`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 see convert_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.

returnn.frontend.const.ones(dims: Sequence[Dim], *, dtype: str | None = None, device: str | None = None, sparse_dim: Dim | None = None, feature_dim: Dim | None = None) → Tensor[source]#: ones. float by default.

returnn.frontend.const.zeros_like(other: Tensor) → Tensor[source]#: zeros like other

returnn.frontend.const.ones_like(other: Tensor) → Tensor[source]#: ones like other