returnn.frontend.const
¶
Constant / full / fill / zeros / ones, etc
- returnn.frontend.const.full(*, dims: Sequence[Dim], fill_value: int | float | complex | number | ndarray | bool | str | Tensor, dtype: str | None = None, device: str | None = None, sparse_dim: Dim | None = None, feature_dim: Dim | None = None) Tensor [source]¶
full, fill, constant.
https://data-apis.org/array-api/latest/API_specification/generated/array_api.full.html
Also see
convert_to_tensor()
.- Parameters:
dims – shape
fill_value – scalar to fill the tensor
dtype
device
sparse_dim
feature_dim
- returnn.frontend.const.fill(*, dims: Sequence[Dim], fill_value: int | float | complex | number | ndarray | bool | str | Tensor, dtype: str | None = None, device: str | None = None, sparse_dim: Dim | None = None, feature_dim: Dim | None = None) Tensor [source]¶
full, fill, constant.
https://data-apis.org/array-api/latest/API_specification/generated/array_api.full.html
Also see
convert_to_tensor()
.- Parameters:
dims – shape
fill_value – scalar to fill the tensor
dtype
device
sparse_dim
feature_dim
- returnn.frontend.const.constant(fill_value: int | float | complex | number | ndarray | bool | str, *, dims: Sequence[Dim], dtype: str | None = None, device: str | None = None, sparse_dim: Dim | None = None, feature_dim: Dim | None = None) Tensor [source]¶
alias to
full()
, mapping value to fill_value. also seeconvert_to_tensor()
- returnn.frontend.const.zeros(dims: Sequence[Dim], *, dtype: str | None = None, device: str | None = None, sparse_dim: Dim | None = None, feature_dim: Dim | None = None) Tensor [source]¶
zeros. float by default.