diff options
| author |  Justin Lebar <jlebar@google.com> | 2017-12-17 10:43:11 -0800 |
|---|---|---|
| committer |  TensorFlower Gardener <gardener@tensorflow.org> | 2017-12-18 11:21:02 -0800 |
| commit | 483e439c7494dbe30a660b90a3bca1349a1bf8fd (patch) | |
| tree | 2a1610815b659c89465475e8e7c1c41f032db336 /tensorflow/stream_executor/stream.cc | |
| parent | 01da208158687c575a9c459cb62e3c5f90968bd2 (diff) | |
[StreamExecutor] Change "variance" to "inv_var" in BatchNormalizationBackward.
This parameter is not the variance of the data, but rather is
1/(sqrt(variance + epsilon). Neglecting epsilon, this is the inverse
standard deviation.
"inv_stddev" might be a better name, but "inv_var" is certainly better
than plain "variance", and it matches nvidia's name for this parameter,
which I think may override the desire for a more precise name.
No functional change.
PiperOrigin-RevId: 179352839
Diffstat (limited to 'tensorflow/stream_executor/stream.cc')
| -rw-r--r-- | tensorflow/stream_executor/stream.cc | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/stream_executor/stream.cc b/tensorflow/stream_executor/stream.cc index e92ed14779..ba5001e273 100644 --- a/tensorflow/stream_executor/stream.cc +++ b/tensorflow/stream_executor/stream.cc @@ -342,7 +342,7 @@ Stream &Stream::ThenBatchNormalizationForward( Stream &Stream::ThenBatchNormalizationBackward( const DeviceMemory<float> &y_backprop, const DeviceMemory<float> &x, const DeviceMemory<float> &scale, const DeviceMemory<float> &mean, - const DeviceMemory<float> &variance, const dnn::BatchDescriptor &x_desc, + const DeviceMemory<float> &inv_var, const dnn::BatchDescriptor &x_desc, const dnn::BatchDescriptor &scale_offset_desc, const double epsilon, DeviceMemory<float> *x_backprop, DeviceMemory<float> *scale_backprop, DeviceMemory<float> *offset_backprop) { @@ -352,7 +352,7 @@ Stream &Stream::ThenBatchNormalizationBackward( if (ok()) { if (dnn::DnnSupport *dnn = parent_->AsDnn()) { CheckError(dnn->DoBatchNormalizationBackward( - this, y_backprop, x, scale, mean, variance, x_desc, scale_offset_desc, + this, y_backprop, x, scale, mean, inv_var, x_desc, scale_offset_desc, epsilon, x_backprop, scale_backprop, offset_backprop)); } else { SetErrorAndLogNoDnnSupport(); @@ -392,7 +392,7 @@ Stream &Stream::ThenBatchNormalizationForward( Stream &Stream::ThenBatchNormalizationBackward( const DeviceMemory<Eigen::half> &y_backprop, const DeviceMemory<Eigen::half> &x, const DeviceMemory<float> &scale, - const DeviceMemory<float> &mean, const DeviceMemory<float> &variance, + const DeviceMemory<float> &mean, const DeviceMemory<float> &inv_var, const dnn::BatchDescriptor &x_desc, const dnn::BatchDescriptor &scale_offset_desc, const double epsilon, DeviceMemory<Eigen::half> *x_backprop, DeviceMemory<float> *scale_backprop, @@ -403,7 +403,7 @@ Stream &Stream::ThenBatchNormalizationBackward( if (ok()) { if (dnn::DnnSupport *dnn = parent_->AsDnn()) { CheckError(dnn->DoBatchNormalizationBackward( - this, y_backprop, x, scale, mean, variance, x_desc, scale_offset_desc, + this, y_backprop, x, scale, mean, inv_var, x_desc, scale_offset_desc, epsilon, x_backprop, scale_backprop, offset_backprop)); } else { SetErrorAndLogNoDnnSupport(); |