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tinker.types.TensorData

class tinker.types.TensorData(StrictBase)

Fields:

  • data – Flattened tensor data as array of numbers.
  • dtype

  • shape – 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 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 CSR column indices. Must be set together with sparse_crow_indices.

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.

Returns: 'TensorData'

to_numpy()

Convert TensorData to numpy array.

Returns: npt.NDArray[Any]

to_torch()

Convert TensorData to torch tensor.

Returns: 'torch.Tensor'