Layer Base Classes

ITensor

class tensorrt_rtx.ITensor

A tensor in an INetworkDefinition .

Variables:

  • name – str The tensor name. For a network input, the name is assigned by the application. For tensors which are layer outputs, a default name is assigned consisting of the layer name followed by the index of the output in brackets. Each network input and output tensor must have a unique name.

  • shape – Dims The shape of a tensor. For a network input the shape is assigned by the application. For a network output it is computed based on the layer parameters and the inputs to the layer. If a tensor size or a parameter is modified in the network, the shape of all dependent tensors will be recomputed. This call is only legal for network input tensors, since the shape of layer output tensors are inferred based on layer inputs and parameters.

  • dtype – DataType The data type of a tensor. The type is unchanged if the type is invalid for the given tensor.

  • broadcast_across_batch – bool [DEPRECATED] Deprecated in TensorRT 10.0. Always false since the implicit batch dimensions support has been removed.

  • location – TensorLocation The storage location of a tensor.

  • is_network_input – bool Whether the tensor is a network input.

  • is_network_output – bool Whether the tensor is a network output.

  • dynamic_range – Tuple[float, float] [DEPRECATED] Deprecated in TensorRT 10.1. Superseded by explicit quantization. A tuple containing the [minimum, maximum] of the dynamic range, or None if the range was not set.

  • is_shape – bool Whether the tensor is a shape tensor.

  • allowed_formats – int32 The allowed set of TensorFormat candidates. This should be an integer consisting of one or more TensorFormat s, combined via bitwise OR after bit shifting. For example, 1 << int(TensorFormat.CHW4) | 1 << int(TensorFormat.CHW32).

get_dimension_name(self: tensorrt_rtx.tensorrt_rtx.ITensor, index: int) → str

Get the name of an input dimension.

Parameters:

index – index of the dimension.

Returns:

name of the dimension, or null if dimension is unnamed.

set_dimension_name(self: tensorrt_rtx.tensorrt_rtx.ITensor, index: int, name: str) → None

Name a dimension of an input tensor.

Associate a runtime dimension of an input tensor with a symbolic name. Dimensions with the same non-empty name must be equal at runtime. Knowing this equality for runtime dimensions may help the TensorRT optimizer. Both runtime and build-time dimensions can be named. If the function is called again, with the same index, it will overwrite the previous name. If None is passed as name, it will clear the name of the dimension.

For example, setDimensionName(0, “n”) associates the symbolic name “n” with the leading dimension.

Parameters:

  • index – index of the dimension.

  • name – name of the dimension.

ILayer

class tensorrt_rtx.ILayer

Base class for all layer classes in an INetworkDefinition .

Variables:

  • name – str The name of the layer.

  • type – LayerType The type of the layer.

  • num_inputs – int The number of inputs of the layer.

  • num_outputs – int The number of outputs of the layer.

  • precision – DataType The computation precision.

  • precision_is_set – bool Whether the precision is set or not.

Ival metadata:

str The per-layer metadata.

get_input(self: tensorrt_rtx.tensorrt_rtx.ILayer, index: int) → tensorrt_rtx.tensorrt_rtx.ITensor

Get the layer input corresponding to the given index.

Parameters:

index – The index of the input tensor.

Returns:

The input tensor, or None if the index is out of range.

get_output(self: tensorrt_rtx.tensorrt_rtx.ILayer, index: int) → tensorrt_rtx.tensorrt_rtx.ITensor

Get the layer output corresponding to the given index.

Parameters:

index – The index of the output tensor.

Returns:

The output tensor, or None if the index is out of range.

get_output_type(self: tensorrt_rtx.tensorrt_rtx.ILayer, index: int) → tensorrt_rtx.tensorrt_rtx.DataType

Get the output type of the layer.

Parameters:

index – The index of the output tensor.

Returns:

The output precision. Default : DataType.FLOAT.

output_type_is_set(self: tensorrt_rtx.tensorrt_rtx.ILayer, index: int) → bool

[DEPRECATED] Deprecated in TensorRT 10.12. Superseded by strong typing. Whether the output type has been set for this layer.

Parameters:

index – The index of the output.

Returns:

Whether the output type has been explicitly set.

reset_output_type(self: tensorrt_rtx.tensorrt_rtx.ILayer, index: int) → None

[DEPRECATED] Deprecated in TensorRT 10.12. Superseded by strong typing. Reset output type of this layer.

Parameters:

index – The index of the output.

reset_precision(self: tensorrt_rtx.tensorrt_rtx.ILayer) → None

[DEPRECATED] Deprecated in TensorRT 10.12. Superseded by strong typing. Reset the computation precision of the layer.

set_input(self: tensorrt_rtx.tensorrt_rtx.ILayer, index: int, tensor: tensorrt_rtx.tensorrt_rtx.ITensor) → None

Set the layer input corresponding to the given index.

Parameters:

  • index – The index of the input tensor.

  • tensor – The input tensor.

set_output_type(self: tensorrt_rtx.tensorrt_rtx.ILayer, index: int, dtype: tensorrt_rtx.tensorrt_rtx.DataType) → None

[DEPRECATED] Deprecated in TensorRT 10.12. Superseded by strong typing. Constraint layer to generate output data with given type. Note that this method cannot be used to set the data type of the second output tensor of the topK layer. The data type of the second output tensor of the topK layer is always int32 .

Parameters:

  • index – The index of the output tensor to set the type.

  • dtype – DataType of the output.