Update docs.

Change: 147419923
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A. Unique TensorFlower 2017-02-13 18:06:46 -08:00 committed by TensorFlower Gardener
parent 08950c20ed
commit 6cfa696b45
5 changed files with 6 additions and 96 deletions

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@ -13,10 +13,7 @@
# limitations under the License.
# ==============================================================================
"""## Control Flow Operations
TensorFlow provides several operations and classes that you can use to control
the execution of operations and add conditional dependencies to your graph.
"""Control Flow Operations. See the @{python/control_flow_ops} guide.
@@identity
@@tuple
@ -26,22 +23,10 @@ the execution of operations and add conditional dependencies to your graph.
@@cond
@@case
@@while_loop
## Logical Operators
TensorFlow provides several operations that you can use to add logical operators
to your graph.
@@logical_and
@@logical_not
@@logical_or
@@logical_xor
## Comparison Operators
TensorFlow provides several operations that you can use to add comparison
operators to your graph.
@@equal
@@not_equal
@@less
@ -49,12 +34,6 @@ operators to your graph.
@@greater
@@greater_equal
@@where
## Debugging Operations
TensorFlow provides several operations that you can use to validate values and
debug your graph.
@@is_finite
@@is_inf
@@is_nan

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@ -12,13 +12,10 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""## Script Language Operators.
TensorFlow provides allows you to wrap python/numpy functions as
TensorFlow operators.
"""Script Language Operators. See the @{python/script_ops} guide.
@@py_func
"""
# pylint: disable=g-bad-name

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# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""## Tensor Handle Operations.
TensorFlow provides several operators that allows the user to keep tensors
"in-place" across run calls.
"""Tensor Handle Operations. See the @{python/session_ops} guide.
@@get_session_handle
@@get_session_tensor

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@ -14,25 +14,14 @@
# ==============================================================================
# pylint: disable=g-short-docstring-punctuation
"""## Sparse Tensor Representation
TensorFlow supports a `SparseTensor` representation for data that is sparse
in multiple dimensions. Contrast this representation with `IndexedSlices`,
which is efficient for representing tensors that are sparse in their first
dimension, and dense along all other dimensions.
"""Sparse Tensor Representation. See the @{python/sparse_ops} guide.
@@SparseTensor
@@SparseTensorValue
## Conversion
@@sparse_to_dense
@@sparse_tensor_to_dense
@@sparse_to_indicator
@@sparse_merge
## Manipulation
@@sparse_concat
@@sparse_reorder
@@sparse_reshape
@ -41,18 +30,15 @@ dimension, and dense along all other dimensions.
@@sparse_reset_shape
@@sparse_fill_empty_rows
@@sparse_transpose
## Reduction
@@sparse_reduce_sum
@@sparse_reduce_sum_sparse
## Math Operations
@@sparse_add
@@sparse_softmax
@@sparse_tensor_dense_matmul
@@sparse_maximum
@@sparse_minimum
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

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@ -13,46 +13,27 @@
# limitations under the License.
# ==============================================================================
"""## Variables
"""Variables. See the @{python/state_ops} guide.
@@Variable
## Variable helper functions
TensorFlow provides a set of functions to help manage the set of variables
collected in the graph.
@@global_variables
@@local_variables
@@model_variables
@@trainable_variables
@@moving_average_variables
@@global_variables_initializer
@@local_variables_initializer
@@variables_initializer
@@is_variable_initialized
@@report_uninitialized_variables
@@assert_variables_initialized
@@assign
@@assign_add
@@assign_sub
## Saving and Restoring Variables
@@Saver
@@latest_checkpoint
@@get_checkpoint_state
@@update_checkpoint_state
## Sharing Variables
TensorFlow provides several classes and operations that you can use to
create variables contingent on certain conditions.
@@get_variable
@@get_local_variable
@@VariableScope
@ -60,9 +41,7 @@ create variables contingent on certain conditions.
@@variable_op_scope
@@get_variable_scope
@@make_template
@@no_regularizer
@@constant_initializer
@@random_normal_initializer
@@truncated_normal_initializer
@ -71,27 +50,9 @@ create variables contingent on certain conditions.
@@zeros_initializer
@@ones_initializer
@@orthogonal_initializer
## Variable Partitioners for Sharding
@@fixed_size_partitioner
@@variable_axis_size_partitioner
@@min_max_variable_partitioner
## Sparse Variable Updates
The sparse update ops modify a subset of the entries in a dense `Variable`,
either overwriting the entries or adding / subtracting a delta. These are
useful for training embedding models and similar lookup-based networks, since
only a small subset of embedding vectors change in any given step.
Since a sparse update of a large tensor may be generated automatically during
gradient computation (as in the gradient of
[`tf.gather`](../../api_docs/python/array_ops.md#gather)),
an [`IndexedSlices`](#IndexedSlices) class is provided that encapsulates a set
of sparse indices and values. `IndexedSlices` objects are detected and handled
automatically by the optimizers in most cases.
@@scatter_update
@@scatter_add
@@scatter_sub
@ -102,25 +63,14 @@ automatically by the optimizers in most cases.
@@scatter_nd_sub
@@sparse_mask
@@IndexedSlices
### Read-only Lookup Tables
@@initialize_all_tables
@@tables_initializer
## Exporting and Importing Meta Graphs
@@export_meta_graph
@@import_meta_graph
# Deprecated functions (removed after 2017-03-02). Please don't use them.
@@all_variables
@@initialize_all_variables
@@initialize_local_variables
@@initialize_variables
"""
from __future__ import absolute_import