(inputs, attrs, shape, op_type)
| 404 | |
| 405 | |
| 406 | def get_shape_tensor_inputs(inputs, attrs, shape, op_type): |
| 407 | from paddle.tensor import fill_constant |
| 408 | |
| 409 | def _get_attr_shape(list_shape): |
| 410 | attr_shape = [] |
| 411 | for idx, dim in enumerate(list_shape): |
| 412 | if isinstance(dim, Variable): |
| 413 | attr_shape.append(-1) |
| 414 | else: |
| 415 | attr_shape.append(dim) |
| 416 | return attr_shape |
| 417 | |
| 418 | def _get_shape_tensor(list_shape): |
| 419 | shape_tensor_list = [] |
| 420 | for idx, dim in enumerate(list_shape): |
| 421 | if isinstance(dim, Variable): |
| 422 | dim.stop_gradient = True |
| 423 | check_dtype( |
| 424 | dim.dtype, |
| 425 | 'shape[' + str(idx) + ']', |
| 426 | ['int32', 'int64'], |
| 427 | op_type, |
| 428 | f'(When type of shape in {op_type} is list or tuple.)', |
| 429 | ) |
| 430 | if convert_dtype(dim.dtype) == 'int64': |
| 431 | dim = paddle.cast(x=dim, dtype='int32') |
| 432 | shape_tensor_list.append(dim) |
| 433 | else: |
| 434 | temp_out = fill_constant([], 'int32', dim, force_cpu=True) |
| 435 | shape_tensor_list.append(temp_out) |
| 436 | return shape_tensor_list |
| 437 | |
| 438 | if isinstance(shape, Variable): |
| 439 | shape.stop_gradient = True |
| 440 | check_dtype( |
| 441 | shape.dtype, |
| 442 | 'shape', |
| 443 | ['int32', 'int64'], |
| 444 | 'fill_constant', |
| 445 | f'(When type of shape in {op_type} is Variable.)', |
| 446 | ) |
| 447 | if convert_dtype(shape.dtype) == 'int64': |
| 448 | shape = paddle.cast(shape, 'int32') |
| 449 | inputs["ShapeTensor"] = shape |
| 450 | elif isinstance(shape, (list, tuple)): |
| 451 | attrs["shape"] = _get_attr_shape(shape) |
| 452 | if _contain_var(shape): |
| 453 | inputs['ShapeTensorList'] = _get_shape_tensor(shape) |
| 454 | else: |
| 455 | raise TypeError("Shape only supports Variable, or list, or tuple.") |
| 456 | |
| 457 | |
| 458 | def _convert_to_tensor_list(old_list, dtype="int32"): |
nothing calls this directly
no test coverage detected