137 lines
5.7 KiB
Python
137 lines
5.7 KiB
Python
#################################################################################################
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#
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# Copyright (c) 2017 - 2025 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 math import prod
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from typing import Union
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from cutlass_cppgen.utils.lazy_import import lazy_import
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cuda = lazy_import("cuda.cuda")
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cudart = lazy_import("cuda.cudart")
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import numpy as np
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import cutlass_cppgen
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from cutlass_cppgen.backend.frontend import CupyFrontend, NumpyFrontend, TorchFrontend
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from cutlass_cppgen.backend.memory_manager import DevicePtrWrapper
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from cutlass_cppgen.utils.datatypes import is_cupy_tensor, is_numpy_tensor, is_torch_tensor
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class ArgumentBase:
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"""
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Base class for operation arguments
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"""
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def __init__(
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self,
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A: "Union[cuda.CUdeviceptr, np.ndarray, torch.Tensor, cp.ndarray]",
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B: "Union[cuda.CUdeviceptr, np.ndarray, torch.Tensor, cp.ndarray]",
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C: "Union[cuda.CUdeviceptr, np.ndarray, torch.Tensor, cp.ndarray]",
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D: "Union[cuda.CUdeviceptr, np.ndarray, torch.Tensor, cp.ndarray]",
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**kwargs,
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) -> None:
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# tensor_C can be interpreted as the bias with bias=True in keyword args
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self.bias = kwargs.get("bias", False)
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self.stream = kwargs.get("stream", cuda.CUstream(0))
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# RMM buffers used to track tensor lifetime
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self.buffers = {}
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# Host tensor to copy the computed result back
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self.host_tensors = {}
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self.ptr_A = self.tensor_to_ptr(A, "A")
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self.ptr_B = self.tensor_to_ptr(B, "B")
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self.ptr_C = self.tensor_to_ptr(C, "C")
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self.ptr_D = self.tensor_to_ptr(D, "D", is_output=True)
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if C is not None:
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if not isinstance(C, cuda.CUdeviceptr):
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self.tensor_c_numel = prod(C.shape)
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def tensor_to_ptr(self, tensor, name, is_output=False):
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"""
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Convert and remember the input tensor to cuda.CUdeviceptr used by cuda python
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For numpy.ndarray, it also remembers the host buffer for synchronization
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"""
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if tensor is None:
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return cuda.CUdeviceptr(0)
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if is_numpy_tensor(tensor):
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if is_output:
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assert name
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self.buffers[name] = NumpyFrontend.argument(tensor, is_output)
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if is_output:
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self.host_tensors[name] = tensor
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return self.buffers[name].ptr
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elif is_torch_tensor(tensor):
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return TorchFrontend.argument(tensor)
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elif isinstance(tensor, cuda.CUdeviceptr):
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return tensor
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elif is_cupy_tensor(tensor):
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return CupyFrontend.argument(tensor)
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else:
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raise TypeError("Unsupported Frontend. Only support numpy and torch")
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def sync(self, stream_sync=True):
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if stream_sync:
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(err,) = cudart.cudaDeviceSynchronize()
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if err != cuda.CUresult.CUDA_SUCCESS:
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raise RuntimeError("CUDA Error %s" % str(err))
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for key in self.host_tensors.keys():
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host_tensor = self.host_tensors[key]
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(err,) = cuda.cuMemcpyDtoH(
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host_tensor,
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self.buffers[key].ptr,
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host_tensor.size * host_tensor.itemsize,
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)
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if err != cuda.CUresult.CUDA_SUCCESS:
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raise RuntimeError("CUDA Error %s" % str(err))
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self.free()
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def free(self):
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"""
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Frees allocated device-side memory
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"""
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# Free any device memory allocated manually
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if not cutlass_cppgen.use_rmm:
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for name, buf in self.buffers.items():
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if isinstance(buf, DevicePtrWrapper):
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err, = cudart.cudaFree(buf.ptr)
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if err != cudart.cudaError_t.cudaSuccess:
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raise RuntimeError(f"cudaFree failed with error {err}")
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if hasattr(self, "workspace_buffer") and isinstance(self.workspace_buffer, DevicePtrWrapper):
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err, = cudart.cudaFree(self.workspace_buffer.ptr)
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if err != cudart.cudaError_t.cudaSuccess:
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raise RuntimeError(f"cudaFree failed with error {err}")
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del self.workspace_buffer
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