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QUESTION
I am new to NestJS and I am trying to use the HttpModule
which incorporates axios
. The problem I have is that I don't know how to return the data from the response. I am getting some Subscription
object. For now I could only make it console.log like this:
ANSWER
Answered 2021-Jun-15 at 22:04I solve it using it like this:
QUESTION
There is a function given as follows
...ANSWER
Answered 2021-Jun-15 at 21:34Your code doesn’t attempt to not fail if w
isn’t a key in id2word
, so it shouldn’t be too much of a surprise when it does fail. You could try changing
QUESTION
I'm trying to create an app that meets two random users in Django. my question is how to create an object Meeting out of 2 random users from my User model, I want something like a for loop so that every 2 users in my database have a meeting!
ps: I have only one day left to submit my work I will be so thankful if u help me
this is my code so far:
...ANSWER
Answered 2021-Jun-15 at 21:48I can't decipher what you're doing there, but:
QUESTION
Consider this dataframe:
...ANSWER
Answered 2021-Jun-15 at 20:30Try:
QUESTION
I tried 5 different implementations of the Sobel operator in Python, one of which I implemented myself, and the results are radically different.
My questions is similar to this one, but there are still differences I don't understand with the other implementations.
Is there any agreed on definition of the Sobel operator, and is it always synonymous to "image gradient"?
Even the definition of the Sobel kernel is different from source to source, according to Wikipedia it is [[1, 0, -1],[2, 0, -2],[1, 0, -1]]
, but according to other sources it is [[-1, 0, 1],[-2, 0, 2],[-1, 0, 1]]
.
Here is my code where I tried the different techniques:
...ANSWER
Answered 2021-Jun-15 at 14:22according to wikipedia it's [[1, 0, -1],[2, 0, -2],[1, 0, 1]] but according to other sources it's [[-1, 0, 1],[-2, 0, 2],[-1, 0, 1]]
Both are used for detecting vertical edges. Difference here is how these kernels mark "left" and "right" edges.
For simplicity sake lets consider 1D example, and let array be
[0, 0, 255, 255, 255]
then if we calculate using padding then
- kernel
[2, 0, -2]
gives[0, -510, -510, 0, 0]
- kernel
[-2, 0, 2]
gives[0, 510, 510, 0, 0]
As you can see abrupt increase in value was marked with negative values by first kernel and positive values by second. Note that is is relevant only if you need to discriminate left vs right edges, when you want just to find vertical edges, you might use any of these 2 aboves and then get absolute value.
QUESTION
I have updated IntelliJ Idea Ultimate and scala plugin, it's working ok so far with sbt to build some projects.
Using a scala worksheet in REPL Interactive mode, I put in some code from a course lecture,
...ANSWER
Answered 2021-Jun-15 at 18:10Put everything in an object
.
This way the 2 def
s that depends on each other will be available at the same time.
IntelliJ worksheets do not like such definitions as they are "evaluated" one by one. You cannot define 2 depending on one the other at the top-level, they need to be encapsulated.
QUESTION
I saw some solutions that accessed the THREE.BoxGeometry faces like that:
...ANSWER
Answered 2021-Jun-15 at 17:54Try it like so:
QUESTION
WWDC21 introduces Swift 5.5, with async/await. Following the Explore structured concurrency in Swift and Meet async/await in Swift WWDC21 sessions, I'm trying to use the async let function.
Here's my Playground code:
...ANSWER
Answered 2021-Jun-11 at 00:14My advice would be: don't try this in a playground. Playgrounds aren't ready for this stuff yet. Your code compiles and runs fine in a real project. Here's an example:
QUESTION
I am trying to send otp and then validate otp for login. I am able to send otp but it is not validating for some reason.
the code for sending otp is below and it is working fine-
...ANSWER
Answered 2021-Jun-15 at 16:41I don't see where old.otp
is being set in the SendOTP
class, that's probably why it's None. Should be something like this:
QUESTION
I am trying to use my own train step in with Keras by creating a class that inherits from Model. It seems that the training works correctly but the evaluate function always returns 0 on the loss even if I send to it the train data, which have a big loss value during the training. I can't share my code but was able to reproduce using the example form the Keras api in https://keras.io/guides/customizing_what_happens_in_fit/ I changed the Dense layer to have 2 units instead of one, and made its activation to sigmoid.
The code:
...ANSWER
Answered 2021-Jun-12 at 17:27As you manually use the loss and metrics function in the train_step
(not in the .compile
) for the training set, you should also do the same for the validation set or by defining the test_step
in the custom model in order to get the loss score and metrics score. Add the following function to your custom model.
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