LoadAndRemapMatrix

public final class LoadAndRemapMatrix

Loads a 2-D (matrix) `Tensor` with name `old_tensor_name` from the checkpoint

at `ckpt_path` and potentially reorders its rows and columns using the specified remappings.

Most users should use one of the wrapper initializers (such as `tf.contrib.framework.load_and_remap_matrix_initializer`) instead of this function directly.

The remappings are 1-D tensors with the following properties:

• `row_remapping` must have exactly `num_rows` entries. Row `i` of the output matrix will be initialized from the row corresponding to index `row_remapping[i]` in the old `Tensor` from the checkpoint.
• `col_remapping` must have either 0 entries (indicating that no column reordering is needed) or `num_cols` entries. If specified, column `j` of the output matrix will be initialized from the column corresponding to index `col_remapping[j]` in the old `Tensor` from the checkpoint.
• A value of -1 in either of the remappings signifies a "missing" entry. In that case, values from the `initializing_values` tensor will be used to fill that missing row or column. If `row_remapping` has `r` missing entries and `col_remapping` has `c` missing entries, then the following condition must be true:

`(r * num_cols) + (c * num_rows) - (r * c) == len(initializing_values)`

The remapping tensors can be generated using the GenerateVocabRemapping op.

As an example, with row_remapping = [1, 0, -1], col_remapping = [0, 2, -1], initializing_values = [0.5, -0.5, 0.25, -0.25, 42], and w(i, j) representing the value from row i, column j of the old tensor in the checkpoint, the output matrix will look like the following:

[[w(1, 0), w(1, 2), 0.5], [w(0, 0), w(0, 2), -0.5], [0.25, -0.25, 42]]

Nested Classes

class

LoadAndRemapMatrix.Options

Optional attributes for LoadAndRemapMatrix

Constants

String

OP_NAME

The name of this op, as known by TensorFlow core engine

Public Methods

Output<TFloat32>	asOutput() Returns the symbolic handle of the tensor.
static LoadAndRemapMatrix	create(Scope scope, Operand<TString> ckptPath, Operand<TString> oldTensorName, Operand<TInt64> rowRemapping, Operand<TInt64> colRemapping, Operand<TFloat32> initializingValues, Long numRows, Long numCols, Options... options) Factory method to create a class wrapping a new LoadAndRemapMatrix operation.
static LoadAndRemapMatrix.Options	maxRowsInMemory(Long maxRowsInMemory)
Output<TFloat32>	outputMatrix() Output matrix containing existing values loaded from the checkpoint, and with any missing values filled in from initializing_values.

Inherited Methods

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single Operation.
final String	toString()

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

From interface org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single Operation.

From interface org.tensorflow.Operand

abstract Output<TFloat32>	asOutput() Returns the symbolic handle of the tensor.
abstract TFloat32	asTensor() Returns the tensor at this operand.
abstract Shape	shape() Returns the (possibly partially known) shape of the tensor referred to by the Output of this operand.
abstract Class<TFloat32>	type() Returns the tensor type of this operand

From interface org.tensorflow.ndarray.Shaped

abstract int	rank()
abstract Shape	shape()
abstract long	size() Computes and returns the total size of this container, in number of values.

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "LoadAndRemapMatrix"

Public Methods

public Output<TFloat32> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static LoadAndRemapMatrix create (Scope scope, Operand<TString> ckptPath, Operand<TString> oldTensorName, Operand<TInt64> rowRemapping, Operand<TInt64> colRemapping, Operand<TFloat32> initializingValues, Long numRows, Long numCols, Options... options)

Factory method to create a class wrapping a new LoadAndRemapMatrix operation.

Parameters

scope	current scope
ckptPath	Path to the TensorFlow checkpoint (version 2, `TensorBundle`) from which the old matrix `Tensor` will be loaded.
oldTensorName	Name of the 2-D `Tensor` to load from checkpoint.
rowRemapping	An int `Tensor` of row remappings (generally created by `generate_vocab_remapping`). Even if no row remapping is needed, this must still be an index-valued Tensor (e.g. [0, 1, 2, ...]), or a shifted index-valued `Tensor` (e.g. [8, 9, 10, ...], for partitioned `Variables`).
colRemapping	An int `Tensor` of column remappings (generally created by `generate_vocab_remapping`). May be a size-0 `Tensor` if only row remapping is to be done (e.g. column ordering is the same).
initializingValues	A float `Tensor` containing values to fill in for cells in the output matrix that are not loaded from the checkpoint. Length must be exactly the same as the number of missing / new cells.
numRows	Number of rows (length of the 1st dimension) in the output matrix.
numCols	Number of columns (length of the 2nd dimension) in the output matrix.
options	carries optional attributes values

Returns

• a new instance of LoadAndRemapMatrix

public static LoadAndRemapMatrix.Options maxRowsInMemory (Long maxRowsInMemory)

Parameters

maxRowsInMemory	The maximum number of rows to load from the checkpoint at once. If less than or equal to 0, the entire matrix will be loaded into memory. Setting this arg trades increased disk reads for lower memory usage.

public Output<TFloat32> outputMatrix ()

Output matrix containing existing values loaded from the checkpoint, and with any missing values filled in from initializing_values.