Computes the eigen decomposition of a batch of self-adjoint matrices
(Note: Only real inputs are supported).
Computes the eigenvalues and eigenvectors of the innermost M-by-N matrices in tensor such that tensor[...,:,:] = u[..., :, :] * Diag(s[..., :]) * Transpose(v[...,:,:]).
Constants
String | OP_NAME | The name of this op, as known by TensorFlow core engine |
Public Methods
Inherited Methods
boolean |
equals(Object arg0)
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final Class<?> |
getClass()
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int |
hashCode()
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final void |
notify()
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final void |
notifyAll()
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String |
toString()
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final void |
wait(long arg0, int arg1)
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final void |
wait(long arg0)
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final void |
wait()
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abstract ExecutionEnvironment |
env()
Return the execution environment this op was created in.
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abstract Operation |
Constants
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
Public Methods
public static Svd<T> create (Scope scope, Operand<T> a, Long maxIter, Float epsilon, String precisionConfig)
Factory method to create a class wrapping a new Svd operation.
Parameters
scope | current scope |
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a | the input tensor. |
maxIter | maximum number of sweep update, i.e., the whole lower triangular part or upper triangular part based on parameter lower. Heuristically, it has been argued that approximately log(min (M, N)) sweeps are needed in practice (Ref: Golub & van Loan "Matrix Computation"). |
epsilon | the tolerance ratio. |
precisionConfig | a serialized xla::PrecisionConfig proto. |
Returns
- a new instance of Svd
public Output<T> s ()
Singular values. The values are sorted in reverse order of magnitude, so s[..., 0] is the largest value, s[..., 1] is the second largest, etc.