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author | Jianwei Xie <xiejw@google.com> | 2018-03-29 10:50:46 -0700 |
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committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-03-29 10:52:55 -0700 |
commit | 63dffd5a3bc4e94e74cb140cbf7a68e0e5644ad6 (patch) | |
tree | 087e334cd7e71d44cdcd1ce5ebab483768fcf474 /tensorflow/contrib/timeseries | |
parent | 9fbb5b3b8fef1caa2ee2ca4a0f8dde900d1f2aa5 (diff) |
Automated g4 rollback of changelist 190858242
PiperOrigin-RevId: 190953197
Diffstat (limited to 'tensorflow/contrib/timeseries')
3 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/contrib/timeseries/python/timeseries/ar_model.py b/tensorflow/contrib/timeseries/python/timeseries/ar_model.py index ff140efd48..4f6527a546 100644 --- a/tensorflow/contrib/timeseries/python/timeseries/ar_model.py +++ b/tensorflow/contrib/timeseries/python/timeseries/ar_model.py @@ -70,7 +70,7 @@ class ARModel(model.TimeSeriesModel): input_window_size: Number of past time steps of data to look at when doing the regression. output_window_size: Number of future time steps to predict. Note that - setting it to > 1 empiricaly seems to give a better fit. + setting it to > 1 empirically seems to give a better fit. num_features: number of input features per time step. num_time_buckets: Number of buckets into which to divide (time % periodicity) for generating time based features. diff --git a/tensorflow/contrib/timeseries/python/timeseries/math_utils.py b/tensorflow/contrib/timeseries/python/timeseries/math_utils.py index 23452a81c3..26793c80bf 100644 --- a/tensorflow/contrib/timeseries/python/timeseries/math_utils.py +++ b/tensorflow/contrib/timeseries/python/timeseries/math_utils.py @@ -185,7 +185,7 @@ def batch_matrix_pow(matrices, powers): { matmul(A, power(matmul(A, A), (p - 1) / 2)) for odd p power(A, 0) = I - The power(A, 0) = I case is handeled by starting with accumulator set to the + The power(A, 0) = I case is handled by starting with accumulator set to the identity matrix; matrices with zero residual powers are passed through unchanged. diff --git a/tensorflow/contrib/timeseries/python/timeseries/state_space_models/varma.py b/tensorflow/contrib/timeseries/python/timeseries/state_space_models/varma.py index 1afc58cfb2..6746dd7b43 100644 --- a/tensorflow/contrib/timeseries/python/timeseries/state_space_models/varma.py +++ b/tensorflow/contrib/timeseries/python/timeseries/state_space_models/varma.py @@ -107,7 +107,7 @@ class VARMA(state_space_model.StateSpaceModel): Returns: the state transition matrix. It has shape - [self.state_dimendion, self.state_dimension]. + [self.state_dimension, self.state_dimension]. """ # Pad any unused AR blocks with zeros. The extra state is necessary if # ma_order >= ar_order. @@ -127,7 +127,7 @@ class VARMA(state_space_model.StateSpaceModel): Returns: the state noise transform matrix. It has shape - [self.state_dimendion, self.num_features]. + [self.state_dimension, self.num_features]. """ # Noise is broadcast, through the moving average coefficients, to # un-observed parts of the latent state. |