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sha256:73544a68ce12d9a3954ea8187523cfb72ebfda7d909e0678bc9c594b6c1f249d +size 4800851 diff --git a/SynthData0523/main/m8/tabpfgen/tabpfgen-m8-20260501_041014/tabpfgen_meta.json b/SynthData0523/main/m8/tabpfgen/tabpfgen-m8-20260501_041014/tabpfgen_meta.json new file mode 100644 index 0000000000000000000000000000000000000000..4c3b2889d9b9eeaf2f3d71e76dcb00a24d5868db --- /dev/null +++ b/SynthData0523/main/m8/tabpfgen/tabpfgen-m8-20260501_041014/tabpfgen_meta.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bca2a71ae737138e26f018bf1b9f308a21f30a28fe2e02f4b2c7c011c7aeaf42 +size 442 diff --git a/SynthData0523/main/m8/tabpfgen/tabpfgen-m8-20260501_041014/train_20260501_041015.log b/SynthData0523/main/m8/tabpfgen/tabpfgen-m8-20260501_041014/train_20260501_041015.log new file mode 100644 index 0000000000000000000000000000000000000000..75dfdf806a4337531097c304ca46843f3c2ef6f7 --- /dev/null +++ b/SynthData0523/main/m8/tabpfgen/tabpfgen-m8-20260501_041014/train_20260501_041015.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:adf60cf4bb06aa19e6e6234ca72b24e46110e57714d374ed37dff34ceb1a38d8 +size 595 diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/_tabsyn_sample.py b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/_tabsyn_sample.py new file mode 100644 index 0000000000000000000000000000000000000000..5d6eee3a7df834c856342d3fa5412adf42f91853 --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/_tabsyn_sample.py @@ -0,0 +1,39 @@ +import os, sys, subprocess + +work_dir = "/work/output-SpecializedModels/m8/tabsyn/tabsyn-m8-20260420_230925" +dataname = "tabsyn_m8" +output_csv = "/work/output-SpecializedModels/m8/tabsyn/tabsyn-m8-20260420_230925/tabsyn-m8-36168-20260421_005047.csv" +tabsyn_root = "/workspace/tabsyn" + +assert os.path.exists(tabsyn_root), f"TabSyn source not mounted: {tabsyn_root}" + +old = os.environ.get("PYTHONPATH", "") +os.environ["PYTHONPATH"] = tabsyn_root + (os.pathsep + old if old else "") +sys.path.insert(0, tabsyn_root) + +os.chdir(tabsyn_root) + +# Ensure data symlink exists +data_link = os.path.join(tabsyn_root, "data", dataname) +data_src = os.path.join(work_dir, "data", dataname) +os.makedirs(os.path.join(tabsyn_root, "data"), exist_ok=True) +if os.path.exists(data_link): + os.remove(data_link) +os.symlink(data_src, data_link) + +print(f"[TabSyn] Sampling 36168 rows") +env = os.environ.copy() +env.setdefault("TABSYN_RESUME", "1") +ret = subprocess.run( + [sys.executable, "main.py", + "--dataname", dataname, + "--mode", "sample", + "--method", "tabsyn", + "--gpu", "0", + "--save_path", output_csv], + cwd=tabsyn_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) +print(f"[TabSyn] Saved -> {output_csv}") diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/_tabsyn_train.py b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/_tabsyn_train.py new file mode 100644 index 0000000000000000000000000000000000000000..c459551e52aa9604a740b1c8cfa937009ce798bf --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/_tabsyn_train.py @@ -0,0 +1,62 @@ +import os, sys, subprocess + +work_dir = "/work/output-SpecializedModels/m8/tabsyn/tabsyn-m8-20260420_230925" +dataname = "tabsyn_m8" +tabsyn_root = "/workspace/tabsyn" + +assert os.path.exists(tabsyn_root), f"TabSyn source not mounted: {tabsyn_root}" + +old = os.environ.get("PYTHONPATH", "") +os.environ["PYTHONPATH"] = tabsyn_root + (os.pathsep + old if old else "") +sys.path.insert(0, tabsyn_root) + +os.chdir(tabsyn_root) + +# Symlink data dir into TabSyn data/ +data_link = os.path.join(tabsyn_root, "data", dataname) +data_src = os.path.join(work_dir, "data", dataname) +os.makedirs(os.path.join(tabsyn_root, "data"), exist_ok=True) +if os.path.exists(data_link): + os.remove(data_link) +os.symlink(data_src, data_link) + +env = os.environ.copy() +env.setdefault("TABSYN_RESUME", "1") +_te = None +if _te is not None: + env["TABSYN_VAE_EPOCHS"] = str(_te) + env["TABSYN_DIFFUSION_MAX_EPOCHS"] = str(max(_te + 1, 2)) + +# Data preprocessing is done on the host side (_prepare_data_dir) +# which creates .npy files, train/test CSVs, and info.json + +# Step 1: Train VAE (produces latent embeddings) +print(f"[TabSyn] Step 1/2: Training VAE in {tabsyn_root}, dataname={dataname}") +ret = subprocess.run( + [sys.executable, "main.py", + "--dataname", dataname, + "--mode", "train", + "--method", "vae", + "--gpu", "0"], + cwd=tabsyn_root, + env=env +) +if ret.returncode != 0: + print("[TabSyn] VAE training failed") + sys.exit(ret.returncode) + +# Step 2: Train diffusion model on latent space +print(f"[TabSyn] Step 2/2: Training diffusion model") +ret = subprocess.run( + [sys.executable, "main.py", + "--dataname", dataname, + "--mode", "train", + "--method", "tabsyn", + "--gpu", "0"], + cwd=tabsyn_root, + env=env +) +if ret.returncode != 0: + print("[TabSyn] Diffusion training failed") + sys.exit(ret.returncode) +print("[TabSyn] Training complete (VAE + Diffusion)") diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/X_cat_test.npy b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/X_cat_test.npy new file mode 100644 index 0000000000000000000000000000000000000000..922026ef7352eeffb4f4433919127d9767c257e4 --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/X_cat_test.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b56f1f1b7c8959f505e4a23ab45ff41a1c1cf4cf8e543affa9bc528122451e3a +size 325712 diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/X_cat_train.npy b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/X_cat_train.npy new file mode 100644 index 0000000000000000000000000000000000000000..09b3d6ecd05c408c0ce2b6d4d40b60bf097ef547 --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/X_cat_train.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c19ea036a6e636c4f03ca4f40d3a7c1e45c4b6ed5ebd9636405393d4810d695a +size 2929736 diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/X_num_test.npy b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/X_num_test.npy new file mode 100644 index 0000000000000000000000000000000000000000..f9cf206785192d97965eee4ea30dd08808aa8365 --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/X_num_test.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2b2724f29951cc2e602d10a7c82b57c4195ba6724f76660c2c4fc108eb8a5b36 +size 126744 diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/X_num_train.npy b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/X_num_train.npy new file mode 100644 index 0000000000000000000000000000000000000000..80d7307defae4d56c488db10b1a21f8023f259d7 --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/X_num_train.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dd9e45e023d45f9c5cec9cb44ce403ecff8d3ecf44931c62cd98ea5f4e8e23cf +size 1139420 diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/info.json b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/info.json new file mode 100644 index 0000000000000000000000000000000000000000..52014a84204904b9cd2bb5fa71f3d4a1fd9a40fa --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/data/tabsyn_m8/info.json @@ -0,0 +1,175 @@ +{ + "name": "tabsyn_m8", + "task_type": "multiclass", + "n_num_features": 7, + "n_cat_features": 9, + "train_size": 40689, + "num_col_idx": [ 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sha256:8a98d0c20fa375b2fc72c29d69e2fddbd8bd708a73919b0ba0f609dc92f57d76 +size 670 diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/input_snapshot.json b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..fb0c42e475e34706a8a778875e8cd9fd19e6839c --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "m8", + "model": "tabsyn", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m8/m8-train.csv", + "exists": true, + "size": 2964802, + "sha256": "f9cbb71aa793de19869a138d41aea5808f772b31082741b185ffb8ca7b821833" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m8/m8-val.csv", + "exists": true, + "size": 370535, + "sha256": "5ee8612128aae92155906abc0fdc752ac24fd04d63c78c080c89e3900efe6525" + }, + "test_csv": { + "path": 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newline at end of file diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/synthetic/tabsyn_m8/real.csv b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/synthetic/tabsyn_m8/real.csv new file mode 100644 index 0000000000000000000000000000000000000000..1dfa3756b65ae971ee86d6b777332abc5317a69e --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/synthetic/tabsyn_m8/real.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d8f5840c3788e1d52e1535d3cdae7e814a450f5b0683c4097d9a15adde55a8be +size 1662550 diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/synthetic/tabsyn_m8/test.csv b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/synthetic/tabsyn_m8/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..ae796b09266de6e09591553688401ee62c5d024d --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/synthetic/tabsyn_m8/test.csv @@ -0,0 +1,3 @@ +version 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b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260420_230925/train_20260420_230928.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c3c15166ce422e5d6b1cda812cc67580de8a3dafd695f990a27991830a14e0bf +size 3631424 diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/_tabsyn_sample.py b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/_tabsyn_sample.py new file mode 100644 index 0000000000000000000000000000000000000000..72470aa2de30fbca27af07b6ccf097b3a05f1aaa --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/_tabsyn_sample.py @@ -0,0 +1,39 @@ +import os, sys, subprocess + +work_dir = "/work/output-Benchmark-trainonly-v1/m8/tabsyn/tabsyn-m8-20260501_041249" +dataname = "tabsyn_m8" +output_csv = "/work/output-Benchmark-trainonly-v1/m8/tabsyn/tabsyn-m8-20260501_041249/tabsyn-m8-36168-20260501_052934.csv" +tabsyn_root = "/workspace/tabsyn" + +assert os.path.exists(tabsyn_root), f"TabSyn source not mounted: {tabsyn_root}" + +old = os.environ.get("PYTHONPATH", "") +os.environ["PYTHONPATH"] = tabsyn_root + (os.pathsep + old if old else "") +sys.path.insert(0, tabsyn_root) + +os.chdir(tabsyn_root) + +# Ensure data symlink exists +data_link = os.path.join(tabsyn_root, "data", dataname) +data_src = os.path.join(work_dir, "data", dataname) +os.makedirs(os.path.join(tabsyn_root, "data"), exist_ok=True) +if os.path.exists(data_link): + os.remove(data_link) +os.symlink(data_src, data_link) + +print(f"[TabSyn] Sampling 36168 rows") +env = os.environ.copy() +env.setdefault("TABSYN_RESUME", "1") +ret = subprocess.run( + [sys.executable, "main.py", + "--dataname", dataname, + "--mode", "sample", + "--method", "tabsyn", + "--gpu", "0", + "--save_path", output_csv], + cwd=tabsyn_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) +print(f"[TabSyn] Saved -> {output_csv}") diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/_tabsyn_train.py b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/_tabsyn_train.py new file mode 100644 index 0000000000000000000000000000000000000000..1d9ba5dc060c64f0a613f74a493785f1ec730055 --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/_tabsyn_train.py @@ -0,0 +1,65 @@ +import os, sys, subprocess + +work_dir = "/work/output-Benchmark-trainonly-v1/m8/tabsyn/tabsyn-m8-20260501_041249" +dataname = "tabsyn_m8" +tabsyn_root = "/workspace/tabsyn" + +assert os.path.exists(tabsyn_root), f"TabSyn source not mounted: {tabsyn_root}" + +old = os.environ.get("PYTHONPATH", "") +os.environ["PYTHONPATH"] = tabsyn_root + (os.pathsep + old if old else "") +sys.path.insert(0, tabsyn_root) + +os.chdir(tabsyn_root) + +# Symlink data dir into TabSyn data/ +data_link = os.path.join(tabsyn_root, "data", dataname) +data_src = os.path.join(work_dir, "data", dataname) +os.makedirs(os.path.join(tabsyn_root, "data"), exist_ok=True) +if os.path.exists(data_link): + os.remove(data_link) +os.symlink(data_src, data_link) + +env = os.environ.copy() +env.setdefault("TABSYN_RESUME", "1") +env.setdefault("TABSYN_VAE_BATCH_SIZE", "1024") +# Safer defaults for wide tables on Docker: reduce shared-memory pressure in diffusion DataLoader. +env.setdefault("TABSYN_DIFFUSION_NUM_WORKERS", "0") +_te = None +if _te is not None: + env["TABSYN_VAE_EPOCHS"] = str(_te) + env["TABSYN_DIFFUSION_MAX_EPOCHS"] = str(max(_te + 1, 2)) + +# Data preprocessing is done on the host side (_prepare_data_dir) +# which creates .npy files, train/test CSVs, and info.json + +# Step 1: Train VAE (produces latent embeddings) +print(f"[TabSyn] Step 1/2: Training VAE in {tabsyn_root}, dataname={dataname}") +ret = subprocess.run( + [sys.executable, "main.py", + "--dataname", dataname, + "--mode", "train", + "--method", "vae", + "--gpu", "0"], + cwd=tabsyn_root, + env=env +) +if ret.returncode != 0: + print("[TabSyn] VAE training failed") + sys.exit(ret.returncode) + +# Step 2: Train diffusion model on latent space +print(f"[TabSyn] Step 2/2: Training diffusion model") +ret = subprocess.run( + [sys.executable, "main.py", + "--dataname", dataname, + "--mode", "train", + "--method", "tabsyn", + "--gpu", "0"], + cwd=tabsyn_root, + env=env +) +if ret.returncode != 0: + print("[TabSyn] Diffusion training failed") + sys.exit(ret.returncode) +print("[TabSyn] Training complete (VAE + Diffusion)") diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/data/tabsyn_m8/X_cat_test.npy b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/data/tabsyn_m8/X_cat_test.npy new file mode 100644 index 0000000000000000000000000000000000000000..dfaa4e2bc4a57a6eb51233a33b8a5fd7f2f93a4a --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/data/tabsyn_m8/X_cat_test.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0d99902744d834e11e1488b296a6cbdc2c1f9ea547184c42c2e8e7ce08364d8f +size 2604224 diff --git 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b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/tabsyn-m8-36168-20260501_052934.csv new file mode 100644 index 0000000000000000000000000000000000000000..41db089c7ca1d65879e0a415fd11d5531ccc2859 --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/tabsyn-m8-36168-20260501_052934.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:749006a55e442a625d744199ebe10553dd87e705346655de2e10a9e0189fba2d +size 3701860 diff --git a/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/train_20260501_041250.log b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/train_20260501_041250.log new file mode 100644 index 0000000000000000000000000000000000000000..2616afb916a485273206f1e68a181d57d1bdc4b0 --- /dev/null +++ b/SynthData0523/main/m8/tabsyn/tabsyn-m8-20260501_041249/train_20260501_041250.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bca6471647633c03de726a570dd88454c7ca77e42c73cc12c9cc51c1cf6049eb +size 5116388 diff --git a/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/_tvae_generate.py b/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/_tvae_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..473b5a43c88883ef905145ec56ffd65e38e1af7a --- /dev/null +++ b/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/_tvae_generate.py @@ -0,0 +1,18 @@ +import sys +sys.path.insert(0, "/work") +from src.SpecificModels.ctgan_rdt_inverse_fix import apply_ctgan_inverse_fix +apply_ctgan_inverse_fix() +import pandas as pd +from ctgan.synthesizers.tvae import TVAE +model = TVAE.load("/work/output-SpecializedModels/m8/tvae/tvae-m8-20260419_192253/models_300epochs/tvae_300epochs.pt") +total = 36168 +chunk = min(50000, total) if total > 50000 else total +parts = [] +left = total +while left > 0: + take = min(chunk, left) + parts.append(model.sample(take)) + left -= take +samples = pd.concat(parts, ignore_index=True) if len(parts) > 1 else parts[0] +samples.to_csv("/work/output-SpecializedModels/m8/tvae/tvae-m8-20260419_192253/tvae-m8-36168-20260419_194252.csv", index=False) +print(f"[TVAE] Generated {total} rows (chunks={len(parts)}) -> /work/output-SpecializedModels/m8/tvae/tvae-m8-20260419_192253/tvae-m8-36168-20260419_194252.csv") diff --git a/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/_tvae_train.py b/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/_tvae_train.py new file mode 100644 index 0000000000000000000000000000000000000000..c0d63586a23f7aa59c97e7c03c034d3f4db4abdc --- /dev/null +++ b/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/_tvae_train.py @@ -0,0 +1,16 @@ +import json, sys +import pandas as pd +from ctgan.data import read_csv +from ctgan.synthesizers.tvae import TVAE + +csv_path = "/work/output-SpecializedModels/m8/tvae/tvae-m8-20260419_192253/staged/public/train.csv" +meta_path = "/work/output-SpecializedModels/m8/tvae/tvae-m8-20260419_192253/tvae_metadata.json" +save_path = "/work/output-SpecializedModels/m8/tvae/tvae-m8-20260419_192253/models_300epochs/tvae_300epochs.pt" +epochs = 300 + +data, discrete_columns = read_csv(csv_path, meta_path, header=True, discrete=None) +print(f"[TVAE] Training on {len(data)} rows, {len(data.columns)} cols, epochs={epochs}") +model = TVAE(epochs=epochs, batch_size=500) +model.fit(data, discrete_columns) +model.save(save_path) +print(f"[TVAE] Model saved -> {save_path}") diff --git a/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/gen_20260419_194252.log b/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/gen_20260419_194252.log new file mode 100644 index 0000000000000000000000000000000000000000..9d790e3e328bb131def40f0cae6e96af0204dcb8 --- /dev/null +++ b/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/gen_20260419_194252.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6ea4699897673e4a415716cb4a5f511c88c0c5d047a6ae4a76caee7e55ed8c99 +size 139 diff --git a/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/input_snapshot.json b/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..bcb7e1b12eb711001b34b13d667b25bea1fd4143 --- /dev/null +++ b/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "m8", + "model": "tvae", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m8/m8-train.csv", + "exists": true, + "size": 2964802, + "sha256": "f9cbb71aa793de19869a138d41aea5808f772b31082741b185ffb8ca7b821833" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m8/m8-val.csv", + "exists": true, + "size": 370535, + "sha256": "5ee8612128aae92155906abc0fdc752ac24fd04d63c78c080c89e3900efe6525" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m8/m8-test.csv", + "exists": true, + "size": 370991, + "sha256": "6221943e422e75c8317b79b7ef93e9cd01f61fdd8de6ce42909a8e4610966310" + }, + "profile_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m8/m8-dataset_profile.json", + "exists": true, + "size": 6553, + "sha256": "44f883858641584035a0a8859cb95dbcd3a023c03cbc76931aadfc4c70ef871f" + }, + "contract_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m8/m8-dataset_contract_v1.json", + "exists": true, + "size": 8214, + "sha256": "e76df134780ec9b6c6c625a54e5d0c1935e9f4a7d09320ad19279a0492438d92" + } + } +} \ No newline at end of file diff --git a/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/models_300epochs/train_20260419_192254.log b/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/models_300epochs/train_20260419_192254.log new file mode 100644 index 0000000000000000000000000000000000000000..4d1319195c61199072109befaf3eb04eb4ab1b2c --- /dev/null +++ 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"example_values": [ + "no", + "yes" + ] + } + } + ], + "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m8/tvae/tvae-m8-20260419_192253/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m8/tvae/tvae-m8-20260419_192253/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m8/tvae/tvae-m8-20260419_192253/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m8/tvae/tvae-m8-20260419_192253/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m8/tvae/tvae-m8-20260419_192253/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m8/tvae/tvae-m8-20260419_192253/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/tvae-m8-36168-20260419_194252.csv b/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/tvae-m8-36168-20260419_194252.csv new file mode 100644 index 0000000000000000000000000000000000000000..713c5cf2b3501c14fa0c55a9a1120f4e07b034b6 --- /dev/null +++ b/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/tvae-m8-36168-20260419_194252.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2e80f4bb821090465eec686a5c181ee536eb2ce63090d89d0b802e9c90fbbed1 +size 2922942 diff --git a/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/tvae_metadata.json b/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/tvae_metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..e4311b6e09b701b44e2d352b6d6f50ef5702793a --- /dev/null +++ b/SynthData0523/main/m8/tvae/tvae-m8-20260419_192253/tvae_metadata.json @@ -0,0 +1,72 @@ +{ + "columns": [ + { + "name": "age", + "type": "continuous" + }, + { + "name": "job", + "type": "categorical" + }, + { + "name": "marital", + "type": "categorical" + }, + { + "name": "education", + "type": "categorical" + }, + { + "name": "default", + "type": "categorical" + }, + { + "name": "balance", + "type": "continuous" + }, + { + "name": "housing", + "type": "categorical" + }, + { + "name": "loan", + "type": "categorical" + }, + { + "name": "contact", + "type": "categorical" + }, + { + "name": "day", + "type": "continuous" + }, + { + "name": "month", + "type": "categorical" + }, + { + "name": "duration", + "type": "continuous" + }, + { + "name": "campaign", + "type": "continuous" + }, + { + "name": "pdays", + "type": "continuous" + }, + { + "name": "previous", + "type": "continuous" + }, + { + "name": "poutcome", + "type": "categorical" + }, + { + "name": "y", + "type": "categorical" + } + ] +} \ No newline at end of file diff --git a/SynthData0523/main/m8/tvae/tvae-m8-20260501_055847/_tvae_generate.py b/SynthData0523/main/m8/tvae/tvae-m8-20260501_055847/_tvae_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..f47b334efe1734d573bbf45d3fafae0128d146c6 --- /dev/null +++ b/SynthData0523/main/m8/tvae/tvae-m8-20260501_055847/_tvae_generate.py @@ -0,0 +1,23 @@ +import os, sys +sys.path.insert(0, "/work") +from src.SpecificModels.ctgan_joblib_parallel_cap import apply_parallel_cap_from_env +apply_parallel_cap_from_env() +from src.SpecificModels.ctgan_rdt_inverse_fix import apply_ctgan_inverse_fix +apply_ctgan_inverse_fix() +import pandas as pd +from ctgan.synthesizers.tvae import TVAE +os.environ.setdefault("LOKY_MAX_CPU_COUNT", "8") +os.environ.setdefault("OPENBLAS_NUM_THREADS", "8") +os.environ.setdefault("MKL_NUM_THREADS", "8") +model = TVAE.load("/work/output-Benchmark-trainonly-v1/m8/tvae/tvae-m8-20260501_055847/models_300epochs/tvae_300epochs.pt") +total = 36168 +chunk = min(50000, total) if total > 50000 else total +parts = [] +left = total +while left > 0: + take = min(chunk, left) + parts.append(model.sample(take)) + left -= take +samples = pd.concat(parts, ignore_index=True) if len(parts) > 1 else parts[0] +samples.to_csv("/work/output-Benchmark-trainonly-v1/m8/tvae/tvae-m8-20260501_055847/tvae-m8-36168-20260501_060307.csv", index=False) +print(f"[TVAE] Generated {total} rows (chunks={len(parts)}) -> /work/output-Benchmark-trainonly-v1/m8/tvae/tvae-m8-20260501_055847/tvae-m8-36168-20260501_060307.csv") diff --git a/SynthData0523/main/m8/tvae/tvae-m8-20260501_055847/_tvae_train.py b/SynthData0523/main/m8/tvae/tvae-m8-20260501_055847/_tvae_train.py new file mode 100644 index 0000000000000000000000000000000000000000..69eef92bbb44aaab7bb99b98a6d725b1f7f45645 --- /dev/null +++ b/SynthData0523/main/m8/tvae/tvae-m8-20260501_055847/_tvae_train.py @@ -0,0 +1,30 @@ +import json, os, sys +sys.path.insert(0, "/work") +from src.SpecificModels.ctgan_joblib_parallel_cap import apply_parallel_cap_from_env +apply_parallel_cap_from_env() +import pandas as pd +from ctgan.data import read_csv +from ctgan.synthesizers.tvae import TVAE + +# Keep transform stage parallelism bounded for stability on shared host. +os.environ.setdefault("LOKY_MAX_CPU_COUNT", "8") +os.environ.setdefault("OPENBLAS_NUM_THREADS", "8") +os.environ.setdefault("MKL_NUM_THREADS", "8") +_nj = (os.environ.get("TVAE_CTGAN_JOBTRANS_N_JOBS") or "").strip() +if _nj: + print("[TVAE] joblib Parallel cap ON, TVAE_CTGAN_JOBTRANS_N_JOBS=" + _nj) +else: + print("[TVAE] joblib Parallel cap OFF (unset TVAE_CTGAN_JOBTRANS_N_JOBS)") +print("[TVAE] LOKY_MAX_CPU_COUNT=" + str(os.environ.get("LOKY_MAX_CPU_COUNT", ""))) + +csv_path = "/work/output-Benchmark-trainonly-v1/m8/tvae/tvae-m8-20260501_055847/staged/public/train.csv" +meta_path = "/work/output-Benchmark-trainonly-v1/m8/tvae/tvae-m8-20260501_055847/tvae_metadata.json" +save_path = "/work/output-Benchmark-trainonly-v1/m8/tvae/tvae-m8-20260501_055847/models_300epochs/tvae_300epochs.pt" +epochs = 300 + +data, discrete_columns = read_csv(csv_path, meta_path, header=True, discrete=None) +print(f"[TVAE] Training on {len(data)} rows, {len(data.columns)} cols, epochs={epochs}") +model = TVAE(epochs=epochs, batch_size=500) +model.fit(data, discrete_columns) +model.save(save_path) +print(f"[TVAE] Model saved -> {save_path}") diff --git a/SynthData0523/main/m8/tvae/tvae-m8-20260501_055847/gen_20260501_060307.log b/SynthData0523/main/m8/tvae/tvae-m8-20260501_055847/gen_20260501_060307.log new file mode 100644 index 0000000000000000000000000000000000000000..07b374bf268db958ab89fd4172f989abee2f50c8 --- /dev/null +++ b/SynthData0523/main/m8/tvae/tvae-m8-20260501_055847/gen_20260501_060307.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:178a801c5e38643c3ac46d8b92c798424648b05e57d99eb37979e38c392b3331 +size 406 diff --git a/SynthData0523/main/m8/tvae/tvae-m8-20260501_055847/input_snapshot.json b/SynthData0523/main/m8/tvae/tvae-m8-20260501_055847/input_snapshot.json new file 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