tf.data.Dastaset.from_generator has error 'charmap' codec cannot encode character \u2022

Question

from keras.models import Sequential
from keras.layers import Dense, Dropout, LSTM, BatchNormalization,Flatten
from keras.optimizers import adam
import tensorflow as tf
import numpy as np

a = np.array([[1,2,3,4,4,5,61,2,3,4,4,5,6],[1,2,3,4,4,5,61,2,3,4,4,5,6],[1,2,3,4,4,5,61,2,3,4,4,5,6],[1,2,3,4,4,5,61,2,3,4,4,5,6]])
y = np.array([[1],[1],[1],[1]])
model = Sequential([
   
    Dense(20, activation="relu"),
    Dense(100, activation="relu"),
    Dense(1, activation="sigmoid")
])

print(np.shape(a))

def generator_aa(a, y, batch_size):
    while True:
        indices = np.random.permutation(len(a))
        for i in range(0, len(indices), batch_size):
            batch_indices = indices[i:i+batch_size]
            yield a[batch_indices], y[batch_indices]



my_opt = adam(learning_rate=0.01)
model.compile(loss='binary_crossentropy', optimizer=my_opt, metrics=['accuracy'])

dataset = tf.data.Dataset.from_generator(generator, args=(a,y,2),     
                                      output_types=('float32', 'float32'),
                                    )
        
model.fit(dataset, epochs=3)

The above code has the following error. I believe it is related to the tf.data.Dataset, the error is like this:

enter image description here

I tried the following, it works fine, not sure what is the issue with my tf.data.Dataset.from_generator.

batch_size=2
model.fit(generator_aa(a,y,2),epochs=2,steps_per_epoch=2)