Pool (Deep Java Library 0.14.0 API specification)

java.lang.Object
- ai.djl.nn.pooling.Pool

```
public final class Pool
extends java.lang.Object
```
Utility class that provides Block and methods for different pooling functions.

See Also:

The D2L chapter on pooling

Method Summary

All Methods Static Methods Concrete Methods
Modifier and Type	Method and Description
`static NDArray`	`avgPool1d(NDArray input, Shape kernelShape, Shape stride, Shape padding, boolean ceilMode, boolean countIncludePad)` Performs 1-D Avg Pooling on the input.
`static Block`	`avgPool1dBlock(Shape kernelShape)` Creates a `LambdaBlock` that applies the `avgPool1dBlock` pooling function in its forward function.
`static Block`	`avgPool1dBlock(Shape kernelShape, Shape stride)` Creates a `LambdaBlock` that applies the `avgPool1dBlock` pooling function in its forward function.
`static Block`	`avgPool1dBlock(Shape kernelShape, Shape stride, Shape padding)` Creates a `LambdaBlock` that applies the `avgPool1dBlock` pooling function in its forward function.
`static Block`	`avgPool1dBlock(Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Creates a `LambdaBlock` that applies the `avgPool1dBlock` pooling function in its forward function.
`static Block`	`avgPool1dBlock(Shape kernelShape, Shape stride, Shape padding, boolean ceilMode, boolean countIncludePad)` Creates a `LambdaBlock` that applies the `avgPool1dBlock` pooling function in its forward function.
`static NDArray`	`avgPool2d(NDArray input, Shape kernelShape, Shape stride, Shape padding, boolean ceilMode, boolean countIncludePad)` Performs 2-D Avg Pooling on the input.
`static Block`	`avgPool2dBlock(Shape kernelShape)` Creates a `LambdaBlock` that applies the `avgPool2dBlock` pooling function in its forward function.
`static Block`	`avgPool2dBlock(Shape kernelShape, Shape stride)` Creates a `LambdaBlock` that applies the `avgPool2dBlock` pooling function in its forward function.
`static Block`	`avgPool2dBlock(Shape kernelShape, Shape stride, Shape padding)` Creates a `LambdaBlock` that applies the `avgPool2dBlock` pooling function in its forward function.
`static Block`	`avgPool2dBlock(Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Creates a `LambdaBlock` that applies the `avgPool2dBlock` pooling function in its forward function.
`static Block`	`avgPool2dBlock(Shape kernelShape, Shape stride, Shape padding, boolean ceilMode, boolean countIncludePad)` Creates a `LambdaBlock` that applies the `avgPool2dBlock` pooling function in its forward function.
`static NDArray`	`avgPool3d(NDArray input, Shape kernelShape, Shape stride, Shape padding, boolean ceilMode, boolean countIncludePad)` Performs 3-D Avg Pooling on the input.
`static Block`	`avgPool3dBlock(Shape kernelShape)` Creates a `LambdaBlock` that applies the `avgPool3dBlock` pooling function in its forward function.
`static Block`	`avgPool3dBlock(Shape kernelShape, Shape stride)` Creates a `LambdaBlock` that applies the `avgPool3dBlock` pooling function in its forward function.
`static Block`	`avgPool3dBlock(Shape kernelShape, Shape stride, Shape padding)` Creates a `LambdaBlock` that applies the `avgPool3dBlock` pooling function in its forward function.
`static Block`	`avgPool3dBlock(Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Creates a `LambdaBlock` that applies the `avgPool3dBlock` pooling function in its forward function.
`static Block`	`avgPool3dBlock(Shape kernelShape, Shape stride, Shape padding, boolean ceilMode, boolean countIncludePad)` Creates a `LambdaBlock` that applies the `avgPool3dBlock` pooling function in its forward function.
`static NDArray`	`globalAvgPool1d(NDArray input)` Performs 1-D Global Avg Pooling on the input.
`static Block`	`globalAvgPool1dBlock()` Creates a `LambdaBlock` that applies the `globalAvgPool1d` pooling function.
`static NDArray`	`globalAvgPool2d(NDArray input)` Performs 2-D Global Avg Pooling on the input.
`static Block`	`globalAvgPool2dBlock()` Creates a `LambdaBlock` that applies the `globalAvgPool2d` pooling function.
`static NDArray`	`globalAvgPool3d(NDArray input)` Performs 3-D Global Avg Pooling on the input.
`static Block`	`globalAvgPool3dBlock()` Creates a `LambdaBlock` that applies the `globalAvgPool3d` pooling function.
`static NDArray`	`globalLpPool1d(NDArray input, float normType)` Performs 1-D Global LP Pooling on the input.
`static Block`	`globalLpPool1dBlock(float normType)` Creates a `LambdaBlock` that applies the `globalLpPool1d` pooling function.
`static NDArray`	`globalLpPool2d(NDArray input, float normType)` Performs 2-D Global LP Pooling on the input.
`static Block`	`globalLpPool2dBlock(float normType)` Creates a `LambdaBlock` that applies the `globalLpPool2d` pooling function.
`static NDArray`	`globalLpPool3d(NDArray input, float normType)` Performs 3-D Global LP Pooling on the input.
`static Block`	`globalLpPool3dBlock(float normType)` Creates a `LambdaBlock` that applies the `globalLpPool3d` pooling function.
`static NDArray`	`globalMaxPool1d(NDArray input)` Performs 1-D Global Max Pooling on the input.
`static Block`	`globalMaxPool1dBlock()` Creates a `LambdaBlock` that applies the `globalmaxPool1dBlock` pooling function.
`static NDArray`	`globalMaxPool2d(NDArray input)` Performs 2-D Global Max Pooling on the input.
`static Block`	`globalMaxPool2dBlock()` Creates a `LambdaBlock` that applies the `globalmaxPool2dBlock` pooling function.
`static NDArray`	`globalMaxPool3d(NDArray input)` Performs 3-D Global Max Pooling on the input.
`static Block`	`globalMaxPool3dBlock()` Creates a `LambdaBlock` that applies the `globalmaxPool3dBlock` pooling function.
`static NDArray`	`lpPool1d(NDArray input, float normType, Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Performs 1-D LP Pooling on the input.
`static Block`	`lpPool1dBlock(float normType, Shape kernelShape)` Creates a `LambdaBlock` that applies the `lpPool1dBlock` pooling function in its forward function.
`static Block`	`lpPool1dBlock(float normType, Shape kernelShape, Shape stride, Shape padding)` Creates a `LambdaBlock` that applies the `lpPool1dBlock` pooling function in its forward function.
`static Block`	`lpPool1dBlock(float normType, Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Creates a `LambdaBlock` that applies the `lpPool1dBlock` pooling function in its forward function.
`static NDArray`	`lpPool2d(NDArray input, float normType, Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Performs 2-D LP Pooling on the input.
`static Block`	`lpPool2dBlock(float normType, Shape kernelShape)` Creates a `LambdaBlock` that applies the `lpPool2dBlock` pooling function in its forward function.
`static Block`	`lpPool2dBlock(float normType, Shape kernelShape, Shape stride)` Creates a `LambdaBlock` that applies the `lpPool2dBlock` pooling function in its forward function.
`static Block`	`lpPool2dBlock(float normType, Shape kernelShape, Shape stride, Shape padding)` Creates a `LambdaBlock` that applies the `lpPool2dBlock` pooling function in its forward function.
`static Block`	`lpPool2dBlock(float normType, Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Creates a `LambdaBlock` that applies the `lpPool2dBlock` pooling function in its forward function.
`static NDArray`	`lpPool3d(NDArray input, float normType, Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Performs 3-D LP Pooling on the input.
`static Block`	`lpPool3dBlock(float normType, Shape kernelShape)` Creates a `LambdaBlock` that applies the `lpPool3dBlock` pooling function in its forward function.
`static Block`	`lpPool3dBlock(float normType, Shape kernelShape, Shape stride)` Creates a `LambdaBlock` that applies the `LpPoo3D` pooling function in its forward function.
`static Block`	`lpPool3dBlock(float normType, Shape kernelShape, Shape stride, Shape padding)` Creates a `LambdaBlock` that applies the `lpPool3dBlock` pooling function in its forward function.
`static Block`	`lpPool3dBlock(float normType, Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Creates a `LambdaBlock` that applies the `lpPool3dBlock` pooling function in its forward function.
`static NDArray`	`maxPool1d(NDArray input, Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Performs 1-D Max Pooling on the input.
`static Block`	`maxPool1dBlock(Shape kernelShape)` Creates a `LambdaBlock` that applies the `maxPool1dBlock` pooling function in its forward function.
`static Block`	`maxPool1dBlock(Shape kernelShape, Shape stride)` Creates a `LambdaBlock` that applies the `maxPool1dBlock` pooling function in its forward function.
`static Block`	`maxPool1dBlock(Shape kernelShape, Shape stride, Shape padding)` Creates a `LambdaBlock` that applies the `maxPool1dBlock` pooling function in its forward function.
`static Block`	`maxPool1dBlock(Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Creates a `LambdaBlock` that applies the `maxPool1d` pooling function in its forward function.
`static NDArray`	`maxPool2d(NDArray input, Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Performs 2-D Max Pooling on the input.
`static Block`	`maxPool2dBlock(Shape kernelShape)` Creates a `LambdaBlock` that applies the `maxPool2dBlock` pooling function in its forward function.
`static Block`	`maxPool2dBlock(Shape kernelShape, Shape stride)` Creates a `LambdaBlock` that applies the `maxPool2dBlock` pooling function in its forward function.
`static Block`	`maxPool2dBlock(Shape kernelShape, Shape stride, Shape padding)` Creates a `LambdaBlock` that applies the `maxPool2dBlock` pooling function in its forward function.
`static Block`	`maxPool2dBlock(Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Creates a `LambdaBlock` that applies the `maxPool2dBlock` pooling function in its forward function.
`static NDArray`	`maxPool3d(NDArray input, Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Performs 3-D Max Pooling on the input.
`static Block`	`maxPool3dBlock(Shape kernelShape)` Creates a `LambdaBlock` that applies the `maxPool3dBlock` pooling function in its forward function.
`static Block`	`maxPool3dBlock(Shape kernelShape, Shape stride)` Creates a `LambdaBlock` that applies the `maxPool3dBlock` pooling function in its forward function.
`static Block`	`maxPool3dBlock(Shape kernelShape, Shape stride, Shape padding)` Creates a `LambdaBlock` that applies the `maxPool3dBlock` pooling function in its forward function.
`static Block`	`maxPool3dBlock(Shape kernelShape, Shape stride, Shape padding, boolean ceilMode)` Creates a `LambdaBlock` that applies the `maxPool3dBlock` pooling function in its forward function.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Method Detail
  - maxPool1d
```
public static NDArray maxPool1d(NDArray input,
                                Shape kernelShape,
                                Shape stride,
                                Shape padding,
                                boolean ceilMode)
```
    Performs 1-D Max Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which max pooling is performed
    
    kernelShape - the shape of the kernel to be used
    
    stride - the stride to be used for each dimension
    
    padding - the padding to be set in each dimension
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the NDArray after applying max pooling
  - maxPool2d
```
public static NDArray maxPool2d(NDArray input,
                                Shape kernelShape,
                                Shape stride,
                                Shape padding,
                                boolean ceilMode)
```
    Performs 2-D Max Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which max pooling is performed
    
    kernelShape - the shape of the kernel to be used
    
    stride - the stride to be used for each dimension
    
    padding - the padding to be set in each dimension
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the NDArray after applying max pooling
  - maxPool3d
```
public static NDArray maxPool3d(NDArray input,
                                Shape kernelShape,
                                Shape stride,
                                Shape padding,
                                boolean ceilMode)
```
    Performs 3-D Max Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which max pooling is performed
    
    kernelShape - the shape of the kernel to be used
    
    stride - the stride to be used for each dimension
    
    padding - the padding to be set in each dimension
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the NDArray after applying max pooling
  - globalMaxPool1d
```
public static NDArray globalMaxPool1d(NDArray input)
```
    Performs 1-D Global Max Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which max pooling is performed
    
    Returns:
    
    the NDArray after applying global max pooling
  - globalMaxPool2d
```
public static NDArray globalMaxPool2d(NDArray input)
```
    Performs 2-D Global Max Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which max pooling is performed
    
    Returns:
    
    the NDArray after applying global max pooling
  - globalMaxPool3d
```
public static NDArray globalMaxPool3d(NDArray input)
```
    Performs 3-D Global Max Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which max pooling is performed
    
    Returns:
    
    the NDArray after applying global max pooling
  - avgPool1d
```
public static NDArray avgPool1d(NDArray input,
                                Shape kernelShape,
                                Shape stride,
                                Shape padding,
                                boolean ceilMode,
                                boolean countIncludePad)
```
    Performs 1-D Avg Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which average pooling is performed
    
    kernelShape - the shape of the kernel to be used
    
    stride - the stride to be used for each dimension
    
    padding - the padding to be set in each dimension
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    countIncludePad - whether to include padding for calculations
    
    Returns:
    
    the NDArray after applying avg pooling
  - avgPool2d
```
public static NDArray avgPool2d(NDArray input,
                                Shape kernelShape,
                                Shape stride,
                                Shape padding,
                                boolean ceilMode,
                                boolean countIncludePad)
```
    Performs 2-D Avg Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which average pooling is performed
    
    kernelShape - the shape of the kernel to be used
    
    stride - the stride to be used for each dimension
    
    padding - the padding to be set in each dimension
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    countIncludePad - whether to include padding for calculations
    
    Returns:
    
    the NDArray after applying avg pooling
  - avgPool3d
```
public static NDArray avgPool3d(NDArray input,
                                Shape kernelShape,
                                Shape stride,
                                Shape padding,
                                boolean ceilMode,
                                boolean countIncludePad)
```
    Performs 3-D Avg Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which average pooling is performed
    
    kernelShape - the shape of the kernel to be used
    
    stride - the stride to be used for each dimension
    
    padding - the padding to be set in each dimension
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    countIncludePad - whether to include padding for calculations
    
    Returns:
    
    the NDArray after applying avg pooling
  - globalAvgPool1d
```
public static NDArray globalAvgPool1d(NDArray input)
```
    Performs 1-D Global Avg Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which average pooling is performed
    
    Returns:
    
    the NDArray after applying global avg pooling
  - globalAvgPool2d
```
public static NDArray globalAvgPool2d(NDArray input)
```
    Performs 2-D Global Avg Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which average pooling is performed
    
    Returns:
    
    the NDArray after applying global avg pooling
  - globalAvgPool3d
```
public static NDArray globalAvgPool3d(NDArray input)
```
    Performs 3-D Global Avg Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which average pooling is performed
    
    Returns:
    
    the NDArray after applying global avg pooling
  - lpPool1d
```
public static NDArray lpPool1d(NDArray input,
                               float normType,
                               Shape kernelShape,
                               Shape stride,
                               Shape padding,
                               boolean ceilMode)
```
    Performs 1-D LP Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which LP pooling is performed
    
    normType - float value indicating norm
    
    kernelShape - the shape of the kernel to be used
    
    stride - the stride to be used for each dimension
    
    padding - the padding to be set in each dimension
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the NDArray after applying lp pooling
  - lpPool2d
```
public static NDArray lpPool2d(NDArray input,
                               float normType,
                               Shape kernelShape,
                               Shape stride,
                               Shape padding,
                               boolean ceilMode)
```
    Performs 2-D LP Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which LP pooling is performed
    
    normType - float value indicating norm
    
    kernelShape - the shape of the kernel to be used
    
    stride - the stride to be used for each dimension
    
    padding - the padding to be set in each dimension
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the NDArray after applying lp pooling
  - lpPool3d
```
public static NDArray lpPool3d(NDArray input,
                               float normType,
                               Shape kernelShape,
                               Shape stride,
                               Shape padding,
                               boolean ceilMode)
```
    Performs 3-D LP Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which LP pooling is performed
    
    normType - float value indicating norm
    
    kernelShape - the shape of the kernel to be used
    
    stride - the stride to be used for each dimension
    
    padding - the padding to be set in each dimension
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the NDArray after applying lp pooling
  - globalLpPool1d
```
public static NDArray globalLpPool1d(NDArray input,
                                     float normType)
```
    Performs 1-D Global LP Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which LP pooling is performed
    
    normType - float value indicating norm
    
    Returns:
    
    the NDArray after applying global lp pooling
  - globalLpPool2d
```
public static NDArray globalLpPool2d(NDArray input,
                                     float normType)
```
    Performs 2-D Global LP Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which LP pooling is performed
    
    normType - float value indicating norm
    
    Returns:
    
    the NDArray after applying global lp pooling
  - globalLpPool3d
```
public static NDArray globalLpPool3d(NDArray input,
                                     float normType)
```
    Performs 3-D Global LP Pooling on the input.
    
    Parameters:
    
    input - the NDArray on which LP pooling is performed
    
    normType - float value indicating norm
    
    Returns:
    
    the NDArray after applying global lp pooling
  - maxPool1dBlock
```
public static Block maxPool1dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding,
                                   boolean ceilMode)
```
    Creates a LambdaBlock that applies the maxPool1d pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the LambdaBlock that applies the maxPool1dBlock activation function
  - maxPool1dBlock
```
public static Block maxPool1dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding)
```
    Creates a LambdaBlock that applies the maxPool1dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    Returns:
    
    the LambdaBlock that applies the maxPool1dBlock activation function
  - maxPool1dBlock
```
public static Block maxPool1dBlock(Shape kernelShape,
                                   Shape stride)
```
    Creates a LambdaBlock that applies the maxPool1dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    Returns:
    
    the LambdaBlock that applies the maxPool1dBlock activation function
  - maxPool1dBlock
```
public static Block maxPool1dBlock(Shape kernelShape)
```
    Creates a LambdaBlock that applies the maxPool1dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    Returns:
    
    the LambdaBlock that applies the maxPool1dBlock activation function
  - maxPool2dBlock
```
public static Block maxPool2dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding,
                                   boolean ceilMode)
```
    Creates a LambdaBlock that applies the maxPool2dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the LambdaBlock that applies the maxPool2dBlock activation function
  - maxPool2dBlock
```
public static Block maxPool2dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding)
```
    Creates a LambdaBlock that applies the maxPool2dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    Returns:
    
    the LambdaBlock that applies the maxPool2dBlock activation function
  - maxPool2dBlock
```
public static Block maxPool2dBlock(Shape kernelShape,
                                   Shape stride)
```
    Creates a LambdaBlock that applies the maxPool2dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    Returns:
    
    the LambdaBlock that applies the maxPool2dBlock activation function
  - maxPool2dBlock
```
public static Block maxPool2dBlock(Shape kernelShape)
```
    Creates a LambdaBlock that applies the maxPool2dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    Returns:
    
    the LambdaBlock that applies the maxPool2dBlock activation function
  - maxPool3dBlock
```
public static Block maxPool3dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding,
                                   boolean ceilMode)
```
    Creates a LambdaBlock that applies the maxPool3dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the LambdaBlock that applies the maxPool3dBlock activation function
  - maxPool3dBlock
```
public static Block maxPool3dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding)
```
    Creates a LambdaBlock that applies the maxPool3dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    Returns:
    
    the LambdaBlock that applies the maxPool3dBlock activation function
  - maxPool3dBlock
```
public static Block maxPool3dBlock(Shape kernelShape,
                                   Shape stride)
```
    Creates a LambdaBlock that applies the maxPool3dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    Returns:
    
    the LambdaBlock that applies the maxPool3dBlock activation function
  - maxPool3dBlock
```
public static Block maxPool3dBlock(Shape kernelShape)
```
    Creates a LambdaBlock that applies the maxPool3dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    Returns:
    
    the LambdaBlock that applies the maxPool3dBlock activation function
  - globalMaxPool1dBlock
```
public static Block globalMaxPool1dBlock()
```
    Creates a LambdaBlock that applies the globalmaxPool1dBlock pooling function.
    
    Returns:
    
    the LambdaBlock that applies the globalmaxPool1dBlock pooling function
  - globalMaxPool2dBlock
```
public static Block globalMaxPool2dBlock()
```
    Creates a LambdaBlock that applies the globalmaxPool2dBlock pooling function.
    
    Returns:
    
    the LambdaBlock that applies the globalmaxPool2dBlock pooling function
  - globalMaxPool3dBlock
```
public static Block globalMaxPool3dBlock()
```
    Creates a LambdaBlock that applies the globalmaxPool3dBlock pooling function.
    
    Returns:
    
    the LambdaBlock that applies the globalmaxPool3dBlock pooling function
  - avgPool1dBlock
```
public static Block avgPool1dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding,
                                   boolean ceilMode,
                                   boolean countIncludePad)
```
    Creates a LambdaBlock that applies the avgPool1dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    countIncludePad - Boolean indicating whether to include padding for calculations
    
    Returns:
    
    the LambdaBlock that applies the avgPool1dBlock activation function
  - avgPool1dBlock
```
public static Block avgPool1dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding,
                                   boolean ceilMode)
```
    Creates a LambdaBlock that applies the avgPool1dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the LambdaBlock that applies the avgPool1dBlock activation function
  - avgPool1dBlock
```
public static Block avgPool1dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding)
```
    Creates a LambdaBlock that applies the avgPool1dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    Returns:
    
    the LambdaBlock that applies the avgPool1dBlock activation function
  - avgPool1dBlock
```
public static Block avgPool1dBlock(Shape kernelShape,
                                   Shape stride)
```
    Creates a LambdaBlock that applies the avgPool1dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    Returns:
    
    the LambdaBlock that applies the avgPool1dBlock activation function
  - avgPool1dBlock
```
public static Block avgPool1dBlock(Shape kernelShape)
```
    Creates a LambdaBlock that applies the avgPool1dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    Returns:
    
    the LambdaBlock that applies the avgPool1dBlock activation function
  - avgPool2dBlock
```
public static Block avgPool2dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding,
                                   boolean ceilMode,
                                   boolean countIncludePad)
```
    Creates a LambdaBlock that applies the avgPool2dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    countIncludePad - Boolean indicating whether to include padding for calculations
    
    Returns:
    
    the LambdaBlock that applies the avgPool2dBlock activation function
  - avgPool2dBlock
```
public static Block avgPool2dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding,
                                   boolean ceilMode)
```
    Creates a LambdaBlock that applies the avgPool2dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the LambdaBlock that applies the avgPool2dBlock activation function
  - avgPool2dBlock
```
public static Block avgPool2dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding)
```
    Creates a LambdaBlock that applies the avgPool2dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    Returns:
    
    the LambdaBlock that applies the avgPool2dBlock activation function
  - avgPool2dBlock
```
public static Block avgPool2dBlock(Shape kernelShape,
                                   Shape stride)
```
    Creates a LambdaBlock that applies the avgPool2dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    Returns:
    
    the LambdaBlock that applies the avgPool2dBlock activation function
  - avgPool2dBlock
```
public static Block avgPool2dBlock(Shape kernelShape)
```
    Creates a LambdaBlock that applies the avgPool2dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    Returns:
    
    the LambdaBlock that applies the avgPool2dBlock activation function
  - avgPool3dBlock
```
public static Block avgPool3dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding,
                                   boolean ceilMode,
                                   boolean countIncludePad)
```
    Creates a LambdaBlock that applies the avgPool3dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    countIncludePad - Boolean indicating whether to include padding for calculations
    
    Returns:
    
    the LambdaBlock that applies the avgPool3dBlock activation function
  - avgPool3dBlock
```
public static Block avgPool3dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding,
                                   boolean ceilMode)
```
    Creates a LambdaBlock that applies the avgPool3dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the LambdaBlock that applies the avgPool3dBlock activation function
  - avgPool3dBlock
```
public static Block avgPool3dBlock(Shape kernelShape,
                                   Shape stride,
                                   Shape padding)
```
    Creates a LambdaBlock that applies the avgPool3dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    Returns:
    
    the LambdaBlock that applies the avgPool3dBlock activation function
  - avgPool3dBlock
```
public static Block avgPool3dBlock(Shape kernelShape,
                                   Shape stride)
```
    Creates a LambdaBlock that applies the avgPool3dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    Returns:
    
    the LambdaBlock that applies the avgPool3dBlock activation function
  - avgPool3dBlock
```
public static Block avgPool3dBlock(Shape kernelShape)
```
    Creates a LambdaBlock that applies the avgPool3dBlock pooling function in its forward function.
    
    Parameters:
    
    kernelShape - the shape of the kernel to be used
    
    Returns:
    
    the LambdaBlock that applies the avgPool3dBlock activation function
  - globalAvgPool1dBlock
```
public static Block globalAvgPool1dBlock()
```
    Creates a LambdaBlock that applies the globalAvgPool1d pooling function.
    
    Returns:
    
    the LambdaBlock that applies the globalAvgPool1d pooling function
  - globalAvgPool2dBlock
```
public static Block globalAvgPool2dBlock()
```
    Creates a LambdaBlock that applies the globalAvgPool2d pooling function.
    
    Returns:
    
    the LambdaBlock that applies the globalAvgPool2d pooling function
  - globalAvgPool3dBlock
```
public static Block globalAvgPool3dBlock()
```
    Creates a LambdaBlock that applies the globalAvgPool3d pooling function.
    
    Returns:
    
    the LambdaBlock that applies the globalAvgPool3d pooling function
  - lpPool1dBlock
```
public static Block lpPool1dBlock(float normType,
                                  Shape kernelShape,
                                  Shape stride,
                                  Shape padding,
                                  boolean ceilMode)
```
    Creates a LambdaBlock that applies the lpPool1dBlock pooling function in its forward function.
    
    Parameters:
    
    normType - integer indicating pValue
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - padding of pooling layer
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the LambdaBlock that applies the lpPool1dBlock activation function
  - lpPool1dBlock
```
public static Block lpPool1dBlock(float normType,
                                  Shape kernelShape,
                                  Shape stride,
                                  Shape padding)
```
    Creates a LambdaBlock that applies the lpPool1dBlock pooling function in its forward function.
    
    Parameters:
    
    normType - integer indicating pValue
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - padding of pooling layer
    
    Returns:
    
    the LambdaBlock that applies the lpPool1dBlock activation function
  - lpPool1dBlock
```
public static Block lpPool1dBlock(float normType,
                                  Shape kernelShape)
```
    Creates a LambdaBlock that applies the lpPool1dBlock pooling function in its forward function.
    
    Parameters:
    
    normType - float value indicating norm
    
    kernelShape - the shape of the kernel to be used
    
    Returns:
    
    the LambdaBlock that applies the lpPool1dBlock activation function
  - lpPool2dBlock
```
public static Block lpPool2dBlock(float normType,
                                  Shape kernelShape,
                                  Shape stride,
                                  Shape padding,
                                  boolean ceilMode)
```
    Creates a LambdaBlock that applies the lpPool2dBlock pooling function in its forward function.
    
    Parameters:
    
    normType - float value indicating norm
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the LambdaBlock that applies the lpPool2dBlock activation function
  - lpPool2dBlock
```
public static Block lpPool2dBlock(float normType,
                                  Shape kernelShape,
                                  Shape stride,
                                  Shape padding)
```
    Creates a LambdaBlock that applies the lpPool2dBlock pooling function in its forward function.
    
    Parameters:
    
    normType - float value indicating norm
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    Returns:
    
    the LambdaBlock that applies the lpPool2dBlock activation function
  - lpPool2dBlock
```
public static Block lpPool2dBlock(float normType,
                                  Shape kernelShape,
                                  Shape stride)
```
    Creates a LambdaBlock that applies the lpPool2dBlock pooling function in its forward function.
    
    Parameters:
    
    normType - float value indicating norm
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    Returns:
    
    the LambdaBlock that applies the lpPool2dBlock activation function
  - lpPool2dBlock
```
public static Block lpPool2dBlock(float normType,
                                  Shape kernelShape)
```
    Creates a LambdaBlock that applies the lpPool2dBlock pooling function in its forward function.
    
    Parameters:
    
    normType - float value indicating norm
    
    kernelShape - the shape of the kernel to be used
    
    Returns:
    
    the LambdaBlock that applies the lpPool2dBlock activation function
  - lpPool3dBlock
```
public static Block lpPool3dBlock(float normType,
                                  Shape kernelShape,
                                  Shape stride,
                                  Shape padding,
                                  boolean ceilMode)
```
    Creates a LambdaBlock that applies the lpPool3dBlock pooling function in its forward function.
    
    Parameters:
    
    normType - float value indicating norm
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    ceilMode - when true, will use ceil instead of floor in the formula to compute the output shape. The formula is f(x, k, p, s) = floor((x+2*p-k)/s)+1.
    
    Returns:
    
    the LambdaBlock that applies the lpPool3dBlock activation function
  - lpPool3dBlock
```
public static Block lpPool3dBlock(float normType,
                                  Shape kernelShape,
                                  Shape stride,
                                  Shape padding)
```
    Creates a LambdaBlock that applies the lpPool3dBlock pooling function in its forward function.
    
    Parameters:
    
    normType - float value indicating norm
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    padding - pad of the pooling layer
    
    Returns:
    
    the LambdaBlock that applies the lpPool3dBlock activation function
  - lpPool3dBlock
```
public static Block lpPool3dBlock(float normType,
                                  Shape kernelShape,
                                  Shape stride)
```
    Creates a LambdaBlock that applies the LpPoo3D pooling function in its forward function.
    
    Parameters:
    
    normType - float value indicating norm
    
    kernelShape - the shape of the kernel to be used
    
    stride - stride of pooling layer
    
    Returns:
    
    the LambdaBlock that applies the lpPool3dBlock activation function
  - lpPool3dBlock
```
public static Block lpPool3dBlock(float normType,
                                  Shape kernelShape)
```
    Creates a LambdaBlock that applies the lpPool3dBlock pooling function in its forward function.
    
    Parameters:
    
    normType - float value indicating norm
    
    kernelShape - the shape of the kernel to be used
    
    Returns:
    
    the LambdaBlock that applies the lpPool3dBlock activation function
  - globalLpPool1dBlock
```
public static Block globalLpPool1dBlock(float normType)
```
    Creates a LambdaBlock that applies the globalLpPool1d pooling function.
    
    Parameters:
    
    normType - float value indicating norm
    
    Returns:
    
    the LambdaBlock that applies the globalLpPool1d pooling function
  - globalLpPool2dBlock
```
public static Block globalLpPool2dBlock(float normType)
```
    Creates a LambdaBlock that applies the globalLpPool2d pooling function.
    
    Parameters:
    
    normType - float value indicating norm
    
    Returns:
    
    the LambdaBlock that applies the globalLpPool2d pooling function
  - globalLpPool3dBlock
```
public static Block globalLpPool3dBlock(float normType)
```
    Creates a LambdaBlock that applies the globalLpPool3d pooling function.
    
    Parameters:
    
    normType - float value indicating norm
    
    Returns:
    
    the LambdaBlock that applies the globalLpPool3d pooling function

Class Pool

Method Summary

Methods inherited from class java.lang.Object

Method Detail

maxPool1d

maxPool2d

maxPool3d

globalMaxPool1d

globalMaxPool2d

globalMaxPool3d

avgPool1d

avgPool2d

avgPool3d

globalAvgPool1d

globalAvgPool2d

globalAvgPool3d

lpPool1d

lpPool2d

lpPool3d

globalLpPool1d

globalLpPool2d

globalLpPool3d

maxPool1dBlock

maxPool1dBlock

maxPool1dBlock

maxPool1dBlock

maxPool2dBlock

maxPool2dBlock

maxPool2dBlock

maxPool2dBlock

maxPool3dBlock

maxPool3dBlock

maxPool3dBlock

maxPool3dBlock

globalMaxPool1dBlock

globalMaxPool2dBlock

globalMaxPool3dBlock

avgPool1dBlock

avgPool1dBlock

avgPool1dBlock

avgPool1dBlock

avgPool1dBlock

avgPool2dBlock

avgPool2dBlock

avgPool2dBlock

avgPool2dBlock

avgPool2dBlock

avgPool3dBlock

avgPool3dBlock

avgPool3dBlock

avgPool3dBlock

avgPool3dBlock

globalAvgPool1dBlock

globalAvgPool2dBlock

globalAvgPool3dBlock

lpPool1dBlock

lpPool1dBlock

lpPool1dBlock

lpPool2dBlock

lpPool2dBlock

lpPool2dBlock

lpPool2dBlock

lpPool3dBlock

lpPool3dBlock

lpPool3dBlock

lpPool3dBlock

globalLpPool1dBlock

globalLpPool2dBlock

globalLpPool3dBlock