MegEngine/src/opr/impl/tensor_gen.oprdecl

decl_opr(
    'Alloc',
    inputs=['shape'],
    params='DType',
    canonize_input_vars='canonize_shape_input',
    pyname='_alloc'
)

decl_raw_opr(
    'alloc',
    desc='allocate a tensor of given shape and dtype',
    inputs=[
        Doc('shape', 'shape of output value'),
        Doc('dtype', 'data type of output value',
            ':class:`numpy.dtype`-compatible', '"float32"')
    ],
    body=[
        'output=_alloc(shape, dtype=dtype, '
        'config=config, comp_graph=comp_graph)'
    ]
)

decl_opr(
    'Linspace',
    desc='like :func:`numpy.linspace`, generate a sequence of equally-spaced '
    'numbers; dtype is always ``float32``.',
    inputs=[
        Doc('start', 'The starting value of the sequence.'),
        Doc('stop', 'The end value of the sequence, unless endpoint is set to '
            '``False``. In that case, the sequence consists of all but the '
            'last of ``num + 1`` evenly spaced samples, so that stop is '
            'excluded. Note that the step size changes when endpoint is '
            'False.'),
        Doc('num', 'Number of samples to generate.'),
    ],
    params='Linspace'
)

decl_opr(
    'Eye',
    desc='Generate a matrix with ones on the diagonal and zeros elsewhere',
    inputs=[
        Doc('shape', 'Shape of the generated matrix; it must contain one or '
            'two elements')
    ],
    params='Eye',
    canonize_input_vars='canonize_shape_input'
)

# vim: ft=python