Python diagonal示例

示例#1

def _kl_multivariatenormal_multivariatenormal(dist1, dist2):
    diag = diagonal.diagonal(dist1.scale_tril, axis1=-2, axis2=-1)
    logdet1 = sum_mod.sum(exponential.log(abs(diag)), axis=-1)

    diag = diagonal.diagonal(dist2.scale_tril, axis1=-2, axis2=-1)
    logdet2 = sum_mod.sum(exponential.log(abs(diag)), axis=-1)

    scale_tril_inv2 = _batch_triangular_inv(dist2.scale_tril.reshape(
        -1, dist2.d, dist2.d))
    trace = sum_mod.sum(matmul.matmul(
        scale_tril_inv2, dist1.scale_tril.reshape(-1, dist2.d, dist2.d)) ** 2,
        axis=(-1, -2)).reshape(dist1.batch_shape)

    mu = dist1.loc - dist2.loc
    mah = matmul.matmul(scale_tril_inv2, mu.reshape(-1, dist1.d, 1))
    mah = sum_mod.sum(mah ** 2, axis=-2).reshape(dist1.batch_shape)
    return logdet2 - logdet1 + 0.5 * trace + 0.5 * mah - 0.5 * dist1.d

示例#2

文件： multivariate_normal.py 项目： mitmul/chainer

def _kl_multivariatenormal_multivariatenormal(dist1, dist2):
    diag = diagonal.diagonal(dist1.scale_tril, axis1=-2, axis2=-1)
    logdet1 = sum_mod.sum(exponential.log(abs(diag)), axis=-1)

    diag = diagonal.diagonal(dist2.scale_tril, axis1=-2, axis2=-1)
    logdet2 = sum_mod.sum(exponential.log(abs(diag)), axis=-1)

    scale_tril_inv2 = _batch_triangular_inv(dist2.scale_tril.reshape(
        -1, dist2.d, dist2.d))
    trace = sum_mod.sum(matmul.matmul(
        scale_tril_inv2, dist1.scale_tril.reshape(-1, dist2.d, dist2.d)) ** 2,
        axis=(-1, -2)).reshape(dist1.batch_shape)

    mu = dist1.loc - dist2.loc
    mah = matmul.matmul(scale_tril_inv2, mu.reshape(-1, dist1.d, 1))
    mah = sum_mod.sum(mah ** 2, axis=-2).reshape(dist1.batch_shape)
    return logdet2 - logdet1 + 0.5 * trace + 0.5 * mah - 0.5 * dist1.d

示例#3

 def _logdet(self, x):
     diag = diagonal.diagonal(x, axis1=-2, axis2=-1)
     logdet = sum_mod.sum(
         exponential.log(abs(diag)), axis=-1)
     return logdet

示例#4

def _triangular_logdet(x):
    diag = diagonal.diagonal(x, axis1=-2, axis2=-1)
    return sum_mod.sum(exponential.log(abs(diag)), axis=-1)

示例#5

文件： multivariate_normal.py 项目： mitmul/chainer

 def _logdet(self, x):
     diag = diagonal.diagonal(x, axis1=-2, axis2=-1)
     logdet = sum_mod.sum(
         exponential.log(abs(diag)), axis=-1)
     return logdet

示例#6

文件： multivariate_normal.py 项目： asi1024/chainer

def _triangular_logdet(x):
    diag = diagonal.diagonal(x, axis1=-2, axis2=-1)
    return sum_mod.sum(exponential.log(abs(diag)), axis=-1)