def forward_streaming(self, input: torch.Tensor):
        """Forward.

        Args:
            input (torch.Tensor): mixed speech [Batch, frame_length]
        Return:
            B, 1, F
        """

        assert (
            input.dim() == 2
        ), "forward_streaming only support for single-channel input currently."

        windowed = self._apply_window_func(input)

        feature = (
            torch.fft.rfft(windowed) if self.stft.onesided else torch.fft.fft(windowed)
        )
        feature = feature.unsqueeze(1)
        if not (is_torch_1_9_plus and self.use_builtin_complex):
            feature = ComplexTensor(feature.real, feature.imag)

        feature = self.spec_transform_func(feature)

        return feature
Forward.

        Args:
            input (torch.Tensor): mixed speech [Batch, frame_length]
        Return:
            B, 1, F
        
train/target_speaker_extraction/models/av_tfgridnetV3/espnet2/stft_encoder.py