# Copyright (C) 2020-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0

"""FastEsitmatorDataLoader module."""

from .loader import DataLoader


class FastEstimatorDataLoader(DataLoader):
    """Federation Data Loader for FastEstimator."""

    def __init__(self, pipeline, **kwargs):
        """
        Instantiate the data object.

        Args:
            batch_size: Size of batches used for all data loaders
            kwargs: consumes all un-used kwargs

        Returns:
            None
        """
        self.pipeline = pipeline

        self.batch_size = pipeline.batch_size
        self.X_train = None
        self.y_train = None
        self.X_valid = None
        self.y_valid = None

        # Child classes should have init signature:
        # (self, batch_size, **kwargs), should call this __init__ and then
        # define self.X_train, self.y_train, self.X_valid, and self.y_valid

    def get_train_data_size(self):
        """
        Get total number of training samples.

        Returns:
            int: number of training samples
        """
        return len(self.pipeline.data['train'])

    def get_valid_data_size(self):
        """
        Get total number of validation samples.

        Returns:
            int: number of validation samples
        """
        return len(self.pipeline.data['test'])

    def get_feature_shape(self):
        """
        Get feature shape.

        Returns:
            tuple: shape of the input data.
        """
        return self.pipeline.data['train']['x'].shape[1:]

5fcb3ee8328c62d5b683800a18fa5809bb73c85a
<mask token>


class FastEstimatorDataLoader(DataLoader):
    <mask token>

    def __init__(self, pipeline, **kwargs):
        """
        Instantiate the data object.

        Args:
            batch_size: Size of batches used for all data loaders
            kwargs: consumes all un-used kwargs

        Returns:
            None
        """
        self.pipeline = pipeline
        self.batch_size = pipeline.batch_size
        self.X_train = None
        self.y_train = None
        self.X_valid = None
        self.y_valid = None
    <mask token>

    def get_valid_data_size(self):
        """
        Get total number of validation samples.

        Returns:
            int: number of validation samples
        """
        return len(self.pipeline.data['test'])
    <mask token>

<mask token>


class FastEstimatorDataLoader(DataLoader):
    <mask token>

    def __init__(self, pipeline, **kwargs):
        """
        Instantiate the data object.

        Args:
            batch_size: Size of batches used for all data loaders
            kwargs: consumes all un-used kwargs

        Returns:
            None
        """
        self.pipeline = pipeline
        self.batch_size = pipeline.batch_size
        self.X_train = None
        self.y_train = None
        self.X_valid = None
        self.y_valid = None

    def get_train_data_size(self):
        """
        Get total number of training samples.

        Returns:
            int: number of training samples
        """
        return len(self.pipeline.data['train'])

    def get_valid_data_size(self):
        """
        Get total number of validation samples.

        Returns:
            int: number of validation samples
        """
        return len(self.pipeline.data['test'])

    def get_feature_shape(self):
        """
        Get feature shape.

        Returns:
            tuple: shape of the input data.
        """
        return self.pipeline.data['train']['x'].shape[1:]

<mask token>


class FastEstimatorDataLoader(DataLoader):
    """Federation Data Loader for FastEstimator."""

    def __init__(self, pipeline, **kwargs):
        """
        Instantiate the data object.

        Args:
            batch_size: Size of batches used for all data loaders
            kwargs: consumes all un-used kwargs

        Returns:
            None
        """
        self.pipeline = pipeline
        self.batch_size = pipeline.batch_size
        self.X_train = None
        self.y_train = None
        self.X_valid = None
        self.y_valid = None

    def get_train_data_size(self):
        """
        Get total number of training samples.

        Returns:
            int: number of training samples
        """
        return len(self.pipeline.data['train'])

    def get_valid_data_size(self):
        """
        Get total number of validation samples.

        Returns:
            int: number of validation samples
        """
        return len(self.pipeline.data['test'])

    def get_feature_shape(self):
        """
        Get feature shape.

        Returns:
            tuple: shape of the input data.
        """
        return self.pipeline.data['train']['x'].shape[1:]

<mask token>
from .loader import DataLoader


class FastEstimatorDataLoader(DataLoader):
    """Federation Data Loader for FastEstimator."""

    def __init__(self, pipeline, **kwargs):
        """
        Instantiate the data object.

        Args:
            batch_size: Size of batches used for all data loaders
            kwargs: consumes all un-used kwargs

        Returns:
            None
        """
        self.pipeline = pipeline
        self.batch_size = pipeline.batch_size
        self.X_train = None
        self.y_train = None
        self.X_valid = None
        self.y_valid = None

    def get_train_data_size(self):
        """
        Get total number of training samples.

        Returns:
            int: number of training samples
        """
        return len(self.pipeline.data['train'])

    def get_valid_data_size(self):
        """
        Get total number of validation samples.

        Returns:
            int: number of validation samples
        """
        return len(self.pipeline.data['test'])

    def get_feature_shape(self):
        """
        Get feature shape.

        Returns:
            tuple: shape of the input data.
        """
        return self.pipeline.data['train']['x'].shape[1:]

# Copyright (C) 2020-2021 Intel Corporation
# SPDX-License-Identifier: Apache-2.0

"""FastEsitmatorDataLoader module."""

from .loader import DataLoader


class FastEstimatorDataLoader(DataLoader):
    """Federation Data Loader for FastEstimator."""

    def __init__(self, pipeline, **kwargs):
        """
        Instantiate the data object.

        Args:
            batch_size: Size of batches used for all data loaders
            kwargs: consumes all un-used kwargs

        Returns:
            None
        """
        self.pipeline = pipeline

        self.batch_size = pipeline.batch_size
        self.X_train = None
        self.y_train = None
        self.X_valid = None
        self.y_valid = None

        # Child classes should have init signature:
        # (self, batch_size, **kwargs), should call this __init__ and then
        # define self.X_train, self.y_train, self.X_valid, and self.y_valid

    def get_train_data_size(self):
        """
        Get total number of training samples.

        Returns:
            int: number of training samples
        """
        return len(self.pipeline.data['train'])

    def get_valid_data_size(self):
        """
        Get total number of validation samples.

        Returns:
            int: number of validation samples
        """
        return len(self.pipeline.data['test'])

    def get_feature_shape(self):
        """
        Get feature shape.

        Returns:
            tuple: shape of the input data.
        """
        return self.pipeline.data['train']['x'].shape[1:]
