(
self, param_id, param, key=None, shape=None, length=None,
grad=None, blob_copy=None)
| 17 | class ParameterInfo: |
| 18 | |
| 19 | def __init__( |
| 20 | self, param_id, param, key=None, shape=None, length=None, |
| 21 | grad=None, blob_copy=None): |
| 22 | assert isinstance(param, core.BlobReference) |
| 23 | self.param_id = param_id |
| 24 | self.name = str(param) |
| 25 | self.blob = param |
| 26 | self.key = key |
| 27 | self.shape = shape |
| 28 | self.size = None if shape is None else np.prod(shape) |
| 29 | self.length = max(1, length if length is not None else 1) |
| 30 | self.grad = grad |
| 31 | self._cloned_init_net = None |
| 32 | # Optionally store equivalent copies of the blob |
| 33 | # in different precisions (i.e. half and float copies) |
| 34 | # stored as a dict of TensorProto.DataType -> BlobReference |
| 35 | self.blob_copy = blob_copy |
| 36 | # each param_info can have its own optimizer. It can be set within |
| 37 | # OptimizerContext (caffe2/python/optimizer.py) |
| 38 | self._optimizer = None |
| 39 | |
| 40 | @property |
| 41 | def parameter(self): |
nothing calls this directly
no test coverage detected