distributions.py 文件源码

def sample_dtype(self):
        return tf.int32

# WRONG SECOND DERIVATIVES
# class CategoricalPd(Pd):
#     def __init__(self, logits):
#         self.logits = logits
#         self.ps = tf.nn.softmax(logits)
#     @classmethod
#     def fromflat(cls, flat):
#         return cls(flat)
#     def flatparam(self):
#         return self.logits
#     def mode(self):
#         return U.argmax(self.logits, axis=1)
#     def logp(self, x):
#         return -tf.nn.sparse_softmax_cross_entropy_with_logits(self.logits, x)
#     def kl(self, other):
#         return tf.nn.softmax_cross_entropy_with_logits(other.logits, self.ps) \
#                 - tf.nn.softmax_cross_entropy_with_logits(self.logits, self.ps)
#     def entropy(self):
#         return tf.nn.softmax_cross_entropy_with_logits(self.logits, self.ps)
#     def sample(self):
#         u = tf.random_uniform(tf.shape(self.logits))
#         return U.argmax(self.logits - tf.log(-tf.log(u)), axis=1)