wehub-resource-sync
64 lines
1.8 KiB
Python
64 lines
1.8 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 numpy as np
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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 test_op_size():
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@tvm.script.ir_module
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class Module:
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@R.function
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def main(x: R.Tensor((2, 3), "float32")) -> R.Tensor((), "int64"):
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return R.size(x)
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x_np = np.random.rand(2, 3).astype("float32")
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x = tvm.runtime.tensor(x_np)
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target = tvm.target.Target("llvm")
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ex = relax.build(Module, target)
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vm = relax.VirtualMachine(ex, tvm.cpu())
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res = vm["main"](x)
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assert res.numpy() == 6
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def test_op_size_dynamic():
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@tvm.script.ir_module
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class Module:
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@R.function
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def main(x: R.Tensor(("m", "n"), "float32")) -> R.Tensor((), "int64"):
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return R.size(x)
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x_np = np.random.rand(4, 5).astype("float32")
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x = tvm.runtime.tensor(x_np)
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target = tvm.target.Target("llvm")
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ex = relax.build(Module, target)
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vm = relax.VirtualMachine(ex, tvm.cpu())
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res = vm["main"](x)
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assert res.numpy() == 20
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if __name__ == "__main__":
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tvm.testing.main()
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