chore: remove obsolete code for torch<2

Minimum torch version is 2.1 now.

TTS/tts/layers/glow_tts/glow.py

@@ -1,5 +1,4 @@
 import torch
-from packaging.version import Version
 from torch import nn
 from torch.nn import functional as F
 
@@ -90,10 +89,7 @@ class InvConvNear(nn.Module):
         self.no_jacobian = no_jacobian
         self.weight_inv = None
 
-        if Version(torch.__version__) < Version("1.9"):
-            w_init = torch.qr(torch.FloatTensor(self.num_splits, self.num_splits).normal_())[0]
-        else:
-            w_init = torch.linalg.qr(torch.FloatTensor(self.num_splits, self.num_splits).normal_(), "complete")[0]
+        w_init = torch.linalg.qr(torch.FloatTensor(self.num_splits, self.num_splits).normal_(), "complete")[0]
 
         if torch.det(w_init) < 0:
             w_init[:, 0] = -1 * w_init[:, 0]

TTS/tts/layers/xtts/perceiver_encoder.py

@@ -7,7 +7,6 @@ import torch
 import torch.nn.functional as F
 from einops import rearrange, repeat
 from einops.layers.torch import Rearrange
-from packaging import version
 from torch import einsum, nn
 
 
@@ -44,9 +43,6 @@ class Attend(nn.Module):
         self.register_buffer("mask", None, persistent=False)
 
         self.use_flash = use_flash
-        assert not (
-            use_flash and version.parse(torch.__version__) < version.parse("2.0.0")
-        ), "in order to use flash attention, you must be using pytorch 2.0 or above"
 
         # determine efficient attention configs for cuda and cpu
         self.config = namedtuple("EfficientAttentionConfig", ["enable_flash", "enable_math", "enable_mem_efficient"])