paddle_aux.py

# This file is generated by PaConvert ToolKit, please Don't edit it!
import paddle

def split(x, num_or_sections, axis=0):
    if isinstance(num_or_sections, int):
        return paddle.split(x, x.shape[axis]//num_or_sections, axis)
    else:
        return paddle.split(x, num_or_sections, axis)


def repeat(self, *args, **kwargs):
    if args:
        if len(args)==1 and isinstance(args[0], (tuple, list)):
            return paddle.tile(self, args[0])
        else:
            return paddle.tile(self, list(args))
    elif kwargs:
        assert 'repeats' in kwargs
        return paddle.tile(self, repeat_times=kwargs['repeats'])

setattr(paddle.Tensor, 'repeat', repeat)
setattr(paddle.base.framework.Variable, 'repeat', repeat)

def to(self, *args, **kwargs):
    args_list = ["x", "y", "non_blocking", "copy", "memory_format"]
    new_kwargs = {}
    for i, node in enumerate(args):
        k = args_list[i]
        new_kwargs[k] = node
    for node in kwargs:
        v = kwargs[node]
        new_kwargs[node] = v
    kwargs = new_kwargs
    if not kwargs:
        return self
    elif "tensor" in kwargs:
        return paddle.cast(self, "{}.dtype".format(kwargs["tensor"]))
    elif "dtype" in kwargs:
        return paddle.cast(self, "{}".format(kwargs["dtype"]))
    elif "device" in kwargs and "dtype" not in kwargs:
        return self
    elif kwargs:
        if "y" not in kwargs and "x" in kwargs:
            if isinstance(kwargs["x"], paddle.dtype):
                dtype = kwargs["x"]
            elif isinstance(kwargs["x"], str) and kwargs["x"] not in ['cpu', 'cuda', 'ipu', 'xpu']:
                dtype = kwargs["x"]
            elif isinstance(kwargs["x"], paddle.Tensor):
                dtype = kwargs["x"].dtype
            else:
                dtype = self.dtype
            return paddle.cast(self, dtype)

        elif "y" in kwargs and "x" in kwargs:
            if isinstance(kwargs["x"], paddle.dtype):
                dtype = kwargs["x"]
            elif isinstance(kwargs["x"], str):
                if x not in ['cpu', 'cuda', 'ipu', 'xpu']:
                    dtype = kwargs["x"]
                else:
                    dtype = kwargs["y"] if isinstance(kwargs["y"], str) else self.dtype
            else:
                dtype = kwargs["x"]
            return paddle.cast(self, dtype)
        else:
            return self

setattr(paddle.Tensor, 'to', to)

def reshape(self, *args, **kwargs):
    if args:
        if len(args)==1 and isinstance(args[0], (tuple, list)):
            return paddle.reshape(self, args[0])
        else:
            return paddle.reshape(self, list(args))
    elif kwargs:
        assert 'shape' in kwargs
        return paddle.reshape(self, shape=kwargs['shape'])

setattr(paddle.Tensor, 'reshape', reshape)
setattr(paddle.base.framework.Variable, 'reshape', reshape)

def add(self, *args, **kwargs):
    if 'other' in kwargs:
        y = kwargs['other']
    elif 'y' in kwargs:
        y = kwargs['y']
    else:
        y = args[0]

    if 'alpha' in kwargs:
        alpha = kwargs['alpha']
        if alpha != 1:
            if not isinstance(y, paddle.Tensor):
                y = paddle.to_tensor(alpha * y)
            else:
                y = alpha * y
    else:
        if not isinstance(y, paddle.Tensor):
            y = paddle.to_tensor(y)

    return paddle.add(self, y)

setattr(paddle.Tensor, 'add', add)
setattr(paddle.base.framework.Variable, 'add', add)