forked from huawei/mindspore2022
50 lines
2.0 KiB
Python
50 lines
2.0 KiB
Python
# Copyright 2019 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Cache client
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"""
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import copy
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from mindspore._c_dataengine import CacheClient
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class DatasetCache:
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"""
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A client to interface with tensor caching service
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"""
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def __init__(self, session_id=None, size=None, spilling=False):
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if session_id is None:
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raise RuntimeError("Session generation is not implemented yet. session id required")
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self.size = size if size is not None else 0
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if size < 0:
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raise ValueError("cache size should be 0 or positive integer value but got: size={}".format(size))
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if not isinstance(spilling, bool):
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raise ValueError(
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"spilling argument for cache should be a boolean value but got: spilling={}".format(spilling))
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self.session_id = session_id
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self.spilling = spilling
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self.cache_client = CacheClient(session_id, size, spilling)
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def __deepcopy__(self, memodict):
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if id(self) in memodict:
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return memodict[id(self)]
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cls = self.__class__
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new_cache = cls.__new__(cls)
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memodict[id(self)] = new_cache
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new_cache.session_id = copy.deepcopy(self.session_id, memodict)
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new_cache.spilling = copy.deepcopy(self.spilling, memodict)
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new_cache.size = copy.deepcopy(self.size, memodict)
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new_cache.cache_client = self.cache_client
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return new_cache
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