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NormalizeOp

public class NormalizeOp
Known Direct Subclasses

Normalizes a TensorBuffer with given mean and stddev: output = (input - mean) / stddev.

Public Constructors

NormalizeOp(float mean, float stddev)
Initializes a NormalizeOp.
NormalizeOp(float[] mean, float[] stddev)
Initializes a NormalizeOp.

Public Methods

TensorBuffer
apply(TensorBuffer input)
Applies the defined normalization on given tensor and returns the result.

Inherited Methods

Public Constructors

public NormalizeOp (float mean, float stddev)

Initializes a NormalizeOp. When being called, it creates a new TensorBuffer, which satisfies:

   output = (input - mean) / stddev
 

In the following two cases, reset mean to 0 and stddev to 1 to bypass the normalization.
1. Both mean and {code stddev} are 0.
2. mean is 0 and {stddev} is Infinity.

Note: If mean is set to 0 and stddev is set to 1, no computation will happen, and original input will be directly returned in execution.

Note: The returned TensorBuffer is always a DataType.FLOAT32 tensor at present, except when the input is a DataType.UINT8 tensor, mean is set to 0 and stddev is set to 1, so that the original DataType.UINT8 tensor is returned.

Parameters
mean the mean value to be subtracted first.
stddev the standard deviation value to divide then.
Throws
IllegalArgumentException if stddev is zero.

public NormalizeOp (float[] mean, float[] stddev)

Initializes a NormalizeOp. When being called, it creates a new TensorBuffer, which satisfies:

   // Pseudo code. [...][i] means a certain element whose channel id is i.
   output[...][i] = (input[...][i] - mean[i]) / stddev[i]
 

Note: If all values in mean are set to 0 and all stddev are set to 1, no computation will happen, and original input will be directly returned in execution.

Note: The returned TensorBuffer is always a DataType.FLOAT32 tensor at present, except that the input is a DataType.UINT8 tensor, all mean are set to 0 and all stddev are set to 1.

Parameters
mean the mean values to be subtracted first for each channel.
stddev the standard deviation values to divide then for each channel.
Throws
IllegalArgumentException if any stddev is zero, or mean has different number of elements with stddev, or any of them is empty.

Public Methods

public TensorBuffer apply (TensorBuffer input)

Applies the defined normalization on given tensor and returns the result.

Note: input is possibly the same instance with the output.

Parameters
input input tensor. It may be the same instance with the output.
Returns
  • output tensor.