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Auto generated TensorFlow SelfAdjointEigV2 op

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PiperOrigin-RevId: 320648488
Change-Id: I719b3cd44392e7699f80c697c9c64a75cdf6ac15
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Smit Hinsu 2020-07-10 12:05:33 -07:00 committed by TensorFlower Gardener
parent 63cb494e94
commit fc0b3b42ea
1 changed files with 33 additions and 0 deletions
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33
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
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@ -8266,6 +8266,39 @@ def TF_SelectV2Op : TF_Op<"SelectV2", [NoSideEffect, ResultsBroadcastableShape]>
];
}
def TF_SelfAdjointEigV2Op : TF_Op<"SelfAdjointEigV2", [NoSideEffect]> {
let summary = [{
Computes the eigen decomposition of one or more square self-adjoint matrices.
}];
let description = [{
Computes the eigenvalues and (optionally) eigenvectors of each inner matrix in
`input` such that `input[..., :, :] = v[..., :, :] * diag(e[..., :])`. The eigenvalues
are sorted in non-decreasing order.
```python
# a is a tensor.
# e is a tensor of eigenvalues.
# v is a tensor of eigenvectors.
e, v = self_adjoint_eig(a)
e = self_adjoint_eig(a, compute_v=False)
```
}];
let arguments = (ins
TensorOf<[F16, F32, F64, TF_Complex128, TF_Complex64]>:$input,
DefaultValuedAttr<BoolAttr, "true">:$compute_v
);
let results = (outs
TensorOf<[F16, F32, F64, TF_Complex128, TF_Complex64]>:$e,
TensorOf<[F16, F32, F64, TF_Complex128, TF_Complex64]>:$v
);
TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
}
def TF_SeluOp : TF_Op<"Selu", [NoSideEffect, SameOperandsAndResultType]> {
let summary = [{
Computes scaled exponential linear: `scale * alpha * (exp(features) - 1)`