cuBERT | Fast implementation of BERT inference | Machine Learning library
kandi X-RAY | cuBERT Summary
kandi X-RAY | cuBERT Summary
|batch size|128 (ms) |32 (ms) | |--- |--- |--- | |tensorflow|255.2 |70.0 | |cuBERT |184.6|54.5|.
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Community Discussions
Trending Discussions on cuBERT
QUESTION
hopefully a relatively easy one for those more experienced than me!
Trying to perform a Box-Cox transformation using the following code:
...ANSWER
Answered 2020-May-13 at 02:24I thought 'x' was being defined in line 3?
Line 3 is lambda<-with(bc, x[which.max(y)])
. It doesn't define x
, it defines lambda
. It does use x
, which it looks for within the bc
environment. If you're using boxcox()
from the MASS
package, bc
should indeed include x
and y
components, so bc$x
shouldn't give you the same error message. I'd expect an error about the replacement lengths. Because...
bc$x
are the potential lambda values tried by boxcox
- you're using the default seq(-2, 2, 1/10)
, and it would be an unlikely coincidence if your data had a multiple of 41 rows needed to not give an error when assigning 41 values to a new column.
Line 3 picks out the lambda value that maximizes the likelihood, so you shouldn't need the rest of the values in bc
ever again. I'd expect you to use that lambda
values to transform your response variable, as that's what the Box Cox transformation is for. ((x^lambda)-1/lambda)
doesn't make any statistical or programmatic sense. Use this instead:
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Vulnerabilities
No vulnerabilities reported
Install cuBERT
Pre-built python binary package (currently only with MKL on Linux) can be installed as follows:.
Download and install [MKL](https://github.com/intel/mkl-dnn/releases) to system path.
Download the wheel package and pip install cuBERT-xxx-linux_x86_64.whl
run python -c 'import libcubert' to verify your installation.
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