r"""Returns a new tensor having a specified shape and filled with given value. Args: shape(int...): output tensor shape. value(Scalar): fill value. Keyword args: dtype(:attr:`.Tensor.dtype`, optional): output tensor data type. If ``dtype`` is ``None``,
(
shape: Union[int, Tuple[int, ...]],
value: Union[bool, int, float],
*,
dtype=None,
device=None,
)
| 280 | |
| 281 | |
| 282 | def full( |
| 283 | shape: Union[int, Tuple[int, ...]], |
| 284 | value: Union[bool, int, float], |
| 285 | *, |
| 286 | dtype=None, |
| 287 | device=None, |
| 288 | ) -> Tensor: |
| 289 | r"""Returns a new tensor having a specified shape and filled with given value. |
| 290 | |
| 291 | Args: |
| 292 | shape(int...): output tensor shape. |
| 293 | value(Scalar): fill value. |
| 294 | |
| 295 | Keyword args: |
| 296 | dtype(:attr:`.Tensor.dtype`, optional): output tensor data type. |
| 297 | If ``dtype`` is ``None``, the output tensor data type must be inferred from ``value``. |
| 298 | If the value is an ``int``, the output tensor data type must be the default integer data type. |
| 299 | If the value is a ``float``, the output tensor data type must be the default floating-point data type. |
| 300 | If the value is a ``bool``, the output tensor must have boolean data type. |
| 301 | device(:attr:`.Tensor.device`, optional): device on which to place the created tensor. |
| 302 | |
| 303 | Returns: |
| 304 | a tensor where every element is equal to ``value``. |
| 305 | |
| 306 | Examples: |
| 307 | >>> F.full((2, 3), 6) |
| 308 | Tensor([[6 6 6] |
| 309 | [6 6 6]], dtype=int32, device=xpux:0) |
| 310 | """ |
| 311 | |
| 312 | if isinstance(shape, int): |
| 313 | shape = (shape,) |
| 314 | if device is None: |
| 315 | device = get_default_device() |
| 316 | x = Const(value, dtype, device) |
| 317 | if type(shape) in (list, tuple) and len(shape) == 0: |
| 318 | return x |
| 319 | return broadcast_to(x, shape) |
| 320 | |
| 321 | |
| 322 | def ones( |
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