# BSD 3-Clause License
#
# Copyright (c) 2017,
# All rights reserved.
# Copyright 2020 Huawei Technologies Co., Ltd
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
#   list of conditions and the following disclaimer.
#
# * Redistributions in binary form must reproduce the above copyright notice,
#   this list of conditions and the following disclaimer in the documentation
#   and/or other materials provided with the distribution.
#
# * Neither the name of the copyright holder nor the names of its
#   contributors may be used to endorse or promote products derived from
#   this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

import torch

class MultiEpochsDataLoader(torch.utils.data.DataLoader):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self._DataLoader__initialized = False
        self.batch_sampler = _RepeatSampler(self.batch_sampler)
        self._DataLoader__initialized = True
        self.iterator = super().__iter__()
    
    def __len__(self):
        return len(self.batch_sampler.sampler)
    
    def __iter__(self):
        for _ in range(len(self)):
            yield next(self.iterator)

class _RepeatSampler(object):
    """
    Sampler that repeats forever.
    Args:
        sampler (Sampler)
    """

    def __init__(self, sampler):
        self.sampler = sampler
    
    def __iter__(self):
        while True:
            yield from iter(self.sampler)
# BSD 3-Clause License
#
# Copyright (c) 2017,
# All rights reserved.
# Copyright 2020 Huawei Technologies Co., Ltd
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
#   list of conditions and the following disclaimer.
#
# * Redistributions in binary form must reproduce the above copyright notice,
#   this list of conditions and the following disclaimer in the documentation
#   and/or other materials provided with the distribution.
#
# * Neither the name of the copyright holder nor the names of its
#   contributors may be used to endorse or promote products derived from
#   this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

import torch

class MultiEpochsDataLoader(torch.utils.data.DataLoader):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self._DataLoader__initialized = False
        self.batch_sampler = _RepeatSampler(self.batch_sampler)
        self._DataLoader__initialized = True
        self.iterator = super().__iter__()
    
    def __len__(self):
        return len(self.batch_sampler.sampler)
    
    def __iter__(self):
        for _ in range(len(self)):
            yield next(self.iterator)

class _RepeatSampler(object):
    """
    Sampler that repeats forever.
    Args:
        sampler (Sampler)
    """

    def __init__(self, sampler):
        self.sampler = sampler
    
    def __iter__(self):
        while True:
            yield from iter(self.sampler)
# BSD 3-Clause License # # Copyright (c) 2017, # All rights reserved. # Copyright 2020 Huawei Technologies Co., Ltd # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # * Redistributions of source code must retain the above copyright notice, this #   list of conditions and the following disclaimer. # # * Redistributions in binary form must reproduce the above copyright notice, #   this list of conditions and the following disclaimer in the documentation #   and/or other materials provided with the distribution. # # * Neither the name of the copyright holder nor the names of its #   contributors may be used to endorse or promote products derived from #   this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Sampler that repeats forever.     Args:         sampler (Sampler)