Removed all (most) BASE_HLO_* ops.
Moved the corresponding `summary` and `description` fields into the subclasses. Kept BASE_HLO_ConvOp for `hasWindowReversal()'. PiperOrigin-RevId: 373173025
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@ -44,8 +44,13 @@ def I32Buffer : MemRefOf<[I32]>;
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// calls generate or consume standard deviation, whereas LHLO ops generate or
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// consume variance (= std-dev ^ 2).
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def LHLOGPU_BatchNormGradOp : LHLOGPU_Op<"batch_norm_grad">,
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BASE_HLO_BatchNormGradOp {
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def LHLOGPU_BatchNormGradOp : LHLOGPU_Op<"batch_norm_grad"> {
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let summary = "Batch Normalization Gradient";
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let description = [{
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Calculates gradients of batch norm.
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See https://www.tensorflow.org/xla/operation_semantics#batchnormgrad
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}];
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let arguments = (ins
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Arg<LHLO_FpBuffer, "", [MemRead]>:$operand,
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Arg<LHLO_FpBuffer, "", [MemRead]>:$scale,
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@ -60,8 +65,13 @@ def LHLOGPU_BatchNormGradOp : LHLOGPU_Op<"batch_norm_grad">,
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);
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}
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def LHLOGPU_BatchNormInferenceOp : LHLOGPU_Op<"batch_norm_inference">,
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BASE_HLO_BatchNormInferenceOp {
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def LHLOGPU_BatchNormInferenceOp : LHLOGPU_Op<"batch_norm_inference"> {
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let summary = "Batch Normalization for Inference";
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let description = [{
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Normalizes an array across batch and spatial dimensions.
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See https://www.tensorflow.org/xla/operation_semantics#batchnorminference
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}];
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let arguments = (ins
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Arg<LHLO_FpBuffer, "", [MemRead]>:$operand,
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Arg<LHLO_FpBuffer, "", [MemRead]>:$scale,
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@ -73,8 +83,13 @@ def LHLOGPU_BatchNormInferenceOp : LHLOGPU_Op<"batch_norm_inference">,
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I64Attr:$feature_index);
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}
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def LHLOGPU_BatchNormTrainingOp : LHLOGPU_Op<"batch_norm_training">,
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BASE_HLO_BatchNormTrainingOp {
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def LHLOGPU_BatchNormTrainingOp : LHLOGPU_Op<"batch_norm_training"> {
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let summary = "Batch Normalization for Training";
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let description = [{
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Normalizes an array across batch and spatial dimensions.
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See https://www.tensorflow.org/xla/operation_semantics#batchnormtraining
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}];
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let arguments = (ins
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Arg<LHLO_FpBuffer, "", [MemRead]>:$operand,
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