wehub-resource-sync
60 lines
1.9 KiB
Python
Executable File
60 lines
1.9 KiB
Python
Executable File
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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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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import pgl
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from paddle.io import DataLoader
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__all__ = ["GraphDataLoader"]
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class GraphDataLoader(object):
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def __init__(self, dataset, batch_size=1, shuffle=True, num_workers=1, collate_fn=None, **kwargs):
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self.loader = DataLoader(
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dataset=dataset,
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batch_size=batch_size,
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shuffle=shuffle,
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num_workers=num_workers,
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collate_fn=collate_fn,
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**kwargs,
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)
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def __iter__(self):
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func = self.__callback__()
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for data in self.loader():
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yield func(data)
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def __call__(self):
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return self.__iter__()
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def __callback__(self):
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"""callback function, for reconstruct a dict or graph."""
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def construct(tensors):
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"""tensor list to ([graph_tensor, graph_tensor, ...],
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other tensor)
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"""
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graph_num = 1
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start_len = 0
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data = []
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graph_list = []
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for graph in range(graph_num):
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graph_list.append(pgl.Graph(num_nodes=tensors[start_len], edges=tensors[start_len + 1]))
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start_len += 2
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for i in range(start_len, len(tensors)):
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data.append(tensors[i])
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return graph_list, data
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return construct
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