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Add tf.BatchToSpace and tf.SpaceToBatch to TF MLIR ODS.

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These ops are autogenerated from TensorFlow op registry.

PiperOrigin-RevId: 316215438
Change-Id: I6ddbe3bc714a448a3cfded7b6f3282858cc674f0
This commit is contained in:
Andy Ly 2020-06-12 18:46:07 -07:00 committed by TensorFlower Gardener
parent 6d73ffb374
commit 7cf2c773e4
1 changed files with 56 additions and 0 deletions
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56
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
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@ -794,6 +794,34 @@ This op is deprecated. Prefer `tf.nn.batch_normalization`.
TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
}
def TF_BatchToSpaceOp : TF_Op<"BatchToSpace", [NoSideEffect]> {
let summary = "BatchToSpace for 4-D tensors of type T.";
let description = [{
This is a legacy version of the more general BatchToSpaceND.
Rearranges (permutes) data from batch into blocks of spatial data, followed by
cropping. This is the reverse transformation of SpaceToBatch. More specifically,
this op outputs a copy of the input tensor where values from the `batch`
dimension are moved in spatial blocks to the `height` and `width` dimensions,
followed by cropping along the `height` and `width` dimensions.
}];
let arguments = (ins
TF_Tensor:$input,
TF_I32OrI64Tensor:$crops,
Confined<I64Attr, [IntMinValue<2>]>:$block_size
);
let results = (outs
TF_Tensor:$output
);
TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
TF_DerivedOperandTypeAttr Tidx = TF_DerivedOperandTypeAttr<1>;
}
def TF_BatchToSpaceNDOp : TF_Op<"BatchToSpaceND", [NoSideEffect]> {
let summary = "BatchToSpace for N-D tensors of type T.";
@ -8475,6 +8503,34 @@ def TF_SoftsignGradOp : TF_Op<"SoftsignGrad", [NoSideEffect, SameOperandsAndResu
TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
}
def TF_SpaceToBatchOp : TF_Op<"SpaceToBatch", [NoSideEffect]> {
let summary = "SpaceToBatch for 4-D tensors of type T.";
let description = [{
This is a legacy version of the more general SpaceToBatchND.
Zero-pads and then rearranges (permutes) blocks of spatial data into batch.
More specifically, this op outputs a copy of the input tensor where values from
the `height` and `width` dimensions are moved to the `batch` dimension. After
the zero-padding, both `height` and `width` of the input must be divisible by the
block size.
}];
let arguments = (ins
TF_Tensor:$input,
TF_I32OrI64Tensor:$paddings,
Confined<I64Attr, [IntMinValue<2>]>:$block_size
);
let results = (outs
TF_Tensor:$output
);
TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;
TF_DerivedOperandTypeAttr Tpaddings = TF_DerivedOperandTypeAttr<1>;
}
def TF_SpaceToBatchNDOp : TF_Op<"SpaceToBatchND", [NoSideEffect]> {
let summary = "SpaceToBatch for N-D tensors of type T.";