message: NFC: Remove mentions of the TensorFlow dialect from the langref.
diff: @@ -1224,39 +1224,12 @@ a conversion pass.
  Currently, MLIR supports the following dialects:
  -* [Standard dialect](Dialects/Standard.md)
  * [Affine dialect](Dialects/Affine.md)
  +* [GPU dialect](Dialects/GPU.md)
  +* [LLVM dialect](Dialects/LLVM.md)
  +* [SPIR-V dialect](Dialects/SPIR-V.md)
  +* [Standard dialect](Dialects/Standard.md)
  * [Vector dialect](Dialects/Vector.md)
  -* [TensorFlow dialect](#tensorflow-operations)
  -
  -### TensorFlow operations
  -
  -MLIR operations can represent arbitrary TensorFlow operations with a reversible
  -mapping. Switch and merge nodes are represented with the MLIR control flow
  -graph. TensorFlow dataflow operations are mapped over to MLIR operations whose
  -name gets a "tf." prefix.
  -
  -The normal dtypes supported by TensorFlow are mapped onto a Tensor type with an
  -unknown rank. The resource and variant dtypes are mapped onto our resource and
  -variant type specifically (TODO: Specify this). Attributes get mapped over
  -directly, with type attributes represented as strings.
  -
  -Examples:
  -
  -```mlir {.mlir}
  -// TensorFlow Add operation.
  -%a = "tf.Add"(%b, %c)
  - : (tensor<*xf32>,tensor<*xf32>) -> tensor<*xf32>
  -
  -// TensorFlow Add operation with partially inferred shapes.
  -%d = "tf.Add"(%e, %f)
  - : (tensor<?x42x?xf32>,tensor<?x42x?xf32>) -> tensor<?x42x?xf32>
  -
  -// TensorFlow Conv2d operation.
  -%y = "tf.Conv2d"(%input, %filter)
  - {strides: [1,1,2,1], padding: "SAME", dilations: [2,1,1,1]}
  - : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
  -```
  ### Target specific operations
  @@ -1332,16 +1305,3 @@ that are not allowed in the lighter syntax, as well as unbalanced `<>`
  characters.
  See [here](DefiningAttributesAndTypes.md) to learn how to define dialect types.
  -
  -### TensorFlow types
  -
  -The TensorFlow dialect in MLIR defines several extended types:
  -
  -``` {.ebnf}
  -// TensorFlow specific types (TODO: the rest ref data types)
  -type-specific-data ::= `control` | `resource` | `variant` | `string`
  - `complex64` | `complex128` | `f32ref`
  -```
  -
  -`control` is used in TensorFlow graphs to represent
  -[control dependence edges](https://docs.google.com/document/d/1Iey7MfrAlBWd0nrHNdnVKvIKRoo8XHsWG5g5pi1iDV4/edit?ts=5b5a0a9f#heading=h.1dv5wuya469j).
  