wehub-resource-sync
70 lines
2.5 KiB
Python
70 lines
2.5 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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import tvm
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import tvm.testing
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from tvm import relax
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from tvm.script import relax as R
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def _check_inference(bb: relax.BlockBuilder, call: relax.Call, expected_ty: relax.Type):
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ret = bb.normalize(call)
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tvm.ir.assert_structural_equal(ret.ty, expected_ty)
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def test_multinomial_from_uniform():
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bb = relax.BlockBuilder()
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prob0 = relax.Var("prob", R.Tensor((3, 5), "float32"))
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prob1 = relax.Var("prob", R.Tensor(ndim=2, dtype="float32"))
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prob2 = relax.Var("prob", R.Tensor(dtype="float32"))
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uniform_sample0 = relax.Var("u", R.Tensor((6, 1), "float32"))
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uniform_sample1 = relax.Var("u", R.Tensor(ndim=2, dtype="float32"))
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uniform_sample2 = relax.Var("u", R.Tensor(dtype="float32"))
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sample_indices0 = relax.Var("s", R.Tensor((6, 1), "int64"))
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sample_indices1 = relax.Var("s", R.Tensor((6, 1), "int32"))
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_check_inference(
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bb,
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relax.op.multinomial_from_uniform(prob0, uniform_sample0, sample_indices0),
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R.Tensor((6, 1), "int64"),
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)
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_check_inference(
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bb,
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relax.op.multinomial_from_uniform(prob0, uniform_sample0, sample_indices0, dtype="int32"),
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R.Tensor((6, 1), "int32"),
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)
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_check_inference(
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bb,
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relax.op.multinomial_from_uniform(prob1, uniform_sample1, sample_indices1),
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R.Tensor(ndim=2, dtype="int64"),
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)
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_check_inference(
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bb,
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relax.op.multinomial_from_uniform(prob1, uniform_sample1, sample_indices1, dtype="int32"),
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R.Tensor(ndim=2, dtype="int32"),
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)
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_check_inference(
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bb,
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relax.op.multinomial_from_uniform(prob2, uniform_sample2, sample_indices0),
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R.Tensor(dtype="int64"),
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)
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if __name__ == "__main__":
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tvm.testing.main()
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