stdx | The missing batteries of Rust | DevOps library
kandi X-RAY | stdx Summary
kandi X-RAY | stdx Summary
Rust has a lovely and portable standard library, but it is not featureful enough to write software of any great sophistication. Compared to common platforms including Java, Python, and Go, Rust's standard library is small. In Rust, the libraries we use for even simple tasks live and evolve on crates.io. This affords the Rust community freedom to experiment - discovering the Rustiest solutions to even common problems can take quite some iteration - but it also means that we're in for a slow evolutionary process to converge around the best of those solutions. In the meantime, you just have to know which crates to use for what. stdx contains some of the most important crates in Rust. I mean it. If Rust had a more expansive standard library, many of the stdx crates would be in it, or at least the features they provide. Many of the crates of stdx are maintained by the same authors as the Rust standard library, and they are designed to be idiomatic and interoperable. These are core elements of the crate ecosystem that all Rusticians should be aware of.
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QUESTION
I try to run this Neural Network script (for a regression model) There are two classes defined above. One is Standardizer class and other is Neural Net class. The Standardizer class normalizes all the values and the NeuralNet class builds the neural network that learns the data through feed forward and back propagation.
This function takes the the number of inputs, hidden units, and outputs as the three parameters.
The set_hunit function is used to either update or initiate the weights.It takes the weight as the parameter.
The Pack function packs the multiple weights of each layer into one vector. The unpack function does vice versa.
Forward pass in neural network propagates as shown below:
ππ=β(ππβ π)=ππβ π
Activation function is used to make the network non linear. We may use tanh or RBG or etc.
In the backward pass the function takes the the z values, Target values and the error as input. Based on the delta value, the weights and the bias are updated accoringly. This method returns the weight vector packed together of that particualr layer. Below are the functions that are excecuted during backward pass.
ππβπ+πΌβ1π1πΎππβ€((πβπ)πβ€β(1βπ2))βπ+πΌπ1π1πΎππβ€(πβπ)
The train function takes the feautures and the target as the input. The gradientf unpacks the weights,proceeds with the forward pass by calling forward function. Now error is calculated using results of forward pass. Now back propagation is proceeded by calling backward function with parameters as error, Z, T(Target), _lambda.
The optimtarget function tries to reduce the error by using the object function and updates the weights accordingly.
The use method is applied to the test data after training the model. Testing data is passed as parameter and it stadardizes the data. Then forward is applied on the data which returns the predictions
...This shows module not found error, but I have installed grad module with pip installation
ANSWER
Answered 2021-May-11 at 13:16Try to open command prompt and type pip install grad
or if you using jupyter notebook, make a new code shell and type !pip install grad
before you importing it
Hope that solves your problem
QUESTION
My understanding is the second central moment should give me an object's variance. Which I should be able to use as a measure of distribution of pixels from the center of the object, and so I would think I could find the size of the enclosing rectangle of an object using the second moments. Say in Malab I create an image with a white rectangle of dimensions 100x200 and find the center of mass using the first moments, then I calculate the variance
...ANSWER
Answered 2021-Feb-22 at 16:28After you've computed your normalized second order central moments, you get a matrix like this:
QUESTION
I want to make a class one
that can build up class two
by func1
.
I have two type of class overloading. The primary template class, and the overloading template specialization class.
Primary class one
is fine. But class one
can not implement func1
.
The compiler complains return type 'class two' is incomplete
, aggregate 'two t' has incomplete type and cannot be defined
, and two used in a nested specifier, stdx::shared_future::num_copies_ = 2;
.
What can I do to make a one version of func1
?
Thank you.
ANSWER
Answered 2021-Jan-30 at 07:08To avoid errors related to incomplete types the one::func1
method can be defined after two
. It can be declared like this:
QUESTION
#include
#include
#include
#include
#include
#include
#include
using namespace std;
int main()
{
ofstream myfile;
myfile.open("newtest.csv");
mongocxx::instance instance{};
mongocxx::uri uri("mongodb://localhost:27017");
mongocxx::client client(uri);
mongocxx::database db = client["work"];
mongocxx::collection coll = db["User"];
bsoncxx::stdx::optional maybe_result = coll.find_one({});
}
...ANSWER
Answered 2020-Sep-01 at 19:34Here's one way to do it. There are a few more bsoncxx::type
s than I've cared to decode in this example. If you need them, you'll have to add them. This should be enough output your bson data as csv though.
I've put the support functions in a class to support streaming to any std::ostream
.
bson_csv_adapter.hpp
QUESTION
The following simple code exhibits different behaviour on mongo 4.2.6 and 4.0
...ANSWER
Answered 2020-May-28 at 08:14We've been able to verify that this is a bug in the mongocxx driver. It has been documented here: https://jira.mongodb.org/browse/CXX-2028
QUESTION
I'm using MongoDB C++ driver (version 3.4.0 for reference). I need to get the _id
of a given document. First, I grab the document:
ANSWER
Answered 2020-Jan-28 at 15:58I think you can call to_string()
from the value
field:
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