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Fix tests. #2277

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Fix tests. #2277

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54 changes: 32 additions & 22 deletions exir/backend/test/test_backends_lifted.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1012,17 +1012,19 @@ def false_fn(x, y):
x = x - y
return x

def f(x, y):
x = x + y
x = control_flow.cond(x[0][0] == 1, true_fn, false_fn, [x, y])
x = x - y
return x
class Module(torch.nn.Module):
def forward(self, x, y):
x = x + y
x = control_flow.cond(x[0][0] == 1, true_fn, false_fn, [x, y])
x = x - y
return x

f = Module()
inputs = (torch.ones(2, 2), torch.ones(2, 2))
orig_res = f(*inputs)
orig = to_edge(
export(
torch.export.WrapperModule(f),
f,
inputs,
)
)
Expand Down Expand Up @@ -1066,15 +1068,17 @@ def map_fn(x, y):
x = x + y
return x

def f(xs, y):
y = torch.mm(y, y)
return control_flow.map(map_fn, xs, y)
class Module(torch.nn.Module):
def forward(self, xs, y):
y = torch.mm(y, y)
return control_flow.map(map_fn, xs, y)

f = Module()
inputs = (torch.ones(2, 2), torch.ones(2, 2))
orig_res = f(*inputs)
orig = to_edge(
export(
torch.export.WrapperModule(f),
f,
inputs,
)
)
Expand Down Expand Up @@ -1132,9 +1136,10 @@ def map_fn(x, pred1, pred2, y):
x = x + y
return x.sin()

def f(xs, pred1, pred2, y):
y = torch.mm(y, y)
return control_flow.map(map_fn, xs, pred1, pred2, y)
class Module(torch.nn.Module):
def forward(self, xs, pred1, pred2, y):
y = torch.mm(y, y)
return control_flow.map(map_fn, xs, pred1, pred2, y)

inputs = (
torch.ones(2, 2),
Expand All @@ -1143,10 +1148,11 @@ def f(xs, pred1, pred2, y):
torch.ones(2, 2),
)

f = Module()
orig_res = f(*inputs)
orig = to_edge(
export(
torch.export.WrapperModule(f),
f,
inputs,
)
)
Expand Down Expand Up @@ -1205,12 +1211,14 @@ def f(xs, pred1, pred2, y):
)

def test_list_input(self):
def f(x: List[torch.Tensor]):
y = x[0] + x[1]
return y
class Module(torch.nn.Module):
def forward(self, x: List[torch.Tensor]):
y = x[0] + x[1]
return y

f = Module()
inputs = ([torch.randn(2, 2), torch.randn(2, 2)],)
edge_prog = to_edge(export(torch.export.WrapperModule(f), inputs))
edge_prog = to_edge(export(f, inputs))
lowered_gm = to_backend(
BackendWithCompilerDemo.__name__, edge_prog.exported_program(), []
)
Expand All @@ -1227,12 +1235,14 @@ def forward(self, x: List[torch.Tensor]):
gm.exported_program().module()(*inputs)

def test_dict_input(self):
def f(x: Dict[str, torch.Tensor]):
y = x["a"] + x["b"]
return y
class Module(torch.nn.Module):
def forward(self, x: Dict[str, torch.Tensor]):
y = x["a"] + x["b"]
return y

f = Module()
inputs = ({"a": torch.randn(2, 2), "b": torch.randn(2, 2)},)
edge_prog = to_edge(export(torch.export.WrapperModule(f), inputs))
edge_prog = to_edge(export(f, inputs))
lowered_gm = to_backend(
BackendWithCompilerDemo.__name__, edge_prog.exported_program(), []
)
Expand Down
12 changes: 11 additions & 1 deletion exir/program/test/test_program.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,16 @@

from torch.library import impl, Library


class WrapperModule(torch.nn.Module):
def __init__(self, fn):
super().__init__()
self.fn = fn

def forward(self, *args, **kwargs):
return self.fn(*args, **kwargs)


lib = Library("test_op", "DEF")

# Fake a operator for testing.
Expand Down Expand Up @@ -374,7 +384,7 @@ def _test_edge_dialect_verifier(self, callable, validate_ir=True):
two,
)
if not isinstance(callable, torch.nn.Module):
callable = torch.export.WrapperModule(callable)
callable = WrapperModule(callable)

exported_foo = export(callable, inputs)
_ = to_edge(exported_foo, compile_config=edge_compile_config)
Expand Down