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 |
|---|---|---|---|---|---|---|---|---|---|---|
UpBlok | import torch
from torch import nn
import torch.nn.functional as F
class UpBlok(nn.Module):
def __init__(self, in_channels, out_channels):
super().__init__()
self.conv1x1 = nn.Conv2d(in_channels, out_channels, kernel_size=1,
stride=1, padding=0)
self.conv3x3 = nn.Conv2d(out_cha... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | robtu328/TextBPN | UpBlok | false | 16,338 | [
"MIT"
] | 49 | 225844770e0107817be9fb86d53f873fa3eb07ae | https://github.com/robtu328/TextBPN/tree/225844770e0107817be9fb86d53f873fa3eb07ae |
ODEfunc | import torch
import torch.nn as nn
def norm(dim):
return nn.GroupNorm(min(32, dim), dim)
class ConcatConv2d(nn.Module):
def __init__(self, dim_in, dim_out, ksize=3, stride=1, padding=0,
dilation=1, groups=1, bias=True, transpose=False):
super(ConcatConv2d, self).__init__()
module = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | TylerChoi1224/torchdiffeq | ODEfunc | false | 1,191 | [
"MIT"
] | 0 | 72f74d9651a58ab11cdadd60682f1b61e625ef53 | https://github.com/TylerChoi1224/torchdiffeq/tree/72f74d9651a58ab11cdadd60682f1b61e625ef53 |
KDLoss | import torch
import torch.nn.functional as F
import torch.nn as nn
class KDLoss(nn.Module):
"""Knowledge Distillation Loss"""
def __init__(self, T):
super().__init__()
self.t = T
def forward(self, stu_pred, tea_pred):
s = F.log_softmax(stu_pred / self.t, dim=1)
t = F.soft... | 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... | LANCEREN/simpleAICV-pytorch-ImageNet-COCO-training | KDLoss | false | 13,974 | [
"MIT"
] | 154 | 86c1b38df3cdcb195ec5b6229c343f07a52aeb7b | https://github.com/LANCEREN/simpleAICV-pytorch-ImageNet-COCO-training/tree/86c1b38df3cdcb195ec5b6229c343f07a52aeb7b |
KernelSharedTensorTrain | import torch
from torch import nn
from torch.nn import Parameter
class KernelSharedTensorTrain(nn.Module):
def __init__(self, first_rank, m, second_rank, init_value):
super(KernelSharedTensorTrain, self).__init__()
self.first_rank = first_rank
self.m = m
self.second_rank = second_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
from torch.nn import Parameter
assert_size_stride = torch._... | AndresOtero/TensorDecompositionMachineLearning | KernelSharedTensorTrain | false | 16,912 | [
"MIT"
] | 3 | 455f16b405ec9d031999b0ebf9c5a68d3c20b233 | https://github.com/AndresOtero/TensorDecompositionMachineLearning/tree/455f16b405ec9d031999b0ebf9c5a68d3c20b233 |
AddAndNorm | import torch
import torch.nn as nn
class AddAndNorm(nn.Module):
def __init__(self, d_model):
super(AddAndNorm, self).__init__()
self.layer_norm = nn.LayerNorm(d_model)
def forward(self, x, residual):
return self.layer_norm(x + residual)
def get_inputs():
return [torch.rand([4, ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | francismontalbo/attention-is-all-you-need-paper | AddAndNorm | false | 15,365 | [
"MIT"
] | 167 | 21ba3e48917da0c6808126d183bece6a9969cfd2 | https://github.com/francismontalbo/attention-is-all-you-need-paper/tree/21ba3e48917da0c6808126d183bece6a9969cfd2 |
SmoothnessLoss | # 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... | hologerry/DewarpNet | SmoothnessLoss | false | 3,617 | [
"MIT"
] | 0 | b0a11b9fbb98bd124e65d3165ce177d9ebf2e836 | https://github.com/hologerry/DewarpNet/tree/b0a11b9fbb98bd124e65d3165ce177d9ebf2e836 |
FocalLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
def focal_loss(input_values, gamma=10):
"""Computes the focal loss"""
p = torch.exp(-input_values)
loss = (1 - p) ** gamma * input_values
return loss.mean()
class FocalLoss(nn.Module):
def __init__(self, weight=None, gamma=0.5):... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | naver-ai/cgl_fairness | FocalLoss | false | 7,317 | [
"MIT"
] | 1 | 00d3bec233c9b3e0f88496118abaed8321ca3159 | https://github.com/naver-ai/cgl_fairness/tree/00d3bec233c9b3e0f88496118abaed8321ca3159 |
NPairLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_s... | bm2-lab/MDML | NPairLoss | false | 1,586 | [
"MIT"
] | 0 | 222fb22b2ee53dd3c1a6f2e99a88f71e9635e3a0 | https://github.com/bm2-lab/MDML/tree/222fb22b2ee53dd3c1a6f2e99a88f71e9635e3a0 |
RQLoss | # 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.... | ethanwhite/torchgeo | RQLoss | false | 15,315 | [
"MIT"
] | 678 | cb20e1abfd9213f9ee7700df972385db13568642 | https://github.com/ethanwhite/torchgeo/tree/cb20e1abfd9213f9ee7700df972385db13568642 |
DisaggregatedPinballLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | FedericoGarza/esrnn_torch | DisaggregatedPinballLoss | false | 11,423 | [
"MIT"
] | 0 | 9f28f38e27dc0ba12cc965e60f7e08e635c8b19d | https://github.com/FedericoGarza/esrnn_torch/tree/9f28f38e27dc0ba12cc965e60f7e08e635c8b19d |
BertSelfAttention | from _paritybench_helpers import _mock_config
import math
import torch
import torch.nn as nn
import torch.utils.data
class BertSelfAttention(nn.Module):
def __init__(self, config):
super(BertSelfAttention, self).__init__()
if config.hidden_size % config.num_attention_heads != 0:
raise... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | ashutoshbaghel/tgifqa-lxmert | BertSelfAttention | false | 1,497 | [
"MIT"
] | 0 | 7969f478d20fbfbba1c0eaaf0b96891654bfcc26 | https://github.com/ashutoshbaghel/tgifqa-lxmert/tree/7969f478d20fbfbba1c0eaaf0b96891654bfcc26 |
MaskNet | # 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_... | DongChengdongHangZhou/adversarial-attack-iris | MaskNet | false | 11,415 | [
"Apache-2.0"
] | 0 | ae7e408c47c332fc876d572acd4701e4b8970487 | https://github.com/DongChengdongHangZhou/adversarial-attack-iris/tree/ae7e408c47c332fc876d572acd4701e4b8970487 |
Clump | import torch
from torch import nn
class Clump(nn.Module):
"""Clipping input tensor."""
def __init__(self, min_v: 'int'=-50, max_v: 'int'=50):
"""Class for preparing input for DL model with mixed data.
Args:
min_v: Min value.
max_v: Max value.
"""
supe... | 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... | Andrey-Nikitin/LightAutoML | Clump | false | 4,840 | [
"Apache-2.0"
] | 1 | fe58d98d1ab05e177f0b9dea918fef8b922ae922 | https://github.com/Andrey-Nikitin/LightAutoML/tree/fe58d98d1ab05e177f0b9dea918fef8b922ae922 |
AvgPoolHead | # 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.optim
assert_size_stride = torch._C._dynamo.g... | KGMSFT/integral-human-pose | AvgPoolHead | false | 13,917 | [
"MIT"
] | 472 | d3ad4117ed71c580d2ab17987e15f9b2c3318a3b | https://github.com/KGMSFT/integral-human-pose/tree/d3ad4117ed71c580d2ab17987e15f9b2c3318a3b |
WeightedMCEloss | # 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 | WeightedMCEloss | false | 5,300 | [
"MIT"
] | 1 | faa9b7850fe2a0f8c08193bb129b5fec4639d616 | https://github.com/HelenGuohx/cv-ferattn-code/tree/faa9b7850fe2a0f8c08193bb129b5fec4639d616 |
FocalLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.cuda
import torch.distributed
import torch.multiprocessing
class FocalLoss(nn.Module):
"""Focal Loss - https://arxiv.org/abs/1708.02002"""
def __init__(self, alpha=0.25, gamma=2):
super().__init__()
self.alpha = a... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | Mo5mami/retinanet-examples | FocalLoss | false | 14,053 | [
"BSD-3-Clause"
] | 848 | f7ad4ff6a99fe3e66f8a9c8e8a6e03b870f84700 | https://github.com/Mo5mami/retinanet-examples/tree/f7ad4ff6a99fe3e66f8a9c8e8a6e03b870f84700 |
Sum | import torch
import torch.nn as nn
class Sum(nn.Module):
def __init__(self, n, weight=False):
super().__init__()
self.weight = weight
self.iter = range(n - 1)
if weight:
self.w = nn.Parameter(-torch.arange(1.0, n) / 2, requires_grad=True
)
def forw... | 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... | Aditya239233/MDP | Sum | false | 16,904 | [
"MIT"
] | 4 | 87491e1d67e547c11f4bdd5d784d120473429eae | https://github.com/Aditya239233/MDP/tree/87491e1d67e547c11f4bdd5d784d120473429eae |
PreActBlock | import torch
import torch.nn as nn
import torch.nn.functional as F
class PreActBlock(nn.Module):
"""Pre-activation version of the BasicBlock."""
expansion = 1
def __init__(self, in_planes, planes, num_group=4, stride=1, bias=False):
super(PreActBlock, self).__init__()
self.conv1 = nn.Conv... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | cwmok/LapIRN | PreActBlock | false | 15,095 | [
"MIT"
] | 53 | d8f96770a704b1f190955cc26297c7b01a270b0a | https://github.com/cwmok/LapIRN/tree/d8f96770a704b1f190955cc26297c7b01a270b0a |
Triaffine | import torch
import torch.nn as nn
class Triaffine(nn.Module):
"""
Triaffine layer for second-order scoring.
This function has a tensor of weights `W` and bias terms if needed.
The score `s(x, y, z)` of the vector triple `(x, y, z)` is computed as `x^T z^T W y`.
Usually, `x` and `y` can be concat... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | matejklemen/morphological-dependency-parsing | Triaffine | false | 3,981 | [
"MIT"
] | 0 | 2ab24b8621debe6e3288ade01c9604a06f9bd453 | https://github.com/matejklemen/morphological-dependency-parsing/tree/2ab24b8621debe6e3288ade01c9604a06f9bd453 |
TensorExp | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_str... | Minyus/kedex | TensorExp | false | 9,683 | [
"Apache-2.0"
] | 0 | 92f952eed3cb6109bc783f449051f2bd13579d2a | https://github.com/Minyus/kedex/tree/92f952eed3cb6109bc783f449051f2bd13579d2a |
GatedConv2d | # 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... | davidreiman/nsf | GatedConv2d | false | 15,136 | [
"MIT"
] | 231 | ed70316c3bf1acd4ffdf309f1773172c34e48320 | https://github.com/davidreiman/nsf/tree/ed70316c3bf1acd4ffdf309f1773172c34e48320 |
GeM | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.functional
from torch.nn import Parameter
from torch.nn.parameter import Parameter
import torch.nn.parallel
import torch.utils.data
import torch.optim
import torch.utils.data.distributed
import torch.autograd
class GeM(nn.Module):
... | 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... | Liuhongzhi2018/Person_ReID | GeM | false | 2,552 | [
"MIT"
] | 0 | 51c576ed5b4ed960801669d6d59c0a77405b369d | https://github.com/Liuhongzhi2018/Person_ReID/tree/51c576ed5b4ed960801669d6d59c0a77405b369d |
PixelDynamicsLoss | # 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
a... | CompVis/interactive-image2video-synthesis | PixelDynamicsLoss | false | 7,921 | [
"MIT"
] | 20 | 05ea449d3a2704b6d79a5f08683035220d615576 | https://github.com/CompVis/interactive-image2video-synthesis/tree/05ea449d3a2704b6d79a5f08683035220d615576 |
MSE_loss | import torch
import torch.nn as nn
import torch.utils.data
import torch.optim
class MSE_loss(nn.Module):
def __init__(self):
super(MSE_loss, self).__init__()
def forward(self, prediction, gt, epoch=0):
err = prediction[:, 0:1] - gt
mask = (gt > 0).detach()
mse_loss = torch.me... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
import torch.optim
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strid... | alopezgit/project-adapt | MSE_loss | false | 18,303 | [
"MIT"
] | 8 | e93ab350344a5504f76f4e460002e0163996f88a | https://github.com/alopezgit/project-adapt/tree/e93ab350344a5504f76f4e460002e0163996f88a |
PoolReducer | # 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... | Dreem-Organization/RobustSleepNet | PoolReducer | false | 7,994 | [
"MIT"
] | 16 | c8ff3f6f857299eb2bf2e9400483084d5ecd4106 | https://github.com/Dreem-Organization/RobustSleepNet/tree/c8ff3f6f857299eb2bf2e9400483084d5ecd4106 |
Qnet | # 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 random
import torch.nn... | shwetasrsh/minimalRL | Qnet | false | 12,981 | [
"MIT"
] | 0 | e6fef1730238dd268b1a43fd9fca0b0c40d97837 | https://github.com/shwetasrsh/minimalRL/tree/e6fef1730238dd268b1a43fd9fca0b0c40d97837 |
AddNorm | # 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.functional as F
import torch.nn as nn
assert_size_stride = torc... | JustinNeumann/pytorch-forecasting | AddNorm | false | 705 | [
"MIT"
] | 0 | 4f6e449cb3788b856e66c4283398a5db201aa6ff | https://github.com/JustinNeumann/pytorch-forecasting/tree/4f6e449cb3788b856e66c4283398a5db201aa6ff |
GlobalAttentionGeneral | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.onnx
def conv1x1(in_planes, out_planes, bias=False):
"""1x1 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=1, stride=1,
padding=0, bias=bias)
class GlobalAttentionGeneral(nn.Module):
def __... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Amritds/AttnGAN | GlobalAttentionGeneral | false | 11,261 | [
"MIT"
] | 0 | 806ae70142a699bfe384c4964be2f7fce2b83d29 | https://github.com/Amritds/AttnGAN/tree/806ae70142a699bfe384c4964be2f7fce2b83d29 |
PartialConv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from itertools import product as product
import torch.nn as nn
asser... | TaroNakasendo/MaskEraser | PartialConv | false | 17,981 | [
"MIT"
] | 3 | 373af686194aff716f53785e40252beae7b26cff | https://github.com/TaroNakasendo/MaskEraser/tree/373af686194aff716f53785e40252beae7b26cff |
h_sigmoid | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | Felicia980317/mytorch | h_sigmoid | false | 443 | [
"Apache-2.0"
] | 0 | e463122c0d402878ec5b4c5a823a0feeba8fdbfe | https://github.com/Felicia980317/mytorch/tree/e463122c0d402878ec5b4c5a823a0feeba8fdbfe |
L1Loss | # 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
... | ALISCIFP/mmpose | L1Loss | false | 2,070 | [
"Apache-2.0"
] | 0 | 2433e3dbcc44baa2253e2a7c748ba0216937933e | https://github.com/ALISCIFP/mmpose/tree/2433e3dbcc44baa2253e2a7c748ba0216937933e |
DoubleConv | # 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_... | Aoi-hosizora/UNet-pytorch | DoubleConv | false | 8,847 | [
"MIT"
] | 0 | 96951d5d1fdc6c6266a11e1bd97fbf72010bc87d | https://github.com/Aoi-hosizora/UNet-pytorch/tree/96951d5d1fdc6c6266a11e1bd97fbf72010bc87d |
SACQ | # 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_... | Purple-PI/rlstructures | SACQ | false | 14,257 | [
"MIT"
] | 281 | 9b201b083715bbda2f3534b010c84e11dfc0a1c7 | https://github.com/Purple-PI/rlstructures/tree/9b201b083715bbda2f3534b010c84e11dfc0a1c7 |
GlobalLayerNorm | # 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
from itertools import product as product
assert_size_stri... | TaoRuijie/TalkNet_ASD | GlobalLayerNorm | false | 14,461 | [
"MIT"
] | 79 | 4a2bc4859ee192ab450eaf63937a799212f2b021 | https://github.com/TaoRuijie/TalkNet_ASD/tree/4a2bc4859ee192ab450eaf63937a799212f2b021 |
FiLMLayerEqualFC | # 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 math
i... | justinjohn0306/CIPS-3D | FiLMLayerEqualFC | false | 7,006 | [
"MIT"
] | 1 | 69a910a7841846419a6b5e03182c8cf061a82584 | https://github.com/justinjohn0306/CIPS-3D/tree/69a910a7841846419a6b5e03182c8cf061a82584 |
ImagenetNorm | import torch
import torch.nn as nn
class ImagenetNorm(nn.Module):
def __init__(self, from_raw=True):
"""
:param from_raw: whether the input image lies in the range of [0, 255]
"""
super().__init__()
self.from_raw = from_raw
self.mean = nn.Parameter(torch.tensor([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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | jokingbear/DM | ImagenetNorm | false | 6,975 | [
"MIT"
] | 1 | 9c4dada1756f3d866455a397511d4f3bacfadc60 | https://github.com/jokingbear/DM/tree/9c4dada1756f3d866455a397511d4f3bacfadc60 |
affinity_loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | cj4L/DeepCO3-python | affinity_loss | false | 6,453 | [
"MIT"
] | 1 | fa28ed7b43a3a236d0cc7bf31ce9fd68c01b5888 | https://github.com/cj4L/DeepCO3-python/tree/fa28ed7b43a3a236d0cc7bf31ce9fd68c01b5888 |
TemporallyBatchedAdditiveAttention | # 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.... | fireofearth/Trajectron-plus-plus | TemporallyBatchedAdditiveAttention | false | 3,510 | [
"MIT"
] | 0 | b39df025b62a8ce466266936198baee9bfa14e89 | https://github.com/fireofearth/Trajectron-plus-plus/tree/b39df025b62a8ce466266936198baee9bfa14e89 |
CombinedTargetMSELoss | import torch
import torch.nn as nn
class CombinedTargetMSELoss(nn.Module):
"""MSE loss for combined target.
CombinedTarget: The combination of classification target
(response map) and regression target (offset map).
Paper ref: Huang et al. The Devil is in the Details: Delving into
... | 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... | Jackqu/mmpose | CombinedTargetMSELoss | false | 8,341 | [
"Apache-2.0"
] | 38 | ad8acc5ff5da7993c6befdc4b1ced2c2ecb64533 | https://github.com/Jackqu/mmpose/tree/ad8acc5ff5da7993c6befdc4b1ced2c2ecb64533 |
SmallMnist | # 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.... | Rohan-Chaudhury/aimet | SmallMnist | false | 17,953 | [
"BSD-3-Clause"
] | 3 | 1c38cac8cc0fd32dca40ce5e39940805d29f7a4a | https://github.com/Rohan-Chaudhury/aimet/tree/1c38cac8cc0fd32dca40ce5e39940805d29f7a4a |
FiLMLayer | import torch
import torch.nn as nn
class FiLMLayer(nn.Module):
def __init__(self, input_dim, hidden_dim):
super().__init__()
self.layer = nn.Linear(input_dim, hidden_dim)
def forward(self, x, freq, phase_shift):
x = self.layer(x)
freq = freq.unsqueeze(1).expand_as(x)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | justinjohn0306/CIPS-3D | FiLMLayer | false | 7,003 | [
"MIT"
] | 1 | 69a910a7841846419a6b5e03182c8cf061a82584 | https://github.com/justinjohn0306/CIPS-3D/tree/69a910a7841846419a6b5e03182c8cf061a82584 |
Attn | import torch
from torch import nn
class Attn(torch.nn.Module):
"""
Attention:
feature_dim: dimension of feature embedding
method: method to calculate attention, (general, dot, concat)
input_dim: dimension of input embedding, default is the same as feature_dim; method dot is only availa... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | stillarrow/NRT-Lite | Attn | false | 4,389 | [
"MIT"
] | 0 | ba0f091ebfeae19325ce713e11bc426ff63402cd | https://github.com/stillarrow/NRT-Lite/tree/ba0f091ebfeae19325ce713e11bc426ff63402cd |
CustomKLDivLoss | import torch
from torch import Tensor
from torch.nn import functional as F
class CustomKLDivLoss(torch.nn.Module):
def __init__(self, reduction='batchmean', log_target=False,
apply_softmax=True) ->None:
super(CustomKLDivLoss, self).__init__()
self.reduction = reduction
self.log_ta... | 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
assert_size... | PiaCuk/KD_Lib | CustomKLDivLoss | false | 14,233 | [
"MIT"
] | 360 | 153299d484e4c6b33793749709dbb0f33419f190 | https://github.com/PiaCuk/KD_Lib/tree/153299d484e4c6b33793749709dbb0f33419f190 |
T5LayerNorm | # 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
import torch.utils.checkpoint
assert_size_stride = torch.... | longquan0609/bert_seq2seq | T5LayerNorm | false | 12,825 | [
"Apache-2.0"
] | 0 | 3aaeb2ea76cd435d53ebcfedd2a080d0c37c1976 | https://github.com/longquan0609/bert_seq2seq/tree/3aaeb2ea76cd435d53ebcfedd2a080d0c37c1976 |
Combiner | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
im... | autodidact-m/Projects | Combiner | false | 3,145 | [
"Apache-2.0"
] | 0 | f4c0473adba42f3a629b62eb09d3b1df91982f46 | https://github.com/autodidact-m/Projects/tree/f4c0473adba42f3a629b62eb09d3b1df91982f46 |
RobertaClassificationHead | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from ty... | nateanl/text | RobertaClassificationHead | false | 16,141 | [
"BSD-3-Clause"
] | 3,172 | b26e9350ad387a84aefe131443bbbf1c51a8a618 | https://github.com/nateanl/text/tree/b26e9350ad387a84aefe131443bbbf1c51a8a618 |
Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | MonteYang/P1_Facial_Keypoints | Net | false | 11,740 | [
"MIT"
] | 0 | 1e3e4c9c6b48ec241f6fc7e072b25c7211cebd18 | https://github.com/MonteYang/P1_Facial_Keypoints/tree/1e3e4c9c6b48ec241f6fc7e072b25c7211cebd18 |
OhemLoss | # 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... | suifengwangshi/MotifC | OhemLoss | false | 4,383 | [
"Apache-2.0"
] | 0 | 34117a6bfb7dacd5a84da3abd5b8a339ae73cc76 | https://github.com/suifengwangshi/MotifC/tree/34117a6bfb7dacd5a84da3abd5b8a339ae73cc76 |
AutoregressiveShift | import torch
import torch.nn as nn
class AutoregressiveShift(nn.Module):
"""Shifts input right to make model autoregressive."""
def __init__(self, embed_dim):
super(AutoregressiveShift, self).__init__()
self.embed_dim = embed_dim
self.first_token = nn.Parameter(torch.Tensor(1, 1, embe... | 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... | alisiahkoohi/survae_flows | AutoregressiveShift | false | 14,785 | [
"MIT"
] | 262 | e1747b05524c7ab540a211ed360ab3e67bc3e96d | https://github.com/alisiahkoohi/survae_flows/tree/e1747b05524c7ab540a211ed360ab3e67bc3e96d |
InnerProductDecoder | import torch
import torch.nn as nn
import torch.nn.functional as F
class InnerProductDecoder(nn.Module):
def __init__(self, activation=torch.sigmoid, dropout=0.1):
super().__init__()
self.dropout = dropout
self.activation = activation
def forward(self, z):
z = F.dropout(z, se... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | leiyu-thunder/gae_dgl | InnerProductDecoder | false | 7,069 | [
"Apache-2.0"
] | 1 | c743acc96e24c4ca3ae72d08956381f302b373bd | https://github.com/leiyu-thunder/gae_dgl/tree/c743acc96e24c4ca3ae72d08956381f302b373bd |
InformedSender | # 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.... | Slowika/GameBias-EmeCom2020 | InformedSender | false | 17,968 | [
"MIT"
] | 5 | 5b94c47559f8202bca99c26fc1bcb078dd0509a6 | https://github.com/Slowika/GameBias-EmeCom2020/tree/5b94c47559f8202bca99c26fc1bcb078dd0509a6 |
DotProduct | # 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.... | EGO4D/episodic-memory | DotProduct | false | 8,053 | [
"MIT"
] | 27 | 2a3464882cd4f665c358c1b05a6397339e33c2e1 | https://github.com/EGO4D/episodic-memory/tree/2a3464882cd4f665c358c1b05a6397339e33c2e1 |
ComplexRotationComposition | import torch
from torch import nn
from abc import abstractmethod
import torch.utils.data
def _to_complex(x: 'torch.Tensor') ->torch.Tensor:
"""View real tensor as complex."""
return torch.view_as_complex(x.view(*x.shape[:-1], -1, 2))
def _to_real(x: 'torch.Tensor') ->torch.Tensor:
"""View complex tensor... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
from abc import abstractmethod
import torch.utils.data
assert_size_s... | DimitrisAlivas/StarQE | ComplexRotationComposition | false | 7,969 | [
"MIT"
] | 11 | c17676e5f1e3f19c0c4c117a50abe2ce22ffef28 | https://github.com/DimitrisAlivas/StarQE/tree/c17676e5f1e3f19c0c4c117a50abe2ce22ffef28 |
DenseSAGEConv | # 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
from torch.nn imp... | rbshi/pytorch_geometric | DenseSAGEConv | false | 4,180 | [
"MIT"
] | 0 | fcfbad49219974689eb5c6e32365939ae09ace84 | https://github.com/rbshi/pytorch_geometric/tree/fcfbad49219974689eb5c6e32365939ae09ace84 |
std_norm | # 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... | DandilionLau/Visually-Imbalanced-Stereo | std_norm | false | 5,045 | [
"MIT"
] | 1 | e80b63be134c326f8a036db7af669a6b3b23ed24 | https://github.com/DandilionLau/Visually-Imbalanced-Stereo/tree/e80b63be134c326f8a036db7af669a6b3b23ed24 |
visual_context | import torch
import torch.nn as nn
import torch.utils.data
class visual_context(nn.Module):
def __init__(self):
super(visual_context, self).__init__()
self.AdaptiveAvgPool = nn.AdaptiveAvgPool2d((None, 1))
def forward(self, visual_feature):
visual_feature = self.AdaptiveAvgPool(visua... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | prabhatrmishra/IDCardInfoExtr | visual_context | false | 16,279 | [
"Apache-2.0"
] | 66 | c59270f61a3251a6aff55bc7d81f2057c4663a37 | https://github.com/prabhatrmishra/IDCardInfoExtr/tree/c59270f61a3251a6aff55bc7d81f2057c4663a37 |
BalancedL1Loss | # 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 functools
impor... | Fanzhongjie/ARFE | BalancedL1Loss | false | 435 | [
"Apache-2.0"
] | 0 | 4b96b8c5bc0895d3d30acec2a490f81a860fe860 | https://github.com/Fanzhongjie/ARFE/tree/4b96b8c5bc0895d3d30acec2a490f81a860fe860 |
FFModule | # 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 ... | wenjie-p/CAT | FFModule | false | 4,652 | [
"Apache-2.0"
] | 0 | 0e6904658dd3d14afe51faf1d0141ae95fef44e8 | https://github.com/wenjie-p/CAT/tree/0e6904658dd3d14afe51faf1d0141ae95fef44e8 |
RegressionModel | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | DerekGloudemans/temporary-repo | RegressionModel | false | 5,083 | [
"MIT"
] | 1 | f278e9c7c9c7c1f362a64aec492ddb8fb1f984ad | https://github.com/DerekGloudemans/temporary-repo/tree/f278e9c7c9c7c1f362a64aec492ddb8fb1f984ad |
mix_Linear | import torch
from torch import nn
def Binarize(tensor):
"""
Binarize function: binarize input tensors
Input:
tensor: the input tensor.
Output:
binarized: the binarized tensor.
"""
binarized = torch.where(tensor > 0, torch.ones_like(tensor, dtype=torch
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | snudatalab/SensiMix | mix_Linear | false | 12,995 | [
"Apache-2.0"
] | 0 | e5d790f48a96806e9ae01449bb4a66e8f09c4d3a | https://github.com/snudatalab/SensiMix/tree/e5d790f48a96806e9ae01449bb4a66e8f09c4d3a |
GeLU | import torch
import torch.nn as nn
import torch.nn.functional as F
class GeLU(nn.Module):
def __init__(self):
super().__init__()
def forward(self, x):
return 0.5 * x * (1 + F.tanh(0.7978845608 * (x + 0.044715 * x * x * x))
)
def get_inputs():
return [torch.rand([4, 4, 4, 4]... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | Blind-Aid/sentiment-discovery | GeLU | false | 13,397 | [
"BSD-3-Clause"
] | 1,093 | 081c7c855e00864b52e97cac0b0e097cc86d9731 | https://github.com/Blind-Aid/sentiment-discovery/tree/081c7c855e00864b52e97cac0b0e097cc86d9731 |
QuickGELU | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | CryhanFang/CLIP2Video | QuickGELU | false | 13,517 | [
"MIT"
] | 113 | e94131800a3a1434f6d00b89b7301d741db8ba06 | https://github.com/CryhanFang/CLIP2Video/tree/e94131800a3a1434f6d00b89b7301d741db8ba06 |
Critic | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | jinPrelude/ksp-ai | Critic | false | 12,616 | [
"MIT"
] | 0 | d8b235d1ef77afe413fbff2e859e1210330bde37 | https://github.com/jinPrelude/ksp-ai/tree/d8b235d1ef77afe413fbff2e859e1210330bde37 |
GateLayer | import torch
from torch import nn
class GateLayer(nn.Module):
def __init__(self, input_dim):
super(GateLayer, self).__init__()
self._norm_layer1 = nn.Linear(input_dim * 2, input_dim)
self._norm_layer2 = nn.Linear(input_dim, 1)
def forward(self, input1, input2):
norm_input = 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... | hcmus-nlp-chatbot/CRSLab | GateLayer | false | 15,499 | [
"MIT"
] | 315 | b3ab262a4ad93cbae98fe66541eb735377768a35 | https://github.com/hcmus-nlp-chatbot/CRSLab/tree/b3ab262a4ad93cbae98fe66541eb735377768a35 |
LinearCombine | import torch
import torch.nn as nn
import torch.nn.functional as F
class LinearCombine(nn.Module):
def __init__(self, layers_num, trainable=True, input_aware=False,
word_level=False):
super(LinearCombine, self).__init__()
self.input_aware = input_aware
self.word_level = word_level... | 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... | charliemorning/mlws | LinearCombine | false | 1,675 | [
"MIT"
] | 0 | 8e9bad59ca9f5e774cc1ae7fe454ff3b8a8e1784 | https://github.com/charliemorning/mlws/tree/8e9bad59ca9f5e774cc1ae7fe454ff3b8a8e1784 |
Downsample | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
reinterpret_tens... | JasonQSY/Associative3D | Downsample | false | 8,347 | [
"MIT"
] | 25 | c50818b593ec48c38ed7ee3e109c23531089da32 | https://github.com/JasonQSY/Associative3D/tree/c50818b593ec48c38ed7ee3e109c23531089da32 |
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.... | FilippoC/-deep-syntactic-dependency-parsing-release | ScaledDotProductAttention | false | 17,277 | [
"MIT"
] | 4 | 30e2571ea930c2fd81559f5a2a971e3738cc6d39 | https://github.com/FilippoC/-deep-syntactic-dependency-parsing-release/tree/30e2571ea930c2fd81559f5a2a971e3738cc6d39 |
SimpleStackModel | # 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.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guar... | geoffberry/glow | SimpleStackModel | false | 12,416 | [
"Apache-2.0"
] | 0 | 24b2827c830eb58af56a0704e899968026832e9c | https://github.com/geoffberry/glow/tree/24b2827c830eb58af56a0704e899968026832e9c |
LabelPredictor | # 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... | JasonQSY/Associative3D | LabelPredictor | false | 8,359 | [
"MIT"
] | 25 | c50818b593ec48c38ed7ee3e109c23531089da32 | https://github.com/JasonQSY/Associative3D/tree/c50818b593ec48c38ed7ee3e109c23531089da32 |
LFF | import torch
import numpy as np
from torch import nn
class SinActivation(nn.Module):
def __init__(self):
super(SinActivation, self).__init__()
def forward(self, x):
return torch.sin(x)
class ConLinear(nn.Module):
def __init__(self, ch_in, ch_out, is_first=False, bias=True):
su... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | Ugness/CIPS_SR | LFF | false | 14,539 | [
"MIT"
] | 172 | abce872f5bc1b84afb9634a7dd1991e8c74d7616 | https://github.com/Ugness/CIPS_SR/tree/abce872f5bc1b84afb9634a7dd1991e8c74d7616 |
NanoNet | import torch
from torch import nn
from torch.nn import functional as f
class NanoNet(nn.Module):
def __init__(self, dimension):
super().__init__()
self.conv1 = nn.Conv2d(1, 32, 3, padding=1)
self.conv2 = nn.Conv2d(32, 32, 3, padding=1)
self.conv3 = nn.Conv2d(32, 32, 3, padding=1)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | cmsflash/ocean-text | NanoNet | false | 9,972 | [
"MIT"
] | 0 | d2f98077cb5e6949aec87f88a369ba4c2e99d178 | https://github.com/cmsflash/ocean-text/tree/d2f98077cb5e6949aec87f88a369ba4c2e99d178 |
UpConcat2d | import torch
import torch.nn as nn
import torch.nn.functional as F
class UpConcat2d(nn.Module):
def __init__(self, in_channels_conv, out_channels_conv, scale_factor=2):
super(UpConcat2d, self).__init__()
self.in_channels_conv = in_channels_conv
self.out_channels_conv = out_channels_conv
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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_... | rinkwitz/Thesis_Semantic_Image_Segmentation_on_Satellite_Imagery_using_UNets | UpConcat2d | false | 7,560 | [
"MIT"
] | 1 | 75d3a4a536f6ef81fe0efd4f5fbba32b627a7472 | https://github.com/rinkwitz/Thesis_Semantic_Image_Segmentation_on_Satellite_Imagery_using_UNets/tree/75d3a4a536f6ef81fe0efd4f5fbba32b627a7472 |
CMVN | import torch
import torch.nn as nn
class CMVN(nn.Module):
__constants__ = ['mode', 'dim', 'eps']
def __init__(self, mode='global', dim=2, eps=1e-10):
super(CMVN, self).__init__()
if mode != 'global':
raise NotImplementedError(
'Only support global mean variance nor... | 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_... | chiluen/s3prl | CMVN | false | 1,688 | [
"Apache-2.0"
] | 0 | c81838f6414d3c4767de355144449e40f86c7066 | https://github.com/chiluen/s3prl/tree/c81838f6414d3c4767de355144449e40f86c7066 |
SelfAttention | # 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.... | fanyix/flownet2 | SelfAttention | false | 6,698 | [
"Apache-2.0"
] | 1 | 0643beef59eeaf4cf4907d0d51f486ffd713363f | https://github.com/fanyix/flownet2/tree/0643beef59eeaf4cf4907d0d51f486ffd713363f |
GCN | from torch.nn import Module
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
from torch.nn.modules.module import Module
import torch.optim
class GraphConvolution(Module):
"""
Simple GCN layer, similar to https://arxiv.org/abs/1609.02907
"""
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | Myeongchan-Kim/SVAMP | GCN | false | 5,628 | [
"MIT"
] | 1 | 9ff9ad471a61aa390199df4b99beb3b654f5c943 | https://github.com/Myeongchan-Kim/SVAMP/tree/9ff9ad471a61aa390199df4b99beb3b654f5c943 |
BertTextPooler | from _paritybench_helpers import _mock_config
import torch
from torch import nn
class BertTextPooler(nn.Module):
def __init__(self, config):
super(BertTextPooler, self).__init__()
self.dense = nn.Linear(config.hidden_size, config.bi_hidden_size)
self.activation = nn.ReLU()
def forwar... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | eaidova/lxmert | BertTextPooler | false | 1,866 | [
"MIT"
] | 0 | c74616907125242112c6ee5c516b54c250168e8b | https://github.com/eaidova/lxmert/tree/c74616907125242112c6ee5c516b54c250168e8b |
Residual_Covolution | # 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_... | SultanAbuGhazal/CGNet | Residual_Covolution | false | 1,098 | [
"MIT"
] | 0 | f10b976b984ba09be26b902ed4da97cd1311cf17 | https://github.com/SultanAbuGhazal/CGNet/tree/f10b976b984ba09be26b902ed4da97cd1311cf17 |
LogCoshWithIgnore | import torch
import torch.nn.functional
from torch import nn
class LogCoshWithIgnore(nn.Module):
def __init__(self, ignore_value, fraction: 'float'=1.0):
super().__init__()
self.ignore_value = ignore_value
self.fraction = fraction
def forward(self, output, target):
r = 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, math as tl_math
import torc... | drivendataorg/DrivenData-2021-Geopose-Solution | LogCoshWithIgnore | false | 6,603 | [
"MIT"
] | 1 | fc1dead0aeb1ade9e9d87b55f56e631c57e966a6 | https://github.com/drivendataorg/DrivenData-2021-Geopose-Solution/tree/fc1dead0aeb1ade9e9d87b55f56e631c57e966a6 |
DiscShiftLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | rivergold/mmediting | DiscShiftLoss | false | 7,561 | [
"Apache-2.0"
] | 1 | fd972635c48bb065db29d1b5090592a87c7263d2 | https://github.com/rivergold/mmediting/tree/fd972635c48bb065db29d1b5090592a87c7263d2 |
MLP | import torch
import torch.nn as nn
class MLP(nn.Module):
"""
Multi-Layer Perceptron network
"""
def __init__(self, obs_dim, dim_latent):
"""
Constructor
Args:
obs_dim: (int) dimension of observation
latent_dim: (int) dimension of output latent
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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_... | baihuaxie/drl-lib | MLP | false | 1,519 | [
"MIT"
] | 0 | 3ad344901c3bb59e0bc16bb70202d2cfd538fd77 | https://github.com/baihuaxie/drl-lib/tree/3ad344901c3bb59e0bc16bb70202d2cfd538fd77 |
UpSampleConv | import torch
import torch.nn as nn
class CustomConv2d(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, stride=1,
padding=None, bias=True, residual_init=True):
super(CustomConv2d, self).__init__()
self.residual_init = residual_init
if padding is None:
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | ChiragCD/NR-GAN | UpSampleConv | false | 13,485 | [
"MIT"
] | 54 | fc455c6219b09bc8bf605715504b78b2bb801e48 | https://github.com/ChiragCD/NR-GAN/tree/fc455c6219b09bc8bf605715504b78b2bb801e48 |
SentinelMBSI | import torch
from typing import *
class SentinelMBSI(torch.nn.Module):
def __init__(self, band_count):
super(SentinelMBSI, self).__init__()
self.no_weights = True
def forward(self, x):
self.red = x[:, 3:4, :, :]
self.green = x[:, 2:3, :, :]
return 2 * (self.red - self... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from typing import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | geotrellis/deeplab-nlcd | SentinelMBSI | false | 10,380 | [
"MIT"
] | 0 | 9444299597e1d1bc34ee187f2092890449c188be | https://github.com/geotrellis/deeplab-nlcd/tree/9444299597e1d1bc34ee187f2092890449c188be |
AdaptiveAvgMaxPool2d | # 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... | hfyer/NAIC2020_ReID_R1 | AdaptiveAvgMaxPool2d | false | 6,810 | [
"Apache-2.0"
] | 1 | 240f0c9f65e482e6b0090f01d9f9e3373a337033 | https://github.com/hfyer/NAIC2020_ReID_R1/tree/240f0c9f65e482e6b0090f01d9f9e3373a337033 |
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
from torch import nn
import t... | PredatorK9/GANwriting | Conv2dBlock | false | 9,420 | [
"MIT"
] | 0 | 246d7e87152c98f0c6af999d619dc51190fad8ae | https://github.com/PredatorK9/GANwriting/tree/246d7e87152c98f0c6af999d619dc51190fad8ae |
FocalLossSigmoid | # 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
... | No43problem/SSD_Pytorch | FocalLossSigmoid | false | 14,100 | [
"MIT"
] | 163 | ddc548824bffbc83b540a68b176ee0261b133ee0 | https://github.com/No43problem/SSD_Pytorch/tree/ddc548824bffbc83b540a68b176ee0261b133ee0 |
Hidden2Normal | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cu... | JosephGesnouin/Asymmetrical-Bi-RNNs-to-encode-pedestrian-trajectories | Hidden2Normal | false | 17,512 | [
"MIT"
] | 9 | 488924e938fc1674b5a0d2cb9f05178cad8de561 | https://github.com/JosephGesnouin/Asymmetrical-Bi-RNNs-to-encode-pedestrian-trajectories/tree/488924e938fc1674b5a0d2cb9f05178cad8de561 |
Rot180 | # 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... | IEM-Computer-Vision/kornia | Rot180 | false | 9,255 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | f98bd9a2158a6e59cda076d55d476acf13f4e0af | https://github.com/IEM-Computer-Vision/kornia/tree/f98bd9a2158a6e59cda076d55d476acf13f4e0af |
SelfAttention | import torch
import torch.nn.functional as F
import torch.nn as nn
class SelfAttention(nn.Module):
def __init__(self, input_size, heads, embed_size):
super().__init__()
self.input_size = input_size
self.heads = heads
self.emb_size = embed_size
self.tokeys = nn.Linear(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.... | johnson7788/pymarl2 | SelfAttention | false | 3,909 | [
"Apache-2.0"
] | 0 | 8ec3e58fc3325ae82165cae0a5ea8a391ce42bd5 | https://github.com/johnson7788/pymarl2/tree/8ec3e58fc3325ae82165cae0a5ea8a391ce42bd5 |
LinearDiag | import torch
import torch.nn as nn
class LinearDiag(nn.Module):
def __init__(self, num_features, bias=False):
super(LinearDiag, self).__init__()
weight = torch.FloatTensor(num_features).fill_(1)
self.weight = nn.Parameter(weight, requires_grad=True)
if bias:
bias = tor... | 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... | CSer-Tang-hao/FS-KTN | LinearDiag | false | 7,832 | [
"MIT"
] | 19 | 8e5b1637e0f86f9d29dad7ff740a9c7a4a292a74 | https://github.com/CSer-Tang-hao/FS-KTN/tree/8e5b1637e0f86f9d29dad7ff740a9c7a4a292a74 |
DisparityRegression | import torch
import torch.nn as nn
import torch.utils.data
class DisparityRegression(nn.Module):
def __init__(self, maxdisp, win_size):
super(DisparityRegression, self).__init__()
self.max_disp = maxdisp
self.win_size = win_size
def forward(self, x):
disp = torch.arange(0, se... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | SpadeLiu/Graft-PSMNet | DisparityRegression | false | 1,094 | [
"MIT"
] | 0 | 1f2950d5afd85237f8d3604caab20dd47a8c9889 | https://github.com/SpadeLiu/Graft-PSMNet/tree/1f2950d5afd85237f8d3604caab20dd47a8c9889 |
AdaIN | import torch
class AdaIN(torch.nn.Module):
def __init__(self, channels_in, channels_out, norm=True):
super(AdaIN, self).__init__()
self.channels_in = channels_in
self.channels_out = channels_out
self.norm = norm
self.affine_scale = torch.nn.Linear(channels_in, channels_out... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | pigunther/Self-Correction-Human-Parsing-Updated | AdaIN | false | 7,467 | [
"MIT"
] | 1 | 17331eaa5d6586a1ebb633eb61ed810d00d30a2f | https://github.com/pigunther/Self-Correction-Human-Parsing-Updated/tree/17331eaa5d6586a1ebb633eb61ed810d00d30a2f |
Correct | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.utils.data.distributed
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda ... | amitport/grace | Correct | false | 12,088 | [
"BSD-2-Clause"
] | 0 | b0e442057d2f36f09cd1817a4acb966c6b0b780f | https://github.com/amitport/grace/tree/b0e442057d2f36f09cd1817a4acb966c6b0b780f |
RegLoss | import torch
import torch.nn as nn
class RegLoss(nn.Module):
""" RegLoss, L2 regularization on model parameters
"""
def __init__(self):
super(RegLoss, self).__init__()
def forward(self, parameters):
reg_loss = None
for W in parameters:
if reg_loss is None:
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | Ahren09/RecBole | RegLoss | false | 1,950 | [
"MIT"
] | 0 | b3921818dfbc1b81f9eda8d5e9f05bc9d9114089 | https://github.com/Ahren09/RecBole/tree/b3921818dfbc1b81f9eda8d5e9f05bc9d9114089 |
LayoutNet | # 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_... | wellowdata/pytorch-layoutnet | LayoutNet | false | 16,857 | [
"MIT"
] | 155 | 3d4352f94ed00d3c37890e9119452811d4f0893f | https://github.com/wellowdata/pytorch-layoutnet/tree/3d4352f94ed00d3c37890e9119452811d4f0893f |
InputInjection | import torch
import torch.nn as nn
import torch._C
import torch.serialization
class InputInjection(nn.Module):
"""Downsampling module for CGNet."""
def __init__(self, num_downsampling):
super(InputInjection, self).__init__()
self.pool = nn.ModuleList()
for i in range(num_downsampling)... | 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._C
import torch.serialization
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strid... | Jun-jieChen/real-time-segmentation | InputInjection | false | 5,415 | [
"Apache-2.0"
] | 1 | 22d0cb1a8a0dfa3b38f25bcd05db15f345be291a | https://github.com/Jun-jieChen/real-time-segmentation/tree/22d0cb1a8a0dfa3b38f25bcd05db15f345be291a |
SimpleAvgPool2dModule | import torch
import torch.jit
import torch.nn.functional as F
import torch.onnx
import torch.nn
class SimpleAvgPool2dModule(torch.nn.Module):
def __init__(self, kernel_size, stride=None, padding=0):
super(SimpleAvgPool2dModule, self).__init__()
self.kernel_size = kernel_size
self.padding ... | 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... | mciprian13/glow | SimpleAvgPool2dModule | false | 3,997 | [
"Apache-2.0"
] | 0 | 90f88205d9bf8baff8df5bbda51c9d138e3e668b | https://github.com/mciprian13/glow/tree/90f88205d9bf8baff8df5bbda51c9d138e3e668b |
FC2 | # 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_... | Thibaud-Ardoin/Dial-a-Ride | FC2 | false | 5,888 | [
"MIT"
] | 1 | 7d9b3cd904d3194dccad31fec2533e2cf58cad0c | https://github.com/Thibaud-Ardoin/Dial-a-Ride/tree/7d9b3cd904d3194dccad31fec2533e2cf58cad0c |
Mod | import torch
class Mod(torch.nn.Module):
def __init__(self):
super(Mod, self).__init__()
def forward(self, x, y):
return 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
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | NVIDIA-AI-IOT-private/torch2trt | Mod | false | 10,520 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
VarianceNorm2d | import torch
import torch.nn as nn
class VarianceNorm2d(nn.Module):
def __init__(self, num_features, bias=False):
super().__init__()
self.num_features = num_features
self.bias = bias
self.alpha = nn.Parameter(torch.zeros(num_features))
self.alpha.data.normal_(1, 0.02)
... | 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_... | samsartor/score_sde | VarianceNorm2d | false | 7,601 | [
"Apache-2.0"
] | 1 | d25c8d092a68d643c796d771c55f80075aa041d1 | https://github.com/samsartor/score_sde/tree/d25c8d092a68d643c796d771c55f80075aa041d1 |
CrossEntropyLossOneHot | import torch
import torch.nn as nn
class CrossEntropyLossOneHot(nn.Module):
def __init__(self):
super(CrossEntropyLossOneHot, self).__init__()
self.log_softmax = nn.LogSoftmax(dim=-1)
def forward(self, preds, labels):
return torch.mean(torch.sum(-labels * self.log_softmax(preds), -1)... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | B0Qi/hualubei2020-callingsmoking | CrossEntropyLossOneHot | false | 7,738 | [
"MIT"
] | 27 | 73d1049d95554b5d669afa93132a0fce37461ff4 | https://github.com/B0Qi/hualubei2020-callingsmoking/tree/73d1049d95554b5d669afa93132a0fce37461ff4 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.