(self,
shape=(),
device=None,
dtype=float32,
data=None,
requires_grad=True,
stores_grad=False,
creator=None,
name=None)
| 88 | tensor_count = 0 |
| 89 | |
| 90 | def __init__(self, |
| 91 | shape=(), |
| 92 | device=None, |
| 93 | dtype=float32, |
| 94 | data=None, |
| 95 | requires_grad=True, |
| 96 | stores_grad=False, |
| 97 | creator=None, |
| 98 | name=None): |
| 99 | if device is None: |
| 100 | device = get_default_device() |
| 101 | if isinstance(data, np.ndarray): |
| 102 | self.data = CTensor(list(data.shape), device, dtype) |
| 103 | copy_from_numpy(self.data, data) |
| 104 | elif isinstance(data, CTensor): |
| 105 | self.data = data |
| 106 | assert data.device().id() == device.id(), 'not the same device' |
| 107 | else: |
| 108 | self.data = CTensor(list(shape), device, dtype) |
| 109 | |
| 110 | self.shape = tuple(self.data.shape()) |
| 111 | self.device = device |
| 112 | self.dtype = self.data.data_type() |
| 113 | self.requires_grad = requires_grad |
| 114 | self.stores_grad = stores_grad |
| 115 | if name is None: |
| 116 | self.name = 'Dummy#{}'.format(Tensor.tensor_count) |
| 117 | Tensor.tensor_count += 1 |
| 118 | else: |
| 119 | self.name = name |
| 120 | if creator is None: |
| 121 | from . import autograd |
| 122 | self.creator = autograd.Dummy(self, name) |
| 123 | else: |
| 124 | self.creator = creator |
| 125 | |
| 126 | def __getitem__(self, keys): |
| 127 | if type(keys) != tuple: |
nothing calls this directly
no test coverage detected