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https://github.com/YuzuZensai/spleeter.git
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removing useless code
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@@ -98,30 +98,6 @@ class Separator(object):
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prediction.pop('audio_id')
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prediction.pop('audio_id')
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return prediction
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return prediction
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def get_valid_chunk_size(self, sample_rate: int, chunk_max_duration: float) -> int:
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"""
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Given a sample rate, and a maximal duration that a chunk can represent, return the maximum chunk
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size in samples. The chunk size must be a non-zero multiple of T (temporal dimension of the input spectrogram)
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times F (number of frequency bins in the input spectrogram). If no such value exist, we return T*F.
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:param sample_rate: sample rate of the pcm data
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:param chunk_max_duration: maximal duration in seconds of a chunk
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:return: highest non-zero chunk size of duration less than chunk_max_duration or minimal valid chunk size.
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"""
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assert chunk_max_duration > 0
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chunk_size = chunk_max_duration * sample_rate
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min_sample_size = self._params["T"] * self._params["F"]
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if chunk_size < min_sample_size:
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min_duration = min_sample_size / sample_rate
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logger.warning("chunk_duration must be at least {:.2f} seconds. Ignoring parameter".format(min_duration))
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chunk_size = min_sample_size
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return min_sample_size*int(chunk_size/min_sample_size)
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def get_batch_size_for_chunk_size(self, chunk_size):
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d = self._params["T"] * self._params["F"]
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assert chunk_size % d == 0
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return chunk_size//d
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def stft(self, waveform, inverse=False):
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def stft(self, waveform, inverse=False):
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N = self._params["frame_length"]
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N = self._params["frame_length"]
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H = self._params["frame_step"]
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H = self._params["frame_step"]
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