wehub-resource-sync
63 lines
2.2 KiB
Python
63 lines
2.2 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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"""Tests to validate relax fast math tranform pass."""
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import pytest
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import tvm.testing
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from tvm import relax, topi
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from tvm.ir.base import assert_structural_equal
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from tvm.relax.transform import FastMathTransform
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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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def _run_pass_compare_output(Before, Expected):
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fast_mod = FastMathTransform()(Before)
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if not relax.analysis.check_well_formed(fast_mod):
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print("IRModule is not well-formed")
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assert_structural_equal(Expected, fast_mod)
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def test_optimize_transform_layout_pass_one_arg():
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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(x: R.Tensor((16,), dtype="float32")) -> R.Tensor((16,), dtype="float32"):
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lv1: R.Tensor((16,), dtype="float32") = R.nn.softmax(x)
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lv2: R.Tensor((16,), dtype="float32") = R.exp(lv1)
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lv3: R.Tensor((16,), dtype="float32") = R.erf(lv2)
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lv4: R.Tensor((16,), dtype="float32") = R.tanh(lv3)
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return lv4
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bb = relax.BlockBuilder()
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x = relax.Var("x", R.Tensor((16,), "float32"))
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with bb.function("main", [x]):
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lv1 = bb.emit_te(topi.nn.fast_softmax, x)
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lv2 = bb.emit_te(topi.fast_exp, lv1)
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lv3 = bb.emit_te(topi.fast_erf, lv2)
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lv4 = bb.emit_te(topi.fast_tanh, lv3)
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bb.emit_func_output(lv4)
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Expected = bb.get()
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_run_pass_compare_output(Before, Expected)
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if __name__ == "__main__":
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tvm.testing.main()
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