
+joblib.dump((m, meta), "/tmp/fd_model.joblib")
+print("ForestDiffusion train OK")
+
+shutil.copy('/tmp/fd_model.joblib', r'/work/output-Benchmark-trainonly-v1/c5/forestdiffusion/forest-c5-20260511_040339/forestdiffusion_model.joblib')

SynthData0523/main/c5/forestdiffusion/forest-c5-20260511_040339/forest-c5-6732-20260511_040341.csv

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SynthData0523/main/c5/forestdiffusion/forest-c5-20260511_040339/gen_20260511_040341.log

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SynthData0523/main/c5/forestdiffusion/forest-c5-20260511_040339/input_snapshot.json

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SynthData0523/main/c5/forestdiffusion/forest-c5-20260511_040339/models_fd/model.joblib

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SynthData0523/main/c5/realtabformer/rtf-c5-20260328_094434/public_gate/staged_input_manifest.json

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SynthData0523/main/c5/realtabformer/rtf-c5-20260328_094434/realtabformer_features.json

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+    "feature_name": "ring-type",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "spore-print-color",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "population",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "habitat",
+    "data_type": "categorical",
+    "is_target": false
+  }
+]