NAME
AI::MXNet::NDArray - Multidimensional tensor object of MXNet.
aspdl
Returns a copied PDL array of current array.
Returns
-------
array : PDL
A copy of the array content.
asmpdl
Returns copied PDL::Matrix objectt of current array.
Requires caller to "use PDL::Matrix" in user space.
Returns
-------
array : PDL::Matrix
A copy of array content.
_slice
Returns sliced NDArray that shares memory with the current one.
Parameters
----------
start : int
Starting index of slice.
stop : int
Finishing index of slice.
_at
Returns a sub NDArray that shares memory with current one.
Parameters
----------
idx : int
index of the sub array.
reshape
Returns a **view** of this array with a new shape without altering any data.
One shape dimension can be -1. In this case, the value is inferred
from the length of the array and remaining dimensions.
Parameters
----------
$new_shape : Shape
new shape of NDArray
:$reverse : bool, default 0
If true then the special values are inferred from right to left.
ndim
Returns the number of dimensions of this array.
moveaxis
Moves the 'source' axis into the 'destination' position
while leaving the other axes in their original order
Parameters
----------
source : int
Original position of the axes to move.
destination : int
Destination position for each of the original axes.
Returns
-------
result :NDArray
Array with moved axes.
Examples
--------
> $X = mx->nd->array([[1, 2, 3],
[4, 5, 6]]);
> print Dumper($X->moveaxis(0, 1)->shape)
> [3, 2]
broadcast_to
Broadcasting the current NDArray into the given shape.
Parameters
---------
Shape $shape : the shape to broadcast
wait_to_read
Block until all pending write operations on the NDArray are finished.
This function will return when all the pending writes to the current
NDArray are finished. There can be pending reads going on when the
function returns.
shape
Get the shape of current NDArray.
Returns
-------
an array ref representing the shape of current ndarray
size
Number of elements in the array.
context
The context of the NDArray.
Returns
-------
$context : AI::MXNet::Context
dtype
The data type of current NDArray.
Returns
-------
a data type string ('float32', 'float64', 'float16', 'uint8', 'int32')
representing the data type of the ndarray.
'float32' is the default dtype for the ndarray class.
copyto
Copy the content of current array to another entity.
When another entity is the NDArray, the content is copied over.
When another entity is AI::MXNet::Context, a new NDArray in the context
will be created.
Parameters
----------
other : NDArray or Context
Target NDArray or context we want to copy data to.
Returns
-------
dst : NDArray
copy
Makes a copy of the current ndarray in the same context
Returns
------
$copy : NDArray
T
Get transpose of the NDArray.
Works only on 2-D matrices.
astype
Returns copied ndarray of current array with the specified type.
Parameters
----------
$dtype : Dtype
Returns
-------
$array : ndarray
A copy of the array content.
as_in_context
Returns an NDArray in the target context.
If the array is already in that context, self is returned. Otherwise, a copy is
made.
Parameters
----------
context : AI::MXNet::Context
The target context we want the return value to live in.
Returns
-------
A copy or self as an NDArray in the target context.
onehot_encode
One hot encoding indices into matrix out.
Parameters
----------
indices: NDArray
An NDArray containing indices of the categorical features.
out: NDArray
The result of the encoding.
Returns
-------
$out: NDArray
_ufunc_helper(lhs, rhs, fn_array, lfn_scalar, rfn_scalar):
Helper function for element-wise operation
The function will perform numpy-like broadcasting if needed and call different functions
Parameters
----------
lhs : NDArray or numeric value
left hand side operand
rhs : NDArray or numeric value
right hand side operand
fn_array : function
function to be called if both lhs and rhs are of NDArray type
lfn_scalar : function
function to be called if lhs is NDArray while rhs is numeric value
rfn_scalar : function
function to be called if lhs is numeric value while rhs is NDArray;
if none is provided, then the function is commutative, so rfn_scalar is equal to lfn_scalar
Returns
-------
out: NDArray
result array
empty
Creates an empty uninitialized NDArray, with the specified shape.
Parameters
----------
$shape : Shape
shape of the NDArray.
:$ctx : AI::MXNet::Context, optional
The context of the NDArray, defaults to current default context.
:$dtype : Dtype, optional
The dtype of the NDArray, defaults to 'float32'.
:$stype: Stype, optional
The stype of the NDArray, defaults to 'default'
Returns
-------
out: Array
The created NDArray.
zeros
Creates a new NDArray filled with 0, with specified shape.
Parameters
----------
$shape : Shape
shape of the NDArray.
:$ctx : AI::MXNet::Context, optional
The context of the NDArray, defaults to current default context.
:$dtype : Dtype, optional
The dtype of the NDArray, defaults to 'float32'.
:$stype: Stype, optional
The stype of the NDArray, defaults to 'default'
Returns
-------
out: Array
The created NDArray.
ones
Creates a new NDArray filled with 1, with specified shape.
Parameters
----------
$shape : Shape
shape of the NDArray.
:$ctx : AI::MXNet::Context, optional
The context of the NDArray, defaults to current default context.
:$dtype : Dtype, optional
The dtype of the NDArray, defaults to 'float32'.
Returns
-------
out: Array
The created NDArray.
full
Creates a new NDArray filled with given value, with specified shape.
Parameters
----------
$shape : Shape
shape of the NDArray.
val : float or int
The value to be filled with.
:$ctx : AI::MXNet::Context, optional
The context of the NDArray, defaults to current default context.
:$dtype : Dtype, optional
The dtype of the NDArray, defaults to 'float32'.
Returns
-------
out: Array
The created NDArray.
array
Creates a new NDArray that is a copy of the source_array.
Parameters
----------
$source_array : AI::MXNet::NDArray PDL, PDL::Matrix, Array ref in PDL::pdl format
Source data to create NDArray from.
:$ctx : AI::MXNet::Context, optional
The context of the NDArray, defaults to current default context.
:$dtype : Dtype, optional
The dtype of the NDArray, defaults to 'float32'.
Returns
-------
out: Array
The created NDArray.
concatenate
Concatenates an array ref of NDArrays along the first dimension.
Parameters
----------
$arrays : array ref of NDArrays
Arrays to be concatenate. They must have identical shape except
for the first dimension. They also must have the same data type.
:$axis=0 : int
The axis along which to concatenate.
:$always_copy=1 : bool
Default is 1. When not 1, if the arrays only contain one
NDArray, that element will be returned directly, avoid copying.
Returns
-------
An NDArray in the same context as $arrays->[0]->context.
arange
Similar function in the MXNet ndarray as numpy.arange
See Also https://docs.scipy.org/doc/numpy/reference/generated/numpy.arange.html.
Parameters
----------
:$start=0 : number, optional
Start of interval. The interval includes this value. The default start value is 0.
:$stop= : number, optional
End of interval. The interval does not include this value.
:$step=1 : number, optional
Spacing between the values
:$repeat=1 : number, optional
The repeating time of all elements.
E.g repeat=3, the element a will be repeated three times --> a, a, a.
:$ctx : Context, optional
The context of the NDArray, defaultw to current default context.
:$dtype : data type, optional
The value type of the NDArray, defaults to float32
Returns
-------
$out : NDArray
The created NDArray
load
Loads ndarrays from a binary file.
You can also use Storable to do the job if you only work with Perl.
The advantage of load/save is the file is language agnostic.
This means the file saved using save can be loaded by other language binding of mxnet.
You also get the benefit being able to directly load/save from cloud storage(S3, HDFS)
Parameters
----------
fname : str
The name of the file.Can be S3 or HDFS address (remember built with S3 support).
Example of fname:
- `s3://my-bucket/path/my-s3-ndarray`
- `hdfs://my-bucket/path/my-hdfs-ndarray`
- `/path-to/my-local-ndarray`
Returns
-------
$out : array ref of NDArrays or hash ref with NDArrays
load_frombuffer
Loads an array dictionary or list from a buffer
See more details in 'save'.
Parameters
----------
buf : str
Binary string containing contents of a file.
Returns
-------
array ref of AI::MXNet::NDArray, AI::MXNet::NDArrayRowSparseNDArray or AI::MXNet::NDArray::CSR, or
hash ref of AI::MXNet::NDArray, AI::MXNet::NDArrayRowSparseNDArray or AI::MXNet::NDArray::CSR
Loaded data.
save
Save array ref of NDArray or hash of str->NDArray to a binary file.
You can also use Storable to do the job if you only work with Perl.
The advantage of load/save is the file is language agnostic.
This means the file saved using save can be loaded by other language binding of mxnet.
You also get the benefit being able to directly load/save from cloud storage(S3, HDFS)
Parameters
----------
fname : str
The name of the file.Can be S3 or HDFS address (remember built with S3 support).
Example of fname:
- `s3://my-bucket/path/my-s3-ndarray`
- `hdfs://my-bucket/path/my-hdfs-ndarray`
- `/path-to/my-local-ndarray`
$data : array ref of NDArrays or hash ref of NDArrays
The data to be saved.
imdecode
Decode an image from string. Requires OpenCV to work.
Parameters
----------
$str_img : str
binary image data
:$clip_rect : iterable of 4 int
clip decoded image to rectangle (x0, y0, x1, y1)
:$out= : Maybe[NDArray]
output buffer. can be 3 dimensional (c, h, w) or 4 dimensional (n, c, h, w)
:$index : int
output decoded image to i-th slice of 4 dimensional buffer
:$channels=3 : int
number of channels to output. Decode to grey scale when channels = 1.
$mean= : Maybe[NDArray]
subtract mean from decode image before outputting.
_new_empty_handle
Returns a new empty handle.
Empty handle can be used to hold result
Returns
-------
a new empty ndarray handle
_new_alloc_handle
Returns a new handle with specified shape and context.
Empty handle is only used to hold results
Returns
-------
a new empty ndarray handle
tostype
Return a copy of the array with chosen storage type.
Returns
-------
AI::MXNet::NDArray or AI::MXNet::NDArray::CSR or AI::MXNet::NDArray::RowSparse
A copy of the array with the chosen storage stype
waitall
Wait for all async operations to finish in MXNet.
This function is used for benchmarks only.
_fresh_grad
Parameters:
----------
Maybe[Bool] $state=
Whether this array's corresponding gradient array
(registered via `autograd->mark_variables`) has been
updated by `autograd->backward` since last reset.
`_fresh_grad` need to be manually set to False
after consuming gradient (usually after updating this
array).
detach
Returns a new NDArray, detached from the current graph.
attach_grad
Attach a gradient buffer to this NDArray, so that `backward`
can compute gradient with respect to it.
Parameters
----------
GradReq :$grad_req='write' : {'write', 'add', 'null'}
How gradient will be accumulated.
- 'write': gradient will be overwritten on every backward.
- 'add': gradient will be added to existing value on every backward.
- 'null': do not compute gradient for this NDArray.
Maybe[Str] :$stype= : str, optional
The storage type of the gradient array. Defaults to the same stype of this NDArray.
grad
Returns gradient buffer attached to this NDArray.
backward
Compute the gradients of this NDArray w.r.t variables.
Parameters
----------
:$out_grad= : NDArray, optional
Gradient with respect to head.
:$retain_graph=0 : bool, optional
Whether to retain the computaion graph for another backward
pass on the same graph. By default the computaion history
is cleared.
:$train_mode=1 : bool, optional
Whether to compute gradient for training or inference.