Source code for nvtripy.frontend.ops.masked_fill

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import numbers

from nvtripy import export
from nvtripy.utils import wrappers


[docs] @export.public_api(document_under="operations/functions") @wrappers.interface( dtype_constraints={"input": "T1", "mask": "T2", wrappers.RETURN_VALUE: "T1"}, dtype_variables={ "T1": ["float32", "float16", "bfloat16", "int4", "int8", "int32", "int64", "bool"], "T2": ["bool"], }, ) def masked_fill(input: "nvtripy.Tensor", mask: "nvtripy.Tensor", value: numbers.Number) -> "nvtripy.Tensor": r""" Returns a new tensor filled with ``value`` where ``mask`` is ``True`` and elements from the input tensor otherwise. Args: input: The input tensor. mask: The mask tensor. value: the value to fill with. This will be casted to match the data type of the input tensor. Returns: A new tensor of the same shape as the input tensor. .. code-block:: python :linenos: mask = tp.Tensor([[True, False], [True, True]]) input = tp.zeros([2, 2]) output = tp.masked_fill(input, mask, -1.0) assert np.array_equal(cp.from_dlpack(output).get(), np.array([[-1, 0], [-1, -1]], dtype=np.float32)) """ from nvtripy.frontend.ops.full import full_like from nvtripy.frontend.ops.where import where fill_tensor = full_like(input, value) return where(mask, fill_tensor, input)