# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.# SPDX-License-Identifier: Apache-2.0## Licensed under the Apache License, Version 2.0 (the "License");# you may not use this file except in compliance with the License.# You may obtain a copy of the License at## http://www.apache.org/licenses/LICENSE-2.0## Unless required by applicable law or agreed to in writing, software# distributed under the License is distributed on an "AS IS" BASIS,# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.# See the License for the specific language governing permissions and# limitations under the License.importnumbersfromnvtripyimportexportfromnvtripy.utilsimportwrappers
[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"],},)defmasked_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)) """fromnvtripy.frontend.ops.fullimportfull_likefromnvtripy.frontend.ops.whereimportwherefill_tensor=full_like(input,value)returnwhere(mask,fill_tensor,input)