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# to you under the Apache License, Version 2.0 (the
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#
# http://www.apache.org/licenses/LICENSE-2.0
#
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import numpy as np
import pytest
import tvm
from tvm import te
from tvm import relay
from tvm.relay import transform
def test_basic():
mod = tvm.IRModule()
x2 = relay.var("x2", shape=(10, 5))
y2 = relay.var("y2", shape=(1, 5))
level2_func = relay.Function([x2, y2], relay.op.add(x2, y2))
x1 = relay.var("x1", shape=(10, 5))
y1 = relay.var("y1", shape=(1, 5))
level1_func = relay.Function([x1, y1], level2_func(x1, y1))
mod["main"] = level1_func
mod = relay.transform.InferType()(mod)
new_mod = transform.LambdaLift()(mod)
assert len(new_mod.functions) == 2
def test_closure():
mod = tvm.IRModule()
x = relay.var("x", shape=(2,))
y = relay.var("y", shape=(2,))
inner_func = relay.Function([x], x + y)
outer_func = relay.Function([y], inner_func)
clo = outer_func(relay.ones(shape=(2,), dtype="float32"))
mod["main"] = relay.Function([], relay.Call(clo, [relay.zeros(shape=(2,), dtype="float32")]))
mod = relay.transform.InferType()(mod)
new_mod = transform.LambdaLift()(mod)
assert len(new_mod.functions) == 3
def test_recursive():
mod = tvm.IRModule()
x = relay.var("x", shape=(2,))
i = relay.var("i", shape=(), dtype="int32")
s = relay.var("s", shape=(2,))
cond = i < relay.const(10, dtype="int32")
loop = relay.var("while_loop")
sb = relay.scope_builder.ScopeBuilder()
with sb.if_scope(cond):
ii = i + relay.const(1, dtype="int32")
ss = s + x
sb.ret(loop(ii, ss))
with sb.else_scope():
sb.ret(s)
func = relay.Function([i, s], sb.get())
ret = relay.Let(
loop, func, loop(relay.const(0, dtype="int32"), relay.zeros(shape=(2,), dtype="float32"))
)
mod["main"] = relay.Function([x], ret)
mod = relay.transform.InferType()(mod)
new_mod = transform.LambdaLift()(mod)
assert len(new_mod.functions) == 2
if __name__ == "__main__":
tvm.testing.main()