How to fix ipykernel_launcher.py: error: unrecognized arguments in jupyter?
Question:
I am following this tensorflow tutorial after two days setting up the environment I finally could run premade_estimator.py using cmd
but when I try to run the same code in a jupyter notebook I am getting this error:
usage: ipykernel_launcher.py [-h] [--batch_size BATCH_SIZE]
[--train_steps TRAIN_STEPS]
ipykernel_launcher.py: error: unrecognized arguments: -f C:UsersdavidAppDataRoamingjupyterruntimekernel-4faecb24-6e87-40b4-bf15-5d24520d7130.json
An exception has occurred, use %tb to see the full traceback.
SystemExit: 2
C:Anaconda3envspython3xlibsite-packagesIPythoncoreinteractiveshell.py:2918:
UserWarning: To exit: use 'exit', 'quit', or Ctrl-D. warn("To exit: use 'exit', 'quit', or Ctrl-D.", stacklevel=1)
I have tried to fix it without success using:
pip install --ignore-installed --upgrade jupyter
pip install ipykernel
python -m ipykernel install
conda install notebook ipykernel
ipython kernelspec install-self
Any idea will be appreciate! Thanks!
Answers:
Have you tried :
conda install ipykernel --name Python3
python -m ipykernel install
I got it! the reason why we get the error is because this code is using argparse and this module is used to write user-friendly command-line interfaces, so it seems, it has a conflict with Jupyter Notebook.
I found the solution in this page:
What we have to do is:
Delete or comment these lines:
parser = argparse.ArgumentParser()
parser.add_argument('--batch_size', default=100, type=int, help='batch size')
parser.add_argument('--train_steps', default=1000, type=int,
help='number of training steps')
and replace args
args = parser.parse_args(argv[1:])
for a dictionary using the library easydict in this way:
args = easydict.EasyDict({
"batch_size": 100,
"train_steps": 1000
})
With easydict we can access dict values as attributes for the arguments.
Update
After all this year diving deeper in python, I found the solution for this question is way more simple (We don’t need to use any external library or method). argparse is just one of the many ways to pass arguments to a script in python from the terminal. When I tried to do it in a jupyter notebook obviously that wasn’t going to work. We can just replace in the function directly the parameters like:
funtion(batch_size=100, train_steps=1000)
Now, if we have a long list of parameters for our function, we can use *args or **kargs.
*args pass a tuple as parameters in the function, for this case, in particular, it will be:
args = (100, 1000)
function(*args)
**kargs pass a dictionary as arguments to our function:
kargs = {"batch_size": 100,
"train_steps": 1000}
function(**kargs)
just google it and you will find a really good explanation on how to use them both, here one documentation that I used to study this.
A more elegant solution would be:
args, unknown = parser.parse_known_args()
instead of
args = parser.parse_args()
I just ran into this problem today and found a quick, stupid solution is to insert an argument processor for the -f argument that qtconsole/ipython passes though and we did not expect. At end of parser.add_argument I put in:
parser.add_argument("-f", "--fff", help="a dummy argument to fool ipython", default="1")
I don’t use the -f parameter, so there’s no loss for me.
I’d rather not re-engineer a larger argument processing framework just because of ipython cropping up in workflow on one particular computer…
I got this problem with :
from serial.tools.list_ports import main
main()
but it’s a library from serial import
so i make a copy in my own directory the file from :
/usr/lib/python3/dist-packages/serial/tools
and edit to add :
parser.add_argument("-f", "--fff", help="a dummy argument to fool ipython", default="1")
as pauljohn32 (https://stackoverflow.com/users/1086346/pauljohn32) did !
now using the new file locally:
from list_ports import main
main()
it works fine !
I was getting error for many more "unrecognized arguments":
ipykernel_launcher: error: unrecognized arguments: --ip=127.0.0.1 --stdin=9008 --control=9006 --hb=9005 --Session.signature_scheme="hmac-sha256" --Session.key=b"2dd531d9" --shell=9007 --transport="tcp" --iopub=9009 --f=tmp-18240vZXCSGIbxxcJ.json An exception has occurred, use %tb to see the full traceback.
For each unrecognized argument (i.e ip, stdin, control, ..), I added a line to add the argument to my ArgParser (as suggested by @pauljohn32):
ap.add_argument(
"-i", "--ip", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-s", "--stdin", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-c", "--control", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-b", "--hb", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-K", "--Session.key", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-S", "--Session.signature_scheme", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-l", "--shell", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-t", "--transport", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-o", "--iopub", help="a dummy argument to fool ipython", default="1")
Another solution as suggested here is passing empty string to the parse_args method.
For instance:
import argparse
def arguments():
parser = argparse.ArgumentParser(description='Example')
return parser.parse_args("")
The above solution actually works in google-colab.
because this code is using argparse and this module is used to write user-friendly command-line interfaces, so it seems, it has a conflict with Jupyter Notebook.
the reason is as above, but I think it is better to convert args to class than to dict as @virtualdvid and @Hrvoje said
class args_:
self.batch_size = 100,
self.train_steps = 1000
args = args_
I am following this tensorflow tutorial after two days setting up the environment I finally could run premade_estimator.py using cmd
but when I try to run the same code in a jupyter notebook I am getting this error:
usage: ipykernel_launcher.py [-h] [--batch_size BATCH_SIZE] [--train_steps TRAIN_STEPS] ipykernel_launcher.py: error: unrecognized arguments: -f C:UsersdavidAppDataRoamingjupyterruntimekernel-4faecb24-6e87-40b4-bf15-5d24520d7130.jsonAn exception has occurred, use %tb to see the full traceback.
SystemExit: 2 C:Anaconda3envspython3xlibsite-packagesIPythoncoreinteractiveshell.py:2918: UserWarning: To exit: use 'exit', 'quit', or Ctrl-D. warn("To exit: use 'exit', 'quit', or Ctrl-D.", stacklevel=1)
I have tried to fix it without success using:
pip install --ignore-installed --upgrade jupyter
pip install ipykernel
python -m ipykernel install
conda install notebook ipykernel
ipython kernelspec install-self
Any idea will be appreciate! Thanks!
Have you tried :
conda install ipykernel --name Python3
python -m ipykernel install
I got it! the reason why we get the error is because this code is using argparse and this module is used to write user-friendly command-line interfaces, so it seems, it has a conflict with Jupyter Notebook.
I found the solution in this page:
What we have to do is:
Delete or comment these lines:
parser = argparse.ArgumentParser()
parser.add_argument('--batch_size', default=100, type=int, help='batch size')
parser.add_argument('--train_steps', default=1000, type=int,
help='number of training steps')
and replace args
args = parser.parse_args(argv[1:])
for a dictionary using the library easydict in this way:
args = easydict.EasyDict({
"batch_size": 100,
"train_steps": 1000
})
With easydict we can access dict values as attributes for the arguments.
Update
After all this year diving deeper in python, I found the solution for this question is way more simple (We don’t need to use any external library or method). argparse is just one of the many ways to pass arguments to a script in python from the terminal. When I tried to do it in a jupyter notebook obviously that wasn’t going to work. We can just replace in the function directly the parameters like:
funtion(batch_size=100, train_steps=1000)
Now, if we have a long list of parameters for our function, we can use *args or **kargs.
*args pass a tuple as parameters in the function, for this case, in particular, it will be:
args = (100, 1000)
function(*args)
**kargs pass a dictionary as arguments to our function:
kargs = {"batch_size": 100,
"train_steps": 1000}
function(**kargs)
just google it and you will find a really good explanation on how to use them both, here one documentation that I used to study this.
A more elegant solution would be:
args, unknown = parser.parse_known_args()
instead of
args = parser.parse_args()
I just ran into this problem today and found a quick, stupid solution is to insert an argument processor for the -f argument that qtconsole/ipython passes though and we did not expect. At end of parser.add_argument I put in:
parser.add_argument("-f", "--fff", help="a dummy argument to fool ipython", default="1")
I don’t use the -f parameter, so there’s no loss for me.
I’d rather not re-engineer a larger argument processing framework just because of ipython cropping up in workflow on one particular computer…
I got this problem with :
from serial.tools.list_ports import main
main()
but it’s a library from serial import
so i make a copy in my own directory the file from :
/usr/lib/python3/dist-packages/serial/tools
and edit to add :
parser.add_argument("-f", "--fff", help="a dummy argument to fool ipython", default="1")
as pauljohn32 (https://stackoverflow.com/users/1086346/pauljohn32) did !
now using the new file locally:
from list_ports import main
main()
it works fine !
I was getting error for many more "unrecognized arguments":
ipykernel_launcher: error: unrecognized arguments: --ip=127.0.0.1 --stdin=9008 --control=9006 --hb=9005 --Session.signature_scheme="hmac-sha256" --Session.key=b"2dd531d9" --shell=9007 --transport="tcp" --iopub=9009 --f=tmp-18240vZXCSGIbxxcJ.json An exception has occurred, use %tb to see the full traceback.
For each unrecognized argument (i.e ip, stdin, control, ..), I added a line to add the argument to my ArgParser (as suggested by @pauljohn32):
ap.add_argument(
"-i", "--ip", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-s", "--stdin", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-c", "--control", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-b", "--hb", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-K", "--Session.key", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-S", "--Session.signature_scheme", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-l", "--shell", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-t", "--transport", help="a dummy argument to fool ipython", default="1")
ap.add_argument(
"-o", "--iopub", help="a dummy argument to fool ipython", default="1")
Another solution as suggested here is passing empty string to the parse_args method.
For instance:
import argparse
def arguments():
parser = argparse.ArgumentParser(description='Example')
return parser.parse_args("")
The above solution actually works in google-colab.
because this code is using argparse and this module is used to write user-friendly command-line interfaces, so it seems, it has a conflict with Jupyter Notebook.
the reason is as above, but I think it is better to convert args to class than to dict as @virtualdvid and @Hrvoje said
class args_:
self.batch_size = 100,
self.train_steps = 1000
args = args_