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df2153e
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Upload feature_extraction_moment.py

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  1. feature_extraction_moment.py +2 -2
feature_extraction_moment.py CHANGED
@@ -23,7 +23,7 @@ class MomentFeatureExtractor(FeatureExtractionMixin):
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  # TODO: 本来はMoment側のTokenizerもts_tokenizerとして入れたかったが、モデルに組み込まれてしまっている。
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  # refers: https://github.com/moment-timeseries-foundation-model/moment/blob/088b253a1138ac7e48a7efc9bf902336c9eec8d9/momentfm/models/moment.py#L105
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- model_input_names = ["time_series_values", "input_mask"]
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  def __init__(self, **kwargs):
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  super().__init__(**kwargs)
@@ -50,7 +50,7 @@ class MomentFeatureExtractor(FeatureExtractionMixin):
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  time_series_values = None
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  input_mask = None
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- return BatchFeature(data={"time_series_values": time_series_values, "input_mask": input_mask})
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  def _convert_time_series(self, time_series, return_tensors, torch_dtype, padding, max_length):
 
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  # TODO: 本来はMoment側のTokenizerもts_tokenizerとして入れたかったが、モデルに組み込まれてしまっている。
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  # refers: https://github.com/moment-timeseries-foundation-model/moment/blob/088b253a1138ac7e48a7efc9bf902336c9eec8d9/momentfm/models/moment.py#L105
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+ model_input_names = ["time_series_values", "time_series_input_mask"]
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  def __init__(self, **kwargs):
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  super().__init__(**kwargs)
 
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  time_series_values = None
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  input_mask = None
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+ return BatchFeature(data={"time_series_values": time_series_values, "time_series_input_mask": input_mask})
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  def _convert_time_series(self, time_series, return_tensors, torch_dtype, padding, max_length):