Name: チャットボットとのインタラクション - ディープラーニング、Python、TensorFlowを使ったチャットボットの作成 p.9 (Interacting with our Chatbot - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.9)
Uploaded: 2021-01-14T12:27:47.000Z
Duration: 20 min 31 s
Description: VoiceTubeの動画で発音を聞きながら英語表現を覚えよう！学べる英語：

Everybody welcome apart nine of our chat bought with Python in Tensorflow tutorial.

What we're really talking about is how you can interact with your chatbots, so there's quite a few ways for us to interact in a few different reasons why we might be interacting with her chatbots.

So let's go ahead and kind of cover all of those ways.

So first of all, the first way you're going, you're active there, chap butter, that you're going to kind of see how your chat but is doing is obviously, I guess, in stats intense or bored or something like that.

But generally, I mean, our goal here is to create a chap, but so we actually care most about the output of our chatbots.

The first way you're seeing output for your check pot is in the console as its training.

Every 1000 steps it's gonna show you like source reference and then an empty sources where it's, you know, the actual input, text references, the training, or that I'm sorry that testing output on and then the nnt is your chatbots actual response.

You really kind of want to see a lot of output.

T really gauge how your chapel it's actually doing, like, one outputs just not enough.

So that's kind of like the first way you're gonna interact with your chap out, in my opinion, or at least see higher chat.

But it's doing so I'm gonna open up the MMT model directory and head into the model directory.

This is where all your checkpoint files go and all that.

So just in case I forget to mention it later like, let's say you want to go into production, Um, and you want to make a move this chap out somewhere else, all you need to run this model live is the N M T code, right?

Wanna bring h prams if you don't have the same exact settings file.

But you could go either way too, actually.

Um, but anyway, you're gonna want Checkpoint, probably H Paramus, and then the three files that correspond to what's which checkpoint file you want.

So in this case is would be Step one thousand's checkpoint s O you want all three, And then you'd also need to modify the checkpoint file to contain the number.

So if we actually wanted 1000 we would need to change this 2000.

Okay, Um and you might as well change all of these.

Basically, normally, this would be like for 96 45 44 so on, all the way down.

But I just threw in for 96 because I was actually kind of happy with model for 96.

So just copy and paste it into all of them.

Anyway, the first form of output is gonna come in these output depth.

So Output Dev is the result of your chap pot.

Every 5000 steps is going to take your test 2013 dot from file.

That's located in in your data directory.

So then perhaps I tried to hit the back, but on my mouse and I'm in paper space right now, so it just actually did my browser.

So your 1st 4 outputs gonna be that output, Dev and test, but output will look at real quick.

But anyways, um, so this is output from our actual model.

So you can see some examples really quickly of how our models doing right now, So that's pretty cool.

And you can either manually compare, you know, the input output.

Or I just wrote a simple kind of pairing script real quick, So I was gonna drag this over.

So the output file output Dev the testing script bubble block.

So give the full paths to wherever these air located.

Then you can run this, and that is gonna output line by line.

And it's all just gonna look like this so you can more clearly see Hey, here's the input.

There's really nothing interesting here, so I'm just don't see a point for me to, like, write this out on tutorial video for you guys.

You can go to the text based version of suit Auriol.

It's all there, so Yeah, so now we're gonna talk about the inference script s I'm gonna close this out, So that's one way.

We're like, Say you like the way that's looking.

You might want to start interacting with your chap on.

And chances are you're gonna come up with some questions that you tend to ask for.

You tend to see Oh, these are problematic questions.

You wanna ask them from time to time to see how you chat bots doing?

Um, if it's the same questions you're gonna ask every chap, though, what you should do is create is just add them to your test your test file.

You'll have needed to have done that before.

You did prepare data on all that, but just keep that in mind, like if if you're gonna keep doing the same stuff, you could just throw it into the test.

In that way, output of every 5000 steps is gonna do that for you.

But chances are you're gonna come up with new stuff or you're going to see new ways that your chat bott is kind of weak, and then each one is gonna be a little different.

Some chatbots liketo uncle over the place.

Some chat bots like toe not finished their thoughts.

Some of my chat bots have liked t give way too many links, tow things that don't really need links, stuff like that.

Anyway, uh, the next way is with inference so inference that pie and things are highly likely to change.

So I'm just gonna throw that caveat out there, right this moment if I go to the get, Huh?

This is kind of the way things are right now.

And in there, I've got a few things that have changed, including a modern inference, a modest bulk inference and then some scoring information.

Now I'm going to go over all these in a moment.

But I just want to say that as time goes on, chances are the scoring ends, the modifications to inference and picking the right one.

And again, I'll explain that a little bit a moment.

That's probably going to be implemented in a much better way by Daniel later.

What's Yeah, this guy, Anyway, I meant to just go to here in the in the main project directory.

So chances are if it's enough, time has gone on.

There's probably a better way than using my coat.

So just I'm just going to say that for now.

Uh, anyway, the default one is just inference that pie that's the one that doesn't do any scoring or anything.

So first, let's go ahead and run that one.

So I'm gonna go ahead and open up a terminal change directory and a desktop and empty chat by And let's see if I can't make this big good, cool.

So I'll run Python train, not pie, And this is gonna open up based on the checkpoint director.

So again, if you wanted to test different checkpoint, you could go into model.

You could just edit this checkpoint filed to contain any checkpoint you want, and that will be the model it loads.

Okay, so just keep that in mind if you want to check a different one, and I highly suggest you do because even though let's say for 96 4 let's say let's say, for 96,000 compared to 4 95,000 might be it of surprisingly different jet, but front.

チャットボットとのインタラクション - ディープラーニング、Python、TensorFlowを使ったチャットボットの作成 p.9 (Interacting with our Chatbot - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.9)

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チャットボットとのインタラクション - ディープラーニング、Python、TensorFlowを使ったチャットボットの作成 p.9 (Interacting with our Chatbot - Creating a Chatbot with Deep Learning, Python, and TensorFlow p.9)

stuff

period

basically

tend