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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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# specific language governing permissions and limitations
# under the License.
import tvm
from tvm.ir import IRModule
from tvm import relay
from tvm.relay.transform import FastMath

def test_exp():
    x = relay.var("x", shape=(1, 16, 16, 16), dtype="float32")
    y = relay.exp(x)
    func = relay.Function([x], y)
    mod = tvm.IRModule.from_expr(func)

    fast_mod = FastMath()(mod)
    assert "fast_exp" in fast_mod.astext()

    # Check that FastMath option works for relay.build.
    with tvm.transform.PassContext(opt_level=3, required_pass=['FastMath']):
        fast_mod = relay.optimize(mod, target='llvm', params=None)
    assert "fast_exp" in fast_mod[0].astext()

def test_tanh():
    x = relay.var("x", shape=(1, 16, 16, 16), dtype="float32")
    y = relay.tanh(x)
    func = relay.Function([x], y)
    mod = tvm.IRModule.from_expr(func)

    fast_mod = FastMath()(mod)
    assert "fast_tanh" in fast_mod.astext()

    # Check that FastMath option works for relay.build.
    with tvm.transform.PassContext(opt_level=3, required_pass=['FastMath']):
        fast_mod = relay.optimize(mod, target='llvm', params=None)
    assert "fast_tanh" in fast_mod[0].astext()

if __name__ == "__main__":
    test_exp()
    test_tanh()

@@ -1877,16 +1877,512 @@
 text()%0A%0A
+def test_erf():%0A    x = relay.var(%22x%22, shape=(1, 16, 16, 16), dtype=%22float32%22)%0A    y = relay.erf(x)%0A    func = relay.Function(%5Bx%5D, y)%0A    mod = tvm.IRModule.from_expr(func)%0A%0A    fast_mod = FastMath()(mod)%0A    assert %22fast_erf%22 in fast_mod.astext()%0A%0A    # Check that FastMath option works for relay.build.%0A    with tvm.transform.PassContext(opt_level=3, required_pass=%5B'FastMath'%5D):%0A        fast_mod = relay.optimize(mod, target='llvm', params=None)%0A    assert %22fast_erf%22 in fast_mod%5B0%5D.astext()%0A%0A
 if __nam
@@ -2431,8 +2431,23 @@
 _tanh()%0A
+    test_erf()%0A

Add missing test for fast erf (#6058)