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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2022/05/25 22:38:17 UTC
[GitHub] [tvm] mehrdadh opened a new pull request, #11464: [MLF] Add support for multiple modules in Model Library Format
mehrdadh opened a new pull request, #11464:
URL: https://github.com/apache/tvm/pull/11464
Draft for testing in CI.
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[GitHub] [tvm] mehrdadh commented on a diff in pull request #11464: [MLF] Add support for multiple modules in Model Library Format
Posted by GitBox <gi...@apache.org>.
mehrdadh commented on code in PR #11464:
URL: https://github.com/apache/tvm/pull/11464#discussion_r897356445
##########
python/tvm/micro/model_library_format.py:
##########
@@ -67,56 +69,75 @@ def generate_c_interface_header(
EPHEMERAL_MODULE_TYPE_KEYS = ("metadata_module",)
-def _populate_codegen_dir(mod, codegen_dir: str, module_name: str = None):
+def _populate_codegen_dir(
+ mods: Union[
+ typing.List[executor_factory.ExecutorFactoryModule], typing.List[tvm.runtime.Module]
Review Comment:
actually since we are passing modules like `build_module.OperatorModule` and `tvm.support.FrontendTestModule` I changed it back to tvm.runtime.Module
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[GitHub] [tvm] areusch commented on a diff in pull request #11464: [MLF] Add support for multiple modules in Model Library Format
Posted by GitBox <gi...@apache.org>.
areusch commented on code in PR #11464:
URL: https://github.com/apache/tvm/pull/11464#discussion_r900355444
##########
tests/python/unittest/test_micro_model_library_format.py:
##########
@@ -95,8 +101,35 @@ def test_export_operator_model_library_format():
assert tir_f.read() == str(ir_mod)
+@tvm.testing.requires_micro
+def test_export_multiple_operator_model_library_format():
+ target = tvm.target.target.micro("host")
+ with tvm.transform.PassContext(opt_level=3, config={"tir.disable_vectorize": True}):
+ A = tvm.te.placeholder((2,), dtype="int8")
+ B = tvm.te.placeholder((1,), dtype="int8")
+ C = tvm.te.compute(A.shape, lambda i: A[i] + B[0], name="C")
+ sched = tvm.te.create_schedule(C.op)
+ mod = tvm.build(
+ sched,
+ [A, B, C],
+ tvm.target.Target(target, target),
+ runtime=Runtime("crt", {"system-lib": True}),
+ name="add",
+ )
+
+ temp_dir = utils.tempdir()
+ mlf_tar_path = temp_dir.relpath("lib.tar")
+
+ with pytest.raises(RuntimeError) as exc:
+ micro.export_model_library_format([mod, mod], mlf_tar_path)
+
+ assert str(exc.exception) == ("Multiple operator is not supported.")
Review Comment:
yeah can you add another? it seems like passing duplicate modules is a separate error
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[GitHub] [tvm] mehrdadh commented on a diff in pull request #11464: [MLF] Add support for multiple modules in Model Library Format
Posted by GitBox <gi...@apache.org>.
mehrdadh commented on code in PR #11464:
URL: https://github.com/apache/tvm/pull/11464#discussion_r887026583
##########
python/tvm/micro/model_library_format.py:
##########
@@ -449,47 +498,53 @@ def _eval_shape(param_name, buffer_shape):
return memory_map
-def _export_operator_model_library_format(mod: build_module.OperatorModule, tempdir):
+def _export_operator_model_library_format(
+ mods: typing.List[build_module.OperatorModule], tempdir: pathlib.Path
Review Comment:
yeah makes sense.
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[GitHub] [tvm] mkatanbaf commented on pull request #11464: [MLF] Add support for multiple modules in Model Library Format
Posted by GitBox <gi...@apache.org>.
mkatanbaf commented on PR #11464:
URL: https://github.com/apache/tvm/pull/11464#issuecomment-1157878888
@areusch sure, working on it now!
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[GitHub] [tvm] areusch commented on a diff in pull request #11464: [MLF] Add support for multiple modules in Model Library Format
Posted by GitBox <gi...@apache.org>.
areusch commented on code in PR #11464:
URL: https://github.com/apache/tvm/pull/11464#discussion_r882219117
##########
python/tvm/micro/model_library_format.py:
##########
@@ -449,47 +498,53 @@ def _eval_shape(param_name, buffer_shape):
return memory_map
-def _export_operator_model_library_format(mod: build_module.OperatorModule, tempdir):
+def _export_operator_model_library_format(
+ mods: typing.List[build_module.OperatorModule], tempdir: pathlib.Path
Review Comment:
i wonder if for operator MLF, we should just not allow multiple module export? if they don't have a mod_name, then we can't really identify them or namespace them properly. wdyt?
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[GitHub] [tvm] areusch commented on a diff in pull request #11464: [MLF] Add support for multiple modules in Model Library Format
Posted by GitBox <gi...@apache.org>.
areusch commented on code in PR #11464:
URL: https://github.com/apache/tvm/pull/11464#discussion_r894786749
##########
python/tvm/micro/contrib/stm32/emitter.py:
##########
@@ -482,8 +482,18 @@ def parse_library_format(self, model_library_format_path, quantization=None):
with tarfile.TarFile(model_library_format_path) as f:
f.extractall(extract_path)
+ with open(os.path.join(extract_path, "metadata.json")) as metadata_f:
+ metadata = json.load(metadata_f)
+
+ all_module_names = []
+ for name in metadata["modules"].keys():
+ all_module_names.append(name)
+ assert len(all_module_names) == 1, "Multiple modules is not supported."
Review Comment:
i think you could simplify to just len(metadata["modules"])
##########
python/tvm/micro/model_library_format.py:
##########
@@ -67,56 +69,75 @@ def generate_c_interface_header(
EPHEMERAL_MODULE_TYPE_KEYS = ("metadata_module",)
-def _populate_codegen_dir(mod, codegen_dir: str, module_name: str = None):
+def _populate_codegen_dir(
+ mods: Union[
+ typing.List[executor_factory.ExecutorFactoryModule], typing.List[tvm.runtime.Module]
Review Comment:
how come tvm.runtime.Module is allowed? also, do we want `List[Union[ExecutorFactoryModule, tvm.runtime.Module]]`?
##########
tests/python/unittest/test_micro_model_library_format.py:
##########
@@ -95,8 +101,35 @@ def test_export_operator_model_library_format():
assert tir_f.read() == str(ir_mod)
+@tvm.testing.requires_micro
+def test_export_multiple_operator_model_library_format():
+ target = tvm.target.target.micro("host")
+ with tvm.transform.PassContext(opt_level=3, config={"tir.disable_vectorize": True}):
+ A = tvm.te.placeholder((2,), dtype="int8")
+ B = tvm.te.placeholder((1,), dtype="int8")
+ C = tvm.te.compute(A.shape, lambda i: A[i] + B[0], name="C")
+ sched = tvm.te.create_schedule(C.op)
+ mod = tvm.build(
+ sched,
+ [A, B, C],
+ tvm.target.Target(target, target),
+ runtime=Runtime("crt", {"system-lib": True}),
+ name="add",
+ )
+
+ temp_dir = utils.tempdir()
+ mlf_tar_path = temp_dir.relpath("lib.tar")
+
+ with pytest.raises(RuntimeError) as exc:
+ micro.export_model_library_format([mod, mod], mlf_tar_path)
+
+ assert str(exc.exception) == ("Multiple operator is not supported.")
Review Comment:
it seems like in this case the error is that you've passed duplicate `mod`, right? maybe we should be checking for that or de-duping?
##########
tests/python/unittest/test_micro_model_library_format.py:
##########
@@ -439,5 +474,140 @@ def test_export_byoc_c_module():
]
+@tvm.testing.requires_micro
+def test_multiple_relay_modules_same_module_name():
+ mod = get_conv2d_relay_module()
+
+ executor = Executor("graph")
+ runtime = Runtime("crt")
+ target = tvm.target.target.micro("host")
+
+ with tvm.transform.PassContext(opt_level=3, config={"tir.disable_vectorize": True}):
+ factory1 = tvm.relay.build(mod, target, runtime=runtime, executor=executor, mod_name="mod")
+ factory2 = tvm.relay.build(mod, target, runtime=runtime, executor=executor, mod_name="mod")
+
+ temp_dir = utils.tempdir()
+ mlf_tar_path = temp_dir.relpath("lib.tar")
+
+ with pytest.raises(AssertionError, match="Multiple modules should have unique names"):
+ micro.export_model_library_format([factory1, factory2], mlf_tar_path)
+
+
+@tvm.testing.requires_micro
+def test_multiple_relay_modules_graph():
+ mod = get_conv2d_relay_module()
+
+ executor = Executor("graph")
+ runtime = Runtime("crt")
+ target = tvm.target.target.micro("host")
+
+ with tvm.transform.PassContext(opt_level=3, config={"tir.disable_vectorize": True}):
+ factory1 = tvm.relay.build(mod, target, runtime=runtime, executor=executor, mod_name="mod1")
+ factory2 = tvm.relay.build(mod, target, runtime=runtime, executor=executor, mod_name="mod2")
+
+ temp_dir = utils.tempdir()
+ mlf_tar_path = temp_dir.relpath("lib.tar")
+ micro.export_model_library_format([factory1, factory2], mlf_tar_path)
+
+ with tarfile.open(mlf_tar_path, "r:*") as tf:
+ tar_members = [ti.name for ti in tf.getmembers()]
+ print("tar members", tar_members)
+ assert "./metadata.json" in tar_members
+ assert "./codegen/host/src/mod1_lib0.c" in tar_members
+ assert "./codegen/host/src/mod2_lib0.c" in tar_members
+
+ with tf.extractfile("./metadata.json") as f:
+ metadata = json.load(f)
+ mod2_main_md = metadata["modules"]["mod2"]["memory"]["functions"]["main"]
+ assert mod2_main_md == [
+ {
+ "constants_size_bytes": 0,
+ "device": 1,
+ "io_size_bytes": 143960,
+ "workspace_size_bytes": 158088,
+ }
+ ]
+ assert metadata["modules"]["mod1"]["model_name"] == "mod1"
+ assert metadata["modules"]["mod2"]["model_name"] == "mod2"
+
+
+@tvm.testing.requires_micro
+def test_multiple_relay_modules_c():
+ mod = get_conv2d_relay_module()
+
+ executor = Executor("aot", {"unpacked-api": True, "interface-api": "c"})
+ runtime = Runtime("crt")
+ target = tvm.target.target.micro("host")
+
+ with tvm.transform.PassContext(opt_level=3, config={"tir.disable_vectorize": True}):
+ factory1 = tvm.relay.build(mod, target, runtime=runtime, executor=executor, mod_name="mod1")
+ factory2 = tvm.relay.build(mod, target, runtime=runtime, executor=executor, mod_name="mod2")
+
+ temp_dir = utils.tempdir()
+ mlf_tar_path = temp_dir.relpath("lib.tar")
+
+ micro.export_model_library_format([factory1, factory2], mlf_tar_path)
+
+ tf = tarfile.open(mlf_tar_path)
+
+ extract_dir = temp_dir.relpath("extract")
+ os.mkdir(extract_dir)
+ tf.extractall(extract_dir)
+
+ assert os.path.exists(os.path.join(extract_dir, "codegen", "host", "src", "mod1_lib0.c"))
+ assert os.path.exists(os.path.join(extract_dir, "codegen", "host", "src", "mod1_lib1.c"))
+ assert os.path.exists(os.path.join(extract_dir, "codegen", "host", "src", "mod2_lib0.c"))
+ assert os.path.exists(os.path.join(extract_dir, "codegen", "host", "src", "mod2_lib1.c"))
+
+ assert os.path.exists(os.path.join(extract_dir, "codegen", "host", "include", "tvmgen_mod1.h"))
+ assert os.path.exists(os.path.join(extract_dir, "codegen", "host", "include", "tvmgen_mod2.h"))
+
+ # check CRT runtime directory
+ assert os.path.exists(os.path.join(extract_dir, "runtime"))
+
+
+@tvm.testing.requires_micro
+def test_multiple_relay_modules_aot_graph():
Review Comment:
do we need to test mixing the executor styles? i think it's prob legit, but just wanted to understand where this is providing test coverage.
##########
python/tvm/micro/model_library_format.py:
##########
@@ -24,6 +24,7 @@
import re
import tarfile
import typing
+from typing import Union
Review Comment:
i think we should unify on style here (either also import List, etc) or just typing.
##########
python/tvm/micro/model_library_format.py:
##########
@@ -67,56 +69,75 @@ def generate_c_interface_header(
EPHEMERAL_MODULE_TYPE_KEYS = ("metadata_module",)
-def _populate_codegen_dir(mod, codegen_dir: str, module_name: str = None):
+def _populate_codegen_dir(
+ mods: Union[
+ typing.List[executor_factory.ExecutorFactoryModule], typing.List[tvm.runtime.Module]
+ ],
+ codegen_dir: str,
+):
"""Populate the codegen sub-directory as part of a Model Library Format export.
Parameters
----------
- mod : tvm.runtime.Module
- Module which should be written to codegen_dir.
+ mods : List[tvm.relay.backend.executor_factory.ExecutorFactoryModule], List[tvm.runtime.Module]
+ A list of the return value of tvm.relay.build, which
+ will be exported into Model Library Format.
codegen_dir : str
Path to the codegen directory on disk.
module_name: Optional[str]
Name used to prefix the generated source files
"""
- dso_modules = mod._collect_dso_modules()
- non_dso_modules = mod._collect_from_import_tree(lambda m: m not in dso_modules)
-
- # Filter ephemeral modules which cannot be exported.
- dso_modules = [m for m in dso_modules if m.type_key not in EPHEMERAL_MODULE_TYPE_KEYS]
- non_dso_modules = [m for m in non_dso_modules if m.type_key not in EPHEMERAL_MODULE_TYPE_KEYS]
+ dso_modules = []
+ for mod in mods:
+ if isinstance(mod, executor_factory.ExecutorFactoryModule):
+ lib = mod.lib
+ elif isinstance(mod, tvm.runtime.Module):
Review Comment:
add `else` block and raise error
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[GitHub] [tvm] areusch commented on pull request #11464: [MLF] Add support for multiple modules in Model Library Format
Posted by GitBox <gi...@apache.org>.
areusch commented on PR #11464:
URL: https://github.com/apache/tvm/pull/11464#issuecomment-1157000964
@mkatanbaf could you try this out and verify it's working for you?
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[GitHub] [tvm] mehrdadh merged pull request #11464: [MLF] Add support for multiple modules in Model Library Format
Posted by GitBox <gi...@apache.org>.
mehrdadh merged PR #11464:
URL: https://github.com/apache/tvm/pull/11464
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[GitHub] [tvm] mehrdadh commented on a diff in pull request #11464: [MLF] Add support for multiple modules in Model Library Format
Posted by GitBox <gi...@apache.org>.
mehrdadh commented on code in PR #11464:
URL: https://github.com/apache/tvm/pull/11464#discussion_r900379365
##########
tests/python/unittest/test_micro_model_library_format.py:
##########
@@ -95,8 +101,35 @@ def test_export_operator_model_library_format():
assert tir_f.read() == str(ir_mod)
+@tvm.testing.requires_micro
+def test_export_multiple_operator_model_library_format():
+ target = tvm.target.target.micro("host")
+ with tvm.transform.PassContext(opt_level=3, config={"tir.disable_vectorize": True}):
+ A = tvm.te.placeholder((2,), dtype="int8")
+ B = tvm.te.placeholder((1,), dtype="int8")
+ C = tvm.te.compute(A.shape, lambda i: A[i] + B[0], name="C")
+ sched = tvm.te.create_schedule(C.op)
+ mod = tvm.build(
+ sched,
+ [A, B, C],
+ tvm.target.Target(target, target),
+ runtime=Runtime("crt", {"system-lib": True}),
+ name="add",
+ )
+
+ temp_dir = utils.tempdir()
+ mlf_tar_path = temp_dir.relpath("lib.tar")
+
+ with pytest.raises(RuntimeError) as exc:
+ micro.export_model_library_format([mod, mod], mlf_tar_path)
+
+ assert str(exc.exception) == ("Multiple operator is not supported.")
Review Comment:
sure, will do a follow up PR. thanks!
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[GitHub] [tvm] mehrdadh commented on a diff in pull request #11464: [MLF] Add support for multiple modules in Model Library Format
Posted by GitBox <gi...@apache.org>.
mehrdadh commented on code in PR #11464:
URL: https://github.com/apache/tvm/pull/11464#discussion_r897143785
##########
python/tvm/micro/model_library_format.py:
##########
@@ -24,6 +24,7 @@
import re
import tarfile
import typing
+from typing import Union
Review Comment:
done.
##########
python/tvm/micro/contrib/stm32/emitter.py:
##########
@@ -482,8 +482,18 @@ def parse_library_format(self, model_library_format_path, quantization=None):
with tarfile.TarFile(model_library_format_path) as f:
f.extractall(extract_path)
+ with open(os.path.join(extract_path, "metadata.json")) as metadata_f:
+ metadata = json.load(metadata_f)
+
+ all_module_names = []
+ for name in metadata["modules"].keys():
+ all_module_names.append(name)
+ assert len(all_module_names) == 1, "Multiple modules is not supported."
Review Comment:
done
##########
tests/python/unittest/test_micro_model_library_format.py:
##########
@@ -95,8 +101,35 @@ def test_export_operator_model_library_format():
assert tir_f.read() == str(ir_mod)
+@tvm.testing.requires_micro
+def test_export_multiple_operator_model_library_format():
+ target = tvm.target.target.micro("host")
+ with tvm.transform.PassContext(opt_level=3, config={"tir.disable_vectorize": True}):
+ A = tvm.te.placeholder((2,), dtype="int8")
+ B = tvm.te.placeholder((1,), dtype="int8")
+ C = tvm.te.compute(A.shape, lambda i: A[i] + B[0], name="C")
+ sched = tvm.te.create_schedule(C.op)
+ mod = tvm.build(
+ sched,
+ [A, B, C],
+ tvm.target.Target(target, target),
+ runtime=Runtime("crt", {"system-lib": True}),
+ name="add",
+ )
+
+ temp_dir = utils.tempdir()
+ mlf_tar_path = temp_dir.relpath("lib.tar")
+
+ with pytest.raises(RuntimeError) as exc:
+ micro.export_model_library_format([mod, mod], mlf_tar_path)
+
+ assert str(exc.exception) == ("Multiple operator is not supported.")
Review Comment:
No I wanted to simply check the case where we pass multiple operator modules. I can add another module with different name to make it more obvious. thoughts?
##########
python/tvm/micro/model_library_format.py:
##########
@@ -67,56 +69,75 @@ def generate_c_interface_header(
EPHEMERAL_MODULE_TYPE_KEYS = ("metadata_module",)
-def _populate_codegen_dir(mod, codegen_dir: str, module_name: str = None):
+def _populate_codegen_dir(
+ mods: Union[
+ typing.List[executor_factory.ExecutorFactoryModule], typing.List[tvm.runtime.Module]
+ ],
+ codegen_dir: str,
+):
"""Populate the codegen sub-directory as part of a Model Library Format export.
Parameters
----------
- mod : tvm.runtime.Module
- Module which should be written to codegen_dir.
+ mods : List[tvm.relay.backend.executor_factory.ExecutorFactoryModule], List[tvm.runtime.Module]
+ A list of the return value of tvm.relay.build, which
+ will be exported into Model Library Format.
codegen_dir : str
Path to the codegen directory on disk.
module_name: Optional[str]
Name used to prefix the generated source files
"""
- dso_modules = mod._collect_dso_modules()
- non_dso_modules = mod._collect_from_import_tree(lambda m: m not in dso_modules)
-
- # Filter ephemeral modules which cannot be exported.
- dso_modules = [m for m in dso_modules if m.type_key not in EPHEMERAL_MODULE_TYPE_KEYS]
- non_dso_modules = [m for m in non_dso_modules if m.type_key not in EPHEMERAL_MODULE_TYPE_KEYS]
+ dso_modules = []
+ for mod in mods:
+ if isinstance(mod, executor_factory.ExecutorFactoryModule):
+ lib = mod.lib
+ elif isinstance(mod, tvm.runtime.Module):
Review Comment:
done
##########
python/tvm/micro/model_library_format.py:
##########
@@ -67,56 +69,75 @@ def generate_c_interface_header(
EPHEMERAL_MODULE_TYPE_KEYS = ("metadata_module",)
-def _populate_codegen_dir(mod, codegen_dir: str, module_name: str = None):
+def _populate_codegen_dir(
+ mods: Union[
+ typing.List[executor_factory.ExecutorFactoryModule], typing.List[tvm.runtime.Module]
Review Comment:
I changed it to `build_module.OperatorModule`
I think Union of List is correct because the input could be Union of two different list, but not a list of two different type
##########
tests/python/unittest/test_micro_model_library_format.py:
##########
@@ -439,5 +474,140 @@ def test_export_byoc_c_module():
]
+@tvm.testing.requires_micro
+def test_multiple_relay_modules_same_module_name():
+ mod = get_conv2d_relay_module()
+
+ executor = Executor("graph")
+ runtime = Runtime("crt")
+ target = tvm.target.target.micro("host")
+
+ with tvm.transform.PassContext(opt_level=3, config={"tir.disable_vectorize": True}):
+ factory1 = tvm.relay.build(mod, target, runtime=runtime, executor=executor, mod_name="mod")
+ factory2 = tvm.relay.build(mod, target, runtime=runtime, executor=executor, mod_name="mod")
+
+ temp_dir = utils.tempdir()
+ mlf_tar_path = temp_dir.relpath("lib.tar")
+
+ with pytest.raises(AssertionError, match="Multiple modules should have unique names"):
+ micro.export_model_library_format([factory1, factory2], mlf_tar_path)
+
+
+@tvm.testing.requires_micro
+def test_multiple_relay_modules_graph():
+ mod = get_conv2d_relay_module()
+
+ executor = Executor("graph")
+ runtime = Runtime("crt")
+ target = tvm.target.target.micro("host")
+
+ with tvm.transform.PassContext(opt_level=3, config={"tir.disable_vectorize": True}):
+ factory1 = tvm.relay.build(mod, target, runtime=runtime, executor=executor, mod_name="mod1")
+ factory2 = tvm.relay.build(mod, target, runtime=runtime, executor=executor, mod_name="mod2")
+
+ temp_dir = utils.tempdir()
+ mlf_tar_path = temp_dir.relpath("lib.tar")
+ micro.export_model_library_format([factory1, factory2], mlf_tar_path)
+
+ with tarfile.open(mlf_tar_path, "r:*") as tf:
+ tar_members = [ti.name for ti in tf.getmembers()]
+ print("tar members", tar_members)
+ assert "./metadata.json" in tar_members
+ assert "./codegen/host/src/mod1_lib0.c" in tar_members
+ assert "./codegen/host/src/mod2_lib0.c" in tar_members
+
+ with tf.extractfile("./metadata.json") as f:
+ metadata = json.load(f)
+ mod2_main_md = metadata["modules"]["mod2"]["memory"]["functions"]["main"]
+ assert mod2_main_md == [
+ {
+ "constants_size_bytes": 0,
+ "device": 1,
+ "io_size_bytes": 143960,
+ "workspace_size_bytes": 158088,
+ }
+ ]
+ assert metadata["modules"]["mod1"]["model_name"] == "mod1"
+ assert metadata["modules"]["mod2"]["model_name"] == "mod2"
+
+
+@tvm.testing.requires_micro
+def test_multiple_relay_modules_c():
+ mod = get_conv2d_relay_module()
+
+ executor = Executor("aot", {"unpacked-api": True, "interface-api": "c"})
+ runtime = Runtime("crt")
+ target = tvm.target.target.micro("host")
+
+ with tvm.transform.PassContext(opt_level=3, config={"tir.disable_vectorize": True}):
+ factory1 = tvm.relay.build(mod, target, runtime=runtime, executor=executor, mod_name="mod1")
+ factory2 = tvm.relay.build(mod, target, runtime=runtime, executor=executor, mod_name="mod2")
+
+ temp_dir = utils.tempdir()
+ mlf_tar_path = temp_dir.relpath("lib.tar")
+
+ micro.export_model_library_format([factory1, factory2], mlf_tar_path)
+
+ tf = tarfile.open(mlf_tar_path)
+
+ extract_dir = temp_dir.relpath("extract")
+ os.mkdir(extract_dir)
+ tf.extractall(extract_dir)
+
+ assert os.path.exists(os.path.join(extract_dir, "codegen", "host", "src", "mod1_lib0.c"))
+ assert os.path.exists(os.path.join(extract_dir, "codegen", "host", "src", "mod1_lib1.c"))
+ assert os.path.exists(os.path.join(extract_dir, "codegen", "host", "src", "mod2_lib0.c"))
+ assert os.path.exists(os.path.join(extract_dir, "codegen", "host", "src", "mod2_lib1.c"))
+
+ assert os.path.exists(os.path.join(extract_dir, "codegen", "host", "include", "tvmgen_mod1.h"))
+ assert os.path.exists(os.path.join(extract_dir, "codegen", "host", "include", "tvmgen_mod2.h"))
+
+ # check CRT runtime directory
+ assert os.path.exists(os.path.join(extract_dir, "runtime"))
+
+
+@tvm.testing.requires_micro
+def test_multiple_relay_modules_aot_graph():
Review Comment:
I think there could be cases where someone build a graph along with an AOT executor. Fundamentally I don't see a reason that we cannot support it.
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