WIP - first working version with UI, hooray!

- added logging in UI
- added switcher for models, batch size etc.
- added device configuration dataclass
- minor improvements in audio transcription

transcription/device_configuration.py

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+from dataclasses import dataclass
+import torch
+
+@dataclass
+class DeviceConfiguration:
+    """
+    Configurations for Whisper model on different devices.
+
+    Attributes:
+        device (str): Type of device. Possible options: "cuda", "cpu", "mps".
+        
+        model_name (str): Whisper models. Possible options:
+            - "openai/whisper-tiny"
+            - "openai/whisper-small"
+            - "openai/whisper-medium"
+            - "openai/whisper-large"
+            - "openai/whisper-large-v2"
+        
+        batch_size (int): Chunks in one batch. Selected for VRAM.
+        
+        chunk_length_s (int): Length of one audio chunk in seconds. Smaller -> less VRAM.
+        
+        data_type (str): custom data type of model. Variants:
+            - torch.float16 - for GPUs
+            - torch.float32 - for CPU / weak GPU
+            - torch.bfloat16 - for GPUs which has BF16 support
+    """
+    device: str = "cuda"
+    model_name: str = "openai/whisper-large-v2"
+    batch_size: int = 16
+    chunk_length_s: int = 30
+    data_type: str = "torch.float16"
+    
+    _dtype_map = {
+        "torch.float16": torch.float16,
+        "torch.float32": torch.float32,
+        "torch.bfloat16": torch.bfloat16
+    }
+    
+    torch_dtype: torch.dtype = None
+    
+    def __post_init__(self):
+        self.torch_dtype = self._dtype_map[self.data_type]