# Copyright 2021 IBM Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import pandas as pd
try:
from torch.utils.data import Dataset
except ModuleNotFoundError as exc:
raise ModuleNotFoundError(
"""Your Python environment does not have torch installed. You can install it with
pip install torch
or with
pip install 'lale[full]'"""
) from exc
[docs]class PandasTorchDataset(Dataset):
"""Pytorch Dataset subclass that takes a pandas DataFrame and an optional label pandas Series."""
def __init__(self, X, y=None):
"""X and y are the dataset and labels respectively.
Parameters
----------
X : pandas DataFrame
Two dimensional dataset of input features.
y : pandas Series
Labels
"""
self.X = X
self.y = y
def __len__(self):
return self.X.shape[0]
def __getitem__(self, idx):
if self.y is not None:
return self.X.iloc[idx], self.y.iloc[idx]
else:
return self.X.iloc[idx]
[docs] def get_data(self):
if self.y is None:
return self.X
else:
return self.X, self.y
[docs]def pandas_collate_fn(batch):
return_X = None
return_y = None
for item in batch:
if isinstance(item, tuple):
if return_X is None:
return_X = [item[0].to_dict()]
else:
return_X.append(item[0].to_dict())
if return_y is None:
return_y = [item[1]]
else:
return_y.append(item[1])
else:
if return_X is None:
return_X = [item.to_dict()]
else:
return_X.append(item.to_dict())
if return_y is not None:
return (pd.DataFrame(return_X), pd.Series(return_y))
else:
return pd.DataFrame(return_X)