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| author |  A. Unique TensorFlower <gardener@tensorflow.org> | 2017-08-17 18:04:58 -0700 |
|---|---|---|
| committer | TensorFlower Gardener <gardener@tensorflow.org> | 2017-08-17 18:08:34 -0700 |
| commit | 7359fec792e4efec1670a12332bb524a5608b215 (patch) | |
| tree | cce4b3a2360071424ab2d794bc86de4598fe51fb /tensorflow/compiler/xla/service/hlo_opcode.cc | |
| parent | f0da8bf56ba1b625d53b760683bc44f67e204199 (diff) | |
Implement Batchnorm Inference by expanding them into smaller ops.
1. Add batch norm inference support in batchnorm_rewriter
2. Connect xla's batchnorm inference to tf's FusedBatchNorm
RELNOTES: n/a
PiperOrigin-RevId: 165655351
Diffstat (limited to 'tensorflow/compiler/xla/service/hlo_opcode.cc')
| -rw-r--r-- | tensorflow/compiler/xla/service/hlo_opcode.cc | 2 |
1 files changed, 2 insertions, 0 deletions
diff --git a/tensorflow/compiler/xla/service/hlo_opcode.cc b/tensorflow/compiler/xla/service/hlo_opcode.cc index 3888f757ad..314512d0a8 100644 --- a/tensorflow/compiler/xla/service/hlo_opcode.cc +++ b/tensorflow/compiler/xla/service/hlo_opcode.cc @@ -33,6 +33,8 @@ string HloOpcodeString(HloOpcode opcode) { return "add"; case HloOpcode::kBatchNormTraining: return "batch-norm-training"; + case HloOpcode::kBatchNormInference: + return "batch-norm-inference"; case HloOpcode::kBatchNormGrad: return "batch-norm-grad"; case HloOpcode::kBitcast: |