class M5:
in0 = Input(dim(types.i32, 16))
in1 = Input(types.i32)
t_c = dim(types.i32, 16)
c = Output(t_c)
@generator
def build(ports):
# a 32x32xi1 ndarray.
# A dtype of i32 is fairly expensive wrt. the size of the output IR, but
# but allows for assigning indiviudal bits.
m = NDArray((32, 32), dtype=types.i1, name='m1')
# Assign individual bits to the first 32 bits.
for i in range(32):
m[0, i] = hw.ConstantOp(types.i1, 1)
# Fill the next 15 values with an i32. The ndarray knows how to convert
# from i32 to <32xi1> to comply with the ndarray dtype.
for i in range(1, 16):
m[i] = ports.in1
# Fill the upportmost 16 rows with the input array of in0 : 16xi32
m[16:32] = ports.in0
# We don't provide a method of reshaping the ndarray wrt. its dtype.
# that is: 32x32xi1 => 32xi32
# This has massive overhead in the generated IR, and can be easily
# achieved by a bitcast.
ports.c = hw.BitcastOp(M5.t_c, m.to_circt())
class M1:
in1 = Input(dim(types.i32, 4, 8))
out = Output(dim(types.i32, 2, 16))
@generator
def build(ports):
ports.out = ports.in1.transpose((1, 0)).reshape((16, 2))
class M1:
in1 = Input(dim(types.i32, 4, 8))
out = Output(dim(types.i32, 8, 4))
@generator
def build(ports):
ports.out = ports.in1.transpose((1, 0))
class M1:
in1 = Input(dim(types.i32, 10))
out = Output(dim(types.i32, 10))
@generator
def build(ports):
ports.out = ports.in1.roll(3)
class M1:
in1 = Input(dim(types.i32, 10))
out = Output(dim(types.i32, 10))
@generator
def build(ports):
m = NDArray(from_value=ports.in1, name='m1')
ports.out = m.to_circt(create_wire=False)
class MyMod:
in_port = Input(dim(8))
out0 = Output(dim(5))
out1 = Output(dim(5))
@generator
def construct(mod):
# Partial lower slice
mod.out0 = mod.in_port[3:]
# partial upper slice
mod.out1 = mod.in_port[:5]
class M1:
in1 = Input(dim(types.i32, 10))
in2 = Input(dim(types.i32, 10))
in3 = Input(dim(types.i32, 10))
out = Output(dim(types.i32, 30))
@generator
def build(ports):
# Explicit ndarray.
m = NDArray(from_value=ports.in1, name='m1')
# Here we could do a sequence of transformations on 'm'...
# Finally, concatenate [in2, m, in3]
ports.out = ports.in2.concatenate((m, ports.in3))
class M2:
in0 = Input(dim(types.i32, 16))
in1 = Input(types.i32)
t_c = dim(types.i32, 8, 4)
c = Output(t_c)
@generator
def build(ports):
# a 32xi32 ndarray.
m = NDArray((32, ), dtype=types.i32, name='m2')
for i in range(16):
m[i] = ports.in1
m[16:32] = ports.in0
m = m.reshape((4, 8))
ports.c = m.to_circt()
class M1:
in1 = Input(dim(types.i32, 10))
@generator
def build(ports):
# CHECK: ValueError: Must specify either shape and dtype, or initialize from a value, but not both.
NDArray((10, 32), from_value=ports.in1, dtype=types.i1, name='m1')
class M1:
out = Output(dim(types.i32, 3, 3))
@generator
def build(ports):
m = NDArray((3, 3), dtype=types.i32)
for i in range(3):
for j in range(3):
m[i][j] = types.i32(i * 3 + j)
ports.out = m.to_circt()