/* Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/phi/kernels/range_kernel.h" #include "paddle/phi/backends/cpu/cpu_context.h" #include "paddle/phi/common/amp_type_traits.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/kernels/funcs/range_function.h" namespace phi { template void RangeFunc(const Context& dev_ctx, const T& start_value, const T& end_value, const T& step_value, DenseTensor* out) { int64_t size = static_cast((end_value - start_value) / step_value + 1); out->Resize({size}); T* out_data = dev_ctx.template Alloc(out); if (size == 0) { return; } T value = start_value; for (int64_t i = 0; i < size; ++i) { out_data[i] = value; value += step_value; } } template void RangeTensorKernel(const Context& dev_ctx, const DenseTensor& start, const DenseTensor& end, const DenseTensor& step, DenseTensor* out) { int64_t size = 0; using MPType = typename phi::dtype::MPTypeTrait::Type; Scalar start_scalar(start); Scalar end_scalar(end); Scalar step_scalar(step); MPType start_value = start_scalar.to(); MPType end_value = end_scalar.to(); MPType step_value = step_scalar.to(); funcs::GetSizeForRange(start_value, end_value, step_value, &size); out->Resize({size}); T* out_data = dev_ctx.template Alloc(out); if (size == 0) { return; } MPType value = start_value; for (int64_t i = 0; i < size; ++i) { out_data[i] = static_cast(value); value += step_value; } } template void RangeKernel(const Context& dev_ctx, const Scalar& start, const Scalar& end, const Scalar& step, DenseTensor* out) { int64_t size = 0; using MPType = typename phi::dtype::MPTypeTrait::Type; MPType start_value = start.to(); MPType end_value = end.to(); MPType step_value = step.to(); funcs::GetSizeForRange(start_value, end_value, step_value, &size); out->Resize({size}); T* out_data = dev_ctx.template Alloc(out); if (size == 0) { return; } MPType value = start_value; for (int64_t i = 0; i < size; ++i) { out_data[i] = static_cast(value); value += step_value; } } } // namespace phi PD_REGISTER_KERNEL(range_tensor, CPU, ALL_LAYOUT, phi::RangeTensorKernel, float, double, int, int64_t) {} PD_REGISTER_KERNEL( range, CPU, ALL_LAYOUT, phi::RangeKernel, float, double, int, int64_t) {}