You can pass in `dtype` and `device` keyword arguments to control the data type and device of the tensor. Additionally, all other keyword arguments are passed to the constructor of the tensor. ```pyth
(*shape, **kwargs)
| 737 | |
| 738 | @staticmethod |
| 739 | def glorot_uniform(*shape, **kwargs) -> Tensor: |
| 740 | """ |
| 741 | <https://www.tensorflow.org/api_docs/python/tf/keras/initializers/GlorotUniform> |
| 742 | |
| 743 | You can pass in `dtype` and `device` keyword arguments to control the data type and device of the tensor. |
| 744 | Additionally, all other keyword arguments are passed to the constructor of the tensor. |
| 745 | |
| 746 | ```python exec="true" source="above" session="tensor" result="python" |
| 747 | Tensor.manual_seed(42) |
| 748 | print(Tensor.glorot_uniform(2, 3).numpy()) |
| 749 | ``` |
| 750 | """ |
| 751 | bound = (6 / (argfix(*shape)[0]+prod(argfix(*shape)[1:]))) ** 0.5 |
| 752 | return Tensor.uniform(*shape, low=-bound, high=bound, **kwargs) |
| 753 | |
| 754 | @staticmethod |
| 755 | def kaiming_uniform(*shape, a:float = 0.01, **kwargs) -> Tensor: |