/* Copyright (c) 2021 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. */
// disable numpy compile error
#include <Python.h>
// Avoid a problem with copysign defined in pyconfig.h on Windows.
#ifdef copysign
#undef copysign
#endif

#include <string>
#include <vector>

#include "paddle/fluid/eager/accumulation/accumulation_node.h"
#include "paddle/fluid/eager/api/all.h"
#include "paddle/fluid/eager/autograd_meta.h"
#include "paddle/fluid/eager/utils.h"
#include "paddle/fluid/imperative/op_base.h"
#include "paddle/fluid/memory/allocation/allocator.h"
#include "paddle/fluid/memory/memcpy.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/pybind/eager.h"
#include "paddle/fluid/pybind/eager_utils.h"
#include "paddle/fluid/pybind/exception.h"
#include "paddle/phi/common/data_type.h"
#include "paddle/phi/core/compat/convert_utils.h"
#include "paddle/phi/core/dense_tensor.h"

#pragma GCC diagnostic ignored "-Wwrite-strings"

namespace paddle {
namespace pybind {

extern PyTypeObject* p_tensor_type;

PyObject* tensor_properties_get_name(TensorObject* self, void* closure) {
  EAGER_TRY
  // NOTE(dev): [why not use egr::Controller::Instance::GenerateUniqueName()?]
  // Because Controller must holder a tracer, but 'tensor.name' maybe called
  // everywhere such as static graph mode in @to_static, which means tracer is
  // None.
  static egr::UniqueNameGenerator name_generator;
  if (self->tensor.name().empty()) {
    self->tensor.set_name(name_generator.Generate());
  }
  return ToPyObject(self->tensor.name());
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

PyObject* tensor_properties_get_type(TensorObject* self, void* closure) {
  EAGER_TRY
  if (!self->tensor.defined()) {
    // be same to old dygraph
    return ToPyObject(paddle::framework::proto::VarType::LOD_TENSOR);
  }
  if (self->tensor.is_dense_tensor()) {
    return ToPyObject(paddle::framework::proto::VarType::LOD_TENSOR);
  } else if (self->tensor.is_selected_rows()) {
    return ToPyObject(paddle::framework::proto::VarType::SELECTED_ROWS);
  } else if (egr::IsVariableCompatTensor(self->tensor)) {
    return ToPyObject(static_cast<paddle::framework::proto::VarType::Type>(
        static_cast<const egr::VariableCompatTensor*>(self->tensor.impl().get())
            ->Type()));
  } else {
    RETURN_PY_NONE
  }
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

PyDoc_STRVAR(tensor_is_leaf__doc__,  // NOLINT
             R"DOC(is_leaf

Whether a Tensor is leaf Tensor.

For the Tensor whose stop_gradient is ``True`` , it will be leaf Tensor.

For the Tensor whose stop_gradient is ``False`` , it will be leaf Tensor too if it is created by user.

Returns:
    bool: Whether a Tensor is leaf Tensor.

Examples:
    .. code-block:: python

        import paddle

        x = paddle.to_tensor(1.)
        print(x.is_leaf) # True

        x = paddle.to_tensor(1., stop_gradient=True)
        y = x + 1
        print(x.is_leaf) # True
        print(y.is_leaf) # True

        x = paddle.to_tensor(1., stop_gradient=False)
        y = x + 1
        print(x.is_leaf) # True
        print(y.is_leaf) # False
)DOC");

PyObject* tensor_properties_is_leaf(TensorObject* self, void* closure) {
  EAGER_TRY
  return ToPyObject(egr::EagerUtils::IsLeafTensor(self->tensor));
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

int tensor_properties_set_name(TensorObject* self,
                               PyObject* value,
                               void* closure) {
  EAGER_TRY
  self->tensor.set_name(CastPyArg2AttrString(value, 0));
  return 0;
  EAGER_CATCH_AND_THROW_RETURN_NEG
}

PyObject* tensor_properties_get_stop_gradient(TensorObject* self,
                                              void* closure) {
  EAGER_TRY
  auto meta = egr::EagerUtils::autograd_meta(&self->tensor);
  return ToPyObject(meta->StopGradient());
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

PyObject* tensor_properties_get_data(TensorObject* self, void* closure) {
  EAGER_TRY
  return reinterpret_cast<PyObject*>(self);
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

int tensor_properties_set_data(TensorObject* self,
                               PyObject* value,
                               void* closure) {
  EAGER_TRY
  auto src = CastPyArg2Tensor(value, 0);
  self->tensor = src;
  phi::DenseTensor tmp;
  auto dense_tensor = static_cast<phi::DenseTensor*>(self->tensor.impl().get());
  if (dense_tensor) {
    dense_tensor->ShareInplaceVersionCounterWith(tmp);
  }
  return 0;
  EAGER_CATCH_AND_THROW_RETURN_NEG
}

PyObject* tensor_properties_get_grad(TensorObject* self, void* closure) {
  EAGER_TRY
  VLOG(6) << "Get grad for tensor: " << self->tensor.name();
  auto meta = egr::EagerUtils::nullable_autograd_meta(self->tensor);
  VLOG(6) << meta << " initialized: " << meta->Grad().initialized();
  if (meta && meta->Grad().initialized()) {
    return ToPyObject(meta->Grad());
  } else {
    RETURN_PY_NONE
  }
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

int tensor_properties_set_grad(TensorObject* self,
                               PyObject* value,
                               void* closure) {
  EAGER_TRY
  auto src = CastPyArg2Tensor(value, 0);
  PADDLE_ENFORCE(
      egr::EagerUtils::IsLeafTensor(self->tensor),
      paddle::platform::errors::Fatal("Only leaf Tensor can be set grad."));

  paddle::Tensor* grad = egr::EagerUtils::mutable_grad(self->tensor);
  PADDLE_ENFORCE(grad != nullptr,
                 paddle::platform::errors::Fatal(
                     "Detected NULL grad"
                     "Please check if you have manually cleared"
                     "the grad inside autograd_meta"));
  grad->copy_(src, self->tensor.place(), true);
  return 0;
  EAGER_CATCH_AND_THROW_RETURN_NEG
}

int tensor_properties_set_grad_(TensorObject* self,
                                PyObject* value,
                                void* closure) {
  EAGER_TRY
  auto src = CastPyArg2Tensor(value, 0);
  PADDLE_ENFORCE(
      egr::EagerUtils::IsLeafTensor(self->tensor),
      paddle::platform::errors::Fatal("Only leaf Tensor can be set grad."));

  paddle::Tensor* grad = egr::EagerUtils::mutable_grad(self->tensor);
  PADDLE_ENFORCE(grad != nullptr,
                 paddle::platform::errors::Fatal(
                     "Detected NULL grad"
                     "Please check if you have manually cleared"
                     "the grad inside autograd_meta"));
  *grad = src;
  return 0;
  EAGER_CATCH_AND_THROW_RETURN_NEG
}

int tensor_properties_set_stop_gradient(TensorObject* self,
                                        PyObject* value,
                                        void* closure) {
  EAGER_TRY
  auto meta = egr::EagerUtils::autograd_meta(&self->tensor);
  meta->SetStopGradient(CastPyArg2AttrBoolean(value, 0));
  if (!meta->GradNode()) {
    meta->SetGradNode(std::make_shared<egr::GradNodeAccumulation>(meta));
  }
  return 0;
  EAGER_CATCH_AND_THROW_RETURN_NEG
}

PyObject* tensor_properties_get_persistable(TensorObject* self, void* closure) {
  EAGER_TRY
  auto meta = egr::EagerUtils::autograd_meta(&self->tensor);
  return ToPyObject(meta->Persistable());
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

int tensor_properties_set_persistable(TensorObject* self,
                                      PyObject* value,
                                      void* closure) {
  EAGER_TRY
  auto meta = egr::EagerUtils::autograd_meta(&self->tensor);
  meta->SetPersistable(CastPyArg2AttrBoolean(value, 0));
  return 0;
  EAGER_CATCH_AND_THROW_RETURN_NEG
}

PyDoc_STRVAR(tensor_dist_attr__doc__,
             R"DOC(dist_attr

Get dist_attr property from shard tensor.

Returns:
    core.TensorDistAttr: the dist attr of shard tensor

Examples:
    .. code-block:: python

        import paddle
        import paddle.distributed as dist

        mesh = dist.ProcessMesh([[2, 4, 5], [0, 1, 3]], dim_names=["x", "y"])
        dist_attr = dist.DistAttr(mesh=mesh, sharding_specs=['x', 'y'])

        a = paddle.to_tensor([[1,2,3],
                              [5,6,7]])
        d_tensor = dist.shard_tensor(a, dist_attr=dist_attr)

        print(d_tensor.dist_attr)

)DOC");

PyObject* tensor_properties_get_dist_attr(TensorObject* self, void* closure) {
  EAGER_TRY
  if (self->tensor.is_dist_tensor()) {
#ifdef PADDLE_WITH_DISTRIBUTE
    phi::distributed::DistTensor* dist_tensor =
        static_cast<phi::distributed::DistTensor*>(self->tensor.impl().get());
    return ToPyObject(dist_tensor->dist_attr().get());
#else
    RETURN_PY_NONE
#endif
  } else {
    RETURN_PY_NONE
  }
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

PyObject* tensor_properties_get_shape(TensorObject* self, void* closure) {
  EAGER_TRY
  std::vector<int64_t> value;
  if (!self->tensor.defined()) {
    return ToPyObject(value);
  }
  if (egr::IsVariableCompatTensor(self->tensor)) {
    auto* var_tensor = static_cast<const egr::VariableCompatTensor*>(
        self->tensor.impl().get());
    if (var_tensor->IsType<paddle::framework::Vocab>()) {
      value.emplace_back(static_cast<int64_t>(
          var_tensor->Get<paddle::framework::Vocab>().size()));
    } else if (var_tensor->IsType<paddle::framework::Strings>()) {
      value.emplace_back(static_cast<int64_t>(
          var_tensor->Get<paddle::framework::Strings>().size()));
    } else {
      PADDLE_THROW(paddle::platform::errors::Unavailable(
          "VariableCompatTensor only support get shape from Vocab or "
          "Strings."));
    }
  } else {
    auto ddim = self->tensor.shape();
    size_t rank = static_cast<size_t>(ddim.size());
    value.resize(rank);
    for (size_t i = 0; i < rank; i++) {
      value[i] = ddim[i];
    }
  }
  if (!egr::IsVariableCompatTensor(self->tensor)) {
    auto desired_layout =
        paddle::imperative::LayoutAutoTune::Instance().GetDesiredLayout();
    auto default_layout =
        paddle::imperative::LayoutAutoTune::Instance().GetDefaultLayout();
    bool change_dim =
        (desired_layout != default_layout &&
         self->tensor.layout() == desired_layout && value.size() == 4);
    VLOG(6) << "eager_properties 'Shape' method, layout autotune "
            << " desired_layout: " << desired_layout
            << " default_layout: " << default_layout
            << " tensor layout: " << self->tensor.layout()
            << " tensor's shape size is : " << value.size();
    std::vector<int64_t> dims = value;
    if (change_dim && phi::DataLayoutToString(desired_layout) == "NCHW") {
      // NCHW -> NHWC
      VLOG(6) << "layout autotune get Shape from NCHW -> NHWC " << value[0]
              << " " << value[1] << " " << value[2] << " " << value[3] << " to "
              << dims[0] << " " << dims[2] << " " << dims[3] << " " << dims[1];
      value[0] = dims[0];
      value[1] = dims[2];
      value[2] = dims[3];
      value[3] = dims[1];
    } else if (change_dim &&
               phi::DataLayoutToString(desired_layout) == "NHWC") {
      // NHWC -> NCHW
      VLOG(6) << "layout autotune get Shape from NHWC -> NCHW " << value[0]
              << " " << value[1] << " " << value[2] << " " << value[3] << " to "
              << dims[0] << " " << dims[3] << " " << dims[1] << " " << dims[2]
              << " " << dims[1];
      value[0] = dims[0];
      value[1] = dims[3];
      value[2] = dims[1];
      value[3] = dims[2];
    }
  }

  return ToPyObject(value);
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

PyObject* tensor_properties_get_strides(TensorObject* self, void* closure) {
  EAGER_TRY
  std::vector<int64_t> value;
  if (!self->tensor.defined() || !self->tensor.is_dense_tensor()) {
    return ToPyObject(value);
  }

  auto stride = self->tensor.strides();
  size_t rank = static_cast<size_t>(stride.size());
  value.resize(rank);

  for (size_t i = 0; i < rank; i++) {
    value[i] = stride[i];
  }

  return ToPyObject(value);
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

PyObject* tensor_properties_get_offset(TensorObject* self, void* closure) {
  EAGER_TRY
  if (!self->tensor.defined() || !self->tensor.is_dense_tensor()) {
    RETURN_PY_NONE;
  }

  auto dense_tensor =
      std::dynamic_pointer_cast<phi::DenseTensor>(self->tensor.impl());

  if (dense_tensor == nullptr) {
    RETURN_PY_NONE;
  } else {
    return ToPyObject(dense_tensor->offset());
  }

  EAGER_CATCH_AND_THROW_RETURN_NULL
}

PyObject* tensor_properties_get_layout(TensorObject* self, void* closure) {
  EAGER_TRY
  std::string layout = "";
  if (!self->tensor.defined()) {
    return ToPyObject(layout);
  }

  if (egr::IsVariableCompatTensor(self->tensor)) {
    VLOG(3) << "VariableCompatTensor does not support `layout` method.";
    return ToPyObject(layout);
  } else {
    return ToPyObject(phi::DataLayoutToString(self->tensor.layout()));
  }

  return ToPyObject(layout);
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

PyObject* tensor_properties_get_place(TensorObject* self, void* closure) {
  EAGER_TRY
  return ToPyObject(self->tensor.place());
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

PyObject* tensor_properties_get_place_str(TensorObject* self, void* closure) {
  EAGER_TRY
  std::stringstream ostr;
  ostr << self->tensor.place();
  return ToPyObject(ostr.str());
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

PyObject* tensor_properties_get_dtype(TensorObject* self, void* closure) {
  EAGER_TRY
  if (!self->tensor.defined()) {
    // be same to old dygraph
    return ToPyObject(framework::proto::VarType::FP32);
  }
  if (egr::IsVariableCompatTensor(self->tensor)) {
    auto* var_tensor = static_cast<const egr::VariableCompatTensor*>(
        self->tensor.impl().get());
    if (var_tensor->IsType<paddle::framework::Vocab>()) {
      return ToPyObject(framework::proto::VarType::RAW);
    } else if (var_tensor->IsType<paddle::framework::Strings>()) {
      return ToPyObject(framework::proto::VarType::STRING);
    } else {
      PADDLE_THROW(paddle::platform::errors::Unavailable(
          "VariableCompatTensor only support get shape from Vocab or "
          "Strings."));
    }
  } else {
    return ToPyObject(
        paddle::framework::TransToProtoVarType(self->tensor.type()));
  }
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

PyObject* tensor_properties_get_grad_fn(TensorObject* self, void* closure) {
  EAGER_TRY
  if (!self->tensor.defined()) {
    // Handle undefined tensors if necessary; otherwise, return nullptr or an
    // appropriate PyObject. In this case, I will return Py_None.
    Py_INCREF(Py_None);
    return Py_None;
  }

  // Get GradNode from the tensor
  auto meta = egr::EagerUtils::nullable_autograd_meta(
      self->tensor);  // If meta exists, get the GradNode

  if (meta) {
    // Get the GradNode from meta
    auto grad_node_ptr = meta->GetMutableGradNode();
    if (!grad_node_ptr) {
      Py_INCREF(Py_None);
      return Py_None;
    }

    PyObject* py_grad_node = ToPyObject(grad_node_ptr);

    return py_grad_node;

  } else {
    // If meta does not exist, return an appropriate Python object (e.g., None
    // or a special value).
    Py_INCREF(Py_None);
    return Py_None;
  }
  EAGER_CATCH_AND_THROW_RETURN_NULL
}

struct PyGetSetDef variable_properties[] = {  // NOLINT
    {"data",
     (getter)tensor_properties_get_data,
     (setter)tensor_properties_set_data,
     nullptr,
     nullptr},
    {"grad",
     (getter)tensor_properties_get_grad,
     (setter)tensor_properties_set_grad,
     nullptr,
     nullptr},
    {"grad_",
     (getter)tensor_properties_get_grad,
     (setter)tensor_properties_set_grad_,
     nullptr,
     nullptr},
    {"name",
     (getter)tensor_properties_get_name,
     (setter)tensor_properties_set_name,
     nullptr,
     nullptr},
    {"stop_gradient",
     (getter)tensor_properties_get_stop_gradient,
     (setter)tensor_properties_set_stop_gradient,
     nullptr,
     nullptr},
    {"persistable",
     (getter)tensor_properties_get_persistable,
     (setter)tensor_properties_set_persistable,
     nullptr,
     nullptr},
    {"shape", (getter)tensor_properties_get_shape, nullptr, nullptr, nullptr},
    {"layout", (getter)tensor_properties_get_layout, nullptr, nullptr, nullptr},
    {"strides",
     (getter)tensor_properties_get_strides,
     nullptr,
     nullptr,
     nullptr},
    {"place", (getter)tensor_properties_get_place, nullptr, nullptr, nullptr},
    {"offset", (getter)tensor_properties_get_offset, nullptr, nullptr, nullptr},
    {"dist_attr",
     (getter)tensor_properties_get_dist_attr,
     nullptr,
     tensor_dist_attr__doc__,
     nullptr},
    {"_place_str",
     (getter)tensor_properties_get_place_str,
     nullptr,
     nullptr,
     nullptr},
    {"dtype", (getter)tensor_properties_get_dtype, nullptr, nullptr, nullptr},
    {"type", (getter)tensor_properties_get_type, nullptr, nullptr, nullptr},
    {"is_leaf",
     (getter)tensor_properties_is_leaf,
     nullptr,
     tensor_is_leaf__doc__,
     nullptr},
    {"grad_fn",
     (getter)tensor_properties_get_grad_fn,
     nullptr,
     nullptr,
     nullptr},
    {nullptr, nullptr, nullptr, nullptr, nullptr}};

// variable_properties for core.eager.StringTensor
struct PyGetSetDef string_tensor_variable_properties[] = {  // NOLINT
    {"name",
     (getter)tensor_properties_get_name,
     (setter)tensor_properties_set_name,
     nullptr,
     nullptr},
    {"shape", (getter)tensor_properties_get_shape, nullptr, nullptr, nullptr},
    {"layout", (getter)tensor_properties_get_layout, nullptr, nullptr, nullptr},
    {"place", (getter)tensor_properties_get_place, nullptr, nullptr, nullptr},
    {"_place_str",
     (getter)tensor_properties_get_place_str,
     nullptr,
     nullptr,
     nullptr},
    {nullptr, nullptr, nullptr, nullptr, nullptr}};

}  // namespace pybind
}  // namespace paddle