[INTEL_HPU] Add strided copy op

backends/intel_hpu/kernels/strided_copy_kernel.cc

@@ -0,0 +1,137 @@
+// 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 "kernels/funcs.h"
+#include "kernels/hpu_operator.h"
+#include "utils/utils.h"
+
+namespace custom_kernel {
+struct ContiguousParams {
+  synStridedOpParams params;
+};
+
+class Contiguous : public HpuOperator {
+ public:
+  Contiguous() : HpuOperator("strided_view") {}
+
+  void AddNode(ConvertTensors& ct, ContiguousParams& params) {
+    auto inputs = ct.GetTensors();
+    auto outputs = ct.GetTensors(false);
+    std::vector<synTensor> syn_inputs;
+    syn_inputs.push_back(createTensor(inputs[0].dims.size(),
+                                      inputs[0].type,
+                                      inputs[0].dims,
+                                      true,
+                                      inputs[0].name));
+
+    std::vector<synTensor> syn_outputs;
+    syn_outputs.push_back(createTensor(outputs[0].dims.size(),
+                                       outputs[0].type,
+                                       outputs[0].dims,
+                                       true,
+                                       outputs[0].name));
+
+    synStatus status = synNodeCreate(graphHandle_,
+                                     syn_inputs.data(),
+                                     syn_outputs.data(),
+                                     syn_inputs.size(),
+                                     syn_outputs.size(),
+                                     &params.params,
+                                     sizeof(params.params),
+                                     guid_.c_str(),
+                                     "Contiguous",
+                                     nullptr,
+                                     nullptr);
+    PD_CHECK(
+        status == synSuccess, "[RUNTIME] synNodeCreate () failed = %d", status);
+  }
+};
+
+template <typename T, typename Context>
+void StridedCopyKernel(const Context& dev_ctx,
+                       const phi::DenseTensor& input,
+                       const std::vector<int64_t>& dims,
+                       const std::vector<int64_t>& out_stride,
+                       int64_t offset,
+                       phi::DenseTensor* out) {
+  phi::DenseTensorMeta meta = input.meta();
+
+  ContiguousParams params;
+  params.params.baseOffset = meta.offset / sizeof(T);
+
+  std::vector<int32_t> input_strides = phi::vectorize<int32_t>(meta.strides);
+  auto rank = input_strides.size();
+  for (size_t i = 0; i < rank; i++) {
+    params.params.strides[rank - 1 - i] = input_strides[i];
+  }
+  for (size_t i = rank; i < HABANA_DIM_MAX; i++) {
+    params.params.strides[i] = 0;
+  }
+  // calculate inputs dim
+  std::vector<int64_t> input_dims = phi::vectorize<int64_t>(meta.dims);
+  uint64_t lastElementOffset = 0;
+  for (size_t i = 0; i < rank; i++) {
+    lastElementOffset += input_strides[i] * (input_dims[i] - 1);
+  }
+  int64_t numOfInputElements = params.params.baseOffset + lastElementOffset + 1;
+
+  phi::DenseTensor flat_input(input);
+  phi::DenseTensorMeta fake_meta({input.dtype(), {numOfInputElements}});
+  flat_input.set_meta(fake_meta);
+
+  meta.dims = common::make_ddim(dims);
+  meta.strides = common::make_ddim(out_stride);
+  meta.offset = offset;
+  out->set_meta(meta);
+
+  dev_ctx.template Alloc<T>(out);
+
+  ConvertTensors ct;
+  ct.Add(flat_input);
+  ct.Add(out, false);
+
+  std::vector<DIMS> outputs_dims = ct.GetDims(false);
+  OpCacheOperator op_info;
+  op_info.prepareOpInfo<T, ContiguousParams>(
+      "StridedCopyKernel", outputs_dims, &params);
+  auto recipe = op_info.GetRecipe();
+
+  if (recipe == nullptr) {
+    Contiguous op;
+    op.AddNode(ct, params);
+    op.Compile();
+    op_info.setOp(op);
+    recipe = op_info.GetRecipe();
+  }
+
+  RecipeRunner runner(recipe);
+  auto tensors = ct.GetDeviceAddr();
+  runner.Run(reinterpret_cast<C_Stream>(dev_ctx.stream()), tensors);
+}
+}  // namespace custom_kernel
+
+PD_REGISTER_PLUGIN_KERNEL(strided_copy,
+                          intel_hpu,
+                          ALL_LAYOUT,
+                          custom_kernel::StridedCopyKernel,
+                          uint8_t,
+                          int8_t,
+                          bool,
+                          int16_t,
+                          int32_t,
+                          int64_t,
+                          float,
+                          phi::dtype::float16,
+                          phi::dtype::bfloat16,
+                          phi::dtype::float8_e4m3fn) {}