wehub-resource-sync
116 lines
3.7 KiB
C++
116 lines
3.7 KiB
C++
// Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <ATen/core/Tensor.h>
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namespace at {
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inline at::Tensor narrow(const at::Tensor& self,
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int64_t dim,
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int64_t start,
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int64_t length) {
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// Bounds checks matching PyTorch behavior
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PD_CHECK(self.dim() > 0, "narrow() cannot be applied to a 0-dim tensor.");
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PD_CHECK(length >= 0, "narrow(): length must be non-negative.");
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// Normalize negative dim
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int64_t ndim = self.dim();
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if (dim < 0) dim += ndim;
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PD_CHECK(dim >= 0 && dim < ndim,
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"start out of range (expected to be in range of [",
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-ndim,
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", ",
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ndim - 1,
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"], but got ",
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dim,
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")");
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int64_t cur_size = self.sizes()[dim];
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// Wrap negative start (matching PyTorch: only wrap when start != cur_size)
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if (start < 0) {
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start = start + cur_size;
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}
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PD_CHECK(start <= cur_size - length,
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"start (",
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start,
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") + length (",
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length,
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") exceeds dimension size (",
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cur_size,
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").");
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// Use slice to implement narrow: narrow(dim, start, length) is equivalent
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// to slice(dim, start, start + length)
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return Tensor(paddle::experimental::slice(
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self._PD_GetInner(), {dim}, {start}, {start + length}, {1}, {}));
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}
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inline at::Tensor narrow_symint(const at::Tensor& self,
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int64_t dim,
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c10::SymInt start,
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c10::SymInt length) {
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return narrow(self, dim, start, length);
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}
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inline at::Tensor narrow(const at::Tensor& self,
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int64_t dim,
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const at::Tensor& start,
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int64_t length) {
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// Extract scalar value from start tensor
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PD_CHECK(start.numel() == 1,
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"start must be a 0-dim tensor or 1-element tensor");
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int64_t start_val = start.item<int64_t>();
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return narrow(self, dim, start_val, length);
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}
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inline at::Tensor narrow_symint(const at::Tensor& self,
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int64_t dim,
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const at::Tensor& start,
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c10::SymInt length) {
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return narrow(self, dim, start, length);
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}
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} // namespace at
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namespace at {
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inline at::Tensor Tensor::narrow(int64_t dim,
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int64_t start,
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int64_t length) const {
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return at::narrow(*this, dim, start, length);
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}
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inline at::Tensor Tensor::narrow_symint(int64_t dim,
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c10::SymInt start,
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c10::SymInt length) const {
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return at::narrow_symint(*this, dim, start, length);
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}
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inline at::Tensor Tensor::narrow(int64_t dim,
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const at::Tensor& start,
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int64_t length) const {
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return at::narrow(*this, dim, start, length);
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}
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inline at::Tensor Tensor::narrow_symint(int64_t dim,
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const at::Tensor& start,
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c10::SymInt length) const {
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return at::narrow_symint(*this, dim, start, length);
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}
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} // namespace at
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