70 lines
2.9 KiB
Python
70 lines
2.9 KiB
Python
################################################################################
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#
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# Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: BSD-3-Clause
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# 1. Redistributions of source code must retain the above copyright notice, this
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# list of conditions and the following disclaimer.
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#
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# 2. Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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#
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# 3. Neither the name of the copyright holder nor the names of its
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# contributors may be used to endorse or promote products derived from
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# this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#
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################################################################################
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from cuda import cuda
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import cutlass_bindings
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import numpy as np
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from cutlass.backend.utils.software import CheckPackages
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cupy_available = CheckPackages().check_cupy()
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if cupy_available:
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import cupy as cp
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torch_available = CheckPackages().check_torch()
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if torch_available:
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import torch
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class TensorRef:
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"""
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Python Wrapper for cutlass_bindings.TensorRef
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"""
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def __init__(self, tensor, dtype, layout) -> None:
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if isinstance(tensor, np.ndarray):
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ptr = cuda.CUdeviceptr(tensor.__array_interface__["data"][0])
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elif torch_available and isinstance(tensor, torch.Tensor):
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ptr = cuda.CUdeviceptr(tensor.data_ptr())
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elif torch_available and isinstance(tensor, cp.ndarray):
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ptr = cuda.CUdeviceptr(int(tensor.data.ptr))
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elif isinstance(tensor, cuda.CUdeviceptr):
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ptr = tensor
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elif isinstance(tensor, int):
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ptr = cuda.CUdeviceptr(tensor)
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else:
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raise NotImplementedError(tensor)
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# the dtype(0) is used to overload between different data types
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# with the same layout
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self.tensor_ref = cutlass_bindings.get_tensor_ref(int(ptr), dtype(0), layout)
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