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from .event import Event | ||
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from . import cublas | ||
from . import cudnn |
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# Licensed 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. | ||
from .ffi import cudnnDataType | ||
from .kernels import conv2d |
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# Licensed 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. | ||
import os | ||
import sys | ||
import glob | ||
from enum import IntEnum | ||
from ctypes import c_int32, c_void_p, c_char_p | ||
from hidet.ffi.ffi import get_func | ||
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from hidet.utils.py import initialize | ||
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class cudnnDataType(IntEnum): | ||
""" | ||
defined in cudnn_ops_infer_v8.h | ||
""" | ||
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CUDNN_DATA_FLOAT = 0 | ||
CUDNN_DATA_DOUBLE = 1 | ||
CUDNN_DATA_HALF = 2 | ||
CUDNN_DATA_INT8 = 3 | ||
CUDNN_DATA_INT32 = 4 | ||
CUDNN_DATA_INT8x4 = 5 | ||
CUDNN_DATA_UINT8 = 6 | ||
CUDNN_DATA_UINT8x4 = 7 | ||
CUDNN_DATA_INT8x32 = 8 | ||
CUDNN_DATA_BFLOAT16 = 9 | ||
CUDNN_DATA_INT64 = 10 | ||
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set_library_path = get_func(func_name='hidet_cudnn_set_library_path', arg_types=[c_char_p], restype=None) | ||
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conv2d = get_func( | ||
func_name='hidet_cudnn_conv2d', | ||
arg_types=[ | ||
c_int32, # n | ||
c_int32, # c | ||
c_int32, # h | ||
c_int32, # w | ||
c_int32, # k | ||
c_int32, # r | ||
c_int32, # s | ||
c_int32, # p | ||
c_int32, # q | ||
c_void_p, # ptr_x | ||
c_void_p, # ptr_w | ||
c_void_p, # ptr_y | ||
c_int32, # tx | ||
c_int32, # tw | ||
c_int32, # ty | ||
c_int32, # compute_type | ||
c_int32, # pad_dim1 | ||
c_int32, # pad_dim2 | ||
c_int32, # str_dim1 | ||
c_int32, # str_dim2 | ||
c_int32, # dil_dim1 | ||
c_int32, # dil_dim2 | ||
], | ||
restype=None, | ||
) | ||
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@initialize() | ||
def set_cudnn_library_path(): | ||
# use nvidia-cuda-cudnn | ||
for path in sys.path: | ||
nvidia_path = os.path.join(path, 'nvidia') | ||
if not os.path.exists(nvidia_path): | ||
continue | ||
cudnn_path = glob.glob(os.path.join(nvidia_path, 'cudnn', 'lib', 'libcudnn.so.[0-9]*')) | ||
if cudnn_path: | ||
set_library_path(cudnn_path[0].encode('utf-8')) | ||
return |
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# 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. | ||
from typing import Union | ||
from hidet.ir.dtypes import DataType | ||
from .ffi import cudnnDataType | ||
from . import ffi | ||
from .utils import as_pointer, as_cudnn_type | ||
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def conv2d( | ||
n: int, | ||
c: int, | ||
h: int, | ||
w: int, | ||
k: int, | ||
r: int, | ||
s: int, | ||
p: int, | ||
q: int, | ||
ptr_x, | ||
ptr_w, | ||
ptr_y, | ||
tx: Union[int, DataType], | ||
tw: Union[int, DataType], | ||
ty: Union[int, DataType], | ||
compute_type: Union[int, cudnnDataType], | ||
pad_dim1: int, | ||
pad_dim2: int, | ||
str_dim1: int, | ||
str_dim2: int, | ||
dil_dim1: int, | ||
dil_dim2: int, | ||
): | ||
""" | ||
Calculates the 2D convolution of tensor x with filter w, stores the result in tensor y. | ||
Parameters | ||
---------- | ||
n: int | ||
Batch number. | ||
c: int | ||
Number of channels in the input tensor x. | ||
h: int | ||
Height of the input tensor x. | ||
w: int | ||
Width of the input tensor x. | ||
k: int | ||
Number of channels in the output tensor y. | ||
r: int | ||
Height of the filter w. | ||
s: int | ||
Width of the filter w. | ||
p: int | ||
Height of the output tensor y. | ||
q: int | ||
Width of the output tensor y. | ||
ptr_x: hidet.Tensor or int | ||
Input tensor x, can be either a Tensor or an integer (the address of the tensor). | ||
ptr_w: hidet.Tensor or int | ||
Weight tensor w, can be either a Tensor or an integer (the address of the tensor). | ||
ptr_y: hidet.Tensor or int | ||
Output tensor y, can be either a Tensor or an integer (the address of the tensor). | ||
tx: Union[int, DataType] | ||
Type of elements in tensor x. | ||
tw: Union[int, DataType] | ||
Type of elements in tensor w. | ||
ty: Union[int, DataType] | ||
Type of elements in tensor y. | ||
compute_type: Union[int, cudnnDataType] | ||
The compute type of the operation. | ||
For cuDNN, there's no such thing as a cudnnComputeType_t type. | ||
As per the official example, the computeType is defined in terms of cudnnDataType_t | ||
pad_dim1: int | ||
The value to use for padding along the height dimension | ||
pad_dim2: int | ||
The value to use for padding along the width dimension | ||
str_dim1: int | ||
The stride to use for the height dimension | ||
str_dim2: int | ||
The stride to use for the width dimension | ||
dil_dim1: int | ||
The dilation to use for the height dimension | ||
dil_dim2: int | ||
The dilation to use for the width dimension | ||
""" | ||
ffi.conv2d( | ||
n, | ||
c, | ||
h, | ||
w, | ||
k, | ||
r, | ||
s, | ||
p, | ||
q, | ||
as_pointer(ptr_x), | ||
as_pointer(ptr_w), | ||
as_pointer(ptr_y), | ||
as_cudnn_type(tx), | ||
as_cudnn_type(tw), | ||
as_cudnn_type(ty), | ||
compute_type, | ||
pad_dim1, | ||
pad_dim2, | ||
str_dim1, | ||
str_dim2, | ||
dil_dim1, | ||
dil_dim2, | ||
) |
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# Licensed 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. | ||
from hidet.ir import dtypes | ||
from hidet.ir.dtypes import DataType | ||
from .ffi import cudnnDataType | ||
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_cudnn_type_dict = { | ||
dtypes.float32: cudnnDataType.CUDNN_DATA_FLOAT, | ||
dtypes.float64: cudnnDataType.CUDNN_DATA_DOUBLE, | ||
dtypes.int32: cudnnDataType.CUDNN_DATA_INT32, | ||
dtypes.int64: cudnnDataType.CUDNN_DATA_INT64, | ||
} | ||
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def as_pointer(obj) -> int: | ||
from hidet.graph.tensor import Tensor | ||
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if isinstance(obj, Tensor): | ||
return obj.storage.addr | ||
elif isinstance(obj, int): | ||
return obj | ||
else: | ||
raise TypeError(f'Expected Tensor or int, but got {type(obj)}') | ||
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def as_cudnn_type(obj) -> int: | ||
if isinstance(obj, DataType): | ||
return _cudnn_type_dict[obj] | ||
elif isinstance(obj, int): | ||
return obj | ||
else: | ||
raise TypeError(f'Expected DataType or int, but got {type(obj)}') |
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