49 lines
1.5 KiB
C++
49 lines
1.5 KiB
C++
// sherpa-onnx/csrc/slice.h
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//
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// Copyright (c) 2023 Xiaomi Corporation
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#ifndef SHERPA_ONNX_CSRC_SLICE_H_
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#define SHERPA_ONNX_CSRC_SLICE_H_
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#include "onnxruntime_cxx_api.h" // NOLINT
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namespace sherpa_onnx {
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/** Get a deep copy by slicing a 3-D tensor v.
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*
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* It returns v[dim0_start:dim0_end, dim1_start:dim1_end, :]
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*
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* @param allocator
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* @param v A 2-D tensor. Its data type is T.
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* @param dim0_start Start index of the first dimension..
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* @param dim0_end End index of the first dimension..
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* @param dim1_start Start index of the second dimension.
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* @param dim1_end End index of the second dimension.
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*
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* @return Return a 3-D tensor of shape
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* (dim0_end-dim0_start, dim1_end-dim1_start, v.shape[2])
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*/
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template <typename T = float>
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Ort::Value Slice(OrtAllocator *allocator, const Ort::Value *v,
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int32_t dim0_start, int32_t dim0_end, int32_t dim1_start,
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int32_t dim1_end);
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/** Get a deep copy by slicing a 2-D tensor v.
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*
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* It returns v[dim0_start:dim0_end, :]
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*
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* @param allocator
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* @param v A 2-D tensor. Its data type is T.
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* @param dim0_start Start index of the first dimension..
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* @param dim0_end End index of the first dimension..
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*
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* @return Return a 2-D tensor of shape
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* (dim0_end-dim0_start, v.shape[1])
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*/
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template <typename T = float>
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Ort::Value Slice(OrtAllocator *allocator, const Ort::Value *v,
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int32_t dim0_start, int32_t dim0_end);
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} // namespace sherpa_onnx
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#endif // SHERPA_ONNX_CSRC_SLICE_H_
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