$OpDocBasicBatchToSpace
$OpDocBasicBatchToSpaceND
$OpDocBasicBatchToSpaceND
One-dimensional INT32 or INT64 tensor with shape [M]
whose elements must all be
>= 1
.
Two-dimensional INT32 or INT64 tensor with shape [M, 2]
whose elements must all be
non-negative. crops(i) = [cropStart, cropEnd]
specifies the amount to crop from input
dimension i + 1
, which corresponds to spatial dimension i
. It is required that
cropStart(i) + cropEnd(i) <= blockShape(i) * inputShape(i + 1)
.
Result as a new tensor.
$OpDocBasicBooleanMask
$OpDocBasicBooleanMask
K
-dimensional boolean tensor, where K <= N
and K
must be known statically.
Result as a new tensor.
$OpDocBasicCheckNumerics
$OpDocBasicCheckNumerics
Prefix to print for the error message.
Result as a new tensor which has the same value as the input tensor.
$OpDocBasicDepthToSpace
$OpDocBasicDepthToSpace
Block size which must be greater than 1
.
Format of the input and output data.
Result as a new tensor.
$OpDocBasicExpandDims
$OpDocBasicExpandDims
Dimension index at which to expand the shape of this tensor.
Result as a new tensor.
$OpDocBasicGather
$OpDocBasicGather
Tensor containing indices to gather.
Tensor containing the axis along which to gather.
Result as a new tensor.
$OpDocBasicGatherND
$OpDocBasicGatherND
Tensor containing indices to gather.
Result as a new tensor which contains the values from input
gathered from indices given by indices
,
with shape indices.shape(::-1) + input.shape(indices.shape(-1)::)
.
$OpDocBasicInvertPermutation
$OpDocBasicInvertPermutation
Result as a new tensor.
$OpDocBasicListDiff
$OpDocBasicMatrixTranspose
$OpDocBasicMatrixTranspose
If true
, then the complex conjugate of the transpose result is returned.
Result as a new tensor.
$OpDocBasicOneHot
$OpDocBasicOneHot
Scalar tensor defining the depth of the one-hot dimension.
Scalar tensor defining the value to fill in the output i
th value, when indices[j] = i
.
Defaults to the value 1
with type dataType
.
Scalar tensor defining the value to fill in the output i
th value, when indices[j] != i
.
Defaults to the value 0
with type dataType
.
Axis to fill. Defaults to -1
, representing the last axis.
Data type of the output tensor. If not provided, the function will attempt to assume the data
type of onValue
or offValue
, if one or both are passed in. If none of onValue
, offValue
,
or dataType
are provided, dataType
will default to the FLOAT32
data type.
Result as a new tensor.
$OpDocBasicPad
$OpDocBasicPad
INT32
or INT64
tensor containing the paddings.
Padding mode to use.
Result as a new tensor.
$OpDocBasicPreventGradient
$OpDocBasicPreventGradient
Message to print along with the error.
Result as a new tensor which has the same value as this tensor.
$OpDocBasicReshape
$OpDocBasicReshape
Shape of the output tensor.
Result as a new tensor.
$OpDocBasicReverse
$OpDocBasicReverseSequence
$OpDocBasicReverseSequence
One-dimensional tensor with length input.shape(batchAxis)
and
max(sequenceLengths) <= input.shape(sequenceAxis)
.
Tensor dimension which is partially reversed.
Tensor dimension along which the reversal is performed.
Result as a new tensor which has the same shape as input
.
$OpDocBasicScatterND
$OpDocBasicScatterND
Updates to scatter into the output tensor.
One-dimensional INT32
or INT64
tensor specifying the shape of the output tensor.
Result as a new tensor.
$OpDocBasicSequenceMask
$OpDocBasicSequenceMask
Scalar integer tensor representing the maximum length of each row. Defaults to the maximum value in this tensor.
Data type for the output tensor.
Result as a new tensor.
Creates an op that slices this op according to the provided indexers.
Creates an op that slices this op according to the provided indexers.
More details into how to construct and use indexers are provided in the Indexer documentation.
Sequence of indexers to use.
Created op.
$OpDocBasicSpaceToBatch
$OpDocBasicSpaceToBatchND
$OpDocBasicSpaceToBatchND
One-dimensional INT32 or INT64 tensor with shape [M]
whose elements must all be
>= 1
.
Two-dimensional INT32 or INT64 tensor with shape [M, 2]
whose elements must all be
non-negative. paddings(i) = [padStart, padEnd]
specifies the padding for input dimension
i + 1
, which corresponds to spatial dimension i
. It is required that blockShape(i)
divides inputShape(i + 1) + padStart + padEnd
.
Result as a new tensor.
$OpDocBasicSpaceToDepth
$OpDocBasicSpaceToDepth
Block size which must be greater than 1
.
Format of the input and output data.
Result as a new tensor.
$OpDocBasicSplit
$OpDocBasicSplit
Sizes for the splits to obtain.
Dimension along which to split the input tensor.
Result as a new tensor.
$OpDocBasicSplitEvenly
$OpDocBasicSplitEvenly
Number of splits to obtain along the axis
dimension.
Dimension along which to split the input tensor.
Result as a sequence of new tensors.
$OpDocBasicSqueeze
$OpDocBasicSqueeze
Dimensions of size 1 to squeeze. If this argument is not provided, then all dimensions of size 1 will be squeezed.
Result as a new tensor.
$OpDocBasicStopGradient
$OpDocBasicStopGradient
Result as a new tensor which has the same value as this tensor.
$OpDocBasicTile
$OpDocBasicTile
One-dimensional tensor containing the tiling multiples. Its length must be the same as the rank
of input
.
Result as a new tensor.
$OpDocBasicTranspose
$OpDocBasicTranspose
Permutation of the input tensor dimensions.
If true
, then the complex conjugate of the transpose result is returned.
Result as a new tensor.
$OpDocBasicUnique
$OpDocBasicUniqueWithCounts
$OpDocBasicUnstack
$OpDocBasicUnstack
Number of tensors to unstack. If set to -1
(the default value), its value will be inferred.
Dimension along which to unstack the input tensor.
Result as a new tensor.
$OpDocBasicWhere
$OpDocBasicWhere
Result as a new tensor.