Google I/O एक लपेट है! TensorFlow सत्रों पर पकड़ बनाएं सत्र

# टेंसरफ़्लो :: ऑप्स :: TakeManySparseFromTensorsMap

#include <sparse_ops.h>

एक घने तन्यता में एक विरल प्रतिनिधित्व को रूपांतरित करता है।

## सारांश

आकृति के साथ एक सरणी dense बनाता है output_shape ऐसा

# यदि विरल_बिंदु अदिश है

घना [i] = (i == sparse_indices; sparse_values: default_value)

[

# यदि sparse_indices d मैट्रिक्स द्वारा एक n है, तो प्रत्येक में I [0, n) में

घने [विरल_इंदाईस [i] [०], ..., विरल_इंदिकाएँ [i] [डी -१]] = विरल_वाले [i] ०६२६38४३20२०

Indices should be sorted in lexicographic order, and indices must not
contain any repeats. If `validate_indices` is true, these properties
are checked during execution.

Arguments:
* scope: A Scope object
* sparse_indices: 0-D, 1-D, or 2-D.  `sparse_indices[i]` contains the complete
index where `sparse_values[i]` will be placed.
* output_shape: 1-D.  Shape of the dense output tensor.
* sparse_values: 1-D.  Values corresponding to each row of `sparse_indices`,
or a scalar value to be used for all sparse indices.
* default_value: Scalar value to set for indices not specified in
`sparse_indices`.

Optional attributes (see `Attrs`):
* validate_indices: If true, indices are checked to make sure they are sorted in
lexicographic order and that there are no repeats.

Returns:
* `Output`: Dense output tensor of shape `output_shape`. */
class SparseToDense {
public:
/// Optional attribute setters for SparseToDense
struct Attrs {
/** If true, indices are checked to make sure they are sorted in
lexicographic order and that there are no repeats.

Defaults to true */
TF_MUST_USE_RESULT Attrs ValidateIndices(bool x) {
Attrs ret = *this;
ret.validate_indices_ = x;
return ret;
}

bool validate_indices_ = true;
};
SparseToDense(const tensorflow::Scope& scope, tensorflow::Input
sparse_indices, tensorflow::Input output_shape,
tensorflow::Input sparse_values, tensorflow::Input
default_value);
SparseToDense(const tensorflow::Scope& scope, tensorflow::Input
sparse_indices, tensorflow::Input output_shape,
tensorflow::Input sparse_values, tensorflow::Input
default_value, const SparseToDense::Attrs& attrs);
operator ::tensorflow::Output() const { return dense; }
operator ::tensorflow::Input() const { return dense; }
::tensorflow::Node* node() const { return dense.node(); }

static Attrs ValidateIndices(bool x) {
return Attrs().ValidateIndices(x);
}

Operation operation;
tensorflow::Output dense;
};

/** Read `SparseTensors` from a `SparseTensorsMap` and concatenate them.

The input `sparse_handles` must be an `int64` matrix of shape `[N, 1]` where
`N` is the minibatch size and the rows correspond to the output handles of
original `SparseTensor` objects that went into the given input ops must all
match.  When the final `SparseTensor` is created, it has rank one
higher than the ranks of the incoming `SparseTensor` objects
(they have been concatenated along a new row dimension on the left).

The output `SparseTensor` object's shape values for all dimensions but the
first are the max across the input `SparseTensor` objects' shape values
for the corresponding dimensions.  Its first shape value is `N`, the minibatch
size.

The input `SparseTensor` objects' indices are assumed ordered in
standard lexicographic order.  If this is not the case, after this
step run `SparseReorder` to restore index ordering.

For example, if the handles represent an input, which is a `[2, 3]` matrix
representing two original `SparseTensor` objects:

index = [ 0] [10] [20] values = [1, 2, 3] shape = [50]

and

index = [ 2] [10] values = [4, 5] shape = [30]

then the final `SparseTensor` will be:

index = [0 0] [0 10] [0 20] [1 2] [1 10] values = [1, 2, 3, 4, 5] shape = [2 50] ```

Arguments:

• scope: A Scope object
• sparse_handles: 1-D, The N serialized SparseTensor objects. Shape: [N].
• dtype: The dtype of the SparseTensor objects stored in the SparseTensorsMap.

Optional attributes (see Attrs):

• container: The container name for the SparseTensorsMap read by this op.
• shared_name: The shared name for the SparseTensorsMap read by this op. It should not be blank; rather the shared_name or unique Operation name of the Op that created the original SparseTensorsMap should be used.

Returns:

• Output sparse_indices: 2-D. The indices of the minibatch SparseTensor.
• Output sparse_values: 1-D. The values of the minibatch SparseTensor.
• Output sparse_shape: 1-D. The shape of the minibatch SparseTensor.

### Constructors and Destructors

TakeManySparseFromTensorsMap(const ::tensorflow::Scope & scope, ::tensorflow::Input sparse_handles, DataType dtype)
TakeManySparseFromTensorsMap(const ::tensorflow::Scope & scope, ::tensorflow::Input sparse_handles, DataType dtype, const TakeManySparseFromTensorsMap::Attrs & attrs)

operation
sparse_indices
sparse_shape
sparse_values

### Public static functions

Container(StringPiece x)
SharedName(StringPiece x)

### Structs

tensorflow::ops::TakeManySparseFromTensorsMap::Attrs

Optional attribute setters for TakeManySparseFromTensorsMap.

## Public attributes

### operation

Operation operation
है

### विरल

::tensorflow::Output sparse_indices

### sparse_shape

::tensorflow::Output sparse_shape

### sparse_values

::tensorflow::Output sparse_values

## सार्वजनिक कार्य

### TakeManySparseFromTensorsMap

TakeManySparseFromTensorsMap(
const ::tensorflow::Scope & scope,
::tensorflow::Input sparse_handles,
DataType dtype
)

### TakeManySparseFromTensorsMap

TakeManySparseFromTensorsMap(
const ::tensorflow::Scope & scope,
::tensorflow::Input sparse_handles,
DataType dtype,
const TakeManySparseFromTensorsMap::Attrs & attrs
)

## सार्वजनिक स्थैतिक कार्य

Attrs Container(
StringPiece x
)

### साझानाम

Attrs SharedName(
StringPiece x
)
[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "translationIssue", "label":"Translation issue" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"सैंपल / कोड से जुड़ी समस्या" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]