# 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.""" from __future__ import absolute_import as _abs from .. import api as _api, intrin as _intrin 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 _api.extern( (n, m), [lhs, rhs], lambda ins, outs: _intrin.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 _api.extern( (b, n, m), [lhs, rhs], lambda ins, outs: _intrin.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 )