mlp = lasagne.layers.BatchNormLayer(mlp)
test_output = lasagne.layers.get_output(mlp, deterministic=True)
test_err = T.mean(T.neq(T.argmax(test_output, axis=1), target),dtype=theano.config.floatX)
# Compile a second function computing the validation loss and accuracy:
val_fn = theano.function([input, target], test_err)
print("Loading the trained parameters and binarizing the weights...")
# Load parameters
with np.load('mnist_parameters.npz') as f:
param_values = [f['arr_%d' % i] for i in range(len(f.files))]
lasagne.layers.set_all_param_values(mlp, param_values)
# Binarize the weights
params = lasagne.layers.get_all_params(mlp)
for param in params:
# print param.name
if param.name == "W":
param.set_value(binary_ops.SignNumpy(param.get_value()))
print('Running...')
start_time = time.time()
test_error = val_fn(test_set.X,test_set.y)*100.
print "test_error = " + str(test_error) + "%"
run_time = time.time() - start_time
print("run_time = "+str(run_time)+"s")
print("Loading the trained parameters and binarizing the weights...")
# Load parameters
with np.load('mnist_parameters.npz') as f:
param_values = [f['arr_%d' % i] for i in range(len(f.files))]
lasagne.layers.set_all_param_values(mlp, param_values)
# Binarize the weights
weights_count = 0
params = lasagne.layers.get_all_params(mlp)
for param in params:
print(param.name)
if param.name == "W":
orig_weights = param.get_value()
param.set_value(binary_ops.SignNumpy(orig_weights))
weights_count = weights_count + len(orig_weights.reshape(-1))
print(param.get_value())
# Print some stats
total_params_count = lasagne.layers.count_params(mlp)
weights_needed_bytes_count = weights_count / 8
non_weights_needed_bytes_count = total_params_count * 4 - weights_count / 8
print(
'The model has a total of %d parameters of which %d (the weights) are binary.'
% (total_params_count, weights_count))
print('Space requirements:')
print(' - %d bytes for the weights' % weights_needed_bytes_count)
print(' - %d bytes for the other parameters (assumed 32bit floats each)' %
non_weights_needed_bytes_count)
print(' = %d bytes' %