Example training code over oxford pet dataset #144
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eddyxu
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Rough Benchmarks: Configuration
The Dataset / Scanner does not work well with partition pruning tho. |
changhiskhan
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Sep 7, 2022
| @@ -173,6 +173,15 @@ class PlainDecoderImpl : public Decoder { | |||
| return fmt::format("PlainEncoder({})", type_->ToString()); | |||
| } | |||
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| protected: | |||
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just curious why protected instead of private?
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This one is used by BooleanDecoder as well.
| @@ -78,8 +78,8 @@ def read_metadata(self, check_quality=False) -> pd.DataFrame: | |||
| no_index = pd.Index(names.values).difference(df.filename) | |||
| self._data_quality_issues["missing_index"] = no_index | |||
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| # TODO lance doesn't support writing booleans yet | |||
| with_xmls['segmented'] = with_xmls.segmented.astype(pd.Int8Dtype()) | |||
| with_xmls['segmented'] = with_xmls.segmented.apply( | |||
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with_xmls.segments.astype('boolean') should work (https://pandas.pydata.org/docs/user_guide/boolean.html) no?
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yup I tried, but it does not work. So the segmented is mixed with string and float NaN.
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A Pytorch lighting model to train classification models over Oxford Pet dataset.