Rename python/cutlass to python/cutlass_cppgen (#2652)

python/cutlass_cppgen/backend/utils/__init__.py

@@ -0,0 +1,33 @@
+################################################################################
+#
+# Copyright (c) 2017 - 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: BSD-3-Clause
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+# 1. Redistributions of source code must retain the above copyright notice, this
+# list of conditions and the following disclaimer.
+#
+# 2. Redistributions in binary form must reproduce the above copyright notice,
+# this list of conditions and the following disclaimer in the documentation
+# and/or other materials provided with the distribution.
+#
+# 3. Neither the name of the copyright holder nor the names of its
+# contributors may be used to endorse or promote products derived from
+# this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+#
+################################################################################
+
+from cutlass_cppgen.backend.utils.device import check_cuda_errors, device_cc

python/cutlass_cppgen/backend/utils/device.py

@@ -0,0 +1,126 @@
+#################################################################################################
+#
+# Copyright (c) 2017 - 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: BSD-3-Clause
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+# 1. Redistributions of source code must retain the above copyright notice, this
+# list of conditions and the following disclaimer.
+#
+# 2. Redistributions in binary form must reproduce the above copyright notice,
+# this list of conditions and the following disclaimer in the documentation
+# and/or other materials provided with the distribution.
+#
+# 3. Neither the name of the copyright holder nor the names of its
+# contributors may be used to endorse or promote products derived from
+# this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+#
+#################################################################################################
+
+"""
+Utility functions for interacting with the device
+"""
+from __future__ import annotations
+
+from cutlass_cppgen.utils.lazy_import import lazy_import
+cuda = lazy_import("cuda.cuda")
+cudart =  lazy_import("cuda.cudart")
+
+import cutlass_cppgen
+from cutlass_cppgen.utils.datatypes import is_cupy_tensor, is_numpy_tensor, is_torch_tensor
+
+
+def check_cuda_errors(result: list):
+    """
+    Checks whether `result` contains a CUDA error raises the error as an exception, if so. Otherwise,
+    returns the result contained in the remaining fields of `result`.
+
+    :param result: the results of the `cudart` method, consisting of an error code and any method results
+    :type result: list
+
+    :return: non-error-code results from the `results` parameter
+    """
+    # `result` is of the format : (cudaError_t, result...)
+    err = result[0]
+    if err.value:
+        raise RuntimeError("CUDA error: {}".format(cudart.cudaGetErrorName(err)))
+
+    if len(result) == 1:
+        return None
+    elif len(result) == 2:
+        return result[1]
+    else:
+        return result[1:]
+
+
+def device_cc(device: int = -1) -> int:
+    """
+    Returns the compute capability of the device with ID `device`.
+
+    :param device: ID of the device to query
+    :type device: int
+
+    :return: compute capability of the queried device (e.g., 80 for SM80)
+    :rtype: int
+    """
+    if device == -1:
+        device = cutlass_cppgen.device_id()
+
+    deviceProp = check_cuda_errors(cudart.cudaGetDeviceProperties(device))
+    major = str(deviceProp.major)
+    minor = str(deviceProp.minor)
+    return int(major + minor)
+
+
+def device_sm_count(device: int = -1):
+    if device == -1:
+        device = cutlass_cppgen.device_id()
+    err, device_sm_count = cuda.cuDeviceGetAttribute(
+        cuda.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT, device
+    )
+    if err != cuda.CUresult.CUDA_SUCCESS:
+        raise Exception(
+            "Failed to retireve SM count. "
+            f"cuDeviceGetAttribute() failed with error: {cuda.cuGetErrorString(err)[1]}"
+        )
+
+    return device_sm_count
+
+
+def to_device_ptr(tensor) -> cuda.CUdeviceptr:
+    """
+    Converts a tensor to a CUdeviceptr
+
+    :param tensor: tensor to convert
+    :type tensor: np.ndarray | torch.Tensor | cp.ndarray | int
+
+    :return: device pointer
+    :rtype: cuda.CUdeviceptr
+    """
+    if is_numpy_tensor(tensor):
+        ptr = cuda.CUdeviceptr(tensor.__array_interface__["data"][0])
+    elif is_torch_tensor(tensor):
+        ptr = cuda.CUdeviceptr(tensor.data_ptr())
+    elif is_cupy_tensor(tensor):
+        ptr = cuda.CUdeviceptr(int(tensor.data.ptr))
+    elif isinstance(tensor, cuda.CUdeviceptr):
+        ptr = tensor
+    elif isinstance(tensor, int):
+        ptr = cuda.CUdeviceptr(tensor)
+    else:
+        raise NotImplementedError(tensor)
+
+    return ptr