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# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
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#
#   http://www.apache.org/licenses/LICENSE-2.0
#
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# ruff: noqa: F401

from typing import Optional, Union

import pytest

import tvm
import tvm.script
import tvm.testing
from tvm import IRModule, relax, tirx, topi
from tvm.ir import Range
from tvm.relax import Call, SeqExpr, VarBinding
from tvm.relax.distributed import DeviceMesh
from tvm.script.parser import ir as I
from tvm.script.parser import relax as R
from tvm.script.parser import tirx as T


def _check(
    parsed: relax.Function | IRModule,
    expect: relax.Function | IRModule | None = None,
):
    test = parsed.script(show_meta=True)
    roundtrip_mod = tvm.script.from_source(test)
    tvm.ir.assert_structural_equal(parsed, roundtrip_mod)
    if expect:
        tvm.ir.assert_structural_equal(parsed, expect)


def test_call_tir_dtensor():
    @I.ir_module(s_tir=True)
    class TestModule:
        I.module_attrs({"device_num": 10})
        I.module_global_infos(
            {
                "mesh": [
                    R.device_mesh((2, 2), I.Range(0, 4)),  # mesh[0]
                    R.device_mesh((1,), I.Range(4, 5)),  # mesh[1]
                ]
            }
        )

        @T.prim_func(s_tir=True)
        def tir_func(
            x: T.Buffer((T.int64(128), T.int64(128)), "float32"),
            y: T.Buffer((T.int64(128), T.int64(128)), "float32"),
        ):
            T.func_attr({"tirx.noalias": True})
            for i, j in T.grid(T.int64(128), T.int64(128)):
                with T.sblock():
                    vi, vj = T.axis.remap("SS", [i, j])
                    y[vi, vj] = x[vi, vj] + 1.0

        @R.function
        def foo(
            x: R.DTensor((128, 128), "float32", device_mesh="mesh[0]", placement="S[0], R"),
        ) -> R.DTensor((128, 128), "float32", device_mesh="mesh[0]", placement="S[0], R"):
            gv0 = R.dist.call_tir(
                TestModule.tir_func,
                x,
                R.DTensor(
                    shape=(128, 128), dtype="float32", device_mesh="mesh[0]", placement="S[0], R"
                ),
            )
            return gv0

    device_mesh_list = [DeviceMesh((2, 2), Range(0, 4)), DeviceMesh((1,), Range(4, 5))]
    foo_func = TestModule["foo"]
    params = foo_func.params
    assert len(params) == 1
    assert params[0].ty == R.DTensor(
        (128, 128), "float32", device_mesh_list[0], placement="S[0], R"
    )
    assert foo_func.ret_ty == R.DTensor(
        (128, 128), "float32", device_mesh_list[0], placement="S[0], R"
    )
    assert isinstance(foo_func.body, SeqExpr)
    assert len(foo_func.body.blocks[0].bindings) == 1
    assert isinstance(foo_func.body.blocks[0].bindings[0], VarBinding)
    value = foo_func.body.blocks[0].bindings[0].value
    assert isinstance(value, Call)
    assert value.ty_args[0] == R.DTensor(
        (128, 128), "float32", device_mesh_list[0], placement="S[0], R"
    )
    _check(TestModule)


def test_explicit_device_id():
    @I.ir_module(s_tir=True)
    class TestModule:
        I.module_attrs({"device_num": 10})
        I.module_global_infos(
            {
                "mesh": [
                    R.device_mesh((2, 2), [0, 1, 2, 3]),  # mesh[0]
                    R.device_mesh(
                        (1,),
                        [
                            4,
                        ],
                    ),  # mesh[1]
                ]
            }
        )

        @T.prim_func(s_tir=True)
        def tir_func(
            x: T.Buffer((T.int64(128), T.int64(128)), "float32"),
            y: T.Buffer((T.int64(128), T.int64(128)), "float32"),
        ):
            T.func_attr({"tirx.noalias": True})
            for i, j in T.grid(T.int64(128), T.int64(128)):
                with T.sblock():
                    vi, vj = T.axis.remap("SS", [i, j])
                    y[vi, vj] = x[vi, vj] + 1.0

        @R.function
        def foo(
            x: R.DTensor((128, 128), "float32", device_mesh="mesh[0]", placement="S[0], R"),
        ) -> R.DTensor((128, 128), "float32", device_mesh="mesh[0]", placement="S[0], R"):
            gv0 = R.dist.call_tir(
                TestModule.tir_func,
                x,
                R.DTensor(
                    shape=(128, 128), dtype="float32", device_mesh="mesh[0]", placement="S[0], R"
                ),
            )
            return gv0

    _check(TestModule)


def test_constant():
    @I.ir_module(s_tir=True)
    class TestModule:
        I.module_attrs({"device_num": 10})
        I.module_global_infos(
            {
                "mesh": [
                    R.device_mesh((2, 2), I.Range(0, 4)),  # mesh[0]
                    R.device_mesh((1,), I.Range(4, 5)),  # mesh[1]
                ]
            }
        )

        @T.prim_func(s_tir=True)
        def tir_func(
            x: T.Buffer((T.int64(128), T.int64(128)), "float32"),
            y: T.Buffer((T.int64(128), T.int64(128)), "float32"),
        ):
            T.func_attr({"tirx.noalias": True})
            for i, j in T.grid(T.int64(128), T.int64(128)):
                with T.sblock():
                    vi, vj = T.axis.remap("SS", [i, j])
                    y[vi, vj] = x[vi, vj] + 1.0

        @R.function
        def foo(
            x: R.DTensor((128, 128), "float32", device_mesh="mesh[0]", placement="S[0], R"),
        ) -> R.DTensor((128, 128), "float32", device_mesh="mesh[0]", placement="S[0], R"):
            gv0 = R.dist.call_tir(
                TestModule.tir_func,
                x,
                R.DTensor(
                    shape=(128, 128), dtype="float32", device_mesh="mesh[0]", placement="S[0], R"
                ),
            )
            gv1 = R.add(gv0, R.dist.const(1.0, ty=R.DTensor((), "float32", "mesh[0]", "R, R")))
            return gv1

    _check(TestModule)


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