torch_tensor_from_blob Subroutine

public subroutine torch_tensor_from_blob(tensor, data, ndims, tensor_shape, layout, dtype, device_type, device_index, requires_grad)

Uses

  • proc~~torch_tensor_from_blob~~UsesGraph proc~torch_tensor_from_blob torch_tensor_from_blob iso_c_binding iso_c_binding proc~torch_tensor_from_blob->iso_c_binding

Exposes the given data as a tensor without taking ownership of the original data. This routine will take an (i, j, k) array and return an (k, j, i) tensor.

Arguments

Type IntentOptional Attributes Name
type(torch_tensor), intent(out) :: tensor

Returned tensor
type(c_ptr), intent(in) :: data

Pointer to data
integer(kind=c_int), intent(in) :: ndims

Number of dimensions of the tensor
integer(kind=c_int64_t), intent(in) :: tensor_shape(:)

Shape of the tensor
integer(kind=c_int), intent(in) :: layout(:)

Layout for strides for accessing data
integer(kind=c_int), intent(in) :: dtype

Data type of the tensor
integer(kind=c_int), intent(in) :: device_type

Device type the tensor will live on (torch_kCPU or torch_kCUDA)
integer, intent(in), optional :: device_index

Device index to use for torch_kCUDA case
logical, intent(in), optional :: requires_grad

Whether gradients need to be computed for the created tensor

Calls

proc~~torch_tensor_from_blob~~CallsGraph proc~torch_tensor_from_blob torch_tensor_from_blob interface~torch_from_blob_c torch_from_blob_c proc~torch_tensor_from_blob->interface~torch_from_blob_c

Called by

proc~~torch_tensor_from_blob~~CalledByGraph proc~torch_tensor_from_blob torch_tensor_from_blob proc~torch_tensor_from_array_int16_1d torch_tensor_from_array_int16_1d proc~torch_tensor_from_array_int16_1d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int16_2d torch_tensor_from_array_int16_2d proc~torch_tensor_from_array_int16_2d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int16_3d torch_tensor_from_array_int16_3d proc~torch_tensor_from_array_int16_3d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int16_4d torch_tensor_from_array_int16_4d proc~torch_tensor_from_array_int16_4d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int16_5d torch_tensor_from_array_int16_5d proc~torch_tensor_from_array_int16_5d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int32_1d torch_tensor_from_array_int32_1d proc~torch_tensor_from_array_int32_1d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int32_2d torch_tensor_from_array_int32_2d proc~torch_tensor_from_array_int32_2d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int32_3d torch_tensor_from_array_int32_3d proc~torch_tensor_from_array_int32_3d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int32_4d torch_tensor_from_array_int32_4d proc~torch_tensor_from_array_int32_4d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int32_5d torch_tensor_from_array_int32_5d proc~torch_tensor_from_array_int32_5d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int64_1d torch_tensor_from_array_int64_1d proc~torch_tensor_from_array_int64_1d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int64_2d torch_tensor_from_array_int64_2d proc~torch_tensor_from_array_int64_2d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int64_3d torch_tensor_from_array_int64_3d proc~torch_tensor_from_array_int64_3d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int64_4d torch_tensor_from_array_int64_4d proc~torch_tensor_from_array_int64_4d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int64_5d torch_tensor_from_array_int64_5d proc~torch_tensor_from_array_int64_5d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int8_1d torch_tensor_from_array_int8_1d proc~torch_tensor_from_array_int8_1d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int8_2d torch_tensor_from_array_int8_2d proc~torch_tensor_from_array_int8_2d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int8_3d torch_tensor_from_array_int8_3d proc~torch_tensor_from_array_int8_3d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int8_4d torch_tensor_from_array_int8_4d proc~torch_tensor_from_array_int8_4d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_int8_5d torch_tensor_from_array_int8_5d proc~torch_tensor_from_array_int8_5d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_real32_1d torch_tensor_from_array_real32_1d proc~torch_tensor_from_array_real32_1d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_real32_2d torch_tensor_from_array_real32_2d proc~torch_tensor_from_array_real32_2d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_real32_3d torch_tensor_from_array_real32_3d proc~torch_tensor_from_array_real32_3d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_real32_4d torch_tensor_from_array_real32_4d proc~torch_tensor_from_array_real32_4d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_real32_5d torch_tensor_from_array_real32_5d proc~torch_tensor_from_array_real32_5d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_real64_1d torch_tensor_from_array_real64_1d proc~torch_tensor_from_array_real64_1d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_real64_2d torch_tensor_from_array_real64_2d proc~torch_tensor_from_array_real64_2d->proc~torch_tensor_from_blob proc~torch_tensor_from_array_real64_3d torch_tensor_from_array_real64_3d 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Source Code

  subroutine torch_tensor_from_blob(tensor, data, ndims, tensor_shape, layout, dtype, &
                                    device_type, device_index, &
                                    requires_grad)
    use, intrinsic :: iso_c_binding, only : c_bool, c_int, c_int64_t, c_ptr
    type(torch_tensor), intent(out) :: tensor     !! Returned tensor
    type(c_ptr), intent(in)         :: data       !! Pointer to data
    integer(c_int), intent(in)      :: ndims      !! Number of dimensions of the tensor
    integer(c_int64_t), intent(in)  :: tensor_shape(:)  !! Shape of the tensor
    integer(c_int), intent(in)      :: layout(:)  !! Layout for strides for accessing data
    integer(c_int), intent(in)      :: dtype      !! Data type of the tensor
    integer(c_int), intent(in)      :: device_type  !! Device type the tensor will live on (`torch_kCPU` or `torch_kCUDA`)
    integer, optional, intent(in) :: device_index   !! Device index to use for `torch_kCUDA` case
    logical, optional, intent(in) :: requires_grad  !! Whether gradients need to be computed for the created tensor

    integer(c_int)                  :: i                    !! loop index
    integer(c_int64_t)              :: strides(ndims)       !! Strides for accessing data
    integer(c_int)                  :: device_index_value   !! device index used
    logical(c_bool)                 :: requires_grad_value  !! Whether gradients need to be computed for the created tensor

    if (.not. present(requires_grad)) then
      requires_grad_value = logical(.false., c_bool)
    else
      requires_grad_value = requires_grad
    end if

    strides(:) = 0
    do i = 1, ndims
      if (i == 1) then
        strides(layout(i)) = 1
      else
        strides(layout(i)) = strides(layout(i - 1)) * tensor_shape(layout(i - 1))
      end if
    end do

    ! Process optional arguments
    if (present(device_index)) then
      device_index_value = device_index
    else if (device_type == torch_kCPU) then
      device_index_value = -1
    else
      device_index_value = 0
    endif

    tensor%p = torch_from_blob_c(data, ndims, tensor_shape, strides, dtype,    &
                                 device_type, device_index_value,              &
                                 requires_grad_value)
  end subroutine torch_tensor_from_blob