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I have read all discussions on #5023 and the related issues, but do not seem to find a solution that works.
My problem is that my merror differs between runs, but only when running 'gpu_hist' for the tree method.
Code (including dataset):
#!/home/user/miniconda/envs/xgboost-1.0.2-cuda-10.1/bin/python
import xgboost as xgb
import numpy as np
from sklearn.datasets import fetch_covtype
from sklearn.model_selection import train_test_split
import time
import random
# Fetch dataset using sklearn
cov = fetch_covtype()
X = cov.data
y = cov.target
np.random.seed(0)
random.seed(0) # Python general seed
# Create 0.75/0.25 train/test split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, train_size=0.75, random_state=0)
# Leave most parameters as default
param = {'objective': 'multi:softmax',
'num_class': 8,
'seed': 0,
# 'single_precision_histogram': True
}
# Convert input data from numpy to XGBoost format
dtrain = xgb.DMatrix(X_train, label=y_train)
dtest = xgb.DMatrix(X_test, label=y_test)
# Specify sufficient boosting iterations to reach a minimum
num_round = 100
# GPU Training
param['tree_method'] = 'gpu_hist'
gpu_res = {}
tmp = time.time()
xgb.train(param, dtrain, num_round, evals=[(dtest, 'test')], evals_result=gpu_res)
print("GPU Training Time: %s seconds" % (str(time.time() - tmp)))
I have set the numpy seed, the python random seed, the train test split seed and the XGBoost seed. Furthermore, I tried the single_precision_histogram.
It is reproducible using the 'hist' tree_method.
My environment:
Docker container based on Cuda 10.1, python 3.7 and the following environment:
Dear everyone,
I have read all discussions on #5023 and the related issues, but do not seem to find a solution that works.
My problem is that my merror differs between runs, but only when running 'gpu_hist' for the tree method.
Code (including dataset):
I have set the numpy seed, the python random seed, the train test split seed and the XGBoost seed. Furthermore, I tried the single_precision_histogram.
It is reproducible using the 'hist' tree_method.
My environment:
Docker container based on Cuda 10.1, python 3.7 and the following environment:
I hope that I am not replicating an already existing issue or am overseeing something trivial.
Thank you very much!
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