nums.core.array.blockarray module

class nums.core.array.blockarray.BlockArray(grid, cm, blocks=None)[source]

Bases: nums.core.array.base.BlockArrayBase

astype(dtype)[source]

check_or_convert_other(other, compute_block_shape=False)[source]

copy()[source]

classmethod create(create_op_name, shape, block_shape, dtype, cm)[source]

classmethod empty(shape, block_shape, dtype, cm)[source]

expand_dims(axis)[source]: This function refers to the numpy implementation of expand_dims.

flattened_oids()[source]

classmethod from_blocks(arr, result_shape, cm)[source]

classmethod from_np(arr, block_shape, copy, cm)[source]

classmethod from_oid(oid, shape, dtype, cm)[source]

classmethod from_scalar(val, cm)[source]

is_single_block()[source]

reduce_axis(op_name, axis, keepdims=False)[source]

reshape(*shape, **kwargs)[source]

squeeze()[source]

swapaxes(axis1, axis2)[source]

tensordot(other, axes=2)[source]

static to_block_array(obj, cm, block_shape=None)[source]

to_single_block(replicate=False)[source]

touch()[source]: “Touch” an array. This is an efficient distributed “wait” operation.

transpose(defer=False, redistribute=False)[source]: Transpose this matrix. Only use defer with arithmetic operations. Setting redistribute to True may significantly impact performance. :param defer: When true, the transpose operation will be applied with the next arithmetic operation. :param redistribute: If defer is false, setting this to true will redistribute the data according to the device grid (data placement policy). This parameter has no effect when defer is true. :return: The transposed matrix.

ufunc(op_name)[source]

class nums.core.array.blockarray.Reshape[source]

Bases: object

static compute_shape(shape, input_shape)[source]