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 |
|---|---|---|---|---|---|---|---|---|---|---|
ShiftedSoftplus | # 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
from torch import nn
assert_size_stride = torch._C._dynamo.gua... | cmusatyalab/mega-nerf | ShiftedSoftplus | false | 15,051 | [
"MIT"
] | 107 | 306e06cc316dd4f5c84d0610308bcbc208228fc3 | https://github.com/cmusatyalab/mega-nerf/tree/306e06cc316dd4f5c84d0610308bcbc208228fc3 |
Hflip | # 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... | justanhduc/kornia | Hflip | false | 15,750 | [
"ECL-2.0",
"Apache-2.0"
] | 51 | c14081292dfb2491fad50ba10e27491cad8cb3e3 | https://github.com/justanhduc/kornia/tree/c14081292dfb2491fad50ba10e27491cad8cb3e3 |
MLP | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | MichaelLee-ceo/FedSAUC | MLP | false | 5,596 | [
"Apache-2.0"
] | 1 | 8c00008772213562ff6a07bf9fa92c3831713118 | https://github.com/MichaelLee-ceo/FedSAUC/tree/8c00008772213562ff6a07bf9fa92c3831713118 |
Sys_R | import torch
import torch.nn as nn
import torch.nn.functional as F
class Sys_R(nn.Module):
def __init__(self, state_size, action_size, fc1_units=256, fc2_units=256):
super(Sys_R, self).__init__()
self.l1 = nn.Linear(2 * state_size + action_size, fc1_units)
self.l2 = nn.Linear(fc1_units, f... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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_... | LuckierDodge/ROS_Dockerfiles | Sys_R | false | 2,630 | [
"MIT"
] | 0 | 42fd0e7ecfef86d792fcc29197fcd79dcb789122 | https://github.com/LuckierDodge/ROS_Dockerfiles/tree/42fd0e7ecfef86d792fcc29197fcd79dcb789122 |
Sparsemax | import torch
import torch.utils.data
import torch.nn as nn
class Sparsemax(nn.Module):
"""Sparsemax function."""
def __init__(self, dim=None):
"""Initialize sparsemax activation
Args:
dim (int, optional): The dimension over which to apply the sparsemax function.
"... | 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
assert_size_stride = torch._C._dynamo.guard... | tkc-morita/secl | Sparsemax | false | 10,929 | [
"MIT"
] | 0 | d0156cea4fd95ea5071126dbf076a6da69752a37 | https://github.com/tkc-morita/secl/tree/d0156cea4fd95ea5071126dbf076a6da69752a37 |
SACCriticNetwork | import torch
import torch.nn.functional as F
import torch.nn as nn
class SACCriticNetwork(nn.Module):
def __init__(self, input_shape, output_shape, n_features, **kwargs):
super().__init__()
n_input = input_shape[-1]
n_output = output_shape[0]
self._h1 = nn.Linear(n_input, n_featur... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 | SACCriticNetwork | false | 12,547 | [
"MIT"
] | 0 | 5bc2e9b1a12be33827d6edcd5c5ad49571e11275 | https://github.com/jacarvalho/mushroom-rl-benchmark/tree/5bc2e9b1a12be33827d6edcd5c5ad49571e11275 |
SPP | # 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.optim
import torch.utils.data
assert_size_stride = tor... | ldylab/learning_yolo_family_with_pytorch | SPP | false | 3,872 | [
"MIT"
] | 0 | 63fd8d65e5ccd55c9ec124052bbcb040e0d9c549 | https://github.com/ldylab/learning_yolo_family_with_pytorch/tree/63fd8d65e5ccd55c9ec124052bbcb040e0d9c549 |
KdCeLoss | # 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
... | Raiselimit/TorchBlocks | KdCeLoss | false | 5,761 | [
"MIT"
] | 1 | a5baecb9a2470ff175087475630f2b7db3f7ef51 | https://github.com/Raiselimit/TorchBlocks/tree/a5baecb9a2470ff175087475630f2b7db3f7ef51 |
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.optim
import tor... | jwdink/PyTorch-LBFGS | ConvNet | false | 10,308 | [
"MIT"
] | 0 | 7e18ea3d9cb16a0af1a76f7c9c023c916b408a04 | https://github.com/jwdink/PyTorch-LBFGS/tree/7e18ea3d9cb16a0af1a76f7c9c023c916b408a04 |
AugCNN | import torch
import torch.nn as nn
import torch.nn.functional as F
def apply_init_(modules):
"""
Initialize NN modules
"""
for m in modules:
if isinstance(m, nn.Conv2d):
nn.init.xavier_uniform_(m.weight)
if m.bias is not None:
nn.init.constant_(m.bias, 0... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | joshnroy/contrastive-rl | AugCNN | false | 12,636 | [
"MIT"
] | 0 | d0e8cd8fd6963983dc62dd282b788002a892704e | https://github.com/joshnroy/contrastive-rl/tree/d0e8cd8fd6963983dc62dd282b788002a892704e |
BCEDiceLoss | import torch
from torch import nn
import torch.utils.data
import torch.nn.functional as F
class BCEDiceLoss(nn.Module):
def __init__(self):
super().__init__()
def forward(self, input, target):
bce = F.binary_cross_entropy_with_logits(input, target)
smooth = 1e-05
input = 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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch ... | Information-Fusion-Lab-Umass/pytorch-nested-unet | BCEDiceLoss | false | 11,512 | [
"MIT"
] | 0 | 29b8704795f9d0ab17952b19bf8b4624e7aa16c0 | https://github.com/Information-Fusion-Lab-Umass/pytorch-nested-unet/tree/29b8704795f9d0ab17952b19bf8b4624e7aa16c0 |
AddSubNet | import torch
from torch import nn
class AddSubNet(nn.Module):
"""
Simple AddSub network in PyTorch. This network outputs the sum and
subtraction of the inputs.
"""
def __init__(self):
super(AddSubNet, self).__init__()
def forward(self, input0, input1):
return torch.sub(input0... | 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... | fivetran-VitaliyMalkin/server | AddSubNet | false | 10,037 | [
"BSD-3-Clause"
] | 0 | 643840a61038aa090c37e1544826264925d0b483 | https://github.com/fivetran-VitaliyMalkin/server/tree/643840a61038aa090c37e1544826264925d0b483 |
Bar | import torch
import torch.onnx
import torch.nn
class Bar(torch.nn.Module):
def __init__(self, x):
super(Bar, self).__init__()
self.x = x
def forward(self, a, b):
return a * b + self.x
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_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
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guar... | hl475/glow | Bar | false | 3,591 | [
"Apache-2.0"
] | 0 | f24d960e3cc80db95ac0bc17b1900dbf60ca044a | https://github.com/hl475/glow/tree/f24d960e3cc80db95ac0bc17b1900dbf60ca044a |
ConvNCFBPRLoss | # 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
... | MIracleyin/RecBole-notebook | ConvNCFBPRLoss | false | 9,575 | [
"MIT"
] | 0 | ef32b3e57a297ff4889dec1f63c7984f8f901a23 | https://github.com/MIracleyin/RecBole-notebook/tree/ef32b3e57a297ff4889dec1f63c7984f8f901a23 |
TransferNet | import torch
import torch.nn as nn
class GenericLayer(nn.Module):
def __init__(self, layer, out_channels, padding=(0, 0, 0, 0),
activation=None):
super(GenericLayer, self).__init__()
self._act = activation
self._layer = layer
self._norm = nn.InstanceNorm2d(out_channels, af... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | ThomasRanvier/cnn_style_transfer | TransferNet | false | 1,222 | [
"MIT"
] | 0 | 90b6c76c20263c22f4e45184d572284726ecbd7b | https://github.com/ThomasRanvier/cnn_style_transfer/tree/90b6c76c20263c22f4e45184d572284726ecbd7b |
bhaModel | # 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_... | BharathC15/bharathML | bhaModel | false | 8,855 | [
"MIT"
] | 0 | ab0460eace3bc83a6b9a7ba7c40e9721baead09a | https://github.com/BharathC15/bharathML/tree/ab0460eace3bc83a6b9a7ba7c40e9721baead09a |
Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from logging import info
from... | ChsHub/ai_denoiser | Net | false | 309 | [
"MIT"
] | 0 | abb0852765b10a0f05593a850f9922c5737f5f6a | https://github.com/ChsHub/ai_denoiser/tree/abb0852765b10a0f05593a850f9922c5737f5f6a |
Normalize | # 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... | JindongGu/SimDis | Normalize | false | 8,352 | [
"MIT"
] | 12 | 0871a217a756acc268f35f802e35b01b12817f0d | https://github.com/JindongGu/SimDis/tree/0871a217a756acc268f35f802e35b01b12817f0d |
ShuffleCat | import torch
import torch.nn as nn
class ShuffleCat(nn.Module):
def forward(self, a, b):
assert a.size() == b.size()
n, c, h, w = a.size()
a = a.permute(0, 2, 3, 1).contiguous().view(-1, c)
b = b.permute(0, 2, 3, 1).contiguous().view(-1, c)
x = torch.cat((a, b), dim=0).tra... | 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... | akaneko1019/yolact_edge | ShuffleCat | false | 14,769 | [
"MIT"
] | 1,036 | a9a00281b33b3ac90253a4939773308a8f95e21d | https://github.com/akaneko1019/yolact_edge/tree/a9a00281b33b3ac90253a4939773308a8f95e21d |
FromRGB | # 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... | uthree/gan-image-generator | FromRGB | false | 11,001 | [
"MIT"
] | 0 | 85585e389b5a494393da0789d82824f8c811e263 | https://github.com/uthree/gan-image-generator/tree/85585e389b5a494393da0789d82824f8c811e263 |
HighwayLayer | import torch
from torch import nn
import torch.utils.data
import torch.utils.data.distributed
import torch.utils.checkpoint
import torch.utils.tensorboard
def my_xavier_init(m, gain=1):
"""Xavier initialization: weights initialization that tries to make variance of outputs
of a layer equal to variance of its ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | ali-senguel/fairo-explore | HighwayLayer | false | 10,033 | [
"MIT"
] | 0 | 893481da270eed1e6d504c71e483d685ca9218d1 | https://github.com/ali-senguel/fairo-explore/tree/893481da270eed1e6d504c71e483d685ca9218d1 |
_GatedLinearUnit | import torch
import torch.nn as nn
import torch.nn.functional as F
class _GatedLinearUnit(nn.Module):
"""Gated Linear Unit"""
def __init__(self, input_size: 'int', hidden_size: 'int'=None, dropout:
'float'=None):
super().__init__()
if dropout is not None:
self.dropout = 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... | Gian-Wiher/darts | _GatedLinearUnit | false | 5,205 | [
"Apache-2.0"
] | 1 | 0d267e08643e2e3f88163a5d955b8be75840c2f6 | https://github.com/Gian-Wiher/darts/tree/0d267e08643e2e3f88163a5d955b8be75840c2f6 |
ScaledDotProduct | import math
import torch
from torch import nn
class ScaledDotProduct(nn.Module):
def __init__(self, attentionHeadSize, dropOutProb=0.1):
super(ScaledDotProduct, self).__init__()
self.attentionHeadSize = attentionHeadSize
self.dropout = nn.Dropout(dropOutProb)
def forward(self, Q, K, ... | 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... | simonepreite/QABERT | ScaledDotProduct | false | 4,336 | [
"MIT"
] | 0 | ed3e49f6619f3ff660068291231909693cb8f5d5 | https://github.com/simonepreite/QABERT/tree/ed3e49f6619f3ff660068291231909693cb8f5d5 |
GeneralizedDiceLoss | # 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 collections
from typi... | Alxaline/MONAI | GeneralizedDiceLoss | false | 4,894 | [
"Apache-2.0"
] | 1 | 6b8fdf9db7f13ed7d88d605155a0463840abcbf2 | https://github.com/Alxaline/MONAI/tree/6b8fdf9db7f13ed7d88d605155a0463840abcbf2 |
CoordConv | # 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... | MingSungChao/IPN-hand | CoordConv | false | 14,019 | [
"MIT"
] | 54 | 0b061e4438f159e3e312af4959cb424917b5c367 | https://github.com/MingSungChao/IPN-hand/tree/0b061e4438f159e3e312af4959cb424917b5c367 |
discriminator | import torch
from torch import nn
import torch.nn.functional as F
class discriminator(nn.Module):
def __init__(self):
super(discriminator, self).__init__()
self.d1 = nn.Conv2d(in_channels=1, out_channels=4, kernel_size=2,
stride=2, padding=0)
self.d2 = nn.Conv2d(in_channels=4,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | layel2/layyer-lib | discriminator | false | 3,878 | [
"MIT"
] | 0 | db48b5c38098ee93d2d34693d98e5ef4d319d919 | https://github.com/layel2/layyer-lib/tree/db48b5c38098ee93d2d34693d98e5ef4d319d919 |
Cov2Corr | import torch
import torch.nn as nn
class Cov2Corr(nn.Module):
"""Conversion from covariance matrix to correlation matrix."""
def forward(self, covmat):
"""Convert.
Parameters
----------
covmat : torch.Tensor
Covariance matrix of shape (n_samples, n_assets, n_asset... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | vishalbelsare/deepdow | Cov2Corr | false | 16,676 | [
"Apache-2.0"
] | 511 | cbb99347fba9a447d4fcae64fe5137c203643e44 | https://github.com/vishalbelsare/deepdow/tree/cbb99347fba9a447d4fcae64fe5137c203643e44 |
MultiHeadAttention | import math
import torch
import torch.nn as nn
class MultiHeadAttention(nn.Module):
"""
Multi-head Self-attention layers, a attention score dropout layer is introduced.
Args:
input_tensor (torch.Tensor): the input of the multi-head self-attention layer
attention_mask (torch.Tensor): the 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
from torch._inductor.runtime.... | BELIEVEfxy/LightSANs | MultiHeadAttention | false | 7,802 | [
"MIT"
] | 17 | 94ce7e59d144dbc787153b8c486cad334790ec6e | https://github.com/BELIEVEfxy/LightSANs/tree/94ce7e59d144dbc787153b8c486cad334790ec6e |
PureUpsampling | import torch
import torch.nn as nn
import torch.nn.functional as F
class PureUpsampling(nn.Module):
def __init__(self, scale=2, mode='bilinear'):
super(PureUpsampling, self).__init__()
assert isinstance(scale, int)
self.scale = scale
self.mode = mode
def forward(self, 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | vlbthambawita/polyp-inpainting | PureUpsampling | false | 4,502 | [
"MIT"
] | 0 | f1d754f8ffb3f6d991206b2a661933ff32de0d7a | https://github.com/vlbthambawita/polyp-inpainting/tree/f1d754f8ffb3f6d991206b2a661933ff32de0d7a |
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.... | carolmanderson/NeMo | MultiHeadAttn | false | 6,418 | [
"Apache-2.0"
] | 1 | be7114e2d983af751e1af4119465c626682747b7 | https://github.com/carolmanderson/NeMo/tree/be7114e2d983af751e1af4119465c626682747b7 |
UnaryBlock | # 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.utils.... | wuxingzhe/OverPredactor | UnaryBlock | false | 11,036 | [
"MIT"
] | 0 | 3a0965f4c3fc84ec0dcba555ec7c460f265d9143 | https://github.com/wuxingzhe/OverPredactor/tree/3a0965f4c3fc84ec0dcba555ec7c460f265d9143 |
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.... | krasserm/perceiver-io | MultiHeadAttention | false | 15,853 | [
"Apache-2.0"
] | 133 | 16e1029300304b617c0b0ae8eb06129ec103c755 | https://github.com/krasserm/perceiver-io/tree/16e1029300304b617c0b0ae8eb06129ec103c755 |
EncoderLayer | # 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.... | csyhhu/attention-is-all-you-need-pytorch | EncoderLayer | false | 6,520 | [
"MIT"
] | 1 | 5792c9714295b1a33d1ca074206ec223f436b954 | https://github.com/csyhhu/attention-is-all-you-need-pytorch/tree/5792c9714295b1a33d1ca074206ec223f436b954 |
Critic | import torch
import torch.nn.functional as f
from torch import nn
class Critic(nn.Module):
def __init__(self, input_dim):
super(Critic, self).__init__()
self._input_dim = input_dim
self.dense1 = nn.Linear(self._input_dim, self._input_dim)
self.dense2 = nn.Linear(self._input_dim, s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | amirarsalan90/TabFairGAN | Critic | false | 18,297 | [
"MIT"
] | 5 | 402c434e0aa7a335fda652a67e72b132edb5f663 | https://github.com/amirarsalan90/TabFairGAN/tree/402c434e0aa7a335fda652a67e72b132edb5f663 |
EntropyLoss | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
import torch.utils.data.distributed
import torch.nn.functional as F
class EntropyLoss(nn.Module):
def __init__(self):
super(EntropyLoss, self).__init__()
def forward(self, input):
prob = F.softmax(input, dim=... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | LakeAndCat/CluOReg | EntropyLoss | false | 746 | [
"MIT"
] | 0 | ba50cb056061b3833050d32e532e08152bdc8de2 | https://github.com/LakeAndCat/CluOReg/tree/ba50cb056061b3833050d32e532e08152bdc8de2 |
SymKlCriterion | # 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
from torch.... | kiminh/mt-dnn | SymKlCriterion | false | 7,038 | [
"MIT"
] | 1 | 133884b380244dbe74acc4d7507e551b2c5035b3 | https://github.com/kiminh/mt-dnn/tree/133884b380244dbe74acc4d7507e551b2c5035b3 |
Rot180 | import torch
import torch.nn as nn
def rot180(input: 'torch.Tensor') ->torch.Tensor:
"""Rotate a tensor image or a batch of tensor images
180 degrees. Input must be a tensor of shape (C, H, W)
or a batch of tensors :math:`(*, C, H, W)`.
Args:
input (torch.Tensor): input tensor
Returns:
... | 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... | connorlee77/kornia | Rot180 | false | 6,476 | [
"ECL-2.0",
"Apache-2.0"
] | 1 | af5b1f76bedf2a7fc0e0da2386b1be3032b6534f | https://github.com/connorlee77/kornia/tree/af5b1f76bedf2a7fc0e0da2386b1be3032b6534f |
SqueezeExcitation | # 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... | NephrenCake/FlameRecognition | SqueezeExcitation | false | 9,408 | [
"MIT"
] | 0 | 3075a345b51c2c855a5cb2decd839065230e1484 | https://github.com/NephrenCake/FlameRecognition/tree/3075a345b51c2c855a5cb2decd839065230e1484 |
SpatialGate | # 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... | PRIS-CV/AP-CNN_Pytorch-master | SpatialGate | false | 8,630 | [
"MIT"
] | 26 | 00ddefee69ab35b8435b732bdf3bd7514a3e4545 | https://github.com/PRIS-CV/AP-CNN_Pytorch-master/tree/00ddefee69ab35b8435b732bdf3bd7514a3e4545 |
FCDiscriminator | # 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... | unicredit/ganzo | FCDiscriminator | false | 16,647 | [
"Apache-2.0"
] | 73 | fb1d270f5091073e8f27da76ab508ab24e5d40e9 | https://github.com/unicredit/ganzo/tree/fb1d270f5091073e8f27da76ab508ab24e5d40e9 |
BiDAFAttention | # 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.... | Derek318/Adversarial-Squad-CS224N | BiDAFAttention | false | 5,091 | [
"MIT"
] | 1 | 9b4a5da2a262f4de9b9b05d7b67dc48b2b857e46 | https://github.com/Derek318/Adversarial-Squad-CS224N/tree/9b4a5da2a262f4de9b9b05d7b67dc48b2b857e46 |
ContrastivePairwiseEmbeddingLoss | # 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.... | bbradt/catalyst | ContrastivePairwiseEmbeddingLoss | false | 3,180 | [
"Apache-2.0"
] | 0 | 38a503c8af040906e377b7485d7fe15a7bc1de19 | https://github.com/bbradt/catalyst/tree/38a503c8af040906e377b7485d7fe15a7bc1de19 |
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... | hassony2/frankmocap | ConvertPointsToHomogeneous | false | 6,785 | [
"BSD-3-Clause"
] | 1 | 50aae41d9b41d2f344ae1709bbf1b25974209fa9 | https://github.com/hassony2/frankmocap/tree/50aae41d9b41d2f344ae1709bbf1b25974209fa9 |
ReceptiveFieldNorm | # 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... | amazon-research/network-deconvolution-pp | ReceptiveFieldNorm | false | 18,354 | [
"Apache-2.0"
] | 6 | 99e27ecec7d27c7c4c3fb230e96005bdcbf6f2ce | https://github.com/amazon-research/network-deconvolution-pp/tree/99e27ecec7d27c7c4c3fb230e96005bdcbf6f2ce |
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | JDAI-CV/LIO | Classifier | false | 13,855 | [
"Apache-2.0"
] | 105 | 7bcd4d5e2990db5c8a7ec6ecc76a23c2e913e523 | https://github.com/JDAI-CV/LIO/tree/7bcd4d5e2990db5c8a7ec6ecc76a23c2e913e523 |
L1CompositionLoss | import functools
import torch
import torch.nn as nn
from torch.nn import 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".
Returns:
Tensor: Reduced lo... | 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... | akimotty877/mmediting | L1CompositionLoss | false | 3,066 | [
"Apache-2.0"
] | 0 | cae872d6f3e867ba144c7c0dbc29a0ee1a29e5a6 | https://github.com/akimotty877/mmediting/tree/cae872d6f3e867ba144c7c0dbc29a0ee1a29e5a6 |
Quantization | import torch
import torch.utils.data
import torch.nn as nn
class Quant(torch.autograd.Function):
@staticmethod
def forward(ctx, input):
input = torch.clamp(input, 0, 1)
output = (input * 255.0).round() / 255.0
return output
@staticmethod
def backward(ctx, grad_output):
... | 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
impo... | peterhan91/Invertible-Image-Rescaling | Quantization | false | 4,109 | [
"Apache-2.0"
] | 0 | b92162f5e9be2cff2f5dba379914fcded4e04f4c | https://github.com/peterhan91/Invertible-Image-Rescaling/tree/b92162f5e9be2cff2f5dba379914fcded4e04f4c |
CustomBatchNormManualModule | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | RaymondKoopmanschap/DL_assignment_code | CustomBatchNormManualModule | false | 978 | [
"MIT"
] | 0 | 68b3290be9fbd6c55433a7585e2cfa18e0f35f5c | https://github.com/RaymondKoopmanschap/DL_assignment_code/tree/68b3290be9fbd6c55433a7585e2cfa18e0f35f5c |
GraphGaussianBlock | import math
import torch
import torch.nn as nn
import torch.optim
import torch.multiprocessing
from torch.nn.parameter import Parameter
class GraphConvolution(nn.Module):
def __init__(self, in_features, out_features, bias=True, node_n=48,
out_node_n=None):
super(GraphConvolution, 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 import triton_helpers
import math
import torch.nn a... | bouracha/Gen_Motion | GraphGaussianBlock | false | 9,931 | [
"MIT"
] | 0 | 873caa496d14c9a9723581cdf1464f44db4cf358 | https://github.com/bouracha/Gen_Motion/tree/873caa496d14c9a9723581cdf1464f44db4cf358 |
SelfAttn | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.init
import torch as th
class SelfAttn(nn.Module):
def __init__(self, hidden_size):
super(SelfAttn, self).__init__()
self.query = nn.Linear(hidden_size, 1)
def forward(self, keys, values, attn_mask=None):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | haojiepan1/CrossWOZ | SelfAttn | false | 6,789 | [
"Apache-2.0"
] | 1 | 6d7b4c4cfb73a528b76074764687906abecc90b6 | https://github.com/haojiepan1/CrossWOZ/tree/6d7b4c4cfb73a528b76074764687906abecc90b6 |
MixerMLP | import torch
import torch.nn as nn
class MixerMLP(nn.Module):
"""Some Information about MixerMLP"""
def __init__(self, dim, activation='gelu'):
super(MixerMLP, self).__init__()
if activation == 'gelu':
self.activation = nn.GELU()
elif activation == 'relu':
self... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | uthree/ReMixer | MixerMLP | false | 13,064 | [
"MIT"
] | 0 | 587e1b6a01850df649eccf043689f84a7dd5e2dc | https://github.com/uthree/ReMixer/tree/587e1b6a01850df649eccf043689f84a7dd5e2dc |
SplAtConv2d | # 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.... | DYF-AI/openvino-x | SplAtConv2d | false | 5,054 | [
"Apache-2.0"
] | 1 | 0f18ebb240ea3394f7e461aca34fac158e686d95 | https://github.com/DYF-AI/openvino-x/tree/0f18ebb240ea3394f7e461aca34fac158e686d95 |
GDeconv1DBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.nn.utils.spectral_norm import spectral_norm
ass... | silvadirceu/segan_pytorch | GDeconv1DBlock | false | 10,802 | [
"MIT"
] | 0 | 2215e711f7223b144e0c4d4fb4ed1d4842b18c5f | https://github.com/silvadirceu/segan_pytorch/tree/2215e711f7223b144e0c4d4fb4ed1d4842b18c5f |
SimpleACosModule | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleACosModule(torch.nn.Module):
def __init__(self):
super(SimpleACosModule, self).__init__()
def forward(self, a):
return torch.acos(a + a)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._... | andreas-hommel/glow | SimpleACosModule | false | 3,311 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
QuaternionLinear | # 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.nn import Module
import numpy as np
from numpy.random import RandomSt... | eleGAN23/HI2I | QuaternionLinear | false | 6,678 | [
"MIT"
] | 1 | 7730ee0963614290099b011c113048ef6d1b149c | https://github.com/eleGAN23/HI2I/tree/7730ee0963614290099b011c113048ef6d1b149c |
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... | Akababa/torch2trt | TorchSub | false | 18,433 | [
"MIT"
] | 2 | 03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 | https://github.com/Akababa/torch2trt/tree/03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 |
StrongMask | # 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 math
import torch.nn.f... | IssamLaradji/wisenet | StrongMask | false | 17,470 | [
"Apache-2.0"
] | 7 | 881457f5168815f5e9d03f110244842d539747a0 | https://github.com/IssamLaradji/wisenet/tree/881457f5168815f5e9d03f110244842d539747a0 |
Acos | # 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.onnx
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | mil-tokyo/webdnn | Acos | false | 16,067 | [
"MIT"
] | 1,967 | 38a60fd3e1a4e72bc01108189a3aa51e0752aecd | https://github.com/mil-tokyo/webdnn/tree/38a60fd3e1a4e72bc01108189a3aa51e0752aecd |
DQNet | import torch
import torch.nn as nn
from torch.nn import functional as F
class DQNet(nn.Module):
"""
Definition: DQNet(obs_size,act_size,hid_size=256)
Regular Deep Q Network with three Linear layers
"""
def __init__(self, obs_size, act_size, hid_size=256):
super().__init__()
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
assert_... | ayjabri/DeepRL | DQNet | false | 1,505 | [
"MIT"
] | 0 | 0be095e3a3d04f60b4cdc97ed330dffc17b3024a | https://github.com/ayjabri/DeepRL/tree/0be095e3a3d04f60b4cdc97ed330dffc17b3024a |
AverageAttention | # 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.cuda
import torch.distributed
assert_size_str... | NaomiatLibrary/OpenNMT-kpg-release | AverageAttention | false | 880 | [
"MIT"
] | 0 | 1da3468d7dad22529a77f3526abf9b373bd3dc4c | https://github.com/NaomiatLibrary/OpenNMT-kpg-release/tree/1da3468d7dad22529a77f3526abf9b373bd3dc4c |
SigmoidDeepLiftModel | import torch
import torch.nn as nn
class SigmoidDeepLiftModel(nn.Module):
"""
Model architecture from:
https://medium.com/coinmonks/create-a-neural-network-in
-pytorch-and-make-your-life-simpler-ec5367895199
"""
def __init__(self, num_in, num_hidden, num_out) ->None:
super().__ini... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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_... | YNNEKUW/captum | SigmoidDeepLiftModel | false | 11,995 | [
"BSD-3-Clause"
] | 0 | c8b5357b21f2ddf440e5f0ce25635977292aa5d1 | https://github.com/YNNEKUW/captum/tree/c8b5357b21f2ddf440e5f0ce25635977292aa5d1 |
Attn | import torch
from torch import nn
import torch.nn.functional as F
class Attn(nn.Module):
def __init__(self, hidden_size):
super(Attn, self).__init__()
self.hidden_size = hidden_size
self.attn = nn.Linear(self.hidden_size * 2, hidden_size)
self.v = nn.Linear(self.hidden_size, 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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | AuCson/SEDST | Attn | false | 7,739 | [
"MIT"
] | 23 | 1c1691e2abc50eb2120ed49c874090f6c4f741d3 | https://github.com/AuCson/SEDST/tree/1c1691e2abc50eb2120ed49c874090f6c4f741d3 |
ScalarMix | import torch
import torch.utils.data.dataloader
import torch.nn as nn
import torch.nn
class ScalarMix(nn.Module):
def __init__(self, n_layers, dropout=0):
super(ScalarMix, self).__init__()
self.n_layers = n_layers
self.dropout = dropout
self.weights = nn.Parameter(torch.zeros(n_la... | 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.utils.data.dataloader
import torch.nn as nn
import torch.nn
... | Dadmatech/DadmaTools | ScalarMix | false | 7,971 | [
"Apache-2.0"
] | 25 | c1b7add5c33544f69c1ba1c5250a5ea07caf9aa2 | https://github.com/Dadmatech/DadmaTools/tree/c1b7add5c33544f69c1ba1c5250a5ea07caf9aa2 |
RandomShiftsAug | import torch
import torch.nn as nn
import torch.nn.functional as F
class RandomShiftsAug(nn.Module):
def __init__(self, pad):
super().__init__()
self.pad = pad
def forward(self, x):
x = x.float()
n, _c, h, w = x.size()
assert h == w
padding = tuple([self.pad] ... | 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.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._d... | RobertMcCarthy97/url_benchmark | RandomShiftsAug | false | 2,774 | [
"MIT"
] | 0 | e2d99b05bc7fd62d1e8d9789840a0cc5d8174136 | https://github.com/RobertMcCarthy97/url_benchmark/tree/e2d99b05bc7fd62d1e8d9789840a0cc5d8174136 |
adaModule | import math
import torch
from torch import Tensor
import torch.nn as nn
from torch.nn import Parameter
class adaConv2d(nn.Module):
def __init__(self, in_channels: 'int', out_channels: 'int', kernel_size:
'int', stride: 'int'=1, padding: 'int'=0, dilation: 'int'=1, bias:
'bool'=True):
supe... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import math
i... | Artem531/pytorch-unet | adaModule | false | 74 | [
"MIT"
] | 0 | a8048f88f34a59f12f7f74735f03cf3c111a8415 | https://github.com/Artem531/pytorch-unet/tree/a8048f88f34a59f12f7f74735f03cf3c111a8415 |
WSDiceLoss | # 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
import torch.nn as nn
import torch.nn.parallel
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty... | devaansh100/pytorch_connectomics | WSDiceLoss | false | 6,566 | [
"MIT"
] | 1 | b1e4b16b0480546ea806d14876208080815ed964 | https://github.com/devaansh100/pytorch_connectomics/tree/b1e4b16b0480546ea806d14876208080815ed964 |
down_right_shifted_conv2d | import torch
import torch.nn as nn
from torch.nn.utils import weight_norm as wn
def right_shift(x, pad=None):
xs = [int(y) for y in x.size()]
x = x[:, :, :, :xs[3] - 1]
pad = nn.ZeroPad2d((1, 0, 0, 0)) if pad is None else pad
return pad(x)
class down_right_shifted_conv2d(nn.Module):
def __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 ... | VahidZee/PixelCnnPP | down_right_shifted_conv2d | false | 2,942 | [
"MIT"
] | 0 | b0d7bffb3cc18263e55d7851f60f5682ba09e5c2 | https://github.com/VahidZee/PixelCnnPP/tree/b0d7bffb3cc18263e55d7851f60f5682ba09e5c2 |
tofp16 | import torch
import torch.nn as nn
class tofp16(nn.Module):
def __init__(self):
super(tofp16, self).__init__()
def forward(self, input):
return input.half()
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | AnonymousAuthors444/VEC_VAD | tofp16 | false | 13,240 | [
"MIT"
] | 67 | 0072bf857030e621e2f9c12689407b81e45ed603 | https://github.com/AnonymousAuthors444/VEC_VAD/tree/0072bf857030e621e2f9c12689407b81e45ed603 |
Sinc | import torch
import torch.nn as nn
class Sinc(nn.Module):
def forward(self, x, epsilon=1e-09):
return torch.sin(x + epsilon) / (x + epsilon)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | awlange/pysurvival | Sinc | false | 14,921 | [
"Apache-2.0"
] | 242 | 841b9bc6ce700ba8898d2a1488aa9cd25ee7a8e6 | https://github.com/awlange/pysurvival/tree/841b9bc6ce700ba8898d2a1488aa9cd25ee7a8e6 |
FiLM | # 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... | Daupler/CA-MTL | FiLM | false | 2,136 | [
"MIT"
] | 0 | d417b039dee973e32f42ba5c1c346738cd29ab3c | https://github.com/Daupler/CA-MTL/tree/d417b039dee973e32f42ba5c1c346738cd29ab3c |
SelfMatch2 | # 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.... | nikcaryo/cs224n-squad | SelfMatch2 | false | 4,098 | [
"MIT"
] | 0 | 4bebca38f3cbaab8c80cd306863d6dca1d9cdf76 | https://github.com/nikcaryo/cs224n-squad/tree/4bebca38f3cbaab8c80cd306863d6dca1d9cdf76 |
FDiv | # 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... | dawnclaude/onnx2keras | FDiv | false | 15,132 | [
"MIT"
] | 115 | 3d2a47c0a228b91fd434232274e216e491da36e3 | https://github.com/dawnclaude/onnx2keras/tree/3d2a47c0a228b91fd434232274e216e491da36e3 |
weighted_mae_windows | import torch
import torch.nn as nn
class weighted_mae_windows(nn.Module):
def __init__(self, weights=(0.5, 1.2, 1.4, 1.6, 1.8, 2.0), thresholds=(
5.0, 15.0, 30.0, 40.0, 45.0)):
super(weighted_mae_windows, self).__init__()
assert len(thresholds) + 1 == len(weights)
self.weights = w... | 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
... | YuchenGUOGYC/gan_for_radar_extrapolation | weighted_mae_windows | false | 9,647 | [
"MIT"
] | 0 | cc43e6a691a81355faf0cda53a6b5555e886d75c | https://github.com/YuchenGUOGYC/gan_for_radar_extrapolation/tree/cc43e6a691a81355faf0cda53a6b5555e886d75c |
PSNRLoss | import torch
import torch.nn as nn
from torch.nn.functional import mse_loss as mse
def psnr(input: 'torch.Tensor', target: 'torch.Tensor', max_val: 'float'
) ->torch.Tensor:
"""Creates a function that calculates the PSNR between 2 images.
PSNR is Peek Signal to Noise Ratio, which is similar to mean squar... | 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
from t... | JoanFM/kornia | PSNRLoss | false | 11,543 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 808898887cde69074ca3e3df9b24dea9682aad90 | https://github.com/JoanFM/kornia/tree/808898887cde69074ca3e3df9b24dea9682aad90 |
GumbelSoftMaxSampler | # 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 import nn
f... | jvrana/deep-learning-guides | GumbelSoftMaxSampler | false | 12,641 | [
"MIT"
] | 0 | 18b7a0808073dd7b345e7a683dd7ee89e97e47ce | https://github.com/jvrana/deep-learning-guides/tree/18b7a0808073dd7b345e7a683dd7ee89e97e47ce |
MultiNonLinearClassifier | # 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 ... | BeyonderXX/MINER | MultiNonLinearClassifier | false | 8,846 | [
"Apache-2.0"
] | 0 | 552049139cc61dec8fba19f1e941e96caf630a6a | https://github.com/BeyonderXX/MINER/tree/552049139cc61dec8fba19f1e941e96caf630a6a |
MLP | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from abc import *
from torch.... | ramanuzan/JORLDY | MLP | false | 12,939 | [
"Apache-2.0"
] | 0 | be371ad0607e5dba5d5082101c38c6a9f2c96767 | https://github.com/ramanuzan/JORLDY/tree/be371ad0607e5dba5d5082101c38c6a9f2c96767 |
MaskedInstanceNorm1d | # 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
from torch import nn
import ... | Malkovsky/NeMo | MaskedInstanceNorm1d | false | 2,615 | [
"Apache-2.0"
] | 0 | 8cf9aad8ecba36f1bd7b096cf274c2bc8ac695c3 | https://github.com/Malkovsky/NeMo/tree/8cf9aad8ecba36f1bd7b096cf274c2bc8ac695c3 |
Attention | import torch
import torch.nn as nn
import torch.nn.functional as F
class Attention(nn.Module):
def __init__(self, image_features_dim, decoder_hidden_state_dim,
attention_dim):
super(Attention, self).__init__()
self.attention_dim = attention_dim
self.U = nn.Linear(in_features=image... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | ppujol76/-Pere_Transformers | Attention | false | 12,916 | [
"MIT"
] | 0 | e267bcc6559c998accaed647cacbff253031f8b0 | https://github.com/ppujol76/-Pere_Transformers/tree/e267bcc6559c998accaed647cacbff253031f8b0 |
SEModule | import torch
import torch.nn as nn
class SEModule(nn.Module):
def __init__(self, channels, reduction):
super(SEModule, self).__init__()
self.fc1 = nn.Conv2d(channels, channels // reduction, kernel_size=1,
padding=0)
self.relu = nn.ReLU(inplace=True)
self.fc2 = nn.Conv2... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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_... | amajidsinar/seer | SEModule | false | 1,426 | [
"Apache-2.0"
] | 0 | 35f25b3fbf22968f0b09c266b8fd66a44fcc4d9c | https://github.com/amajidsinar/seer/tree/35f25b3fbf22968f0b09c266b8fd66a44fcc4d9c |
DAInsHead | # 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 ... | Feobi1999/unbiased-teacher | DAInsHead | false | 2,254 | [
"MIT"
] | 0 | 9baacec16833bdff0dc089057e50903a92c700cb | https://github.com/Feobi1999/unbiased-teacher/tree/9baacec16833bdff0dc089057e50903a92c700cb |
SmallConvNet | # 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 typing import Tuple
import torch.nn as nn
from numpy import prod
assert_siz... | johnanthonyjose/fvcore | SmallConvNet | false | 15,725 | [
"Apache-2.0"
] | 1,137 | af30fd4028553c1d1e4e5d389f309f52e046e67d | https://github.com/johnanthonyjose/fvcore/tree/af30fd4028553c1d1e4e5d389f309f52e046e67d |
FusedUpsample | # 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
from math import sqrt
assert_size_stride = torch._C._dynamo... | uzielroy/StyleGan_FewShot | FusedUpsample | false | 16,645 | [
"MIT"
] | 76 | 94e4c49dbf39d1c6299f33787afb3e471ece11e3 | https://github.com/uzielroy/StyleGan_FewShot/tree/94e4c49dbf39d1c6299f33787afb3e471ece11e3 |
SimpleAttention | # 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.... | Anshul044/Project-NN | SimpleAttention | false | 60 | [
"MIT"
] | 0 | ef080846715a95b735f0381e4f60742e40791630 | https://github.com/Anshul044/Project-NN/tree/ef080846715a95b735f0381e4f60742e40791630 |
UpBlock2d | # 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.... | KangweiiLiu/Thin-Plate-Spline-Motion-Model | UpBlock2d | false | 5,433 | [
"MIT"
] | 1 | 0ec14f6c06f5beeef159340142ec5182a1be9bc7 | https://github.com/KangweiiLiu/Thin-Plate-Spline-Motion-Model/tree/0ec14f6c06f5beeef159340142ec5182a1be9bc7 |
Residual | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
class ConvBnRelu(nn.Module):
"""
A block of convolution, relu, batchnorm
"""
def __init__(self, in_channels, out_channels, kernel_size=1, stride=1,
pa... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | SkywalkerAtlas/HRGAN | Residual | false | 5,839 | [
"MIT"
] | 1 | bf6d58c1f3c6e042c7ea70319a25e3420531d552 | https://github.com/SkywalkerAtlas/HRGAN/tree/bf6d58c1f3c6e042c7ea70319a25e3420531d552 |
SparseConv2d | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import autograd
class Sparse(autograd.Function):
""""
Prune the unimprotant weight for the forwards phase,
but pass the gradient to dense weight using SR-STE in the backwards phase
"""
@staticmethod
def forward(ctx,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | Sense-GVT/BigPretrain | SparseConv2d | false | 17,920 | [
"Apache-2.0"
] | 8 | d8d9b43d94dd1364c18c1e5ba21b85a31cdbba9e | https://github.com/Sense-GVT/BigPretrain/tree/d8d9b43d94dd1364c18c1e5ba21b85a31cdbba9e |
Stalin3000_anal_probe | # 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 math import *
import tor... | skabrits/- | Stalin3000_anal_probe | false | 10,779 | [
"MIT"
] | 0 | 396ccb457f1f1048377be6a8b8f5e5cf060f9b0d | https://github.com/skabrits/-/tree/396ccb457f1f1048377be6a8b8f5e5cf060f9b0d |
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... | Akababa/torch2trt | Pow | false | 18,422 | [
"MIT"
] | 2 | 03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 | https://github.com/Akababa/torch2trt/tree/03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 |
GlobalAveragePooling | # 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... | ALISCIFP/mmpose | GlobalAveragePooling | false | 2,050 | [
"Apache-2.0"
] | 0 | 2433e3dbcc44baa2253e2a7c748ba0216937933e | https://github.com/ALISCIFP/mmpose/tree/2433e3dbcc44baa2253e2a7c748ba0216937933e |
TanhDeepLiftModel | import torch
import torch.nn as nn
class TanhDeepLiftModel(nn.Module):
"""
Same as the ReLUDeepLiftModel, but with activations
that can have negative outputs
"""
def __init__(self) ->None:
super().__init__()
self.tanh1 = nn.Tanh()
self.tanh2 = nn.Tanh()
def forward(se... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | LMdeLiangMi/captum | TanhDeepLiftModel | false | 5,474 | [
"BSD-3-Clause"
] | 1 | 8bd9686013fe0ba8996e9b1cbeb0ea8e91512787 | https://github.com/LMdeLiangMi/captum/tree/8bd9686013fe0ba8996e9b1cbeb0ea8e91512787 |
GE2ELoss | # 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.... | greenstar1151/pytorch-benchmark | GE2ELoss | false | 10,464 | [
"BSD-3-Clause"
] | 0 | 8b7808d3be6b7ca1d57f1812e35fd2df5e470f8b | https://github.com/greenstar1151/pytorch-benchmark/tree/8b7808d3be6b7ca1d57f1812e35fd2df5e470f8b |
Hsigmoid | import torch
from torch import nn
import torch.nn.functional as F
import torch.nn.parallel
class Hsigmoid(nn.Module):
def __init__(self, inplace=True):
super(Hsigmoid, self).__init__()
self.inplace = inplace
def forward(self, x):
return F.relu6(x + 3.0, inplace=self.inplace) / 6.0
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import torch.nn.parallel
assert_size_stride = torch._C._dynamo.guard... | EllisHui/outOfRailWay | Hsigmoid | false | 403 | [
"BSD-2-Clause"
] | 0 | e3bf9aaa18879bee5536740d55006c872f06278f | https://github.com/EllisHui/outOfRailWay/tree/e3bf9aaa18879bee5536740d55006c872f06278f |
MockOpposite | import torch
import torch.nn as nn
class MockOpposite(nn.Module):
def __init__(self):
"""Initialize the model"""
super(MockOpposite, self).__init__()
def forward(self, input):
"""A single forward pass of the model. Returns input - 1.
Args:
input: The input to the... | 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... | blagojce95/ai-research-mamo-framework | MockOpposite | false | 1,552 | [
"Apache-2.0"
] | 0 | 7f3b5a5a9fb8b19c9eef453b81b03b6046a33bf2 | https://github.com/blagojce95/ai-research-mamo-framework/tree/7f3b5a5a9fb8b19c9eef453b81b03b6046a33bf2 |
PositionwiseFeedForward | import torch
from torch import nn
from torchvision import models as models
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
from torchvision.transforms import *
import torch.onnx
class Identity(nn.Module):
def forward(self, input_):
return input_
c... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | aalborov/openvino_training_extensions | PositionwiseFeedForward | false | 6,057 | [
"Apache-2.0"
] | 1 | a0bb39424151a98e1ca80c4aa5c865636d401785 | https://github.com/aalborov/openvino_training_extensions/tree/a0bb39424151a98e1ca80c4aa5c865636d401785 |
BBoxTransform | import torch
import torch.nn as nn
class BBoxTransform(nn.Module):
def forward(self, anchors, regression):
"""
decode_box_outputs adapted from https://github.com/google/automl/blob/master/efficientdet/anchors.py
Args:
anchors: [batchsize, boxes, (y1, x1, y2, x2)]
... | 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... | DerryHub/the-TaobaoLive-Commodity-Identify-Competition | BBoxTransform | false | 17,283 | [
"MIT"
] | 4 | 7e5e5c4fbddd9949fe01810d58bd7994889c007c | https://github.com/DerryHub/the-TaobaoLive-Commodity-Identify-Competition/tree/7e5e5c4fbddd9949fe01810d58bd7994889c007c |
ClassificationModel | import torch
import torch.nn as nn
import torch.utils.data.distributed
class ClassificationModel(nn.Module):
def __init__(self, num_features_in, num_anchors=1, num_classes=80,
prior=0.01, feature_size=256):
super(ClassificationModel, self).__init__()
self.num_classes = num_classes
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | YuBeomGon/pytorch_retina | ClassificationModel | false | 1,285 | [
"Apache-2.0"
] | 0 | a1713ecbf99e3cf2f8f5edce3329b808b4f9dee8 | https://github.com/YuBeomGon/pytorch_retina/tree/a1713ecbf99e3cf2f8f5edce3329b808b4f9dee8 |
DenseCrossEntropy | # 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
... | LichenYang-Jeffrey/DCL-with-Efficient-B7 | DenseCrossEntropy | false | 17,569 | [
"MIT"
] | 4 | 84940c96a8c7926c630a7a6d5bfd5c6e52a57c2e | https://github.com/LichenYang-Jeffrey/DCL-with-Efficient-B7/tree/84940c96a8c7926c630a7a6d5bfd5c6e52a57c2e |
MaxPool2dDynamicSamePadding | import math
import torch
from torch import nn
import torch.nn.functional as F
class MaxPool2dDynamicSamePadding(nn.MaxPool2d):
"""2D MaxPooling like TensorFlow's 'SAME' mode, with a dynamic image size.
The padding is operated in forward function by calculating dynamically.
"""
def __init__(self, k... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | AustinCai/gmaxup-augmentation | MaxPool2dDynamicSamePadding | false | 72 | [
"MIT"
] | 0 | a64ca0a76eb333e5ce6b217c301d27ca04d73bce | https://github.com/AustinCai/gmaxup-augmentation/tree/a64ca0a76eb333e5ce6b217c301d27ca04d73bce |
Maxout | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | demdecuong/SEGMENT | Maxout | false | 1,821 | [
"MIT"
] | 0 | 629dc55dcbc9629b35fb237e313b95ceacecdc89 | https://github.com/demdecuong/SEGMENT/tree/629dc55dcbc9629b35fb237e313b95ceacecdc89 |
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