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 |
|---|---|---|---|---|---|---|---|---|---|---|
EqualLinear | import torch
from torch import nn
import torch.nn.functional as F
class EqualLinear(nn.Module):
def __init__(self, in_dim, out_dim, lr_mul=1, bias=True):
super().__init__()
self.weight = nn.Parameter(torch.randn(out_dim, in_dim))
if bias:
self.bias = nn.Parameter(torch.zeros(o... | 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... | TheSignPainter/AGGAN | EqualLinear | false | 1,133 | [
"Apache-2.0"
] | 0 | d75144f81df3f5a0a761d48c6285c38e74002be3 | https://github.com/TheSignPainter/AGGAN/tree/d75144f81df3f5a0a761d48c6285c38e74002be3 |
AsymmetricLoss | # 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... | davidaderup/query2labels | AsymmetricLoss | false | 15,123 | [
"MIT"
] | 164 | 5a10c861dda85d94ba01ec6ad4119eef67a9f441 | https://github.com/davidaderup/query2labels/tree/5a10c861dda85d94ba01ec6ad4119eef67a9f441 |
PixelNorm | import torch
from torch import nn
class PixelNorm(nn.Module):
def __init__(self):
super().__init__()
def forward(self, input):
return input * torch.rsqrt(torch.mean(input ** 2, dim=1, keepdim=
True) + 1e-08)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Liamkuo/SAIR | PixelNorm | false | 17,574 | [
"MIT"
] | 6 | 0fb289cd975b5a196b58e7d16bac00e31fd41d39 | https://github.com/Liamkuo/SAIR/tree/0fb289cd975b5a196b58e7d16bac00e31fd41d39 |
ECB | import torch
import torch.nn as nn
import torch.nn.functional as F
class SeqConv3x3(nn.Module):
def __init__(self, seq_type, inp_planes, out_planes, depth_multiplier):
super(SeqConv3x3, self).__init__()
self.type = seq_type
self.inp_planes = inp_planes
self.out_planes = out_planes... | 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... | thinkreed/ECBSR | ECB | false | 16,624 | [
"Apache-2.0"
] | 162 | 152b9fef9b9fb61b6e5a93677229143652ef305d | https://github.com/thinkreed/ECBSR/tree/152b9fef9b9fb61b6e5a93677229143652ef305d |
Gaussian | # 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.triton_helpers import libd... | pclucas14/GMVAE | Gaussian | false | 12,870 | [
"MIT"
] | 0 | cdabcd636b70a47adf8c06e9dde4f34c46b68a5d | https://github.com/pclucas14/GMVAE/tree/cdabcd636b70a47adf8c06e9dde4f34c46b68a5d |
RgbaToRgb | # 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... | NickleDave/kornia | RgbaToRgb | false | 2,685 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 5392651d0bc268da577fa0a49aa50f957289c7dd | https://github.com/NickleDave/kornia/tree/5392651d0bc268da577fa0a49aa50f957289c7dd |
_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
import torch.nn as nn
import torch.nn.init
assert_size_stride = torch._C._dynamo... | simonmeister/pytorch-mono-depth | _TransitionUp | false | 16,449 | [
"MIT"
] | 56 | 713c70e2fdae6d9d6e0322febadfedcaee9470d3 | https://github.com/simonmeister/pytorch-mono-depth/tree/713c70e2fdae6d9d6e0322febadfedcaee9470d3 |
ConcatSquashLinear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | D-hash-code/ffjord | ConcatSquashLinear | false | 11,359 | [
"MIT"
] | 0 | 3647ab35537a8bac3b4dc1e45a593819ac8e2c18 | https://github.com/D-hash-code/ffjord/tree/3647ab35537a8bac3b4dc1e45a593819ac8e2c18 |
LinearARD | # 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.... | x-zho14/pytorch_ard | LinearARD | false | 10,991 | [
"MIT"
] | 0 | 5a9b790f33bf0340b2b3a2108c45d97786a2be86 | https://github.com/x-zho14/pytorch_ard/tree/5a9b790f33bf0340b2b3a2108c45d97786a2be86 |
LRN | import torch
import torch.optim
import torch.nn as nn
class LRN(nn.Module):
def __init__(self, local_size=1, alpha=1.0, beta=0.75, ACROSS_CHANNELS=True
):
super(LRN, self).__init__()
self.ACROSS_CHANNELS = ACROSS_CHANNELS
if ACROSS_CHANNELS:
self.average = nn.AvgPool3d... | 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.optim
import torch.nn as nn
assert_size_stride = torch._C._dynamo.... | Fyy10/UESTC-Thesis-DA | LRN | false | 473 | [
"MIT"
] | 0 | 6cb16efd1f80aa569c90874a806a62dec8afaec4 | https://github.com/Fyy10/UESTC-Thesis-DA/tree/6cb16efd1f80aa569c90874a806a62dec8afaec4 |
WeightedBCELoss | # 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.functi... | HelenGuohx/cv-ferattn-code | WeightedBCELoss | false | 5,283 | [
"MIT"
] | 1 | faa9b7850fe2a0f8c08193bb129b5fec4639d616 | https://github.com/HelenGuohx/cv-ferattn-code/tree/faa9b7850fe2a0f8c08193bb129b5fec4639d616 |
PreNet | # 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... | airobotnews/cloneVoice | PreNet | false | 14,764 | [
"MIT"
] | 15,983 | 8ad9ba2b60aef57d6d7c83832f07c4f1173d493b | https://github.com/airobotnews/cloneVoice/tree/8ad9ba2b60aef57d6d7c83832f07c4f1173d493b |
h_tanh | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
class h_tanh(nn.Module):
def __init__(self, inplace=True, h_max=1):
super(h_tanh, self).__init__()
self.relu = nn.ReLU6(inplace=inplace)
self.h_max = ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data... | SpectrePrediction/micronet | h_tanh | false | 2,845 | [
"MIT"
] | 0 | f56269c7a8744f750e9870f0baa9fb6e68f27b9c | https://github.com/SpectrePrediction/micronet/tree/f56269c7a8744f750e9870f0baa9fb6e68f27b9c |
GlobalWeightedAvgPool2d | import torch
import torch.nn as nn
import torch.nn.functional
import torch.nn.parallel
import torch.utils.data
import torch.optim
import torch.utils.data.distributed
def import_flatten_impl():
global flatten_impl, unflatten_impl, imported_flatten_impl
try:
flatten_impl = apex_C.flatten
unflatt... | 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.... | dong03/dfdc_deepfake_challenge | GlobalWeightedAvgPool2d | false | 1,865 | [
"MIT"
] | 0 | bee310d0e4f1f6c9bd8ec7c0c97a98b52667673d | https://github.com/dong03/dfdc_deepfake_challenge/tree/bee310d0e4f1f6c9bd8ec7c0c97a98b52667673d |
HSwish | # 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.utils.data
assert_size_stride = torch._C._dynamo.guards... | shiyuann/determined | HSwish | false | 16,421 | [
"Apache-2.0"
] | 1,729 | 856123ae112759de7bded9bc7bd0e07055f2174b | https://github.com/shiyuann/determined/tree/856123ae112759de7bded9bc7bd0e07055f2174b |
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.... | ChangQingAAS/Deep-Reinforcement-Learning | Actor | false | 249 | [
"MIT"
] | 0 | 3bc1381c632b1730a48e63e972aea62086c4287c | https://github.com/ChangQingAAS/Deep-Reinforcement-Learning/tree/3bc1381c632b1730a48e63e972aea62086c4287c |
BBoxTransform | # 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | MikoyChinese/Learn | BBoxTransform | false | 852 | [
"Apache-2.0"
] | 0 | c482b1e84496279935b5bb2cfc1e6d78e2868c63 | https://github.com/MikoyChinese/Learn/tree/c482b1e84496279935b5bb2cfc1e6d78e2868c63 |
DepthConv2d | import torch
import torch.nn as nn
class DepthConv2d(nn.Module):
def __init__(self, input_channel, hidden_channel, kernel, padding,
dilation=1):
super(DepthConv2d, self).__init__()
self.conv2d = nn.Conv2d(input_channel, hidden_channel, 1)
self.padding = padding
self.dconv2... | 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.... | c-ma13/sepTFNet | DepthConv2d | false | 6,384 | [
"MIT"
] | 1 | a06c89c080f9449ac2e5090f80d9645deea7f23a | https://github.com/c-ma13/sepTFNet/tree/a06c89c080f9449ac2e5090f80d9645deea7f23a |
Block | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | huazai-1994/24th-resolution-for-STAC-Overflow | Block | false | 6,848 | [
"Apache-2.0"
] | 1 | 80bb3b367a126264823ffc597dc01586c262f9d9 | https://github.com/huazai-1994/24th-resolution-for-STAC-Overflow/tree/80bb3b367a126264823ffc597dc01586c262f9d9 |
LinearEnsemble | import torch
import torch as T
import torch.nn as nn
class LinearEnsemble(nn.Module):
__constants__ = ['in_features', 'out_features']
ensemble_size: 'int'
in_features: 'int'
out_features: 'int'
weight: 'T.Tensor'
def __init__(self, ensemble_size: 'int', in_features: 'int',
out_feature... | 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 as T
import torch.nn as nn
assert_size_stride = torch._C._dynamo.gu... | RamiSketcher/AMMI-RL | LinearEnsemble | false | 975 | [
"MIT"
] | 0 | 6d51587ff4d5dc14cba87fca561bd7b340b44586 | https://github.com/RamiSketcher/AMMI-RL/tree/6d51587ff4d5dc14cba87fca561bd7b340b44586 |
ARFB | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.model_zoo
assert_size_stride = torch._C... | NawaNae/ESRT-Huawei | ARFB | false | 2,668 | [
"MIT"
] | 0 | edea1c0bafec940dc7ea8e5110c355a83188665c | https://github.com/NawaNae/ESRT-Huawei/tree/edea1c0bafec940dc7ea8e5110c355a83188665c |
HyperpriorSynthesisDLMM | import torch
import torch.nn as nn
import torch.nn.functional as F
def get_num_DLMM_channels(C, K=4, params=['mu', 'scale', 'mix']):
"""
C: Channels of latent representation (L3C uses 5).
K: Number of mixture coefficients.
"""
return C * K * len(params)
class HyperpriorSynthesisDLMM(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
import torch.nn as nn
import ... | sedrickkeh/high-fidelity-dual-image | HyperpriorSynthesisDLMM | false | 16,417 | [
"Apache-2.0"
] | 266 | 9cefd378467826b91596653df38666e469bb23e0 | https://github.com/sedrickkeh/high-fidelity-dual-image/tree/9cefd378467826b91596653df38666e469bb23e0 |
CosineLinear | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Parameter
class CosineLinear(nn.Module):
def __init__(self, in_features, out_features):
super(CosineLinear, self).__init__()
self.in_features = in_features
self.out_features = out_features
self... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | QingquanBao/Spear-Shield | CosineLinear | false | 983 | [
"Apache-2.0"
] | 0 | d57b8f4412c3d651b6f7e056c9c45cfd0dc950c3 | https://github.com/QingquanBao/Spear-Shield/tree/d57b8f4412c3d651b6f7e056c9c45cfd0dc950c3 |
Position_wise_Feed_Forward | # 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.... | NTDXYG/Text-Classify-based-pytorch | Position_wise_Feed_Forward | false | 8,577 | [
"Apache-2.0"
] | 20 | b12a264a0ea64b2f8b46fafd5383ef0a8025ef2f | https://github.com/NTDXYG/Text-Classify-based-pytorch/tree/b12a264a0ea64b2f8b46fafd5383ef0a8025ef2f |
DCGANGenerator_mnist | import functools
import torch
import torch.utils.data
import torch
import torch.nn as nn
class DCGANGenerator_mnist(nn.Module):
def __init__(self, z_dim, ngf=64, output_nc=1, norm_layer=nn.BatchNorm2d):
super(DCGANGenerator_mnist, self).__init__()
self.z_dim = z_dim
self.ngf = ngf
... | 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 functools
im... | Gabriele91/EvolutionaryGAN-pytorch | DCGANGenerator_mnist | false | 9,135 | [
"MIT"
] | 0 | 993cb13551908727e52aef738f8954072b5b398a | https://github.com/Gabriele91/EvolutionaryGAN-pytorch/tree/993cb13551908727e52aef738f8954072b5b398a |
PKTCosSim | import torch
import torch.nn as nn
import torch._utils
from itertools import product as product
import torch.utils.data.distributed
class PKTCosSim(nn.Module):
"""
Learning Deep Representations with Probabilistic Knowledge Transfer
http://openaccess.thecvf.com/content_ECCV_2018/papers/Nikolaos_Passalis_Learning... | 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... | Capetian/FaceX-Zoo | PKTCosSim | false | 4,977 | [
"Apache-2.0"
] | 1 | 029786c40d8aba15d891d33973de25fcd7e5399a | https://github.com/Capetian/FaceX-Zoo/tree/029786c40d8aba15d891d33973de25fcd7e5399a |
AddFunction | # 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.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
assert_size_st... | ShounoLab/res-net-interpretation-open | AddFunction | false | 1,069 | [
"MIT"
] | 0 | 282dc0ae261467ee1866996416149959db216c02 | https://github.com/ShounoLab/res-net-interpretation-open/tree/282dc0ae261467ee1866996416149959db216c02 |
ChannelAttentionBlock | # 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.... | cnuzh/CSNet | ChannelAttentionBlock | false | 6,466 | [
"MIT"
] | 1 | a6c3163624f55dc294ec2e5a6de020d77bd4ff91 | https://github.com/cnuzh/CSNet/tree/a6c3163624f55dc294ec2e5a6de020d77bd4ff91 |
ConvSwishInplace | # 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.cuda
import torch.backends.cudnn
import torch.... | Observer007/intel-extension-for-pytorch | ConvSwishInplace | false | 5,662 | [
"Apache-2.0"
] | 1 | f8ab25c305c89d5aaf06190a4fec0727aeb4dcd7 | https://github.com/Observer007/intel-extension-for-pytorch/tree/f8ab25c305c89d5aaf06190a4fec0727aeb4dcd7 |
CrossEntropyLoss | # 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
from torch.nn import f... | Atten4Vis/DemystifyLocalViT | CrossEntropyLoss | false | 13,344 | [
"MIT"
] | 64 | 2e2327caec6d56ae2c8aa861b32bb62f3cdb786e | https://github.com/Atten4Vis/DemystifyLocalViT/tree/2e2327caec6d56ae2c8aa861b32bb62f3cdb786e |
SoftDiceLoss | import torch
import numpy as np
from torch import nn
import torch.nn.functional
def sum_tensor(inp, axes, keepdim=False):
axes = np.unique(axes).astype(int)
if keepdim:
for ax in axes:
inp = inp.sum(int(ax), keepdim=True)
else:
for ax in sorted(axes, reverse=True):
... | 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 numpy as np
from torch import nn
import torch.nn.functional
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_str... | Ramsha04/kits19_cnn | SoftDiceLoss | false | 8,708 | [
"Apache-2.0"
] | 15 | 0c1c861ca1a211a840a77e52895548e8d8033470 | https://github.com/Ramsha04/kits19_cnn/tree/0c1c861ca1a211a840a77e52895548e8d8033470 |
AUGRUCell | import torch
import torch.nn as nn
import torch.nn.functional as F
from sklearn.metrics import *
class AUGRUCell(nn.Module):
""" Effect of GRU with attentional update gate (AUGRU)
Reference:
- Deep Interest Evolution Network for Click-Through Rate Prediction[J]. arXiv preprint arXiv:1809.03672, ... | 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 | AUGRUCell | false | 4,742 | [
"Apache-2.0"
] | 0 | d6b880cc6b3761dbef90920a28182ef6737dd665 | https://github.com/zzz123xyz/DeepCTR-Torch/tree/d6b880cc6b3761dbef90920a28182ef6737dd665 |
Decoder | import torch
import torch.utils.data
import torch.nn as nn
import torch.nn.functional as F
class Decoder(nn.Module):
""" VAE decoder """
def __init__(self, img_channels, latent_size):
super(Decoder, self).__init__()
self.latent_size = latent_size
self.img_channels = img_channels
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
impor... | susanwe/world-models | Decoder | false | 10,867 | [
"MIT"
] | 0 | 0f246a430683e6ab741726df0a97f35830044356 | https://github.com/susanwe/world-models/tree/0f246a430683e6ab741726df0a97f35830044356 |
FFNet | import torch
import torch.nn as nn
import torch.nn.functional as F
class FFNet(nn.Module):
"""Modified ResidualNetworkSegment model class"""
def __init__(self, block, num_blocks, width, depth):
super(FFNet, self).__init__()
assert (depth - 4
) % 4 == 0, 'Depth not compatible with ... | 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_... | Maosef/easy-to-hard | FFNet | false | 8,525 | [
"MIT"
] | 44 | 711ec0965229444a6c51b1b06a4e2cad3e32d02e | https://github.com/Maosef/easy-to-hard/tree/711ec0965229444a6c51b1b06a4e2cad3e32d02e |
EcaModule | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.utils.data
import torch.nn as nn
import torch.nn.parall... | dumpmemory/NonDeepNetworks | EcaModule | false | 15,250 | [
"BSD-3-Clause"
] | 307 | 5513bf588f4e64c99583440507232675c2e21e34 | https://github.com/dumpmemory/NonDeepNetworks/tree/5513bf588f4e64c99583440507232675c2e21e34 |
StyleBlock | # 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 ... | techthiyanes/annotated_deep_learning_paper_implementations | StyleBlock | false | 16,576 | [
"MIT"
] | 3,714 | 8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 | https://github.com/techthiyanes/annotated_deep_learning_paper_implementations/tree/8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 |
SAM | import torch
import torch.nn as nn
def conv(in_channels, out_channels, kernel_size, bias=False, stride=1):
return nn.Conv2d(in_channels, out_channels, kernel_size, padding=
kernel_size // 2, bias=bias, stride=stride)
class SAM(nn.Module):
def __init__(self, n_feat, kernel_size=3, bias=True):
... | 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... | HolyWu/vs-hinet | SAM | false | 17,384 | [
"MIT"
] | 4 | b1083ab169d082696d4bf40281922ee52c762714 | https://github.com/HolyWu/vs-hinet/tree/b1083ab169d082696d4bf40281922ee52c762714 |
OutputTransition | import torch
from torch import nn
class OutputTransition(nn.Module):
def __init__(self, inChans, n_labels):
super(OutputTransition, self).__init__()
self.final_conv = nn.Conv3d(inChans, n_labels, kernel_size=1)
self.sigmoid = nn.Sigmoid()
def forward(self, x):
out = self.sigm... | 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... | JXQI/ModelsGenesis | OutputTransition | false | 2,394 | [
"MIT"
] | 0 | f961288313a78f03bd3045ac27722f791f365bd8 | https://github.com/JXQI/ModelsGenesis/tree/f961288313a78f03bd3045ac27722f791f365bd8 |
CriticArchitecture | # 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
from abc i... | bootml/agent | CriticArchitecture | false | 1,577 | [
"Apache-2.0"
] | 0 | 84235db931d6e4ef956962961c619994898ebdd5 | https://github.com/bootml/agent/tree/84235db931d6e4ef956962961c619994898ebdd5 |
NST | # 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
import... | Capetian/FaceX-Zoo | NST | false | 4,970 | [
"Apache-2.0"
] | 1 | 029786c40d8aba15d891d33973de25fcd7e5399a | https://github.com/Capetian/FaceX-Zoo/tree/029786c40d8aba15d891d33973de25fcd7e5399a |
DenseConv2dLayer_5C | import torch
import torch.nn as nn
from torch.nn import Parameter
def l2normalize(v, eps=1e-12):
return v / (v.norm() + eps)
class LayerNorm(nn.Module):
def __init__(self, num_features, eps=1e-08, affine=True):
super(LayerNorm, self).__init__()
self.num_features = num_features
self.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.nn import Parameter
assert_size_stride = torch.... | LenKerr/Semantic-Colorization-GAN | DenseConv2dLayer_5C | false | 5,526 | [
"MIT"
] | 1 | 2ce52406ca6fc92e69692b451b1c9ae66ba3b76f | https://github.com/LenKerr/Semantic-Colorization-GAN/tree/2ce52406ca6fc92e69692b451b1c9ae66ba3b76f |
SkipLastTargetChannelWrapper | import torch
from torch import nn as nn
from torch.nn import MSELoss
class SkipLastTargetChannelWrapper(nn.Module):
"""
Loss wrapper which removes additional target channel
"""
def __init__(self, loss, squeeze_channel=False):
super(SkipLastTargetChannelWrapper, self).__init__()
self.l... | 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 as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._emp... | ciubecca/3dunet-cavity | SkipLastTargetChannelWrapper | false | 1,719 | [
"MIT"
] | 0 | cfcc827773b18a95d221ab86c1afc5e2f7c30ecb | https://github.com/ciubecca/3dunet-cavity/tree/cfcc827773b18a95d221ab86c1afc5e2f7c30ecb |
ActionAttentionV2 | # 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.... | footoredo/pymarl | ActionAttentionV2 | false | 3,512 | [
"Apache-2.0"
] | 0 | 9c62dda7a7ed984e020f2cafab93601342305af2 | https://github.com/footoredo/pymarl/tree/9c62dda7a7ed984e020f2cafab93601342305af2 |
autoencoder | import torch
import torch.nn.functional as F
class autoencoder(torch.nn.Module):
def __init__(self, inputDim):
"""
In the constructor we instantiate two nn.Linear modules and assign them as
member variables.
"""
h_size = 128
c_size = 8
use_bias = True
... | 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... | charlesmackin/tiny | autoencoder | false | 1,676 | [
"Apache-2.0"
] | 0 | bf8afc5cfc15e12efdd3bca0d559adfdfc435981 | https://github.com/charlesmackin/tiny/tree/bf8afc5cfc15e12efdd3bca0d559adfdfc435981 |
AttentionSelf | import torch
class AttentionSelf(torch.nn.Module):
def __init__(self, input_size, hidden_size, device=torch.device('cpu')):
"""
implementation of self-attention.
"""
super().__init__()
self.ff1 = torch.nn.Linear(input_size, hidden_size)
self.ff2 = torch.nn.Linear(h... | 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.... | haophancs/TREQS | AttentionSelf | false | 15,493 | [
"MIT"
] | 149 | 49e354ce2a08cf963ec139d99936020e0f80ced8 | https://github.com/haophancs/TREQS/tree/49e354ce2a08cf963ec139d99936020e0f80ced8 |
TransposeGatedConv2d | import torch
import torch.nn as nn
from torch.nn import functional as F
from torch.nn import Parameter
def l2normalize(v, eps=1e-12):
return v / (v.norm() + eps)
class LayerNorm(nn.Module):
def __init__(self, num_features, eps=1e-08, affine=True):
super(LayerNorm, self).__init__()
self.num_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | autocomic/deepfillv2 | TransposeGatedConv2d | false | 12,147 | [
"MIT"
] | 0 | 4b0f565accbf20ee90093a4504b1cff0099d9cb9 | https://github.com/autocomic/deepfillv2/tree/4b0f565accbf20ee90093a4504b1cff0099d9cb9 |
distLinear | import torch
import torch.nn as nn
import torch.utils.data
from torch.nn.utils.weight_norm import WeightNorm
import torch.nn.parallel
import torch.optim
class distLinear(nn.Module):
def __init__(self, indim, outdim):
super(distLinear, self).__init__()
self.L = nn.Linear(indim, outdim, bias=False)... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | MuawizChaudhary/STARTUP | distLinear | false | 873 | [
"MIT"
] | 0 | 03f39b34a4ec232f132173b4a1e67ea04165e52b | https://github.com/MuawizChaudhary/STARTUP/tree/03f39b34a4ec232f132173b4a1e67ea04165e52b |
TransposeConv2dLayer | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Parameter
def l2normalize(v, eps=1e-12):
return v / (v.norm() + eps)
class LayerNorm(nn.Module):
def __init__(self, num_features, eps=1e-08, affine=True):
super(LayerNorm, self).__init__()
self.num_featu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | Sheroa/Video_Colorization | TransposeConv2dLayer | false | 2,855 | [
"MIT"
] | 0 | 5c772ac0ec944814cd8be0a94b0746116b11ac01 | https://github.com/Sheroa/Video_Colorization/tree/5c772ac0ec944814cd8be0a94b0746116b11ac01 |
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.... | Roestlab/massformer | MultiHeadAttention | false | 17,859 | [
"BSD-2-Clause"
] | 6 | c6324970c392f8ee96651679f49d21e430caa0c9 | https://github.com/Roestlab/massformer/tree/c6324970c392f8ee96651679f49d21e430caa0c9 |
FocalLoss | # 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | jokingbear/DM | FocalLoss | false | 6,977 | [
"MIT"
] | 1 | 9c4dada1756f3d866455a397511d4f3bacfadc60 | https://github.com/jokingbear/DM/tree/9c4dada1756f3d866455a397511d4f3bacfadc60 |
Decoder | import torch
import torch.nn.functional as F
from torch import nn
class Decoder(torch.nn.Module):
def __init__(self, Z_dim, h_dim, X_dim):
super(Decoder, self).__init__()
self.hidden1 = torch.nn.Linear(Z_dim, int(h_dim / 4))
self.hidden2 = torch.nn.Linear(int(h_dim / 4), int(h_dim / 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 libdevice
assert_size_stride ... | onimaru/Generative_models | Decoder | false | 12,858 | [
"Apache-2.0"
] | 0 | 915750066996aa3d4dce6ae605778b4eee3f0f3d | https://github.com/onimaru/Generative_models/tree/915750066996aa3d4dce6ae605778b4eee3f0f3d |
SIREN_CONV | # 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 numpy ... | dustlrdk/noise2self | SIREN_CONV | false | 3,454 | [
"MIT"
] | 0 | 46e8c4650f7ec4f664448417fecd39b4cae477f7 | https://github.com/dustlrdk/noise2self/tree/46e8c4650f7ec4f664448417fecd39b4cae477f7 |
PermEqui2_mean | # 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... | dvirsamuel/CrowdDet | PermEqui2_mean | false | 1,869 | [
"MIT"
] | 0 | db729bf71c0ca72229e5d446019769e095fdaa79 | https://github.com/dvirsamuel/CrowdDet/tree/db729bf71c0ca72229e5d446019769e095fdaa79 |
CosNorm_Classifier | import math
import torch
import torch.optim
import torch.utils.data
import torch.nn as nn
from torch.nn.parameter import Parameter
class CosNorm_Classifier(nn.Module):
def __init__(self, in_dims, out_dims, scale=16, margin=0.5, init_std=0.001
):
super(CosNorm_Classifier, 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 math
import ... | caisarl76/BalancedMetaSoftmax-Classification | CosNorm_Classifier | false | 3,260 | [
"BSD-3-Clause"
] | 0 | 48b9c8af19de261d95a5ef38f5780cbadf7bb64b | https://github.com/caisarl76/BalancedMetaSoftmax-Classification/tree/48b9c8af19de261d95a5ef38f5780cbadf7bb64b |
Pow | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | PogChamper/torch2trt | Pow | false | 14,235 | [
"MIT"
] | 3,363 | 43b12627ec0de4d212efb6d02b07570205085ccc | https://github.com/PogChamper/torch2trt/tree/43b12627ec0de4d212efb6d02b07570205085ccc |
ActorNetwork | import torch
import torch.nn as nn
import torch.nn.functional as F
class ActorNetwork(nn.Module):
def __init__(self, input_shape, output_shape, **kwargs):
super(ActorNetwork, self).__init__()
n_input = input_shape[-1]
n_output = output_shape[0]
self._h = nn.Linear(n_input, n_outpu... | 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_... | AmmarFahmy/mushroom-rl | ActorNetwork | false | 4,860 | [
"MIT"
] | 1 | 2625ee7f64d5613b3b9fba00f0b7a39fece88ca5 | https://github.com/AmmarFahmy/mushroom-rl/tree/2625ee7f64d5613b3b9fba00f0b7a39fece88ca5 |
_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.... | amadejkocbek/darts | _ScaledDotProductAttention | false | 12,106 | [
"Apache-2.0"
] | 0 | 074be2a76eee11258da066878c564badf40834e9 | https://github.com/amadejkocbek/darts/tree/074be2a76eee11258da066878c564badf40834e9 |
SimpleCumSumModule | # 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.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | opti-mix/glow | SimpleCumSumModule | false | 7,400 | [
"Apache-2.0"
] | 1 | 4ba074df5da9822986a23a6679ab592c22660f6d | https://github.com/opti-mix/glow/tree/4ba074df5da9822986a23a6679ab592c22660f6d |
FocalLoss | # 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
... | Juggernaut93/InsightFace-v2 | FocalLoss | false | 679 | [
"Apache-2.0"
] | 0 | 65e9b8d1f285a87472ffb913bec136d4e046798f | https://github.com/Juggernaut93/InsightFace-v2/tree/65e9b8d1f285a87472ffb913bec136d4e046798f |
LipschitzCube | # 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... | zxydi1992/residual-flows | LipschitzCube | false | 13,192 | [
"MIT"
] | 0 | 4ec289681dc91cff5312b22f7ebed93838b440fb | https://github.com/zxydi1992/residual-flows/tree/4ec289681dc91cff5312b22f7ebed93838b440fb |
OfstMapL1Loss | # 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | ezxzeng/FFB6D | OfstMapL1Loss | false | 15,336 | [
"MIT"
] | 145 | fd0ea6471532ab1dc68f9a58b52d9a63f8fb76f2 | https://github.com/ezxzeng/FFB6D/tree/fd0ea6471532ab1dc68f9a58b52d9a63f8fb76f2 |
EdgeGateFree | # 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
from torch.nn import Parameter
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = to... | AnchoretY/botnet-detection | EdgeGateFree | false | 11,188 | [
"MIT"
] | 0 | e2066ff314f1ea2ccbf4c10ddff819f344a2b715 | https://github.com/AnchoretY/botnet-detection/tree/e2066ff314f1ea2ccbf4c10ddff819f344a2b715 |
LandmarkLoss | import math
import torch
from torch import nn
def wing_loss(y_true, y_pred, N_LANDMARK, w=10.0, epsilon=2.0):
y_pred = y_pred.reshape(-1, N_LANDMARK, 2)
y_true = y_true.reshape(-1, N_LANDMARK, 2)
x = y_true - y_pred
c = w * (1.0 - math.log(1.0 + w / epsilon))
absolute_x = torch.abs(x)
losses =... | 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 math
from torch import nn
assert_size_stride = torch._C._dynamo.gu... | AnthonyF333/FaceLandmark_PFLD_UltraLight | LandmarkLoss | false | 7,719 | [
"Apache-2.0"
] | 38 | c7c9543bd7f44ab434240eab077242f259df21f8 | https://github.com/AnthonyF333/FaceLandmark_PFLD_UltraLight/tree/c7c9543bd7f44ab434240eab077242f259df21f8 |
MixPad2d | import torch
from torch import nn
class MixPad2d(nn.Module):
"""Mixed padding modes for H and W dimensions
Args:
padding (tuple): the size of the padding for x and y, ie (pad_x, pad_y)
modes (tuple): the padding modes for x and y, the values of each can be
``'constant'``, ``'refle... | 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... | hhj1897/face_parsing | MixPad2d | false | 15,515 | [
"MIT"
] | 70 | 9cd26b6916f562a2ab356b6b22e9ad93e19f2051 | https://github.com/hhj1897/face_parsing/tree/9cd26b6916f562a2ab356b6b22e9ad93e19f2051 |
ConcatClassifierHead | # 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.nn import Module
i... | SpyrosMouselinos/DeltaFormers | ConcatClassifierHead | false | 5,857 | [
"Apache-2.0"
] | 1 | 38508fa9b85f2c50aa0031b67e7e8feff1a75b27 | https://github.com/SpyrosMouselinos/DeltaFormers/tree/38508fa9b85f2c50aa0031b67e7e8feff1a75b27 |
GatedTransition | # 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.... | autodidact-m/Projects | GatedTransition | false | 3,144 | [
"Apache-2.0"
] | 0 | f4c0473adba42f3a629b62eb09d3b1df91982f46 | https://github.com/autodidact-m/Projects/tree/f4c0473adba42f3a629b62eb09d3b1df91982f46 |
Net5 | import torch
from torch import nn
from torch.nn.init import kaiming_normal
from torch.nn.init import normal
def weights_init(m):
if isinstance(m, (nn.Conv1d, nn.Linear)):
kaiming_normal(m.weight.data)
try:
kaiming_normal(m.bias.data)
except ValueError:
normal(m.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
from torch._inductor.runtime import triton_helpers
from torch import nn
from tor... | moritzschaefer/pavooc | Net5 | false | 7,282 | [
"MIT"
] | 1 | 735f5455f9a95a5734436a24e2aa92cf600c91af | https://github.com/moritzschaefer/pavooc/tree/735f5455f9a95a5734436a24e2aa92cf600c91af |
Net | import torch
import torch.nn as tnn
class Net(tnn.Module):
def __init__(self):
super(Net, self).__init__()
self.conv1 = tnn.Conv2d(3, 6, 5)
self.pool = tnn.MaxPool2d(2, 2)
self.conv2 = tnn.Conv2d(6, 16, 5)
self.fc1 = tnn.Linear(16 * 5 * 5, 120)
self.fc2 = tnn.Linea... | 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 tnn
assert... | AbbasMZ/jittor | Net | false | 36 | [
"Apache-2.0"
] | 0 | fcec57f70422b52d6b8d0235e29f91fd2212f559 | https://github.com/AbbasMZ/jittor/tree/fcec57f70422b52d6b8d0235e29f91fd2212f559 |
MSELoss | # 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
import torch.nn.parallel
import torch.optim
import torch.utils.data... | akshayka/gavel | MSELoss | false | 14,772 | [
"MIT"
] | 67 | 40a22a725f2e70478483e98c9b07c6fc588e0c40 | https://github.com/akshayka/gavel/tree/40a22a725f2e70478483e98c9b07c6fc588e0c40 |
ANNClassifier | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.init as init
class AttentionConv(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, stride=1,
padding=0, groups=1, bias=False):
super(AttentionConv, self).__init__()
self.out_channels = ... | 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.... | Sam-limyr/End-to-end-ASR-Pytorch | ANNClassifier | false | 1,035 | [
"MIT"
] | 0 | 623a50792f48218228549ea17b8ea5e8bb1b342f | https://github.com/Sam-limyr/End-to-end-ASR-Pytorch/tree/623a50792f48218228549ea17b8ea5e8bb1b342f |
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... | HolyLow/examples | VAE | false | 11,514 | [
"BSD-3-Clause"
] | 0 | 23b0cb1022cf7a21428883e95fded01d74a059bf | https://github.com/HolyLow/examples/tree/23b0cb1022cf7a21428883e95fded01d74a059bf |
Unfold | # 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.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_... | XrosLiang/GraphCL | Unfold | false | 5,998 | [
"MIT"
] | 1 | fdf9fabcdaddbc17e5c8b7ac9e9d2bdfe4acc56c | https://github.com/XrosLiang/GraphCL/tree/fdf9fabcdaddbc17e5c8b7ac9e9d2bdfe4acc56c |
MultiheadAttention | import math
import torch
import torch as th
import torch.nn as nn
class QKVMultiheadAttention(nn.Module):
def __init__(self, n_heads: 'int', n_ctx: 'int'):
super().__init__()
self.n_heads = n_heads
self.n_ctx = n_ctx
def forward(self, qkv):
bs, n_ctx, width = qkv.shape
... | 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.... | dashstander/glide-text2im | MultiheadAttention | false | 1,806 | [
"MIT"
] | 0 | 58f03a871ee0567e27fccc40df98203e675a9b8e | https://github.com/dashstander/glide-text2im/tree/58f03a871ee0567e27fccc40df98203e675a9b8e |
DeiTEmbeddings | # 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
from torch import nn
import torch.utils.checkpoint
import col... | jxhe/unify-parameter-efficient-tuning | DeiTEmbeddings | false | 15,762 | [
"Apache-2.0"
] | 101 | 3222ce2c0079566a28043e22380eb4ab6ad14389 | https://github.com/jxhe/unify-parameter-efficient-tuning/tree/3222ce2c0079566a28043e22380eb4ab6ad14389 |
GroupPointWise | # 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... | nachiket273/VisTrans | GroupPointWise | false | 7,309 | [
"MIT"
] | 1 | 99129b02f275424ebff900189ec2055f26bb9912 | https://github.com/nachiket273/VisTrans/tree/99129b02f275424ebff900189ec2055f26bb9912 |
Adjust_naive | # 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_... | AndersonYong/URetinex-Net-Retinex-based-Deep-Unfolding-Network-for-Low-light-Image-Enhancem | Adjust_naive | false | 10,313 | [
"MIT"
] | 0 | 9d837b8df9c761defb1eca390b3a60aa4a6fbb1a | https://github.com/AndersonYong/URetinex-Net-Retinex-based-Deep-Unfolding-Network-for-Low-light-Image-Enhancem/tree/9d837b8df9c761defb1eca390b3a60aa4a6fbb1a |
FSM | import torch
from torch import Tensor
from torch import nn
from torch.nn import functional as F
class FSM(nn.Module):
def __init__(self, c1, c2):
super().__init__()
self.conv_atten = nn.Conv2d(c1, c1, 1, bias=False)
self.conv = nn.Conv2d(c1, c2, 1, bias=False)
def forward(self, x: 'T... | 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... | Genevievekim/segformer | FSM | false | 17,324 | [
"MIT"
] | 10 | 4a0800746ade51101ec2573c683b06eccadb9683 | https://github.com/Genevievekim/segformer/tree/4a0800746ade51101ec2573c683b06eccadb9683 |
Block | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | q5628077/Transformer-in-RL | Block | false | 4,206 | [
"MIT"
] | 0 | 14679656779a372d91d9fbd89bd802b5ff34c200 | https://github.com/q5628077/Transformer-in-RL/tree/14679656779a372d91d9fbd89bd802b5ff34c200 |
Delta | # 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
from torchaudio import transforms
assert_size_stride = tor... | AyushExel/s3prl | Delta | false | 2,029 | [
"MIT"
] | 0 | 6531904e9621a778978b9cfef3ba9f582e56639a | https://github.com/AyushExel/s3prl/tree/6531904e9621a778978b9cfef3ba9f582e56639a |
SimpleXorModule | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleXorModule(torch.nn.Module):
def __init__(self):
super(SimpleXorModule, self).__init__()
def forward(self, a, b):
c = torch.logical_xor(a, b)
return torch.logical_xor(c, c)
def get_inputs():
return [torc... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | briancoutinho/glow | SimpleXorModule | false | 12,587 | [
"Apache-2.0"
] | 0 | 4c919d60b3c33296c4109aec8020a1733c98f5b5 | https://github.com/briancoutinho/glow/tree/4c919d60b3c33296c4109aec8020a1733c98f5b5 |
expandEncoder | from torch.autograd import Function
import math
import torch
import torch.nn as nn
import torch.utils.data
class LowerBound(Function):
@staticmethod
def forward(ctx, inputs, bound):
b = torch.ones_like(inputs) * bound
ctx.save_for_backward(inputs, b)
return torch.max(inputs, b)
@... | 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 | expandEncoder | false | 13,861 | [
"MIT"
] | 56 | a28746b1f1c518d91125d8f289d9511cde488c77 | https://github.com/Geunwoo-Jeon/iclr_17_compression/tree/a28746b1f1c518d91125d8f289d9511cde488c77 |
Dense_net_transition | import torch
import torch.nn as nn
import torch.nn.functional as F
class Dense_net_transition(nn.Module):
def __init__(self, nChannels, outChannels):
super(Dense_net_transition, self).__init__()
self.conv = nn.Conv2d(nChannels, outChannels, kernel_size=1, bias=False
)
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
assert_... | aditya140/NoveltyDetectionResearch | Dense_net_transition | false | 6,072 | [
"MIT"
] | 1 | f9b27e6e8d9c23f85d4d91241ee5d050ecd6b6ef | https://github.com/aditya140/NoveltyDetectionResearch/tree/f9b27e6e8d9c23f85d4d91241ee5d050ecd6b6ef |
Temp | import torch
import torch.nn as nn
import torch.nn.functional as F
class Temp(nn.Module):
def __init__(self, input_dim, output_dim):
super(Temp, self).__init__()
self.linear1 = nn.Linear(input_dim, 256)
self.linear2 = nn.Linear(256, 256)
self.linear3 = nn.Linear(256, 256)
... | 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... | gautam-sharma1/Imitation-Learning | Temp | false | 3,528 | [
"MIT"
] | 0 | 20b6fcd2a8d6de8eb95e6831f5b379a083306361 | https://github.com/gautam-sharma1/Imitation-Learning/tree/20b6fcd2a8d6de8eb95e6831f5b379a083306361 |
SqueezeExcite | import torch
import torch.nn as nn
import torch.nn.functional as F
def _make_divisible(v, divisor, min_value=None):
"""
This function is taken from the original tf repo.
It ensures that all layers have a channel number that is divisible by 8
It can be seen here:
https://github.com/tensorflow/model... | 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 ... | EileenWang90/mmpose | SqueezeExcite | false | 2,185 | [
"Apache-2.0"
] | 0 | 3fa1328a3b6351bf9b35df60d4d959973a6f8a71 | https://github.com/EileenWang90/mmpose/tree/3fa1328a3b6351bf9b35df60d4d959973a6f8a71 |
SqueezeEmbedding | import torch
import torch.nn as nn
class SqueezeEmbedding(nn.Module):
"""
Squeeze sequence embedding length to the longest one in the batch
"""
def __init__(self, batch_first=True):
super(SqueezeEmbedding, self).__init__()
self.batch_first = batch_first
def forward(self, x, x_len... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | minionssso/PyABSA | SqueezeEmbedding | false | 4,001 | [
"MIT"
] | 0 | fd9a9a6fd55552a60329fd04b6830e1bb144d50f | https://github.com/minionssso/PyABSA/tree/fd9a9a6fd55552a60329fd04b6830e1bb144d50f |
Permute | import torch
from torch import nn
class Permute(nn.Module):
def __init__(self, permutation=[2, 1, 0]):
super().__init__()
self.permutation = permutation
def forward(self, input):
return input[:, self.permutation]
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_ini... | 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... | Alibaba-AAIG/Beyond-ImageNet-Attack | Permute | false | 7,658 | [
"MIT"
] | 23 | c14b4844b64a8035b8fe033a617c0567224a9fa4 | https://github.com/Alibaba-AAIG/Beyond-ImageNet-Attack/tree/c14b4844b64a8035b8fe033a617c0567224a9fa4 |
SpatialGate | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
class Conv3DSimple(nn.Conv3d):
def __init__(self, in_planes, out_planes, stride=1, kernel_size=3):
padding = (kernel_size - 1) // 2
super(Conv3DSimple, 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 ... | JoohyungLee0106/rectal_MR_volume_classification | SpatialGate | false | 694 | [
"MIT"
] | 0 | d2a7d13dae9fe7255b983cbc210567dd452a936f | https://github.com/JoohyungLee0106/rectal_MR_volume_classification/tree/d2a7d13dae9fe7255b983cbc210567dd452a936f |
WeightedCrossEntropyLoss | # 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
... | LaudateCorpus1/LIGA-Stereo | WeightedCrossEntropyLoss | false | 13,994 | [
"Apache-2.0"
] | 56 | aee3731a24a0ab1667e633e520cc89be2f135272 | https://github.com/LaudateCorpus1/LIGA-Stereo/tree/aee3731a24a0ab1667e633e520cc89be2f135272 |
ProtoNN | # 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 numpy ... | ShishirPatil/EdgeML-1 | ProtoNN | false | 1,072 | [
"MIT"
] | 0 | cbba9f8b989e545788427c004eb8450e7e4c1a21 | https://github.com/ShishirPatil/EdgeML-1/tree/cbba9f8b989e545788427c004eb8450e7e4c1a21 |
GroupLinear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | Lakonik/EPro-PnP | GroupLinear | false | 8,433 | [
"Apache-2.0"
] | 19 | 931df847190ce10eddd1dc3e3168ce1a2f295ffa | https://github.com/Lakonik/EPro-PnP/tree/931df847190ce10eddd1dc3e3168ce1a2f295ffa |
BasicModel5_MultiArgs | import torch
import torch.nn as nn
import torch.nn.functional as F
class BasicModel5_MultiArgs(nn.Module):
"""
Slightly modified example model from the paper
https://arxiv.org/pdf/1703.01365.pdf
f(x1, x2) = RELU(ReLU(x1 - 1) * x3[0] - ReLU(x2) * x3[1])
"""
def __init__(self) ->None:
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 import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | LMdeLiangMi/captum | BasicModel5_MultiArgs | false | 5,470 | [
"BSD-3-Clause"
] | 1 | 8bd9686013fe0ba8996e9b1cbeb0ea8e91512787 | https://github.com/LMdeLiangMi/captum/tree/8bd9686013fe0ba8996e9b1cbeb0ea8e91512787 |
InnerProductLoss | # 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, math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.gu... | Ahren09/RecBole | InnerProductLoss | false | 1,925 | [
"MIT"
] | 0 | b3921818dfbc1b81f9eda8d5e9f05bc9d9114089 | https://github.com/Ahren09/RecBole/tree/b3921818dfbc1b81f9eda8d5e9f05bc9d9114089 |
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... | hendraet/research-GANwriting | Conv2dBlock | false | 12,496 | [
"MIT"
] | 0 | e62a16529db3037169d9b33ecba5735c99e73bc3 | https://github.com/hendraet/research-GANwriting/tree/e62a16529db3037169d9b33ecba5735c99e73bc3 |
MarginRankingLearningLoss | # 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 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._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guard... | VKCOM/TopicsDataset | MarginRankingLearningLoss | false | 5,919 | [
"MIT"
] | 1 | 149919321ba61a8f17b22f62f60f4aedec43d72b | https://github.com/VKCOM/TopicsDataset/tree/149919321ba61a8f17b22f62f60f4aedec43d72b |
l1normalization | import torch
import torch.nn as nn
class l1normalization(nn.Module):
def __init__(self, scale):
super(l1normalization, self).__init__()
self.scale = scale
def forward(self, x, dim=1):
return self.scale * x * x.pow(1).sum(dim).clamp(min=1e-12).rsqrt(
).expand_as(x)
def g... | 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... | tommy90191/Find_Tiny_but_Important_Image_Changes | l1normalization | false | 4,439 | [
"MIT"
] | 0 | 429d679606f96f32db4cddf167a9cfb963d3df26 | https://github.com/tommy90191/Find_Tiny_but_Important_Image_Changes/tree/429d679606f96f32db4cddf167a9cfb963d3df26 |
ScaleNorm | import torch
import torch.nn as nn
class ScaleNorm(nn.Module):
def __init__(self, dim, eps=1e-05):
super().__init__()
self.scale = dim ** -0.5
self.eps = eps
self.g = nn.Parameter(torch.ones(1))
def forward(self, x):
norm = torch.norm(x, dim=-1, keepdim=True) * self.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 import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | poliver269/latent-diffusion | ScaleNorm | false | 12,904 | [
"MIT"
] | 0 | 08e7c987ad423e3f93125b49980c36302ffe3d82 | https://github.com/poliver269/latent-diffusion/tree/08e7c987ad423e3f93125b49980c36302ffe3d82 |
Complex_nn | import torch
import torch.nn.functional as F
class Complex_nn(torch.nn.Module):
def __init__(self, dims_in, hidden):
super(Complex_nn, self).__init__()
self.fc1 = torch.nn.Linear(dims_in, hidden)
self.fc2 = torch.nn.Linear(hidden, hidden)
self.fc3 = torch.nn.Linear(hidden, 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 import triton_helpers
from torch._inductor.runtime.... | urbanriskmap/timeseries-analysis | Complex_nn | false | 10,903 | [
"MIT"
] | 0 | 6b9a8d1a916ff784cb0de93d6997cd072d1ca6ae | https://github.com/urbanriskmap/timeseries-analysis/tree/6b9a8d1a916ff784cb0de93d6997cd072d1ca6ae |
CrossLayer | import torch
import torch.nn as nn
import torch.optim
class CrossLayer(nn.Module):
def __init__(self, d, dropout):
super().__init__()
self.linear = nn.Linear(d, d)
self.dropout = nn.Dropout(dropout)
def forward(self, x0, x):
return self.dropout(x0 * self.linear(x)) + x
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
import torch.nn as nn
import torch.optim
assert_size_stride = torch._C._dynamo.g... | piers-hinds/rtdl | CrossLayer | false | 10,627 | [
"Apache-2.0"
] | 0 | 66cf9b90d2269395152dabf32653bdd599ddb12e | https://github.com/piers-hinds/rtdl/tree/66cf9b90d2269395152dabf32653bdd599ddb12e |
KLLoss | import torch
import torch.nn as nn
import torch.cuda
from torch import linalg as linalg
class BaseMeasure(nn.Module):
"""
"""
NAME: 'str' = NotImplemented
REFERENCE: 'str' = None
BIGGER_IS_BETTER = False
OPT_VALUE = 0.0
def __init__(self, device):
"""
Args:
dev... | 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 torch.nn as nn
import torch.cuda
from torch import linalg as linal... | angelvillar96/vp-suite | KLLoss | false | 3,107 | [
"MIT"
] | 0 | 3e7c7d852862bad09a771d754fc56a71abf0a25f | https://github.com/angelvillar96/vp-suite/tree/3e7c7d852862bad09a771d754fc56a71abf0a25f |
Triaffine | # 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... | KoichiYasuoka/SuPar | Triaffine | false | 11,631 | [
"MIT"
] | 0 | 9bcf10fb946cae75b6a311d4cd19bec5bb1a9487 | https://github.com/KoichiYasuoka/SuPar/tree/9bcf10fb946cae75b6a311d4cd19bec5bb1a9487 |
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