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SynthData0523/main/n3/realtabformer/rtf-n3-20260505_024350/train_20260505_024350.log

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SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/_tabbyflow_gen.py

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+
+import os, shutil, subprocess, sys
+root = r"/workspace/ef-vfm"
+name = r"pipeline_n3"
+src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260501_005234/tabular_bundle/pipeline_n3"
+dst_data = os.path.join(root, "data", name)
+shutil.rmtree(dst_data, ignore_errors=True)
+shutil.copytree(src, dst_data)
+dst_syn = os.path.join(root, "synthetic", name)
+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(root)
+os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "")
+subprocess.check_call([
+    sys.executable, "main.py",
+    "--dataname", name, "--mode", "test", "--gpu", "0",
+    "--no_wandb", "--exp_name", r"adapter_efvfm",
+    "--ckpt_path", r"/workspace/ef-vfm/ef_vfm/ckpt/pipeline_n3/adapter_efvfm/model_500.pt",
+    "--num_samples_to_generate", str(int(3918)),
+])
+base = os.path.join(root, "ef_vfm", "result", name, r"adapter_efvfm")
+best = None
+best_t = -1.0
+for r, _, files in os.walk(base):
+    if "samples.csv" in files:
+        p = os.path.join(r, "samples.csv")
+        t = os.path.getmtime(p)
+        if t > best_t:
+            best_t, best = t, p
+if not best:
+    raise SystemExit("tabbyflow: no samples.csv in " + base)
+shutil.copy(best, r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260501_005234/tabbyflow-n3-3918-20260501_005942.csv")

SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/_tabbyflow_train.py

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+
+import os, shutil, subprocess, sys
+root = r"/workspace/ef-vfm"
+name = r"pipeline_n3"
+src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260501_005234/tabular_bundle/pipeline_n3"
+os.makedirs(os.path.join(root, "data", name), exist_ok=True)
+dst_data = os.path.join(root, "data", name)
+dst_syn = os.path.join(root, "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(root)
+os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "")
+os.environ["EFVFM_SMOKE_STEPS"] = "500"
+os.environ["EFVFM_ADAPTER_TRAIN"] = "1"
+subprocess.check_call([
+    sys.executable, "main.py",
+    "--dataname", name, "--mode", "train", "--gpu", "0",
+    "--no_wandb", "--exp_name", r"adapter_efvfm",
+])

SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/gen_20260501_005942.log

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SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/input_snapshot.json

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+{
+  "dataset_id": "n3",
+  "model": "tabbyflow",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n3/n3-train.csv",
+      "exists": true,
+      "size": 211519,
+      "sha256": "2160a06db2fea02adb0ebb79d8d853bd2544580be301e71f6e8deeb1489a9009"
+    },
+    "val_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n3/n3-val.csv",
+      "exists": true,
+      "size": 26499,
+      "sha256": "d5ccfee07dfa9e7bdee5bb87642b43828e09f74c6cc0266a3d19d9feaa83106e"
+    },
+    "test_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n3/n3-test.csv",
+      "exists": true,
+      "size": 26676,
+      "sha256": "6f83aacb0d1747b95e287352a7fff5d9d65a1c127b773852346c68485c4ede47"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n3/n3-dataset_profile.json",
+      "exists": true,
+      "size": 5235,
+      "sha256": "23d2e5904a2ca90cbf8d6e3c75887681721e9b90cc705c31a680c11513d0c46f"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n3/n3-dataset_contract_v1.json",
+      "exists": true,
+      "size": 6281,
+      "sha256": "c0cc56f5fe28e1b65927255c6e3c2b0e9479862c2ec6f2fea1664da36c9a3a09"
+    }
+  }
+}

SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/models_tabbyflow/trained.pt

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+version https://git-lfs.github.com/spec/v1
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+size 40

SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/public_gate/normalized_schema_snapshot.json

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SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/public_gate/public_gate_report.json

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+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n3/n3-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n3/n3-test.csv"
+  }
+}

SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260501_005234/public_gate/staged_input_manifest.json

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+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260501_005234/public_gate/public_gate_report.json",
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+root = r"/workspace/ef-vfm"
+name = r"pipeline_n3"
+src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_010259/tabular_bundle/pipeline_n3"
+dst_data = os.path.join(root, "data", name)
+shutil.rmtree(dst_data, ignore_errors=True)
+shutil.copytree(src, dst_data)
+dst_syn = os.path.join(root, "synthetic", name)
+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(root)
+os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "")
+os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128")
+subprocess.check_call([
+    sys.executable, "main.py",
+    "--dataname", name, "--mode", "test", "--gpu", "0",
+    "--no_wandb", "--exp_name", r"adapter_efvfm",
+    "--ckpt_path", r"/workspace/ef-vfm/ef_vfm/ckpt/pipeline_n3/adapter_efvfm/model_500.pt",
+    "--num_samples_to_generate", str(int(3918)),
+])
+base = os.path.join(root, "ef_vfm", "result", name, r"adapter_efvfm")
+best = None
+best_t = -1.0
+for r, _, files in os.walk(base):
+    if "samples.csv" in files:
+        p = os.path.join(r, "samples.csv")
+        t = os.path.getmtime(p)
+        if t > best_t:
+            best_t, best = t, p
+if not best:
+    raise SystemExit("tabbyflow: no samples.csv in " + base)
+shutil.copy(best, r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_010259/tabbyflow-n3-3918-20260505_010451.csv")

SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010259/_tabbyflow_train.py

@@ -0,0 +1,24 @@
+
+import os, shutil, subprocess, sys
+root = r"/workspace/ef-vfm"
+name = r"pipeline_n3"
+src = r"/work/output-Benchmark-trainonly-v1/n3/tabbyflow/tabbyflow-n3-20260505_010259/tabular_bundle/pipeline_n3"
+os.makedirs(os.path.join(root, "data", name), exist_ok=True)
+dst_data = os.path.join(root, "data", name)
+dst_syn = os.path.join(root, "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(root)
+os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "")
+os.environ["EFVFM_SMOKE_STEPS"] = "100"
+os.environ["EFVFM_ADAPTER_TRAIN"] = "1"
+os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128")
+os.environ.setdefault("EFVFM_EVAL_NUM_SAMPLES", "512")
+subprocess.check_call([
+    sys.executable, "main.py",
+    "--dataname", name, "--mode", "train", "--gpu", "0",
+    "--no_wandb", "--exp_name", r"adapter_efvfm",
+])

SynthData0523/main/n3/tabbyflow/tabbyflow-n3-20260505_010259/gen_20260505_010451.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2207d6f293ecd0e612f9dd8f2b81fd12cf4cd60b1c0e2e76fee2985655f5c5a8
+size 3945