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 |
|---|---|---|---|---|---|---|---|---|---|---|
PredictorCNN | import torch
import torch.nn as nn
class PredictorCNN(nn.Module):
def __init__(self, latent_dim=1024, reduced_dim=64):
super(PredictorCNN, self).__init__()
self.latent_dim = latent_dim
self.reduced_dim = reduced_dim
self.conv1 = nn.Conv2d(self.latent_dim, self.reduced_dim, 1, bias... | 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... | SarodYatawatta/federated-pytorch-test | PredictorCNN | false | 8,796 | [
"Apache-2.0"
] | 33 | 42a51ba12a92b32fa19273340d5b61e74e11d8e0 | https://github.com/SarodYatawatta/federated-pytorch-test/tree/42a51ba12a92b32fa19273340d5b61e74e11d8e0 |
AvgPoolPad | # 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
from torchvision.transforms import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cud... | DRACOyu/deep-person-reid | AvgPoolPad | false | 5,199 | [
"MIT"
] | 1 | 8ca8be28c204dbc37cff76e77691f29045773aa2 | https://github.com/DRACOyu/deep-person-reid/tree/8ca8be28c204dbc37cff76e77691f29045773aa2 |
Conv2dSame | # 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
import torch.utils.data.distributed
from torch import nn... | xmyyzy123/zen_nas | Conv2dSame | false | 4,592 | [
"Apache-2.0"
] | 0 | 4870eb0a030856bd67afe8529f65af8dc3bd81dc | https://github.com/xmyyzy123/zen_nas/tree/4870eb0a030856bd67afe8529f65af8dc3bd81dc |
GraphEncoderDecoderAttentionLayer | import torch
import torch.utils.data
import torch
import torch.nn as nn
import torch.nn.functional as F
class GraphEncoderDecoderAttentionLayer(nn.Module):
"""
Graph-to-Graph message passing, adapted from https://arxiv.org/abs/1710.10903
"""
def __init__(self, in_src_features, in_tgt_features, out_fe... | 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.... | Nmegha2601/activitygraph_transformer | GraphEncoderDecoderAttentionLayer | false | 14,132 | [
"MIT"
] | 63 | 4e21a4ea12527df470b7586d149fa4168a41307c | https://github.com/Nmegha2601/activitygraph_transformer/tree/4e21a4ea12527df470b7586d149fa4168a41307c |
ModulatedConv2d | import math
import torch
from torch import nn
from torch.nn import functional as F
def make_kernel(k):
k = torch.tensor(k, dtype=torch.float32)
if k.ndim == 1:
k = k[None, :] * k[:, None]
k /= k.sum()
return k
def upfirdn2d_native(input, kernel, up_x, up_y, down_x, down_y, pad_x0,
pad_x1... | 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
from to... | ishine/GANsNRoses | ModulatedConv2d | false | 15,624 | [
"MIT"
] | 969 | 414e9e77c3df47d4ecf7941b5dcfdffec67403ee | https://github.com/ishine/GANsNRoses/tree/414e9e77c3df47d4ecf7941b5dcfdffec67403ee |
ConvBlock | # 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 ... | ZonePG/Machine-Learning-Collection | ConvBlock | false | 14,735 | [
"MIT"
] | 3,094 | 85f1e761fab85b61d4dbd44285d6483b75ba649c | https://github.com/ZonePG/Machine-Learning-Collection/tree/85f1e761fab85b61d4dbd44285d6483b75ba649c |
SAB | import math
import torch
from torch import Tensor
from torch.nn import Linear
from typing import Type
from typing import Optional
from typing import Tuple
from torch.nn import LayerNorm
class MAB(torch.nn.Module):
def __init__(self, dim_Q: 'int', dim_K: 'int', dim_V: 'int', num_heads:
'int', Conv: 'Optio... | 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.... | ClintvanHoesel/MXMNet_adapted | SAB | false | 344 | [
"MIT"
] | 0 | 091aae4a664b5b0944dfe95dbd2f5da441541437 | https://github.com/ClintvanHoesel/MXMNet_adapted/tree/091aae4a664b5b0944dfe95dbd2f5da441541437 |
MiniBatchStdDev | # 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 torch.nn as nn
import torch.utils.cpp_extension
assert_size_stride = tor... | STomoya/animeface | MiniBatchStdDev | false | 14,368 | [
"MIT"
] | 61 | 37b3cd26097d7874559d4c152e41e5712b7a1a42 | https://github.com/STomoya/animeface/tree/37b3cd26097d7874559d4c152e41e5712b7a1a42 |
Linear | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
def keep_variance_fn(x):
return x + 0.001
class Linear(nn.Module):
def __init__(self, in_features, out_features, bias=True,
keep_variance_fn=None):
super(Linear, self).__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
import torch.nn as nn
from torch.nn.parameter import Parameter
assert_size_strid... | collector-m/LiDAR-MOS | Linear | false | 15,068 | [
"MIT"
] | 268 | 7ccbb63b4ee7c40195b35dd0dddd71473fae25b1 | https://github.com/collector-m/LiDAR-MOS/tree/7ccbb63b4ee7c40195b35dd0dddd71473fae25b1 |
AdaptiveBilinear | # 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.... | LindgeW/BiaffineNER | AdaptiveBilinear | false | 8,459 | [
"Apache-2.0"
] | 13 | 0ae179e9ff731362f6c8ba6d0b24485ad45e8bbf | https://github.com/LindgeW/BiaffineNER/tree/0ae179e9ff731362f6c8ba6d0b24485ad45e8bbf |
Actor | import torch
import torch.nn as nn
import torch.nn.functional as F
class CNN_encoder(nn.Module):
def __init__(self):
super(CNN_encoder, self).__init__()
self.net = nn.Sequential(nn.Conv2d(4, 8, kernel_size=3, padding=1,
stride=1), nn.ReLU(), nn.MaxPool2d(4, 2), nn.Conv2d(8, 8,
... | 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.... | Lttcc/Olympics | Actor | false | 791 | [
"MIT"
] | 0 | 97411244073d127e83e84bf61b1b0a1d6718c31c | https://github.com/Lttcc/Olympics/tree/97411244073d127e83e84bf61b1b0a1d6718c31c |
ConvNet | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim
class ConvNet(nn.Module):
def __init__(self, NumChannels):
super(ConvNet, self).__init__()
self.conv1 = nn.Conv2d(NumChannels, 6, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(6, 16, 5... | 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 ... | FedericoZocco/VarMemLBFGS-PyTorch | ConvNet | false | 5,165 | [
"MIT"
] | 1 | 5a0ed7b95fc71c9a421a07071f8d5199cf6a6216 | https://github.com/FedericoZocco/VarMemLBFGS-PyTorch/tree/5a0ed7b95fc71c9a421a07071f8d5199cf6a6216 |
AdjustNormFunc | # 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_... | akashpalrecha/tanhNorm | AdjustNormFunc | false | 9,664 | [
"Apache-2.0"
] | 0 | bff7ba81aa5c805c423a59a36339254c83a3c28a | https://github.com/akashpalrecha/tanhNorm/tree/bff7ba81aa5c805c423a59a36339254c83a3c28a |
VAE | # 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 import device
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... | Kabongosalomon/examples | VAE | false | 2,453 | [
"BSD-3-Clause"
] | 0 | c4bdf77ca3687c4a43ae3f50f78f63f041f1a0c8 | https://github.com/Kabongosalomon/examples/tree/c4bdf77ca3687c4a43ae3f50f78f63f041f1a0c8 |
DotRNNSelector | from _paritybench_helpers import _mock_config
import torch
import torch as th
from torch.distributions import Categorical
import torch.nn as nn
import torch.nn.functional as F
class DotRNNSelector(nn.Module):
def __init__(self, input_shape, args):
super(DotRNNSelector, self).__init__()
self.args ... | 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 as th
from torch... | NagisaZj/RODE | DotRNNSelector | false | 10,585 | [
"Apache-2.0"
] | 0 | f7f6831fee58a7910e1d7c3a8ae19cef82ab8d03 | https://github.com/NagisaZj/RODE/tree/f7f6831fee58a7910e1d7c3a8ae19cef82ab8d03 |
CARAFE | import torch
import torch.nn as nn
import torch.nn.functional as F
class CARAFE(nn.Module):
def __init__(self, inC, outC, Kencoder=3, delta=2, Kup=5, Cm=64):
super(CARAFE, self).__init__()
self.Kencoder = Kencoder
self.delta = delta
self.Kup = Kup
self.down = nn.Conv2d(in_... | 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.... | cs18chen/fbnn | CARAFE | false | 1,776 | [
"MIT"
] | 0 | 1f52c49f8d1e0e1fa7b5a04677351817c4c0e977 | https://github.com/cs18chen/fbnn/tree/1f52c49f8d1e0e1fa7b5a04677351817c4c0e977 |
Max2d | # 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 as T
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_s... | DouglasOrr/Snippets | Max2d | false | 2,163 | [
"MIT"
] | 0 | 026e15a422b518ee7d9ce4849f971c4403ad9fe8 | https://github.com/DouglasOrr/Snippets/tree/026e15a422b518ee7d9ce4849f971c4403ad9fe8 |
Expand | # 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... | GoalballAnalysis/GUI | Expand | false | 2,304 | [
"MIT"
] | 0 | c7f1cc27f4fd7f861c3ca09f5ca25d1a3f19a8a7 | https://github.com/GoalballAnalysis/GUI/tree/c7f1cc27f4fd7f861c3ca09f5ca25d1a3f19a8a7 |
HorizontalMaxPool2d | # 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... | LT1st/ReID_Alined_beginer | HorizontalMaxPool2d | false | 13,980 | [
"MIT"
] | 370 | 1a12403a32d99900451ac05cd3623a9b770f6d24 | https://github.com/LT1st/ReID_Alined_beginer/tree/1a12403a32d99900451ac05cd3623a9b770f6d24 |
SE | import torch
import torch.nn as nn
import torch.nn.functional as F
class SE(nn.Module):
"""Squeeze-and-Excitation block."""
def __init__(self, in_planes, se_planes):
super(SE, self).__init__()
self.se1 = nn.Conv2d(in_planes, se_planes, kernel_size=1, bias=True)
self.se2 = nn.Conv2d(se... | 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_... | AlexHoffman9/HAET-2021-competition-baseline-code | SE | false | 11,177 | [
"MIT"
] | 0 | 1d71c94c68c9903854eceda6caf07442930caa44 | https://github.com/AlexHoffman9/HAET-2021-competition-baseline-code/tree/1d71c94c68c9903854eceda6caf07442930caa44 |
LinearModel | # 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
import torch.nn
import torch.optim
assert_size_stride = ... | ajsampathk/trt_pose | LinearModel | false | 18,234 | [
"MIT"
] | 7 | 592e038cacaf43b6a502b759a035a4e7cae9db9e | https://github.com/ajsampathk/trt_pose/tree/592e038cacaf43b6a502b759a035a4e7cae9db9e |
FeatExemplarAvgBlock | # 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... | CSer-Tang-hao/FS-KTN | FeatExemplarAvgBlock | false | 7,869 | [
"MIT"
] | 19 | 8e5b1637e0f86f9d29dad7ff740a9c7a4a292a74 | https://github.com/CSer-Tang-hao/FS-KTN/tree/8e5b1637e0f86f9d29dad7ff740a9c7a4a292a74 |
ImageTransformNet | import torch
import torch.nn.functional as F
import torch.nn as nn
class ResidualBlock(nn.Module):
"""Redisual network block for style transfer."""
def __init__(self, nchannels):
"""Create a block of a residual network."""
super(ResidualBlock, self).__init__()
self.conv1 = nn.Conv2d(n... | 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.... | TrueMatthewKirkham/face-preserving-style-transfer | ImageTransformNet | false | 6,032 | [
"MIT"
] | 1 | ae8a9509570227ea52776fba85658022124c886c | https://github.com/TrueMatthewKirkham/face-preserving-style-transfer/tree/ae8a9509570227ea52776fba85658022124c886c |
LowRankEncoderLayer | # 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.... | bahducoup/factorized_training | LowRankEncoderLayer | false | 12,173 | [
"MIT"
] | 0 | 0af38f16338a9bcfcc11091b1a6b75befd67f234 | https://github.com/bahducoup/factorized_training/tree/0af38f16338a9bcfcc11091b1a6b75befd67f234 |
CosineSimilarityLoss | # 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
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn.functional
f... | drivendataorg/DrivenData-2021-Geopose-Solution | CosineSimilarityLoss | false | 6,605 | [
"MIT"
] | 1 | fc1dead0aeb1ade9e9d87b55f56e631c57e966a6 | https://github.com/drivendataorg/DrivenData-2021-Geopose-Solution/tree/fc1dead0aeb1ade9e9d87b55f56e631c57e966a6 |
SelfAttn | # 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.... | caisarl76/alfred | SelfAttn | false | 12,208 | [
"MIT"
] | 0 | b73bdc1651e14c02440938b639fa3c7f3ab3d321 | https://github.com/caisarl76/alfred/tree/b73bdc1651e14c02440938b639fa3c7f3ab3d321 |
Lookahead | import torch
import torch.nn as nn
import torch.nn.functional as F
class Lookahead(nn.Module):
def __init__(self, n_features, context):
super(Lookahead, self).__init__()
assert context > 0
self.context = context
self.n_features = n_features
self.pad = 0, self.context - 1
... | 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... | maxwellzh/CAT | Lookahead | false | 16,051 | [
"Apache-2.0"
] | 237 | b1a9c3f95e84d968593a05bf8b176b5f77b8055e | https://github.com/maxwellzh/CAT/tree/b1a9c3f95e84d968593a05bf8b176b5f77b8055e |
Swish | import torch
import torch.nn as nn
class Swish(nn.Module):
def forward(self, x):
return x.mul_(torch.sigmoid(x))
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
@triton.jit
def triton_poi_fused_mul_sigmoid_0(in_pt... | minhduc0711/labelImg | Swish | false | 12,781 | [
"MIT"
] | 0 | 5030721bb6a59424bfed1d7c09b56e01d08662a1 | https://github.com/minhduc0711/labelImg/tree/5030721bb6a59424bfed1d7c09b56e01d08662a1 |
AuxCNN | # 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 import nn
from tor... | EE559DeepLearningEPFL/Project1 | AuxCNN | false | 399 | [
"MIT"
] | 0 | cbafdfee26771ae0ba3cd36375e68d92e9f108b2 | https://github.com/EE559DeepLearningEPFL/Project1/tree/cbafdfee26771ae0ba3cd36375e68d92e9f108b2 |
Norm | # 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_... | CS-savvy/Transformer-for-Parkinsons-disease | Norm | false | 2,077 | [
"MIT"
] | 0 | 42ef54071092f4aab74c8b9ec82c52e944806a5b | https://github.com/CS-savvy/Transformer-for-Parkinsons-disease/tree/42ef54071092f4aab74c8b9ec82c52e944806a5b |
HyperConv2d | # 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.functional as F
assert_size_stride = torch... | D-hash-code/ffjord-rnode-finalweek-mnist | HyperConv2d | false | 2,149 | [
"MIT"
] | 0 | 4cabcbadda79c68df53ec25f1f8fe03cfeee78f9 | https://github.com/D-hash-code/ffjord-rnode-finalweek-mnist/tree/4cabcbadda79c68df53ec25f1f8fe03cfeee78f9 |
mIoULoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class mIoULoss(nn.Module):
def __init__(self, weight=None, size_average=True, n_classes=4):
super(mIoULoss, self).__init__()
self.classes = n_classes
def forward(self, inputs, target_oneHot):
"""
IoU Loss for ... | 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
import torch.nn as nn
... | ozcell/ENet-SAD_Pytorch | mIoULoss | false | 16,216 | [
"MIT"
] | 53 | aaa79b5e96316e1bf24d3c2147ee622d4f17bc24 | https://github.com/ozcell/ENet-SAD_Pytorch/tree/aaa79b5e96316e1bf24d3c2147ee622d4f17bc24 |
Tanh | # 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 torch.nn as nn
import torch.nn.parallel
assert_size_stride = torch._C._d... | Fanzhongjie/ARFE | Tanh | false | 448 | [
"Apache-2.0"
] | 0 | 4b96b8c5bc0895d3d30acec2a490f81a860fe860 | https://github.com/Fanzhongjie/ARFE/tree/4b96b8c5bc0895d3d30acec2a490f81a860fe860 |
Net1 | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
import torch.utils.data.distributed
class Net1(nn.Module):
def __init__(self):
super(Net1, self).__init__()
self.conv1 = nn.Conv2d(1, 32, 3, 1)
self.conv2 = nn.Conv2d(32, 64, 3, 1)
def forward(... | 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 ... | abhinavs95/deep-learning-containers | Net1 | false | 1,359 | [
"Apache-2.0"
] | 0 | bd1cb70a8cd1cbb5d39bc825fc7ab9f53ebf9f89 | https://github.com/abhinavs95/deep-learning-containers/tree/bd1cb70a8cd1cbb5d39bc825fc7ab9f53ebf9f89 |
ReGLU | import torch
import torch.nn as nn
class PositionWiseFeedForward(nn.Module):
"""
title: Position-wise Feed-Forward Network (FFN)
summary: Documented reusable implementation of the position wise feedforward network.
# Position-wise Feed-Forward Network (FFN)
This is a [PyTorch](https://pytorch.org... | 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_... | edchengmoore/pytorch_tabular | ReGLU | false | 3,448 | [
"MIT"
] | 0 | 25f87089fbed95b46f2a1a8a96fba1f581aa8af1 | https://github.com/edchengmoore/pytorch_tabular/tree/25f87089fbed95b46f2a1a8a96fba1f581aa8af1 |
SEModule | # 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 torchvision import datas... | Alibaba-MIIL/ZS_SDL | SEModule | false | 8,024 | [
"MIT"
] | 20 | 769fe4f57d2d458a7c4b5468a6395c9b296b1dad | https://github.com/Alibaba-MIIL/ZS_SDL/tree/769fe4f57d2d458a7c4b5468a6395c9b296b1dad |
GlobalMaxPool2d | import torch
import torch.nn as nn
class GlobalMaxPool2d(nn.Module):
def forward(self, inputs):
return nn.functional.adaptive_max_pool2d(inputs, 1).view(inputs.
size(0), -1)
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 import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | rlmwang/torch-tools | GlobalMaxPool2d | false | 10,799 | [
"MIT"
] | 0 | 822132534d73414f26045bad38a0a345661b057f | https://github.com/rlmwang/torch-tools/tree/822132534d73414f26045bad38a0a345661b057f |
C51ValueNetwork | # 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 numpy as np
import tor... | HzcIrving/DLRL_PlayGround | C51ValueNetwork | false | 8,286 | [
"MIT"
] | 27 | 0db9a4bdb87130d1d26aea1591ef74cbe6aaa43b | https://github.com/HzcIrving/DLRL_PlayGround/tree/0db9a4bdb87130d1d26aea1591ef74cbe6aaa43b |
ExponentialEnvelope | # 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 math as tl_math
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_str... | chris-price19/ocp | ExponentialEnvelope | false | 1,696 | [
"MIT",
"BSD-3-Clause"
] | 0 | 0175c5a11dd3aaccd4f4780c8cb559401f1ca15e | https://github.com/chris-price19/ocp/tree/0175c5a11dd3aaccd4f4780c8cb559401f1ca15e |
ResBlock | import torch
import torch.nn.functional as F
from functools import partial
import torch.nn as nn
def dispatcher(dispatch_fn):
def decorated(key, *args):
if callable(key):
return key
if key is None:
key = 'none'
return dispatch_fn(key, *args)
return decorated
... | 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.functional as... | derwind/dmfont | ResBlock | false | 15,180 | [
"MIT"
] | 95 | 17a91a9cc1917d2485eaa8e92b68245578920c76 | https://github.com/derwind/dmfont/tree/17a91a9cc1917d2485eaa8e92b68245578920c76 |
RewardCriterion | # 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
from torch.autograd import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | helloMickey/self-critical.pytorch | RewardCriterion | false | 10,178 | [
"MIT"
] | 0 | 3a26111012099e13daeb688136fea45186127935 | https://github.com/helloMickey/self-critical.pytorch/tree/3a26111012099e13daeb688136fea45186127935 |
ScoreCap | # 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
from torch import nn
import torch.nn
import torch.optim
assert_size_stride = torch._C._dy... | mikaylagawarecki/ReAgent | ScoreCap | false | 10,696 | [
"BSD-3-Clause"
] | 0 | b1a306a9d3641c8adeb03ac272e5774a0009fa88 | https://github.com/mikaylagawarecki/ReAgent/tree/b1a306a9d3641c8adeb03ac272e5774a0009fa88 |
GDN | # 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.... | Geunwoo-Jeon/iclr_17_compression | GDN | false | 13,724 | [
"MIT"
] | 56 | a28746b1f1c518d91125d8f289d9511cde488c77 | https://github.com/Geunwoo-Jeon/iclr_17_compression/tree/a28746b1f1c518d91125d8f289d9511cde488c77 |
BertPredictionHeadTransform | from _paritybench_helpers import _mock_config
import math
import torch
from torch import nn
def gelu(x):
"""Implementation of the gelu activation function.
For information: OpenAI GPT"s gelu is slightly different (and gives slightly different results):
0.5 * x * (1 + torch.tanh(math.sqrt(2 / math.... | 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
from to... | Sy-Zhang/recurrent-transformer | BertPredictionHeadTransform | false | 11,136 | [
"MIT"
] | 0 | f66ba49a2c9ec42759d3d00d497b49ffe39e18de | https://github.com/Sy-Zhang/recurrent-transformer/tree/f66ba49a2c9ec42759d3d00d497b49ffe39e18de |
PAM_Module | # 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.... | vis-opt-group/GTANet | PAM_Module | false | 4,494 | [
"MIT"
] | 0 | 269ff4418ee5f0267987e1fa4c69bda13e5cb00d | https://github.com/vis-opt-group/GTANet/tree/269ff4418ee5f0267987e1fa4c69bda13e5cb00d |
NormSoftmaxLoss | # 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.... | kikaitech/classification_metric_learning | NormSoftmaxLoss | false | 15,847 | [
"Apache-2.0"
] | 93 | 6c90cecf8be01eda6efb7f6aa4049d8449ca33f1 | https://github.com/kikaitech/classification_metric_learning/tree/6c90cecf8be01eda6efb7f6aa4049d8449ca33f1 |
Aggregation | # 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 import nn
from torch.nn import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._d... | ezelikman/autonomous-learning-library | Aggregation | false | 6,676 | [
"MIT"
] | 1 | b32d059ca8b191afe0b310102d0754796f391aff | https://github.com/ezelikman/autonomous-learning-library/tree/b32d059ca8b191afe0b310102d0754796f391aff |
LogSumExpPool | import torch
from torch import nn
class LogSumExpPool(nn.Module):
def __init__(self, gamma):
super(LogSumExpPool, self).__init__()
self.gamma = gamma
def forward(self, feat_map):
"""
Numerically stable implementation of the operation
Arguments:
feat_map(Te... | 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... | iampartho/EEE426 | LogSumExpPool | false | 3,647 | [
"Apache-2.0"
] | 0 | a706660c0efcd4adea44d54c57a34bcaa4439ec1 | https://github.com/iampartho/EEE426/tree/a706660c0efcd4adea44d54c57a34bcaa4439ec1 |
SimpleConvNetBlock | # 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_... | cle-ros/RoutingNetworks | SimpleConvNetBlock | false | 15,040 | [
"Apache-2.0"
] | 63 | 0f1fe1221c67a224a02bca6247d3c4488ede0a04 | https://github.com/cle-ros/RoutingNetworks/tree/0f1fe1221c67a224a02bca6247d3c4488ede0a04 |
MLP | # 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... | jjxu217/pytorch-sso | MLP | false | 15,710 | [
"MIT"
] | 121 | 124954a5588120885e2f017c99db7fc540d5b9ab | https://github.com/jjxu217/pytorch-sso/tree/124954a5588120885e2f017c99db7fc540d5b9ab |
SoftDiceLoss_binary | import torch
from torch import nn
import torch.nn.functional as F
class SoftDiceLoss_binary(nn.Module):
def __init__(self):
super(SoftDiceLoss_binary, self).__init__()
def forward(self, input, target):
smooth = 0.01
batch_size = input.size(0)
input = F.sigmoid(input).view(bat... | 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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | Nareshvrao/Understanding-Clouds-from-Satellite-Images | SoftDiceLoss_binary | false | 5,638 | [
"MIT"
] | 1 | 14c5e1f15e803e9638d7a3fa8b9e0d929a6015b6 | https://github.com/Nareshvrao/Understanding-Clouds-from-Satellite-Images/tree/14c5e1f15e803e9638d7a3fa8b9e0d929a6015b6 |
LinearSum | # 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 import nn
assert_s... | AndresPMD/GCN_classification | LinearSum | false | 7,721 | [
"MIT"
] | 39 | b005c4256d68f1f90a7f73e7fdb3d066448de28c | https://github.com/AndresPMD/GCN_classification/tree/b005c4256d68f1f90a7f73e7fdb3d066448de28c |
MNIST_CNN | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
class SqueezeLastTwo(nn.Module):
"""A module which squeezes the last two dimensions, ordinary squeeze can be a problem for batch size 1"""
def __init__(self):
super(SqueezeLastTwo, self).__init__()
def for... | 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.... | AllenPu/DomainBed | MNIST_CNN | false | 2,042 | [
"MIT"
] | 0 | 77519d71471e67f0356134abe0bf01a6dd2fdcfa | https://github.com/AllenPu/DomainBed/tree/77519d71471e67f0356134abe0bf01a6dd2fdcfa |
SimpleSoftmaxModel | import torch
import torch.nn.functional as F
import torch.jit
import torch.onnx
import torch.nn
class SimpleSoftmaxModel(torch.nn.Module):
def __init__(self, dimension):
super(SimpleSoftmaxModel, self).__init__()
self.dimension = dimension
def forward(self, tensor):
return F.softmax(... | 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
import torch.jit
impor... | andreas-hommel/glow | SimpleSoftmaxModel | false | 3,344 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
Siren | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class Sine(nn.Module):
"""
A wrapper for PyTorch sine function.
"""
def __init__(self, w0=1.0):
super().__init__()
self.w0 = w0
@staticmethod
def forward(x):
return torch.sin(x)
class Sir... | 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 math
i... | FinbarArgus/phynn | Siren | false | 2,250 | [
"Apache-2.0"
] | 0 | 436bfd6fa4ad86692bf12b4f76c92bc177626c40 | https://github.com/FinbarArgus/phynn/tree/436bfd6fa4ad86692bf12b4f76c92bc177626c40 |
RewardCriterion | # 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
from torch.autograd import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | Romero027/ImageCaptioning.pytorch | RewardCriterion | false | 2,784 | [
"MIT"
] | 0 | 069c95f5d343fb126afa8b10ec18e472f30b7b35 | https://github.com/Romero027/ImageCaptioning.pytorch/tree/069c95f5d343fb126afa8b10ec18e472f30b7b35 |
LxmertAttentionOutput | # 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 import n... | ashutoshbsathe/SmBop | LxmertAttentionOutput | false | 9,800 | [
"MIT"
] | 0 | ce5f67ec070df55b84d7f3617659011732020c96 | https://github.com/ashutoshbsathe/SmBop/tree/ce5f67ec070df55b84d7f3617659011732020c96 |
SiQU | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | RolnickLab/ocp | SiQU | false | 2,777 | [
"MIT"
] | 0 | e120c3b90203a46f5fc7626f0b5c8979e4944765 | https://github.com/RolnickLab/ocp/tree/e120c3b90203a46f5fc7626f0b5c8979e4944765 |
ApplySingleAttention | # 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.... | zhanwenchen/Scene-Graph-Benchmark.pytorch | ApplySingleAttention | false | 4,660 | [
"MIT"
] | 0 | c86475bcbdaefcc1656a2890194355c2b32aa694 | https://github.com/zhanwenchen/Scene-Graph-Benchmark.pytorch/tree/c86475bcbdaefcc1656a2890194355c2b32aa694 |
DML | import torch
import torch.nn.functional as F
import torch.nn as nn
import torch._utils
from itertools import product as product
import torch.utils.data.distributed
class DML(nn.Module):
"""
Deep Mutual Learning
https://zpascal.net/cvpr2018/Zhang_Deep_Mutual_Learning_CVPR_2018_paper.pdf
"""
def __init__(se... | 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... | Capetian/FaceX-Zoo | DML | false | 4,968 | [
"Apache-2.0"
] | 1 | 029786c40d8aba15d891d33973de25fcd7e5399a | https://github.com/Capetian/FaceX-Zoo/tree/029786c40d8aba15d891d33973de25fcd7e5399a |
ShiftedSoftplus | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.tensorboard
class ShiftedSoftplus(nn.Module):
def __init__(self):
super().__init__()
self.shift = torch.log(torch.tensor(2.0)).item()
def forward(self, x):
return F.softplus(x) - self.shift
def ge... | 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, math as tl_math
import torch.nn as nn
import torch.utils.tensorboard
assert_si... | hengwei-chan/3D_SBDD | ShiftedSoftplus | false | 16,349 | [
"MIT"
] | 67 | eda6d51aaf01ef25581a46920a25161678fab76d | https://github.com/hengwei-chan/3D_SBDD/tree/eda6d51aaf01ef25581a46920a25161678fab76d |
MeanVoxelFeatureExtractor | # 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... | Hub-Tian/CADNet | MeanVoxelFeatureExtractor | false | 17,383 | [
"Apache-2.0"
] | 7 | 37d2be6121bb184d8ded92fa468cb6490a15caea | https://github.com/Hub-Tian/CADNet/tree/37d2be6121bb184d8ded92fa468cb6490a15caea |
AsymmetricLoss | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
class AsymmetricLoss(nn.Module):
def __init__(self, gamma_neg=4, gamma_pos=1, clip=0.05, eps=1e-08,
disable_torch_grad_focal_loss=False):
super(AsymmetricLoss... | 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... | ckvic3/query2labels | AsymmetricLoss | false | 1,723 | [
"MIT"
] | 0 | e9c30e1b445be773be397a093fa66aef71d54556 | https://github.com/ckvic3/query2labels/tree/e9c30e1b445be773be397a093fa66aef71d54556 |
Base | # 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 numpy as np
import tor... | SJTUwbl/mfrl_pytorch | Base | false | 5,801 | [
"MIT"
] | 1 | 2b385121cc9a8aa16ed6d554d1dc10f02f2fc5d9 | https://github.com/SJTUwbl/mfrl_pytorch/tree/2b385121cc9a8aa16ed6d554d1dc10f02f2fc5d9 |
Affine | # 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
import torch.nn.parallel
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty... | Yuki-Tanaka-33937424/pytorch-image-models | Affine | false | 12,027 | [
"Apache-2.0"
] | 0 | 6c1da622dcb2a0421aeb6cdcadd03cc366331f66 | https://github.com/Yuki-Tanaka-33937424/pytorch-image-models/tree/6c1da622dcb2a0421aeb6cdcadd03cc366331f66 |
AODnet | # 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_... | misads/cv_template | AODnet | false | 16,106 | [
"MIT"
] | 69 | 9976ee0ada449a494d26f896c598610f233edc10 | https://github.com/misads/cv_template/tree/9976ee0ada449a494d26f896c598610f233edc10 |
LinearVarianceUnif | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
from torch.nn import Parameter
class ModuleWrapper(nn.Module):
"""Wrapper for nn.Module with support for arbitrary flags and a universal forward pass"""
def __init__(self):
super(ModuleW... | 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
import torch.nn as nn
from torch.nn import Parameter
assert_size_str... | AlliedToasters/elko_den | LinearVarianceUnif | false | 7,675 | [
"Apache-2.0"
] | 38 | 4e69f7f5c0dc7ffad54c7e190a2b75aba2eab7d2 | https://github.com/AlliedToasters/elko_den/tree/4e69f7f5c0dc7ffad54c7e190a2b75aba2eab7d2 |
Noise | import torch
from torch import nn
def exists(val):
return val is not None
class Noise(nn.Module):
def __init__(self):
super().__init__()
self.weight = nn.Parameter(torch.zeros(1))
def forward(self, x, noise=None):
b, _, h, w, device = *x.shape, x.device
if not exists(no... | import torch
from torch import device
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_stride
empty_strided_cuda = torch._C.... | Rexiome/lightweight-gan | Noise | false | 2,747 | [
"MIT"
] | 0 | 4e5c18046fc105129c33995e0bffeb5f14963f4c | https://github.com/Rexiome/lightweight-gan/tree/4e5c18046fc105129c33995e0bffeb5f14963f4c |
CustomMSELoss | import torch
import torch.nn as nn
class CustomMSELoss(nn.Module):
def __init__(self):
super(CustomMSELoss, self).__init__()
def forward(self, x, y):
return torch.mean(torch.pow(torch.log(torch.exp(x) - torch.exp(y)), 2))
def get_inputs():
return [torch.rand([4, 4, 4, 4]), 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 math as tl_math
import torch.nn as nn
... | TAN-OpenLab/TCSE-net | CustomMSELoss | false | 9,537 | [
"Apache-2.0"
] | 0 | fc6ecf704a9c128a9b5b6853cffa8486ee0f54e8 | https://github.com/TAN-OpenLab/TCSE-net/tree/fc6ecf704a9c128a9b5b6853cffa8486ee0f54e8 |
LayerNorm | # 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_... | ishine/tfm-tts | LayerNorm | false | 3,679 | [
"MIT"
] | 0 | a964736467851ddec8f8e8933b9550cbe7d7d7eb | https://github.com/ishine/tfm-tts/tree/a964736467851ddec8f8e8933b9550cbe7d7d7eb |
ycbcr_to_rgb_jpeg | import torch
import numpy as np
import torch.nn as nn
class ycbcr_to_rgb_jpeg(nn.Module):
""" Converts YCbCr image to RGB JPEG
Input:
image(tensor): batch x height x width x 3
Outpput:
result(tensor): batch x 3 x height x width
"""
def __init__(self):
super(ycbcr_to_rgb_jp... | 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 numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | foxtrotmike/DiffJPEG | ycbcr_to_rgb_jpeg | false | 12,394 | [
"MIT"
] | 0 | 7dbc44b1e921f20a213a7206a8578d6a1c8131b4 | https://github.com/foxtrotmike/DiffJPEG/tree/7dbc44b1e921f20a213a7206a8578d6a1c8131b4 |
MultiHeadAttention | # 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.... | NathanYanJing/TransformerReplication | MultiHeadAttention | false | 11,748 | [
"MIT"
] | 0 | b20f987dcc507724971f843c2d214c9c76bd8e34 | https://github.com/NathanYanJing/TransformerReplication/tree/b20f987dcc507724971f843c2d214c9c76bd8e34 |
Highway | # 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... | LinXueyuanStdio/EchoEA | Highway | false | 5,534 | [
"Apache-2.0"
] | 1 | d9b8564023cca71678dec44cf8cab3f91736448a | https://github.com/LinXueyuanStdio/EchoEA/tree/d9b8564023cca71678dec44cf8cab3f91736448a |
decoder4 | # 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.... | czczup/URST | decoder4 | false | 15,109 | [
"Apache-2.0"
] | 119 | 000ec9f7728f12ffad989ec1d07b1dd579514133 | https://github.com/czczup/URST/tree/000ec9f7728f12ffad989ec1d07b1dd579514133 |
GlobalAttentionGeneral | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.onnx
def conv1x1(in_planes, out_planes, bias=False):
"""1x1 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=1,
padding=0, bias=bias)
class GlobalAttentionGeneral(nn.Module):
def __... | 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.... | Thesis-02F/Style-Attn | GlobalAttentionGeneral | false | 1,145 | [
"MIT"
] | 0 | 55f78de4858e395ebf9750a23923fd772600290f | https://github.com/Thesis-02F/Style-Attn/tree/55f78de4858e395ebf9750a23923fd772600290f |
TorchMul | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | Ilyabasharov/torch2trt | TorchMul | false | 2,561 | [
"MIT"
] | 0 | 76bf298b3da408509665e23e2494922b131afb10 | https://github.com/Ilyabasharov/torch2trt/tree/76bf298b3da408509665e23e2494922b131afb10 |
CRNNcell | # 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_... | myyaqubpython/https-github.com-cq615-Deep-MRI-Reconstruction | CRNNcell | false | 16,122 | [
"Apache-2.0"
] | 260 | 4484cff9f1e19ff9874c279c5c5d6cf2a317ddbf | https://github.com/myyaqubpython/https-github.com-cq615-Deep-MRI-Reconstruction/tree/4484cff9f1e19ff9874c279c5c5d6cf2a317ddbf |
rSoftMax | # 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
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | Capetian/FaceX-Zoo | rSoftMax | false | 4,979 | [
"Apache-2.0"
] | 1 | 029786c40d8aba15d891d33973de25fcd7e5399a | https://github.com/Capetian/FaceX-Zoo/tree/029786c40d8aba15d891d33973de25fcd7e5399a |
MinibatchDiscrimination1d | # 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
import torch.... | kayuksel/torchgan | MinibatchDiscrimination1d | false | 10,560 | [
"MIT"
] | 0 | 739d97cef4c49fb80155de84e609471efafab107 | https://github.com/kayuksel/torchgan/tree/739d97cef4c49fb80155de84e609471efafab107 |
AdaptiveCatAvgMaxPool2d | # 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.utils.data
import torchvision.transforms.functional as F
import torch.nn as ... | Exir-lxr/crldr-prune-pytorch | AdaptiveCatAvgMaxPool2d | false | 2,688 | [
"Apache-2.0"
] | 0 | adeb5e0b24ce66ff9531d4d947f72412c1b5c033 | https://github.com/Exir-lxr/crldr-prune-pytorch/tree/adeb5e0b24ce66ff9531d4d947f72412c1b5c033 |
Message_Passing_Unit_v1 | # 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_... | EricssonResearch/scott-eu | Message_Passing_Unit_v1 | false | 8,092 | [
"Apache-2.0"
] | 19 | aad7fd2f767a3c5e7d89223a593fd979ad596db3 | https://github.com/EricssonResearch/scott-eu/tree/aad7fd2f767a3c5e7d89223a593fd979ad596db3 |
FocalLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.cuda
import torch.distributed
import torch.multiprocessing
class FocalLoss(nn.Module):
"""Focal Loss - https://arxiv.org/abs/1708.02002"""
def __init__(self, alpha=0.25, gamma=2):
super().__init__()
self.alpha = a... | 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... | krisk84/retinanet-examples | FocalLoss | false | 12,685 | [
"BSD-3-Clause"
] | 0 | 174d95f3aabe1746d105c66f87aa445607f4eab8 | https://github.com/krisk84/retinanet-examples/tree/174d95f3aabe1746d105c66f87aa445607f4eab8 |
MNACLayer | # 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 collections
import math
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = ... | hoedt/stable-nalu | MNACLayer | false | 3,607 | [
"MIT"
] | 0 | 64b3d240db8bff4da857d955f213ef3c7e38e035 | https://github.com/hoedt/stable-nalu/tree/64b3d240db8bff4da857d955f213ef3c7e38e035 |
FullyConnected | import torch
import torch.nn as nn
class FullyConnected(nn.Module):
def __init__(self, hidden_size, output_size, bias=False):
super(FullyConnected, self).__init__()
self.lrelu = nn.LeakyReLU(0.1)
self.linear_layer = nn.Linear(hidden_size, output_size, bias=bias)
def forward(self, inp... | 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... | Felix2048/SSM-VLN | FullyConnected | false | 8,120 | [
"MIT"
] | 27 | 25b9f98566d6e29d30e09aa8f96257f5935642d6 | https://github.com/Felix2048/SSM-VLN/tree/25b9f98566d6e29d30e09aa8f96257f5935642d6 |
RegressionModel | import torch
import torch.nn as nn
class RegressionModel(nn.Module):
def __init__(self, num_features_in, num_anchors=9, feature_size=256):
super(RegressionModel, self).__init__()
self.conv1 = nn.Conv2d(num_features_in, feature_size, kernel_size=3,
padding=1)
self.act1 = nn.ReL... | 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_... | alexrusciano/nms_free_retinanet | RegressionModel | false | 9,741 | [
"Apache-2.0"
] | 0 | 3461a86e9dea71a756b92a434c62798bbf86b52d | https://github.com/alexrusciano/nms_free_retinanet/tree/3461a86e9dea71a756b92a434c62798bbf86b52d |
NextMinBlock | import torch
import warnings
import torch.nn as nn
import torch.nn.functional as F
from torch import optim as optim
class LayerNorm(nn.Module):
""" LayerNorm that supports two data formats: channels_last (default) or channels_first.
The ordering of the dimensions in the inputs. channels_last corresponds to 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._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | pgruening/ConvNeXt | NextMinBlock | false | 12,895 | [
"MIT"
] | 0 | e9a1beaf312f3a724f0c21d098efbe7db872b049 | https://github.com/pgruening/ConvNeXt/tree/e9a1beaf312f3a724f0c21d098efbe7db872b049 |
OutPutBlock | # 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... | tea321000/SSL4MIS | OutPutBlock | false | 16,538 | [
"MIT"
] | 854 | 8d1b0be08cf089943481a47877b36eb6405fffb2 | https://github.com/tea321000/SSL4MIS/tree/8d1b0be08cf089943481a47877b36eb6405fffb2 |
MultiHeadAttn | # 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.... | EmanuelaBoros/stacked-ner | MultiHeadAttn | false | 17,271 | [
"MIT"
] | 4 | b57e4fcf777a5ad2519ffa7223364e383975bf7d | https://github.com/EmanuelaBoros/stacked-ner/tree/b57e4fcf777a5ad2519ffa7223364e383975bf7d |
MLP_multiple_class | # 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
assert_size_stride = torch._C... | Awannaphasch2016/tgn | MLP_multiple_class | false | 98 | [
"Apache-2.0"
] | 0 | a0eb4b4759cb44e053dfb6a825ccac1d54dba33f | https://github.com/Awannaphasch2016/tgn/tree/a0eb4b4759cb44e053dfb6a825ccac1d54dba33f |
Conv2dSame | import torch
import torch.nn as nn
import torch.nn.functional
class Conv2dSame(torch.nn.Module):
"""2D convolution that pads to keep spatial dimensions equal.
Cannot deal with stride. Only quadratic kernels (=scalar kernel_size).
"""
def __init__(self, in_channels, out_channels, kernel_size, bias=Tru... | 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 torch.... | ChenFengYe/relightable-nr | Conv2dSame | false | 13,465 | [
"MIT"
] | 105 | 239a97406f4df01cf5786dcdde58e464395a682d | https://github.com/ChenFengYe/relightable-nr/tree/239a97406f4df01cf5786dcdde58e464395a682d |
BinResBlock | import torch
import torch.nn as nn
def get_same_padding(kernel_size, dilation):
kernel_size = kernel_size + (kernel_size - 1) * (dilation - 1)
padding = (kernel_size - 1) // 2
return padding
class BinResBlock(nn.Module):
def __init__(self, inplanes, kernel_size=3, dilation=1):
super(BinResB... | 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_... | NeilDG/SGID-PFF | BinResBlock | false | 17,751 | [
"MIT"
] | 8 | e027ac65e63f3c052665290cd0438bb7bdeabf9f | https://github.com/NeilDG/SGID-PFF/tree/e027ac65e63f3c052665290cd0438bb7bdeabf9f |
ScaledLeakyReLU | import math
import torch
from torch import nn
import torch.nn.functional as F
class ScaledLeakyReLU(nn.Module):
def __init__(self, negative_slope=0.2):
super().__init__()
self.negative_slope = negative_slope
def forward(self, input):
out = F.leaky_relu(input, negative_slope=self.nega... | 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | ArashVahabpour/encoder4editing-contrastive | ScaledLeakyReLU | false | 13,269 | [
"MIT"
] | 1,051 | 1b91afe1693e01a41118e1ce2451b7d14bec51f4 | https://github.com/ArashVahabpour/encoder4editing-contrastive/tree/1b91afe1693e01a41118e1ce2451b7d14bec51f4 |
BlurPool2d | # 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
import torch.nn as nn
import ... | Noodles-321/RegistrationEval | BlurPool2d | false | 8,644 | [
"MIT"
] | 38 | 3631d3d5bd65acf980fcfed803fa6125970f3e88 | https://github.com/Noodles-321/RegistrationEval/tree/3631d3d5bd65acf980fcfed803fa6125970f3e88 |
GatedLinearUnit | import torch
import torch.nn as nn
class GatedLinearUnit(nn.Module):
"""**The unit of gating operation that maps the input to the range of 0-1 and multiple original input through the
sigmoid function.**
"""
def __init__(self, input_size, hidden_layer_size, dropout_rate,
activation=None):
... | 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... | OneToolsCollection/4paradigm-AutoX | GatedLinearUnit | false | 9,339 | [
"Apache-2.0"
] | 0 | f8e838021354de17f5bb9bc44e9d68d12dda6427 | https://github.com/OneToolsCollection/4paradigm-AutoX/tree/f8e838021354de17f5bb9bc44e9d68d12dda6427 |
SimpleCeilModule | # 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 torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._... | andreas-hommel/glow | SimpleCeilModule | false | 3,321 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
UpConv | import torch
import torch.nn as nn
class Conv3x3(nn.Module):
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 = nn.ZeroPad2d(1)
self.conv = nn.Conv2d(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._inductor.runtime.triton_helpers import libdevice, math as tl_math
im... | prstrive/EPCDepth | UpConv | false | 16,287 | [
"MIT"
] | 76 | 84119c806741334b652749ee953e3eab60a3718c | https://github.com/prstrive/EPCDepth/tree/84119c806741334b652749ee953e3eab60a3718c |
PositionwiseFeedForward | # 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_... | jetd1/dcp | PositionwiseFeedForward | false | 12,605 | [
"MIT"
] | 0 | 2fe7256a14bf382f1ea0a9e1df6d52ff21a99a4d | https://github.com/jetd1/dcp/tree/2fe7256a14bf382f1ea0a9e1df6d52ff21a99a4d |
LayerNorm | import torch
import torch.fft
import torch.nn
import torch.nn as nn
class LayerNorm(nn.Module):
def __init__(self, num_channels: 'int', eps: 'float'=1e-12):
"""Uses GroupNorm implementation with group=1 for speed."""
super().__init__()
self.layer_norm = torch.nn.GroupNorm(1, num_channels=... | 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.fft
import torch.nn
import torch.nn as nn
assert_size_stride = tor... | dwromero/ckconv | LayerNorm | false | 15,294 | [
"MIT"
] | 74 | d44c6441a98792477d6259368c210089bb33fe7a | https://github.com/dwromero/ckconv/tree/d44c6441a98792477d6259368c210089bb33fe7a |
BarlowTwinsLoss | # 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.triton_helpers import libdevice
import torch.nn as ... | ashutoshml/lightning-tutorials | BarlowTwinsLoss | false | 6,262 | [
"Apache-2.0"
] | 1 | 898b8b6f9852c0b80f034a3187bc1cd34dd521ce | https://github.com/ashutoshml/lightning-tutorials/tree/898b8b6f9852c0b80f034a3187bc1cd34dd521ce |
DiceLoss | # 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.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | KeeratKG/pytorch_connectomics | DiceLoss | false | 702 | [
"MIT"
] | 0 | ba168da6f077ccfbeffcd8936df90ba413895086 | https://github.com/KeeratKG/pytorch_connectomics/tree/ba168da6f077ccfbeffcd8936df90ba413895086 |
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