Class and Description 

Accumulation
An accumulation is an op that given:
x > the origin ndarray y > the pairwise ndarray n > the number of times to accumulate
Of note here in the extra arguments. 
BaseAccumulation
Base class for accumulation, initiates the initial entry
with respect to the child class.

BaseOp
Base op.

BroadcastOp
A broad cast op is one where a scalar
or less rank array
is broadcast to fill
a bigg er array.

GridOp
MetaOp is special op, that contains multiple ops

IndexAccumulation
An index accumulation is an operation that returns an index within
a NDArray.
Examples of IndexAccumulation operations include finding the index of the minimim value, index of the maximum value, index of the first element equal to value y, index of the maximum pairwise difference between two NDArrays X and Y etc. Index accumulation is similar to Accumulation in that both are
accumulation/reduction operations, however index accumulation returns
an integer corresponding to an index, rather than a real (or complex)
value.Index accumulation operations generally have 3 inputs: x > the origin ndarray y > the pairwise ndarray (frequently null/not applicable) n > the number of times to accumulate Note that IndexAccumulation op implementations should be stateless (other than the final result and x/y/n arguments) and hence threadsafe, such that they may be parallelized using the update, combineSubResults and set/getFinalResults methods. 
LossFunction
A loss function for computing
the delta between two arrays

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
Op.Type 
ScalarOp
Applies a scalar
along a bigger input array.

TransformOp
Transform operation:
stores the result in an ndarray

Class and Description 

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
Class and Description 

Accumulation
An accumulation is an op that given:
x > the origin ndarray y > the pairwise ndarray n > the number of times to accumulate
Of note here in the extra arguments. 
BroadcastOp
A broad cast op is one where a scalar
or less rank array
is broadcast to fill
a bigg er array.

GridOp
MetaOp is special op, that contains multiple ops

IndexAccumulation
An index accumulation is an operation that returns an index within
a NDArray.
Examples of IndexAccumulation operations include finding the index of the minimim value, index of the maximum value, index of the first element equal to value y, index of the maximum pairwise difference between two NDArrays X and Y etc. Index accumulation is similar to Accumulation in that both are
accumulation/reduction operations, however index accumulation returns
an integer corresponding to an index, rather than a real (or complex)
value.Index accumulation operations generally have 3 inputs: x > the origin ndarray y > the pairwise ndarray (frequently null/not applicable) n > the number of times to accumulate Note that IndexAccumulation op implementations should be stateless (other than the final result and x/y/n arguments) and hence threadsafe, such that they may be parallelized using the update, combineSubResults and set/getFinalResults methods. 
MetaOp
MetaOp is special op, that contains multiple ops

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
RandomOp 
ScalarOp
Applies a scalar
along a bigger input array.

TransformOp
Transform operation:
stores the result in an ndarray

Class and Description 

Accumulation
An accumulation is an op that given:
x > the origin ndarray y > the pairwise ndarray n > the number of times to accumulate
Of note here in the extra arguments. 
BroadcastOp
A broad cast op is one where a scalar
or less rank array
is broadcast to fill
a bigg er array.

IndexAccumulation
An index accumulation is an operation that returns an index within
a NDArray.
Examples of IndexAccumulation operations include finding the index of the minimim value, index of the maximum value, index of the first element equal to value y, index of the maximum pairwise difference between two NDArrays X and Y etc. Index accumulation is similar to Accumulation in that both are
accumulation/reduction operations, however index accumulation returns
an integer corresponding to an index, rather than a real (or complex)
value.Index accumulation operations generally have 3 inputs: x > the origin ndarray y > the pairwise ndarray (frequently null/not applicable) n > the number of times to accumulate Note that IndexAccumulation op implementations should be stateless (other than the final result and x/y/n arguments) and hence threadsafe, such that they may be parallelized using the update, combineSubResults and set/getFinalResults methods. 
LossFunction
A loss function for computing
the delta between two arrays

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
TransformOp
Transform operation:
stores the result in an ndarray

Class and Description 

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
Class and Description 

Accumulation
An accumulation is an op that given:
x > the origin ndarray y > the pairwise ndarray n > the number of times to accumulate
Of note here in the extra arguments. 
BaseAccumulation
Base class for accumulation, initiates the initial entry
with respect to the child class.

BaseOp
Base op.

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
Class and Description 

Accumulation
An accumulation is an op that given:
x > the origin ndarray y > the pairwise ndarray n > the number of times to accumulate
Of note here in the extra arguments. 
BaseAccumulation
Base class for accumulation, initiates the initial entry
with respect to the child class.

BaseOp
Base op.

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
Class and Description 

BaseBroadcastOp 
BaseOp
Base op.

BroadcastOp
A broad cast op is one where a scalar
or less rank array
is broadcast to fill
a bigg er array.

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
Class and Description 

BaseOp
Base op.

GridOp
MetaOp is special op, that contains multiple ops

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
Class and Description 

BaseIndexAccumulation 
BaseOp
Base op.

IndexAccumulation
An index accumulation is an operation that returns an index within
a NDArray.
Examples of IndexAccumulation operations include finding the index of the minimim value, index of the maximum value, index of the first element equal to value y, index of the maximum pairwise difference between two NDArrays X and Y etc. Index accumulation is similar to Accumulation in that both are
accumulation/reduction operations, however index accumulation returns
an integer corresponding to an index, rather than a real (or complex)
value.Index accumulation operations generally have 3 inputs: x > the origin ndarray y > the pairwise ndarray (frequently null/not applicable) n > the number of times to accumulate Note that IndexAccumulation op implementations should be stateless (other than the final result and x/y/n arguments) and hence threadsafe, such that they may be parallelized using the update, combineSubResults and set/getFinalResults methods. 
Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
Class and Description 

Accumulation
An accumulation is an op that given:
x > the origin ndarray y > the pairwise ndarray n > the number of times to accumulate
Of note here in the extra arguments. 
BaseOp
Base op.

GridOp
MetaOp is special op, that contains multiple ops

MetaOp
MetaOp is special op, that contains multiple ops

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
ScalarOp
Applies a scalar
along a bigger input array.

TransformOp
Transform operation:
stores the result in an ndarray

Class and Description 

BaseOp
Base op.

BaseScalarOp
Base scalar operation

BroadcastOp
A broad cast op is one where a scalar
or less rank array
is broadcast to fill
a bigg er array.

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
ScalarOp
Applies a scalar
along a bigger input array.

Class and Description 

BaseOp
Base op.

BaseScalarOp
Base scalar operation

BroadcastOp
A broad cast op is one where a scalar
or less rank array
is broadcast to fill
a bigg er array.

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
ScalarOp
Applies a scalar
along a bigger input array.

Class and Description 

BaseOp
Base op.

BaseTransformOp
A base op for basic getters and setters

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
TransformOp
Transform operation:
stores the result in an ndarray

Class and Description 

BaseOp
Base op.

BaseTransformOp
A base op for basic getters and setters

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
TransformOp
Transform operation:
stores the result in an ndarray

Class and Description 

BaseOp
Base op.

BaseTransformOp
A base op for basic getters and setters

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
TransformOp
Transform operation:
stores the result in an ndarray

Class and Description 

BaseOp
Base op.

BaseTransformOp
A base op for basic getters and setters

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
TransformOp
Transform operation:
stores the result in an ndarray

Class and Description 

BaseOp
Base op.

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
RandomOp 
Class and Description 

BaseOp
Base op.

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
RandomOp 
Class and Description 

Op
An op is defined as follows:
name: name of the operation
x: the origin ndarray
y: the ndarray to parse in parallel
z: the resulting buffer
n: the number of elements to iterate over
where x is the origin ndarray,
y, is a pairwise op
over n elements in the ndarray
stored in result z
This is followed from the standard template for a BLAS operation such that given a linear buffer, a function defines 3 buffers (x,y,z) and the associated strides and offsets (handled by the ndarrays in this case) 
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