Is there a process that causes the following error when inserting more than N data for the data to be synthesized?

[limhasic]

Is there a process that causes the following error when inserting more than N data for the data to be synthesized?

Epoch: 0%| | 0/1 [00:00<?, ?it/s]../aten/src/ATen/native/cuda/ScatterGatherKernel.cu:365: operator(): block: [0,0,0], thread: [0,0,0] Assertion idx_dim >= 0 && idx_dim < index_size && "index out of bounds" failed.
../aten/src/ATen/native/cuda/ScatterGatherKernel.cu:365: operator(): block: [0,0,0], thread: [1,0,0] Assertion idx_dim >= 0 && idx_dim < index_size && "index out of bounds" failed.
../aten/src/ATen/native/cuda/ScatterGatherKernel.cu:365: operator(): block: [0,0,0], thread: [3,0,0] Assertion idx_dim >= 0 && idx_dim < index_size && "index out of bounds" failed.
../aten/src/ATen/native/cuda/ScatterGatherKernel.cu:365: operator(): block: [0,0,0], thread: [7,0,0] Assertion idx_dim >= 0 && idx_dim < index_size && "index out of bounds" failed.
../aten/src/ATen/native/cuda/ScatterGatherKernel.cu:365: operator(): block: [0,0,0], thread: [8,0,0] Assertion idx_dim >= 0 && idx_dim < index_size && "index out of bounds" failed.
Epoch: 0%|

`# stdlib
import sys
import warnings

third party

import numpy as np
from sklearn.datasets import load_iris, load_diabetes

synthcity absolute

import synthcity.logger as log
from synthcity.plugins import Plugins
from synthcity.plugins.core.dataloader import GenericDataLoader
import os

CUDA 비활성화

os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
log.add(sink=sys.stderr, level="INFO")
warnings.filterwarnings("ignore")

Note: preprocessing data with OneHotEncoder or StandardScaler is not needed or recommended. Synthcity handles feature encoding and standardization internally.

import pandas as pd
data = pd.read_csv('train.csv')#.drop('Unnamed: 0', axis=1)
data = data.drop('ID' ,axis = 1)
data = data[data['Fraud_Type'] == 'm'] # 왜지?

X = data.drop("Fraud_Type", axis = 1)
y = data["Fraud_Type"]
X["target"] = y

loader = GenericDataLoader(X, target_column="target", sensitive_columns=[])

모델 하이퍼파라미터 정의

plugin_params = dict(
is_classification=True,
n_iter=1, # epochs
lr=0.002,
weight_decay=1e-4,
batch_size=10,
model_type="mlp", # or "resnet"
model_params=dict(
n_layers_hidden=3,
n_units_hidden=256,
dropout=0.0,
),
num_timesteps=500, # timesteps in diffusion
dim_embed=128,
# 성능 로깅
log_interval=10,
)

plugin = Plugins().get("ddpm", **plugin_params)

plugin.fit(loader) # cond = subset_df["Race=Asian or Pacific Islander"] `

Data is from the competition below.
https://dacon.io/competitions/official/236297/codeshare