# Copyright (c) 2020 Johns Hopkins University (Shinji Watanabe)
#               2020 Northwestern Polytechnical University (Pengcheng Guo)
#               2020 Mobvoi Inc (Binbin Zhang)
#
# 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.
"""Swish() activation function for Conformer."""
import math

import torch


class Swish(torch.nn.Module):
    """Construct an Swish object."""

    def forward(self, x: torch.Tensor) -> torch.Tensor:
        """Return Swish activation function."""
        return x * torch.sigmoid(x)

class New_gelu4npu(torch.nn.Module):
    """Construct an Swish object."""

    def forward(self, x: torch.Tensor) -> torch.Tensor:
        """Return Swish activation function."""
        return x * 0.5 * (1.0 + torch.erf(x / math.sqrt(2.0)))

def new_gelu_func(x: torch.Tensor):
    return x * 0.5 * (1.0 + torch.erf(x / math.sqrt(2.0)))