NdArray

class nnabla._nd_array.NdArray(shape=<???>)

nnabla._nd_array.NdArray is a device-agnostic data container for multi-dimensional arrays (tensors). nnabla._nd_array.NdArray can also implictly handle data transfers across different devices (e.g. CPU to CUDA GPU, CUDA GPU to CPU). See Python API Tutorial for more details.

Parameters:shape (tuple or int) – Shape of tuple.
cast(self, dtype, ctx=None)

In-place cast of data type of the NdArray. It returns the reference values as a numpy.ndarray only if optional parameter ctx is not given, None otherwise.

Parameters:
Returns:

numpy.array if ctx is None, otherwise nothing.

data

Returns the values held by this array as a numpy.ndarray. Note that only the references are returned, and the values are not copied. Therefore, modifying the returned nnabla._nd_array.NdArray will affect the data contained inside the NNabla array. This method can also be called as a setter. Note that this may implicitly invoke a data transfer from device arrays to the CPU.

Parameters:value (numpy.ndarray) –

Returns: numpy.ndarray

dtype

Get dtype.

Returns: numpy.dtype

fill(self, value)

Fill all of the elements with the provided scalar value.

Note: This method is lazily evaluated. It is evaluated during the forward or backward propagation.

Parameters:value (int, float) – The value filled with.
static from_numpy_array(nparr)

Create a NdArray object from Numpy array data.

The data is initialized with the given Numpy array.

Parameters:nparr (ndarray) – Numpy multi-dimensional array.

Returns: ~nnabla._nd_array.NdArray

ndim

Number of dimensions.

Returns: int

shape

Shape of the N-d array.

Returns: tuple of int

size

Total size of the N-d array.

Retuns: int

size_from_axis(self, axis=-1)

Gets the size followed by the provided axis.

Example

a = nnabla.NdArray([10,9])
a.size_from_axis()
# ==> 90
a.size_from_axis(0)
# ==> 90
a.size_from_axis(1)
# ==> 9
a.size_from_axis(2)
# ==> 1
Parameters:axis (int, optional) – -1 as default
Returns:int
strides

Strides.

Returns: tuple of int

zero(self)

Fill all of the elements with 0.

Note: This method is lazily evaluated. It is evaluated during the forward or backward propagation.