cupy.ndarray

class cupy.ndarray

Multi-dimensional array on a CUDA device.

This class implements a subset of methods of numpy.ndarray. The difference is that this class allocates the array content on the current GPU device.

Parameters:
  • shape (tuple of ints) – Length of axes.
  • dtype – Data type. It must be an argument of numpy.dtype.
  • memptr (cupy.cuda.MemoryPointer) – Pointer to the array content head.
  • order ({'C', 'F'}) – Row-major (C-style) or column-major (Fortran-style) order.
Variables:

Methods

__copy__()
all()
any()
argmax()

Returns the indices of the maximum along a given axis.

See also

cupy.argmax() for full documentation, numpy.ndarray.argmax()

argmin()

Returns the indices of the minimum along a given axis.

See also

cupy.argmin() for full documentation, numpy.ndarray.argmin()

astype()

Casts the array to given data type.

Parameters:
  • dtype – Type specifier.
  • copy (bool) – If it is False and no cast happens, then this method returns the array itself. Otherwise, a copy is returned.
Returns:

If copy is False and no cast is required, then the array itself is returned. Otherwise, it returns a (possibly casted) copy of the array.

Note

This method currently does not support order, casting, and subok arguments.

See also

numpy.ndarray.astype()

choose()
clip()

Returns an array with values limited to [a_min, a_max].

See also

cupy.clip() for full documentation, numpy.ndarray.clip()

copy()

Returns a copy of the array.

Parameters:order ({'C', 'F'}) – Row-major (C-style) or column-major (Fortran-style) order. This function currently does not support order ‘A’ and ‘K’.

See also

cupy.copy() for full documentation, numpy.ndarray.copy()

diagonal()

Returns a view of the specified diagonals.

See also

cupy.diagonal() for full documentation, numpy.ndarray.diagonal()

dot()

Returns the dot product with given array.

See also

cupy.dot() for full documentation, numpy.ndarray.dot()

dump()

Dumps a pickle of the array to a file.

Dumped file can be read back to cupy.ndarray by cupy.load().

dumps()

Dumps a pickle of the array to a string.

fill()

Fills the array with a scalar value.

Parameters:value – A scalar value to fill the array content.

See also

numpy.ndarray.fill()

flatten()

Returns a copy of the array flatten into one dimension.

It currently supports C-order only.

Returns:A copy of the array with one dimension.
Return type:cupy.ndarray

See also

numpy.ndarray.flatten()

get()

Returns a copy of the array on host memory.

Parameters:stream (cupy.cuda.Stream) – CUDA stream object. If it is given, the copy runs asynchronously. Otherwise, the copy is synchronous.
Returns:Copy of the array on host memory.
Return type:numpy.ndarray
max()

Returns the maximum along a given axis.

See also

cupy.amax() for full documentation, numpy.ndarray.max()

mean()

Returns the mean along a given axis.

See also

cupy.mean() for full documentation, numpy.ndarray.mean()

min()

Returns the minimum along a given axis.

See also

cupy.amin() for full documentation, numpy.ndarray.min()

nonzero()

Return the indices of the elements that are non-zero.

Returned Array is containing the indices of the non-zero elements in that dimension.

Returns:Indices of elements that are non-zero.
Return type:tuple of arrays

See also

numpy.nonzero()

prod()

Returns the product along a given axis.

See also

cupy.prod() for full documentation, numpy.ndarray.prod()

ravel()

Returns an array flattened into one dimension.

See also

cupy.ravel() for full documentation, numpy.ndarray.ravel()

reduced_view()

Returns a view of the array with minimum number of dimensions.

Parameters:dtype – Data type specifier. If it is given, then the memory sequence is reinterpreted as the new type.
Returns:A view of the array with reduced dimensions.
Return type:cupy.ndarray
repeat()

Returns an array with repeated arrays along an axis.

See also

cupy.repeat() for full documentation, numpy.ndarray.repeat()

reshape()

Returns an array of a different shape and the same content.

See also

cupy.reshape() for full documentation, numpy.ndarray.reshape()

scatter_add()

Adds given values to specified elements of an array.

See also

cupy.scatter_add() for full documentation.

set()

Copies an array on the host memory to cupy.ndarray.

Parameters:
  • arr (numpy.ndarray) – The source array on the host memory.
  • stream (cupy.cuda.Stream) – CUDA stream object. If it is given, the copy runs asynchronously. Otherwise, the copy is synchronous.
sort()

Sort an array, in-place with a stable sorting algorithm.

Note

For its implementation reason, ndarray.sort currently supports only arrays with their rank of one and their own data, and does not support axis, kind and order parameters that numpy.ndarray.sort does support.

See also

cupy.sort() for full documentation, numpy.ndarray.sort()

squeeze()

Returns a view with size-one axes removed.

See also

cupy.squeeze() for full documentation, numpy.ndarray.squeeze()

std()

Returns the standard deviation along a given axis.

See also

cupy.std() for full documentation, numpy.ndarray.std()

sum()

Returns the sum along a given axis.

See also

cupy.sum() for full documentation, numpy.ndarray.sum()

swapaxes()

Returns a view of the array with two axes swapped.

See also

cupy.swapaxes() for full documentation, numpy.ndarray.swapaxes()

take()

Returns an array of elements at given indices along the axis.

See also

cupy.take() for full documentation, numpy.ndarray.take()

tofile()

Writes the array to a file.

See also

numpy.ndarray.tolist()

tolist()

Converts the array to a (possibly nested) Python list.

Returns:The possibly nested Python list of array elements.
Return type:list

See also

numpy.ndarray.tolist()

trace()

Returns the sum along diagonals of the array.

See also

cupy.trace() for full documentation, numpy.ndarray.trace()

transpose()

Returns a view of the array with axes permuted.

See also

cupy.transpose() for full documentation, numpy.ndarray.reshape()

var()

Returns the variance along a given axis.

See also

cupy.var() for full documentation, numpy.ndarray.var()

view()

Returns a view of the array.

Parameters:dtype – If this is different from the data type of the array, the returned view reinterpret the memory sequence as an array of this type.
Returns:A view of the array. A reference to the original array is stored at the base attribute.
Return type:cupy.ndarray

See also

numpy.ndarray.view()

Attributes

T

Shape-reversed view of the array.

If ndim < 2, then this is just a reference to the array itself.

base
cstruct

C representation of the array.

This property is used for sending an array to CUDA kernels. The type of returned C structure is different for different dtypes and ndims. The definition of C type is written in cupy/carray.cuh.

data
device

CUDA device on which this array resides.

dtype
flags

Object containing memory-layout information.

It only contains c_contiguous, f_contiguous, and owndata attributes. All of these are read-only. Accessing by indexes is also supported.

See also

numpy.ndarray.flags

itemsize

Size of each element in bytes.

See also

numpy.ndarray.itemsize

nbytes

Size of whole elements in bytes.

It does not count skips between elements.

See also

numpy.ndarray.nbytes

ndim

Number of dimensions.

a.ndim is equivalent to len(a.shape).

See also

numpy.ndarray.ndim

shape

Lengths of axes.

Setter of this property involves reshaping without copy. If the array cannot be reshaped without copy, it raises an exception.

size
strides

Strides of axes in bytes.

See also

numpy.ndarray.strides