This means that the index that will be returned by argmax will be taken from the last axis. 

Your data has some shape `(19,19,5,80)`. This means:

- Axis 0 = 19 elements   
- Axis 1 = 19 elements   
- Axis 2 = 5 elements    
- Axis 3 = 80 elements

Now, negative numbers work exactly like in python lists, in numpy arrays, etc. Negative numbers represent the inverse order:

- Axis -1 = 80 elements    
- Axis -2 = 5 elements   
- Axis -3 = 19 elements    
- Axis -4 = 19 elements

When you pass the `axis` parameter to the `argmax` function, the indices returned will be based on this axis. Your results will lose this specific axes, but keep the others. 

See what shape `argmax` will return for each index:

- `K.argmax(a,axis= 0 or -4)` returns `(19,5,80)` with values from `0 to 18`  
- `K.argmax(a,axis= 1 or -3)` returns `(19,5,80)` with values from `0 to 18`  
- `K.argmax(a,axis= 2 or -2)` returns `(19,19,80)` with values from `0 to 4`  
- `K.argmax(a,axis= 3 or -1)` returns `(19,19,5)` with values from `0 to 79`

I&#39;m new to Material-UI and just started fiddling around with their [App bar with Menu example][1]. When toggling the menu dropdown, it opens up over the Appbar itself, whereas I&#39;d like it to open below the Navbar. 

From the docs, I understand that this can be done with `anchorEl` as explained [here][2]. But when I implement this to my `menu` component nothing happens. What is &quot;the right material-UI way&quot; to take care of this?

    class Header extends React.Component {
      state = {
        auth: true,
        anchorEl: null,
        anchorOriginVertical: &#39;bottom&#39;,
        anchorOriginHorizontal: &#39;right&#39;,
        transformOriginVertical: &#39;top&#39;,
        transformOriginHorizontal: &#39;right&#39;,
        anchorReference: &#39;anchorEl&#39;,
      };
    
      handleChange = (event, checked) =&gt; {
        this.setState({ auth: checked });
      };
    
      handleMenu = event =&gt; {
        this.setState({ anchorEl: event.currentTarget });
      };
    
      handleClose = () =&gt; {
        this.setState({ anchorEl: null });
      };
    
      render() {
        const { classes } = this.props;
        const { auth, anchorEl } = this.state;
        const open = Boolean(anchorEl);
    
        return (
          &lt;div className={classes.root}&gt;
            &lt;AppBar position=&quot;static&quot;&gt;
              &lt;Toolbar&gt;
                &lt;Typography type=&quot;title&quot; color=&quot;inherit&quot; className={classes.flex}&gt;
                  Title
                &lt;/Typography&gt;
                {auth &amp;&amp; (
                  &lt;div&gt;
                    &lt;IconButton
                      aria-owns={open ? &#39;menu-appbar&#39; : null}
                      aria-haspopup=&quot;true&quot;
                      onClick={this.handleMenu}
                      color=&quot;contrast&quot;
                    &gt;
                      &lt;AccountCircle /&gt;
                    &lt;/IconButton&gt;
                    &lt;Menu
                      id=&quot;menu-appbar&quot;
                      anchorEl={anchorEl}
                      open={open}
                      onClose={this.handleClose}
                    &gt;
                      &lt;MenuItem onClick={this.handleClose}&gt;Profile&lt;/MenuItem&gt;
                      &lt;MenuItem onClick={this.handleClose}&gt;My account&lt;/MenuItem&gt;
                    &lt;/Menu&gt;
                  &lt;/div&gt;
                )}
              &lt;/Toolbar&gt;
            &lt;/AppBar&gt;
          &lt;/div&gt;
        );
      }
    }


  [1]: https://material-ui.com/components/app-bar/#app-bar-with-menu
  [2]: https://material-ui.com/components/popover/#anchor-playground

How to make a dropdown menu open below the Appbar using Material-UI?

I have a .NET Core 2.0 app and have a problem with authorization. I want to use custom authorization with special requests. Header and standard default authentication.
First, I add configuration in `Startup.cs`:

    public IServiceProvider ConfigureServices(IServiceCollection services)
    {
        // ...
        services.AddAuthorization(options =&gt;
    	{
    		options.AddPolicy(DefaultAuthorizedPolicy, policy =&gt;
    		{
    			policy.Requirements.Add(new TokenAuthRequirement());
    		});
    	});
        services.AddSingleton&lt;IAuthorizationHandler, AuthTokenPolicy&gt;();
        // ...
    }

`AuthTokenPolicy.cs`:

    public class AuthTokenPolicy : AuthorizationHandler&lt;TokenAuthRequirement&gt;
	{	
		protected override Task HandleRequirementAsync(AuthorizationHandlerContext context, TokenAuthRequirement requirement)
		{
			var filterContext = context.Resource as AuthorizationFilterContext;
			var response = filterContext.HttpContext.Response;
			try
			{
				// some validation code

				var isValidToken = isValidTokenTask.Result;
				if (!isValidToken)
				{
					response.StatusCode = 401;
					return Task.CompletedTask;
				}

				response.StatusCode = 200;
				context.Succeed(requirement);
			}
			catch (Exception)
			{
				return Task.CompletedTask;
			}
			return Task.CompletedTask;
		}
	}
and in `HomeController.cs`:

    [Authorize(Policy = Startup.DefaultAuthorizedPolicy)]
    public async Task&lt;IActionResult&gt; IsVisible()

If I use the wrong request.header in `AuthTokenPolicy` I see it, but in the logs I see this error:

&gt; System.InvalidOperationException: No authenticationScheme was specified, and there was no DefaultChallengeScheme found.\r\n   at Microsoft.AspNetCore.Authentication.AuthenticationService.&lt;ChallengeAsync&gt;d__11.MoveNext()\r\n--- End of stack trace from previous location where exception was thrown ---\r\n   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()\r\n   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)\r\n   at Microsoft.AspNetCore.Mvc.ChallengeResult.&lt;ExecuteResultAsync&gt;d__14.MoveNext()\r\n--- End of stack trace from previous location where exception was thrown ---\r\n   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()\r\n   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)\r\n   at Microsoft.AspNetCore.Mvc.Internal.ResourceInvoker.&lt;InvokeResultAsync&gt;d__19.MoveNext()\r\n--- End of stack trace from previous location where exception was thrown ---\r\n   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()\r\n   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)\r\n   at Microsoft.AspNetCore.Mvc.Internal.ResourceInvoker.&lt;InvokeFilterPipelineAsync&gt;d__17.MoveNext()\r\n--- End of stack trace from previous location where exception was thrown ---\r\n   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()\r\n   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)\r\n   at Microsoft.AspNetCore.Mvc.Internal.ResourceInvoker.&lt;InvokeAsync&gt;d__15.MoveNext()\r\n--- End of stack trace from previous location where exception was thrown ---\r\n   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()\r\n   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)\r\n   at Microsoft.AspNetCore.Builder.RouterMiddleware.&lt;Invoke&gt;d__4.MoveNext()\r\n--- End of stack trace from previous location where exception was thrown ---\r\n   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()\r\n   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)\r\n   at Microsoft.AspNetCore.Diagnostics.StatusCodePagesMiddleware.&lt;Invoke&gt;d__3.MoveNext()\r\n--- End of stack trace from previous location where exception was thrown ---\r\n   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()\r\n   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)\r\n   at React.AspNet.BabelFileMiddleware.&lt;Invoke&gt;d__5.MoveNext()\r\n--- End of stack trace from previous location where exception was thrown ---\r\n   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()\r\n   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)\r\n   at Microsoft.AspNetCore.Authentication.AuthenticationMiddleware.&lt;Invoke&gt;d__6.MoveNext()\r\n--- End of stack trace from previous location where exception was thrown ---\r\n   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()\r\n   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)\r\n   at core.common.Middleware.LoggingMiddleware.&lt;Invoke&gt;d__3.MoveNext() in D:\\Dev\\microservicePDP\\Template\\core.common\\Middleware\\LoggingMiddleware.cs:line 72

After reading [Migrating Authentication and Identity to ASP.NET Core 2.0][1] I&#39;ve added this code in startup.cs


  [1]: https://docs.microsoft.com/en-us/aspnet/core/migration/1x-to-2x/identity-2x
Quotation from the article : 

    services.AddAuthentication(options =&gt; 
    {
        options.DefaultScheme = CookieAuthenticationDefaults.AuthenticationScheme;
        options.DefaultChallengeScheme = OpenIdConnectDefaults.AuthenticationScheme;
    });

&gt; Define a default scheme in 2.0 if one of the following conditions is true:
You want the user to be automatically signed in
You use the [Authorize] attribute or authorization policies without specifying schemes

I added `AuthenticationScheme` and `DefaultChallengeScheme` in `ConfigureServices()`. It didn&#39;t help, the same error here. I&#39;ve tried to use `app.UseAuthentication();` in the `Startup.Configure()` method, with no results.

How can I use a custom authorization without authentication?

No authenticationScheme was specified, and there was no DefaultChallengeScheme found with default authentification and custom authorization

I am a beginner in Keras and need help to understand `keras.argmax(a, axis=-1)` and `keras.max(a, axis=-1)`. What is the meaning of `axis=-1` when `a.shape = (19, 19, 5, 80)`? And also what will be the output of `keras.argmax(a, axis=-1)` and `keras.max(a, axis=-1)`?

What is the meaning of axis=-1 in keras.argmax?

<p>I am a beginner in Keras and need help to understand <code>keras.argmax(a, axis=-1)</code> and <code>keras.max(a, axis=-1)</code>. What is the meaning of <code>axis=-1</code> when <code>a.shape = (19, 19, 5, 80)</code>? And also what will be the output of <code>keras.argmax(a, axis=-1)</code> and <code>keras.max(a, axis=-1)</code>?</p>


I am trying out sample `keras` code from the below `keras` documentation page,
https://keras.io/applications/

What `preprocess_input(x)` function of `keras` module does in the below code? Why do we have to do `expand_dims(x, axis=0)` before that is passed to the `preprocess_input()` method?

    from keras.applications.resnet50 import ResNet50
    from keras.preprocessing import image
    from keras.applications.resnet50 import preprocess_input
    import numpy as np
    
    model = ResNet50(weights=&#39;imagenet&#39;)

    img_path = &#39;elephant.jpg&#39;
    img = image.load_img(img_path, target_size=(224, 224))
    x = image.img_to_array(img)
    x = np.expand_dims(x, axis=0)
    x = preprocess_input(x)

Is there any documentation with a good explanation of these functions?

Thanks!

preprocess_input() method in keras

&lt;!-- What are you trying to accomplish? (Please include sample data.) --&gt;

&lt;!-- Paste the part of the code that shows the problem. (Please indent 4 spaces.) --&gt;

&lt;!-- What do you expect the result to be? --&gt;

&lt;!-- What is the actual result you get? (Please include any errors.) --&gt;
I have seen similar issue but it is not solved either, so I decided to ask.

I am trying to visualize my model in keras using

    from keras.utils import plot_model
    plot_model(model, to_file=&#39;model.png&#39;)

First, it showed error

    ImportError: Failed to import pydot. You must install pydot and graphviz for `pydotprint` to work.

Accordingly, I installed  pydot and graphviz through Anaconda prompt activating my environment using

    conda install -c https://conda.binstar.org/t/TOKEN/j14r pydot
    conda install -c https://conda.binstar.org/t/TOKEN/j14r graphviz

Then, I closed spyder and reopened it. When I run code snippet, it is still showing the same error. 
What am I missing?


ImportError: Failed to import pydot. You must install pydot and graphviz for `pydotprint` to work

I have checked all the solutions, but still, I am facing the same error. My training images shape is `(26721, 32, 32, 1)`, which I believe it is 4 dimension, but I don&#39;t know why error shows it is 5 dimension. 

     model = Sequential()
        
     model.add(Convolution2D(16, 5, 5, border_mode=&#39;same&#39;, input_shape= input_shape ))

So this is how I am defining `model.fit_generator` 

    model.fit_generator(train_dataset, train_labels, nb_epoch=epochs, verbose=1,validation_data=(valid_dataset, valid_labels), nb_val_samples=valid_dataset.shape[0],callbacks=model_callbacks)


Keras ValueError: Input 0 is incompatible with layer conv2d_1: expected ndim=4, found ndim=5

I&#39;m running the LSTM model for the first time.
Here is my model:

    opt = Adam(0.002)
    inp = Input(...)
    print(inp)
    x = Embedding(....)(inp)
    x = LSTM(...)(x)
    x = BatchNormalization()(x)
    pred = Dense(5,activation=&#39;softmax&#39;)(x)
    
    model = Model(inp,pred)
    model.compile(....)
    
    idx = np.random.permutation(X_train.shape[0])
    model.fit(X_train[idx], y_train[idx], nb_epoch=1, batch_size=128, verbose=1)

What is the use of verbose while training the model?

What is the use of verbose in Keras while validating the model?

When I start training a model, there is no model saved previously. I can use `model.compile()` safely. I have now saved the model in a `h5` file for further training using `checkpoint`.
 
Say, I want to train the model further. I am confused at this point: can I use `model.compile()` here? And should it be placed before or after the `model = load_model()` statement? If `model.compile()` reinitializes all the weights and biases, I should place it before `model = load_model()` statement.

After discovering some discussions, it seems to me that `model.compile()` is only needed when I have no model saved previously. Once I have saved the model, there is no need to use `model.compile()`. Is it true or false? And when I want to predict using the trained model, should I use `model.compile()` before predicting? 

Content Type	Original Author	Original Content on Stackoverflow
Question	youngtackpark	View Question on Stackoverflow
Solution 1 - Keras	Daniel Möller	View Answer on Stackoverflow

What is the meaning of axis=-1 in keras.argmax?

Keras Problem Overview

Keras Solutions

Solution 1 - Keras

No authenticationScheme was specified, and there was no DefaultChallengeScheme found with default authentification and custom authorization

How to make a dropdown menu open below the Appbar using Material-UI?

Attributions