Function saveToDisk(ByVal dataout As UByte Ptr, lengteout As Short, fileName As String) As UShort
Dim As Integer fileNum = FreeFile()
If Open(fileName, For Binary, Access Write, As fileNum) = 0 Then
Put #fileNum, , run_counter
Put #fileNum, , CLng(lengteout) 'force long (4 bytes)
Put #fileNum, , dataout[0] ,lengteout
Close #fileNum
Else
Print "error open": Return -1
End If
Return 0
End Function
Function loadFromDisk(ByVal datain As UByte Ptr, lengtein As Short, fileName As String) As Short
Dim As Long fileSize = FileLen(fileName)
If fileSize < 4 Then Print "error lengte header": Return -3
Dim As Integer fileNum = FreeFile()
Dim As Long getlengte
If Open(fileName, For Binary, Access Read, As fileNum) = 0 Then
Get #fileNum, , run_counter
Get #fileNum, , getlengte
If getlengte <> lengtein Then Close #fileNum: Print "error lengte": Return -2
Get #fileNum, , datain[0], lengtein
Close #fileNum
Else
Print "error open": Return -1
End If
Return 0
End Function
Obviously, the developer of Flappy Bird has a familiarity with Neural Networks.
At Beginners, Easy Matrix, I'm attempting to repurpose the routines for use as a very basic Neural Network.
Apart from what already appears there, I've written most of the code for the forward propagation portion of
a Neural Network; now I'm considering back propagation. Perhaps you'd like to contribute insight or code
for this purpose.
Obviously, the developer of Flappy Bird has a familiarity with Neural Networks.
At Beginners, Easy Matrix, I'm attempting to repurpose the routines for use as a very basic Neural Network.
Apart from what already appears there, I've written most of the code for the forward propagation portion of
a Neural Network; now I'm considering back propagation. Perhaps you'd like to contribute insight or code
for this purpose.
I watched all of the video , more viewings are required to glean some insight
into some features he mentioned.
After the completion of what has felt like half a marathon, I may now have a NN that
has the basic features performing as intended. With so many variations on this theme
though, I'm of course not 100% certain.
Rather than using a convolutional NN I'm using back propagation and matrices.
For various reasons I prefer back propagation; for now.
I don't know how you code, I tend to spawn many fragments of code, independently
test these then merge them back into other variants of the main code and also
repeatedly edit those; until provisionally deciding on which main variant to promote
to mostly completed status.