TypeError: only size-1 arrays can be converted to Python scalars (Windows, Python 3.5)

[nikrepp]

Hello,

I run the following code with WordBatch on windows:

import wordbatch from wordbatch.extractors import WordBag from wordbatch.models import FTRL, FM_FTRL import pandas as pd import pandas as pd import numpy as np from sklearn.datasets import make_moons

X, y = make_moons(n_samples=10000, noise=0.7) from sklearn.model_selection import train_test_split X_t, X_v, y_t, y_v = train_test_split(X, y, stratify=y, test_size=0.2, random_state=8)

train_weight = np.array(pd.DataFrame(y_t).replace(1,400).replace(0,1).astype('float64'))

clf = FM_FTRL(alpha=0.5, beta=1, L1=10.0, L2=10.0, D=2 * 20, alpha_fm=0.02, L2_fm=0.0, init_fm=0.01, weight_fm=1.0, D_fm=2, e_noise=0.0, iters=3, inv_link="sigmoid", threads=4 )

clf.fit(X_t, y_t, train_weight) class_pred = clf.predict(X_v)

I get the following error:

TypeError Traceback (most recent call last) in () ---> 30 clf.fit(X_t, y_t, train_weight) 31 class_pred = clf.predict(X_v)

wordbatch\models\fm_ftrl.pyx in wordbatch.models.fm_ftrl.FM_FTRL.fit()

TypeError: only size-1 arrays can be converted to Python scalars

It appears only when WEIGHT is used.

Do you know possible cause?

Thanks, Nikita

[anttttti]

Can you give more details? This doesn't reproduce on Ubuntu 16.04, Python 3.6.4 |Anaconda custom (64-bit), Numpy 1.14.2 and WB 1.35. The model trains fine with this setup.