python_code stringlengths 0 679k | repo_name stringlengths 9 41 | file_path stringlengths 6 149 |
|---|---|---|
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/example_sim_rigid_gyroscopic.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/example_sim_neo_hookean.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/example_sim_sdf_shape.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/example_marching_cubes.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/example_sim_particle_chain.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/example_diffray.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/example_sim_cartpole.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/benchmark_api.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/example_sim_rigid_kinematics.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/example_dem.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/example_sim_rigid_contact.py |
"""
This example simulates a convection-diffusion PDE using FVM with upwind transport
D phi / dt + nu Div f = 0
f = grad phi
"""
import argparse
import warp as wp
from warp.fem.types import *
from warp.fem.geometry import Grid2D, Trimesh2D
from warp.fem.field import make_test, make_trial
from warp.fem.space impo... | warp-main | examples/fem/example_convection_diffusion_dg0.py |
from typing import Union, Any, Tuple
import warp as wp
import warp.types
from warp.sparse import BsrMatrix, bsr_zeros, bsr_get_diag, bsr_mv
from warp.utils import array_inner
try:
from scipy.sparse import csr_array, bsr_array
except ImportError:
# WAR for older scipy
try:
from scipy.sparse import... | warp-main | examples/fem/bsr_utils.py |
"""
This example computes a 3D weakly-compressible Stokes flow around a moving object, including:
- defining active cells from a mask, and restricting the computation domain to those
- utilizing the PicQuadrature to integrate over unstructured particles
"""
import warp as wp
import numpy as np
from warp.fem.type... | warp-main | examples/fem/example_stokes_transfer_3d.py |
"""
This example simulates a convection-diffusion PDE using Discontinuous Galerkin
with upwind transport and Symmetric Interior Penalty
D phi / dt - nu d2 phi / dx^2 = 0
"""
import argparse
import warp as wp
from warp.fem.types import *
from warp.fem.geometry import Grid2D, Trimesh2D
from warp.fem.field import ma... | warp-main | examples/fem/example_convection_diffusion_dg.py |
"""
This example illustrates using domain decomposition to solve a diffusion PDE over multiple devices
"""
from typing import Tuple
import warp as wp
from warp.fem.types import *
from warp.fem.geometry import Grid2D, LinearGeometryPartition
from warp.fem.space import make_polynomial_space, make_space_partition
from ... | warp-main | examples/fem/example_diffusion_mgpu.py |
warp-main | examples/fem/__init__.py | |
import os
import math
from typing import Any
import warp as wp
import numpy as np
import warp.sim.render
from warp.sim import Model, State
from warp.fem.geometry import Grid3D
from warp.fem.domain import Cells, BoundarySides
from warp.fem.space import make_polynomial_space
from warp.fem.quadrature import PicQuadratu... | warp-main | examples/fem/example_apic_fluid.py |
"""
This example computes a 2D weakly-compressible Stokes flow around a moving object, including:
- defining active cells from a mask, and restricting the computation domain to those
- utilizing the PicQuadrature to integrate over unstructured particles
"""
import math
import warp as wp
import numpy as np
from ... | warp-main | examples/fem/example_stokes_transfer.py |
""" This example illustrates using Mixed FEM to solve a 2D linear elasticity problem
Div[ E: D(u) ] = 0
with Dirichlet boundary conditions on horizontal sides, and E the elasticity rank-4 tensor
"""
import argparse
import warp as wp
import numpy as np
from warp.fem.types import *
from warp.fem.geometry import Grid2... | warp-main | examples/fem/example_mixed_elasticity.py |
"""
This example solves a 2D Stokes flow problem
-nu D(u) + grad p = 0
Div u = 0
with (soft) velocity-Dirichlet boundary conditions
"""
import argparse
import warp as wp
import numpy as np
from warp.fem.types import *
from warp.fem.geometry import Grid2D, Trimesh2D
from warp.fem.field import make_test, make_t... | warp-main | examples/fem/example_stokes.py |
import numpy as np
def plot_grid_surface(field, axes=None):
import matplotlib.pyplot as plt
from matplotlib import cm
if axes is None:
fig, axes = plt.subplots(subplot_kw={"projection": "3d"})
node_positions = field.space.node_positions()
# Make data.
X = node_positions[0]
Y = n... | warp-main | examples/fem/plot_utils.py |
"""
This example simulates a convection-diffusion PDE using semi-Lagrangian advection
D phi / dt - nu d2 phi / dx^2 = 0
"""
import argparse
import warp as wp
from warp.fem.types import *
from warp.fem.geometry import Grid2D, Trimesh2D
from warp.fem.field import make_test, make_trial
from warp.fem.space import mak... | warp-main | examples/fem/example_convection_diffusion.py |
"""
This example solves a 3d diffusion problem:
nu Div u = 1
with homogeneous Neumann conditions on horizontal sides and homogeneous Dirichlet boundary conditions other sides.
"""
import argparse
import warp as wp
import numpy as np
from warp.fem.types import *
from warp.fem.geometry import Grid3D, Tetmesh
from war... | warp-main | examples/fem/example_diffusion_3d.py |
"""
This example solves a 2d diffusion problem:
nu Div u = 1
with Dirichlet boundary conditions on vertical edges and homogeneous Neumann on horizontal edges.
"""
import argparse
import warp as wp
from warp.fem.types import *
from warp.fem.geometry import Grid2D, Trimesh2D
from warp.fem.space import make_polynomial... | warp-main | examples/fem/example_diffusion.py |
import numpy as np
import warp as wp
def gen_trimesh(res, bounds_lo: wp.vec2 = wp.vec2(0.0), bounds_hi: wp.vec2 = wp.vec2(1.0)):
"""Constructs a triangular mesh by diving each cell of a dense 2D grid into two triangles
Args:
res: Resolution of the grid along each dimension
bounds_lo: Position... | warp-main | examples/fem/mesh_utils.py |
"""
This example solves a 2D Navier-Stokes flow problem
Du/dt -nu D(u) + grad p = 0
Div u = 0
with (hard) velocity-Dirichlet boundary conditions
and using semi-Lagrangian advection
"""
import argparse
import warp as wp
import numpy as np
from warp.fem.types import *
from warp.fem.geometry import Grid2D, Trime... | warp-main | examples/fem/example_navier_stokes.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/env/env_cartpole.py |
warp-main | examples/env/__init__.py | |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/env/environment.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/env/env_usd.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/env/env_ant.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | examples/env/env_humanoid.py |
# Copyright (c) 2023 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/build_dll.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/build.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/config.py |
import ctypes
import math
from typing import Any
import warp
from warp.types import *
class fabricbucket_t(ctypes.Structure):
_fields_ = [
("index_start", ctypes.c_size_t),
("index_end", ctypes.c_size_t),
("ptr", ctypes.c_void_p),
("lengths", ctypes.c_void_p),
]
def __ini... | warp-main | warp/fabric.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/builtins.py |
# Copyright (c) 2023 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/dlpack.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/tape.py |
# Copyright (c) 2023 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/constants.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/__init__.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/types.py |
# Copyright (c) 2023 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/jax.py |
# Autogenerated file, do not edit, this file provides stubs for builtins autocomplete in VSCode, PyCharm, etc
from typing import Any
from typing import Tuple
from typing import Callable
from typing import TypeVar
from typing import Generic
from typing import overload as over
Length = TypeVar("Length", bound=int)
Rows... | warp-main | warp/stubs.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/context.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/utils.py |
import warp as wp
import warp.types
import warp.utils
from typing import Tuple, Any, Union
_struct_cache = dict()
class BsrMatrix:
"""Untyped base class for BSR and CSR matrices.
Should not be constructed directly but through functions such as :func:`bsr_zeros`.
Attributes:
nrow (int): Number... | warp-main | warp/sparse.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/torch.py |
# Copyright (c) 2022 NVIDIA CORPORATION. All rights reserved.
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and relate... | warp-main | warp/codegen.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
import enum
import os.path
import shutil
import functools
import operator
import collections
from library import *
###################################################################################################
#
# Data structure model... | warp-main | warp/native/cutlass/tools/library/scripts/gemm_operation.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
import re
###################################################################################################
import enum
# The following block implements enum.auto() for Python 3.5 variants that don't include it such
# as the default 3.5... | warp-main | warp/native/cutlass/tools/library/scripts/library.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
import enum
import os.path
import shutil
from library import *
from gemm_operation import *
from rank_k_operation import *
from rank_2k_operation import *
from trmm_operation import *
from symm_operation import *
from conv2d_operation impor... | warp-main | warp/native/cutlass/tools/library/scripts/manifest.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
#
import enum
import os.path
import shutil
import functools
import operator
from library import *
###################################################################################################
#
# Data structure modeling a Rank K up... | warp-main | warp/native/cutlass/tools/library/scripts/rank_k_operation.py |
#################################################################################################
#
# Copyright (c) 2017 - 2022 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 permitt... | warp-main | warp/native/cutlass/tools/library/scripts/rt.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
#
import enum
import os.path
import shutil
from library import *
###################################################################################################
#
class Conv2dOperation:
#
def __init__(self, conv_kind, iterator_alg... | warp-main | warp/native/cutlass/tools/library/scripts/conv2d_operation.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
import enum
import os.path
import shutil
import argparse
from library import *
from manifest import *
from itertools import product
###################################################################################################
#
def ... | warp-main | warp/native/cutlass/tools/library/scripts/generator.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
#
import enum
import os.path
import shutil
from library import *
###################################################################################################
#
class Conv3dOperation:
#
def __init__(self, conv_kind, iterator_alg... | warp-main | warp/native/cutlass/tools/library/scripts/conv3d_operation.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
#
import enum
import os.path
import shutil
import functools
import operator
from library import *
###################################################################################################
#
# Data structure modeling a Rank K up... | warp-main | warp/native/cutlass/tools/library/scripts/rank_2k_operation.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
#
import enum
import os.path
import shutil
import functools
import operator
from library import *
###################################################################################################
#
# Data structure modeling a Symm upda... | warp-main | warp/native/cutlass/tools/library/scripts/symm_operation.py |
#
# \file generator.py
#
# \brief Generates the CUTLASS Library's instances
#
#
import enum
import os.path
import shutil
import functools
import operator
from library import *
###################################################################################################
#
# Data structure modeling a TRMM oper... | warp-main | warp/native/cutlass/tools/library/scripts/trmm_operation.py |
import distutils.cmd
from setuptools import setup
import setuptools.command.build_py
import os
# build rmm dependency
class BuildRMM(distutils.cmd.Command):
user_options = []
def initialize_options(self):
pass
def finalize_options(self):
pass
def run(self):
try:
impo... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/setup.py |
#################################################################################################
#
# Copyright (c) 2017 - 2022 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 permitt... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/unit/test_sm80.py |
#################################################################################################
#
# Copyright (c) 2017 - 2022 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 permitt... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/frontend/test_frontend.py |
# test/unit/conv/device/conv2d_fprop_implicit_gemm_tf32nhwc_tf32nhwc_f32nhwc_tensor_op_f32_sm80.cu
import pycutlass
from pycutlass import *
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 t... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_dgrad_implicit_gemm_tf32nhwc_tf32nhwc_f32nhwc_tensor_op_f32_sm80.py |
# test/unit/conv/device/conv2d_fprop_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm80.cu
import pycutlass
from pycutlass import *
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tes... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_dgrad_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm80.py |
# test/unit/conv/device/conv2d_dgrad_implicit_gemm_f16nhwc_f16nhwc_f16nhwc_tensor_op_f16_sm80.cu
from pycutlass.conv2d_operation import *
from pycutlass import *
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute capability is i... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_dgrad_implicit_gemm_f16nhwc_f16nhwc_f16nhwc_tensor_op_f16_sm80.py |
# test/unit/conv/device/conv2d_strided_dgrad_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm80.cu
import pycutlass
from pycutlass import *
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for ... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_strided_dgrad_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm80.py |
# test/unit/conv/device/conv2d_fprop_few_channels_f16nhwc_f16nhwc_f16nhwc_tensor_op_f32_sm80.cu
import pycutlass
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tests.")
def conv2d_few_chan... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_fprop_few_channels_f16nhwc_f16nhwc_f16nhwc_tensor_op_f32_sm80.py |
# test/unit/conv/device/conv2d_wgrad_implicit_gemm_f16nhwc_f16nhwc_f16nhwc_tensor_op_f16_sm80.cu
import pycutlass
from pycutlass import *
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tes... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_wgrad_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm80.py |
# test/unit/conv/device/conv2d_dgrad_implicit_gemm_f32nhwc_f32nhwc_f32nhwc_simt_f32_sm80.cu
import pycutlass
from pycutlass.conv2d_operation import *
from pycutlass import *
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute cap... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_dgrad_implicit_gemm_f32nhwc_f32nhwc_f32nhwc_simt_f32_sm80.py |
# test/unit/conv/device/conv2d_fprop_implicit_gemm_f32nhwc_f32nhwc_f32nhwc_simt_f32_sm80.cu
import pycutlass
from pycutlass.conv2d_operation import *
from pycutlass import *
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute cap... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_fprop_implicit_gemm_f32nhwc_f32nhwc_f32nhwc_simt_f32_sm80.py |
warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/__init__.py | |
# test/unit/conv/device/conv2d_wgrad_implicit_gemm_f16nhwc_f16nhwc_f16nhwc_tensor_op_f16_sm80.cu
import pycutlass
from pycutlass import *
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tes... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_wgrad_implicit_gemm_f16nhwc_f16nhwc_f16nhwc_tensor_op_f16_sm80.py |
# test/unit/conv/device/conv2d_fprop_fixed_channels_f16nhwc_f16nhwc_f16nhwc_tensor_op_f32_sm80.cu
import pycutlass
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tests.")
def conv2d_fixed_... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_fprop_fixed_channels_f16nhwc_f16nhwc_f16nhwc_tensor_op_f32_sm80.py |
# test/unit/conv/device/conv2d_fprop_implicit_gemm_tf32nhwc_tf32nhwc_f32nhwc_tensor_op_f32_sm80.cu
import pycutlass
from pycutlass import *
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 t... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_fprop_implicit_gemm_tf32nhwc_tf32nhwc_f32nhwc_tensor_op_f32_sm80.py |
# test/unit/conv/device/conv2d_fprop_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm80.cu
import pycutlass
from pycutlass import *
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tes... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_fprop_implicit_gemm_f16nhwc_f16nhwc_f32nhwc_tensor_op_f32_sm80.py |
# test/unit/conv/device/conv2d_wgrad_implicit_gemm_f32nhwc_f32nhwc_f32nhwc_simt_f32_sm80.cu
import pycutlass
from pycutlass.conv2d_operation import *
from pycutlass import *
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute cap... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_wgrad_implicit_gemm_f32nhwc_f32nhwc_f32nhwc_simt_f32_sm80.py |
import pycutlass
import unittest
from pycutlass.memory_manager import *
if __name__ == '__main__':
pycutlass.get_memory_pool(2**32, 2**32)
loader = unittest.TestLoader()
tests = loader.discover('./', 'conv2d_*.py')
testRunner = unittest.runner.TextTestRunner()
testRunner.run(tests)
| warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/run_all_tests.py |
# test/unit/conv/device/conv2d_wgrad_implicit_gemm_tf32nhwc_tf32nhwc_f32nhwc_tensor_op_f32_sm80.cu
import pycutlass
from pycutlass import *
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 t... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_wgrad_implicit_gemm_tf32nhwc_tf32nhwc_f32nhwc_tensor_op_f32_sm80.py |
# test/unit/conv/device/conv2d_fprop_implicit_gemm_f16nhwc_f16nhwc_f16nhwc_tensor_op_f16_sm80.cu
import pycutlass
from pycutlass import *
from pycutlass.test import *
from pycutlass.utils.device import device_cc
import unittest
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tes... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/conv/conv2d_fprop_implicit_gemm_f16nhwc_f16nhwc_f16nhwc_tensor_op_f16_sm80.py |
warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/gemm/__init__.py | |
import pycutlass
from pycutlass import *
from pycutlass.test import *
import unittest
from pycutlass.test.gemm_testbed import test_all_gemm
from pycutlass.utils.device import device_cc
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tests.")
class GemmF64TensorOpSm80(unittest.T... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/gemm/gemm_f64_sm80.py |
import pycutlass
from pycutlass import *
from pycutlass.test import *
import unittest
from pycutlass.test.gemm_testbed import test_all_gemm
from pycutlass.utils.device import device_cc
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tests.")
class GemmBF16TensorOpSm80(unittest.... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/gemm/gemm_bf16_sm80.py |
import pycutlass
from pycutlass import *
from pycutlass.test import *
import unittest
from pycutlass.test.gemm_testbed import test_all_gemm
from pycutlass.utils.device import device_cc
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tests.")
class GemmF16Sm80(unittest.TestCase)... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/gemm/gemm_f16_sm80.py |
import pycutlass
from pycutlass import *
from pycutlass.memory_manager import get_allocated_size
from pycutlass.test import *
import unittest
from pycutlass.test.gemm_testbed import test_all_gemm
from pycutlass.utils.device import device_cc
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficien... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/gemm/gemm_f32_sm80.py |
import pycutlass
from pycutlass import *
from pycutlass.epilogue import LinearCombinationClamp
from pycutlass.test import *
import unittest
from pycutlass.test.gemm_testbed import test_all_gemm
from pycutlass.utils.device import device_cc
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient ... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/gemm/gemm_s8_sm80.py |
import pycutlass
from pycutlass import *
from pycutlass.test import *
import unittest
from pycutlass.test.gemm_grouped_testbed import TestbedGrouped
from pycutlass.utils.device import device_cc
@unittest.skipIf(device_cc() < 80, "Device compute capability is insufficient for SM80 tests.")
class GemmGroupedSm80(unitt... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/gemm/gemm_grouped_sm80.py |
import pycutlass
import unittest
if __name__ == '__main__':
pycutlass.get_memory_pool(2**26, 2**26)
loader = unittest.TestLoader()
tests = loader.discover('./', 'gemm_*.py')
testRunner = unittest.runner.TextTestRunner()
testRunner.run(tests)
| warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/test/gemm/run_all_tests.py |
#################################################################################################
#
# Copyright (c) 2017 - 2022 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 permitt... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/docs/source/conf.py |
#################################################################################################
#
# Copyright (c) 2017 - 2022 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 permitt... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/profile/conv/conv2d_f16_sm80.py |
#################################################################################################
#
# Copyright (c) 2017 - 2022 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 permitt... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/profile/gemm/gemm_f32_sm80.py |
#################################################################################################
#
# Copyright (c) 2017 - 2022 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 permitt... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/src/pycutlass/c_types.py |
#################################################################################################
#
# Copyright (c) 2017 - 2022 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 permitt... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/src/pycutlass/memory_manager.py |
#################################################################################################
#
# Copyright (c) 2017 - 2022 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 permitt... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/src/pycutlass/compiler.py |
################################################################################
#
# Copyright (c) 2017 - 2022 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 ... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/src/pycutlass/gemm_operation.py |
#################################################################################################
#
# Copyright (c) 2017 - 2022 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 permitt... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/src/pycutlass/library.py |
################################################################################
#
# Copyright (c) 2017 - 2022 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 ... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/src/pycutlass/type_hint.py |
################################################################################
#
# Copyright (c) 2017 - 2022 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 ... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/src/pycutlass/reduction_operation.py |
#################################################################################################
#
# Copyright (c) 2017 - 2022 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 permitt... | warp-main | warp/native/cutlass/tools/library/scripts/pycutlass/src/pycutlass/arguments.py |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.