#!/usr/bin/env python
from yann.network import network
from yann.utils.pickle import load
import time
import sys
#run = 1
dataset = sys.argv[1]
momentum = "nesterov"
optim = "rmsprop"
lr = (0.01, 0.005, 0.001)
params = load('network_dataset_96731.pkl')
# create a network
net = network()
dataset_params = {"dataset": dataset, "id": 'svhn', "n_classes": 10}
net.add_layer(type="input", id="input", dataset_init_args=dataset_params)
# adding layers
net.add_layer(type="conv_pool",
origin="input",
id="conv_pool_1",
num_neurons=20,
filter_size=(5, 5),
pool_size=(2, 2),
batch_norm=True,
activation='relu',
input_params=params['conv_pool_1'],
learnable=False)
epochs = (40, 40)
p_vals = [0, 10, 50, 100, 500, 1000, 2500, 4700]
#p_vals = [0]
# setup incremental dataset parameters dataset.
"""temp_splits = { "shot" : [6,7,8,9],
"base" : [0,1,2,3,4,5],
"p" : 0 }"""
temp_base_data = inc_dataset( #splits = temp_splits,
verbose=1)
temp_base_data = temp_base_data.dataset_location()
site2 = igan(init_dataset=temp_base_data, root=root, verbose=1)
print(". Setup transfered gan network from site 1.")
gan_params = load(site_1_root + '/resultor/gan/params/epoch_' + str(gan) +
'.pkl')
site2.setup_gan(dataset=temp_base_data,
root=root,
params=gan_params,
cook=False,
verbose=1)
print(". Setup transfered base network from site 1.")
base_params = load(site_1_root +
'/resultor/base-network/params/epoch_99.pkl')
site2.setup_base_mlp(dataset=temp_base_data,
root=root,
params=base_params,
cook=False,
verbose=1)
"batches2validate": 2,
"mini_batch_size": 500
}
# setup incremental dataset parameters dataset.
temp_splits = {"shot": [6, 7, 8, 9], "base": [0, 1, 2, 3, 4, 5], "p": 0}
temp_base_data = inc_dataset(splits=temp_splits,
data_params=temp_data_params,
location=data_loc,
verbose=1)
temp_base_data = temp_base_data.dataset_location()
site2 = igan(init_dataset=temp_base_data, root=root, verbose=1)
print(". Setup transfered gan network from site 1.")
gan_params = load(site_1_root + '/resultor/gan/params/gan-5-31.pkl')
site2.setup_gan(dataset=temp_base_data,
root=root,
params=gan_params,
cook=False,
verbose=1)
print(". Setup transfered base network from site 1.")
base_params = load(site_1_root +
'/resultor/base-network/params/epoch_9.pkl')
site2.setup_base_mlp(dataset=temp_base_data,
root=root,
params=base_params,
cook=False,
verbose=1)
#!/usr/bin/env python
from yann.network import network
from yann.utils.pickle import load
import time
import sys
#run = 1
dataset = sys.argv[1]
momentum = "nesterov"
optim = "rmsprop"
lr = (0.01, 0.005, 0.001)
params = load('network_dataset_90998.pkl')
# create a network
net = network()
dataset_params = {"dataset": dataset, "id": 'svhn', "n_classes": 10}
net.add_layer(type="input", id="input", dataset_init_args=dataset_params)
# adding layers
net.add_layer(type="conv_pool",
origin="input",
id="conv_pool_1",
num_neurons=20,
filter_size=(5, 5),
pool_size=(2, 2),
batch_norm=True,
activation='relu',
input_params=params['conv_pool_1'],
learnable=False)
#!/usr/bin/env python
from yann.network import network
from yann.utils.pickle import load
import time
import sys
#run = 1
dataset = sys.argv[1]
momentum = "nesterov"
optim = "rmsprop"
lr = (0.01, 0.005, 0.001)
params = load('network_dataset_32589.pkl')
# create a network
net = network()
dataset_params = {"dataset": dataset, "id": 'svhn', "n_classes": 10}
net.add_layer(type="input", id="input", dataset_init_args=dataset_params)
# adding layers
net.add_layer(type="conv_pool",
origin="input",
id="conv_pool_1",
num_neurons=20,
filter_size=(5, 5),
pool_size=(2, 2),
batch_norm=True,
activation='relu',
input_params=params['conv_pool_1'],
learnable=False)
def test_load(self, mock_open, mock_shared_params, mock_load):
util_pickle.load('file', verbose=3)
self.assertTrue(mock_load.called)
self.assertTrue(mock_shared_params.called)
self.assertTrue(mock_open.called)
import theano
print("Theano Default Device: ")
print(theano.config.device)
import sys # For CLI args
from yann.network import network
net = network()
dataset_params = {"dataset": sys.argv[2], "id": 'mnist', "n_classes": 10}
# Begin ConvNet Setup using old params
# Load already trained params
from yann.utils.pickle import load
parts = sys.argv[1].split('/')
load_str = 'network' + parts[1] + '.pkl'
print "Loading Network From: " + load_str
old_params = load(load_str)
print "Old Layers: "
print old_params.keys()
net.add_layer(type="input", id="input", dataset_init_args=dataset_params)
net.add_layer(type="conv_pool",
origin="input",
id="conv_pool_1",
num_neurons=20,
filter_size=(5, 5),
pool_size=(2, 2),
activation=('maxout', 'maxout', 2),
batch_norm=True,
regularize=True,
verbose=True,
