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Clean unused methods and incorrect arg doc
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src/diart/argdoc.py

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@@ -15,4 +15,4 @@
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OUTPUT = "Directory to store the system's output in RTTM format"
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HF_TOKEN = "Huggingface authentication token for hosted models ('true' | 'false' | <token>). If 'true', it will use the token from huggingface-cli login"
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SAMPLE_RATE = "Sample rate of the audio stream"
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NORMALIZE_EMBEDDING_WEIGHTS = "Rescale embedding weights (min-max normalization) to be in the range [0, 1]. This is useful in some models without weighted statistics pooling that rely on masking, like WeSpeaker or ECAPA-TDNN"
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NORMALIZE_EMBEDDING_WEIGHTS = "Rescale embedding weights (min-max normalization) to be in the range [0, 1]. This is useful in some models without weighted statistics pooling that rely on masking, like Nvidia's NeMo or ECAPA-TDNN"

src/diart/models.py

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@@ -35,14 +35,6 @@ def __init__(self, segmentation_model: nn.Module):
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max_speakers_per_chunk = len(specs.classes)
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self.powerset = Powerset(max_speakers_per_chunk, max_speakers_per_frame)
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@property
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def specifications(self):
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return self.model.specifications
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@property
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def audio(self):
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return self.model.audio
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def forward(self, waveform: torch.Tensor) -> torch.Tensor:
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return self.powerset.to_multilabel(self.model(waveform))
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