Defined in tensorflow/contrib/kfac/python/ops/utils_lib.py
.
Utility functions.
class SequenceDict
: A dict convenience wrapper that allows getting/setting with sequences.
class SubGraph
: Defines a subgraph given by all the dependencies of a given set of outputs.
batch_execute(...)
: Executes a subset of ops per global step.
column_to_tensors(...)
: Converts a column vector back to the shape of the given template.
ensure_sequence(...)
: If obj
isn't a tuple or list, return a tuple containing obj
.
extract_convolution_patches(...)
: Extracts inputs to each output coordinate in tf.nn.convolution.
extract_pointwise_conv2d_patches(...)
: Extract patches for a 1x1 conv2d.
fwd_gradients(...)
: Compute forward-mode gradients.
generate_random_signs(...)
: Generate a random tensor with {-1, +1} entries.
is_data_format_channel_last(...)
: True if data_format puts channel last.
kronecker_product(...)
: Computes the Kronecker product two matrices.
layer_params_to_mat2d(...)
: Converts a vector shaped like layer parameters to a 2D matrix.
mat2d_to_layer_params(...)
: Converts a canonical 2D matrix representation back to a vector.
matmul_diag_sparse(...)
: Computes matmul(A, B) where A is a diagonal matrix, B is sparse.
matmul_sparse_dense(...)
: Computes matmul(A, B) where A is sparse, B is dense.
posdef_inv(...)
: Computes the inverse of tensor + damping * identity.
posdef_inv_cholesky(...)
: Computes inverse(tensor + damping * identity) with Cholesky.
posdef_inv_matrix_inverse(...)
: Computes inverse(tensor + damping * identity) directly.
set_global_constants(...)
: Sets various global constants used by the classes in this module.
tensors_to_column(...)
: Converts a tensor or list of tensors to a column vector.
__cached__
__loader__
__spec__
© 2018 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/contrib/kfac/utils