View source on GitHub |
Framework utilities.
Modules
nest
module: ## Functions for working with arbitrarily nested sequences of elements.
Classes
class BoundedTensorSpec
: A TensorSpec
that specifies minimum and maximum values.
class RecordInput
: RecordInput asynchronously reads and randomly yields TFRecords.
class TensorSpec
: Describes a tf.Tensor.
class VariableDeviceChooser
: Device chooser for variables.
class convolutional_delta_orthogonal
: Initializer that generates a delta orthogonal kernel for ConvNets.
class convolutional_orthogonal_1d
: Initializer that generates a 1D orthogonal kernel for ConvNets.
class convolutional_orthogonal_2d
: Initializer that generates a 2D orthogonal kernel for ConvNets.
class convolutional_orthogonal_3d
: Initializer that generates a 3D orthogonal kernel for ConvNets.
Functions
add_arg_scope(...)
: Decorates a function with args so it can be used within an arg_scope.
add_model_variable(...)
: Adds a variable to the GraphKeys.MODEL_VARIABLES
collection.
arg_scope(...)
: Stores the default arguments for the given set of list_ops.
arg_scoped_arguments(...)
: Returns the list kwargs that arg_scope can set for a func.
argsort(...)
: Returns the indices of a tensor that give its sorted order along an axis.
assert_global_step(...)
: DEPRECATED FUNCTION
assert_or_get_global_step(...)
: Verifies that a global step tensor is valid or gets one if None is given.
assert_same_float_dtype(...)
: Validate and return float type based on tensors
and dtype
.
assert_scalar(...)
: Asserts that the given tensor
is a scalar (i.e. zero-dimensional).
assert_scalar_int(...)
: Assert tensor
is 0-D, of type tf.int32
or tf.int64
.
assign_from_checkpoint(...)
: Creates an operation to assign specific variables from a checkpoint.
assign_from_checkpoint_fn(...)
: Returns a function that assigns specific variables from a checkpoint.
assign_from_values(...)
: Creates an assignment operation from a given mapping.
assign_from_values_fn(...)
: Returns a function that assigns specific variables from the given values.
convert_to_tensor_or_sparse_tensor(...)
: Converts value to a SparseTensor
or Tensor
.
create_global_step(...)
: Create global step tensor in graph. (deprecated)
deprecated(...)
: Decorator for marking functions or methods deprecated.
deprecated_arg_values(...)
: Decorator for marking specific function argument values as deprecated.
deprecated_args(...)
: Decorator for marking specific function arguments as deprecated.
filter_variables(...)
: Filter a list of variables using regular expressions.
fuse_op(...)
: Fuse subgraph between input_nodes and output_nodes into a single custom op.
get_global_step(...)
: DEPRECATED FUNCTION
get_graph_from_inputs(...)
: Returns the appropriate graph to use for the given inputs.
get_local_variables(...)
: Gets the list of local variables, filtered by scope and/or suffix.
get_model_variables(...)
: Gets the list of model variables, filtered by scope and/or suffix.
get_name_scope(...)
: Returns the current name scope of the default graph.
get_or_create_global_step(...)
: Returns and create (if necessary) the global step tensor. (deprecated)
get_placeholders(...)
: Get placeholders of a graph.
get_trainable_variables(...)
: Gets the list of trainable variables, filtered by scope and/or suffix.
get_unique_variable(...)
: Gets the variable uniquely identified by that var_op_name.
get_variable_full_name(...)
: Returns the full name of a variable.
get_variables(...)
: Gets the list of variables, filtered by scope and/or suffix.
get_variables_by_name(...)
: Gets the list of variables that were given that name.
get_variables_by_suffix(...)
: Gets the list of variables that end with the given suffix.
get_variables_to_restore(...)
: Gets the list of the variables to restore.
global_variable(...)
: Create a variable with a value and add it to GraphKeys.GLOBAL_VARIABLES
.
has_arg_scope(...)
: Checks whether a func has been decorated with @add_arg_scope or not.
init_from_checkpoint(...)
: Using assignment map initializes current variables with loaded tensors.
is_tensor(...)
: Checks whether x
is a tensor or "tensor-like".
list_variables(...)
: Returns list of all variables in the latest checkpoint.
load_and_remap_matrix_initializer(...)
: Returns a var initializer for loading and remapping a 2-D (matrix) tensor.
load_checkpoint(...)
: Returns CheckpointReader for latest checkpoint.
load_embedding_initializer(...)
: Returns a variable initializer for loading pre-trained embeddings.
load_linear_multiclass_bias_initializer(...)
: Loads pre-trained multi-class biases for linear models from checkpoint.
load_variable(...)
: Returns a Tensor with the contents of the given variable in the checkpoint.
load_variable_slot_initializer(...)
: Loads pre-trained multi-class slots for linear models from checkpoint.
local_variable(...)
: Create a variable with a value and add it to GraphKeys.LOCAL_VARIABLES
.
model_variable(...)
: Gets an existing model variable with these parameters or creates a new one.
prepend_name_scope(...)
: Prepends name scope to a name.
py_func(...)
: Wraps a python function and uses it as a TensorFlow op.
reduce_sum_n(...)
: Reduce tensors to a scalar sum.
remove_squeezable_dimensions(...)
: Squeeze last dim if ranks of predictions
and labels
differ by 1. (deprecated)
smart_case(...)
: Like tf.case, except attempts to statically evaluate predicates.
smart_cond(...)
: Return either true_fn()
if predicate pred
is true else false_fn()
.
smart_constant_value(...)
: Return the bool value for pred
, or None if pred
had a dynamic value.
sort(...)
: Sorts a tensor.
strip_name_scope(...)
: Removes name scope from a name.
variable(...)
: Gets an existing variable with these parameters or creates a new one.
with_same_shape(...)
: Assert tensors are the same shape, from the same graph.
with_shape(...)
: Asserts tensor has expected shape.
zero_initializer(...)
: Initialize 'ref' with all zeros, ref tensor should be uninitialized.