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change meta estimation #409

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merged 2 commits into from
Sep 13, 2023
Merged

change meta estimation #409

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33f1372
change meta estimation
PhilippeMoussalli Sep 5, 2023
2f914d5
remove print statements
PhilippeMoussalli Sep 5, 2023
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38 changes: 28 additions & 10 deletions components/load_from_hf_hub/src/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,24 +2,31 @@
import logging
import typing as t

import dask
import dask.dataframe as dd
import pandas as pd
from fondant.component import DaskLoadComponent
from fondant.component_spec import ComponentSpec

logger = logging.getLogger(__name__)

dask.config.set({"dataframe.convert-string": False})


class LoadFromHubComponent(DaskLoadComponent):

def __init__(self, *_,
dataset_name: str,
column_name_mapping: dict,
image_column_names: t.Optional[list],
n_rows_to_load: t.Optional[int],
index_column:t.Optional[str],
def __init__(self,
spec: ComponentSpec,
*_,
dataset_name: str,
column_name_mapping: dict,
image_column_names: t.Optional[list],
n_rows_to_load: t.Optional[int],
index_column: t.Optional[str],
) -> None:
"""
Args:
spec: the component spec
dataset_name: name of the dataset to load.
column_name_mapping: Mapping of the consumed hub dataset to fondant column names
image_column_names: A list containing the original hub image column names. Used to
Expand All @@ -34,6 +41,7 @@ def __init__(self, *_,
self.image_column_names = image_column_names
self.n_rows_to_load = n_rows_to_load
self.index_column = index_column
self.spec = spec

def load(self) -> dd.DataFrame:
# 1) Load data, read as Dask dataframe
Expand Down Expand Up @@ -74,14 +82,24 @@ def _set_unique_index(dataframe: pd.DataFrame, partition_info=None):
"""Function that sets a unique index based on the partition and row number."""
dataframe["id"] = 1
dataframe["id"] = (
str(partition_info["number"])
+ "_"
+ (dataframe.id.cumsum()).astype(str)
str(partition_info["number"])
+ "_"
+ (dataframe.id.cumsum()).astype(str)
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we set the id as str here. Was there no problem with inferring divisions with this ?

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@PhilippeMoussalli PhilippeMoussalli Sep 13, 2023 •
edited
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I think it's mainly an issue if you cast an index that is already an integer to a string (or vice-versa) because you then change the order/sorting from numerical to lexicographical.

image

This shouldn't be the case here since we're creating a string index from the start. Dask will infer the divisions based on the lexicographical order of the index from the start (and then it should be preserved).

#391 (comment)

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makes sense, thx!

)
dataframe.index = dataframe.pop("id")
return dataframe

dask_df = dask_df.map_partitions(_set_unique_index, meta=dask_df.head())
def _get_meta_df() -> pd.DataFrame:
meta_dict = {"id": pd.Series(dtype="object")}
for subset_name, subset in self.spec.produces.items():
for field_name, field in subset.fields.items():
meta_dict[f"{subset_name}_{field_name}"] = pd.Series(
dtype=pd.ArrowDtype(field.type.value),
)
return pd.DataFrame(meta_dict).set_index("id")

meta = _get_meta_df()
dask_df = dask_df.map_partitions(_set_unique_index, meta=meta)
else:
logger.info(f"Setting `{self.index_column}` as index")
dask_df = dask_df.set_index(self.index_column, drop=True)
Expand Down
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