[GHC] #14535: ghc: panic! (the 'impossible' happened) (GHC version 8.2.1 for x86_64-apple-darwin): stack depth overflow
GHC
ghc-devs at haskell.org
Mon Nov 27 23:46:37 UTC 2017
#14535: ghc: panic! (the 'impossible' happened) (GHC version 8.2.1 for x86_64
-apple-darwin): stack depth overflow
-------------------------------------+-------------------------------------
Reporter: iTotallyExist | Owner: (none)
Type: bug | Status: new
Priority: high | Milestone:
Component: Compiler | Version: 8.2.1
Resolution: | Keywords: panic! stack
| depth overflow
Operating System: MacOS X | Architecture:
| Unknown/Multiple
Type of failure: GHCi crash | Test Case:
Blocked By: | Blocking:
Related Tickets: | Differential Rev(s):
Wiki Page: |
-------------------------------------+-------------------------------------
Description changed by iTotallyExist:
Old description:
> I created a neural network library within haskell. I was able to create,
> test, and train the net (using data from the mNist dataset). I could
> only test manually (try one input at a time and compare the two outputs),
> so i made a function which allowed me to test many test inputs on the net
> at once.
>
> Recreating bug:
> first, load main.hs in ghci (duh)
> then, run the entirety of trainedNetwork.txt as a command to initialise
> the network (i.e. copy paste the file into the ghci command line)
> then run the entirety of test.txt as a command. Here you will get the
> error.
> To test with different input values for the function "test" (the function
> whose being run caused the crash), you can open the jupyter notebook and
> run the function mnistTest with higher or lower values (higher using more
> test cases, lower using less) and run the output of that function as a
> command in haskell. (i know from testing that 30 inputs does not cause a
> crash, but 50 does).
>
> What i know is not the problem/probably causes:
> I know that y was initiliased correctly.
> The function being run here is :
> {{{#!hs
> --takes in a network and an array of test inputs and their corresponding
> outputs and returns the accuracy of the network
> --only works for classification networks
> testClassification :: [Layer] -> [[Double]] -> [[Double]] -> Double
> testClassification net inputs outputs = testClassificationHelper net
> inputs outputs 0 0
>
> testClassificationHelper :: [Layer] -> [[Double]] -> [[Double]] -> Double
> -> Double -> Double
> testClassificationHelper _ [] _ correct incorrect =
> (correct/(correct+incorrect))
> testClassificationHelper net (input:inputs) (output:outputs) correct
> incorrect | netMax == outMax = next (correct+1) incorrect
> | otherwise = next correct (incorrect+1)
> where
> next = testClassificationHelper net inputs outputs
> netMax = greatestIndex (getOutput net input)
> outMax = greatestIndex output
> }}}
> I know that getOutput and greatestIndex work\\
> I know that it works with a small amount of inputs (test3.txt is
> essentially the same command except instead of using the first 100 test
> examples of the mnist data set, it uses the first 3)\\
> I know that it works when using the first 30 data points, but not with
> the first 50.\\
> I know that doing it for the first 30 inputs only takes 2 seconds and 270
> MB, while training the network took 40 minutes and 820GB, take from that
> what you will\\
New description:
I created a neural network library within haskell. I was able to create,
test, and train the net (using data from the mNist dataset). I could only
test manually (try one input at a time and compare the two outputs), so i
made a function which allowed me to test many test inputs on the net at
once.
Recreating bug:
first, load main.hs in ghci (duh)
then, run the entirety of trainedNetwork.txt as a command to initialise
the network (i.e. copy paste the file into the ghci command line)
then run the entirety of test.txt as a command. Here you will get the
error.
To test with different input values for the function "test" (the function
whose being run caused the crash), you can open the jupyter notebook and
run the function mnistTest with higher or lower values (higher using more
test cases, lower using less) and run the output of that function as a
command in haskell. (i know from testing that 41 inputs does not cause a
crash, but 42 does (seriously, this is not a joke)) .
What i know is not the problem/probably causes:
I know that y was initiliased correctly.
The function being run here is :
{{{#!hs
--takes in a network and an array of test inputs and their corresponding
outputs and returns the accuracy of the network
--only works for classification networks
testClassification :: [Layer] -> [[Double]] -> [[Double]] -> Double
testClassification net inputs outputs = testClassificationHelper net
inputs outputs 0 0
testClassificationHelper :: [Layer] -> [[Double]] -> [[Double]] -> Double
-> Double -> Double
testClassificationHelper _ [] _ correct incorrect =
(correct/(correct+incorrect))
testClassificationHelper net (input:inputs) (output:outputs) correct
incorrect | netMax == outMax = next (correct+1) incorrect
| otherwise = next correct (incorrect+1)
where
next = testClassificationHelper net inputs outputs
netMax = greatestIndex (getOutput net input)
outMax = greatestIndex output
}}}
I know that getOutput and greatestIndex work\\
I know that it works with a small amount of inputs (test3.txt is
essentially the same command except instead of using the first 100 test
examples of the mnist data set, it uses the first 3)\\
I know that it works when using the first 30 data points, but not with the
first 50.\\
I know that doing it for the first 30 inputs only takes 2 seconds and 270
MB, while training the network took 40 minutes and 820GB, take from that
what you will\\
--
--
Ticket URL: <http://ghc.haskell.org/trac/ghc/ticket/14535#comment:1>
GHC <http://www.haskell.org/ghc/>
The Glasgow Haskell Compiler
More information about the ghc-tickets
mailing list