public static class
StridedSlice.Options
Optional attributes for StridedSlice
Public Methods
| StridedSlice.Options |
beginMask(Long beginMask)
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| StridedSlice.Options |
ellipsisMask(Long ellipsisMask)
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| StridedSlice.Options |
endMask(Long endMask)
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| StridedSlice.Options |
newAxisMask(Long newAxisMask)
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| StridedSlice.Options |
shrinkAxisMask(Long shrinkAxisMask)
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Inherited Methods
| boolean |
equals(Object arg0)
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| final Class<?> |
getClass()
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| int |
hashCode()
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| final void |
notify()
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| final void |
notifyAll()
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| String |
toString()
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| final void |
wait(long arg0, int arg1)
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| final void |
wait(long arg0)
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| final void |
wait()
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Public Methods
public StridedSlice.Options beginMask (Long beginMask)
Parameters
| beginMask | a bitmask where a bit i being 1 means to ignore the begin value and instead use the largest interval possible. At runtime begin[i] will be replaced with `[0, n-1)` if `stride[i] > 0` or `[-1, n-1]` if `stride[i] < 0` |
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public StridedSlice.Options ellipsisMask (Long ellipsisMask)
Parameters
| ellipsisMask | a bitmask where bit `i` being 1 means the `i`th position is actually an ellipsis. One bit at most can be 1. If `ellipsis_mask == 0`, then an implicit ellipsis mask of `1 << (m+1)` is provided. This means that `foo[3:5] == foo[3:5, ...]`. An ellipsis implicitly creates as many range specifications as necessary to fully specify the sliced range for every dimension. For example for a 4-dimensional tensor `foo` the slice `foo[2, ..., 5:8]` implies `foo[2, :, :, 5:8]`. |
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public StridedSlice.Options newAxisMask (Long newAxisMask)
Parameters
| newAxisMask | a bitmask where bit `i` being 1 means the `i`th specification creates a new shape 1 dimension. For example `foo[:4, tf.newaxis, :2]` would produce a shape `(4, 1, 2)` tensor. |
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public StridedSlice.Options shrinkAxisMask (Long shrinkAxisMask)
Parameters
| shrinkAxisMask | a bitmask where bit `i` implies that the `i`th specification should shrink the dimensionality. begin and end must imply a slice of size 1 in the dimension. For example in python one might do `foo[:, 3, :]` which would result in `shrink_axis_mask` being 2. |
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