def test_low_bw_error(self):
with self.assertRaises(pyrtl.PyrtlError):
libutils.twos_comp_repr(-40, 6)
with self.assertRaises(pyrtl.PyrtlError):
libutils.rev_twos_comp_repr(88, 6)
with self.assertRaises(pyrtl.PyrtlError):
libutils.rev_twos_comp_repr(8, 4)
def test_low_bw_error(self):
with self.assertRaises(pyrtl.PyrtlError):
libutils.twos_comp_repr(-40, 6)
with self.assertRaises(pyrtl.PyrtlError):
libutils.rev_twos_comp_repr(88, 6)
with self.assertRaises(pyrtl.PyrtlError):
libutils.rev_twos_comp_repr(8, 4)
def mult_t_base(self, len_a, len_b, **mult_args):
# Creating the logic nets
a, b = pyrtl.Input(len_a, "a"), pyrtl.Input(len_b, "b")
product = pyrtl.Output(name="product")
product <<= multipliers.signed_tree_multiplier(a, b, **mult_args)
self.assertEqual(len(product), len_a + len_b)
# creating the testing values and the correct results
bound_a = 2**(len_a - 1) - 1
bound_b = 2**(len_b - 1) - 1
xvals = [int(random.uniform(-bound_a, bound_a)) for i in range(20)]
yvals = [int(random.uniform(-bound_b, bound_b)) for i in range(20)]
true_result = [i * j for i, j in zip(xvals, yvals)]
# Setting up and running the tests
sim_trace = pyrtl.SimulationTrace()
sim = pyrtl.Simulation(tracer=sim_trace)
for cycle in range(len(xvals)):
sim.step({
a: libutils.twos_comp_repr(xvals[cycle], len_a),
b: libutils.twos_comp_repr(yvals[cycle], len_b)
})
# Extracting the values and verifying correctness
multiplier_result = [
libutils.rev_twos_comp_repr(p, len(product))
for p in sim_trace.trace[product.name]
]
self.assertEqual(multiplier_result, true_result)
def mult_t_base(self, len_a, len_b, **mult_args):
# Creating the logic nets
a, b = pyrtl.Input(len_a, "a"), pyrtl.Input(len_b, "b")
product = pyrtl.Output(name="product")
product <<= multipliers.signed_tree_multiplier(a, b, **mult_args)
self.assertEquals(len(product), len_a + len_b)
# creating the testing values and the correct results
bound_a = 2**(len_a-1) - 1
bound_b = 2**(len_b-1) - 1
xvals = [int(random.uniform(-bound_a, bound_a)) for i in range(20)]
yvals = [int(random.uniform(-bound_b, bound_b)) for i in range(20)]
true_result = [i * j for i, j in zip(xvals, yvals)]
# Setting up and running the tests
sim_trace = pyrtl.SimulationTrace()
sim = pyrtl.Simulation(tracer=sim_trace)
for cycle in range(len(xvals)):
sim.step({
a: libutils.twos_comp_repr(xvals[cycle], len_a),
b: libutils.twos_comp_repr(yvals[cycle], len_b)
})
# Extracting the values and verifying correctness
multiplier_result = [libutils.rev_twos_comp_repr(p, len(product))
for p in sim_trace.trace[product]]
self.assertEqual(multiplier_result, true_result)
def test_twos_comp_sim(self):
self.out <<= self.in1 + self.in2
sim_trace = pyrtl.SimulationTrace()
sim = pyrtl.Simulation(tracer=sim_trace)
for i in range(10):
sim.step({'in1': i, 'in2': libutils.twos_comp_repr(-2 * i, 8)})
self.assertEquals(
-i, libutils.rev_twos_comp_repr(sim.inspect('out'), 8))
def test_twos_comp_sim(self):
self.out <<= self.in1 + self.in2
sim_trace = pyrtl.SimulationTrace()
sim = pyrtl.Simulation(tracer=sim_trace)
for i in range(10):
sim.step({
'in1': i,
'in2': libutils.twos_comp_repr(-2*i, 8)
})
self.assertEquals(-i, libutils.rev_twos_comp_repr(sim.inspect('out'), 8))
def test_inverse_functionality(self):
for i in range(20):
self.assertEqual(i * 3, libutils.rev_twos_comp_repr(
libutils.twos_comp_repr(i * 3, 16), 16))
def test_inverse_functionality(self):
for i in range(20):
self.assertEquals(i*3, libutils.rev_twos_comp_repr(
libutils.twos_comp_repr(i*3, 16), 16))
