| # 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. |
| """Wrapping functions to bridge frameworks with DLPack support to TVM""" |
| from tvm.runtime import ndarray |
| |
| |
| def convert_func(tvm_func, tensor_type, to_dlpack_func): |
| """Convert a tvm function into one that accepts a tensor from another |
| framework, provided the other framework supports DLPACK |
| |
| Parameters |
| ---------- |
| tvm_func: Function |
| Built tvm function operating on arrays |
| |
| tensor_type: Type |
| Type of the tensors of the target framework |
| |
| to_dlpack_func: Function |
| Function to convert the source tensors to DLPACK |
| """ |
| assert callable(tvm_func) |
| |
| def _wrapper(*args): |
| args = tuple( |
| ndarray.from_dlpack(to_dlpack_func(arg)) if isinstance(arg, tensor_type) else arg |
| for arg in args |
| ) |
| return tvm_func(*args) |
| |
| return _wrapper |
| |
| |
| def to_pytorch_func(tvm_func): |
| """Convert a tvm function into one that accepts PyTorch tensors |
| |
| Parameters |
| ---------- |
| tvm_func: Function |
| Built tvm function operating on arrays |
| |
| Returns |
| ------- |
| wrapped_func: Function |
| Wrapped tvm function that operates on PyTorch tensors |
| """ |
| # pylint: disable=import-outside-toplevel |
| import torch |
| import torch.utils.dlpack |
| |
| return convert_func(tvm_func, torch.Tensor, torch.utils.dlpack.to_dlpack) |