156 lines
6.1 KiB
Python
156 lines
6.1 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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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 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_ipc_allreduce_rewrite():
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@I.ir_module
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class Module:
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@R.function(pure=False)
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def main(shape: R.Shape(["m", "n"])): # type: ignore
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m = T.int64()
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n = T.int64()
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alloc: R.Tensor((m, n), dtype="float16") = R.builtin.alloc_tensor( # type: ignore
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R.shape([m, n]), R.dtype("float16"), R.prim_value(0), R.str("global")
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)
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lv1: R.Tensor((m, n), dtype="float16") = alloc # type: ignore
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alloc1: R.Tensor((m, n), dtype="float16") = R.builtin.alloc_tensor( # type: ignore
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R.shape([m, n]), R.dtype("float16"), R.prim_value(0), R.str("global")
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)
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_: R.Any = R.call_packed(
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"runtime.disco.allreduce", lv1, R.shape([0]), R.prim_value(True), alloc1
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)
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return alloc1
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@I.ir_module
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class Expected:
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@R.function(pure=False)
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def main(shape: R.Shape(["m", "n"])): # type: ignore
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m = T.int64()
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n = T.int64()
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alloc: R.Tensor((m, n), dtype="float16") = R.builtin.alloc_tensor( # type: ignore
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R.shape([m, n]), R.dtype("float16"), R.prim_value(0), R.str("ipc_memory")
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)
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lv1: R.Tensor((m, n), dtype="float16") = alloc # type: ignore
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alloc1: R.Tensor((m, n), dtype="float16") = R.builtin.alloc_tensor( # type: ignore
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R.shape([m, n]), R.dtype("float16"), R.prim_value(0), R.str("global")
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)
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_: R.Any = R.call_packed(
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"runtime.disco.cuda_ipc.custom_allreduce", lv1, R.prim_value(1), alloc1
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)
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return alloc1
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allreduce_strategy = 1
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mod = relax.transform.IPCAllReduceRewrite(allreduce_strategy)(Module)
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tvm.ir.assert_structural_equal(
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mod,
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(
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Expected
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if tvm.get_global_func("runtime.disco.cuda_ipc.custom_allreduce", allow_missing=True)
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is not None
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else Module
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),
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)
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def test_ipc_allreduce_spread_along_reshape():
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@I.ir_module
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class Module:
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@R.function(pure=False)
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def main(shape: R.Shape(["m", "n"])): # type: ignore
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m = T.int64()
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n = T.int64()
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alloc: R.Tensor((m, n), dtype="float16") = R.builtin.alloc_tensor( # type: ignore
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R.shape([m, n]), R.dtype("float16"), R.prim_value(0), R.str("global")
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)
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lv1: R.Tensor((m * n,), dtype="float16") = R.reshape(alloc, (m * n,)) # type: ignore
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alloc1: R.Tensor((m * n,), dtype="float16") = R.builtin.alloc_tensor( # type: ignore
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R.shape([m * n]), R.dtype("float16"), R.prim_value(0), R.str("global")
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)
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_: R.Any = R.call_packed(
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"runtime.disco.allreduce", lv1, R.shape([0]), R.prim_value(False), alloc1
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)
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return alloc1
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@I.ir_module
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class Expected:
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@R.function(pure=False)
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def main(
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shape: R.Shape(["m", "n"]), # type: ignore
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) -> R.Tensor(("m * n",), dtype="float16"): # type: ignore
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m = T.int64()
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n = T.int64()
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alloc: R.Tensor((m, n), dtype="float16") = R.builtin.alloc_tensor( # type: ignore
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R.shape([m, n]), R.dtype("float16"), R.prim_value(0), R.str("ipc_memory")
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)
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lv1: R.Tensor((m * n,), dtype="float16") = R.reshape( # type: ignore
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alloc, R.shape([m * n])
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)
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alloc1: R.Tensor((m * n,), dtype="float16") = R.builtin.alloc_tensor( # type: ignore
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R.shape([m * n]), R.dtype("float16"), R.prim_value(0), R.str("global")
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)
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_: R.Any = R.call_packed(
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"runtime.disco.cuda_ipc.custom_allreduce", lv1, R.prim_value(1), alloc1
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)
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return alloc1
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allreduce_strategy = 1
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mod = relax.transform.IPCAllReduceRewrite(allreduce_strategy)(Module)
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tvm.ir.assert_structural_equal(
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mod,
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(
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Expected
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if tvm.get_global_func("runtime.disco.cuda_ipc.custom_allreduce", allow_missing=True)
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is not None
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else Module
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),
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)
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def test_ipc_allreduce_skip_reducer_other_than_sum():
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@I.ir_module
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class Module:
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@R.function(pure=False)
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def main(shape: R.Shape(["m", "n"])): # type: ignore
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m = T.int64()
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n = T.int64()
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alloc: R.Tensor((m, n), dtype="float16") = R.builtin.alloc_tensor( # type: ignore
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R.shape([m, n]), R.dtype("float16"), R.prim_value(0), R.str("global")
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)
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lv1: R.Tensor((m, n), dtype="float16") = alloc # type: ignore
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alloc1: R.Tensor((m, n), dtype="float16") = R.builtin.alloc_tensor( # type: ignore
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R.shape([m, n]), R.dtype("float16"), R.prim_value(0), R.str("global")
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)
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_: R.Any = R.call_packed(
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"runtime.disco.allreduce", lv1, R.shape([1]), R.prim_value(True), alloc1
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)
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return alloc1
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allreduce_strategy = 1
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mod = relax.transform.IPCAllReduceRewrite(allreduce_strategy)(Module)
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tvm.ir.assert_structural_equal(mod, Module)
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if __name__ == "__main__":
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tvm.testing.main()
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