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I found that the the calculation result of categorical_crossentropy loss function is different from other deep learning libraries, such as tensorflow.
repo code:
theano 1.0.4
import numpy as np
from theano import tensor as T
y_true = np.array([0., 1., 0.], dtype=np.float32)
y_pred = np.array([0.9999999, 0.9999999, 0.0000001], dtype=np.float32)
res = T.nnet.categorical_crossentropy(y_pred, y_true)
print("loss = ", res.eval())
# loss = 1.192093e-07
tensorflow 2.0.0
import numpy as np
import keras
y_true = np.array([0., 1., 0.], dtype=np.float32)
y_pred = np.array([0.9999999, 0.9999999, 0.0000001], dtype=np.float32)
res = keras.losses.categorical_crossentropy(y_true, y_pred)
print("loss = ", res.numpy())
# loss = 0.69314724
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