deterministic

问题 If I start with the same values, and perform the same primitive operations (addition, multiplication, comparision etc.) on double-precision 64-bit IEEE 754-2008 values, will I get the same result, independent of the underlying machine? More concretely: Since ECMAScript 2015 specifies that a number values is primitive value corresponding to a double-precision 64-bit binary format IEEE 754-2008 value can I conclude that the same operations yield the same same result here, independent of the

问题 I am training a neural network using dropout regularization. I save the weights and biases the network is initialized with, so that I can repeat the experiment when I get good results. However, the use of dropout introduces some randomness in the network: since dropout drops units randomly, each time I rerun the network, different units are being dropped - even though I initialize the network with the exact same weights and biases (if I understand this correctly). Is there a way to make the

问题 I am training a neural network using dropout regularization. I save the weights and biases the network is initialized with, so that I can repeat the experiment when I get good results. However, the use of dropout introduces some randomness in the network: since dropout drops units randomly, each time I rerun the network, different units are being dropped - even though I initialize the network with the exact same weights and biases (if I understand this correctly). Is there a way to make the

来源： https://stackoverflow.com/questions/62538942/generate-the-same-sequence-of-random-numbers-in-c-from-a-given-seed

来源： https://stackoverflow.com/questions/62538942/generate-the-same-sequence-of-random-numbers-in-c-from-a-given-seed

问题 var countryCode = new SqlParameter("@countryCode", SqlDbType.VarBinary); var byteArray = Encoding.UTF8.GetBytes(dto.Country); countryCode.Value = byteArray; var country = new SqlParameter("@country", "country"); country.Value = "country"; var rawUsers = DbContext.Users.FromSqlRaw("Select u.* from AspNetUsers u join AspNetUserClaims uc on u.Id = uc.UserId where uc.ClaimType = @country and uc.ClaimValue = @countryCode", country, countryCode) .ToList(); ERROR: [17:16:22 ERR] Error:The data types

问题 While debugging some C++ code with tons of pointers it would be useful if the memory addresses between runs were the same. Is there any way to make the series of addresses that are returned between consecutive runs of a program that perform the same memory allocations deterministic? Maybe an environment variable or something that can be set for the debug heap? I am aware that there are many good reasons you want randomization for release builds, but determinism is handy for debugging in some

问题 The documentation states: Deterministic mode can have a performance impact, depending on your model. My question is, what is meant by performance here. Processing speed or model quality (i.e. minimal loss)? In other words, when setting manual seeds and making the model perform in a deterministic way, does that cause longer training time until minimal loss is found, or is that minimal loss worse than when the model is non-deterministic? For completeness' sake, I manually make the model

问题 The documentation states: Deterministic mode can have a performance impact, depending on your model. My question is, what is meant by performance here. Processing speed or model quality (i.e. minimal loss)? In other words, when setting manual seeds and making the model perform in a deterministic way, does that cause longer training time until minimal loss is found, or is that minimal loss worse than when the model is non-deterministic? For completeness' sake, I manually make the model

问题 The documentation states: Deterministic mode can have a performance impact, depending on your model. My question is, what is meant by performance here. Processing speed or model quality (i.e. minimal loss)? In other words, when setting manual seeds and making the model perform in a deterministic way, does that cause longer training time until minimal loss is found, or is that minimal loss worse than when the model is non-deterministic? For completeness' sake, I manually make the model