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[Bugfix] Preserve IRModule type definition and imports in NameMangleExtFuncs #8523

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Merged
comaniac merged 4 commits into from
Jul 29, 2021
Merged

[Bugfix] Preserve IRModule type definition and imports in NameMangleExtFuncs #8523

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301df56
bug fix and add tensorarray with partition pass test case
Jul 21, 2021
a95ce8a
change test function location and address comments
Jul 21, 2021
6510042
Update tests/python/relay/test_pass_partition_graph.py
Jul 21, 2021
2cc8b98
trigger CI
comaniac Jul 23, 2021
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2 changes: 1 addition & 1 deletion src/relay/transforms/partition_graph.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -509,7 +509,7 @@ class NameMangleExtFuncs : public MixedModeMutator {

// Walk the tree and mangle the functions. Then replace compiler functions
// with mangled functions in the module
IRModule new_module;
IRModule new_module = IRModule({}, module_->type_definitions, module_->Imports());
for (const auto& pair : glob_funcs) {
if (auto* fn = pair.second.as<FunctionNode>()) {
auto func = GetRef<Function>(fn);
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29 changes: 29 additions & 0 deletions tests/python/relay/test_pass_partition_graph.py
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Expand Up @@ -1439,6 +1439,34 @@ def Optimize(mod):
tvm.testing.assert_allclose(t0.body.data.numpy(), expected, rtol=1e-5, atol=1e-5)


def test_preserve_type_import():
"""Test to make sure type definition and imports are preserved during the BYOC pipeline."""
from tvm.relay.prelude import Prelude, StaticTensorArrayOps

def run(dtype, shape):
mod = tvm.IRModule()
p = Prelude(mod)
static_tensor_array_ops = StaticTensorArrayOps(p, dtype, shape)
static_tensor_array_ops.register()

tensor_array = p.get_global_var_static("tensor_array", dtype, shape)
tensor = p.get_tensor_ctor_static("tensor_constructor", dtype, shape)
write = p.get_global_var_static("tensor_array_write", dtype, shape)
gather = p.get_global_var_static("tensor_array_gather", dtype, shape)
v = relay.var("v")
indice = relay.var("indice")
init_tensor_array = tensor_array(relay.const(3))
tensor_array1 = write(init_tensor_array, relay.const(0), tensor(v))
tensor_array2 = write(tensor_array1, relay.const(1), tensor(v))
tensor_array3 = write(tensor_array2, relay.const(2), tensor(v))
out = gather(tensor_array3, indice)
mod["main"] = relay.Function([v, indice], out)
mod = transform.RemoveUnusedFunctions()(mod)
mod = transform.PartitionGraph()(mod)

run("float32", [2, 3])


if __name__ == "__main__":
test_multi_node_compiler()
test_extern_ccompiler_single_op()
Expand All @@ -1460,3 +1488,4 @@ def Optimize(mod):
test_flatten_tuple_output()
test_tuple_output_exec()
test_extern_opt()
test_static_tensor_array_gather_partition()