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Op documentation update.

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update of g3doc/tf_ops.md
	update of g3doc/includes/tf_passes.md

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A. Unique TensorFlower 2021-01-08 06:22:20 -08:00 committed by TensorFlower Gardener
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tensorflow/compiler/mlir/g3doc/includes/tf_passes.md
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<!-- Autogenerated by mlir-tblgen; don't manually edit -->
### `-cluster-ops-by-policy`: Clusters ops according to specified policy.
This pass clusters ops according to the policy specified by the pass options.
Clustered ops are moved to a tf_device::clusterOp region.
The only currently supported option is 'oplist=<list of ops>'. This option
specifies the names of the ops that should be clustered if they form
a single use def-use chain, that is, the next op in the list uses the result
of the previous op and is the only user of that result. The ops should
be located in the same block, be assigned to the same device and have no
side effects.
For example, running this pass with option oplist="tf.Cast, tf.Add" on:
```mlir
func @cluster_oplist(%arg0 : tensor<f32>, %arg1 : tensor<i32>) -> tensor<i32> {
%0 = "tf.Cast"(%arg0) : (tensor<f32>) -> tensor<i32>
%1 = "SomeOp" (%arg1) : (tensor<i32>) -> tensor<i32>
%2 = "tf.Add"(%0, %1) : (tensor<i32>, tensor<i32>) -> tensor<i32>
return %2 : tensor<i32>
}
```
will produce tf_device::opCluster enclosing tf.Add and tf.Neg:
```mlir
func @cluster_oplist(%arg0: tensor<f32>, %arg1: tensor<i32>) -> tensor<i32> {
%0 = "SomeOp"(%arg1) : (tensor<i32>) -> tensor<i32>
%1 = "tf_device.cluster"() ( {
%2 = "tf.Cast"(%arg0) : (tensor<f32>) -> tensor<i32>
%3 = "tf.Add"(%2, %0) : (tensor<i32>, tensor<i32>) -> tensor<i32>
tf_device.return %3 : tensor<i32>
}) : () -> tensor<i32>
return %1 : tensor<i32>
}
```
#### Options
```
-oplist : Cluster listed ops when they form a single use def-use chain, such that each op's single user is the next op in the list.
```
### `-tf-device-cluster-outlining`: Outlines regions of tf_device.cluster operations
This pass outlines the body of a `tf_device.cluster` into a function and
replaces the `tf_device.cluster` op with an equivalent `tf_device.cluster_func`