wehub-resource-sync
53 lines
1.9 KiB
Python
53 lines
1.9 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
|
|
# or more contributor license agreements. See the NOTICE file
|
|
# distributed with this work for additional information
|
|
# regarding copyright ownership. The ASF licenses this file
|
|
# to you under the Apache License, Version 2.0 (the
|
|
# "License"); you may not use this file except in compliance
|
|
# with the License. You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing,
|
|
# software distributed under the License is distributed on an
|
|
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
|
|
# KIND, either express or implied. See the License for the
|
|
# specific language governing permissions and limitations
|
|
# under the License.
|
|
# pylint: disable=invalid-name
|
|
"""Default legalization function for search operators."""
|
|
|
|
from tvm import topi
|
|
from tvm.ir import Call
|
|
|
|
from ...block_builder import BlockBuilder
|
|
from ...expr import Expr
|
|
from .common import LegalizeFunc, TEFunc, _call_topi_without_attr, register_legalize
|
|
|
|
register_legalize("relax.where", _call_topi_without_attr(topi.where))
|
|
|
|
|
|
def _argmax_argmin(te_func: TEFunc) -> LegalizeFunc:
|
|
def argmax_argmin_call_te(bb: BlockBuilder, call: Call) -> Expr:
|
|
return bb.call_te(
|
|
te_func,
|
|
call.args[0],
|
|
None if call.attrs.axis is None else call.attrs.axis,
|
|
call.attrs.keepdims,
|
|
)
|
|
|
|
return argmax_argmin_call_te
|
|
|
|
|
|
register_legalize("relax.argmax", _argmax_argmin(topi.argmax))
|
|
register_legalize("relax.argmin", _argmax_argmin(topi.argmin))
|
|
|
|
|
|
@register_legalize("relax.bucketize")
|
|
def _bucketize(bb, call):
|
|
input_tensor = call.args[0]
|
|
boundaries = call.args[1]
|
|
right = call.attrs.right
|
|
out_dtype = "int32" if call.attrs.out_int32 else "int64"
|
|
return bb.call_te(topi.searchsorted, boundaries, input_tensor, right, out_dtype)
|