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在对 sample_neighbor_layerwise OP测试的时候,发现最终结果和预期存在出入。定位到是 DAG流程中 API_SAMPLE_L,3 中采样邻居的输出节点分布不符合预期。以下是具体结果和复现方法:
base.initialize_graph({ 'mode': 'local', 'data_path': '/tmp/euler', 'sampler_type': 'all', 'data_type': 'all' })
sample_neighbor_layerwise([[1, 2, 3]], ['0', '1'], 10, -1, '')(循环执行10000次)
sample_neighbor_layerwise([[1, 2, 3]], ['0', '1'], 10, -1, '')
输出Log打点方法(euler/common/compact_weighted_collection.h): 在执行过程中,只会涉及到3个点(nodeId 1、nodeId 2、nodeId 3),而每个点在采样邻居时先采样边类型、再采样点。根据它们各自的权重列表不同,分为了6种情形,分别统计每种情形下的随机数情况。
统计结果: 将6种情形下各自的随机数落在每个区间的频率情况作了统计。
问题: 观察统计结果,在6种情形下,随机数的区间频数分布并不均匀,甚至出现了频数为0的区间,似乎违背了ThreadLocalRandom()的产生均匀随机数的初衷。请问该结果是否合理呢?
The text was updated successfully, but these errors were encountered:
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在对 sample_neighbor_layerwise OP测试的时候,发现最终结果和预期存在出入。定位到是 DAG流程中 API_SAMPLE_L,3 中采样邻居的输出节点分布不符合预期。以下是具体结果和复现方法:
base.initialize_graph({ 'mode': 'local', 'data_path': '/tmp/euler', 'sampler_type': 'all', 'data_type': 'all' })
sample_neighbor_layerwise([[1, 2, 3]], ['0', '1'], 10, -1, '')
(循环执行10000次)输出Log打点方法(euler/common/compact_weighted_collection.h):
在执行过程中,只会涉及到3个点(nodeId 1、nodeId 2、nodeId 3),而每个点在采样邻居时先采样边类型、再采样点。根据它们各自的权重列表不同,分为了6种情形,分别统计每种情形下的随机数情况。
统计结果:
将6种情形下各自的随机数落在每个区间的频率情况作了统计。
问题:
观察统计结果,在6种情形下,随机数的区间频数分布并不均匀,甚至出现了频数为0的区间,似乎违背了ThreadLocalRandom()的产生均匀随机数的初衷。请问该结果是否合理呢?
The text was updated successfully, but these errors were encountered: