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 |
|---|---|---|---|---|---|---|---|---|---|---|
StackingNNet | # 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
... | ECNU-ICA/ECNU-SenseMaker | StackingNNet | false | 8,005 | [
"MIT"
] | 16 | 24f829c3dfefccea5fecbbe75904858ec1fefffb | https://github.com/ECNU-ICA/ECNU-SenseMaker/tree/24f829c3dfefccea5fecbbe75904858ec1fefffb |
Sharpen_Block | # 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 math as tl_math
import numpy ... | MingSun-Tse/pytorch-vdsr | Sharpen_Block | false | 5,610 | [
"MIT"
] | 1 | 597bacb4ec7385c8cc6cdf91e26e64ef2e6808b7 | https://github.com/MingSun-Tse/pytorch-vdsr/tree/597bacb4ec7385c8cc6cdf91e26e64ef2e6808b7 |
TorchSub | import torch
class TorchSub(torch.nn.Module):
def __init__(self):
super(TorchSub, self).__init__()
def forward(self, x, y):
return torch.sub(x, y)
def get_inputs():
return [torch.rand([4, 4, 4, 4]), 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | NVIDIA-AI-IOT-private/torch2trt | TorchSub | false | 10,550 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
L1_Charbonnier_loss | # 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.utils.data
from... | YDDDDG/3D2Unet | L1_Charbonnier_loss | false | 6,002 | [
"MIT"
] | 1 | daca056958fb2ae319dc18a350e04b3cefe0d99f | https://github.com/YDDDDG/3D2Unet/tree/daca056958fb2ae319dc18a350e04b3cefe0d99f |
CrossEntropy | import torch
from torch import nn
from torch.nn import functional as F
class CrossEntropy(nn.Module):
def __init__(self, ignore_label=-1, weight=None):
super(CrossEntropy, self).__init__()
self.ignore_label = ignore_label
self.criterion = nn.CrossEntropyLoss(weight=weight, ignore_index=
... | 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... | Gummary/Pytorch-Project-Template | CrossEntropy | false | 497 | [
"MIT"
] | 0 | 56bc5e253627d40fb8771eccdb2bb663c833beb3 | https://github.com/Gummary/Pytorch-Project-Template/tree/56bc5e253627d40fb8771eccdb2bb663c833beb3 |
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.... | UoMfzp/transformer-xl-Chinese-Pytorch | MultiHeadAttn | false | 11,959 | [
"Apache-2.0"
] | 0 | 435641ed138e81f949c5b557b5a13c0a09fb6018 | https://github.com/UoMfzp/transformer-xl-Chinese-Pytorch/tree/435641ed138e81f949c5b557b5a13c0a09fb6018 |
ModelWithDuplicates | # 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.... | Emily0219/distiller | ModelWithDuplicates | false | 5,138 | [
"Apache-2.0"
] | 1 | 445ed35b671fb54586acc280b53d951f18bf97ae | https://github.com/Emily0219/distiller/tree/445ed35b671fb54586acc280b53d951f18bf97ae |
BPRLoss | import torch
import torch.nn as nn
class BPRLoss(nn.Module):
""" BPRLoss, based on Bayesian Personalized Ranking
Args:
- gamma(float): Small value to avoid division by zero
Shape:
- Pos_score: (N)
- Neg_score: (N), same shape as the Pos_score
- Output: scalar.
Exampl... | 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
... | Ahren09/RecBole | BPRLoss | false | 1,912 | [
"MIT"
] | 0 | b3921818dfbc1b81f9eda8d5e9f05bc9d9114089 | https://github.com/Ahren09/RecBole/tree/b3921818dfbc1b81f9eda8d5e9f05bc9d9114089 |
AttwNetHead | import torch
import torch.nn as nn
import torch.distributed
import torch.optim.lr_scheduler
import torch.utils.data
class AttwNetHead(nn.Module):
def __init__(self, idim, hdim, odim):
super().__init__()
self.mlp_attn = nn.Linear(idim, 1, bias=False)
self.mlp_out = nn.Linear(idim, odim, bi... | 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.... | CFM-MSG/SDN | AttwNetHead | false | 189 | [
"MIT"
] | 0 | f309602dc2bb73117355003f3744f8e5450dbccc | https://github.com/CFM-MSG/SDN/tree/f309602dc2bb73117355003f3744f8e5450dbccc |
DQN_RAM | import torch
import torch.nn as nn
import torch.nn.functional as F
class DQN_RAM(nn.Module):
def __init__(self, in_features=4, num_actions=18):
"""
Initialize a deep Q-learning network for testing algorithm
in_features: number of features of input.
num_actions: number of a... | 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_... | transedward/pytoch-dqn | DQN_RAM | false | 16,621 | [
"MIT"
] | 358 | 1ffda6f3724b3bb37c3195b09b651b1682d4d4fd | https://github.com/transedward/pytoch-dqn/tree/1ffda6f3724b3bb37c3195b09b651b1682d4d4fd |
NavigatorBranch | import torch
import torch.nn as nn
def conv1x1(in_channels, out_channels, stride=1, groups=1, bias=False):
"""
Convolution 1x1 layer.
Parameters:
----------
in_channels : int
Number of input channels.
out_channels : int
Number of output channels.
stride : int or tuple/list... | 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_... | iofthetiger/pkuad | NavigatorBranch | false | 6,905 | [
"Apache-2.0"
] | 1 | 07496d108c614c84be028f344830becc9cac8fe5 | https://github.com/iofthetiger/pkuad/tree/07496d108c614c84be028f344830becc9cac8fe5 |
ISub | # 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
@triton.jit
def triton_poi_fused_sub_0(in_ptr0, in_ptr1, out_ptr1, xnumel,... | Ilyabasharov/torch2trt | ISub | false | 2,545 | [
"MIT"
] | 0 | 76bf298b3da408509665e23e2494922b131afb10 | https://github.com/Ilyabasharov/torch2trt/tree/76bf298b3da408509665e23e2494922b131afb10 |
GRUStep | # 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 ... | LucasAPayne/graph4nlp | GRUStep | false | 9,695 | [
"Apache-2.0"
] | 0 | 3b72308f6ed9ce04c535f78b4b21b6ae0a8f5421 | https://github.com/LucasAPayne/graph4nlp/tree/3b72308f6ed9ce04c535f78b4b21b6ae0a8f5421 |
policy1 | # 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 import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | JWongDude/FruitLoops | policy1 | false | 11,527 | [
"MIT"
] | 0 | f4346d9db16ba619d71ce5bb819f5da08a88a120 | https://github.com/JWongDude/FruitLoops/tree/f4346d9db16ba619d71ce5bb819f5da08a88a120 |
BalancedL1Loss | import functools
import torch
import numpy as np
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:
Tenso... | 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 functools
impor... | AtticusJohnson/mmdetection | BalancedL1Loss | false | 11,206 | [
"Apache-2.0"
] | 0 | d8d89bafcce13d3b32b1fb3366be3bb9830546c2 | https://github.com/AtticusJohnson/mmdetection/tree/d8d89bafcce13d3b32b1fb3366be3bb9830546c2 |
RobertaClassificationHead | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.utils.data
import torch.nn
class RobertaClassificationHead(nn.Module):
"""Head for sentence-level classification tasks."""
def __init__(self, config):
super(RobertaClassificationHead, 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
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | HeartForNlp/VL-BERT | RobertaClassificationHead | false | 1,886 | [
"MIT"
] | 0 | c1a590e2597b592629329db126cf8eae74b49cc0 | https://github.com/HeartForNlp/VL-BERT/tree/c1a590e2597b592629329db126cf8eae74b49cc0 |
EnchanceReLU | # 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... | XiaotaoChen/model-quantization | EnchanceReLU | false | 14,605 | [
"BSD-2-Clause"
] | 66 | a745ef691e9329b9c973a2dd795761cd3da8b6ae | https://github.com/XiaotaoChen/model-quantization/tree/a745ef691e9329b9c973a2dd795761cd3da8b6ae |
SharedLinear | import torch
import torch.nn as nn
import torch.nn.functional as F
class SharedLinear(nn.Linear):
def __init__(self, in_features, out_features, share_weight=False):
super(SharedLinear, self).__init__(in_features, out_features, bias=True
)
if share_weight:
self.weight = 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | sdw95927/deconvGAN | SharedLinear | false | 12,954 | [
"MIT"
] | 0 | 49dbbfe4827ed8366242870877165482d4ec1e75 | https://github.com/sdw95927/deconvGAN/tree/49dbbfe4827ed8366242870877165482d4ec1e75 |
SE_Connect | # 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
import torch.... | ishine/asv-subtools | SE_Connect | false | 15,644 | [
"Apache-2.0"
] | 370 | 597dcb29a772b8113dbe7ab64f0d4cc1da298707 | https://github.com/ishine/asv-subtools/tree/597dcb29a772b8113dbe7ab64f0d4cc1da298707 |
AGRUCell | import torch
import torch.nn as nn
import torch.nn.functional as F
from sklearn.metrics import *
class AGRUCell(nn.Module):
""" Attention based GRU (AGRU)
Reference:
- Deep Interest Evolution Network for Click-Through Rate Prediction[J]. arXiv preprint arXiv:1809.03672, 2018.
"""
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.triton_helpers import libdevice
import torch.nn as ... | zzz123xyz/DeepCTR-Torch | AGRUCell | false | 4,748 | [
"Apache-2.0"
] | 0 | d6b880cc6b3761dbef90920a28182ef6737dd665 | https://github.com/zzz123xyz/DeepCTR-Torch/tree/d6b880cc6b3761dbef90920a28182ef6737dd665 |
CircleLoss | # 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, math as tl_math
import torc... | HaochengWan/PVT | CircleLoss | false | 8,225 | [
"MIT"
] | 27 | 95818d303ee63084f044a057344b2049d1fa4492 | https://github.com/HaochengWan/PVT/tree/95818d303ee63084f044a057344b2049d1fa4492 |
BetaIntersection | # 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.... | HKUST-KnowComp/EFO-1-QA-benchmark | BetaIntersection | false | 17,373 | [
"MIT"
] | 9 | 600fb02c76ab631f93ee362ceb789216ec085790 | https://github.com/HKUST-KnowComp/EFO-1-QA-benchmark/tree/600fb02c76ab631f93ee362ceb789216ec085790 |
PatchMerging | import torch
import torch.nn as nn
from math import sqrt
import torch.nn.functional as F
import torch.functional as F
class PatchMerging(nn.Module):
"""Patch Merging Layer.
Args:
input_resolution (tuple[int]): Resolution of input feature.
dim (int): Number of input channels.
norm_laye... | 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 ... | rahulmangalampalli/esvit | PatchMerging | false | 12,918 | [
"MIT"
] | 0 | 5caf6e36b088ae2e7aaa4100b307eec991078e3e | https://github.com/rahulmangalampalli/esvit/tree/5caf6e36b088ae2e7aaa4100b307eec991078e3e |
ConvNet | # 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_... | SJHBXShub/Center_Loss | ConvNet | false | 14,402 | [
"MIT"
] | 813 | 4097709144cf4cfc04d91ac1462ebf346b9f0448 | https://github.com/SJHBXShub/Center_Loss/tree/4097709144cf4cfc04d91ac1462ebf346b9f0448 |
EntMinLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class EntMinLoss(nn.Module):
def __init__(self):
super().__init__()
def forward(self, f_x):
soft_f_x = F.softmax(f_x, dim=-1)
log_soft_f_x = F.log_softmax(f_x, dim=-1)
ent = -torch.sum(soft_f_x * log_soft_f_x)... | 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
... | leoandeol/ldir | EntMinLoss | false | 3,887 | [
"MIT"
] | 0 | f90408c5fb16a52c6c5a76fff1c46b9062343ad5 | https://github.com/leoandeol/ldir/tree/f90408c5fb16a52c6c5a76fff1c46b9062343ad5 |
UNetModule | import torch
import torch.nn as nn
import torch.backends.cudnn
import torch.utils.data
def conv3x3(in_, out):
return nn.Conv2d(in_, out, 3, padding=1)
class Conv3BN(nn.Module):
def __init__(self, in_: 'int', out: 'int', bn=False):
super().__init__()
self.conv = conv3x3(in_, out)
sel... | 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 ... | ArmenGhambaryan/kaggle_carvana_segmentation | UNetModule | false | 13,296 | [
"MIT"
] | 447 | 648a6b5c807cb69011316fe6501241dacc027db2 | https://github.com/ArmenGhambaryan/kaggle_carvana_segmentation/tree/648a6b5c807cb69011316fe6501241dacc027db2 |
OffsetNet | # 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 as nn
as... | HypnosXC/mmaction2 | OffsetNet | false | 13,827 | [
"Apache-2.0"
] | 549 | a26d5f981449445a5e22a0a60d8b285e06c3dd6e | https://github.com/HypnosXC/mmaction2/tree/a26d5f981449445a5e22a0a60d8b285e06c3dd6e |
BinaryExpAbs | # 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 math as tl_math
import abc
import inspect
import warnings
import torch.nn as nn
import to... | Johnsonms/NNI_master | BinaryExpAbs | false | 11,563 | [
"MIT"
] | 0 | e5e5c7aed89cf3189cffe1056464833c15eb54ff | https://github.com/Johnsonms/NNI_master/tree/e5e5c7aed89cf3189cffe1056464833c15eb54ff |
ScaledL2Norm | import torch
import torch.onnx
import torch
import torch.nn as nn
import torch.nn.functional as F
class ScaledL2Norm(nn.Module):
def __init__(self, in_channels, initial_scale):
super(ScaledL2Norm, self).__init__()
self.in_channels = in_channels
self.scale = nn.Parameter(torch.Tensor(in_ch... | 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.onnx
import tor... | mirecta/pytorch-ssd | ScaledL2Norm | false | 12,784 | [
"MIT"
] | 0 | 360f31bfff12f2954c9166dc78df038334a01c53 | https://github.com/mirecta/pytorch-ssd/tree/360f31bfff12f2954c9166dc78df038334a01c53 |
SqueezeAndExcitationModule | # 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
import ... | gheyret/EfficientConformer | SqueezeAndExcitationModule | false | 15,436 | [
"Apache-2.0"
] | 101 | b28a0aaa3b182f72abaccbeb12df0402adf96097 | https://github.com/gheyret/EfficientConformer/tree/b28a0aaa3b182f72abaccbeb12df0402adf96097 |
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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | EdenBD/MultiModalStory-demo | ResidualBlock | false | 13,644 | [
"Apache-2.0"
] | 154 | 5e95e2aca766ca7c850e8db4973b8d51dfdba7f8 | https://github.com/EdenBD/MultiModalStory-demo/tree/5e95e2aca766ca7c850e8db4973b8d51dfdba7f8 |
Classifier | # 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.... | FengMingquan-sjtu/pyHGT | Classifier | false | 9,034 | [
"MIT"
] | 0 | 3ad1b10ee11358c02fa199667a80c291323e5e2d | https://github.com/FengMingquan-sjtu/pyHGT/tree/3ad1b10ee11358c02fa199667a80c291323e5e2d |
Scale | import torch
import torch.nn as nn
class Scale(nn.Module):
def __init__(self, scale=1.0):
super(Scale, self).__init__()
self.scale = nn.Parameter(torch.tensor(scale, dtype=torch.float))
def forward(self, x):
return x * self.scale
def get_inputs():
return [torch.rand([4, 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | Complicateddd/Complicateddd-ROITransformer | Scale | false | 11,308 | [
"Apache-2.0"
] | 0 | 2adfbf98892d569c460d100c6e2169c5fa3a9b82 | https://github.com/Complicateddd/Complicateddd-ROITransformer/tree/2adfbf98892d569c460d100c6e2169c5fa3a9b82 |
Flatten | import torch
from torch import nn
from torch.autograd import *
from itertools import product as product
from math import sqrt as sqrt
class Flatten(nn.Module):
def __init__(self):
super(Flatten, self).__init__()
def forward(self, x):
x = x.transpose(3, 2).contiguous()
return x.view(x... | 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.autograd import *
from itertools import product as product
from math import sqrt as sqrt
assert_size_stride ... | Aristochi/Dangerous_driving_behavior_detection | Flatten | false | 13,268 | [
"MIT"
] | 96 | 596d0544c3ed8cbfbc322cc4cd7859a9ef539810 | https://github.com/Aristochi/Dangerous_driving_behavior_detection/tree/596d0544c3ed8cbfbc322cc4cd7859a9ef539810 |
Attention | # 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.... | HWSelf/pytorch_geometric | Attention | false | 516 | [
"MIT"
] | 0 | c1214de674079b5e39e57c045d0f844b60caf590 | https://github.com/HWSelf/pytorch_geometric/tree/c1214de674079b5e39e57c045d0f844b60caf590 |
DownsampleA | # 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.nn.init
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dy... | OBA9k/Test_dev | DownsampleA | false | 17,754 | [
"Apache-2.0"
] | 4 | bfdd337fb56ca160e1d09b6c310d1e6037d55fcd | https://github.com/OBA9k/Test_dev/tree/bfdd337fb56ca160e1d09b6c310d1e6037d55fcd |
Attention | # 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 math
import ... | Lance0226/CIS700_Convex_Hull_RL | Attention | false | 2,502 | [
"MIT"
] | 0 | 3c87e063209d535d75fde719bf17f20dd5e68635 | https://github.com/Lance0226/CIS700_Convex_Hull_RL/tree/3c87e063209d535d75fde719bf17f20dd5e68635 |
Network | import torch
import torch.nn.functional as F
import torch.nn as nn
import torch.nn.init as I
class Network(nn.Module):
"""
Q-network
"""
def __init__(self, state_size, action_size, seed, fc1_units=64,
fc2_units=32):
"""
Build model and Intialize it
Params
... | 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 ... | tae-yeop/Udacity_DRLND_navigation | Network | false | 10,839 | [
"MIT"
] | 0 | dd4a4609c5fe3e00cb4deea3ebd9922dd0772447 | https://github.com/tae-yeop/Udacity_DRLND_navigation/tree/dd4a4609c5fe3e00cb4deea3ebd9922dd0772447 |
ConvGelu | import torch
import torch.nn as nn
import torch.fx
class ConvGelu(torch.nn.Module):
def __init__(self):
super(ConvGelu, self).__init__()
self.conv = nn.Conv2d(3, 32, 3, 1)
self.gelu = nn.GELU()
def forward(self, x):
x = self.conv(x)
x = self.gelu(x)
return 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.triton_helpers import libdevice
import torch.nn as ... | NVIDIA/Torch-TensorRT | ConvGelu | false | 14,076 | [
"BSD-3-Clause"
] | 430 | 1a22204fecec690bc3c2a318dab4f57b98c57f05 | https://github.com/NVIDIA/Torch-TensorRT/tree/1a22204fecec690bc3c2a318dab4f57b98c57f05 |
CoFusion | import torch
import torch.nn.functional as F
import torch.nn as nn
class CoFusion(nn.Module):
def __init__(self, in_ch, out_ch):
super(CoFusion, self).__init__()
self.conv1 = nn.Conv2d(in_ch, 64, kernel_size=3, stride=1, padding=1)
self.conv2 = nn.Conv2d(64, 64, kernel_size=3, stride=1, p... | 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.... | jechague/DexiNed | CoFusion | false | 15,687 | [
"MIT"
] | 471 | 370fe9031579b2d815ab706d7dc9daf23b969a87 | https://github.com/jechague/DexiNed/tree/370fe9031579b2d815ab706d7dc9daf23b969a87 |
BertLayer | from _paritybench_helpers import _mock_config
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class BertSelfAttention(nn.Module):
def __init__(self, config):
super().__init__()
self.num_attention_heads = config.num_attention_heads
self.attention_head_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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | priyamtejaswin/minbert-assignment | BertLayer | false | 10,693 | [
"Apache-2.0"
] | 0 | fd41a54441916a6d421640bbee910f64786b303d | https://github.com/priyamtejaswin/minbert-assignment/tree/fd41a54441916a6d421640bbee910f64786b303d |
LayerNorm | import torch
import torch.cuda
from torch import nn
import torch.distributed
from torch.nn import LayerNorm
import torch.utils.data
import torch.optim
class LayerNorm(nn.Module):
def __init__(self, channels, eps=0.0001):
super().__init__()
self.channels = channels
self.eps = eps
s... | 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.cuda
from torch import nn
import torch.distributed
import torch.ut... | Oreoluwa1234/NeMo | LayerNorm | false | 9,702 | [
"Apache-2.0"
] | 0 | b01e3ceed34efe31fd43866685dbdd19a6b30928 | https://github.com/Oreoluwa1234/NeMo/tree/b01e3ceed34efe31fd43866685dbdd19a6b30928 |
GELU | # 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.data
import torch.onnx.operators
impor... | YNNEKUW/fairseq | GELU | false | 11,989 | [
"MIT"
] | 0 | ef145b330ef26e7fb76609524504ab7933b88172 | https://github.com/YNNEKUW/fairseq/tree/ef145b330ef26e7fb76609524504ab7933b88172 |
Actor | # 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.... | ikamensh/machin | Actor | false | 6,854 | [
"MIT"
] | 1 | af7b423c47bc1412530cf6c96c11bd3af9b3e239 | https://github.com/ikamensh/machin/tree/af7b423c47bc1412530cf6c96c11bd3af9b3e239 |
HausdorffLoss | # 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 as nn
assert... | LiWentomng/boxlevelset | HausdorffLoss | false | 8,477 | [
"Apache-2.0"
] | 25 | 8cc40bf6ae4a343c482c676c72259cc12c29d31c | https://github.com/LiWentomng/boxlevelset/tree/8cc40bf6ae4a343c482c676c72259cc12c29d31c |
ScaleUp | import torch
import torch.nn as nn
from torch.nn import Parameter
class ScaleUp(nn.Module):
"""ScaleUp"""
def __init__(self, scale):
super(ScaleUp, self).__init__()
self.scale = Parameter(torch.tensor(scale))
def forward(self, x):
return x * self.scale
def get_inputs():
ret... | 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = to... | NTDXYG/DeepPseudo | ScaleUp | false | 17,724 | [
"Apache-2.0"
] | 7 | 0d89045ea145f23259306eb024e9bbe261f33d9b | https://github.com/NTDXYG/DeepPseudo/tree/0d89045ea145f23259306eb024e9bbe261f33d9b |
LSTM | # 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 ... | Flash-Of-Thunder/testing | LSTM | false | 8,159 | [
"Apache-2.0"
] | 18 | 36366e2cd32756fb07abc533ecbb7672a4738bc6 | https://github.com/Flash-Of-Thunder/testing/tree/36366e2cd32756fb07abc533ecbb7672a4738bc6 |
ECA | # 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... | cooked-sashimi/Yet-Another-YOLOv4-Pytorch | ECA | false | 15,087 | [
"MIT"
] | 133 | c884ef8849987a75b0e17eba1b739c22d3782e90 | https://github.com/cooked-sashimi/Yet-Another-YOLOv4-Pytorch/tree/c884ef8849987a75b0e17eba1b739c22d3782e90 |
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... | CNLPT/lightNLP | Biaffine | false | 13,451 | [
"Apache-2.0"
] | 889 | c7f128422ba5b16f514bb294145cb3b562e95829 | https://github.com/CNLPT/lightNLP/tree/c7f128422ba5b16f514bb294145cb3b562e95829 |
Down | # 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 ... | Smith42/unet-pytorch | Down | false | 9,551 | [
"MIT"
] | 0 | 45a0459da69cee7f57fb369a8e2fc58668d81167 | https://github.com/Smith42/unet-pytorch/tree/45a0459da69cee7f57fb369a8e2fc58668d81167 |
NoiseBlock | import torch
import torch.nn as nn
import torch.jit
class NoiseBlock(nn.Module):
def __init__(self, sigma):
super(NoiseBlock, self).__init__()
self.sigma = sigma
def forward(self, x):
out = x + self.sigma * torch.randn_like(x)
return out
def set_sigma(self, x):
s... | 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
import torch.nn as nn
import torch.jit
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
@triton.ji... | shuj1234/Hopfield-ODE | NoiseBlock | false | 10,816 | [
"MIT"
] | 0 | 2b770c0141082174f394b189df725088308d8bdd | https://github.com/shuj1234/Hopfield-ODE/tree/2b770c0141082174f394b189df725088308d8bdd |
CrossEntropy | # 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
... | tgxs002/1-stage-wseg | CrossEntropy | false | 4,474 | [
"Apache-2.0"
] | 0 | de16c51cc6cf8cd0ef248145980434d5f6104910 | https://github.com/tgxs002/1-stage-wseg/tree/de16c51cc6cf8cd0ef248145980434d5f6104910 |
Conv2d | # 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_... | ChrisKonishi/multi-stream-crowd-counting-extended | Conv2d | false | 262 | [
"MIT"
] | 0 | 4b1590499bd93ac09e62c4c7760b88ae92e6b301 | https://github.com/ChrisKonishi/multi-stream-crowd-counting-extended/tree/4b1590499bd93ac09e62c4c7760b88ae92e6b301 |
down_shifted_conv2d | # 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 ... | andiac/pixel-cnn-pp | down_shifted_conv2d | false | 6,207 | [
"MIT"
] | 1 | 3ba856320e40208cbb6e9cac3e66a739f148903e | https://github.com/andiac/pixel-cnn-pp/tree/3ba856320e40208cbb6e9cac3e66a739f148903e |
Conv2dBlock | # 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.functional as... | ricklentz/Seg-Uncertainty | Conv2dBlock | false | 16,322 | [
"MIT"
] | 298 | 82fd7056cccb265b3fc3e8a90338866661cab230 | https://github.com/ricklentz/Seg-Uncertainty/tree/82fd7056cccb265b3fc3e8a90338866661cab230 |
LR_PAD | import torch
import torch.nn as nn
def lr_pad(x, padding=1):
""" Pad left/right-most to each other instead of zero padding """
return torch.cat([x[..., -padding:], x, x[..., :padding]], dim=3)
class LR_PAD(nn.Module):
""" Pad left/right-most to each other instead of zero padding """
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | zokin/HorizonNet | LR_PAD | false | 4,673 | [
"MIT"
] | 0 | a93a76ec7fdc76a5ba023adaed869e34f7f3cea4 | https://github.com/zokin/HorizonNet/tree/a93a76ec7fdc76a5ba023adaed869e34f7f3cea4 |
UnaryPrimitivesPredefined_v2 | import math
import torch
from torch import nn
def apply_last_dim(model, x):
size = list(x.size())
y = model(x.contiguous().view(-1, size[-1]))
size[-1] = y.size(-1)
y = y.view(torch.Size(size))
return y
def get_int_dim_index(name):
if isinstance(name, int):
return name
name_list ... | 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 math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.a... | C-SUNSHINE/TOQ-Nets-PyTorch-Release | UnaryPrimitivesPredefined_v2 | false | 17,169 | [
"MIT"
] | 6 | 05e06bf633fb3c6b610dda9a5126ecd7af1db02f | https://github.com/C-SUNSHINE/TOQ-Nets-PyTorch-Release/tree/05e06bf633fb3c6b610dda9a5126ecd7af1db02f |
FuseUnit | # 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.... | sugi-san/PAMA | FuseUnit | false | 13,005 | [
"MIT"
] | 0 | 95141ebf0d3b61828a0e545f989f96b8ef569f34 | https://github.com/sugi-san/PAMA/tree/95141ebf0d3b61828a0e545f989f96b8ef569f34 |
SACActorNetwork | # 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_... | jacarvalho/mushroom-rl-benchmark | SACActorNetwork | false | 12,542 | [
"MIT"
] | 0 | 5bc2e9b1a12be33827d6edcd5c5ad49571e11275 | https://github.com/jacarvalho/mushroom-rl-benchmark/tree/5bc2e9b1a12be33827d6edcd5c5ad49571e11275 |
Intensity_Loss | # 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
... | ChmarsLuo/Hero_anomaly_prediction | Intensity_Loss | false | 4,986 | [
"Apache-2.0"
] | 1 | dba2322dabb3476466e296db6c316fc08e0cb11d | https://github.com/ChmarsLuo/Hero_anomaly_prediction/tree/dba2322dabb3476466e296db6c316fc08e0cb11d |
ConvertPointsToHomogeneous | import torch
import torch.nn as nn
def convert_points_to_homogeneous(points):
"""Function that converts points from Euclidean to homogeneous space.
See :class:`~torchgeometry.ConvertPointsToHomogeneous` for details.
Examples::
>>> input = torch.rand(2, 4, 3) # BxNx3
>>> output = tgm.co... | 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... | DoJing/frankmocap | ConvertPointsToHomogeneous | false | 11,368 | [
"BSD-3-Clause"
] | 0 | ac2ddc5a75a885ede5068a25049ca2bfe9330576 | https://github.com/DoJing/frankmocap/tree/ac2ddc5a75a885ede5068a25049ca2bfe9330576 |
GRUCell | # 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 ... | Avmb/lm-robustness | GRUCell | false | 115 | [
"BSD-3-Clause"
] | 0 | b5417d9aac01bff0d2a56b506eabed899fd718d4 | https://github.com/Avmb/lm-robustness/tree/b5417d9aac01bff0d2a56b506eabed899fd718d4 |
BertSelfAttention | # 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.... | McGill-NLP/imagecode | BertSelfAttention | false | 5,724 | [
"MIT"
] | 1 | 2c636c6c41d705b4c5861841f29ff689748113d1 | https://github.com/McGill-NLP/imagecode/tree/2c636c6c41d705b4c5861841f29ff689748113d1 |
Embbed2 | import torch
class Embbed2(torch.nn.Module):
def __init__(self, in_features, out_features, weight_multiplier=1.0):
super(Embbed2, self).__init__()
self.b = 2.0 ** torch.linspace(0, weight_multiplier, out_features //
in_features) - 1
self.b = torch.nn.Parameter(torch.reshape(to... | 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 | Embbed2 | false | 16,309 | [
"MIT"
] | 113 | d983dcbbcfec1337c9f2040969213c6d1ea0c39e | https://github.com/qway/nerfmeshes/tree/d983dcbbcfec1337c9f2040969213c6d1ea0c39e |
TransformerEncoderLayer | # 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.... | imperial-qore/CAROL | TransformerEncoderLayer | false | 6,872 | [
"BSD-3-Clause"
] | 1 | 57dc42c4ddeb9e75eed43a91ceb336a1ecc9c8b9 | https://github.com/imperial-qore/CAROL/tree/57dc42c4ddeb9e75eed43a91ceb336a1ecc9c8b9 |
FCBottleNeck | # 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 ... | brown-ivl/beacon | FCBottleNeck | false | 6,374 | [
"MIT"
] | 1 | 66a1714473b362294f787f261561e39c52f00e42 | https://github.com/brown-ivl/beacon/tree/66a1714473b362294f787f261561e39c52f00e42 |
AlphaMish | import torch
class AlphaMish(torch.nn.Module):
def __init__(self, in_features):
super().__init__()
self.alpha = torch.nn.Parameter(torch.zeros((in_features, 1, 1)))
self.alpha.requires_grad = True
def forward(self, x):
return torch.mul(x, torch.tanh(torch.mul(1 + torch.nn.fun... | 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
assert_size_stride = torch._C._dynamo.guards.assert_size_strid... | mattroz/yatopi | AlphaMish | false | 3,991 | [
"MIT"
] | 0 | 278bac6f3d2f13916ae9d43309b9f38b608426bd | https://github.com/mattroz/yatopi/tree/278bac6f3d2f13916ae9d43309b9f38b608426bd |
GlobalAttention | import torch
import torch.nn as nn
def aeq(*args):
"""
Assert all arguments have the same value
"""
arguments = (arg for arg in args)
first = next(arguments)
assert all(arg == first for arg in arguments
), 'Not all arguments have the same value: ' + str(args)
class Bottle(nn.Module):... | 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.... | rajasagashe/coarse2fine | GlobalAttention | false | 16,315 | [
"MIT"
] | 164 | d6c51a3073df9018e32c95c257c68b0d69d9aa46 | https://github.com/rajasagashe/coarse2fine/tree/d6c51a3073df9018e32c95c257c68b0d69d9aa46 |
RMSELoss | # 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.utils.data
asse... | gitter-badger/HEPAutoencoders | RMSELoss | false | 12,429 | [
"Apache-2.0"
] | 0 | 43010cd66fa4335a04b30b87926148e1c8d92de9 | https://github.com/gitter-badger/HEPAutoencoders/tree/43010cd66fa4335a04b30b87926148e1c8d92de9 |
SqueezeBertLayerNorm | import torch
from torch import nn
import torch.utils.checkpoint
class SqueezeBertLayerNorm(nn.LayerNorm):
"""
This is a nn.LayerNorm subclass that accepts NCW data layout and performs normalization in the C dimension.
N = batch C = channels W = sequence length
"""
def __init__(self, hidden_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
from torch import nn
import torch.utils.checkpoint
assert_size_stride = torch._... | Clemens123/transformers | SqueezeBertLayerNorm | false | 11,497 | [
"Apache-2.0"
] | 0 | 22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 | https://github.com/Clemens123/transformers/tree/22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 |
SIREN_CONV | import torch
import numpy as np
import torch.nn as nn
def act(act_fun='LeakyReLU'):
"""
Either string defining an activation function or module (e.g. nn.ReLU)
"""
if isinstance(act_fun, str):
if act_fun == 'LeakyReLU':
return nn.LeakyReLU(0.2, inplace=True)
elif act_fun... | 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 ... | dustlrdk/noise2self | SIREN_CONV | false | 3,454 | [
"MIT"
] | 0 | 46e8c4650f7ec4f664448417fecd39b4cae477f7 | https://github.com/dustlrdk/noise2self/tree/46e8c4650f7ec4f664448417fecd39b4cae477f7 |
ResNetBottleneck | import torch
from torch import nn
import torch.nn.functional as F
class ResNetBottleneck(nn.Module):
def __init__(self, in_channels, out_channels, bottleneck_channels,
stride, downsample=None):
super(ResNetBottleneck, self).__init__()
self.conv1 = nn.Conv2d(in_channels, bottleneck_channel... | 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... | KH-Kyle/rmp_nav | ResNetBottleneck | false | 8,396 | [
"MIT"
] | 30 | d598fe70664a4cdc0e9b9dd4b52e84aa3de1b551 | https://github.com/KH-Kyle/rmp_nav/tree/d598fe70664a4cdc0e9b9dd4b52e84aa3de1b551 |
Truncation2D | # 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... | kpoeppel/pytorch_probgraph | Truncation2D | false | 15,972 | [
"BSD-3-Clause"
] | 47 | b78595ab03bbe92595ad2f6b35f5dd8bf84d6da0 | https://github.com/kpoeppel/pytorch_probgraph/tree/b78595ab03bbe92595ad2f6b35f5dd8bf84d6da0 |
ScaledDotProductAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
class ScaledDotProductAttention(nn.Module):
""" Scaled Dot-Product Attention --baseline version"""
def __init__(self, dropout=0.3):
super().__init__()
self.dropout = nn.Dropout(dropout)
def forward(self, q, k, v, mask=Non... | 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.... | Yottaxx/T-LSTM | ScaledDotProductAttention | false | 18,157 | [
"MIT"
] | 9 | 92618d8c3ee2418b194a2e1592512548da955b77 | https://github.com/Yottaxx/T-LSTM/tree/92618d8c3ee2418b194a2e1592512548da955b77 |
Model_CIFAR10_CNN | import torch
import torch.nn as nn
import torch.nn.functional as F
class Model_CIFAR10_CNN(nn.Module):
def __init__(self):
super(Model_CIFAR10_CNN, self).__init__()
self.conv1 = nn.Conv2d(3, 6, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(6, 16, 5)
self.fc1 = 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.... | Pluriscient/learn-to-learn | Model_CIFAR10_CNN | false | 11,801 | [
"MIT"
] | 0 | 4aa0143522eb90f6439b83ed424d12b434cb344b | https://github.com/Pluriscient/learn-to-learn/tree/4aa0143522eb90f6439b83ed424d12b434cb344b |
FPNHead | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
class FPNHead(nn.Module):
def __init__(self, num_in, num_mid, num_out):
super().__init__()
self.block0 = nn.Conv2d(num_in, num_mid, kernel_size=3, padding=1,
bias=False)
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 import triton_helpers
import torch.nn as nn
import ... | lePossum/DeblurGANv2 | FPNHead | false | 10,489 | [
"BSD-2-Clause"
] | 0 | b02c86de98f98604e2416a3a6121110ede7a2de9 | https://github.com/lePossum/DeblurGANv2/tree/b02c86de98f98604e2416a3a6121110ede7a2de9 |
TAM | # 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
import ... | ZijiaLewisLu/action-recognition-pytorch | TAM | false | 14,739 | [
"Apache-2.0"
] | 149 | 6ee04ed249081eb0d8e1b4a3e7a5c11fa65b8d70 | https://github.com/ZijiaLewisLu/action-recognition-pytorch/tree/6ee04ed249081eb0d8e1b4a3e7a5c11fa65b8d70 |
bodypose_model | # 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
from co... | KamaljeetSahoo/6thSense | bodypose_model | false | 9,367 | [
"Unlicense",
"MIT"
] | 0 | db1f2cd2bb7858410c128a6d11cfbdf8ea69e691 | https://github.com/KamaljeetSahoo/6thSense/tree/db1f2cd2bb7858410c128a6d11cfbdf8ea69e691 |
BinaryExpSquare | import abc
import inspect
import torch
import warnings
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
from typing import Any
from typing import *
def get_module_name(cls_or_func):
module_name = cls_or_func.__module__
if module_name == '__main__':
for frm in i... | 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
import abc
import inspect
import warnings
import torch.nn as nn
import to... | Johnsonms/NNI_master | BinaryExpSquare | false | 11,584 | [
"MIT"
] | 0 | e5e5c7aed89cf3189cffe1056464833c15eb54ff | https://github.com/Johnsonms/NNI_master/tree/e5e5c7aed89cf3189cffe1056464833c15eb54ff |
CRFOutputLayer | import torch
import torch.nn as nn
class CRF(nn.Module):
"""
Implements Conditional Random Fields that can be trained via
backpropagation.
"""
def __init__(self, num_tags):
super(CRF, self).__init__()
self.num_tags = num_tags
self.transitions = nn.Parameter(torch.Tensor(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
import torch.nn as nn
assert_... | oya163/torchnlp | CRFOutputLayer | false | 4,118 | [
"Apache-2.0"
] | 0 | 361caa24d741e47b8bd92af122ae281d6ad72d9d | https://github.com/oya163/torchnlp/tree/361caa24d741e47b8bd92af122ae281d6ad72d9d |
baseRNN_predict | # 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... | lysuk96/rl_representations | baseRNN_predict | false | 15,981 | [
"MIT"
] | 438 | 19de69305e40c9b3a1d746a7af26d232c9fb3f6f | https://github.com/lysuk96/rl_representations/tree/19de69305e40c9b3a1d746a7af26d232c9fb3f6f |
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_... | CraigWang1/EfficientDet-PyTorch | RegressionModel | false | 13,539 | [
"Apache-2.0"
] | 66 | 531d3c83338f03aa5c6f0615839c0ea5c03025f6 | https://github.com/CraigWang1/EfficientDet-PyTorch/tree/531d3c83338f03aa5c6f0615839c0ea5c03025f6 |
PosNACLayer | # 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 collections
import torch.utils.data
assert_size_stride = torch._C._dynamo... | wlm2019/Neural-Arithmetic-Units | PosNACLayer | false | 16,718 | [
"MIT"
] | 147 | f9de9d004bb2dc2ee28577cd1760d0a00c185836 | https://github.com/wlm2019/Neural-Arithmetic-Units/tree/f9de9d004bb2dc2ee28577cd1760d0a00c185836 |
Net1 | import torch
def square(x):
return x * x
class Net1(torch.nn.Module):
def __init__(self, hidden=64, output=10):
super().__init__()
self.conv1 = torch.nn.Conv2d(1, 4, kernel_size=7, padding=0, stride=3)
self.fc1 = torch.nn.Linear(256, hidden)
self.fc2 = torch.nn.Linear(hidden... | 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cu... | yxtj/henn | Net1 | false | 11,058 | [
"MIT"
] | 0 | 5093f3e637ba0bb3e48c4f890b3b469c3617f2c5 | https://github.com/yxtj/henn/tree/5093f3e637ba0bb3e48c4f890b3b469c3617f2c5 |
Conv2d_spatial_sep | import torch
import torch.nn as nn
class Conv2d_spatial_sep(nn.Module):
def __init__(self, nin, nout):
super(Conv2d_spatial_sep, self).__init__()
self.conv1 = nn.Conv2d(nin, 1, kernel_size=(1, 3), groups=1, padding=0)
self.conv2 = nn.Conv2d(1, nout, kernel_size=(3, 1), groups=1, padding=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... | maet3608/torchy | Conv2d_spatial_sep | false | 3,969 | [
"Apache-2.0"
] | 0 | 8c73732a1d4631bd97bfafdc18e52a22ff5410f7 | https://github.com/maet3608/torchy/tree/8c73732a1d4631bd97bfafdc18e52a22ff5410f7 |
FullyConnected2 | import torch
import torch.nn as nn
class FullyConnected2(nn.Module):
def __init__(self, hidden_size, output_size):
super(FullyConnected2, self).__init__()
self.lrelu = nn.LeakyReLU(0.1)
self.linear_layer = nn.Linear(hidden_size, hidden_size, bias=True)
self.linear_layer_1 = nn.Lin... | 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 | FullyConnected2 | false | 8,111 | [
"MIT"
] | 27 | 25b9f98566d6e29d30e09aa8f96257f5935642d6 | https://github.com/Felix2048/SSM-VLN/tree/25b9f98566d6e29d30e09aa8f96257f5935642d6 |
OutPutBlock | import torch
import torch.nn as nn
import torch.nn.functional
class OutPutBlock(nn.Module):
def __init__(self, in_channels, out_channels):
super(OutPutBlock, self).__init__()
self.in_chns = in_channels
self.out_chns = out_channels
self.conv1 = nn.Conv2d(self.in_chns, self.in_chns ... | 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
assert_size_stride = torch._C._... | Luoxd1996/awesome-semi-supervised-learning-for-medical-image-segmentation | OutPutBlock | false | 17,709 | [
"MIT"
] | 6 | 34d78f41e4fa5927b03cb9f9b2fd473cd16f5e57 | https://github.com/Luoxd1996/awesome-semi-supervised-learning-for-medical-image-segmentation/tree/34d78f41e4fa5927b03cb9f9b2fd473cd16f5e57 |
CausalConv1d | import torch
import torch.nn as nn
class CausalConv1d(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size=2, dilation=2):
super().__init__()
self.padding = dilation
self.causal_conv = nn.Conv1d(in_channels, out_channels, kernel_size,
padding=self.padding, dil... | 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... | Hao-Kailong/DisFeb | CausalConv1d | false | 518 | [
"MIT"
] | 0 | 2877edd587556e127d6648ee211ed22838c8d015 | https://github.com/Hao-Kailong/DisFeb/tree/2877edd587556e127d6648ee211ed22838c8d015 |
MultiHeadedAttention | # 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.... | dojoteef/synst | MultiHeadedAttention | false | 15,199 | [
"BSD-3-Clause"
] | 81 | a1842682cf757e8a501cd9cee16f20e1a14158f1 | https://github.com/dojoteef/synst/tree/a1842682cf757e8a501cd9cee16f20e1a14158f1 |
BasicBlock | # 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
import t... | ZephyrII/competitive_colaboration | BasicBlock | false | 14,719 | [
"MIT"
] | 357 | a557d1e23ef2c0b8e3794f085a79bfffb860f9df | https://github.com/ZephyrII/competitive_colaboration/tree/a557d1e23ef2c0b8e3794f085a79bfffb860f9df |
Attention | import torch
import torch.nn.functional as F
import torch.nn as nn
class Attention(nn.Module):
"""
Computing the attention over the words
"""
def __init__(self, input_dim, proj_dim):
super(Attention, self).__init__()
self.input_dim = input_dim
self.proj_dim = proj_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 import triton_helpers
from torch._inductor.runtime.... | Sein-Jang/R2A | Attention | false | 5,816 | [
"MIT"
] | 1 | f70b69cedb4de3dd60a36963c4b6a881d9d090ee | https://github.com/Sein-Jang/R2A/tree/f70b69cedb4de3dd60a36963c4b6a881d9d090ee |
NRelu | # 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 torch.nn as nn
import torch.optim
import torch.backends.cu... | minhtannguyen/pytorch_shake_shake | NRelu | false | 12,785 | [
"MIT"
] | 0 | d7f245d8d8b9e81a6020aadb438ffeae6d5593c2 | https://github.com/minhtannguyen/pytorch_shake_shake/tree/d7f245d8d8b9e81a6020aadb438ffeae6d5593c2 |
TransitionUp | # 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
import torch.utils.data
assert_size_stride = torch._C._dyna... | ELEKTRONN/elektronn3 | TransitionUp | false | 13,641 | [
"MIT"
] | 124 | 19c751855dffc67b744cd43e757aa4a5bd577d9b | https://github.com/ELEKTRONN/elektronn3/tree/19c751855dffc67b744cd43e757aa4a5bd577d9b |
PDCBlock_converted | # 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_... | mgpadalkar/pidinet | PDCBlock_converted | false | 16,038 | [
"MIT"
] | 137 | 781924fe30469cdc64f63ce6666a3e1f5b4e576f | https://github.com/mgpadalkar/pidinet/tree/781924fe30469cdc64f63ce6666a3e1f5b4e576f |
GeLU | # 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
from torch.nn import Module
import functools
import torch.utils.data
import tor... | JiahuaWU/fastai | GeLU | false | 13,873 | [
"Apache-2.0"
] | 59 | 13a2df812d875abf0558004283392ab40d9bdea1 | https://github.com/JiahuaWU/fastai/tree/13a2df812d875abf0558004283392ab40d9bdea1 |
SeparableConvBlock | import math
import torch
import torch.utils.data
import torch.nn.functional as F
from itertools import product as product
from math import sqrt as sqrt
class Conv2dSamePadding(torch.nn.Conv2d):
"""
A wrapper around :class:`torch.nn.Conv2d` to support "SAME" padding mode and more features.
"""
def __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
import math
import torch.utils.data
import torch.nn.functional as F
from itertoo... | lingtengqiu/LearnableTreeFilterV2 | SeparableConvBlock | false | 7,098 | [
"Apache-2.0"
] | 1 | 3814a5a84c0a5c33d6538749eaf5aed4827366de | https://github.com/lingtengqiu/LearnableTreeFilterV2/tree/3814a5a84c0a5c33d6538749eaf5aed4827366de |
FourierEmbedding | import torch
from torch import nn
class FourierEmbedding(nn.Module):
def __init__(self, features, height, width, **kwargs):
super().__init__(**kwargs)
self.projector = nn.Linear(2, features)
self._height = height
self._width = width
def forward(self, y, x):
x_norm = 2... | 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
from torch im... | LS4GAN/uvcgan | FourierEmbedding | false | 8,419 | [
"BSD-2-Clause"
] | 20 | 376439ae2a9be684ff279ddf634fe137aadc5df5 | https://github.com/LS4GAN/uvcgan/tree/376439ae2a9be684ff279ddf634fe137aadc5df5 |
ScaledDotProductAttention | # 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.... | KalleBylin/tft_webapp | ScaledDotProductAttention | false | 9,227 | [
"Apache-2.0"
] | 0 | 008f109e77f8bada417655dab482f340adb8cb6b | https://github.com/KalleBylin/tft_webapp/tree/008f109e77f8bada417655dab482f340adb8cb6b |
LearnedPositionalEmbeddings | from torch.nn import Module
import torch
from torch import nn
import torch.utils.data
import torch.nn.functional
import torch.autograd
class LearnedPositionalEmbeddings(Module):
"""
<a id="LearnedPositionalEmbeddings"></a>
## Add parameterized positional encodings
This adds learned positional embedd... | 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.nn import Module
from torch import nn
import torch.utils.data
import torch.nn.functional
import torch.autograd
assert_size_stride... | mcx/annotated_deep_learning_paper_implementations | LearnedPositionalEmbeddings | false | 7,203 | [
"MIT"
] | 1 | f169f3a71dd2d36eb28ad31062d3475efa367b88 | https://github.com/mcx/annotated_deep_learning_paper_implementations/tree/f169f3a71dd2d36eb28ad31062d3475efa367b88 |
Model | # 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.nn import Module
import torch.nn.functional
from torch.nn.parameter import Parameter
from torch.nn.modules import Module
import t... | Jovonni/jukebox | Model | false | 1,908 | [
"MIT"
] | 0 | 965a6f78aae67506a6e4fcdb205e2c39132e12e0 | https://github.com/Jovonni/jukebox/tree/965a6f78aae67506a6e4fcdb205e2c39132e12e0 |
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