Dims

Volume

tensorrt.volume(iterable)

Computes the volume of an iterable.

Parameters:iterable – Any python iterable, including a Dims object.
Returns:The volume of the iterable
Note:This will return 1 for empty iterables, as a scalar has an

empty shape and the volume of a tensor with empty shape is 1.

Dims

class tensorrt.Dims(*args, **kwargs)

Structure to define the dimensions of a tensor. Dims and all derived classes behave like Python tuple s. Furthermore, the TensorRT API can implicitly convert Python iterables to Dims objects, so tuple or list can be used in place of this class.

Overloaded function.

  1. __init__(self: tensorrt.tensorrt.Dims) -> None
  2. __init__(self: tensorrt.tensorrt.Dims, shape: List[int]) -> None
MAX_DIMS

The maximum number of dimensions supported by Dims.

get_type(self: tensorrt.tensorrt.Dims, arg0: int) → tensorrt.tensorrt.DimensionType

Queries the type of a dimension.

Returns:The type of the specified dimension.

Dims2

class tensorrt.Dims2(*args, **kwargs)

Structure to define 2D shape.

Overloaded function.

  1. __init__(self: tensorrt.tensorrt.Dims2) -> None
  2. __init__(self: tensorrt.tensorrt.Dims2, dim0: int, dim1: int) -> None
  3. __init__(self: tensorrt.tensorrt.Dims2, shape: List[int]) -> None

DimsHW

class tensorrt.DimsHW(*args, **kwargs)

Structure to define 2D shape with height and width.

Variables:
  • h – int The first dimension (height).
  • w – int The second dimension (width).

Overloaded function.

  1. __init__(self: tensorrt.tensorrt.DimsHW) -> None
  2. __init__(self: tensorrt.tensorrt.DimsHW, h: int, w: int) -> None
  3. __init__(self: tensorrt.tensorrt.DimsHW, shape: List[int]) -> None

Dims3

class tensorrt.Dims3(*args, **kwargs)

Structure to define 3D shape.

Overloaded function.

  1. __init__(self: tensorrt.tensorrt.Dims3) -> None
  2. __init__(self: tensorrt.tensorrt.Dims3, dim0: int, dim1: int, dim2: int) -> None
  3. __init__(self: tensorrt.tensorrt.Dims3, shape: List[int]) -> None

DimsCHW

class tensorrt.DimsCHW(*args, **kwargs)

Structure to define 3D tensor with a channel dimension, height, and width.

Variables:
  • c – int The first dimension (channel).
  • h – int The second dimension (height).
  • w – int The third dimension (width).

Overloaded function.

  1. __init__(self: tensorrt.tensorrt.DimsCHW) -> None
  2. __init__(self: tensorrt.tensorrt.DimsCHW, c: int, h: int, w: int) -> None
  3. __init__(self: tensorrt.tensorrt.DimsCHW, shape: List[int]) -> None

Dims4

class tensorrt.Dims4(*args, **kwargs)

Structure to define 4D tensor.

Overloaded function.

  1. __init__(self: tensorrt.tensorrt.Dims4) -> None
  2. __init__(self: tensorrt.tensorrt.Dims4, dim0: int, dim1: int, dim2: int, dim3: int) -> None
  3. __init__(self: tensorrt.tensorrt.Dims4, shape: List[int]) -> None

DimsNCHW

class tensorrt.DimsNCHW(*args, **kwargs)

Structure to define 4D tensor with a batch dimension, a channel dimension, height and width.

Variables:
  • n – int The first dimension (batch).
  • c – int The second dimension (channel).
  • h – int The third dimension (height).
  • w – int The fourth dimension (width).

Overloaded function.

  1. __init__(self: tensorrt.tensorrt.DimsNCHW) -> None
  2. __init__(self: tensorrt.tensorrt.DimsNCHW, n: int, c: int, h: int, w: int) -> None
  3. __init__(self: tensorrt.tensorrt.DimsNCHW, shape: List[int]) -> None