tests/python/relax/test_tvmscript_parser_op_search.py

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# to you under the Apache License, Version 2.0 (the
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# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
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# specific language governing permissions and limitations
# under the License.

from typing import Optional, Union

import tvm
import tvm.script
import tvm.testing
from tvm import IRModule, relax
from tvm.script import relax as R


def _check(
    parsed: Union[relax.Function, IRModule],
    expect: Optional[Union[relax.Function, IRModule]],
):
    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_where():
    @R.function
    def foo(
        condition: R.Tensor((2, 1), "bool"),
        x: R.Tensor((2, 3), "float32"),
        y: R.Tensor((1, 3), "float32"),
    ) -> R.Tensor((2, 3), "float32"):
        gv: R.Tensor((2, 3), "float32") = R.where(condition, x, y)
        return gv

    bb = relax.BlockBuilder()
    condition = relax.Var("condition", R.Tensor((2, 1), "bool"))
    x = relax.Var("x", R.Tensor((2, 3), "float32"))
    y = relax.Var("y", R.Tensor((1, 3), "float32"))
    with bb.function("foo", [condition, x, y]):
        gv = bb.emit(relax.op.where(condition, x, y))
        bb.emit_func_output(gv)

    _check(foo, bb.get()["foo"])


def test_argmax():
    @R.function
    def foo(x: R.Tensor((1, 2, 3, 4), "float32")) -> R.Tensor((1, 3, 4), "int64"):
        gv: R.Tensor((1, 3, 4), "int64") = R.argmax(x, axis=1)
        return gv

    x = relax.Var("x", R.Tensor((1, 2, 3, 4), "float32"))
    bb = relax.BlockBuilder()
    with bb.function("foo", [x]):
        gv = bb.emit(relax.op.argmax(x, axis=1))
        bb.emit_func_output(gv)

    _check(foo, bb.get()["foo"])


def test_argmax_without_specified_axis():
    @R.function
    def foo(x: R.Tensor((1, 2, 3, 4), "float32")) -> R.Tensor((), "int64"):
        gv: R.Tensor((), "int64") = R.argmax(x)
        return gv

    x = relax.Var("x", R.Tensor((1, 2, 3, 4), "float32"))
    bb = relax.BlockBuilder()
    with bb.function("foo", [x]):
        gv = bb.emit(relax.op.argmax(x))
        bb.emit_func_output(gv)

    _check(foo, bb.get()["foo"])


def test_argmax_keep_dims():
    @R.function
    def foo(x: R.Tensor((1, 2, 3, 4), "float32")) -> R.Tensor((1, 1, 3, 4), "int64"):
        gv: R.Tensor((1, 1, 3, 4), "int64") = R.argmax(x, axis=1, keepdims=True)
        return gv

    x = relax.Var("x", R.Tensor((1, 2, 3, 4), "float32"))
    bb = relax.BlockBuilder()
    with bb.function("foo", [x]):
        gv = bb.emit(relax.op.argmax(x, axis=1, keepdims=True))
        bb.emit_func_output(gv)

    _check(foo, bb.get()["foo"])


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