Upload feature_extraction_moment.py
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feature_extraction_moment.py
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@@ -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", "
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def __init__(self, **kwargs):
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super().__init__(**kwargs)
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@@ -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, "
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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):
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