I am trying to add two layers each of size (None, 24, 24, 8) but getting the class error as below:
Code:
x = add([layers[i-1],layers[i-9]])
or
x = Add()([layers[i-1],layers[i-9]])
Error:
/keras_222/local/lib/python2.7/site-packages/keras/engine/base_layer.py", line 285, in assert_input_compatibility
str(inputs) + '. All inputs to the layer '
ValueError: Layer add_1 was called with an input that isn't a symbolic tensor. **Received type: <class** 'keras.layers.normalization.BatchNormalization'>. Full input: [<keras.layers.normalization.BatchNormalization object at 0x7f04e4085850>, <keras.layers.normalization.BatchNormalization object at 0x7f050013cd10>]. All inputs to the **layer should be tensors**.
Please advise how to move forward. I also tried putting axis=1 or axis=-1 but it didn't work.
x = Add()([layers[i-1],layers[i-9]],axis=1)
or
x = Add()([layers[i-1],layers[i-9]], axis=-1)
The problem is that you are passing layers instead of tensors to your Add() layer. I suppose you have an Input() layer somewhere in your code. You need to pass this input through your other layers. Your code should instead look something like this:
input = Input(shape)
# pass input through other intermediate layers first if needed
output_1 = layers[i-1](input)
output_2 = layers[i-9](input)
x = Add()([output_1, output_2])
Related
I'm very new to caret package and nnet in R. I've done some projects related to ANN with Matlab before, but now I need to work with R and I need some basic help.
My input dataset has 1000 observations (in rows) and 23 variables (in columns). My output has 1000 observations and 12 variables.
Here are some sample data that represent my dataset and might help to understand my problem better:
input = as.data.frame(matrix(sample(1 : 20, 100, replace = TRUE), ncol = 10))
colnames(input) = paste ( "X" , 1:10, sep = "") #10 observations and 10 variables
output = as.data.frame(matrix(sample(1 : 20, 70, replace = TRUE), ncol = 7))
colnames(output) = paste ( "Y" , 1:7, sep = "") #10 observations and 7 variables
#nnet with caret:
net1 = train(output ~., data = input, method= "nnet", maxit = 1000)
When I run the code, I get this error:
error: invalid type (list) for variable 'output'.
I think I have to add all output variables separately (which is very annoying, especially with a lot of variables), like this:
train(output$Y1 + output$Y2 + output$Y3 + output$Y4 + output$Y5 +
output$Y6 + output$Y7 ~., data = input, method= "nnet", maxit = 1000)
This time it runs but I get this error:
Error in [.data.frame(data, , all.vars(Terms), drop = FALSE) :
undefined columns selected
I try to use neuralnet package, with the code below it works perfectly but I still have to add output variables separately :(
net1 = neuralnet(output$Y1 + output$Y2 + output$Y3 + output$Y4 +
output$Y5 + output$Y6 + output$Y7 ~., data = input, hidden=c(2,10))
p.s. since these sample data are created randomly, the neuralnet cannot converge, but in my real data it works well (in comparison to Matlab ANN)
Now, if you could help me with a way to put output variables automatically (not manually), it solves my problem (although with neuralnet not caret).
use the str() function and ascertain that its a data frame looks like you are inputting a list to the train function. This may be because of a transformation you are doing before to output.
str(output)
Without a full script of earlier steps its difficult to understand what is going on.
After trying different things and searches, I finally found a solution:
First, we must use as.formula to show the relation between our input and output. With the code below we don't need to add all the variables separately:
names1 <- colnames(output) #the name of our variables in the output
names2 = colnames(input) #the name of our variables in the input
a <- as.formula(paste(paste(names1,collapse='+', sep = ""),' ~ '
,paste(names2,collapse='+', sep = "")))
then we have to combine our input and output in a single data frame:
all_data = cbind(output, input)
then, use neuralnet like this:
net1 = neuralnet(formula = a, data = all_data, hidden=c(2,10))
plot(net1)
This is also work with the caret package:
net1 = train(a, data = all_data, method= "nnet", maxit = 1000)
but it seems neuralnet works faster (at least in my case).
I hope this helps someone else.
If I wanted to create an array of specified class I would use an approach like this. So creating an array of int looks like this:
Aint = int16.empty(5,0);
Aint(1) = 3;
And it works fine. Now I want to create an array of tf class objects. My approach was similar:
L = tf.empty(5, 0);
s = tf('s');
L(1) = s;
This gives me an error:
Error using InputOutputModel/subsasgn (line 57)
Not enough input arguments.
Error in tf_array (line 6)
L(1) = s;
I also made sure to display class(s) and it correctly says it's tf. What do I do wrong here?
As usual, the MATLAB documentation has an example for how to do this sort of thing:
sys = tf(zeros(1,1,3));
s = tf('s');
for k = 1:3
sys(:,:,k) = k/(s^2+s+k);
end
So, the problem likely is that the indexing L(1) is wrong, it needs to be L(:,:,1).
Do note that tf.empty(5, 0) is instructing to create a 5x0 array (i.e. an empty array). There is no point to this. You might as well just skip this instruction. Because when you later do L(:,:,1), you'll be increasing the array size any way (it starts with 0 elements, you want to assign a new element, it needs to reallocate the array). You should always strive to create the arrays of the right size from the start.
I wrote a function, wins_plot, to read the scoreboard from a file and store the player's name, number of plays, wins, & losses. I stored all those using struct. I loop over the file, store each line in line, textscan for everything I need from line, and then iterate i (initially == 1) as I go to expand my array of structures. A snippet from the code to represent what I am saying:
c = textscan(line, '%s %s %d %d %d');
player(i).firstName = c{1};
player(i).lastName = c{2};
player(i).plays = c{3};
player(i).wins = c{4};
player(i).losses = c{5};
After all the file has been scanned and stored, I then write this code to extract the number of wins of each player and store it in X and then finally use the pie function to represent the values in X
for n=1:(i-1)
X(n) = player(n).wins;
end
pie(X);
I get a wall of error after:
Undefined function 'cos' for input arguments of type 'int32'.
Error in pol2cart (line 22) x = r.*cos(th);
Error in pie (line 99)
[xtext,ytext] = pol2cart(theta0 + x(i)*pi,1.2);
Error in wins_plot (line 30) pie(X);
I have no clue what might be wrong. Any help would be greatly appreciated. Please keep in mind that I only just started learning MATLAB today so my knowledge of it is very limited (and I have R2013a). Thank you in advance!
The numbers got read as int32, but when you call pie, it requires them to be double to do the computation. So, when you call pie, try casting the values to double. Try this,
pie(double(X));
I would like to have short-hand form about many parameters which I just need to keep fixed in Matlab 2016a because I need them in many places, causing many errors in managing them separately.
Code where the signal is 15x60x3 in dimensions
signal( 1:1 + windowWidth/4, 1:1 + windowWidth,: );
Its pseudocode
videoParams = 1:1 + windowWidth/4, 1:1 + windowWidth,: ;
signal( videoParams );
where you cannot write videoParams as string but should I think write ":" as string and everything else as integers.
There should be some way to do the pseudocode.
Output of 1:size(signal,3) is 3 so it gives 1:3. I do not get it how this would replace : in the pseudocode.
Extension for horcler's code as function
function videoParams = fix(k, windowWidth)
videoParams = {k:k + windowWidth/4, k:k + windowWidth};
end
Test call signal( fix(1,windowWidth){:}, : ) but still unsuccessful giving the error
()-indexing must appear last in an index expression.
so I am not sure if such a function is possible.
How can you make such a int-string-int input for the matrix?
This can be accomplished via comma-separated lists:
signal = rand(15,60,3); % Create random data
windowWidth = 2;
videoParams = {1:1+windowWidth/4, 1:1+windowWidth, 1:size(signal,3)};
Then use the comma-separated list as such:
signal(videoParams{:})
which is equivalent to
signal(1:1+windowWidth/4, 1:1+windowWidth, 1:size(signal,3))
or
signal(1:1+windowWidth/4, 1:1+windowWidth, :)
The colon operator by itself is shorthand for the entirety of a dimension. However, it is only applicable in a direct context. The following is meaningless (and invalid code) as the enclosing cell has no defined size for its third element:
videoParams = {1:1+windowWidth/4, 1:1+windowWidth, :};
To work around this, you could of course use:
videoParams = {1:1+windowWidth/4, 1:1+windowWidth};
signal(videoParams{:},:)
I am using a script which generate a collection of strings in a loop:
'folder1/im1'
'folder1/im2'
...
'folder1/im3'
I assign the string to a variable, when I try to execute the img = dicomread(file); function I get the following error:
Error using dicomread>newDicomread (line 164)
The first input argument must be a filename or DICOM info struct.
Error in dicomread (line 80)
[X, map, alpha, overlays] = newDicomread(msgname, frames);
Error in time (line 14)
img = dicomread(file);
However, using the command line I don't get errors: img = dicomread('folder1/im1').
The code is the next:
for i=1:6 %six cases
nameDir = strcat('folder', int2str(i));
dirData = dir(nameDir);
dirIndex = [dirData.isdir];
fileList = {dirData(~dirIndex).name}; % list of files for each directory
n = size(fileList);
cd(nameDir);
for x = 1:n(2)
img = dicomread(strcat(pwd(), '/', fileList(x)));
end
cd('..');
end
What could be the error?
You've figured it out by now, haven't you.
Based on what you've written, you test
img = dicomread('folder1/im1');
when what you are having trouble with is
img = dicomread(file);
You need to actually test the line you are having trouble with. I would recommend:
putting a break point in test.m a the line img = dicomread(file). When you get to that line you can see what file is equal to. Also do whos file to make sure it is of class char and not a cell array or something random.
If you still want help, edit your original post and show the code where you assign those strings to file and tell us what happens when you type img = dicomread(file) at the command prompt.