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@filmo
filmo / gist:2c1ac7467c26f62f589422aa55206a2e
Created Jun 18, 2018
problem with train.py for donkeycar
View gist:2c1ac7467c26f62f589422aa55206a2e
On line 35 shuffle is imported from sklearn
from sklearn.utils import shuffle
and then later called inside the data generator with:
shuffle(keys)
However, shuffle from sklearn does ~not~ shuffle in-place. It returns a shuffled list, leaving the input parameter untouched.
@filmo
filmo / binned_throttle.py
Last active Mar 14, 2018
binned throttle for donkeycar
View binned_throttle.py
import numpy as np
np.set_printoptions(precision=4,suppress=True,linewidth=180)
def clamp(n, min, max):
if n < min:
return min
if n > max:
return max
return n
View Double DQN
Used a 2-layer Fully Connected network with H1=100, H2=60 and ReLU
He Initialization of weights
Adam Optimizer. Initial learning rate = 0.001 Learning rate reduced using gamma of 0.50 every 350 episodes
Gamma = 0.99
Eps = 1.00
Eps Decay = 0.98
Eps Decay every new episode. (not each step)
View gist:a99db13793397c8364a3be42c711db9b
q_learning walkthrough. GATech OMSCS. (School policy prohibits our publishing code for honor policy)
View gist:e32bb82249c73e868ef3f23234966363
Used Value Iteration as shown in class walkthrough. (School policy prohibits us showing code for honor policy.)
GATech OMSCS
View Random Passes and Failures
philglau (master *) pr1 $ python submit.py gfserver
Tests that the client properly sends an ERROR response.: failed
Tests that the server properly sends an OK response and medium messag: failed
Tests that the server properly sends an OK response and a long messag: failed
Tests that the server properly sends an OK response and a short messa: failed
Tests that the server compiles: passed
Tests that the server properly handles a gfs_abort call.: passed
Tests that the server properly sends a FILE_NOT_FOUND response.: passed
Tests that the server properly handles a malformed request.: passed
Tests that the server properly handles a malformed request.: passed
View Vagrant Install IOS Mac 10.10.5
philglau (master) pr1 $ vagrant up
Bringing machine 'default' up with 'virtualbox' provider...
==> default: Box 'ubuntu/xenial64' could not be found. Attempting to find and install...
default: Box Provider: virtualbox
default: Box Version: >= 0
==> default: Loading metadata for box 'ubuntu/xenial64'
default: URL: https://atlas.hashicorp.com/ubuntu/xenial64
==> default: Adding box 'ubuntu/xenial64' (v20160826.0.0) for provider: virtualbox
default: Downloading: https://atlas.hashicorp.com/ubuntu/boxes/xenial64/versions/20160826.0.0/providers/virtualbox.box
==> default: Successfully added box 'ubuntu/xenial64' (v20160826.0.0) for 'virtualbox'!
@filmo
filmo / gist:0821af03f01da8592e09921953b4ae5a
Last active Aug 13, 2016
Problem Installing cudarray with Anaconda Unbuntu 14.04
View gist:0821af03f01da8592e09921953b4ae5a
make
g++ -DCUDNN_ENABLED -O3 -fPIC -Wall -Wfatal-errors -D_FORCE_INLINES -I./include -I/usr/local/cuda-7.5/include -c -o src/nnet/conv_bc01_matmul.o src/nnet/conv_bc01_matmul.cpp
nvcc -gencode arch=compute_20,code=sm_20 -gencode arch=compute_20,code=compute_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_30,code=compute_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_35,code=compute_35 -O3 --compiler-options '-DCUDNN_ENABLED -O3 -fPIC -Wall -Wfatal-errors -D_FORCE_INLINES' --ftz=true --prec-div=false -prec-sqrt=false --fmad=true -I./include -I/usr/local/cuda-7.5/include -c -o src/nnet/pool_b01.o src/nnet/pool_b01.cu
g++ -DCUDNN_ENABLED -O3 -fPIC -Wall -Wfatal-errors -D_FORCE_INLINES -I./include -I/usr/local/cuda-7.5/include -c -o src/nnet/cudnn.o src/nnet/cudnn.cpp
nvcc -gencode arch=compute_20,code=sm_20 -gencode arch=compute_20,code=compute_20 -gencode arch=compute_30,code=sm_30 -gencode arch=compute_30,code=compute_30 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_35,c
View Lect4-Constraint.txt
https://www.youtube.com/watch?v=T_yhf2HrPfQ
https://www.youtube.com/watch?v=x9_vmhE7yiI
https://www.youtube.com/watch?v=AC7RUSqoJ3k
https://www.youtube.com/watch?v=2va57vCvvYs
https://www.youtube.com/watch?v=vwyNzW2GTtM
https://www.youtube.com/watch?v=Ry7lVkgJ1UY
https://www.youtube.com/watch?v=agLkd2ka3Uk
https://www.youtube.com/watch?v=0M-qni5JPlg
https://www.youtube.com/watch?v=l5HRWFGa9Ps
https://www.youtube.com/watch?v=jwYHU5v2YnM
@filmo
filmo / Lect3-Simulated-Annealing.txt
Created Feb 2, 2016
6601 AI Lecture 3 - Simulated Annealing
View Lect3-Simulated-Annealing.txt
https://www.youtube.com/watch?v=dtCpwQsSthY
https://www.youtube.com/watch?v=xEBSG6-XCcc
https://www.youtube.com/watch?v=JKShXWF6t2I
https://www.youtube.com/watch?v=BUsZp8mk-xo
https://www.youtube.com/watch?v=5zZiO8sNdvw
https://www.youtube.com/watch?v=bPAFnwZx0b4
https://www.youtube.com/watch?v=hTVO07COpwg
https://www.youtube.com/watch?v=ht3hLnulH4g
https://www.youtube.com/watch?v=IdmkCgRiYp4
https://www.youtube.com/watch?v=_xAQNt96jpo
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