Weights
- tensorrt.WeightsRole
How a layer uses particular Weights. The power weights of an IScaleLayer are omitted. Refitting those is not supported.
Members:
KERNEL : Kernel for
IConvolutionLayer
orIDeconvolutionLayer
.BIAS : Bias for
IConvolutionLayer
orIDeconvolutionLayer
.SHIFT : Shift part of
IScaleLayer
.SCALE : Scale part of
IScaleLayer
.CONSTANT : Weights for
IConstantLayer
.ANY : Any other weights role.
- class tensorrt.Weights(*args, **kwargs)
An array of weights used as a layer parameter. The weights are held by reference until the engine has been built - deep copies are not made automatically.
- Variables
dtype –
DataType
The type of the weights.size –
int
The number of weights in the array.nbytes –
int
Total bytes consumed by the elements of the weights buffer.
Overloaded function.
__init__(self: tensorrt.tensorrt.Weights, type: tensorrt.tensorrt.DataType = <DataType.FLOAT: 0>) -> None
Initializes an empty (0-length) Weights object with the specified type.
- type
A type to initialize the weights with. Default:
tensorrt.float32
__init__(self: tensorrt.tensorrt.Weights, type: tensorrt.tensorrt.DataType, ptr: int, count: int) -> None
Initializes a Weights object with the specified data.
- type
A type to initialize the weights with.
- ptr
A pointer to the data.
- count
The number of weights.
__init__(self: tensorrt.tensorrt.Weights, a: numpy.ndarray) -> None
- a
A numpy array whose values to use. No deep copies are made.
- numpy(self: tensorrt.tensorrt.Weights) object
Create a numpy array using the underlying buffer of this weights object. The resulting array is just a view over the existing data, i.e. no deep copy is made.
If the weights cannot be converted to NumPy (e.g. due to unsupported data type), the original weights are returned.
- Returns
The NumPy array or the original weights.