/*!
 *  Copyright (c) 2021 by Contributors
 * \file ndarray_partition.cc
 * \brief DGL utilities for working with the partitioned NDArrays
 */

#include "ndarray_partition.h"

#include <dgl/runtime/registry.h>
#include <dgl/runtime/packed_func.h>
#include <utility>
#include <memory>

#include "partition_op.h"

using namespace dgl::runtime;

namespace dgl {
namespace partition {

NDArrayPartition::NDArrayPartition(
    const int64_t array_size, const int num_parts) :
  array_size_(array_size),
  num_parts_(num_parts) {
}

int64_t NDArrayPartition::ArraySize() const {
  return array_size_;
}

int NDArrayPartition::NumParts() const {
  return num_parts_;
}


class RemainderPartition : public NDArrayPartition {
 public:
  RemainderPartition(
      const int64_t array_size, const int num_parts) :
    NDArrayPartition(array_size, num_parts) {
    // do nothing
  }

  std::pair<IdArray, NDArray>
  GeneratePermutation(
      IdArray in_idx) const override {
#ifdef DGL_USE_CUDA
    auto ctx = in_idx->ctx;
    if (ctx.device_type == kDLGPU) {
      ATEN_ID_TYPE_SWITCH(in_idx->dtype, IdType, {
        return impl::GeneratePermutationFromRemainder<kDLGPU, IdType>(
            ArraySize(), NumParts(), in_idx);
      });
    }
#endif

    LOG(FATAL) << "Remainder based partitioning for the CPU is not yet "
        "implemented.";
    // should be unreachable
    return std::pair<IdArray, NDArray>{};
  }

  IdArray MapToLocal(
      IdArray in_idx) const override {
#ifdef DGL_USE_CUDA
    auto ctx = in_idx->ctx;
    if (ctx.device_type == kDLGPU) {
      ATEN_ID_TYPE_SWITCH(in_idx->dtype, IdType, {
        return impl::MapToLocalFromRemainder<kDLGPU, IdType>(
            NumParts(), in_idx);
      });
    }
#endif

    LOG(FATAL) << "Remainder based partitioning for the CPU is not yet "
        "implemented.";
    // should be unreachable
    return IdArray{};
  }

  IdArray MapToGlobal(
      IdArray in_idx,
      const int part_id) const override {
#ifdef DGL_USE_CUDA
    auto ctx = in_idx->ctx;
    if (ctx.device_type == kDLGPU) {
      ATEN_ID_TYPE_SWITCH(in_idx->dtype, IdType, {
        return impl::MapToGlobalFromRemainder<kDLGPU, IdType>(
            NumParts(), in_idx, part_id);
      });
    }
#endif

    LOG(FATAL) << "Remainder based partitioning for the CPU is not yet "
        "implemented.";
    // should be unreachable
    return IdArray{};
  }

  int64_t PartSize(const int part_id) const override {
    CHECK_LT(part_id, NumParts()) << "Invalid part ID (" << part_id << ") for "
        "partition of size " << NumParts() << ".";
    return ArraySize() / NumParts() + (part_id < ArraySize() % NumParts());
  }
};

class RangePartition : public NDArrayPartition {
 public:
  RangePartition(
      const int64_t array_size,
      const int num_parts,
      IdArray range) :
    NDArrayPartition(array_size, num_parts),
    range_(range),
    // We also need a copy of the range on the CPU, to compute partition
    // sizes. We require the input range on the GPU, as if we have multiple
    // GPUs, we can't know which is the proper one to copy the array to, but we
    // have only one CPU context, and can safely copy the array to that.
    range_cpu_(range.CopyTo(DGLContext{kDLCPU, 0})) {
    auto ctx = range->ctx;
    if (ctx.device_type != kDLGPU) {
        LOG(FATAL) << "The range for an NDArrayPartition is only supported "
            " on GPUs. Transfer the range to the target device before "
            "creating the partition.";
    }
  }

  std::pair<IdArray, NDArray>
  GeneratePermutation(
      IdArray in_idx) const override {
#ifdef DGL_USE_CUDA
    auto ctx = in_idx->ctx;
    if (ctx.device_type == kDLGPU) {
      if (ctx.device_type != range_->ctx.device_type ||
          ctx.device_id != range_->ctx.device_id) {
        LOG(FATAL) << "The range for the NDArrayPartition and the input "
            "array must be on the same device: " << ctx << " vs. " << range_->ctx;
      }
      ATEN_ID_TYPE_SWITCH(in_idx->dtype, IdType, {
        ATEN_ID_TYPE_SWITCH(range_->dtype, RangeType, {
          return impl::GeneratePermutationFromRange<kDLGPU, IdType, RangeType>(
              ArraySize(), NumParts(), range_, in_idx);
        });
      });
    }
#endif

    LOG(FATAL) << "Remainder based partitioning for the CPU is not yet "
        "implemented.";
    // should be unreachable
    return std::pair<IdArray, NDArray>{};
  }

  IdArray MapToLocal(
      IdArray in_idx) const override {
#ifdef DGL_USE_CUDA
    auto ctx = in_idx->ctx;
    if (ctx.device_type == kDLGPU) {
      ATEN_ID_TYPE_SWITCH(in_idx->dtype, IdType, {
        ATEN_ID_TYPE_SWITCH(range_->dtype, RangeType, {
          return impl::MapToLocalFromRange<kDLGPU, IdType, RangeType>(
              NumParts(), range_, in_idx);
        });
      });
    }
#endif

    LOG(FATAL) << "Remainder based partitioning for the CPU is not yet "
        "implemented.";
    // should be unreachable
    return IdArray{};
  }

  IdArray MapToGlobal(
      IdArray in_idx,
      const int part_id) const override {
#ifdef DGL_USE_CUDA
    auto ctx = in_idx->ctx;
    if (ctx.device_type == kDLGPU) {
      ATEN_ID_TYPE_SWITCH(in_idx->dtype, IdType, {
        ATEN_ID_TYPE_SWITCH(range_->dtype, RangeType, {
          return impl::MapToGlobalFromRange<kDLGPU, IdType, RangeType>(
              NumParts(), range_, in_idx, part_id);
        });
      });
    }
#endif

    LOG(FATAL) << "Remainder based partitioning for the CPU is not yet "
        "implemented.";
    // should be unreachable
    return IdArray{};
  }

  int64_t PartSize(const int part_id) const override {
    CHECK_LT(part_id, NumParts()) << "Invalid part ID (" << part_id << ") for "
        "partition of size " << NumParts() << ".";
    ATEN_ID_TYPE_SWITCH(range_cpu_->dtype, RangeType, {
      const RangeType * const ptr = static_cast<const RangeType*>(range_cpu_->data);
      return ptr[part_id+1]-ptr[part_id];
    });
  }

 private:
  IdArray range_;
  IdArray range_cpu_;
};

NDArrayPartitionRef CreatePartitionRemainderBased(
    const int64_t array_size,
    const int num_parts) {
  return NDArrayPartitionRef(std::make_shared<RemainderPartition>(
          array_size, num_parts));
}

NDArrayPartitionRef CreatePartitionRangeBased(
    const int64_t array_size,
    const int num_parts,
    IdArray range) {
  return NDArrayPartitionRef(std::make_shared<RangePartition>(
      array_size,
      num_parts,
      range));
}

DGL_REGISTER_GLOBAL("partition._CAPI_DGLNDArrayPartitionCreateRemainderBased")
.set_body([] (DGLArgs args, DGLRetValue* rv) {
  int64_t array_size = args[0];
  int num_parts = args[1];

  *rv = CreatePartitionRemainderBased(array_size, num_parts);
});

DGL_REGISTER_GLOBAL("partition._CAPI_DGLNDArrayPartitionCreateRangeBased")
.set_body([] (DGLArgs args, DGLRetValue* rv) {
  const int64_t array_size = args[0];
  const int num_parts = args[1];
  IdArray range = args[2];

  *rv = CreatePartitionRangeBased(array_size, num_parts, range);
});



DGL_REGISTER_GLOBAL("partition._CAPI_DGLNDArrayPartitionGetPartSize")
.set_body([] (DGLArgs args, DGLRetValue* rv) {
  NDArrayPartitionRef part = args[0];
  int part_id = args[1];

  *rv = part->PartSize(part_id);
});

DGL_REGISTER_GLOBAL("partition._CAPI_DGLNDArrayPartitionMapToLocal")
.set_body([] (DGLArgs args, DGLRetValue* rv) {
  NDArrayPartitionRef part = args[0];
  IdArray idxs = args[1];

  *rv = part->MapToLocal(idxs);
});

DGL_REGISTER_GLOBAL("partition._CAPI_DGLNDArrayPartitionMapToGlobal")
.set_body([] (DGLArgs args, DGLRetValue* rv) {
  NDArrayPartitionRef part = args[0];
  IdArray idxs = args[1];
  const int part_id = args[2];

  *rv = part->MapToGlobal(idxs, part_id);
});


}  // namespace partition
}  // namespace dgl
