def test_fixed_point_graph(seed, graph_ref, graph_act):
# TODO: adaptive delta case (how to test it...)
from graph_converter_test_utils import structure_tester, value_tester, print_params
# Random number
np.random.seed(seed)
rng = np.random.RandomState(seed)
# Graph
x_data = rng.randn(4, 3, 32, 32)
x = nn.Variable.from_numpy_array(x_data)
y_tgt = graph_act(x)
# Convert weights/activations
args_fpq = {
"sign_w": True,
"n_w": 8,
"delta_w": 2e-4,
"quantize_w": True,
"sign_b": True,
"n_b": 8,
"delta_b": 2e-4,
"quantize_b": True
}
name = "fixed-point-graph"
converter_w = GC.FixedPointWeightConverter(args_fpq=args_fpq, name=name)
name = "fixed-point-graph"
args_fpq = {"n": 8, "sign": False, "delta": 2e-4}
converter_a = GC.FixedPointActivationConverter(args_fpq=args_fpq,
name=name)
# Convert sequentially
converter = GC.SequentialConverter([converter_w, converter_a])
y_act = converter.convert(y_tgt, [x])
# Ref Graph
name = "fixed-point-graph-ref"
y_ref = graph_ref(x, name=name)
# Test
structure_tester(y_ref, y_act)
def test_fixed_point_activation(seed, graph_ref, graph_act):
from graph_converter_test_utils import structure_tester, value_tester, print_params
# Random number
np.random.seed(seed)
rng = np.random.RandomState(seed)
# Graph
x_data = rng.randn(4, 3, 32, 32)
x = nn.Variable.from_numpy_array(x_data)
y_tgt = graph_act(x)
# Convert
args_fpq = {"n": 8, "sign": False, "delta": 2e-4}
name = "fixed-point-activation-graph"
converter = GC.FixedPointActivationConverter(args_fpq=args_fpq, name=name)
y_act = converter.convert(y_tgt, [x])
# Ref Graph
name = "fixed-point-activation-graph-ref"
y_ref = graph_ref(x, name=name)
# Test
structure_tester(y_ref, y_act)
return pred
x = nn.Variable.from_numpy_array(np.random.rand(4, 3, 28, 28))
y = LeNet(x, test=True)
create_graph(y, width=300)
# ## BatchNormalizationLinearConverter
converter = GC.BatchNormalizationLinearConverter(name="bn-linear-lenet")
z = converter.convert(y, [x])
create_graph(z, width=300)
# ## BatchNormalizationFoldedConverter
converter = GC.BatchNormalizationFoldedConverter(name="bn-folded-lenet")
z = converter.convert(y, [x])
create_graph(z, width=300)
# ## FixedPointWeightConverter
converter = GC.FixedPointWeightConverter(name="fixed-point-weight-lenet")
z = converter.convert(y, [x])
create_graph(z, width=300)
# ## FixedPointActivationConverter
converter = GC.FixedPointActivationConverter(
name="fixed-point-activation-lenet")
z = converter.convert(y, [x])
create_graph(z, width=300)
# -
converter_w = GC.FixedPointWeightConverter(name="fixed-point-lenet")
converter_a = GC.FixedPointActivationConverter(name="fixed-point-lenet")
converter = GC.SequentialConverter([converter_w, converter_a])
z = converter.convert(y, [x])
create_graph(z, width=300)