Copy the files in the new repo for public release

pocket_tts/modules/resample.py

@@ -0,0 +1,46 @@
+import torch
+from torch import nn
+
+from pocket_tts.modules.conv import StreamingConv1d, StreamingConvTranspose1d
+
+
+class ConvDownsample1d(nn.Module):
+    """
+    Downsampling by some integer amount `stride` using convolutions
+    with a kernel size of twice the stride.
+    """
+
+    def __init__(self, stride: int, dimension: int):
+        super().__init__()
+        self.conv = StreamingConv1d(
+            dimension,
+            dimension,
+            kernel_size=2 * stride,
+            stride=stride,
+            groups=1,
+            bias=False,
+            pad_mode="replicate",
+        )
+
+    def forward(self, x: torch.Tensor, model_state: dict | None):
+        return self.conv(x, model_state)
+
+
+class ConvTrUpsample1d(nn.Module):
+    """
+    Upsample by some integer amount `stride` using transposed convolutions.
+    """
+
+    def __init__(self, stride: int, dimension: int):
+        super().__init__()
+        self.convtr = StreamingConvTranspose1d(
+            dimension,
+            dimension,
+            kernel_size=2 * stride,
+            stride=stride,
+            groups=dimension,
+            bias=False,
+        )
+
+    def forward(self, x: torch.Tensor, model_state: dict | None):
+        return self.convtr(x, model_state)