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import halide as hl
x = hl.Var("x")
y = hl.Var("y")
c = hl.Var("c")
# Note that this Generator explicitly inherits from hl.Generator;
# this isn't necessary (the decorator will inject the base class for you),
# but is allowed for better compatibility with static type checkers such
# as pytype. Thus, this is left here as a test to verify that this option
# remains functional.
@hl.generator(name="complexpy")
class ComplexPy(hl.Generator):
vectorize = hl.GeneratorParam(True)
extra_input_name = hl.GeneratorParam("")
typed_buffer_input = hl.InputBuffer(hl.UInt(8), 3)
untyped_buffer_input = hl.InputBuffer(None, 3)
simple_input = hl.InputBuffer(None, 3)
float_arg = hl.InputScalar(hl.Float(32))
# We can use `int` as an alias for `hl.Int(32)` if we like
int_arg = hl.InputScalar(int)
simple_output = hl.OutputBuffer(hl.Float(32), 3)
tuple_output = hl.OutputBuffer(None, 3)
typed_buffer_output = hl.OutputBuffer(hl.Float(32), 3)
untyped_buffer_output = hl.OutputBuffer(None, None)
static_compiled_buffer_output = hl.OutputBuffer(hl.UInt(8), 3)
scalar_output = hl.OutputScalar(hl.Float(32))
def configure(self):
g = self
if len(g.extra_input_name):
g.add_input(g.extra_input_name, hl.InputBuffer(hl.UInt(16), 3))
g.add_output("extra_output", hl.OutputBuffer(hl.Float(64), 2))
def generate(self):
g = self
g.simple_output[x, y, c] = hl.f32(g.simple_input[x, y, c])
g.typed_buffer_output[x, y, c] = hl.f32(g.typed_buffer_input[x, y, c])
g.untyped_buffer_output[x, y, c] = hl.cast(
g.untyped_buffer_output.type(),
g.untyped_buffer_input[x, y, c],
)
intermediate = hl.Func("intermediate")
intermediate[x, y, c] = g.simple_input[x, y, c] * g.float_arg
g.tuple_output[x, y, c] = (
intermediate[x, y, c],
intermediate[x, y, c] + g.int_arg,
)
# This should be compiled into the Generator product itself,
# and not produce another input for the Stub or AOT filter.
static_compiled_buffer = hl.Buffer(hl.UInt(8), [4, 4, 1])
for xx in range(4):
for yy in range(4):
for cc in range(1):
static_compiled_buffer[xx, yy, cc] = xx + yy + cc + 42
g.static_compiled_buffer_output[x, y, c] = static_compiled_buffer[x, y, c]
extra_input = getattr(g, g.extra_input_name, None)
if extra_input:
g.extra_output[x, y] = hl.f64(extra_input[x, y, 0] + 1)
else:
g.extra_output[x, y] = hl.f64(0)
g.scalar_output[()] = g.float_arg + g.int_arg
(
intermediate.compute_at(g.tuple_output, y)
.specialize(g.vectorize)
.vectorize(x, g.natural_vector_size(hl.Float(32)))
)
if __name__ == "__main__":
hl.main()
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