pub struct AddPaddingOp<Context> { /* private fields */ }
Expand description

| Given a partitioned tensor $T<N, D_1, | …, D_n>$, where the partitions are | defined as ranges on its outer-most | (slowest varying) dimension $N$, return | a tensor $T<(N + 2 * padding_width), | D_1, …, | | D_n>$ with paddings added to the start | and end of each range. | | Optionally, different paddings can | be provided for beginning and end. | | Paddings provided must be a tensor $T<D_1, | …, | | D_n>$. If no padding is provided, add | zero padding. If no lengths vector is | provided, add padding only once, at | the start and end of data. | | Github Links: | | - https://github.com/pytorch/pytorch/blob/master/caffe2/operators/sequence_ops.cc |

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impl<Context> AddPaddingOp<Context>

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pub fn new<Args>(args: Args) -> Self

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pub fn run_on_device(&mut self) -> bool

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pub fn do_run_with_type<T>(&mut self) -> bool

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impl AddPaddingOp<CPUContext>

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pub fn make_padding<T>( &mut self, in_ptr: *const T, out_ptr: *mut T, lengths_ptr: *const i32, lengths_size: i32, outer_size: i32, padding_start_ptr: *const T, padding_end_ptr: *const T, block_size: i64 ) -> bool

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impl<Context> !RefUnwindSafe for AddPaddingOp<Context>

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impl<Context> !Send for AddPaddingOp<Context>

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impl<Context> !Sync for AddPaddingOp<Context>

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impl<Context> Unpin for AddPaddingOp<Context>where Context: Unpin,

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impl<Context> !UnwindSafe for AddPaddingOp<Context>

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