entry_point stringlengths 1 65 | original_triton_python_code stringlengths 208 619k | optimised_triton_code stringlengths 1.15k 275k | repo_name stringlengths 7 115 | module_name stringlengths 1 65 | synthetic bool 1
class | uuid int64 0 18.5k | licenses listlengths 1 6 | stars int64 0 19.8k | sha stringlengths 40 40 | repo_link stringlengths 72 180 |
|---|---|---|---|---|---|---|---|---|---|---|
Upsample | import torch
import torch.nn as nn
import torch._utils
import torch.utils.data
import torch.utils.data.distributed
import torch.nn.functional as F
import torch.nn.parallel
import torch.optim
class Upsample(nn.Module):
""" nn.Upsample is deprecated """
def __init__(self, scale_factor, mode='linear'):
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch._utils
import torch.utils.data
import torch.utils.data... | fsImageries/video-to-pose3D | Upsample | false | 10,179 | [
"MIT"
] | 0 | 098c87ce19dc3331da03e6eac0b9744684eb66f6 | https://github.com/fsImageries/video-to-pose3D/tree/098c87ce19dc3331da03e6eac0b9744684eb66f6 |
SpatialSELayer3D | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Nightmare4214/FracNet | SpatialSELayer3D | false | 2,698 | [
"Apache-2.0"
] | 0 | db397adb50f71387155d9d110302a5968f86f756 | https://github.com/Nightmare4214/FracNet/tree/db397adb50f71387155d9d110302a5968f86f756 |
LR_PAD | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | roxyrypler/HorizonNet | LR_PAD | false | 12,945 | [
"MIT"
] | 0 | 303322deb652d0985936f084ba9a08d232a60427 | https://github.com/roxyrypler/HorizonNet/tree/303322deb652d0985936f084ba9a08d232a60427 |
Mnist_CNN | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.quantization
import torch.onnx
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
class Mnist_CNN(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | Justin-A/PyTorch-tutorials-kr | Mnist_CNN | false | 5,427 | [
"BSD-3-Clause"
] | 1 | 0d8e407523e5e75de0081becf800b82b37eb912f | https://github.com/Justin-A/PyTorch-tutorials-kr/tree/0d8e407523e5e75de0081becf800b82b37eb912f |
FiLMLayer_PreSin | import torch
import numpy as np
from torch import nn
class FiLMLayer_PreSin(nn.Module):
def __init__(self, in_dim, out_dim, style_dim, use_style_fc=True,
which_linear=nn.Linear, **kwargs):
super(FiLMLayer_PreSin, self).__init__()
self.in_dim = in_dim
self.out_dim = out_dim
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import numpy ... | PeterouZh/CIPS-3D | FiLMLayer_PreSin | false | 14,179 | [
"MIT"
] | 308 | 9b8bfa0fb23f642af042e150ccd70408f9d137c6 | https://github.com/PeterouZh/CIPS-3D/tree/9b8bfa0fb23f642af042e150ccd70408f9d137c6 |
EdgeFeaturesLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | odb9402/MAT | EdgeFeaturesLayer | false | 4,106 | [
"MIT"
] | 0 | 95d8083170da2c8ce1f5898b3a556bcf54eac8cc | https://github.com/odb9402/MAT/tree/95d8083170da2c8ce1f5898b3a556bcf54eac8cc |
Conv2d | from torch.nn import Module
import math
import torch
from torch.nn import functional as F
import torch.utils.data
from torch.nn.parameter import Parameter
from torch.nn.functional import pad
from torch.nn.modules import Module
from torch.nn.modules.utils import _pair
import torch.nn.parallel
def conv2d_same_padding(i... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import Module
import math
from torch.nn import functional as F
imp... | AvrilCheng/LidarStereoNet | Conv2d | false | 7,749 | [
"MIT"
] | 27 | 96c7cd6d5edb9b2fd302e2edd0c05cbda1ed024e | https://github.com/AvrilCheng/LidarStereoNet/tree/96c7cd6d5edb9b2fd302e2edd0c05cbda1ed024e |
ClusterAssignment | import torch
import torch.nn as nn
from torch.nn import Parameter
from typing import Optional
class ClusterAssignment(nn.Module):
def __init__(self, cluster_number: 'int', embedding_dimension: 'int',
alpha: 'float'=1.0, cluster_centers: 'Optional[torch.Tensor]'=None
) ->None:
"""
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.nn import Parameter
from typing import Optional
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | zhyhan/pt-dec | ClusterAssignment | false | 13,179 | [
"MIT"
] | 0 | 52aef59e508c8e7ffdde0fd7bea84570a7571b2a | https://github.com/zhyhan/pt-dec/tree/52aef59e508c8e7ffdde0fd7bea84570a7571b2a |
CovSepBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as M
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | SuperbTUM/RAW-image-denoising | CovSepBlock | false | 17,971 | [
"MIT"
] | 4 | 9f81be8da6a576f641022707d98b8c37f5c599ab | https://github.com/SuperbTUM/RAW-image-denoising/tree/9f81be8da6a576f641022707d98b8c37f5c599ab |
ResHead | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import Module
import torch.utils.data
import torch.nn as nn
assert... | KateHaeun/pycls | ResHead | false | 11,605 | [
"MIT"
] | 0 | f3d87a36cb0a8adead31c7ad98f43facf7fe4c47 | https://github.com/KateHaeun/pycls/tree/f3d87a36cb0a8adead31c7ad98f43facf7fe4c47 |
MeanEmbedding | import torch
import torch.nn as nn
import torch.utils.data
import torch.multiprocessing
import torch.nn.modules.loss
from scipy.sparse import *
class MeanEmbedding(nn.Module):
"""Mean embedding class.
"""
def __init__(self):
super(MeanEmbedding, self).__init__()
def forward(self, emb, len_):... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
import torch.multiprocessing
import torch.nn.modules.loss
from scipy.sparse import *
assert_si... | LucasAPayne/graph4nlp | MeanEmbedding | false | 9,669 | [
"Apache-2.0"
] | 0 | 3b72308f6ed9ce04c535f78b4b21b6ae0a8f5421 | https://github.com/LucasAPayne/graph4nlp/tree/3b72308f6ed9ce04c535f78b4b21b6ae0a8f5421 |
HyperConv2d | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
def get_activation_name(activation):
"""Given a string or a `torch.nn.modules.activation` return the name of the activation."""
if isinstance(activation, str):
return activation
mapper = {nn.LeakyReLU: 'leak... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
as... | Justin-Tan/ffjord | HyperConv2d | false | 698 | [
"MIT"
] | 0 | 2caf8a4ff84933672fe0d94255d665b3dd7a6791 | https://github.com/Justin-Tan/ffjord/tree/2caf8a4ff84933672fe0d94255d665b3dd7a6791 |
PrecomputedNorm | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | albertvillanova/s3prl | PrecomputedNorm | false | 6,154 | [
"MIT"
] | 1 | b127ade4ed2f80a1027901bbd2f204b4fb1aaf03 | https://github.com/albertvillanova/s3prl/tree/b127ade4ed2f80a1027901bbd2f204b4fb1aaf03 |
ResNet | import torch
import torch.nn as nn
import torch.nn.functional as F
class ResNet(nn.Module):
def __init__(self, n_in, n_out):
super(ResNet, self).__init__()
self.fc1 = nn.Linear(n_in, n_out)
self.fc2 = nn.Linear(n_in, n_out)
def forward(self, x):
h1 = F.relu(self.fc1(x))
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | AutumnCrocus/shadow_sim | ResNet | false | 16,959 | [
"MIT"
] | 6 | 79ad13ff9bd7131c82f269af32a3970f3e4bf2ca | https://github.com/AutumnCrocus/shadow_sim/tree/79ad13ff9bd7131c82f269af32a3970f3e4bf2ca |
GeneratorBlock | import math
import torch
import numpy as np
from torch import nn
from typing import Tuple
import torch.nn.functional as F
import torch.utils.data
import torch.nn.functional
from typing import List
from typing import Optional
import torch.autograd
class EqualizedWeight(nn.Module):
"""
<a id="equalized_weight">... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import ... | Aarsh2001/annotated_deep_learning_paper_implementations | GeneratorBlock | false | 4,821 | [
"MIT"
] | 1 | ff0d5c065da1a46769f5f66fddc252c178f8fa37 | https://github.com/Aarsh2001/annotated_deep_learning_paper_implementations/tree/ff0d5c065da1a46769f5f66fddc252c178f8fa37 |
StyleBlock | import math
import torch
import numpy as np
from torch import nn
import torch.nn.functional as F
import torch.utils.data
from typing import Optional
from typing import List
import torch.nn.functional
import torch.autograd
class EqualizedWeight(nn.Module):
"""
<a id="equalized_weight"></a>
## Learning-rat... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import ... | techthiyanes/annotated_deep_learning_paper_implementations | StyleBlock | false | 16,576 | [
"MIT"
] | 3,714 | 8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 | https://github.com/techthiyanes/annotated_deep_learning_paper_implementations/tree/8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 |
IdentityPadding | import torch
import torch.nn as nn
import torch.nn.functional as F
class IdentityPadding(nn.Module):
def __init__(self, num_filters, channels_in, stride):
super(IdentityPadding, self).__init__()
self.identity = nn.MaxPool2d(1, stride=stride)
self.num_zeros = num_filters - channels_in
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | citelab/fastsync | IdentityPadding | false | 1,710 | [
"Apache-2.0"
] | 0 | 8e2166f87fc53479b57fef536a971c3a2e6e4309 | https://github.com/citelab/fastsync/tree/8e2166f87fc53479b57fef536a971c3a2e6e4309 |
ModConst | import torch
class ModConst(torch.nn.Module):
def __init__(self):
super(ModConst, self).__init__()
def forward(self, x):
return x % 2.0
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | Ilyabasharov/torch2trt | ModConst | false | 2,537 | [
"MIT"
] | 0 | 76bf298b3da408509665e23e2494922b131afb10 | https://github.com/Ilyabasharov/torch2trt/tree/76bf298b3da408509665e23e2494922b131afb10 |
ResidualBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | alsgkals2/SRResCGAN | ResidualBlock | false | 14,824 | [
"MIT"
] | 81 | a71201a93e1819045f9c7711743812546d3a1f31 | https://github.com/alsgkals2/SRResCGAN/tree/a71201a93e1819045f9c7711743812546d3a1f31 |
SeqAttnMatch | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | ys7yoo/DrQAKor | SeqAttnMatch | false | 13,157 | [
"BSD-3-Clause"
] | 0 | ed9a69dd2a95f8ccb81bd5d6db0fbd59aae0be50 | https://github.com/ys7yoo/DrQAKor/tree/ed9a69dd2a95f8ccb81bd5d6db0fbd59aae0be50 |
SoftDiceLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.backends.cudnn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
em... | jayden-chua/image-mask | SoftDiceLoss | false | 3,696 | [
"MIT"
] | 0 | ce2c6a32bf13df582e7b57e506d58518258be292 | https://github.com/jayden-chua/image-mask/tree/ce2c6a32bf13df582e7b57e506d58518258be292 |
SaAdaIN | import torch
import torch.nn as nn
import torch.optim
import torch.utils.data
def calc_mean_std(feat, eps=1e-05):
size = feat.size()
assert len(size) == 4
N, C = size[:2]
feat_var = feat.view(N, C, -1).var(dim=2) + eps
feat_std = feat_var.sqrt().view(N, C, 1, 1)
feat_mean = feat.view(N, C, -1)... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.optim
import torch.utils.data
assert_size_st... | VITA-Group/Sandwich-Batch-Normalization | SaAdaIN | false | 14,541 | [
"MIT"
] | 46 | 25e7df6e64a67cebd7e70b911f874cfc1bd19df0 | https://github.com/VITA-Group/Sandwich-Batch-Normalization/tree/25e7df6e64a67cebd7e70b911f874cfc1bd19df0 |
MyElementwiseModule | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn.parallel
import torch.utils.data
import torch.onnx
import torch.fx
import torch.optim
import torch.utils.data.distributed
as... | lenaguignard/examples | MyElementwiseModule | false | 15,899 | [
"BSD-3-Clause"
] | 19,783 | 973e77b725a6028289a90170f0b237ea2e71d4f2 | https://github.com/lenaguignard/examples/tree/973e77b725a6028289a90170f0b237ea2e71d4f2 |
PatchMerging | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | ChristophReich1996/Swin-Transformer-V2 | PatchMerging | false | 7,929 | [
"MIT"
] | 43 | d71c1b412cd0fe13dc2557ad090cf0f027e54d47 | https://github.com/ChristophReich1996/Swin-Transformer-V2/tree/d71c1b412cd0fe13dc2557ad090cf0f027e54d47 |
DepthwiseSeparableConv | import torch
import torch.nn as nn
import torch.nn.functional as F
class DepthwiseSeparableConv(nn.Module):
"""
Depth-wise separable convolution uses less parameters to generate output by convolution.
:Examples:
>>> m = DepthwiseSeparableConv(300, 200, 5, dim=1)
>>> input_tensor = torch.ra... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | minjoong507/TVRetrieval | DepthwiseSeparableConv | false | 10,746 | [
"MIT"
] | 0 | 919e1766ab8aa1ef267bd3b80d4f87b06cde09a9 | https://github.com/minjoong507/TVRetrieval/tree/919e1766ab8aa1ef267bd3b80d4f87b06cde09a9 |
SimpleFusionGenerator | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | fangleai/encoder-agnostic-adaptation | SimpleFusionGenerator | false | 15,347 | [
"MIT"
] | 70 | d917e654152df202dd35bba49c409c3ecd24eaf7 | https://github.com/fangleai/encoder-agnostic-adaptation/tree/d917e654152df202dd35bba49c409c3ecd24eaf7 |
RSoftmax | import torch
import torch.nn.functional as F
from torch import nn
class RSoftmax(nn.Module):
"""Radix Softmax module in ``SplitAttentionConv2d``.
Args:
radix (int): Radix of input.
groups (int): Groups of input.
"""
def __init__(self, radix, groups):
super().__init__()
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
a... | Bo396543018/Picodet_Pytorch | RSoftmax | false | 7,791 | [
"Apache-2.0"
] | 16 | 276ecbf6f4f7eefbf046d1bccc25293acf28ba25 | https://github.com/Bo396543018/Picodet_Pytorch/tree/276ecbf6f4f7eefbf046d1bccc25293acf28ba25 |
CombineSlices | import torch
from torch import nn
import torch.utils.data
import torch.utils.data.distributed
import torch.optim
class CombineSlices(nn.Module):
def __init__(self, slice_dim=2):
super().__init__()
self.slice_dim = slice_dim
def forward(self, x):
return torch.index_select(x, dim=self.... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.utils.data
import torch.utils.data.distributed
import torch.optim
assert_size_stride = torch._C._dynamo.gu... | aslakey/fastMRI | CombineSlices | false | 1,483 | [
"MIT"
] | 0 | e94028aeccfdc70472b453c2ef2f072b40a287c7 | https://github.com/aslakey/fastMRI/tree/e94028aeccfdc70472b453c2ef2f072b40a287c7 |
PerceptronTanh | import torch
import torch.nn as nn
import torch.nn.functional as F
class PerceptronTanh(nn.Module):
"""Implements a 1-layer perceptron with Tanh activaton."""
def __init__(self, input_dimension, hidden_dimension, output_dimension):
super(PerceptronTanh, self).__init__()
self._layer1 = nn.Line... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | negotiatorvivian/SAT-Solver | PerceptronTanh | false | 7,326 | [
"MIT"
] | 1 | acbf375ce73103e945aee3e2a225126684a19076 | https://github.com/negotiatorvivian/SAT-Solver/tree/acbf375ce73103e945aee3e2a225126684a19076 |
SynthWide256 | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | dengliming/iotnets | SynthWide256 | false | 1,873 | [
"MIT"
] | 0 | db744e56769c799dbf765a27fc5aa91e3edeaaa3 | https://github.com/dengliming/iotnets/tree/db744e56769c799dbf765a27fc5aa91e3edeaaa3 |
ClusterAssignment | import torch
import torch.nn as nn
from torch.nn import Parameter
from typing import Optional
class ClusterAssignment(nn.Module):
def __init__(self, cluster_number: 'int', embedding_dimension: 'int',
alpha: 'float'=1.0, cluster_centers: 'Optional[torch.Tensor]'=None
) ->None:
"""
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.nn import Parameter
from typing import Optional
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | Vaaaas/OpenNRE | ClusterAssignment | false | 9,542 | [
"MIT"
] | 0 | d43859975ed3523d9a8cea02adff5c7b43f94da0 | https://github.com/Vaaaas/OpenNRE/tree/d43859975ed3523d9a8cea02adff5c7b43f94da0 |
Decoder | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from torch import nn
import torch.hub
assert_size_stride = torch._C.... | JavierCane/demucs | Decoder | false | 5,387 | [
"MIT"
] | 1 | 01d14844a71be7b5d86adf06a8501a951157c3fe | https://github.com/JavierCane/demucs/tree/01d14844a71be7b5d86adf06a8501a951157c3fe |
minibatch_std_concat_layer | import copy
import torch
import torch.nn as nn
class minibatch_std_concat_layer(nn.Module):
def __init__(self, averaging='all'):
super(minibatch_std_concat_layer, self).__init__()
self.averaging = averaging.lower()
if 'group' in self.averaging:
self.n = int(self.averaging[5:])... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | mikanCan/PG-GAN | minibatch_std_concat_layer | false | 10,648 | [
"MIT"
] | 0 | bc4a1bd2101f836c22a164174381f80b3f5c73c1 | https://github.com/mikanCan/PG-GAN/tree/bc4a1bd2101f836c22a164174381f80b3f5c73c1 |
Generator | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | kompotiks/Boris | Generator | false | 12,683 | [
"Apache-2.0"
] | 0 | 2cf9487e4bc8d81206f819c0fe5c1d793d554062 | https://github.com/kompotiks/Boris/tree/2cf9487e4bc8d81206f819c0fe5c1d793d554062 |
Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | gautam-sharma1/openRL | Net | false | 6,723 | [
"MIT"
] | 1 | 14310a97a328fe5682a01ee85d83a6b5e1ae29ca | https://github.com/gautam-sharma1/openRL/tree/14310a97a328fe5682a01ee85d83a6b5e1ae29ca |
PointLoss | import torch
import torch.nn.parallel
import torch.utils.data
import torch.nn as nn
def array2samples_distance(array1, array2):
"""
arguments:
array1: the array, size: (num_point, num_feature)
array2: the samples, size: (num_point, num_feature)
returns:
distances: each entry is th... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn.parallel
import torch.utils.data
import torch.nn as nn
assert_size_stride... | HeunSeungLim/hl_point | PointLoss | false | 13,809 | [
"MIT"
] | 204 | 866f9e216d1f47517093720f6ff70ef2f0338bbe | https://github.com/HeunSeungLim/hl_point/tree/866f9e216d1f47517093720f6ff70ef2f0338bbe |
SimpleCNNContainerConvBlocks | import torch
import torch.nn.functional as F
import torch.nn as nn
class SimpleCNNContainerConvBlocks(nn.Module):
def __init__(self, input_channel, num_filters, kernel_size, output_dim=10):
super(SimpleCNNContainerConvBlocks, self).__init__()
"""
A testing cnn container, which allows init... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | Propaler/FedMA | SimpleCNNContainerConvBlocks | false | 5,725 | [
"MIT"
] | 1 | e235d971e192fb0e93abd4ad37ac603552b6484c | https://github.com/Propaler/FedMA/tree/e235d971e192fb0e93abd4ad37ac603552b6484c |
ProteinResNetPooler | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
fr... | IC-hub/ProteinLM | ProteinResNetPooler | false | 15,190 | [
"Apache-2.0"
] | 59 | 58fbf1f674569cf814becf32f71dd0d8f0c592fa | https://github.com/IC-hub/ProteinLM/tree/58fbf1f674569cf814becf32f71dd0d8f0c592fa |
Multi_feature_fusing | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import numpy as np
import torch.nn as nn
import torch.nn.init
assert_size_strid... | AndresPMD/semantic_adaptive_margin | Multi_feature_fusing | false | 7,657 | [
"Apache-2.0"
] | 12 | 1e8bf2f1836498c48df030cb0a967b72b52e8460 | https://github.com/AndresPMD/semantic_adaptive_margin/tree/1e8bf2f1836498c48df030cb0a967b72b52e8460 |
InstanceNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
from typing import *
assert_size_stride = torch._C._dynamo... | ImadDabbura/fastai-courses | InstanceNorm | false | 17,434 | [
"Apache-2.0"
] | 3 | 053637a2dd3b4ad6c35f97a13f3fba87af1d3940 | https://github.com/ImadDabbura/fastai-courses/tree/053637a2dd3b4ad6c35f97a13f3fba87af1d3940 |
mlp | import torch
import torch.nn as nn
class mlp(nn.Module):
def __init__(self, seq_len):
super(mlp, self).__init__()
self.lin1 = nn.Linear(seq_len, 2048)
self.lin2 = nn.Linear(2048, 2048)
self.lin3 = nn.Linear(2048, seq_len)
self.relu = nn.ReLU()
def forward(self, input_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | AliRoyat/MACS_IQA | mlp | false | 7,666 | [
"Apache-2.0"
] | 16 | d37ac72170dc0271065a7c54273b70ed52aee4b8 | https://github.com/AliRoyat/MACS_IQA/tree/d37ac72170dc0271065a7c54273b70ed52aee4b8 |
_MCLSTMCell | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | kyleniemeyer/neuralhydrology | _MCLSTMCell | false | 3,892 | [
"BSD-3-Clause"
] | 0 | 440fda715c4f746a2d56b058b9af2f0e03c36aa0 | https://github.com/kyleniemeyer/neuralhydrology/tree/440fda715c4f746a2d56b058b9af2f0e03c36aa0 |
PosLinear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
fr... | KelvinKan/CP-Flow | PosLinear | false | 13,939 | [
"MIT"
] | 64 | d01303cb4ebeb5a0bbfca638ffaf5b7a8ec22fb1 | https://github.com/KelvinKan/CP-Flow/tree/d01303cb4ebeb5a0bbfca638ffaf5b7a8ec22fb1 |
TransposeConv2dLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.nn import Parameter
assert_size_stride = torch.... | autocomic/https-github.com-autocomic-DeepFillv2_Pytorch | TransposeConv2dLayer | false | 3,143 | [
"MIT"
] | 0 | 7f6712a9b42dfd827879271f13856f1da5d6a032 | https://github.com/autocomic/https-github.com-autocomic-DeepFillv2_Pytorch/tree/7f6712a9b42dfd827879271f13856f1da5d6a032 |
TargetContextGate | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | PiescesHusky/OpenNMT-py | TargetContextGate | false | 11,781 | [
"MIT"
] | 0 | 7276cf94f989c50b3169742f64e64142897d1ec0 | https://github.com/PiescesHusky/OpenNMT-py/tree/7276cf94f989c50b3169742f64e64142897d1ec0 |
DotProductSimilarity | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | Aunsiels/qagnn | DotProductSimilarity | false | 11,299 | [
"MIT"
] | 0 | d89a3dd650ac4b8b8aae34e0cce7cfc698892d80 | https://github.com/Aunsiels/qagnn/tree/d89a3dd650ac4b8b8aae34e0cce7cfc698892d80 |
FeedForward | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | and-smith/Vac-Scholar-Curb-GAN | FeedForward | false | 6,202 | [
"MIT"
] | 1 | 142bd70fdf0f1cbc4a1c20c5e58fa5b6a9dbe742 | https://github.com/and-smith/Vac-Scholar-Curb-GAN/tree/142bd70fdf0f1cbc4a1c20c5e58fa5b6a9dbe742 |
TextProcessor | import torch
import torch.utils.data
import torch
import torch.nn as nn
import torch.nn.functional as F
def reset_parameters_util(model):
pass
class TextProcessor(nn.Module):
"""Processes sentence representations to the correct hidden dimension"""
def __init__(self, desc_dim, hid_dim):
super(Te... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
impor... | OfirShechter/NLPMultimodalGame | TextProcessor | false | 11,766 | [
"BSD-3-Clause"
] | 0 | 79bd8476da0c2f3185ed7241932bc1165558917b | https://github.com/OfirShechter/NLPMultimodalGame/tree/79bd8476da0c2f3185ed7241932bc1165558917b |
Downsample | import torch
from torch import nn
class Downsample(nn.Module):
def __init__(self, dim_in, dim_out):
super().__init__()
self.conv = nn.Conv2d(dim_in, dim_out, 3, stride=2, padding=1)
def forward(self, x):
return self.conv(x)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | Mohan-Zhang-u/vit-pytorch | Downsample | false | 11,707 | [
"MIT"
] | 0 | 76050c812474d7c10d67db4e811f537e26c3996a | https://github.com/Mohan-Zhang-u/vit-pytorch/tree/76050c812474d7c10d67db4e811f537e26c3996a |
make_dense | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.model_zoo
assert_size_stride = torch._C... | SeleSchaefer/super_resolution | make_dense | false | 17,946 | [
"MIT"
] | 5 | bf28a959fb150ceeadbd9f0bcfc12f3025cf82f4 | https://github.com/SeleSchaefer/super_resolution/tree/bf28a959fb150ceeadbd9f0bcfc12f3025cf82f4 |
OutputDiscriminator | import torch
import torch.nn as nn
class OutputDiscriminator(nn.Module):
def __init__(self):
super(OutputDiscriminator, self).__init__()
filter_num_list = [64, 128, 256, 512, 1]
self.conv1 = nn.Conv2d(2, filter_num_list[0], kernel_size=4, stride
=2, padding=2, bias=False)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | EmmaW8/BEAL | OutputDiscriminator | false | 13,683 | [
"MIT"
] | 95 | 945cad38a354605b8bca5bc01ae1b65848d605e1 | https://github.com/EmmaW8/BEAL/tree/945cad38a354605b8bca5bc01ae1b65848d605e1 |
FocalLoss | import torch
from torch import nn
class FocalLoss(nn.Module):
def __init__(self, gamma=0, eps=1e-07):
super(FocalLoss, self).__init__()
self.gamma = gamma
self.eps = eps
self.ce = torch.nn.CrossEntropyLoss(reduction='none')
def forward(self, input, target):
logp = sel... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
a... | Lascarfo/kaggle-landmark-recognition-2020-1st-place | FocalLoss | false | 2,501 | [
"MIT"
] | 0 | f9007d81e59ecd1311bdea5586a426b8973a2eb8 | https://github.com/Lascarfo/kaggle-landmark-recognition-2020-1st-place/tree/f9007d81e59ecd1311bdea5586a426b8973a2eb8 |
SFU | import torch
import torch.nn as nn
class SFU(nn.Module):
"""Semantic Fusion Unit
The ouput vector is expected to not only retrieve correlative information from fusion vectors,
but also retain partly unchange as the input vector
"""
def __init__(self, input_size, fusion_size):
super(SFU, s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | MobtgZhang/MWMLNet | SFU | false | 5,608 | [
"MIT"
] | 1 | 125bb39935916b6b4be505c51cb6a04eb49b96d0 | https://github.com/MobtgZhang/MWMLNet/tree/125bb39935916b6b4be505c51cb6a04eb49b96d0 |
MultiheadAttention | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Francois-Aubet/AHGP | MultiheadAttention | false | 8,117 | [
"MIT"
] | 19 | 3ecdd01d138f013ae8da196fbf3a71632aa2cd88 | https://github.com/Francois-Aubet/AHGP/tree/3ecdd01d138f013ae8da196fbf3a71632aa2cd88 |
CausalConv1d | import torch
from torch import nn
class CausalConv1d(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size=2, dilation=2):
super(CausalConv1d, self).__init__()
self.padding = dilation
self.causal_conv = nn.Conv1d(in_channels, out_channels, kernel_size,
padding=... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | heyitsmine/FewRel | CausalConv1d | false | 10,255 | [
"MIT"
] | 0 | 2a2b8ae471298d9eb3557796a085c23b21982fb2 | https://github.com/heyitsmine/FewRel/tree/2a2b8ae471298d9eb3557796a085c23b21982fb2 |
ConvBlock | import torch
import torch.nn as nn
class Conv3x3(nn.Module):
"""Layer to pad and convolve input
"""
def __init__(self, in_channels, out_channels, use_refl=True):
super(Conv3x3, self).__init__()
if use_refl:
self.pad = nn.ReflectionPad2d(1)
else:
self.pad = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
im... | Morbotu/drone-PWS | ConvBlock | false | 11,720 | [
"MIT"
] | 0 | face9cbf30a55783592cce8af59c1c70da982b6a | https://github.com/Morbotu/drone-PWS/tree/face9cbf30a55783592cce8af59c1c70da982b6a |
NCELoss | import torch
import torch.nn as nn
class NCELoss(nn.Module):
"""
Eq. (12): L_{NCE}
"""
def __init__(self, temperature, device):
super(NCELoss, self).__init__()
self.device = device
self.criterion = nn.CrossEntropyLoss()
self.temperature = temperature
self.cossi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | salesforce/CoSeRec | NCELoss | false | 10,763 | [
"BSD-3-Clause"
] | 0 | c0bf5e5c3a5fd645efd3d6cdb9ff6a98d1c477ef | https://github.com/salesforce/CoSeRec/tree/c0bf5e5c3a5fd645efd3d6cdb9ff6a98d1c477ef |
LossCrossentropyAgg | import torch
class LossCrossentropyAgg(torch.nn.Module):
def __init__(self):
super(LossCrossentropyAgg, self).__init__()
def forward(self, preds, target):
""" Modified crossentropy that aggregates allowed output classes into single class. """
preds = torch.clamp(preds, min=1e-10, max... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = t... | johnmous/sfaira | LossCrossentropyAgg | false | 3,763 | [
"BSD-3-Clause"
] | 0 | c50240a74530e614ab7681bf9c63b04cb815b361 | https://github.com/johnmous/sfaira/tree/c50240a74530e614ab7681bf9c63b04cb815b361 |
EncoderImagePrecomp | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import numpy as np
... | ExplorerFreda/VSE-C | EncoderImagePrecomp | false | 13,679 | [
"MIT"
] | 61 | 52d7742adfe017eacd74f36a5953ea2ace9f5fce | https://github.com/ExplorerFreda/VSE-C/tree/52d7742adfe017eacd74f36a5953ea2ace9f5fce |
outblock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.distributions.normal import Normal
import torch... | junyuchen245/TransMorph_Transformer_for_Medical_Image_Registration | outblock | false | 15,761 | [
"MIT"
] | 82 | dfa24a47a564a000aa9b4eea95a6e83a24568359 | https://github.com/junyuchen245/TransMorph_Transformer_for_Medical_Image_Registration/tree/dfa24a47a564a000aa9b4eea95a6e83a24568359 |
Swish | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
class Swish(nn.Module):
def __init__(self):
super(Swish, self).__init__()
def forward(self, x):
return 1.78718727865 * (x * torch.sigmoid(x) - 0.20662096414)
def get_inputs():
return [torch.rand([4, 4, ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty... | doudoulaile/RL-GAN-Net | Swish | false | 15,228 | [
"MIT"
] | 112 | 9c221223d1878bc24f0f39ad34928c1bb2974ae3 | https://github.com/doudoulaile/RL-GAN-Net/tree/9c221223d1878bc24f0f39ad34928c1bb2974ae3 |
SeparableConvBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
import torch.optim
assert_size_st... | carol007/pytorch-ImageNet-CIFAR-COCO-VOC-training | SeparableConvBlock | false | 6,389 | [
"MIT"
] | 1 | e8b37046e6fbe914f6a68bbde1fe419c46373c1d | https://github.com/carol007/pytorch-ImageNet-CIFAR-COCO-VOC-training/tree/e8b37046e6fbe914f6a68bbde1fe419c46373c1d |
LocationLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
from torch import nn
assert_size_stride = torch._C._dyna... | Engineering-Course/tacotron2 | LocationLayer | false | 11,400 | [
"BSD-3-Clause"
] | 0 | 7e3968670cdec9817d219fd36bb2fc631c25d350 | https://github.com/Engineering-Course/tacotron2/tree/7e3968670cdec9817d219fd36bb2fc631c25d350 |
StyleTrack | import torch
import torch.nn as nn
def gram_matrix(input):
""" gram matrix for feature assignments """
a, b, c, d = input.size()
allG = []
for i in range(a):
features = input[i].view(b, c * d)
gram = torch.mm(features, features.t())
gram = gram.div(c * d)
allG.append(gr... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | jaredaevans/UltrafastNST | StyleTrack | false | 6,929 | [
"MIT"
] | 1 | 6671c6b618ce6bb4920b15f782be962e484a5423 | https://github.com/jaredaevans/UltrafastNST/tree/6671c6b618ce6bb4920b15f782be962e484a5423 |
ResidualBlockNoBN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
from ... | achrefjarray/ESRGANplus-master | ResidualBlockNoBN | false | 1,368 | [
"Apache-2.0"
] | 0 | ba470ec5c565a6dc8b48575b1e185ef6b796aec6 | https://github.com/achrefjarray/ESRGANplus-master/tree/ba470ec5c565a6dc8b48575b1e185ef6b796aec6 |
ResidualBlock_noBN | import torch
import torch.utils.data
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.init as init
def initialize_weights(net_l, scale=1):
if not isinstance(net_l, list):
net_l = [net_l]
for net in net_l:
for m in net.modules():
if isinstance(m, nn.Conv3d):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
impor... | LCM1999/VolumeRescaling | ResidualBlock_noBN | false | 17,575 | [
"Apache-2.0"
] | 4 | 3eeabf057e68804ed945711b440f19e419c10d7a | https://github.com/LCM1999/VolumeRescaling/tree/3eeabf057e68804ed945711b440f19e419c10d7a |
CoefficientRegularization | import torch
import torch.utils.data
import torch
import torch.nn as nn
class CoefficientRegularization(nn.Module):
def __init__(self):
super(CoefficientRegularization, self).__init__()
def forward(self, input):
return torch.sum(input ** 2)
def get_inputs():
return [torch.rand([4, 4, 4... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
import torch
import torch.nn as nn
assert_size_stride = torch._C.... | LeoniusChen/AudioDVP | CoefficientRegularization | false | 5,506 | [
"MIT"
] | 1 | c3829b9f1056827e2fe8b2d1fc9083c8cba93984 | https://github.com/LeoniusChen/AudioDVP/tree/c3829b9f1056827e2fe8b2d1fc9083c8cba93984 |
Project3D | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Sid1057/sid1057.github.io | Project3D | false | 17,935 | [
"MIT"
] | 4 | 623d1731e308b42b6f86304dcfd671a061b414bf | https://github.com/Sid1057/sid1057.github.io/tree/623d1731e308b42b6f86304dcfd671a061b414bf |
LRN | import torch
import torch.nn as nn
class LRN(nn.Module):
def __init__(self, local_size=1, alpha=1.0, beta=0.75, ACROSS_CHANNELS=
False):
super(LRN, self).__init__()
self.ACROSS_CHANNELS = ACROSS_CHANNELS
if self.ACROSS_CHANNELS:
self.average = nn.AvgPool3d(kernel_size=... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | nbswords/Paper-implemention-by-Pytorch | LRN | false | 7,316 | [
"MIT"
] | 1 | 429514c4f51c41ec7b3013683fb79ad4b4ab4638 | https://github.com/nbswords/Paper-implemention-by-Pytorch/tree/429514c4f51c41ec7b3013683fb79ad4b4ab4638 |
Conv2dLayer | import torch
import torch.nn as nn
from torch.nn import Parameter
def l2normalize(v, eps=1e-12):
return v / (v.norm() + eps)
class LayerNorm(nn.Module):
def __init__(self, num_features, eps=1e-08, affine=True):
super(LayerNorm, self).__init__()
self.num_features = num_features
self.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | autocomic/deepfillv2 | Conv2dLayer | false | 12,137 | [
"MIT"
] | 0 | 4b0f565accbf20ee90093a4504b1cff0099d9cb9 | https://github.com/autocomic/deepfillv2/tree/4b0f565accbf20ee90093a4504b1cff0099d9cb9 |
TemporalConv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | marcdemers/pytorch_geometric_temporal | TemporalConv | false | 10,455 | [
"MIT"
] | 0 | 446aadcd890158bade2e9974f9840ed5a7bba827 | https://github.com/marcdemers/pytorch_geometric_temporal/tree/446aadcd890158bade2e9974f9840ed5a7bba827 |
PreActResPath | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | ArlindKadra/DeepLearning | PreActResPath | false | 18,258 | [
"Apache-2.0"
] | 4 | 4e9ffe39bbb8722ca658522e6b6d26c6f2291ef6 | https://github.com/ArlindKadra/DeepLearning/tree/4e9ffe39bbb8722ca658522e6b6d26c6f2291ef6 |
MaxPoolPad | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | RndmVariableQ/deep-person-reid | MaxPoolPad | false | 11,871 | [
"MIT"
] | 0 | 9ab8343b2fc2ac130aeca5bc2bd1ae808e9ce1b9 | https://github.com/RndmVariableQ/deep-person-reid/tree/9ab8343b2fc2ac130aeca5bc2bd1ae808e9ce1b9 |
LinearActivation | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch.nn impor... | codecaution/Hetu | LinearActivation | false | 1,726 | [
"Apache-2.0"
] | 0 | e278732c2fe3554c8d576585f5bcbf79ade31b68 | https://github.com/codecaution/Hetu/tree/e278732c2fe3554c8d576585f5bcbf79ade31b68 |
AddBroadcastPosEmbed | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | AshBT/VideoGPT | AddBroadcastPosEmbed | false | 13,306 | [
"MIT"
] | 396 | a823bc734af3387129f3bd624caad3db270707f2 | https://github.com/AshBT/VideoGPT/tree/a823bc734af3387129f3bd624caad3db270707f2 |
AsymmetricLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Return:
Tensor: Reduced loss tensor.
"""
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | kivanctezoren/mmclassification | AsymmetricLoss | false | 15,830 | [
"Apache-2.0"
] | 1,190 | 5c73d4b29f61c47d379bbec4621a465099e64bd7 | https://github.com/kivanctezoren/mmclassification/tree/5c73d4b29f61c47d379bbec4621a465099e64bd7 |
BatchSpectralLoss | import torch
def batch_spectral_loss(x, k):
singular_values = torch.linalg.svdvals(x)
return torch.sum(singular_values[:k] ** 2)
class BatchSpectralLoss(torch.nn.Module):
"""
Implementation of the loss in
[Transferability vs. Discriminability: Batch Spectral
Penalization for Adversarial Doma... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | KevinMusgrave/pytorch-adapt | BatchSpectralLoss | false | 13,946 | [
"MIT"
] | 131 | ff1491e1bfcc586afb8ee619712c8816ddf10358 | https://github.com/KevinMusgrave/pytorch-adapt/tree/ff1491e1bfcc586afb8ee619712c8816ddf10358 |
ChannelNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | B06901052/s3prl | ChannelNorm | false | 106 | [
"MIT"
] | 0 | 5f63d2df043d2d7c81580cd042fa2cea34746f48 | https://github.com/B06901052/s3prl/tree/5f63d2df043d2d7c81580cd042fa2cea34746f48 |
L2Norm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | CuongNguyen218/ObjectDetection-OneStageDet | L2Norm | false | 335 | [
"MIT"
] | 0 | 60efe8b0ee6782b2aea20a32264b2ce1fc21901f | https://github.com/CuongNguyen218/ObjectDetection-OneStageDet/tree/60efe8b0ee6782b2aea20a32264b2ce1fc21901f |
Actor1D | import torch
import torch.nn as nn
import torch.nn.functional as F
class Actor1D(nn.Module):
def __init__(self, state_dim, action_dim, max_action, option_num=3):
super(Actor1D, self).__init__()
"""
Input size: (batch_num, channel = state_dim * option_num, length = 1)
"""
s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | KuangenZhang/StructuredRL | Actor1D | false | 5,458 | [
"MIT"
] | 1 | 9b05e5034ff0e045aabf83786efb0859f08e989a | https://github.com/KuangenZhang/StructuredRL/tree/9b05e5034ff0e045aabf83786efb0859f08e989a |
RepeatModule | import torch
import torch.jit
import torch.onnx
import torch.nn
class RepeatModule(torch.nn.Module):
def __init__(self, repeats):
super(RepeatModule, self).__init__()
self.repeats = repeats
def forward(self, tensor):
tensor = tensor + tensor
return tensor.repeat(self.repeats)... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | opti-mix/glow | RepeatModule | false | 7,376 | [
"Apache-2.0"
] | 1 | 4ba074df5da9822986a23a6679ab592c22660f6d | https://github.com/opti-mix/glow/tree/4ba074df5da9822986a23a6679ab592c22660f6d |
FeedForwardNetwork | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class FeedForwardNetwork(nn.Module):
"""
Based on the paper, each layer has 2 subayers:
A multi-headed attention mechanism &
a position-wise fully connected feed-forward network
Each layer employs a r... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | benedictleedm/sgnlp | FeedForwardNetwork | false | 1,537 | [
"MIT"
] | 0 | 03f0fda8c517d9ca4baf737ce4c46b2495bbd3ba | https://github.com/benedictleedm/sgnlp/tree/03f0fda8c517d9ca4baf737ce4c46b2495bbd3ba |
SpatialGatherModule | import torch
import torch.nn.functional as F
import torch.nn as nn
import torch._C
import torch.serialization
class SpatialGatherModule(nn.Module):
"""Aggregate the context features according to the initial predicted
probability distribution.
Employ the soft-weighted method to aggregate the context.
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | CVIU-CSU/M2MRF-Lesion-Segmentation | SpatialGatherModule | false | 17,056 | [
"Apache-2.0"
] | 10 | 13af87927f4cdeca70e35d570edd1aec43b387b6 | https://github.com/CVIU-CSU/M2MRF-Lesion-Segmentation/tree/13af87927f4cdeca70e35d570edd1aec43b387b6 |
PotCoSirenModule | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_s... | qway/nerfmeshes | PotCoSirenModule | false | 16,311 | [
"MIT"
] | 113 | d983dcbbcfec1337c9f2040969213c6d1ea0c39e | https://github.com/qway/nerfmeshes/tree/d983dcbbcfec1337c9f2040969213c6d1ea0c39e |
FloorDivConst | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | NVIDIA-AI-IOT-private/torch2trt | FloorDivConst | false | 10,503 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
MetaBilinear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import re
import warnings
from torch import nn
from collections import OrderedDict
assert_size_stride = torch._C._dynamo.guards.assert_size_... | Timothy102/light-field-networks | MetaBilinear | false | 14,504 | [
"MIT"
] | 95 | 0d2d6099ea1df4332b173fab47e5606d579b4293 | https://github.com/Timothy102/light-field-networks/tree/0d2d6099ea1df4332b173fab47e5606d579b4293 |
Stoplinear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from collections import Order... | Munna-Manoj/Team7_TTS | Stoplinear | false | 11,729 | [
"MIT"
] | 0 | 5e2d473a2afe429023876bcc51c2ac966a4938b8 | https://github.com/Munna-Manoj/Team7_TTS/tree/5e2d473a2afe429023876bcc51c2ac966a4938b8 |
MLM | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | aced125/alphafold2 | MLM | false | 6,071 | [
"MIT"
] | 1 | c85682ece37d37c608773cef3ec342b9ddc7fca0 | https://github.com/aced125/alphafold2/tree/c85682ece37d37c608773cef3ec342b9ddc7fca0 |
Block | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | LRVerkin/tutorials | Block | false | 2,485 | [
"MIT"
] | 0 | 365757b0dee90f63a53851e40bfad790aca3cf8d | https://github.com/LRVerkin/tutorials/tree/365757b0dee90f63a53851e40bfad790aca3cf8d |
resnet_block | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | czq142857/DECOR-GAN | resnet_block | false | 15,102 | [
"MIT"
] | 55 | 79c80fc202b8af982989a3e3bb3afe85e606b71f | https://github.com/czq142857/DECOR-GAN/tree/79c80fc202b8af982989a3e3bb3afe85e606b71f |
CosAttention | import torch
import torch.nn as nn
class CosAttention(nn.Module):
def __init__(self):
super(CosAttention, self).__init__()
def forward(self, q, k, v):
"""
q: (batchsize, hidden_dim)
k: (batchsize, seqlen, hidden_dim)
v: (batchsize, seqlen, hidden_dim)
"""
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | Raiselimit/TorchBlocks | CosAttention | false | 5,735 | [
"MIT"
] | 1 | a5baecb9a2470ff175087475630f2b7db3f7ef51 | https://github.com/Raiselimit/TorchBlocks/tree/a5baecb9a2470ff175087475630f2b7db3f7ef51 |
Biaffine | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | ashim95/parser | Biaffine | false | 6,245 | [
"MIT"
] | 1 | 61e9cd6bf16dcf1aa2b9d51b3a6c04ed048b3199 | https://github.com/ashim95/parser/tree/61e9cd6bf16dcf1aa2b9d51b3a6c04ed048b3199 |
LxmertSelfAttentionLayer | from _paritybench_helpers import _mock_config
import math
import torch
from torch import nn
import torch.utils.checkpoint
class LxmertAttention(nn.Module):
def __init__(self, config, ctx_dim=None):
super().__init__()
if config.hidden_size % config.num_attention_heads != 0:
raise Value... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Clemens123/transformers | LxmertSelfAttentionLayer | false | 11,815 | [
"Apache-2.0"
] | 0 | 22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 | https://github.com/Clemens123/transformers/tree/22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 |
Normalize | import torch
import torch.utils.data
class Normalize(torch.nn.Module):
def __init__(self):
super(Normalize, self).__init__()
self.normalize = torch.nn.functional.normalize
def forward(self, x):
x = self.normalize(x, dim=-1)
return x
def get_inputs():
return [torch.rand(... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.data
asse... | Alescontrela/AMP_for_hardware | Normalize | false | 7,632 | [
"BSD-3-Clause"
] | 11 | bfb0dbdcf32bdf83a916790bddf193fffc7e79b8 | https://github.com/Alescontrela/AMP_for_hardware/tree/bfb0dbdcf32bdf83a916790bddf193fffc7e79b8 |
Conv2dLayer | import torch
import torch.nn as nn
from torch.nn import Parameter
def l2normalize(v, eps=1e-12):
return v / (v.norm() + eps)
class LayerNorm(nn.Module):
def __init__(self, num_features, eps=1e-08, affine=True):
super(LayerNorm, self).__init__()
self.num_features = num_features
self.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | Sheroa/Video_Colorization | Conv2dLayer | false | 2,847 | [
"MIT"
] | 0 | 5c772ac0ec944814cd8be0a94b0746116b11ac01 | https://github.com/Sheroa/Video_Colorization/tree/5c772ac0ec944814cd8be0a94b0746116b11ac01 |
AttentionPool2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | jasperhu13/deit | AttentionPool2d | false | 10,265 | [
"Apache-2.0"
] | 0 | 97b09b1c131a7ee8d01ee0ce27a936ff33cf62fc | https://github.com/jasperhu13/deit/tree/97b09b1c131a7ee8d01ee0ce27a936ff33cf62fc |
DeConv2dBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | Jimmy-INL/fourier-transformer | DeConv2dBlock | false | 5,393 | [
"MIT"
] | 1 | 44a6ebc68aef24a4eb9aaa2a8c518ede56ec47ce | https://github.com/Jimmy-INL/fourier-transformer/tree/44a6ebc68aef24a4eb9aaa2a8c518ede56ec47ce |
Merge | import torch
import torch.utils.data
from torch import nn
class Conv(nn.Module):
def __init__(self, inp_dim, out_dim, kernel_size=3, stride=1, bn=False,
relu=True):
super(Conv, self).__init__()
self.inp_dim = inp_dim
self.conv = nn.Conv2d(inp_dim, out_dim, kernel_size, stride,
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
from torch import nn
assert_size_stride = torch._C._dyna... | CenIII/pose-ae-train | Merge | false | 13,453 | [
"BSD-3-Clause"
] | 250 | 8780ba9f3d80ca3a724bbee7b815073adc3d3e6e | https://github.com/CenIII/pose-ae-train/tree/8780ba9f3d80ca3a724bbee7b815073adc3d3e6e |
LinearModel | import torch
import torch.nn as nn
import torch.autograd
import torch.backends.cudnn
class LinearModel(nn.Module):
"""
NetModel class for the neural network. inherits from NetModel.
"""
def __init__(self, input_size, output_size, hidden_size):
"""
Initialize the model.
:param ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | Guydada/MIND-Recommender-System-Ptoject-Pytorch-TF-IDF--Deep-Learning | LinearModel | false | 5,247 | [
"MIT"
] | 1 | 1f42db2f5bc29d6bafbd3261407b41ab1a6eae95 | https://github.com/Guydada/MIND-Recommender-System-Ptoject-Pytorch-TF-IDF--Deep-Learning/tree/1f42db2f5bc29d6bafbd3261407b41ab1a6eae95 |
GatedConv | import torch
import torch.nn as nn
import torch.utils.data
class GatedConv(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, stride=1,
padding=0, groups=1):
super(GatedConv, self).__init__()
self.layer_f = nn.Conv2d(in_channels, out_channels, kernel_size,
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | Justin-Tan/ffjord | GatedConv | false | 734 | [
"MIT"
] | 0 | 2caf8a4ff84933672fe0d94255d665b3dd7a6791 | https://github.com/Justin-Tan/ffjord/tree/2caf8a4ff84933672fe0d94255d665b3dd7a6791 |
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