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| import torch | |
| from deepafx_st.processors.autodiff.compressor import Compressor | |
| from deepafx_st.processors.autodiff.peq import ParametricEQ | |
| from deepafx_st.processors.autodiff.fir import FIRFilter | |
| class AutodiffChannel(torch.nn.Module): | |
| def __init__(self, sample_rate): | |
| super().__init__() | |
| self.peq = ParametricEQ(sample_rate) | |
| self.comp = Compressor(sample_rate) | |
| self.ports = [self.peq.ports, self.comp.ports] | |
| self.num_control_params = ( | |
| self.peq.num_control_params + self.comp.num_control_params | |
| ) | |
| def forward(self, x, p, sample_rate=24000, **kwargs): | |
| # split params between EQ and Comp. | |
| p_peq = p[:, : self.peq.num_control_params] | |
| p_comp = p[:, self.peq.num_control_params :] | |
| y = self.peq(x, p_peq, sample_rate) | |
| y = self.comp(y, p_comp, sample_rate) | |
| return y | |