blob: 58bf933d44b8db187ccb4d906323ea38f3194388 [file] [log] [blame]
# 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.
"""External function interface to BLAS libraries."""
import tvm
from tvm import te
def matmul(lhs, rhs, transa=False, transb=False, **kwargs):
"""Create an extern op that compute matrix mult of A and rhs with CrhsLAS
This function serves as an example on how to call external libraries.
Parameters
----------
lhs: Tensor
The left matrix operand
rhs: Tensor
The right matrix operand
transa: bool
Whether transpose lhs
transb: bool
Whether transpose rhs
Returns
-------
C: Tensor
The result tensor.
"""
n = lhs.shape[1] if transa else lhs.shape[0]
m = rhs.shape[0] if transb else rhs.shape[1]
return te.extern(
(n, m),
[lhs, rhs],
lambda ins, outs: tvm.tir.call_packed(
"tvm.contrib.cblas.matmul", ins[0], ins[1], outs[0], transa, transb
),
name="C",
**kwargs,
)
def batch_matmul(lhs, rhs, transa=False, transb=False, iterative=False, **kwargs):
"""Create an extern op that compute batched matrix mult of A and rhs with CBLAS
This function serves as an example on how to call external libraries.
Parameters
----------
lhs: Tensor
The left matrix operand
rhs: Tensor
The right matrix operand
transa: bool
Whether transpose lhs
transb: bool
Whether transpose rhs
Returns
-------
C: Tensor
The result tensor.
"""
b = lhs.shape[0]
n = lhs.shape[2] if transa else lhs.shape[1]
m = rhs.shape[1] if transb else rhs.shape[2]
return te.extern(
(b, n, m),
[lhs, rhs],
lambda ins, outs: tvm.tir.call_packed(
"tvm.contrib.cblas.batch_matmul"
if not iterative
else "tvm.contrib.cblas.batch_matmul_iterative",
ins[0],
ins[1],
outs[0],
transa,
transb,
),
name="C",
**kwargs,
)