wehub-resource-sync
155 lines
4.3 KiB
Python
155 lines
4.3 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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# ruff: noqa: F401
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import tvm
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import tvm.testing
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from tvm.script import ir as I
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from tvm.script import relax as R
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from tvm.script import tirx as T
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def test_simple():
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@I.ir_module
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class Before:
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@R.function
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def main():
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args = Before.func()
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return args[0]
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@R.function(private=True)
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def func() -> R.Tuple([R.Tensor, R.Tensor]):
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A = R.zeros([16, 16], "int32")
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B = R.ones([16, 16], "int32")
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return (A, B)
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@I.ir_module
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class Expected:
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@R.function
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def main():
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A = Expected.func()
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return A
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@R.function(private=True)
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def func() -> R.Tensor([16, 16], "int32"):
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A = R.zeros([16, 16], "int32")
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return A
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After = tvm.relax.transform.RemoveUnusedOutputs()(Before)
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tvm.ir.assert_structural_equal(After, Expected)
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def test_use_multiple_outputs():
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@I.ir_module
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class Before:
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@R.function
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def main():
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args = Before.func()
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return (args[0], args[2])
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@R.function(private=True)
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def func() -> R.Tuple([R.Tensor, R.Tensor, R.Tensor]):
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A = R.zeros([16, 16], "int32")
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B = R.ones([16, 16], "int32")
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C = R.zeros([32, 32], "int32")
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return (A, B, C)
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@I.ir_module
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class Expected:
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@R.function
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def main():
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args = Expected.func()
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return (args[0], args[1])
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@R.function(private=True)
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def func() -> R.Tuple([R.Tensor([16, 16], "int32"), R.Tensor([32, 32], "int32")]):
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A = R.zeros([16, 16], "int32")
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C = R.zeros([32, 32], "int32")
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return (A, C)
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After = tvm.relax.transform.RemoveUnusedOutputs()(Before)
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tvm.ir.assert_structural_equal(After, Expected)
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def test_multiple_call_sites():
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@I.ir_module
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class Before:
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@R.function
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def main_a():
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args = Before.func()
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return args[0]
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@R.function
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def main_b():
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args = Before.func()
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return args[2]
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@R.function(private=True)
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def func() -> R.Tuple([R.Tensor, R.Tensor, R.Tensor]):
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A = R.zeros([16, 16], "int32")
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B = R.ones([16, 16], "int32")
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C = R.zeros([32, 32], "int32")
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return (A, B, C)
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@I.ir_module
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class Expected:
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@R.function
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def main_a():
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args = Expected.func()
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return args[0]
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@R.function
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def main_b():
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args = Expected.func()
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return args[1]
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@R.function(private=True)
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def func() -> R.Tuple([R.Tensor([16, 16], "int32"), R.Tensor([32, 32], "int32")]):
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A = R.zeros([16, 16], "int32")
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C = R.zeros([32, 32], "int32")
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return (A, C)
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After = tvm.relax.transform.RemoveUnusedOutputs()(Before)
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tvm.ir.assert_structural_equal(After, Expected)
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def test_return_tuple():
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@I.ir_module
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class Before:
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@R.function
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def main(A: R.Tensor([16, 16], "int32")):
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B = R.add(A, A)
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out_tuple = Before.func(B)
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return out_tuple
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@R.function(private=True)
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def func(B: R.Tensor([16, 16], "int32")) -> R.Tuple(
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R.Tensor([16, 16], "int32"), R.Tensor([16, 16], "int32")
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):
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C = R.multiply(B, B)
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D = R.add(B, B)
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return (C, D)
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Expected = Before
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After = tvm.relax.transform.RemoveUnusedOutputs()(Before)
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tvm.ir.assert_structural_equal(After, Expected)
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if __name__ == "__main__":
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tvm.testing.main()
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