wehub-resource-sync
119 lines
4.1 KiB
Python
119 lines
4.1 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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from collections.abc import Callable
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import pytest
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import tvm
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import tvm.script
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import tvm.testing
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from tvm import topi
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from tvm.relax.transform import LegalizeOps
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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_static_shape(name: str, relax_op: Callable, te_func: Callable, dtype: str):
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@tvm.script.ir_module
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class Before:
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@R.function
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def main(x: R.Tensor((2, 3), dtype)):
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nonlocal dtype
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gv = relax_op(x)
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return gv
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@tvm.script.ir_module
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class Expected:
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@R.function
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def main(x: R.Tensor((2, 3), dtype)):
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nonlocal dtype
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gv = R.emit_te(te_func, x, primfunc_name_hint=f"tir_{name}")
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return gv
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mod = LegalizeOps()(Before)
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tvm.ir.assert_structural_equal(mod, Expected)
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def _test_symbolic_shape(name: str, relax_op: Callable, te_func: Callable, dtype: str):
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@tvm.script.ir_module
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class Before:
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@R.function
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def main(x: R.Tensor(("m", "n"), dtype)):
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nonlocal dtype
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gv = relax_op(x)
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return gv
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@tvm.script.ir_module
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class Expected:
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@R.function
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def main(x: R.Tensor(("m", "n"), dtype)):
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nonlocal dtype
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gv = R.emit_te(te_func, x, primfunc_name_hint=f"tir_{name}")
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return gv
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mod = LegalizeOps()(Before)
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tvm.ir.assert_structural_equal(mod, Expected)
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@pytest.mark.parametrize(
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"name, relax_op, te_func, dtype",
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[
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("abs", R.abs, topi.abs, "float32"),
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("acos", R.acos, topi.acos, "float32"),
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("acosh", R.acosh, topi.acosh, "float32"),
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("asin", R.asin, topi.asin, "float32"),
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("asinh", R.asinh, topi.asinh, "float32"),
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("atan", R.atan, topi.atan, "float32"),
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("atanh", R.atanh, topi.atanh, "float32"),
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("ceil", R.ceil, topi.ceil, "float32"),
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("ceil", R.ceil, topi.identity, "int32"),
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("cos", R.cos, topi.cos, "float32"),
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("cosh", R.cosh, topi.cosh, "float32"),
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("exp", R.exp, topi.exp, "float32"),
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("floor", R.floor, topi.floor, "float32"),
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("floor", R.floor, topi.identity, "int32"),
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("isfinite", R.isfinite, topi.isfinite, "float32"),
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("isinf", R.isinf, topi.isinf, "float32"),
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("isnan", R.isnan, topi.isnan, "float32"),
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("log", R.log, topi.log, "float32"),
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("negative", R.negative, topi.negative, "float32"),
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("round", R.round, topi.round, "float32"),
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("round", R.round, topi.identity, "int32"),
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("rsqrt", R.rsqrt, topi.rsqrt, "float32"),
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("sigmoid", R.sigmoid, topi.sigmoid, "float32"),
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("sign", R.sign, topi.sign, "float32"),
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("sign", R.sign, topi.sign, "int32"),
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("sin", R.sin, topi.sin, "float32"),
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("sinh", R.sinh, topi.sinh, "float32"),
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("sqrt", R.sqrt, topi.sqrt, "float32"),
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("square", R.square, lambda x: topi.multiply(x, x), "float32"),
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("tan", R.tan, topi.tan, "float32"),
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("tanh", R.tanh, topi.tanh, "float32"),
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("clip", lambda x: R.clip(x, 5, 8), lambda x: topi.clip(x, 5, 8), "float32"),
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],
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)
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def test_unary_ops(name: str, relax_op: Callable, te_func: Callable, dtype: str):
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_test_static_shape(name, relax_op, te_func, dtype)
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_test_symbolic_shape(name, relax_op, te_func, dtype)
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if __name__ == "__main__":
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tvm.testing.main()
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