# keep making bootstraps yo
while(True):
inp, outp = ([[1, 1], [0, 1], [1, 0], [0, 0]], [[0, 1, 1, 0], [1, 0, 0, 1]])
inp = np.array(inp)
outp = np.array(outp)
# create new function arrays for the respective bootstrap
valid_fn_array = []
test_fn_array = []
# this array holds the training errors per minibatch
epoch_train_error_array = [[] for n in xrange(num_tasks)]
log('> ... building functions for bootstrap found %d' % epoch_counter)
# build the finetuning functions for these bootstraps
for idx, task in enumerate(dnn_array):
train_fn, valid_fn, test_fn = dnn.build_functions(
(inp[idx], outp[idx]), ([], []), ([], []), mbatch_size, onlyTrain=True)
train_fn_array.append(train_fn)
total_train_err = 0.0
total_cost = 0.0
# now we're going to train
for taskidx in xrange(num_tasks):
for batchidx in xrange(mbatch_per_bootstrap):
one_err, one_cost = train_fn_array[taskidx](index=batchidx, learning_rate=train_learning_rate)
one_err = float(one_err)
total_cost += one_cost
epoch_train_error_array[taskidx].append(one_err)
batch_test_err = test_fn_array[taskidx](index=batchidx)
if not math.isnan(batch_test_err):
test_err += batch_test_err
mean_train_err = np.mean(epoch_train_error_array[taskidx])
mean_train_error_array = []#[[] for n in xrange(num_tasks)]
epoch_train_error_array = [[] for n in xrange(num_tasks)]
val_error_array = []#[[] for n in xrange(num_tasks)]
test_error_array = []
epoch_counter = 0
# create new function arrays for the respective bootstrap
train_fn_array = []
valid_fn_array = []
test_fn_array = []
inp, outp = get_bootstraps(bootstrap_size)
log('> ... building functions for bootstrap found %d' % epoch_counter)
# build the finetuning functions for these bootstraps
for idx, task in enumerate(dnn_array):
train_fn, valid_fn, test_fn = dnn.build_functions(
(inp[idx], outp[idx]), (None, None), (testin[idx], testout[idx]), mbatch_size, True)
train_fn_array.append(train_fn)
valid_fn_array.append(valid_fn)
test_fn_array.append(test_fn)
try:
# keep making bootstraps yo
while(True):
# this array holds the training errors per minibatch
epoch_train_error_array = [[] for n in xrange(num_tasks)]
