nvinfer.TensorFormat (JavaCPP Presets for TensorRT 10.6-1.5.11 API)

java.lang.Object
- java.lang.Enum<nvinfer.TensorFormat>
- - org.bytedeco.tensorrt.global.nvinfer.TensorFormat

All Implemented Interfaces:

Serializable, Comparable<nvinfer.TensorFormat>

Enclosing class:

nvinfer
```
@Namespace(value="nvinfer1")
public static enum nvinfer.TensorFormat
extends Enum<nvinfer.TensorFormat>
```
\enum TensorFormat \brief Format of the input/output tensors. This enum is used by both plugins and network I/O tensors.

See Also:

IPluginV2::supportsFormat(), safe::ICudaEngine::getBindingFormat() Many of the formats are **vector-major** or **vector-minor**. These formats specify a vector dimension and scalars per vector. For example, suppose that the tensor has has dimensions [M,N,C,H,W], the vector dimension is C and there are V scalars per vector. * A **vector-major** format splits the vectorized dimension into two axes in the memory layout. The vectorized dimension is replaced by an axis of length ceil(C/V) and a new dimension of length V is appended. For the example tensor, the memory layout is equivalent to an array with dimensions [M][N][ceil(C/V)][H][W][V]. Tensor coordinate (m,n,c,h,w) maps to array location [m][n][c/V][h][w][c\%V]. * A **vector-minor** format moves the vectorized dimension to become the last axis in the memory layout. For the example tensor, the memory layout is equivalent to an array with dimensions [M][N][H][W][ceil(C/V)*V]. Tensor coordinate (m,n,c,h,w) maps array location subscript [m][n][h][w][c]. In interfaces that refer to "components per element", that's the value of V above. For more information about data formats, see the topic "Data Format Description" located in the TensorRT Developer Guide. https://docs.nvidia.com/deeplearning/tensorrt/developer-guide/index.html#data-format-desc

Enum Constant Summary

Enum Constants
Enum Constant and Description
`kCDHW32` Vector-major format with 32 scalars per vector.
`kCHW16` Vector-major format with 16 scalars per vector.
`kCHW2` Vector-major format with two scalars per vector.
`kCHW32` Vector-major format with 32 scalars per vector.
`kCHW4` Vector-major format with four scalars per vector.
`kDHWC` Vector-minor format with one scalar per vector.
`kDHWC8` Vector-minor format with eight scalars per vector.
`kDLA_HWC4` DLA image format.
`kDLA_LINEAR` DLA planar format.
`kHWC` Vector-minor format where channel dimension is third to last and unpadded.
`kHWC16` Vector-minor format with 16 scalars per vector.
`kHWC8` Vector-minor format with eight scalars per vector.
`kLINEAR` Memory layout is similar to an array in C or C++.

Field Summary

Fields
Modifier and Type Field and Description

int value

Fields
Modifier and Type	Field and Description
`int`	`value`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`nvinfer.TensorFormat`	`intern()`
`String`	`toString()`
`static nvinfer.TensorFormat`	`valueOf(String name)` Returns the enum constant of this type with the specified name.
`static nvinfer.TensorFormat[]`	`values()` Returns an array containing the constants of this enum type, in the order they are declared.

Methods inherited from class java.lang.Enum
clone, compareTo, equals, finalize, getDeclaringClass, hashCode, name, ordinal, valueOf

Methods inherited from class java.lang.Object
getClass, notify, notifyAll, wait, wait, wait

- Enum Constant Detail
  - kLINEAR
```
public static final nvinfer.TensorFormat kLINEAR
```
    Memory layout is similar to an array in C or C++. The stride of each dimension is the product of the dimensions after it. The last dimension has unit stride. For DLA usage, the tensor sizes are limited to C,H,W in the range [1,8192].
  - kCHW2
```
public static final nvinfer.TensorFormat kCHW2
```
    Vector-major format with two scalars per vector. Vector dimension is third to last. This format requires FP16 and at least three dimensions.
  - kHWC8
```
public static final nvinfer.TensorFormat kHWC8
```
    Vector-minor format with eight scalars per vector. Vector dimension is third to last. This format requires FP16 or BF16 and at least three dimensions.
  - kCHW4
```
public static final nvinfer.TensorFormat kCHW4
```
    Vector-major format with four scalars per vector. Vector dimension is third to last. This format requires INT8 or FP16 and at least three dimensions. For INT8, the length of the vector dimension must be a build-time constant. Deprecated usage: If running on the DLA, this format can be used for acceleration with the caveat that C must be less than or equal to 4. If used as DLA input and the build option kGPU_FALLBACK is not specified, it needs to meet line stride requirement of DLA format. Column stride in bytes must be a multiple of 64 on Orin.
  - kCHW16
```
public static final nvinfer.TensorFormat kCHW16
```
    Vector-major format with 16 scalars per vector. Vector dimension is third to last. This format requires FP16 and at least three dimensions. For DLA usage, this format maps to the native feature format for FP16, and the tensor sizes are limited to C,H,W in the range [1,8192].
  - kCHW32
```
public static final nvinfer.TensorFormat kCHW32
```
    Vector-major format with 32 scalars per vector. Vector dimension is third to last. This format requires at least three dimensions. For DLA usage, this format maps to the native feature format for INT8, and the tensor sizes are limited to C,H,W in the range [1,8192].
  - kDHWC8
```
public static final nvinfer.TensorFormat kDHWC8
```
    Vector-minor format with eight scalars per vector. Vector dimension is fourth to last. This format requires FP16 or BF16 and at least four dimensions.
  - kCDHW32
```
public static final nvinfer.TensorFormat kCDHW32
```
    Vector-major format with 32 scalars per vector. Vector dimension is fourth to last. This format requires FP16 or INT8 and at least four dimensions.
  - kHWC
```
public static final nvinfer.TensorFormat kHWC
```
    Vector-minor format where channel dimension is third to last and unpadded. This format requires either FP32, FP16, UINT8, INT64 or BF16 and at least three dimensions.
  - kDLA_LINEAR
```
public static final nvinfer.TensorFormat kDLA_LINEAR
```
    DLA planar format. For a tensor with dimension {N, C, H, W}, the W axis always has unit stride. The stride for stepping along the H axis is rounded up to 64 bytes. The memory layout is equivalent to a C array with dimensions [N][C][H][roundUp(W, 64/elementSize)] where elementSize is 2 for FP16 and 1 for Int8, with the tensor coordinates (n, c, h, w) mapping to array subscript [n][c][h][w].
  - kDLA_HWC4
```
public static final nvinfer.TensorFormat kDLA_HWC4
```
    DLA image format. For a tensor with dimension {N, C, H, W} the C axis always has unit stride. The stride for stepping along the H axis is rounded up to 64 bytes on Orin. C can only be 1, 3 or 4. If C == 1, it will map to grayscale format. If C == 3 or C == 4, it will map to color image format. And if C == 3, the stride for stepping along the W axis needs to be padded to 4 in elements. When C is {1, 3, 4}, then C' is {1, 4, 4} respectively, the memory layout is equivalent to a C array with dimensions [N][H][roundUp(W, 64/C'/elementSize)][C'] on Orin where elementSize is 2 for FP16 and 1 for Int8. The tensor coordinates (n, c, h, w) mapping to array subscript [n][h][w][c].
  - kHWC16
```
public static final nvinfer.TensorFormat kHWC16
```
    Vector-minor format with 16 scalars per vector. Vector dimension is third to last. This requires FP16 or INT8 and at least three dimensions.
  - kDHWC
```
public static final nvinfer.TensorFormat kDHWC
```
    Vector-minor format with one scalar per vector. Vector dimension is fourth to last. This format requires FP32 and at least four dimensions.
- Field Detail
  - value
```
public final int value
```
- Method Detail
  - values
```
public static nvinfer.TensorFormat[] values()
```
    Returns an array containing the constants of this enum type, in the order they are declared. This method may be used to iterate over the constants as follows:
```
for (nvinfer.TensorFormat c : nvinfer.TensorFormat.values())
    System.out.println(c);
```
    Returns:
    
    an array containing the constants of this enum type, in the order they are declared
  - valueOf
```
public static nvinfer.TensorFormat valueOf(String name)
```
    Returns the enum constant of this type with the specified name. The string must match exactly an identifier used to declare an enum constant in this type. (Extraneous whitespace characters are not permitted.)
    
    Parameters:
    
    name - the name of the enum constant to be returned.
    
    Returns:
    
    the enum constant with the specified name
    
    Throws:
    
    IllegalArgumentException - if this enum type has no constant with the specified name
    
    NullPointerException - if the argument is null
  - intern
```
public nvinfer.TensorFormat intern()
```
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Enum<nvinfer.TensorFormat>

Enum nvinfer.TensorFormat

Enum Constant Summary

Field Summary

Method Summary

Methods inherited from class java.lang.Enum

Methods inherited from class java.lang.Object

Enum Constant Detail

kLINEAR

kCHW2

kHWC8

kCHW4

kCHW16

kCHW32

kDHWC8

kCDHW32

kHWC

kDLA_LINEAR

kDLA_HWC4

kHWC16

kDHWC

Field Detail

value

Method Detail

values

valueOf

intern

toString