chore: import upstream snapshot with attribution
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# 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 pytest
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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.parser 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_redistribute_R_to_S():
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bb = relax.BlockBuilder()
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mesh = R.device_mesh((4,), list(range(4)))
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x = relax.Var("x", R.DTensor((3, 4), "float32", device_mesh=mesh, placement="R"))
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_check_inference(
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bb,
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R.distributed.redistribute_replica_to_shard(x, num_workers=4, axis=1),
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R.DTensor((3, 4), "float32", device_mesh=mesh, placement="S[1]"),
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)
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# wrong: indivisible
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with pytest.raises(ValueError):
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bb.normalize(R.distributed.redistribute_replica_to_shard(x, num_workers=4, axis=0))
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y = relax.Var("y", R.Tensor((3, 4), "float32"))
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_check_inference(
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bb,
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R.distributed.redistribute_replica_to_shard(y, num_workers=4, axis=1),
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R.Tensor((3, 1), "float32"),
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)
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# wrong: indivisible
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with pytest.raises(ValueError):
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bb.normalize(R.distributed.redistribute_replica_to_shard(y, num_workers=4, axis=0))
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if __name__ == "__main__":
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tvm.testing.main()
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