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Make cblas and mkl seperate entities in cmake and topi, allowing users to use both a BLAS library and MKL. In the future, MKL specific functions can be added easily. MKLDNN is also split off from MKL and BLAS for the same reasons. Other improvements: - cblas and mkl strategies are now only applied when they are viable. - compile_engine will log which implementation it has chosen and why.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,126 @@ | ||
| # 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.mkl.matmul", ins[0], ins[1], outs[0], transa, transb | ||
| ), | ||
| name="C", | ||
| **kwargs | ||
| ) | ||
|
|
||
|
|
||
| def matmul_u8s8s32(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.mkl.matmul_u8s8s32", 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 mkl | ||
| 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.mkl.batch_matmul" | ||
| if not iterative | ||
| else "tvm.contrib.mkl.batch_matmul_iterative", | ||
| ins[0], | ||
| ins[1], | ||
| outs[0], | ||
| transa, | ||
| transb, | ||
| ), | ||
| name="C", | ||
| **kwargs | ||
| ) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,52 @@ | ||
| # 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.mkl.matmul", ins[0], ins[1], outs[0], transa, transb | ||
| ), | ||
| name="C", | ||
| **kwargs | ||
| ) |
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