|
TensorFlow中的tf.slice（）函数详解
1.官方注释2.参数解释3.例子参考
tf.slice()是TensorFlow库中分割张量的一个函数，其定义为def slice(input_, begin, size, name=None):。tf.slice()函数的那些参数设置实在是不好理解，查了好多资料才理解，所以这边记录一下。
1.官方注释
官方的注释如下:
"""Extracts a slice from a tensor.
This operation extracts a slice of size `size` from a tensor `input` starting
at the location specified by `begin`. The slice `size` is represented as a
tensor shape, where `size[i]` is the number of elements of the 'i'th dimension
of `input` that you want to slice. The starting location (`begin`) for the
slice is represented as an offset in each dimension of `input`. In other
words, `begin[i]` is the offset into the 'i'th dimension of `input` that you
want to slice from.
Note that @{tf.Tensor.__getitem__} is typically a more pythonic way to
perform slices, as it allows you to write `foo[3:7, :-2]` instead of
`tf.slice([3, 0], [4, foo.get_shape()[1]-2])`.
`begin` is zero-based; `size` is one-based. If `size[i]` is -1,
all remaining elements in dimension i are included in the
slice. In other words, this is equivalent to setting:
`size[i] = input.dim_size(i) - begin[i]`
This operation requires that:
`0 |