Python tf.raw_ops.Where用法及代码示例

返回张量中非零/真值的位置。

用法

tf.raw_ops.Where(
    condition, name=None
)

此操作返回 condition 中真实元素的坐标。坐标以二维张量返回，其中第一维(行)表示真实元素的数量，第二维(列)表示真实元素的坐标。请记住，输出张量的形状可能会根据 condition 中有多少真实值而有所不同。索引以行优先顺序输出。

例如：

# 'input' tensor is [[True, False]
#                    [True, False]]
# 'input' has two true values, so output has two coordinates.
# 'input' has rank of 2, so coordinates have two indices.
where(input) ==> [[0, 0],
                  [1, 0]]

# `condition` tensor is [[[True, False]
#                     [True, False]]
#                    [[False, True]
#                     [False, True]]
#                    [[False, False]
#                     [False, True]]]
# 'input' has 5 true values, so output has 5 coordinates.
# 'input' has rank of 3, so coordinates have three indices.
where(input) ==> [[0, 0, 0],
                  [0, 1, 0],
                  [1, 0, 1],
                  [1, 1, 1],
                  [2, 1, 1]]

# `condition` tensor is [[[1.5,  0.0]
#                     [-0.5, 0.0]]
#                    [[0.0,  0.25]
#                     [0.0,  0.75]]
#                    [[0.0,  0.0]
#                     [0.0,  0.01]]]
# 'input' has 5 nonzero values, so output has 5 coordinates.
# 'input' has rank of 3, so coordinates have three indices.
where(input) ==> [[0, 0, 0],
                  [0, 1, 0],
                  [1, 0, 1],
                  [1, 1, 1],
                  [2, 1, 1]]

# `condition` tensor is [[[1.5 + 0.0j, 0.0  + 0.0j]
#                     [0.0 + 0.5j, 0.0  + 0.0j]]
#                    [[0.0 + 0.0j, 0.25 + 1.5j]
#                     [0.0 + 0.0j, 0.75 + 0.0j]]
#                    [[0.0 + 0.0j, 0.0  + 0.0j]
#                     [0.0 + 0.0j, 0.01 + 0.0j]]]
# 'input' has 5 nonzero magnitude values, so output has 5 coordinates.
# 'input' has rank of 3, so coordinates have three indices.
where(input) ==> [[0, 0, 0],
                  [0, 1, 0],
                  [1, 0, 1],
                  [1, 1, 1],
                  [2, 1, 1]]