Package | Description |
---|---|
org.bytedeco.tensorrt.nvinfer | |
org.bytedeco.tensorrt.nvparsers |
Modifier and Type | Class and Description |
---|---|
class |
Dims2
\class Dims2
\brief Descriptor for two-dimensional data.
|
class |
Dims3
\class Dims3
\brief Descriptor for three-dimensional data.
|
class |
Dims4
\class Dims4
\brief Descriptor for four-dimensional data.
|
class |
DimsHW
\class DimsHW
\brief Descriptor for two-dimensional spatial data.
|
Modifier and Type | Method and Description |
---|---|
Dims32 |
Dims32.d(int i,
int setter) |
Dims32 |
PluginTensorDesc.dims()
Dimensions.
|
Dims32 |
ICudaEngine.getBindingDimensions(int bindingIndex)
Deprecated.
Deprecated in TensorRT 8.5. Superseded by getTensorShape().
|
Dims32 |
VExecutionContext.getBindingDimensions(int bindingIndex) |
Dims32 |
VCudaEngine.getBindingDimensions(int bindingIndex) |
Dims32 |
IExecutionContext.getBindingDimensions(int bindingIndex)
Deprecated.
Deprecated in TensorRT 8.5. Superseded by getTensorShape().
|
Dims32 |
IConvolutionLayer.getDilationNd()
\brief Get the multi-dimension dilation of the convolution.
|
Dims32 |
IDeconvolutionLayer.getDilationNd()
\brief Get the multi-dimension dilation of the deconvolution.
|
Dims32 |
VDeconvolutionLayer.getDilationNd() |
Dims32 |
VConvolutionLayer.getDilationNd() |
Dims32 |
VFillLayer.getDimensions() |
Dims32 |
IFillLayer.getDimensions()
\brief Get the output tensor's dimensions.
|
Dims32 |
ITensor.getDimensions()
\brief Get the dimensions of a tensor.
|
Dims32 |
VConstantLayer.getDimensions() |
Dims32 |
IConstantLayer.getDimensions()
\brief Get the dimensions for the layer.
|
Dims32 |
VTensor.getDimensions() |
Dims32 |
IOptimizationProfile.getDimensions(BytePointer inputName,
int select) |
Dims32 |
VOptimizationProfile.getDimensions(BytePointer inputName,
int select) |
Dims32 |
VAlgorithmContext.getDimensions(int index,
int select) |
Dims32 |
IAlgorithmContext.getDimensions(int index,
int select) |
Dims32 |
VAlgorithmContext.getDimensions(int index,
nvinfer.OptProfileSelector select) |
Dims32 |
IAlgorithmContext.getDimensions(int index,
nvinfer.OptProfileSelector select)
\brief Get the minimum / optimum / maximum dimensions for input or output tensor.
|
Dims32 |
IOptimizationProfile.getDimensions(String inputName,
nvinfer.OptProfileSelector select)
\brief Get the minimum / optimum / maximum dimensions for a dynamic input tensor.
|
Dims32 |
VOptimizationProfile.getDimensions(String inputName,
nvinfer.OptProfileSelector select) |
Dims32 |
IConvolutionLayer.getKernelSizeNd()
\brief Get the multi-dimension kernel size of the convolution.
|
Dims32 |
IDeconvolutionLayer.getKernelSizeNd()
\brief Get the multi-dimension kernel size of the deconvolution.
|
Dims32 |
VDeconvolutionLayer.getKernelSizeNd() |
Dims32 |
VConvolutionLayer.getKernelSizeNd() |
Dims32 |
IResizeLayer.getOutputDimensions()
\brief Get the output dimensions.
|
Dims32 |
VResizeLayer.getOutputDimensions() |
Dims32 |
IPluginV2.getOutputDimensions(int index,
Dims32 inputs,
int nbInputDims)
Deprecated.
\brief Get the dimension of an output tensor.
|
Dims32 |
IConvolutionLayer.getPaddingNd()
\brief Get the multi-dimension padding of the convolution.
|
Dims32 |
IDeconvolutionLayer.getPaddingNd()
\brief Get the multi-dimension padding of the deconvolution.
|
Dims32 |
VPoolingLayer.getPaddingNd() |
Dims32 |
VDeconvolutionLayer.getPaddingNd() |
Dims32 |
VConvolutionLayer.getPaddingNd() |
Dims32 |
IPoolingLayer.getPaddingNd()
\brief Get the multi-dimension padding for pooling.
|
Dims32 |
Dims32.getPointer(long i) |
Dims32 |
IConvolutionLayer.getPostPadding()
\brief Get the post-padding.
|
Dims32 |
IDeconvolutionLayer.getPostPadding()
\brief Get the padding.
|
Dims32 |
VPoolingLayer.getPostPadding() |
Dims32 |
VDeconvolutionLayer.getPostPadding() |
Dims32 |
VConvolutionLayer.getPostPadding() |
Dims32 |
IPoolingLayer.getPostPadding()
\brief Get the padding.
|
Dims32 |
VPaddingLayer.getPostPaddingNd() |
Dims32 |
IPaddingLayer.getPostPaddingNd()
\brief Get the padding that is applied at the end of the tensor.
|
Dims32 |
IConvolutionLayer.getPrePadding()
\brief Get the pre-padding.
|
Dims32 |
IDeconvolutionLayer.getPrePadding()
\brief Get the pre-padding.
|
Dims32 |
VPoolingLayer.getPrePadding() |
Dims32 |
VDeconvolutionLayer.getPrePadding() |
Dims32 |
VConvolutionLayer.getPrePadding() |
Dims32 |
IPoolingLayer.getPrePadding()
\brief Get the pre-padding.
|
Dims32 |
VPaddingLayer.getPrePaddingNd() |
Dims32 |
IPaddingLayer.getPrePaddingNd()
\brief Get the padding that is applied at the start of the tensor.
|
Dims32 |
ICudaEngine.getProfileDimensions(int bindingIndex,
int profileIndex,
int select)
Deprecated.
|
Dims32 |
VCudaEngine.getProfileDimensions(int bindingIndex,
int profileIndex,
int select) |
Dims32 |
ICudaEngine.getProfileDimensions(int bindingIndex,
int profileIndex,
nvinfer.OptProfileSelector select)
Deprecated.
Deprecated in TensorRT 8.5. Superseded by getProfileShape().
|
Dims32 |
VCudaEngine.getProfileDimensions(int bindingIndex,
int profileIndex,
nvinfer.OptProfileSelector select) |
Dims32 |
ICudaEngine.getProfileShape(BytePointer tensorName,
int profileIndex,
int select) |
Dims32 |
VCudaEngine.getProfileShape(BytePointer tensorName,
int profileIndex,
int select) |
Dims32 |
ICudaEngine.getProfileShape(String tensorName,
int profileIndex,
nvinfer.OptProfileSelector select)
\brief Get the minimum / optimum / maximum dimensions for an input tensor given its name under an optimization
profile.
|
Dims32 |
VCudaEngine.getProfileShape(String tensorName,
int profileIndex,
nvinfer.OptProfileSelector select) |
Dims32 |
IShuffleLayer.getReshapeDimensions()
\brief Get the reshaped dimensions.
|
Dims32 |
VShuffleLayer.getReshapeDimensions() |
Dims32 |
VSliceLayer.getSize() |
Dims32 |
ISliceLayer.getSize()
\brief Get dimensions of the output slice.
|
Dims32 |
VSliceLayer.getStart() |
Dims32 |
ISliceLayer.getStart()
\brief Get the start offset for the slice layer.
|
Dims32 |
VSliceLayer.getStride() |
Dims32 |
ISliceLayer.getStride()
\brief Get the stride for the output slice.
|
Dims32 |
IConvolutionLayer.getStrideNd()
\brief Get the multi-dimension stride of the convolution.
|
Dims32 |
IDeconvolutionLayer.getStrideNd()
\brief Get the multi-dimension stride of the deconvolution.
|
Dims32 |
VPoolingLayer.getStrideNd() |
Dims32 |
VDeconvolutionLayer.getStrideNd() |
Dims32 |
VConvolutionLayer.getStrideNd() |
Dims32 |
IPoolingLayer.getStrideNd()
\brief Get the multi-dimension stride for pooling.
|
Dims32 |
IAlgorithmIOInfo.getStrides()
\brief Return strides of the input/output tensor of algorithm.
|
Dims32 |
VAlgorithmIOInfo.getStrides() |
Dims32 |
VExecutionContext.getStrides(int bindingIndex) |
Dims32 |
IExecutionContext.getStrides(int bindingIndex)
Deprecated.
Deprecated in TensorRT 8.5. Superseded by getTensorStrides().
|
Dims32 |
ICudaEngine.getTensorShape(BytePointer tensorName) |
Dims32 |
VExecutionContext.getTensorShape(BytePointer tensorName) |
Dims32 |
VCudaEngine.getTensorShape(BytePointer tensorName) |
Dims32 |
IExecutionContext.getTensorShape(BytePointer tensorName) |
Dims32 |
ICudaEngine.getTensorShape(String tensorName)
\brief Get shape of an input or output tensor.
|
Dims32 |
VExecutionContext.getTensorShape(String tensorName) |
Dims32 |
VCudaEngine.getTensorShape(String tensorName) |
Dims32 |
IExecutionContext.getTensorShape(String tensorName)
\brief Return the shape of the given input or output.
|
Dims32 |
VExecutionContext.getTensorStrides(BytePointer tensorName) |
Dims32 |
IExecutionContext.getTensorStrides(BytePointer tensorName) |
Dims32 |
VExecutionContext.getTensorStrides(String tensorName) |
Dims32 |
IExecutionContext.getTensorStrides(String tensorName)
\brief Return the strides of the buffer for the given tensor name.
|
Dims32 |
VPoolingLayer.getWindowSizeNd() |
Dims32 |
IPoolingLayer.getWindowSizeNd()
\brief Get the multi-dimension window size for pooling.
|
Dims32 |
DynamicPluginTensorDesc.max()
Upper bounds on tensorâs dimensions
|
Dims32 |
DynamicPluginTensorDesc.min()
Lower bounds on tensorâs dimensions
|
Dims32 |
Dims32.nbDims(int setter) |
Dims32 |
Dims32.position(long position) |
Modifier and Type | Method and Description |
---|---|
IConstantLayer |
INetworkDefinition.addConstant(Dims32 dimensions,
Weights weights)
\brief Add a constant layer to the network.
|
IConstantLayer |
VNetworkDefinition.addConstant(Dims32 dimensions,
Weights weights) |
IConvolutionLayer |
INetworkDefinition.addConvolutionNd(ITensor input,
int nbOutputMaps,
Dims32 kernelSize,
Weights kernelWeights,
Weights biasWeights)
\brief Add a multi-dimension convolution layer to the network.
|
IConvolutionLayer |
VNetworkDefinition.addConvolutionNd(ITensor input,
int nbOutputMaps,
Dims32 kernelSize,
Weights kernelWeights,
Weights biasWeights) |
IDeconvolutionLayer |
INetworkDefinition.addDeconvolutionNd(ITensor input,
int nbOutputMaps,
Dims32 kernelSize,
Weights kernelWeights,
Weights biasWeights) |
IDeconvolutionLayer |
VNetworkDefinition.addDeconvolutionNd(ITensor input,
int nbOutputMaps,
Dims32 kernelSize,
Weights kernelWeights,
Weights biasWeights) |
IFillLayer |
INetworkDefinition.addFill(Dims32 dimensions,
int op) |
IFillLayer |
VNetworkDefinition.addFill(Dims32 dimensions,
int op) |
IFillLayer |
INetworkDefinition.addFill(Dims32 dimensions,
nvinfer.FillOperation op)
\brief Add a fill layer to the network.
|
IFillLayer |
VNetworkDefinition.addFill(Dims32 dimensions,
nvinfer.FillOperation op) |
ITensor |
INetworkDefinition.addInput(BytePointer name,
int type,
Dims32 dimensions) |
ITensor |
VNetworkDefinition.addInput(BytePointer name,
int type,
Dims32 dimensions) |
ITensor |
INetworkDefinition.addInput(String name,
nvinfer.DataType type,
Dims32 dimensions)
\brief Add an input tensor to the network.
|
ITensor |
VNetworkDefinition.addInput(String name,
nvinfer.DataType type,
Dims32 dimensions) |
IPaddingLayer |
INetworkDefinition.addPaddingNd(ITensor input,
Dims32 prePadding,
Dims32 postPadding)
Deprecated.
Deprecated in TensorRT 8.0. Superseded by addSlice().
|
IPaddingLayer |
VNetworkDefinition.addPaddingNd(ITensor input,
Dims32 prePadding,
Dims32 postPadding) |
IPoolingLayer |
INetworkDefinition.addPoolingNd(ITensor input,
int type,
Dims32 windowSize) |
IPoolingLayer |
VNetworkDefinition.addPoolingNd(ITensor input,
int type,
Dims32 windowSize) |
IPoolingLayer |
INetworkDefinition.addPoolingNd(ITensor input,
nvinfer.PoolingType type,
Dims32 windowSize)
\brief Add a multi-dimension pooling layer to the network.
|
IPoolingLayer |
VNetworkDefinition.addPoolingNd(ITensor input,
nvinfer.PoolingType type,
Dims32 windowSize) |
ISliceLayer |
INetworkDefinition.addSlice(ITensor input,
Dims32 start,
Dims32 size,
Dims32 stride)
\brief Add a slice layer to the network.
|
ISliceLayer |
VNetworkDefinition.addSlice(ITensor input,
Dims32 start,
Dims32 size,
Dims32 stride) |
void |
IPluginV2Ext.configurePlugin(Dims32 inputDims,
int nbInputs,
Dims32 outputDims,
int nbOutputs,
int[] inputTypes,
int[] outputTypes,
boolean[] inputIsBroadcast,
boolean[] outputIsBroadcast,
int floatFormat,
int maxBatchSize)
Deprecated.
|
void |
IPluginV2Ext.configurePlugin(Dims32 inputDims,
int nbInputs,
Dims32 outputDims,
int nbOutputs,
int[] inputTypes,
int[] outputTypes,
BoolPointer inputIsBroadcast,
BoolPointer outputIsBroadcast,
nvinfer.TensorFormat floatFormat,
int maxBatchSize)
Deprecated.
|
void |
IPluginV2Ext.configurePlugin(Dims32 inputDims,
int nbInputs,
Dims32 outputDims,
int nbOutputs,
IntBuffer inputTypes,
IntBuffer outputTypes,
boolean[] inputIsBroadcast,
boolean[] outputIsBroadcast,
int floatFormat,
int maxBatchSize)
Deprecated.
|
void |
IPluginV2Ext.configurePlugin(Dims32 inputDims,
int nbInputs,
Dims32 outputDims,
int nbOutputs,
IntBuffer inputTypes,
IntBuffer outputTypes,
BoolPointer inputIsBroadcast,
BoolPointer outputIsBroadcast,
nvinfer.TensorFormat floatFormat,
int maxBatchSize)
Deprecated.
|
void |
IPluginV2Ext.configurePlugin(Dims32 inputDims,
int nbInputs,
Dims32 outputDims,
int nbOutputs,
IntPointer inputTypes,
IntPointer outputTypes,
boolean[] inputIsBroadcast,
boolean[] outputIsBroadcast,
int floatFormat,
int maxBatchSize)
Deprecated.
|
void |
IPluginV2Ext.configurePlugin(Dims32 inputDims,
int nbInputs,
Dims32 outputDims,
int nbOutputs,
IntPointer inputTypes,
IntPointer outputTypes,
BoolPointer inputIsBroadcast,
BoolPointer outputIsBroadcast,
nvinfer.TensorFormat floatFormat,
int maxBatchSize)
Deprecated.
\brief Configure the layer with input and output data types.
|
void |
IPluginV2.configureWithFormat(Dims32 inputDims,
int nbInputs,
Dims32 outputDims,
int nbOutputs,
int type,
int format,
int maxBatchSize)
Deprecated.
|
void |
IPluginV2.configureWithFormat(Dims32 inputDims,
int nbInputs,
Dims32 outputDims,
int nbOutputs,
nvinfer.DataType type,
nvinfer.TensorFormat format,
int maxBatchSize)
Deprecated.
\brief Configure the layer.
|
PluginTensorDesc |
PluginTensorDesc.dims(Dims32 setter) |
Dims32 |
IPluginV2.getOutputDimensions(int index,
Dims32 inputs,
int nbInputDims)
Deprecated.
\brief Get the dimension of an output tensor.
|
DynamicPluginTensorDesc |
DynamicPluginTensorDesc.max(Dims32 setter) |
DynamicPluginTensorDesc |
DynamicPluginTensorDesc.min(Dims32 setter) |
void |
IOutputAllocator.notifyShape(BytePointer tensorName,
Dims32 dims) |
void |
IOutputAllocator.notifyShape(String tensorName,
Dims32 dims)
\brief Called by TensorRT when the shape of the output tensor is known.
|
boolean |
VExecutionContext.setBindingDimensions(int bindingIndex,
Dims32 dimensions) |
boolean |
IExecutionContext.setBindingDimensions(int bindingIndex,
Dims32 dimensions)
Deprecated.
Deprecated in TensorRT 8.5. Superseded by setInputShape().
|
void |
IConvolutionLayer.setDilationNd(Dims32 dilation)
\brief Set the multi-dimension dilation of the convolution.
|
void |
IDeconvolutionLayer.setDilationNd(Dims32 dilation)
\brief Set the multi-dimension dilation of the deconvolution.
|
void |
VDeconvolutionLayer.setDilationNd(Dims32 dilation) |
void |
VConvolutionLayer.setDilationNd(Dims32 dilation) |
boolean |
IOptimizationProfile.setDimensions(BytePointer inputName,
int select,
Dims32 dims) |
boolean |
VOptimizationProfile.setDimensions(BytePointer inputName,
int select,
Dims32 dims) |
void |
VFillLayer.setDimensions(Dims32 dimensions) |
void |
IFillLayer.setDimensions(Dims32 dimensions)
\brief Set the output tensor's dimensions.
|
void |
ITensor.setDimensions(Dims32 dimensions)
\brief Set the dimensions of a tensor.
|
void |
VConstantLayer.setDimensions(Dims32 dimensions) |
void |
IConstantLayer.setDimensions(Dims32 dimensions)
\brief Set the dimensions for the layer.
|
void |
VTensor.setDimensions(Dims32 dimensions) |
boolean |
IOptimizationProfile.setDimensions(String inputName,
nvinfer.OptProfileSelector select,
Dims32 dims)
\brief Set the minimum / optimum / maximum dimensions for a dynamic input tensor.
|
boolean |
VOptimizationProfile.setDimensions(String inputName,
nvinfer.OptProfileSelector select,
Dims32 dims) |
boolean |
VExecutionContext.setInputShape(BytePointer tensorName,
Dims32 dims) |
boolean |
IExecutionContext.setInputShape(BytePointer tensorName,
Dims32 dims) |
boolean |
VExecutionContext.setInputShape(String tensorName,
Dims32 dims) |
boolean |
IExecutionContext.setInputShape(String tensorName,
Dims32 dims)
\brief Set shape of given input.
|
void |
IConvolutionLayer.setKernelSizeNd(Dims32 kernelSize)
\brief Set the multi-dimension kernel size of the convolution.
|
void |
IDeconvolutionLayer.setKernelSizeNd(Dims32 kernelSize)
\brief Set the multi-dimension kernel size of the deconvolution.
|
void |
VDeconvolutionLayer.setKernelSizeNd(Dims32 kernelSize) |
void |
VConvolutionLayer.setKernelSizeNd(Dims32 kernelSize) |
void |
IResizeLayer.setOutputDimensions(Dims32 dimensions)
\brief Set the output dimensions.
|
void |
VResizeLayer.setOutputDimensions(Dims32 dimensions) |
void |
IConvolutionLayer.setPaddingNd(Dims32 padding)
\brief Set the multi-dimension padding of the convolution.
|
void |
IDeconvolutionLayer.setPaddingNd(Dims32 padding)
\brief Set the multi-dimension padding of the deconvolution.
|
void |
VPoolingLayer.setPaddingNd(Dims32 padding) |
void |
VDeconvolutionLayer.setPaddingNd(Dims32 padding) |
void |
VConvolutionLayer.setPaddingNd(Dims32 padding) |
void |
IPoolingLayer.setPaddingNd(Dims32 padding)
\brief Set the multi-dimension padding for pooling.
|
void |
IConvolutionLayer.setPostPadding(Dims32 padding)
\brief Set the multi-dimension post-padding of the convolution.
|
void |
IDeconvolutionLayer.setPostPadding(Dims32 padding)
\brief Set the multi-dimension post-padding of the deconvolution.
|
void |
VPoolingLayer.setPostPadding(Dims32 padding) |
void |
VDeconvolutionLayer.setPostPadding(Dims32 padding) |
void |
VConvolutionLayer.setPostPadding(Dims32 padding) |
void |
IPoolingLayer.setPostPadding(Dims32 padding)
\brief Set the multi-dimension post-padding for pooling.
|
void |
VPaddingLayer.setPostPaddingNd(Dims32 padding) |
void |
IPaddingLayer.setPostPaddingNd(Dims32 padding)
\brief Set the padding that is applied at the end of the tensor.
|
void |
IConvolutionLayer.setPrePadding(Dims32 padding)
\brief Set the multi-dimension pre-padding of the convolution.
|
void |
IDeconvolutionLayer.setPrePadding(Dims32 padding)
\brief Set the multi-dimension pre-padding of the deconvolution.
|
void |
VPoolingLayer.setPrePadding(Dims32 padding) |
void |
VDeconvolutionLayer.setPrePadding(Dims32 padding) |
void |
VConvolutionLayer.setPrePadding(Dims32 padding) |
void |
IPoolingLayer.setPrePadding(Dims32 padding)
\brief Set the multi-dimension pre-padding for pooling.
|
void |
VPaddingLayer.setPrePaddingNd(Dims32 padding) |
void |
IPaddingLayer.setPrePaddingNd(Dims32 padding)
\brief Set the padding that is applied at the start of the tensor.
|
void |
IShuffleLayer.setReshapeDimensions(Dims32 dimensions)
\brief Set the reshaped dimensions.
|
void |
VShuffleLayer.setReshapeDimensions(Dims32 dimensions) |
void |
VSliceLayer.setSize(Dims32 size) |
void |
ISliceLayer.setSize(Dims32 size)
\brief Set the dimensions of the output slice.
|
void |
VSliceLayer.setStart(Dims32 start) |
void |
ISliceLayer.setStart(Dims32 start)
\brief Set the start offset that the slice layer uses to create the output slice.
|
void |
VSliceLayer.setStride(Dims32 stride) |
void |
ISliceLayer.setStride(Dims32 stride)
\brief Set the stride for computing the output slice data.
|
void |
IConvolutionLayer.setStrideNd(Dims32 stride)
\brief Set the multi-dimension stride of the convolution.
|
void |
IDeconvolutionLayer.setStrideNd(Dims32 stride)
\brief Set the multi-dimension stride of the deconvolution.
|
void |
VPoolingLayer.setStrideNd(Dims32 stride) |
void |
VDeconvolutionLayer.setStrideNd(Dims32 stride) |
void |
VConvolutionLayer.setStrideNd(Dims32 stride) |
void |
IPoolingLayer.setStrideNd(Dims32 stride)
\brief Set the multi-dimension stride for pooling.
|
void |
VPoolingLayer.setWindowSizeNd(Dims32 windowSize) |
void |
IPoolingLayer.setWindowSizeNd(Dims32 windowSize)
\brief Set the multi-dimension window size for pooling.
|
Modifier and Type | Method and Description |
---|---|
boolean |
IUffParser.registerInput(BytePointer inputName,
Dims32 inputDims,
int inputOrder) |
boolean |
IUffParser.registerInput(String inputName,
Dims32 inputDims,
nvparsers.UffInputOrder inputOrder)
\brief Register an input name of a UFF network with the associated Dimensions.
|
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