AI::MXNet::NDArray - Multidimensional tensor object of MXNet.
AI::MXNet::NDArray - Imperative tensor operations on CPU/GPU In AI::MXNet, NDArray is the core data structure for all mathematical computations. An NDArray represents a multidimensional, fixed-size homogenous array. If you're familiar with the PDL, you might notice some similarities. However, NDArray is row-major, unlike the PDL that is column-major. Like the PDL, MXNet's NDArray enables imperative computation. Some NDArray advandages compared to PDL: MXNet's NDArray supports fast execution on a wide range of hardware configurations, including CPU, GPU, and multi-GPU machines. MXNet also scales to distributed systems in the cloud. MXNet's NDArray executes code lazily, allowing it to automatically parallelize multiple operations across the available hardware. An NDArray is a multidimensional array of numbers with the same type. We could represent the coordinates of a point in 3D space, e.g. [2, 1, 6] as a 1D array with shape (3). Similarly, we could represent a 2D array. Below, we present an array with length 2 along the first axis and length 3 along the second axis. [[0, 1, 2] [3, 4, 5]] Note that here the use of 'dimension' is overloaded. When we say a 2D array, we mean an array with 2 axes, not an array with two components. Each NDArray supports some important attributes that you'll often want to query: $ndarray->shape: The dimensions of the array. It is an array ref of integers indicating the length of the array along each axis. For a matrix with $n rows and $m columns, its shape will be [$n, $m]. $ndarray->dtype: A string describing the type of its elements. Dtype (defined in AI::MXNet::Types) is one of (float32 float64 float16 uint8 int8 int32 int64) $ndarray->size: The total number of components in the array - equal to the product of the components of its shape. $ndarray->context: The device on which this array is stored, represented by an object of AI::MXNet::Context class, e.g. cpu() or gpu(1).
Returns a copied PDL array of current array. Returns ------- array : PDL A copy of the array content.
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.
Returns sliced NDArray that shares memory with the current one. Parameters ---------- start : int Starting index of slice. stop : int Finishing index of slice.
Returns a sub NDArray that shares memory with current one. Parameters ---------- idx : int index of the sub array.
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.
Returns the number of dimensions of this array.
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]
Broadcasting the current NDArray into the given shape. Parameters --------- Shape $shape : the shape to broadcast
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.
Get the shape of current NDArray. Returns ------- an array ref representing the shape of current ndarray
Number of elements in the array.
The context of the NDArray. Returns ------- $context : AI::MXNet::Context
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.
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
Makes a copy of the current ndarray in the same context Returns ------ $copy : NDArray
Get transpose of the NDArray. Works only on 2-D matrices.
Returns copied ndarray of current array with the specified type. Parameters ---------- $dtype : Dtype Returns ------- $array : ndarray A copy of the array content.
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.
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
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.
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.
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.
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.
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.
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 $arrays->[0]->context.
Similar function in the MXNet ndarray as numpy.arange See Also https://docs.scipy.org/doc/numpy/reference/generated/numpy.arange.html. Parameters ---------- :$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 :$repeat=1 : number, optional The repeating time of all elements. E.g repeat=3, the element a will be repeated three times --> a, a, a. :$infer_range=0 : Bool When set to 1, infer stop position from start, step, repeat, and output tensor size. :$ctx : Context, optional The context of the NDArray, defaultw to current default context. :$dtype : data type, optional The value type of the NDArray, defaults to float32 Returns ------- $out : NDArray The created NDArray
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
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 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.
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.
Returns a new empty handle. Empty handle can be used to hold result Returns ------- a new empty ndarray handle
Returns a new handle with specified shape and context. Empty handle is only used to hold results Returns ------- a new empty ndarray handle
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
Wait for all async operations to finish in MXNet. This function is used for benchmarks only.
Parameters: ---------- Maybe[Bool] $state= Whether this array's corresponding gradient array (registered via `autograd->mark_variables`) has been updated by `autograd->backward` since last reset. `_fresh_grad` need to be manually set to False after consuming gradient (usually after updating this array).
Returns a new NDArray, detached from the current graph.
Attach a gradient buffer to this NDArray, so that `backward` can compute gradient with respect to it. Parameters ---------- GradReq :$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] :$stype= : str, optional The storage type of the gradient array. Defaults to the same stype of this NDArray.
Returns gradient buffer attached to this NDArray.
Compute the gradients of this NDArray w.r.t variables. Parameters ---------- :$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.
To install AI::MXNet, copy and paste the appropriate command in to your terminal.
cpanm
cpanm AI::MXNet
CPAN shell
perl -MCPAN -e shell install AI::MXNet
For more information on module installation, please visit the detailed CPAN module installation guide.