[Reshard] Support reshard with same status but different mesh

paddle/fluid/pybind/auto_parallel_py.cc

@@ -45,6 +45,7 @@
 #include "paddle/phi/core/distributed/auto_parallel/r_to_s_reshard_function.h"
 #include "paddle/phi/core/distributed/auto_parallel/s_to_r_reshard_function.h"
 #include "paddle/phi/core/distributed/auto_parallel/s_to_s_reshard_function.h"
+#include "paddle/phi/core/distributed/auto_parallel/same_status_reshard_function.h"
 #include "paddle/phi/core/enforce.h"
 
 #ifdef PADDLE_WITH_DISTRIBUTE
@@ -200,6 +201,10 @@ void BindAutoParallel(py::module *m) {
       *m, "SameNdMeshReshardFunction", ReshardFunction)
       .def(py::init<>());
 
+  py::class_<phi::distributed::SameStatusReshardFunction>(
+      *m, "SameStatusReshardFunction", ReshardFunction)
+      .def(py::init<>());
+
   py::class_<ProcessMesh>(*m, "ProcessMesh")
       .def(py::init<>())
       .def(py::init<const std::vector<int64_t> &,

paddle/phi/core/distributed/auto_parallel/CMakeLists.txt

@@ -17,4 +17,5 @@ collect_srcs(
   r_to_p_reshard_function.cc
   p_to_r_reshard_function.cc
   s_to_s_reshard_function.cc
-  nd_mesh_reshard_function.cc)
+  nd_mesh_reshard_function.cc
+  same_status_reshard_function.cc)

paddle/phi/core/distributed/auto_parallel/dist_tensor.cc

@@ -18,6 +18,7 @@
 #include "paddle/phi/backends/context_pool.h"
 #include "paddle/phi/core/distributed/auto_parallel/reshard_function.h"
 #include "paddle/phi/core/distributed/auto_parallel/reshard_utils.h"
+#include "paddle/phi/core/distributed/store/store_utils.h"
 
 namespace phi {
 namespace distributed {
@@ -35,20 +36,27 @@ inline void check_defined(const DistTensor& dist_tensor,
 DistTensor::DistTensor(const phi::DenseTensor& global_value,
                        const TensorDistAttr& dist_attr)
     : dims_(global_value.dims()), dist_attr_(dist_attr), value_(global_value) {
-  if (value_.initialized() && !dist_attr.is_replicated()) {
-    // 1. create replicated global tensor
-    int64_t dims_size = global_value.dims().size();
-    std::vector<int64_t> dims_mapping(dims_size, -1);
-    dist_attr_.set_dims_mapping(dims_mapping);
-    if (dist_attr_.is_partial()) {
-      dist_attr_.clean_partial_status();
+  // TODO(liyurui): This is a temporary solution. We need to support only infer
+  // meta when the input dense_tensor is empty.
+  // Support the value in DistTensor only has DenseTensor meta
+  // but without actual data. So we can visit its meta attr even if it is
+  // undefined.
+  if (IsCurRankInMesh(dist_attr.process_mesh())) {
+    if (value_.initialized() && !dist_attr.is_replicated()) {
+      // 1. create replicated global tensor
+      int64_t dims_size = global_value.dims().size();
+      std::vector<int64_t> dims_mapping(dims_size, -1);
+      dist_attr_.set_dims_mapping(dims_mapping);
+      if (dist_attr_.is_partial()) {
+        dist_attr_.clean_partial_status();
+      }
+      dist_attr_.set_dims_mapping(dims_mapping);
+
+      // 2. reshard from replicated to other state
+      auto* func = ChooseProperReshardFunction(*this, dist_attr);
+      auto* dev_ctx = DeviceContextPool::Instance().Get(global_value.place());
+      func->Eval(dev_ctx, *this, dist_attr, this);
     }
-    dist_attr_.set_dims_mapping(dims_mapping);
-
-    // 2. reshard from replicated to other state
-    auto* func = ChooseProperReshardFunction(*this, dist_attr);
-    auto* dev_ctx = DeviceContextPool::Instance().Get(global_value.place());
-    func->Eval(dev_ctx, *this, dist_attr, this);
   }
 }
 

paddle/phi/core/distributed/auto_parallel/reshard_utils.cc

@@ -24,13 +24,6 @@ namespace phi {
 namespace distributed {
 
 namespace {
-int64_t GetLocalRankInParticipate(const std::vector<int64_t>& process_ids) {
-  int64_t cur_global_rank = GetCurGlobalRank();
-  auto iter =
-      std::find(process_ids.begin(), process_ids.end(), cur_global_rank);
-  return iter - process_ids.begin();
-}
-
 std::string GenUniqueCommKey(const std::vector<int64_t>& process_ids) {
   std::string unique_comm_key = "ReshardGroup";
   for (const auto& id : process_ids) {
@@ -40,6 +33,20 @@ std::string GenUniqueCommKey(const std::vector<int64_t>& process_ids) {
 }
 }  // namespace
 
+int64_t GetLocalRankInParticipate(const std::vector<int64_t>& process_ids,
+                                  int64_t global_rank) {
+  if (global_rank == -1) {
+    global_rank = GetCurGlobalRank();
+  }
+  auto iter = std::find(process_ids.begin(), process_ids.end(), global_rank);
+  PADDLE_ENFORCE_NE(
+      iter,
+      process_ids.end(),
+      phi::errors::NotFound("Global rank %lld cannot be found in process_mesh",
+                            global_rank));
+  return iter - process_ids.begin();
+}
+
 std::vector<int64_t> GetCurRankCoordInMesh(const ProcessMesh& process_mesh) {
   const auto& process_shape = process_mesh.shape();
   const auto& process_ids = process_mesh.process_ids();
@@ -132,5 +139,12 @@ std::vector<int64_t> BalancedSplit(int64_t total_nums, int64_t num_of_pieces) {
   return result;
 }
 
+bool IsCurRankInMesh(const ProcessMesh& process_mesh) {
+  int64_t cur_global_rank = GetCurGlobalRank();
+  const auto& process_ids = process_mesh.process_ids();
+  return (std::find(process_ids.begin(), process_ids.end(), cur_global_rank) !=
+          process_ids.end());
+}
+
 }  // namespace distributed
 }  // namespace phi

paddle/phi/core/distributed/auto_parallel/reshard_utils.h

@@ -30,6 +30,11 @@ class DeviceContext;
 namespace distributed {
 class ProcessMesh;
 
+bool IsCurRankInMesh(const ProcessMesh& process_mesh);
+
+int64_t GetLocalRankInParticipate(const std::vector<int64_t>& process_ids,
+                                  int64_t global_rank = -1);
+
 // Get the coordinate of cur rank in process mesh. For example, the process mesh
 // is [[0, 1], [2, 3], [4, 5], [6, 7]], if the current rank is 4, then will
 // return [2, 0]; if the current rank is 3, then will return [1, 1].

paddle/phi/core/distributed/auto_parallel/same_status_reshard_function.cc

@@ -0,0 +1,121 @@
+// Copyright (c) 2023 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/core/distributed/auto_parallel/same_status_reshard_function.h"
+
+#include <algorithm>
+
+#include "glog/logging.h"
+#include "paddle/phi/core/distributed/auto_parallel/dist_attr.h"
+#include "paddle/phi/core/distributed/auto_parallel/dist_tensor.h"
+#include "paddle/phi/core/distributed/auto_parallel/reshard_utils.h"
+#include "paddle/phi/core/distributed/store/store_utils.h"
+#include "paddle/phi/kernels/p_recv_kernel.h"
+#include "paddle/phi/kernels/p_send_kernel.h"
+
+namespace phi {
+namespace distributed {
+
+namespace {
+
+std::vector<int64_t> GetUnionProcessIds(std::vector<int64_t> in_process_ids,
+                                        std::vector<int64_t> out_process_ids) {
+  std::vector<int64_t> result;
+  std::sort(in_process_ids.begin(), in_process_ids.end());
+  std::sort(out_process_ids.begin(), out_process_ids.end());
+  std::set_union(in_process_ids.begin(),
+                 in_process_ids.end(),
+                 out_process_ids.begin(),
+                 out_process_ids.end(),
+                 std::back_inserter(result));
+  return result;
+}
+
+}  // namespace
+
+bool SameStatusReshardFunction::IsSuitable(
+    const DistTensor& in, const TensorDistAttr& out_dist_attr) {
+  bool flag = true;
+  const auto& in_dist_attr = in.dist_attr();
+
+  flag &= (in_dist_attr.dims_mapping() == out_dist_attr.dims_mapping());
+  flag &= (in_dist_attr.partial_dims() == out_dist_attr.partial_dims());
+
+  const auto& in_process_mesh = in_dist_attr.process_mesh();
+  const auto& out_process_mesh = out_dist_attr.process_mesh();
+  flag &= (in_process_mesh != out_process_mesh);
+  flag &= (in_process_mesh.shape() == out_process_mesh.shape());
+
+  return flag;
+}
+
+void SameStatusReshardFunction::Eval(phi::DeviceContext* dev_ctx,
+                                     const DistTensor& in,
+                                     const TensorDistAttr& out_dist_attr,
+                                     DistTensor* out) {
+  const auto& in_dist_attr = in.dist_attr();
+  const auto& in_process_mesh = in_dist_attr.process_mesh();
+  const auto& in_process_ids = in_process_mesh.process_ids();
+  const auto& out_process_mesh = out_dist_attr.process_mesh();
+  const auto& out_process_ids = out_process_mesh.process_ids();
+  auto all_process_ids = GetUnionProcessIds(in_process_ids, out_process_ids);
+  auto dtype = in.dtype();
+  // TODO(liyurui): Use dynamic shape will lead to poor performance, but we
+  // don't have any other good idea now. For the following reasons:
+  // 1. We can not ensure the meta being right deduce by the infermeta.
+  // 2. The meta of some kernels can't decide in compile time.
+  // 3. DenseTensor with empty value only need infermeta and skip the real
+  // kernel execution.
+  bool dynamic_shape = true;
+
+  std::vector<std::pair<int64_t, int64_t>> p2p_pair;
+  for (size_t i = 0; i < out_process_ids.size(); ++i) {
+    p2p_pair.emplace_back(
+        std::make_pair(in_process_ids[i], out_process_ids[i]));
+  }
+
+  int64_t cur_global_rank = GetCurGlobalRank();
+  for (const auto& iter : p2p_pair) {
+    int64_t src = iter.first;
+    int64_t dst = iter.second;
+    VLOG(3) << "Send/Recv from src " << src << " to dst " << dst;
+    if (src == cur_global_rank) {
+      int64_t dst_local_rank = GetLocalRankInParticipate(all_process_ids, dst);
+      // Sice send kernel only has input, so we don't need to infermeta
+      // actually. According to this reason, just use the kernel directly.
+      RESHARD_FUNCTOR_WITH_COMM(dev_ctx,
+                                PSendKernel,
+                                dtype,
+                                all_process_ids,
+                                in.value(),
+                                dst_local_rank,
+                                dynamic_shape);
+    } else if (dst == cur_global_rank) {
+      int64_t src_local_rank = GetLocalRankInParticipate(all_process_ids, src);
+      RESHARD_FUNCTOR_WITH_COMM(dev_ctx,
+                                PRecv,
+                                dtype,
+                                all_process_ids,
+                                src_local_rank,
+                                dynamic_shape,
+                                GetMutableTensor(out));
+    }
+  }
+  SetDistProps(out, in.dims(), out_dist_attr);
+}
+
+REGISTER_RESHARD_FUNC(SameStatusReshardFunction);
+
+}  // namespace distributed
+}  // namespace phi

paddle/phi/core/distributed/auto_parallel/same_status_reshard_function.h

@@ -0,0 +1,34 @@
+// Copyright (c) 2023 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.
+
+#pragma once
+
+#include "paddle/phi/core/distributed/auto_parallel/reshard_function.h"
+
+namespace phi {
+namespace distributed {
+
+class SameStatusReshardFunction final : public ReshardFunction {
+ public:
+  bool IsSuitable(const DistTensor& in,
+                  const TensorDistAttr& out_dist_attr) override;
+
+  void Eval(DeviceContext* dev_ctx,
+            const DistTensor& in,
+            const TensorDistAttr& out_dist_attr,
+            DistTensor* out) override;
+};
+
+}  // namespace distributed
+}  // namespace phi

paddle/phi/core/distributed/store/store_utils.cc

@@ -48,19 +48,17 @@ std::string GetMasterEndpoint() {
 
 int64_t GetCurGlobalRank() {
   const char* cur_rank = std::getenv("PADDLE_TRAINER_ID");
-  PADDLE_ENFORCE_NOT_NULL(
-      cur_rank,
-      phi::errors::NotFound(
-          "The environment variable 'PADDLE_TRAINER_ID' cannot be found."));
+  if (cur_rank == nullptr) {
+    return 0;
+  }
   return std::atoi(cur_rank);
 }
 
 int64_t GetGlobalWorldSize() {
   const char* world_size = std::getenv("PADDLE_TRAINERS_NUM");
-  PADDLE_ENFORCE_NOT_NULL(
-      world_size,
-      phi::errors::NotFound(
-          "The environment variable 'PADDLE_TRAINERS_NUM' cannot be found."));
+  if (world_size == nullptr) {
+    return 1;
+  }
   return std::atoi(world_size);
 }
 

paddle/phi/kernels/cpu/p_recv_kernel.cc

@@ -54,6 +54,7 @@ PD_REGISTER_KERNEL(p_recv,
                    bool,
                    int8_t,
                    uint8_t,
+                   int16_t,
                    int64_t,
                    phi::dtype::float16) {}
 
@@ -67,5 +68,6 @@ PD_REGISTER_KERNEL(p_recv_array,
                    bool,
                    int8_t,
                    uint8_t,
+                   int16_t,
                    int64_t,
                    phi::dtype::float16) {}

paddle/phi/kernels/cpu/p_send_kernel.cc

@@ -53,6 +53,7 @@ PD_REGISTER_KERNEL(p_send,
                    bool,
                    int8_t,
                    uint8_t,
+                   int16_t,
                    int64_t,
                    phi::dtype::float16) {}
 
@@ -66,5 +67,6 @@ PD_REGISTER_KERNEL(p_send_array,
                    bool,
                    int8_t,
                    uint8_t,
+                   int16_t,
                    int64_t,
                    phi::dtype::float16) {}

paddle/phi/kernels/gpu/p_recv_kernel.cu

@@ -190,6 +190,7 @@ PD_REGISTER_KERNEL(p_recv,
                    bool,
                    int8_t,
                    uint8_t,
+                   int16_t,
                    int64_t,
                    phi::dtype::bfloat16,
                    phi::dtype::float16) {}
@@ -218,6 +219,7 @@ PD_REGISTER_KERNEL(p_recv,
                    bool,
                    int8_t,
                    uint8_t,
+                   int16_t,
                    int64_t,
                    phi::dtype::float16) {}
 

paddle/phi/kernels/gpu/p_send_kernel.cu

@@ -178,6 +178,7 @@ PD_REGISTER_KERNEL(p_send,
                    bool,
                    int8_t,
                    uint8_t,
+                   int16_t,
                    int64_t,
                    phi::dtype::bfloat16,
                    phi::dtype::float16) {}
@@ -206,6 +207,7 @@ PD_REGISTER_KERNEL(p_send,
                    bool,
                    int8_t,
                    uint8_t,
+                   int16_t,
                    int64_t,
                    phi::dtype::float16) {}