wehub-resource-sync
128 lines
3.6 KiB
Python
128 lines
3.6 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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"""External function interface to BLAS libraries."""
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import tvm
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from tvm import te
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def matmul(lhs, rhs, transa=False, transb=False, **kwargs):
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"""Create an extern op that compute matrix mult of A and rhs with CrhsLAS
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This function serves as an example on how to call external libraries.
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Parameters
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----------
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lhs: Tensor
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The left matrix operand
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rhs: Tensor
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The right matrix operand
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transa: bool
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Whether transpose lhs
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transb: bool
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Whether transpose rhs
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Returns
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-------
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C: Tensor
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The result tensor.
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"""
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n = lhs.shape[1] if transa else lhs.shape[0]
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m = rhs.shape[0] if transb else rhs.shape[1]
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return te.extern(
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(n, m),
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[lhs, rhs],
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lambda ins, outs: tvm.tirx.call_packed(
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"tvm.contrib.mkl.matmul", ins[0], ins[1], outs[0], transa, transb
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),
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name="C",
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**kwargs,
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)
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def matmul_u8s8s32(lhs, rhs, transa=False, transb=False, **kwargs):
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"""Create an extern op that compute matrix mult of A and rhs with CrhsLAS
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This function serves as an example on how to call external libraries.
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Parameters
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----------
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lhs: Tensor
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The left matrix operand
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rhs: Tensor
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The right matrix operand
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transa: bool
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Whether transpose lhs
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transb: bool
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Whether transpose rhs
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Returns
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-------
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C: Tensor
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The result tensor.
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"""
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n = lhs.shape[1] if transa else lhs.shape[0]
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m = rhs.shape[0] if transb else rhs.shape[1]
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return te.extern(
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(n, m),
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[lhs, rhs],
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lambda ins, outs: tvm.tirx.call_packed(
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"tvm.contrib.mkl.matmul_u8s8s32", ins[0], ins[1], outs[0], transa, transb
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),
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name="C",
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**kwargs,
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)
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def batch_matmul(lhs, rhs, transa=False, transb=False, iterative=False, **kwargs):
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"""Create an extern op that compute batched matrix mult of A and rhs with mkl
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This function serves as an example on how to call external libraries.
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Parameters
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----------
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lhs: Tensor
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The left matrix operand
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rhs: Tensor
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The right matrix operand
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transa: bool
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Whether transpose lhs
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transb: bool
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Whether transpose rhs
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Returns
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-------
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C: Tensor
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The result tensor.
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"""
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b = te.max(lhs.shape[0], rhs.shape[0])
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n = lhs.shape[2] if transa else lhs.shape[1]
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m = rhs.shape[1] if transb else rhs.shape[2]
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return te.extern(
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(b, n, m),
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[lhs, rhs],
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lambda ins, outs: tvm.tirx.call_packed(
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"tvm.contrib.mkl.batch_matmul"
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if not iterative
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else "tvm.contrib.mkl.batch_matmul_iterative",
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ins[0],
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ins[1],
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outs[0],
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transa,
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transb,
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),
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name="C",
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**kwargs,
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)
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