tests/python/relax/test_op_ccl.py

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# to you under the Apache License, Version 2.0 (the
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#
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import pytest
import tvm
import tvm.testing
from tvm import relax, tir
from tvm import TVMError
from tvm.ir import Op
from tvm.script import relax as R


def test_op_correctness():
    x = relax.Var("x", R.Tensor((2, 3), "float32"))
    assert relax.op.ccl.allreduce(x).op == Op.get("relax.ccl.allreduce")
    assert relax.op.ccl.broadcast_from_worker0(x).op == Op.get("relax.ccl.broadcast_from_worker0")
    assert relax.op.ccl.allgather(x, 2).op == Op.get("relax.ccl.allgather")


def _check_inference(bb: relax.BlockBuilder, call: relax.Call, expected_sinfo: relax.StructInfo):
    ret = bb.normalize(call)
    tvm.ir.assert_structural_equal(ret.struct_info, expected_sinfo)


def test_allreduce_infer_struct_info():
    bb = relax.BlockBuilder()
    x0 = relax.Var("x", R.Tensor((2, 3), "float32"))
    x1 = relax.Var("x", R.Tensor("float32", ndim=3))
    x2 = relax.Var("x", R.Tensor("float32", ndim=-1))
    x3 = relax.Var("x", R.Tensor((2, 3)))
    x4 = relax.Var("x", R.Tensor())
    x5 = relax.Var("x", R.Tensor((3, 4)))

    _check_inference(bb, relax.op.ccl.allreduce(x0), relax.TensorStructInfo((2, 3), "float32"))
    _check_inference(
        bb, relax.op.ccl.allreduce(x1), relax.TensorStructInfo(dtype="float32", ndim=3)
    )
    _check_inference(bb, relax.op.ccl.allreduce(x2), relax.TensorStructInfo(dtype="float32"))
    _check_inference(bb, relax.op.ccl.allreduce(x3), relax.TensorStructInfo((2, 3), dtype=""))
    _check_inference(bb, relax.op.ccl.allreduce(x4), relax.TensorStructInfo(dtype=""))
    _check_inference(bb, relax.op.ccl.allreduce(x5), relax.TensorStructInfo((3, 4), dtype=""))


def test_allreduce_infer_struct_info_shape_symbolic():
    bb = relax.BlockBuilder()
    m = tir.Var("m", "int64")
    n = tir.Var("n", "int64")
    x0 = relax.Var("x", R.Tensor((m, n), "float32"))
    x1 = relax.Var("x", R.Tensor((4, n), "float32"))

    _check_inference(bb, relax.op.ccl.allreduce(x0), relax.TensorStructInfo((m, n), "float32"))
    _check_inference(bb, relax.op.ccl.allreduce(x1), relax.TensorStructInfo((4, n), "float32"))


def test_allreduce_infer_struct_info_shape_var():
    bb = relax.BlockBuilder()
    s0 = relax.Var("s", relax.ShapeStructInfo(ndim=2))
    s1 = relax.Var("s", relax.ShapeStructInfo())
    x0 = relax.Var("x", relax.TensorStructInfo(s0, "float32"))
    x1 = relax.Var("x", relax.TensorStructInfo(s1, "float32"))

    _check_inference(bb, relax.op.ccl.allreduce(x0), relax.TensorStructInfo(s0, "float32"))
    _check_inference(bb, relax.op.ccl.allreduce(x1), relax.TensorStructInfo(s1, "float32"))


def test_allreduce_infer_struct_info_more_input_dtype():
    bb = relax.BlockBuilder()
    x0 = relax.Var("x", R.Tensor((2, 3), "float64"))
    x1 = relax.Var("x", R.Tensor((2, 3), "int8"))
    x2 = relax.Var("x", R.Tensor((2, 3), "int64"))

    _check_inference(bb, relax.op.ccl.allreduce(x0), relax.TensorStructInfo((2, 3), "float64"))
    _check_inference(bb, relax.op.ccl.allreduce(x1), relax.TensorStructInfo((2, 3), "int8"))
    _check_inference(bb, relax.op.ccl.allreduce(x2), relax.TensorStructInfo((2, 3), "int64"))


def test_allgather_infer_struct_info():
    bb = relax.BlockBuilder()
    x0 = relax.Var("x", R.Tensor((2, 3), "float32"))
    x1 = relax.Var("x", R.Tensor("float32", ndim=3))
    x2 = relax.Var("x", R.Tensor("float32", ndim=-1))
    x3 = relax.Var("x", R.Tensor((2, 3)))
    x4 = relax.Var("x", R.Tensor())
    x5 = relax.Var("x", R.Tensor((3, 4)))

    _check_inference(bb, relax.op.ccl.allgather(x0, 2), relax.TensorStructInfo((4, 3), "float32"))
    _check_inference(
        bb, relax.op.ccl.allgather(x1, 2), relax.TensorStructInfo(dtype="float32", ndim=3)
    )
    _check_inference(bb, relax.op.ccl.allgather(x2, 2), relax.TensorStructInfo(dtype="float32"))
    _check_inference(bb, relax.op.ccl.allgather(x3, 2), relax.TensorStructInfo((4, 3), dtype=""))
    _check_inference(bb, relax.op.ccl.allgather(x4, 2), relax.TensorStructInfo(dtype=""))
    _check_inference(bb, relax.op.ccl.allgather(x5, 2), relax.TensorStructInfo((6, 4), dtype=""))


def test_allgather_infer_struct_info_shape_symbolic():
    bb = relax.BlockBuilder()
    m = tir.Var("m", "int64")
    n = tir.Var("n", "int64")
    x0 = relax.Var("x", R.Tensor((m, n), "float32"))
    x1 = relax.Var("x", R.Tensor((4, n), "float32"))

    _check_inference(
        bb, relax.op.ccl.allgather(x0, 2), relax.TensorStructInfo((m * 2, n), "float32")
    )
    _check_inference(bb, relax.op.ccl.allgather(x1, 2), relax.TensorStructInfo((8, n), "float32"))


def test_allgather_infer_struct_info_shape_var():
    bb = relax.BlockBuilder()
    s0 = relax.Var("s", relax.ShapeStructInfo(ndim=2))
    s1 = relax.Var("s", relax.ShapeStructInfo())
    x0 = relax.Var("x", relax.TensorStructInfo(s0, "float32"))
    x1 = relax.Var("x", relax.TensorStructInfo(s1, "float32"))

    _check_inference(bb, relax.op.ccl.allgather(x0, 2), relax.TensorStructInfo(s0, "float32"))
    _check_inference(bb, relax.op.ccl.allgather(x1, 2), relax.TensorStructInfo(s1, "float32"))


def test_allgather_infer_struct_info_more_input_dtype():
    bb = relax.BlockBuilder()
    x0 = relax.Var("x", R.Tensor((2, 3), "float64"))
    x1 = relax.Var("x", R.Tensor((2, 3), "int8"))
    x2 = relax.Var("x", R.Tensor((2, 3), "int64"))

    _check_inference(bb, relax.op.ccl.allgather(x0, 2), relax.TensorStructInfo((4, 3), "float64"))
    _check_inference(bb, relax.op.ccl.allgather(x1, 2), relax.TensorStructInfo((4, 3), "int8"))
    _check_inference(bb, relax.op.ccl.allgather(x2, 2), relax.TensorStructInfo((4, 3), "int64"))


def test_broadcast_from_worker0_infer_struct_info():
    bb = relax.BlockBuilder()
    x0 = relax.Var("x", R.Tensor((2, 3), "float32"))
    x1 = relax.Var("x", R.Tensor("float32", ndim=3))
    x2 = relax.Var("x", R.Tensor("float32", ndim=-1))
    x3 = relax.Var("x", R.Tensor((2, 3)))
    x4 = relax.Var("x", R.Tensor())
    x5 = relax.Var("x", R.Tensor((3, 4)))

    _check_inference(
        bb, relax.op.ccl.broadcast_from_worker0(x0), relax.TensorStructInfo((2, 3), "float32")
    )
    _check_inference(
        bb, relax.op.ccl.broadcast_from_worker0(x1), relax.TensorStructInfo(dtype="float32", ndim=3)
    )
    _check_inference(
        bb, relax.op.ccl.broadcast_from_worker0(x2), relax.TensorStructInfo(dtype="float32")
    )
    _check_inference(
        bb, relax.op.ccl.broadcast_from_worker0(x3), relax.TensorStructInfo((2, 3), dtype="")
    )
    _check_inference(bb, relax.op.ccl.broadcast_from_worker0(x4), relax.TensorStructInfo(dtype=""))
    _check_inference(
        bb, relax.op.ccl.broadcast_from_worker0(x5), relax.TensorStructInfo((3, 4), dtype="")
    )


def test_broadcast_from_worker0_infer_struct_info_shape_symbolic():
    bb = relax.BlockBuilder()
    m = tir.Var("m", "int64")
    n = tir.Var("n", "int64")
    x0 = relax.Var("x", R.Tensor((m, n), "float32"))
    x1 = relax.Var("x", R.Tensor((4, n), "float32"))

    _check_inference(
        bb, relax.op.ccl.broadcast_from_worker0(x0), relax.TensorStructInfo((m, n), "float32")
    )
    _check_inference(
        bb, relax.op.ccl.broadcast_from_worker0(x1), relax.TensorStructInfo((4, n), "float32")
    )


def test_broadcast_from_worker0_infer_struct_info_shape_var():
    bb = relax.BlockBuilder()
    s0 = relax.Var("s", relax.ShapeStructInfo(ndim=2))
    s1 = relax.Var("s", relax.ShapeStructInfo())
    x0 = relax.Var("x", relax.TensorStructInfo(s0, "float32"))
    x1 = relax.Var("x", relax.TensorStructInfo(s1, "float32"))

    _check_inference(
        bb, relax.op.ccl.broadcast_from_worker0(x0), relax.TensorStructInfo(s0, "float32")
    )
    _check_inference(
        bb, relax.op.ccl.broadcast_from_worker0(x1), relax.TensorStructInfo(s1, "float32")
    )


def test_broadcast_from_worker0_infer_struct_info_more_input_dtype():
    bb = relax.BlockBuilder()
    x0 = relax.Var("x", R.Tensor((2, 3), "float64"))
    x1 = relax.Var("x", R.Tensor((2, 3), "int8"))
    x2 = relax.Var("x", R.Tensor((2, 3), "int64"))

    _check_inference(
        bb, relax.op.ccl.broadcast_from_worker0(x0), relax.TensorStructInfo((2, 3), "float64")
    )
    _check_inference(
        bb, relax.op.ccl.broadcast_from_worker0(x1), relax.TensorStructInfo((2, 3), "int8")
    )
    _check_inference(
        bb, relax.op.ccl.broadcast_from_worker0(x2), relax.TensorStructInfo((2, 3), "int64")
    )


def test_scatter_from_worker0_infer_struct_info():
    bb = relax.BlockBuilder()
    x0 = relax.Var("x", R.Tensor((2, 3), "float32"))
    x1 = relax.Var("x", R.Tensor((3, 4, 5)))

    _check_inference(
        bb, relax.op.ccl.scatter_from_worker0(x0, 2), relax.TensorStructInfo((1, 3), "float32")
    )
    _check_inference(
        bb, relax.op.ccl.scatter_from_worker0(x1, 3), relax.TensorStructInfo((1, 4, 5), dtype="")
    )


def test_scatter_from_worker0_infer_struct_info_shape_symbolic():
    bb = relax.BlockBuilder()
    m = tir.Var("m", "int64")
    n = tir.Var("n", "int64")
    x0 = relax.Var("x", R.Tensor((m, n), "float32"))
    x1 = relax.Var("x", R.Tensor((4, n), "float32"))

    _check_inference(
        bb,
        relax.op.ccl.scatter_from_worker0(x0, 2),
        relax.TensorStructInfo((tir.div(m, 2), n), "float32"),
    )
    _check_inference(
        bb, relax.op.ccl.scatter_from_worker0(x1, 2), relax.TensorStructInfo((2, n), "float32")
    )


def test_scatter_from_worker0_infer_struct_info_shape_var():
    bb = relax.BlockBuilder()
    s0 = relax.Var("s", relax.ShapeStructInfo((2, 4, 8)))
    x0 = relax.Var("x", relax.TensorStructInfo(s0, "float32"))

    _check_inference(
        bb, relax.op.ccl.scatter_from_worker0(x0, 2), relax.TensorStructInfo((1, 4, 8), "float32")
    )


def test_scatter_from_worker0_infer_struct_info_more_input_dtype():
    bb = relax.BlockBuilder()
    x0 = relax.Var("x", R.Tensor((2, 3), "float64"))
    x1 = relax.Var("x", R.Tensor((2, 3), "int8"))
    x2 = relax.Var("x", R.Tensor((2, 3), "int64"))

    _check_inference(
        bb, relax.op.ccl.scatter_from_worker0(x0, 2), relax.TensorStructInfo((1, 3), "float64")
    )
    _check_inference(
        bb, relax.op.ccl.scatter_from_worker0(x1, 2), relax.TensorStructInfo((1, 3), "int8")
    )
    _check_inference(
        bb, relax.op.ccl.scatter_from_worker0(x2, 2), relax.TensorStructInfo((1, 3), "int64")
    )


if __name__ == "__main__":
    tvm.testing.main()