TensorData - Tinker Documentation
tinker.types.TensorData
class tinker.types.TensorData()
Fields:
- dtype ( TensorDtype)
- shape ( Optional[List[int]] ) – Optional.
The shape of the tensor (see PyTorch tensor.shape). The shape of a one-dimensional list of length N is (N,). Can usually be inferred if not provided, and is generally inferred as a 1D tensor.
- sparse_crow_indices ( Optional[List[int]] ) – Optional CSR compressed row pointers. When set, this tensor is sparse CSR:
- data contains only the non-zero values (flattened)
- sparse_crow_indices contains the row pointers (length = nrows + 1)
- sparse_col_indices contains the column indices (length = nnz)
- shape is required and specifies the dense shape
- sparse_col_indices ( _Optional[List[int]_ ) – Optional CSR column indices. Must be set together with sparse_crow_indices.
property data
Flattened tensor data as array of numbers.
Returns: Union[List[int], List[float]]
from_torch_sparse( tensor )
Create a sparse CSR TensorData from a dense 2-D torch tensor.
Automatically detects sparsity and encodes as CSR when it saves space. Falls back to dense if the tensor is 1-D or mostly non-zero.
Parameters:
- tensor ( torch.Tensor )
Returns: TensorData
to_numpy()
Convert TensorData to numpy array.
Returns: npt.NDArray[Any]
to_torch()
Convert TensorData to torch tensor.
Returns: torch.Tensor