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-rw-r--r--models/auto_encoder.py14
1 files changed, 8 insertions, 6 deletions
diff --git a/models/auto_encoder.py b/models/auto_encoder.py
index 1ef7494..6f388c2 100644
--- a/models/auto_encoder.py
+++ b/models/auto_encoder.py
@@ -1,3 +1,5 @@
+from typing import Tuple
+
import torch
import torch.nn as nn
import torch.nn.functional as F
@@ -11,9 +13,9 @@ class Encoder(nn.Module):
def __init__(
self,
in_channels: int = 3,
- frame_size: tuple[int, int] = (64, 48),
+ frame_size: Tuple[int, int] = (64, 48),
feature_channels: int = 64,
- output_dims: tuple[int, int, int] = (128, 128, 64)
+ output_dims: Tuple[int, int, int] = (128, 128, 64)
):
super().__init__()
self.feature_channels = feature_channels
@@ -74,9 +76,9 @@ class Decoder(nn.Module):
def __init__(
self,
- input_dims: tuple[int, int, int] = (128, 128, 64),
+ input_dims: Tuple[int, int, int] = (128, 128, 64),
feature_channels: int = 64,
- feature_size: tuple[int, int] = (4, 3),
+ feature_size: Tuple[int, int] = (4, 3),
out_channels: int = 3,
):
super().__init__()
@@ -125,9 +127,9 @@ class AutoEncoder(nn.Module):
def __init__(
self,
channels: int = 3,
- frame_size: tuple[int, int] = (64, 48),
+ frame_size: Tuple[int, int] = (64, 48),
feature_channels: int = 64,
- embedding_dims: tuple[int, int, int] = (128, 128, 64)
+ embedding_dims: Tuple[int, int, int] = (128, 128, 64)
):
super().__init__()
self.encoder = Encoder(channels, frame_size,