Example #1
0
# inputtype ('binary', 'tfidf', other options?) determines what the
# decoding activation function is for the first layer
# e.g. inputtype 'tfidf' ('tf*idf'?) uses activation function softplus
# to decode the tf*idf.
state.inputtype = 'binary'

state.seed = 123

#here is the for loops that does the grid:

for i in [0.01, 0.001, 0.0001]:
    state.lr = [i]
    for j in [(0.7, 0.0041), (0.5, 0.003), (0.8, 0.005)]:
        state.noise_lvl = [j]
        for k in [0.001, 0.00001, 0.0]:
            state.activation_regularization_coeff = [k]
            sql.insert_job(
                NLPSDAE, flatten(state), db
            )  #this submit the current state DD to the db, if it already exist in the db no additionnal job is added.

db.createView('opentablegpuview')

#in order to access the db from a compute node you need to create an tunnel ssh connection on ang23:
#(to do one time, I think you should keep the shell open or you can create the tunnel on a screen and detached it)

#ssh -v -f -o ServerAliveInterval=60 -o ServerAliveCountMax=60 -N -L *:5432:localhost:5432 gershwin.iro.umontreal.ca

#you will need to give your LISA password.

#here is the command you use to launch 1 jobs of the db.
#THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32  sqsub -q gpu -r 2d -n 1 --gpp=1 --memperproc=2.5G -o the_output_you_want jobman sql 'postgres://glorotxa@ang23/glorotxa_db/opentablegpu' /scratch/glorotxa/
Example #2
0
# If there is a model file specified to build upon, the output of this
# model is the input for the model we are currently building.
state.model_to_build_upon = None

state.ninputs = 5000
#state.ninputs = 1000

# inputtype ('binary', 'tfidf', other options?) determines what the
# decoding activation function is for the first layer
# e.g. inputtype 'tfidf' ('tf*idf'?) uses activation function softplus
# to decode the tf*idf.
state.inputtype = 'binary'

state.seed = 123

state.activation_regularization_coeff = [0]

#here is the for loops that does the grid:

for i in [0.01,0.001]:
    state.lr = [i]
    for j in [0.5,0.25,0.125,0.05]:
        state.noise_lvl=[j]
        for k in [1400,2500,5000]:
            state.n_hid = [k]
            sql.insert_job(NLPSDAE, flatten(state), db) #this submit the current state DD to the db, if it already exist in the db no additionnal job is added.


db.createView('opentablegpuview')

# First run this script