dcmaddix opened a new issue #18865: URL: https://github.com/apache/incubator-mxnet/issues/18865
## Description I am trying to fix the random seed across multiple cpus and followed the example to pass `ctx` here : https://mxnet.apache.org/versions/1.6/api/python/docs/api/mxnet/random/index.html and the example code works but it seems order dependent. See the output below. If I call mx.random.seed(128, ctx=mx.cpu(0)) and mx.random.seed(128, ctx=mx.cpu(1)), it does not work. Also is this the only way to loop over all the num_cpus and set each ctx? ## To Reproduce `mx.random.seed(128, ctx=mx.cpu(0)) print(mx.nd.random.normal(shape=(2,2), ctx=mx.cpu(0)).asnumpy()) [[ 0.47400656 0.20251541] [ 1.3648157 -1.4962182 ]] mx.random.seed(128, ctx=mx.cpu(1)) print(mx.nd.random.normal(shape=(2,2), ctx=mx.cpu(1)).asnumpy()) [[ 0.47400656 0.20251541] [ 1.3648157 -1.4962182 ]] ` `mx.random.seed(128, ctx=mx.cpu(0)) mx.random.seed(128, ctx=mx.cpu(1)) print(mx.nd.random.normal(shape=(2,2), ctx=mx.cpu(0)).asnumpy()) [[ 0.47400656 0.20251541] [ 1.3648157 -1.4962182 ]] print(mx.nd.random.normal(shape=(2,2), ctx=mx.cpu(1)).asnumpy()) [[ 1.0954498 -0.20808885] [ 1.590508 -0.41777727]] ` The second arrays do not match and I am not sure why because the seed is set. We also see this when trying to use multi-processing in our algorithms and the numbers are very different even for fixed seed. Above is a simple representative example. ``` ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
