#ifndef TH_GENERIC_FILE
#define TH_GENERIC_FILE "TH/generic/THTensor.cpp"
#else

#include <ATen/InferSize.h>
#include <new>

/**** access methods ****/
THStorage *THTensor_(storage)(const THTensor *self)
{
  return THTensor_getStoragePtr(self);
}

ptrdiff_t THTensor_(storageOffset)(const THTensor *self)
{
  return self->storage_offset();
}

int THTensor_(nDimension)(const THTensor *self)
{
  return THTensor_nDimension(self);
}

int THTensor_(nDimensionLegacyNoScalars)(const THTensor *self)
{
  return THTensor_nDimensionLegacyNoScalars(self);
}

int THTensor_(nDimensionLegacyAll)(const THTensor *self)
{
  return THTensor_nDimensionLegacyAll(self);
}

int64_t THTensor_(size)(const THTensor *self, int dim)
{
  THArgCheck((dim >= 0) && (dim < self->dim()), 2, "dimension %d out of range of %dD tensor",
      dim, THTensor_(nDimensionLegacyNoScalars)(self));
  return self->size(dim);
}

int64_t THTensor_(stride)(const THTensor *self, int dim)
{
  THArgCheck((dim >= 0) && (dim < self->dim()), 2, "dimension %d out of range of %dD tensor",
      dim, THTensor_(nDimensionLegacyNoScalars)(self));
  return self->stride(dim);
}

scalar_t *THTensor_(data)(const THTensor *self) {
  return self->data<scalar_t>();
}

/**** creation methods ****/

/* Empty init */
THTensor *THTensor_(new)(void)
{
  return c10::make_intrusive<at::TensorImpl, at::UndefinedTensorImpl>(
    c10::intrusive_ptr<at::StorageImpl>::reclaim(THStorage_(new)()),
    at::CPUTensorId()
  ).release();
}

/* Pointer-copy init */
THTensor *THTensor_(newWithTensor)(THTensor *tensor)
{
  THTensor *self = c10::make_intrusive<at::TensorImpl, at::UndefinedTensorImpl>(
    c10::intrusive_ptr<at::StorageImpl>::reclaim(THStorage_(new)()),
    at::CPUTensorId()
  ).release();
  THTensor_(setStorageNd)(self,
                          THTensor_getStoragePtr(tensor),
                          tensor->storage_offset(),
                          tensor->dim(),
                          THTensor_getSizePtr(tensor),
                          THTensor_getStridePtr(tensor));
  return self;
}

/* Storage init */
THTensor *THTensor_(newWithStorage)(THStorage *storage, ptrdiff_t storageOffset, at::IntArrayRef sizes, at::IntArrayRef strides) {
  if (strides.data()) {
    TORCH_CHECK(sizes.size() == strides.size(), "number of sizes and strides must match");
  }
  THTensor *self = c10::make_intrusive<at::TensorImpl, at::UndefinedTensorImpl>(
    c10::intrusive_ptr<at::StorageImpl>::reclaim(THStorage_(new)()),
    at::CPUTensorId()
  ).release();
  THTensor_(setStorageNd)(self, storage, storageOffset, sizes.size(),
                          const_cast<int64_t*>(sizes.data()), const_cast<int64_t*>(strides.data()));

  return self;
}

THTensor *THTensor_(newWithStorage1d)(THStorage *storage, ptrdiff_t storageOffset,
                               int64_t size0, int64_t stride0)
{
  return THTensor_(newWithStorage)(storage, storageOffset, {size0}, {stride0});
}

THTensor *THTensor_(newWithStorage2d)(THStorage *storage, ptrdiff_t storageOffset,
                               int64_t size0, int64_t stride0,
                               int64_t size1, int64_t stride1)
{
  return THTensor_(newWithStorage)(storage, storageOffset, {size0, size1}, {stride0, stride1});
}

THTensor *THTensor_(newWithStorage3d)(THStorage *storage, ptrdiff_t storageOffset,
                               int64_t size0, int64_t stride0,
                               int64_t size1, int64_t stride1,
                               int64_t size2, int64_t stride2)
{
  return THTensor_(newWithStorage)(storage, storageOffset, {size0, size1, size2}, {stride0, stride1, stride2});
}

THTensor *THTensor_(newWithStorage4d)(THStorage *storage, ptrdiff_t storageOffset,
                               int64_t size0, int64_t stride0,
                               int64_t size1, int64_t stride1,
                               int64_t size2, int64_t stride2,
                               int64_t size3, int64_t stride3)
{
  return THTensor_(newWithStorage)(storage, storageOffset,
                                          {size0, size1, size2, size3},
                                          {stride0, stride1, stride2, stride3});
}

THTensor *THTensor_(newWithSize)(at::IntArrayRef size, at::IntArrayRef stride)
{
  return THTensor_(newWithStorage)(NULL, 0, size, stride);
}

THTensor *THTensor_(newWithSize1d)(int64_t size0)
{
  return THTensor_(newWithSize)({size0}, {});
}

THTensor *THTensor_(newWithSize2d)(int64_t size0, int64_t size1)
{
  return THTensor_(newWithSize)({size0, size1}, {});
}

THTensor *THTensor_(newWithSize3d)(int64_t size0, int64_t size1, int64_t size2)
{
  return THTensor_(newWithSize)({size0, size1, size2}, {});
}

THTensor *THTensor_(newWithSize4d)(int64_t size0, int64_t size1, int64_t size2, int64_t size3)
{
  return THTensor_(newWithSize)({size0, size1, size2, size3}, {});
}

THTensor *THTensor_(newClone)(THTensor *self)
{
  THTensor *tensor = THTensor_(new)();
  THTensor_(resizeAs)(tensor, self);
  at::Tensor tensor_wrap = THTensor_wrap(tensor);
  at::Tensor self_wrap = THTensor_wrap(self);
  at::_copy_same_type_(tensor_wrap, self_wrap);
  return tensor;
}

THTensor *THTensor_(newContiguous)(THTensor *self)
{
  if(!THTensor_(isContiguous)(self))
    return THTensor_(newClone)(self);
  else
  {
    THTensor_(retain)(self);
    return self;
  }
}

THTensor *THTensor_(newSelect)(THTensor *tensor, int dimension_, int64_t sliceIndex_)
{
  THTensor *self = THTensor_(newWithTensor)(tensor);
  THTensor_(select)(self, NULL, dimension_, sliceIndex_);
  return self;
}

THTensor *THTensor_(newNarrow)(THTensor *tensor, int dimension_, int64_t firstIndex_, int64_t size_)
{
  THTensor *self = THTensor_(newWithTensor)(tensor);
  THTensor_(narrow)(self, NULL, dimension_, firstIndex_, size_);
  return self;
}

THTensor *THTensor_(newTranspose)(THTensor *tensor, int dimension1_, int dimension2_)
{
  THTensor *self = THTensor_(newWithTensor)(tensor);
  THTensor_(transpose)(self, NULL, dimension1_, dimension2_);
  return self;
}

THTensor *THTensor_(newView)(THTensor *tensor, at::IntArrayRef size)
{
  ptrdiff_t numel = THTensor_(nElement)(tensor);
  THTensor *self = THTensor_(new)();
  auto inferred_size = at::infer_size(size, numel);
  auto stride = THTensor_compute_stride(tensor->sizes(),
                                        tensor->strides(),
                                        inferred_size);
  THArgCheck(stride.has_value(), 2, "view size is "
    "not compatible with input tensor's size and stride (at least one dimension spans "
    "across two contiguous subspaces). Call .contiguous() before .view().");
  auto stride_value = *stride;
  THTensor_setStorage(self, THTensor_getStoragePtr(tensor), tensor->storage_offset(), inferred_size, stride_value);
  return self;
}

/* Resize */
void THTensor_(resize)(THTensor *self, at::IntArrayRef size, at::IntArrayRef stride)
{
  return THTensor_resize(self, size, stride);
}

void THTensor_(resizeAs)(THTensor *self, THTensor *src)
{
  if(!THTensor_(isSameSizeAs)(self, src))
    THTensor_(resizeNd)(self, src->dim(), THTensor_getSizePtr(src), NULL);
}

void THTensor_(resize0d)(THTensor *tensor)
{
  THTensor_(resizeNd)(tensor, 0, {}, nullptr);
}

void THTensor_(resize1d)(THTensor *tensor, int64_t size0)
{
  int64_t size[1] = {size0};
  THTensor_(resizeNd)(tensor, 1, size, nullptr);
}

void THTensor_(resize2d)(THTensor *tensor, int64_t size0, int64_t size1)
{
  int64_t size[2] = {size0, size1};
  THTensor_(resizeNd)(tensor, 2, size, nullptr);
}

void THTensor_(resize3d)(THTensor *tensor, int64_t size0, int64_t size1, int64_t size2)
{
  int64_t size[3] = {size0, size1, size2};
  THTensor_(resizeNd)(tensor, 3, size, nullptr);
}

void THTensor_(resize4d)(THTensor *self, int64_t size0, int64_t size1, int64_t size2, int64_t size3)
{
  int64_t size[4] = {size0, size1, size2, size3};
  THTensor_(resizeNd)(self, 4, size, nullptr);
}

void THTensor_(resize5d)(THTensor *self, int64_t size0, int64_t size1, int64_t size2, int64_t size3, int64_t size4)
{
  int64_t size[5] = {size0, size1, size2, size3, size4};
  THTensor_(resizeNd)(self, 5, size, nullptr);
}

void THTensor_(set)(THTensor *self, THTensor *src)
{
  if(self != src)
    THTensor_(setStorageNd)(self,
                            THTensor_getStoragePtr(src),
                            src->storage_offset(),
                            src->dim(),
                            THTensor_getSizePtr(src),
                            THTensor_getStridePtr(src));
}

void THTensor_(setStorage)(THTensor *self, THStorage *storage_, ptrdiff_t storageOffset_, at::IntArrayRef size_, at::IntArrayRef stride_)
{
  THTensor_setStorage(self, storage_, storageOffset_, size_, stride_);
}

void THTensor_(setStorage1d)(THTensor *self, THStorage *storage_, ptrdiff_t storageOffset_,
                             int64_t size0_, int64_t stride0_)
{
  THTensor_(setStorage)(self, storage_, storageOffset_,
                       {size0_}, {stride0_});
}

void THTensor_(setStorage2d)(THTensor *self, THStorage *storage_, ptrdiff_t storageOffset_,
                             int64_t size0_, int64_t stride0_,
                             int64_t size1_, int64_t stride1_)
{
  THTensor_(setStorage)(self, storage_, storageOffset_,
                       {size0_, size1_},
                       {stride0_, stride1_});
}

void THTensor_(setStorage3d)(THTensor *self, THStorage *storage_, ptrdiff_t storageOffset_,
                             int64_t size0_, int64_t stride0_,
                             int64_t size1_, int64_t stride1_,
                             int64_t size2_, int64_t stride2_)
{
  THTensor_(setStorage)(self, storage_, storageOffset_,
                        {size0_, size1_, size2_},
                        {stride0_, stride1_, stride2_});
}

void THTensor_(setStorage4d)(THTensor *self, THStorage *storage_, ptrdiff_t storageOffset_,
                             int64_t size0_, int64_t stride0_,
                             int64_t size1_, int64_t stride1_,
                             int64_t size2_, int64_t stride2_,
                             int64_t size3_, int64_t stride3_)
{

  int64_t size[4] = {size0_, size1_, size2_, size3_};
  int64_t stride[4] = {stride0_, stride1_, stride2_, stride3_};

  THTensor_(setStorage)(self, storage_, storageOffset_, size, stride);
}


void THTensor_(narrow)(THTensor *self, THTensor *src, int dimension, int64_t firstIndex, int64_t size)
{
  if(!src)
    src = self;

  THArgCheck( (dimension >= 0) && (dimension < src->dim()), 2, "out of range");
  THArgCheck( firstIndex >= 0, 3, "out of range");
  THArgCheck( size >= 0, 4, "out of range");
  THArgCheck(firstIndex <= src->size(dimension) - size, 4, "out of range");

  THTensor_(set)(self, src);

  if (firstIndex > 0) {
    self->set_storage_offset(self->storage_offset() + firstIndex*self->stride(dimension));
  }

  self->set_size(dimension, size);
}

void THTensor_(select)(THTensor *self, THTensor *src, int dimension, int64_t sliceIndex)
{
  int d;

  if(!src)
    src = self;

  THArgCheck(src->dim() > 0, 1, "cannot select on a 0-dim tensor");
  THArgCheck((dimension >= 0) && (dimension < src->dim()), 2, "out of range");
  THArgCheck((sliceIndex >= 0) && (sliceIndex < src->size(dimension)), 3, "out of range");

  THTensor_(set)(self, src);
  THTensor_(narrow)(self, NULL, dimension, sliceIndex, 1);

  std::vector<int64_t> newSize(self->dim()-1);
  std::vector<int64_t> newStride(self->dim()-1);
  for (d = 0; d < dimension; d++)
  {
    newSize[d] = self->size(d);
    newStride[d] = self->stride(d);
  }

  for(d = dimension; d < self->dim()-1; d++)
  {
    newSize[d] = self->size(d+1);
    newStride[d] = self->stride(d+1);
  }
  self->set_sizes_and_strides(newSize, newStride);
}

void THTensor_(transpose)(THTensor *self, THTensor *src, int dimension1, int dimension2)
{
  int64_t z;

  if(!src)
    src = self;

  THArgCheck( (dimension1 >= 0) && (dimension1 < THTensor_nDimensionLegacyNoScalars(src)), 1, "out of range");
  THArgCheck( (dimension2 >= 0) && (dimension2 < THTensor_nDimensionLegacyNoScalars(src)), 2, "out of range");

  THTensor_(set)(self, src);

  if(dimension1 == dimension2)
    return;

  z = self->stride(dimension1);
  self->set_stride(dimension1, self->stride(dimension2));
  self->set_stride(dimension2, z);
  z = self->size(dimension1);
  self->set_size(dimension1, self->size(dimension2));
  self->set_size(dimension2, z);
}

void THTensor_(unfold)(THTensor *self, THTensor *src, int dimension, int64_t size, int64_t step)
{
  int d;

  if(!src)
    src = self;

  THArgCheck((dimension >= 0) && (dimension < THTensor_nDimensionLegacyNoScalars(src)), 2, "out of range");
  THArgCheck(size <= THTensor_sizeLegacyNoScalars(src, dimension), 3, "out of range");
  THArgCheck(step > 0, 4, "invalid step");

  THTensor_(set)(self, src);

  std::vector<int64_t> newSize(/* size */ self->dim()+1);
  std::vector<int64_t> newStride(/* size */ self->dim()+1);

  newSize[self->dim()] = size;
  newStride[self->dim()] = THTensor_strideLegacyNoScalars(self, dimension);
  for(d = 0; d < self->dim(); d++)
  {
    auto self_size = THTensor_sizeLegacyNoScalars(self, d);
    auto self_stride = THTensor_strideLegacyNoScalars(self, d);
    if(d == dimension)
    {
      newSize[d] = (self_size - size) / step + 1;
      newStride[d] = step*self_stride;
    }
    else
    {
      newSize[d] = self_size;
      newStride[d] = self_stride;
    }
  }
  self->set_sizes_and_strides(newSize, newStride);
}

/* we have to handle the case where the result is a number */
void THTensor_(squeeze)(THTensor *self, THTensor *src)
{
  if(!src)
    src = self;

  THTensor_(set)(self, src);

  std::vector<int64_t> newSize;
  std::vector<int64_t> newStride;
  for(int d = 0; d < src->dim(); ++d)
  {
    if(src->size(d) != 1)
    {
      newSize.push_back(src->size(d));
      newStride.push_back(src->stride(d));
    }
  }

  self->set_sizes_and_strides(newSize, newStride);
}

void THTensor_(squeeze1d)(THTensor *self, THTensor *src, int dimension)
{
  int d;

  if(!src)
    src = self;

  THArgCheck((dimension >= 0) && (dimension < src->dim()), 2, "dimension out of range");

  THTensor_(set)(self, src);

  if(src->size(dimension) == 1)
  {
    std::vector<int64_t> newSize(self->dim() - 1);
    std::vector<int64_t> newStride(self->dim() - 1);
    for (d = 0; d < dimension; d++)
    {
      newSize[d] = self->size(d);
      newStride[d] = self->stride(d);
    }

    for(d = dimension; d < self->dim()-1; d++)
    {
      newSize[d] = self->size(d+1);
      newStride[d] = self->stride(d+1);
    }
    self->set_sizes_and_strides(newSize, newStride);
  }
}

void THTensor_(unsqueeze1d)(THTensor *self, THTensor *src, int dimension)
{
  int d;

  if(!src)
    src = self;

  THArgCheck((dimension >= 0) && (dimension <= src->dim()), 2, "dimension out of range");

  THTensor_(set)(self, src);

  std::vector<int64_t> newSize(/* size */ self->dim()+1);
  std::vector<int64_t> newStride(/* size */ self->dim()+1);

  for(d = self->dim(); d > dimension; d--)
  {
    newSize[d] = self->size(d-1);
    newStride[d] = self->stride(d-1);
  }
  if (dimension < self->dim())
  {
    newStride[dimension] = self->size(dimension) * self->stride(dimension);
  }
  else
  {
    newStride[dimension] = 1;
  }
  newSize[dimension] = 1;
  for(d = dimension - 1; d >= 0; d--)
  {
    newSize[d] = self->size(d);
    newStride[d] = self->stride(d);
  }
  self->set_sizes_and_strides(newSize, newStride);
}

int THTensor_(isTransposed)(const THTensor *self)
{
  if (THTensor_(isContiguous)(self)) {
    return 0;
  }
  int64_t max_stride = 1;
  int64_t size_max_stride = 1;
  int64_t z = 1;
  int d;
  for (d = 0; d < self->dim(); ++d) {
    if (self->stride(d) == 0 && self->size(d) != 1)
      return 0;
    if (self->stride(d) > max_stride) {
      max_stride = self->stride(d);
      size_max_stride = self->size(d);
    }
    z *= self->size(d);
  }
  if (z == max_stride * size_max_stride) {
    return 1;
  }
  return 0;
}

int THTensor_(isContiguous)(const THTensor *self)
{
  return self->is_contiguous();
}

int THTensor_(isSameSizeAs)(const THTensor *self, const THTensor* src)
{
  int d;
  if (self->dim() != src->dim())
    return 0;
  for(d = 0; d < self->dim(); ++d)
  {
    if(self->size(d) != src->size(d))
      return 0;
  }
  return 1;
}

int THTensor_(isSetTo)(const THTensor *self, const THTensor* src)
{
  if (!THTensor_getStoragePtr(self))
    return 0;
  if (THTensor_getStoragePtr(self) == THTensor_getStoragePtr(src) &&
      self->storage_offset() == src->storage_offset() &&
      THTensor_nDimensionLegacyAll(self) == THTensor_nDimensionLegacyAll(src))
  {
    int d;
    for (d = 0; d < THTensor_nDimensionLegacyAll(self); ++d)
    {
      if (self->size(d) != src->size(d) || self->stride(d) != src->stride(d))
        return 0;
    }
    return 1;
  }
  return 0;
}

ptrdiff_t THTensor_(nElement)(const THTensor *self)
{
  if(THTensor_nDimensionLegacyAll(self) == 0)
    return 0;
  else
  {
    ptrdiff_t nElement = 1;
    int d;
    for(d = 0; d < THTensor_nDimension(self); d++)
      nElement *= self->size(d);
    return nElement;
  }
}

// NB: It is INVALID to call this on an UndefinedTensorImpl
void THTensor_(retain)(THTensor *self)
{
  c10::raw::intrusive_ptr::incref(self);
}

void THTensor_(free)(THTensor *self)
{
  THTensor_free(self);
}

void THTensor_(freeCopyTo)(THTensor *self, THTensor *dst)
{
  if(self != dst) {
    at::Tensor dst_wrap = THTensor_wrap(dst);
    at::Tensor self_wrap = THTensor_wrap(self);
    at::_copy_same_type_(dst_wrap, self_wrap);
  }

  THTensor_(free)(self);
}

/*******************************************************************************/

void THTensor_(setStorageNd)(THTensor *self, THStorage *storage, ptrdiff_t storageOffset, int nDimension, const int64_t *size, const int64_t *stride)
{
  return THTensor_setStorageNd(self, storage, storageOffset, nDimension, size, stride);
}

void THTensor_(resizeNd)(THTensor *self, int nDimension, const int64_t *size, const int64_t *stride)
{
  return THTensor_resizeNd(self, nDimension, size, stride);
}

void THTensor_(set0d)(THTensor *tensor, scalar_t value)
{
  THArgCheck(THTensor_nDimension(tensor) == 0, 1, "tensor must have no dimensions");
  THStorage_(set)(THTensor_getStoragePtr(tensor), tensor->storage_offset(), value);
}

scalar_t THTensor_(get0d)(const THTensor *tensor)
{
  THArgCheck(THTensor_nDimension(tensor) == 0, 1, "tensor must have no dimensions");
  return THStorage_(get)(THTensor_getStoragePtr(tensor), tensor->storage_offset());
}

void THTensor_(set1d)(THTensor *tensor, int64_t x0, scalar_t value)
{
  THArgCheck(THTensor_nDimensionLegacyNoScalars(tensor) == 1, 1, "tensor must have one dimension");
  THArgCheck( (x0 >= 0) && (x0 < THTensor_sizeLegacyNoScalars(tensor, 0)), 2, "out of range");
  THStorage_(set)(THTensor_getStoragePtr(tensor), tensor->storage_offset()+x0*THTensor_strideLegacyNoScalars(tensor, 0), value);
}

scalar_t THTensor_(get1d)(const THTensor *tensor, int64_t x0)
{
  THArgCheck(THTensor_nDimensionLegacyNoScalars(tensor) == 1, 1, "tensor must have one dimension");
  THArgCheck( (x0 >= 0) && (x0 < THTensor_sizeLegacyNoScalars(tensor, 0)), 2, "out of range");
  return THStorage_(get)(THTensor_getStoragePtr(tensor), tensor->storage_offset()+x0*THTensor_strideLegacyNoScalars(tensor, 0));
}

void THTensor_(set2d)(THTensor *tensor, int64_t x0, int64_t x1, scalar_t value)
{
  THArgCheck(THTensor_nDimensionLegacyAll(tensor) == 2, 1, "tensor must have two dimensions");
  THArgCheck((x0 >= 0) && (x0 < tensor->size(0)) && (x1 >= 0) && (x1 < tensor->size(1)), 2, "out of range");
  THStorage_(set)(THTensor_getStoragePtr(tensor), tensor->storage_offset()+x0*tensor->stride(0)+x1*tensor->stride(1), value);
}

scalar_t THTensor_(get2d)(const THTensor *tensor, int64_t x0, int64_t x1)
{
  THArgCheck(THTensor_nDimensionLegacyAll(tensor) == 2, 1, "tensor must have two dimensions");
  THArgCheck((x0 >= 0) && (x0 < tensor->size(0)) && (x1 >= 0) && (x1 < tensor->size(1)), 2, "out of range");
  return THStorage_(get)(THTensor_getStoragePtr(tensor), tensor->storage_offset()+x0*tensor->stride(0)+x1*tensor->stride(1));
}

void THTensor_(set3d)(THTensor *tensor, int64_t x0, int64_t x1, int64_t x2, scalar_t value)
{
  THArgCheck(THTensor_nDimensionLegacyAll(tensor) == 3, 1, "tensor must have three dimensions");
  THArgCheck( (x0 >= 0) && (x0 < tensor->size(0)) && (x1 >= 0) && (x1 < tensor->size(1)) && (x2 >= 0) && (x2 < tensor->size(2)), 2, "out of range");
  THStorage_(set)(THTensor_getStoragePtr(tensor), tensor->storage_offset()+x0*tensor->stride(0)+x1*tensor->stride(1)+x2*tensor->stride(2), value);
}

scalar_t THTensor_(get3d)(const THTensor *tensor, int64_t x0, int64_t x1, int64_t x2)
{
  THArgCheck(THTensor_nDimensionLegacyAll(tensor) == 3, 1, "tensor must have three dimensions");
  THArgCheck( (x0 >= 0) && (x0 < tensor->size(0)) && (x1 >= 0) && (x1 < tensor->size(1)) && (x2 >= 0) && (x2 < tensor->size(2)), 2, "out of range");
  return THStorage_(get)(THTensor_getStoragePtr(tensor), tensor->storage_offset()+x0*tensor->stride(0)+x1*tensor->stride(1)+x2*tensor->stride(2));
}

void THTensor_(set4d)(THTensor *tensor, int64_t x0, int64_t x1, int64_t x2, int64_t x3, scalar_t value)
{
  THArgCheck(THTensor_nDimensionLegacyAll(tensor) == 4, 1, "tensor must have four dimensions");
  THArgCheck((x0 >= 0) && (x0 < tensor->size(0)) && (x1 >= 0) && (x1 < tensor->size(1)) && (x2 >= 0) && (x2 < tensor->size(2)) && (x3 >= 0) && (x3 < tensor->size(3)), 2, "out of range");
  THStorage_(set)(THTensor_getStoragePtr(tensor), tensor->storage_offset()+x0*tensor->stride(0)+x1*tensor->stride(1)+x2*tensor->stride(2)+x3*tensor->stride(3), value);
}

scalar_t THTensor_(get4d)(const THTensor *tensor, int64_t x0, int64_t x1, int64_t x2, int64_t x3)
{
  THArgCheck(THTensor_nDimensionLegacyAll(tensor) == 4, 1, "tensor must have four dimensions");
  THArgCheck((x0 >= 0) && (x0 < tensor->size(0)) && (x1 >= 0) && (x1 < tensor->size(1)) && (x2 >= 0) && (x2 < tensor->size(2)) && (x3 >= 0) && (x3 < tensor->size(3)), 2, "out of range");
  return THStorage_(get)(THTensor_getStoragePtr(tensor), tensor->storage_offset()+x0*tensor->stride(0)+x1*tensor->stride(1)+x2*tensor->stride(2)+x3*tensor->stride(3));
}


/* Shape manipulation methods */
void THTensor_(cat)(THTensor *r_, THTensor *ta, THTensor *tb, int dimension)
{
  THTensor* inputs[2];
  inputs[0] = ta;
  inputs[1] = tb;
  THTensor_(catArray)(r_, inputs, 2, dimension);
}

void THTensor_(check_shape_except_dim)(THTensor *first, THTensor *second, int dimension);
inline void THTensor_(check_shape_except_dim)(THTensor *first, THTensor *second, int dimension)
{
  int first_dims = first->dim();
  int second_dims = second->dim();
  THArgCheck(first_dims == second_dims, 0,
      "Tensors must have same number of dimensions: got %d and %d",
      first_dims, second_dims);
  for (int dim = 0; dim < first_dims; dim++) {
    if (dim == dimension) {
      continue;
    }
    int64_t first_dim_size = first->size(dim);
    int64_t second_dim_size = second->size(dim);
    THArgCheck(first_dim_size == second_dim_size, 0,
        "Sizes of tensors must match except in dimension %d. Got %lld and %lld in dimension %d",
        dimension, (long long)first_dim_size, (long long)second_dim_size, dim);
  }
}

void THTensor_(catArray)(THTensor *result, THTensor **inputs, int numInputs, int dimension)
{
  // previously, size [0] tensors were the only possible empty tensors; thus, it wasn't possible
  // to cat empty tensors unless all the other tensors were 1-dimensional, so we allowed these tensors
  // to be "skipped".  We maintain this behavior for backwards compatibility, but only for this specific
  // size (i.e. other empty sizes are not skipped).
  // FIXME: warn if this is the case
  bool allSkipped= true;
  int64_t nDims = 0;
  THTensor *notSkippedTensor;  // non-owning reference
  auto should_skip = [](THTensor *t) { return t->is_empty() && t->dim() == 1; };
  for (int i = 0; i < numInputs; i++) {
    if (should_skip(inputs[i])) {
      continue;
    }
    // We've found a non-empty tensor
    allSkipped = false;
    notSkippedTensor = inputs[i];
    nDims = notSkippedTensor->dim();
    break;
  }
  if (allSkipped) {
    return;
  }

  // Compute cat_dimension based on the non-empty tensor
  THArgCheck(dimension < nDims, 4, "invalid dimension %d", dimension);
  THArgCheck(numInputs > 0, 3, "invalid number of inputs %d", numInputs);

  // Compute size of the result in the cat dimension
  int64_t cat_dim_size = 0;
  for (int i = 0; i < numInputs; i++) {
    THTensor *tensor = inputs[i];
    if (should_skip(tensor)) {
      continue;
    }
    THTensor_(check_shape_except_dim)(notSkippedTensor, tensor, dimension);
    cat_dim_size += tensor->size(dimension);
  }

  // Compute the size of the result
  std::vector<int64_t> size(nDims);
  for (int dim = 0; dim < nDims; dim++) {
    int64_t result_dim_size = notSkippedTensor->size(dim);
    if (dim == dimension) {
      result_dim_size = cat_dim_size;
    }
    size[dim] = result_dim_size;
  }
  THTensor_(resize)(result, size, {});

  // Check contiguity of all inputs and result
  bool allContiguous = true;
  for (int i = 0; i < numInputs; i++) {
    if(!should_skip(inputs[i])) {
      allContiguous = allContiguous && THTensor_(isContiguous)(inputs[i]);
    }
  }
  allContiguous = allContiguous && THTensor_(isContiguous)(result);

  // First path is for contiguous inputs
  // Second path for non-contiguous
  int64_t offset;
  if (allContiguous) {
    int64_t outer = 1, inner = 1;

    // Outer is the product of dimensions from the left up to (and not
    // including the concatenation dimension). This becomes the number of times
    // we have to replicate the memcpy call.
    for (int i = 0; i < dimension; ++i) {
      outer *= size[i];
    }

    // The product of dimensions to the right of the concatenation dimension.
    // We go on to multiply this by the size of the concat dimension for
    // each input tensor.
    for (int i = dimension + 1; i < size.size(); ++i) {
      inner *= size[i];
    }

    scalar_t* result_data = THStorage_(data)(THTensor_getStoragePtr(result)) + result->storage_offset();
    offset = 0;
    for (int o = 0; o < outer; ++o) {
      for (int j = 0; j < numInputs; ++j) {
        if (!should_skip(inputs[j])) {
          THTensor* input0 = inputs[j];
          scalar_t* input0_data = THStorage_(data)(THTensor_getStoragePtr(input0)) + input0->storage_offset();
          int local_inner = inner * input0->size(dimension);
          if (local_inner != 0) {
            memcpy(result_data + offset, input0_data + o*local_inner, local_inner*sizeof(scalar_t));
          } // input0_size != 0
          offset += local_inner;
        }  // should_skip
      } // for j
    } // for i
  } else {
    offset = 0;
    for (int j = 0; j < numInputs; j++) {
      if (!should_skip(inputs[j])) {
        int64_t dimSize = inputs[j]->size(dimension);
        THTensor *nt = THTensor_(newWithTensor)(result);
        THTensor_(narrow)(nt, NULL, dimension, offset, dimSize);
        at::Tensor nt__wrap = THTensor_wrap(nt);
        at::Tensor inputs_wrap = THTensor_wrap(inputs[j]);
        at::_copy_same_type_(nt__wrap, inputs_wrap);
        c10::raw::intrusive_ptr::decref(nt);
        offset += dimSize;
      }
    }
  }
}

THDescBuff THTensor_(desc)(const THTensor *tensor) {
  const int L = TH_DESC_BUFF_LEN;
  THDescBuff buf;
  char *str = buf.str;
  int n = 0;
#define _stringify(x) #x
  n += snprintf(str, L-n, "torch." _stringify(x) "Tensor of size ");
#undef _stringify
  int i;
  for(i = 0; i < THTensor_nDimension(tensor); i++) {
    if(n >= L) break;
    n += snprintf(str+n, L-n, "%" PRId64, tensor->size(i));
    if(i < THTensor_nDimension(tensor)-1) {
      n += snprintf(str+n, L-n, "x");
    }
  }
  if(n >= L) {
    snprintf(str+L-4, 4, "...");
  }
  return buf;
}

THDescBuff THTensor_(sizeDesc)(const THTensor *tensor) {
  THDescBuff buf = _THSizeDesc(tensor->sizes().data(), tensor->sizes().size());
  return buf;
}

#endif
