entry_point stringlengths 1 65 | original_triton_python_code stringlengths 208 619k | optimised_triton_code stringlengths 1.15k 275k | repo_name stringlengths 7 115 | module_name stringlengths 1 65 | synthetic bool 1
class | uuid int64 0 18.5k | licenses listlengths 1 6 | stars int64 0 19.8k | sha stringlengths 40 40 | repo_link stringlengths 72 180 |
|---|---|---|---|---|---|---|---|---|---|---|
EqualLinear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.a... | justinjohn0306/CIPS-3D | EqualLinear | false | 6,995 | [
"MIT"
] | 1 | 69a910a7841846419a6b5e03182c8cf061a82584 | https://github.com/justinjohn0306/CIPS-3D/tree/69a910a7841846419a6b5e03182c8cf061a82584 |
GlyphNet | import torch
from torch import nn
from torch.nn import functional as f
class GlyphNet(nn.Module):
def __init__(self, dimension):
super().__init__()
self.conv1 = nn.Conv2d(3, 32, 3, padding=1)
self.conv2 = nn.Conv2d(32, 32, 3, padding=1)
self.fc = nn.Linear(32, dimension)
n... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | cmsflash/ocean-text | GlyphNet | false | 9,971 | [
"MIT"
] | 0 | d2f98077cb5e6949aec87f88a369ba4c2e99d178 | https://github.com/cmsflash/ocean-text/tree/d2f98077cb5e6949aec87f88a369ba4c2e99d178 |
StdConv2d | import torch
from torch import nn
import torch.nn.functional as F
class StdConv2d(nn.Conv2d):
def forward(self, x):
w = self.weight
v, m = torch.var_mean(w, dim=[1, 2, 3], keepdim=True, unbiased=False)
w = (w - m) / torch.sqrt(v + 1e-10)
return F.conv2d(x, w, self.bias, self.strid... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | marekb-sci/kaggle_cassava | StdConv2d | false | 12,750 | [
"Apache-2.0"
] | 0 | 158d1e398e713381c889e071329b96b9c0ba98d2 | https://github.com/marekb-sci/kaggle_cassava/tree/158d1e398e713381c889e071329b96b9c0ba98d2 |
StyledResBlock | import math
import torch
from torch import nn
from torch.nn import functional as F
def make_kernel(k):
k = torch.tensor(k, dtype=torch.float32)
if k.ndim == 1:
k = k[None, :] * k[:, None]
k /= k.sum()
return k
def upfirdn2d_native(input, kernel, up_x, up_y, down_x, down_y, pad_x0,
pad_x1... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
from to... | mkleshchenok/dlcourse_2021_p1_final_project | StyledResBlock | false | 12,811 | [
"MIT"
] | 0 | 1dd4f2e3dccc4604aa98982bf9377273ab4783c1 | https://github.com/mkleshchenok/dlcourse_2021_p1_final_project/tree/1dd4f2e3dccc4604aa98982bf9377273ab4783c1 |
BertPredictionHeadTransform | from _paritybench_helpers import _mock_config
import math
import torch
import torch.nn as nn
def gelu(x):
"""Implementation of the gelu activation function.
For information: OpenAI GPT's gelu is slightly different (and gives slightly different results):
0.5 * x * (1 + torch.tanh(math.sqrt(2 / math... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import ... | minjoong507/Image-Captioning-Transformer | BertPredictionHeadTransform | false | 7,239 | [
"MIT"
] | 1 | 813060f0bb656e336154173f11e99a80362c8c2a | https://github.com/minjoong507/Image-Captioning-Transformer/tree/813060f0bb656e336154173f11e99a80362c8c2a |
KLDivergenceLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch.nn import Module
import torch.utils.data
import torch.nn.functional
... | techthiyanes/annotated_deep_learning_paper_implementations | KLDivergenceLoss | false | 16,632 | [
"MIT"
] | 3,714 | 8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 | https://github.com/techthiyanes/annotated_deep_learning_paper_implementations/tree/8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 |
convBlock_basic | # 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... | YacobBY/ICDAR2019-ArT-Recognition-Alchemy | convBlock_basic | false | 14,624 | [
"MIT"
] | 209 | 911c572c2aff4599a74b7974d46ef4cfb17078b9 | https://github.com/YacobBY/ICDAR2019-ArT-Recognition-Alchemy/tree/911c572c2aff4599a74b7974d46ef4cfb17078b9 |
ActorDiscrete | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | ikamensh/machin | ActorDiscrete | false | 6,859 | [
"MIT"
] | 1 | af7b423c47bc1412530cf6c96c11bd3af9b3e239 | https://github.com/ikamensh/machin/tree/af7b423c47bc1412530cf6c96c11bd3af9b3e239 |
MinElementwise | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | Akababa/torch2trt | MinElementwise | false | 18,418 | [
"MIT"
] | 2 | 03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 | https://github.com/Akababa/torch2trt/tree/03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 |
BinaryDiceLoss | import torch
import torch.nn as nn
class BinaryDiceLoss(nn.Module):
"""Dice loss of binary class
Args:
smooth: A float number to smooth loss, and avoid NaN error, default: 1
p: Denominator value: \\sum{x^p} + \\sum{y^p}, default: 2
predict: A tensor of shape [N, *]
target: A te... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | cnuzh/CSNet | BinaryDiceLoss | false | 6,463 | [
"MIT"
] | 1 | a6c3163624f55dc294ec2e5a6de020d77bd4ff91 | https://github.com/cnuzh/CSNet/tree/a6c3163624f55dc294ec2e5a6de020d77bd4ff91 |
_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
import math
import torch.jit
import torch.nn.functional
import... | leoil/nequip | _ShiftedSoftPlus | false | 7,077 | [
"MIT"
] | 1 | 83b888797025c94b9963a508bc213a7c98da5bcb | https://github.com/leoil/nequip/tree/83b888797025c94b9963a508bc213a7c98da5bcb |
ComponentConditionBlock | import torch
import torch.nn as nn
import torch.utils.data.distributed
class ComponentConditionBlock(nn.Module):
def __init__(self, in_shape, n_comps):
super().__init__()
self.in_shape = in_shape
self.bias = nn.Parameter(torch.zeros(n_comps, in_shape[0], 1, 1),
requires_grad=T... | 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.distributed
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda... | Johnson-yue/lffont | ComponentConditionBlock | false | 13,903 | [
"MIT"
] | 98 | f31f5a1cd6a075449a0f18aaafd945d373121e15 | https://github.com/Johnson-yue/lffont/tree/f31f5a1cd6a075449a0f18aaafd945d373121e15 |
Bilinear | # 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... | iesl/diora-public | Bilinear | false | 15,584 | [
"Apache-2.0"
] | 81 | 110b9b0881907ec049dd60cd93ff6ef084582b3b | https://github.com/iesl/diora-public/tree/110b9b0881907ec049dd60cd93ff6ef084582b3b |
LRN | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | Kitware/VAIME | LRN | false | 13,953 | [
"BSD-3-Clause"
] | 127 | 47b24b9d8a208cf8c621e5bb1088c61fcf507af6 | https://github.com/Kitware/VAIME/tree/47b24b9d8a208cf8c621e5bb1088c61fcf507af6 |
SSIM | # 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
... | ArminMasoumian/GCNDepth | SSIM | false | 7,726 | [
"MIT"
] | 32 | 9fa77812fa944c2701a45f09acf988815ca50aee | https://github.com/ArminMasoumian/GCNDepth/tree/9fa77812fa944c2701a45f09acf988815ca50aee |
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.... | cjlovering/EGG | InformedSender | false | 10,057 | [
"MIT"
] | 0 | cce146e035decbc410e981f8bc7ada32979f3b6d | https://github.com/cjlovering/EGG/tree/cce146e035decbc410e981f8bc7ada32979f3b6d |
LayerNorm | import torch
import torch.nn as nn
import torch.utils.data
class LayerNorm(nn.Module):
"""
Simple 1D LayerNorm.
"""
def __init__(self, features, center=True, scale=False, eps=1e-06):
super().__init__()
self.center = center
self.scale = scale
self.eps = eps
if s... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dy... | Thibaud-Ardoin/d4rl_evaluations | LayerNorm | false | 14,484 | [
"Apache-2.0"
] | 123 | 135b23d3aecc234aacaeaaa019fbc7101d9b87ec | https://github.com/Thibaud-Ardoin/d4rl_evaluations/tree/135b23d3aecc234aacaeaaa019fbc7101d9b87ec |
PositionGenerator | # 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 ... | eweiner/MAT_Extension | PositionGenerator | false | 12,367 | [
"MIT"
] | 0 | 505884a67f97bf54e1198077d15a48531fcac7a5 | https://github.com/eweiner/MAT_Extension/tree/505884a67f97bf54e1198077d15a48531fcac7a5 |
IOUloss | # 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... | Arui66/YOLOX | IOUloss | false | 7,762 | [
"Apache-2.0"
] | 16 | 7ee17936db849600817d7de05269bfdfb1a0eb48 | https://github.com/Arui66/YOLOX/tree/7ee17936db849600817d7de05269bfdfb1a0eb48 |
_CNN | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class _CNN(nn.Module):
def __init__(self, config):
super(_CNN, self).__init__()
self.config = config
self.in_channels = 1
self.in_height = self.config.max_length
self.in_width = self.config.wo... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | Lnna/OpenNRE-PyTorch | _CNN | false | 5,692 | [
"MIT"
] | 1 | 907026a8bece7a867558087131cd1e97d41eb3f2 | https://github.com/Lnna/OpenNRE-PyTorch/tree/907026a8bece7a867558087131cd1e97d41eb3f2 |
SpatialGate3D | # 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.... | Healingl/3DAPRNet | SpatialGate3D | false | 2,382 | [
"BSD-2-Clause"
] | 0 | 7c5e0028ae844df4e1f26327e8b438532ca0745f | https://github.com/Healingl/3DAPRNet/tree/7c5e0028ae844df4e1f26327e8b438532ca0745f |
DownBlock | import torch
import torch.nn as nn
class ConvBlock(nn.Module):
def __init__(self, input_size, output_size, kernel_size=3, stride=1,
padding=1, bias=True, norm=None):
super(ConvBlock, self).__init__()
self.conv = nn.Conv2d(input_size, output_size, kernel_size, stride,
padding, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | MatusBako/MakeFacesGreatAgain | DownBlock | false | 834 | [
"MIT"
] | 0 | e4941a8460db79dec566ed02d4b23eafb416a6db | https://github.com/MatusBako/MakeFacesGreatAgain/tree/e4941a8460db79dec566ed02d4b23eafb416a6db |
Bottleneck | # 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.... | andyqmongo/InstAParam | Bottleneck | false | 18,336 | [
"MIT"
] | 3 | 00494d5367ec32b4ce90d01778cba9d4f1166833 | https://github.com/andyqmongo/InstAParam/tree/00494d5367ec32b4ce90d01778cba9d4f1166833 |
AUXModule | # 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_... | KeremTurgutlu/fast-kaggle | AUXModule | false | 17,535 | [
"Apache-2.0"
] | 8 | 0ea341b44a58da2dfb606a0ae32bac166985b49e | https://github.com/KeremTurgutlu/fast-kaggle/tree/0ea341b44a58da2dfb606a0ae32bac166985b49e |
ModelRegressionGex2Atac | # 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.... | Permoment-95/neurips2021_multimodal_topmethods | ModelRegressionGex2Atac | false | 9,488 | [
"MIT"
] | 0 | 017bc23b366a80ba9b1c2a47ea6c44124f77a7ca | https://github.com/Permoment-95/neurips2021_multimodal_topmethods/tree/017bc23b366a80ba9b1c2a47ea6c44124f77a7ca |
L1Part | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
from itertools import chain as chain
from collections import OrderedDict
import torch.hub
class concatLayer(nn.Module):
def __init__(self, in_channels, out_channels_perSub, i, j, appendix):
super(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
import torch.nn.parallel
import torch.optim
import torch.u... | EddieMG/LateTemporalModeling3DCNN | L1Part | false | 2,362 | [
"MIT"
] | 0 | 94c87dc1d31d09bc310d0e735a2e55453976cb0d | https://github.com/EddieMG/LateTemporalModeling3DCNN/tree/94c87dc1d31d09bc310d0e735a2e55453976cb0d |
ToRGB | from torch.autograd import Function
import math
import torch
import torch.utils.data
from torch.utils import data as data
from torch.nn import functional as F
from torch import nn as nn
from torch.nn import init as init
from torchvision.models import vgg as vgg
from torch import autograd as autograd
def make_resample... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.autograd import Function
import math
import torch.utils.data
from tor... | WoojunePark/BasicSR | ToRGB | false | 18,121 | [
"Apache-2.0"
] | 9 | e0910b022b924bb913045fc412a5470dc2242cf0 | https://github.com/WoojunePark/BasicSR/tree/e0910b022b924bb913045fc412a5470dc2242cf0 |
Attention | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class Attention(nn.Module):
def __init__(self, embed_dim, hidden_dim=None, out_dim=None, n_head=1,
score_function='scaled_dot_product', dropout=0):
""" Attention Mechanism
:param embed_dim:
:param hidde... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | n-log-n/ABSA-PyTorch | Attention | false | 7,310 | [
"MIT"
] | 1 | 27b37e05954940fe37369cc679c080d1d8717362 | https://github.com/n-log-n/ABSA-PyTorch/tree/27b37e05954940fe37369cc679c080d1d8717362 |
LengthPredictor | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn import function... | ygnn123/training_extensions | LengthPredictor | false | 4,729 | [
"Apache-2.0"
] | 0 | c3aeba9359b0d4e0ef9c054de777d3ec081a9892 | https://github.com/ygnn123/training_extensions/tree/c3aeba9359b0d4e0ef9c054de777d3ec081a9892 |
h_swish | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guard... | anonymous2022ijcai/RGSL | h_swish | false | 1,447 | [
"MIT"
] | 0 | 11c38ee50d50127c0f7c2a137bdb21ca5f7f3644 | https://github.com/anonymous2022ijcai/RGSL/tree/11c38ee50d50127c0f7c2a137bdb21ca5f7f3644 |
LearnableMax | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | RiyaoDong/HGSL | LearnableMax | false | 2,764 | [
"Apache-2.0"
] | 0 | 19fa984b3bfde0e3b7acbce87dd40177cd64f9b0 | https://github.com/RiyaoDong/HGSL/tree/19fa984b3bfde0e3b7acbce87dd40177cd64f9b0 |
Evidential_layer | import torch
import torch.nn as nn
class Evidential_layer(nn.Module):
def __init__(self, in_dim, num_classes):
super(Evidential_layer, self).__init__()
self.num_classes = num_classes
self.fc1 = nn.Linear(in_dim, 2 * self.num_classes)
self.relu = torch.nn.ReLU()
def forward(se... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | caisr-hh/DEED | Evidential_layer | false | 1,627 | [
"MIT"
] | 0 | 2a9edb1df31d99c1e8da177dec696d7c90c2e7de | https://github.com/caisr-hh/DEED/tree/2a9edb1df31d99c1e8da177dec696d7c90c2e7de |
Critic | import torch
from torch import nn
import torch.nn.functional as F
class Critic(nn.Module):
"""Critic model
Parameters:
args (object): Parameter class
"""
def __init__(self, state_dim, action_dim):
super(Critic, self).__init__()
l1 = 400
l2 = 300
sel... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | zhan0903/cerl | Critic | false | 4,671 | [
"Apache-2.0"
] | 0 | 6fb8aca9cb78b72947237edf2b9ed8362bd43829 | https://github.com/zhan0903/cerl/tree/6fb8aca9cb78b72947237edf2b9ed8362bd43829 |
GCN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.nn.functional as F
import torch.nn.parallel
im... | UrwLee/AdelaiDet | GCN | false | 9,645 | [
"BSD-2-Clause"
] | 0 | 4cd88a80355d21261e94400767f44701ebc4b402 | https://github.com/UrwLee/AdelaiDet/tree/4cd88a80355d21261e94400767f44701ebc4b402 |
Multi_feature_fusing | import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.init
def l2norm(X, dim=-1, eps=1e-12):
"""L2-normalize columns of X
"""
norm = torch.pow(X, 2).sum(dim=dim, keepdim=True).sqrt() + eps
X = torch.div(X, norm)
return X
class Multi_feature_fusing(... | 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 numpy as np
import torch.nn as nn
import torch.nn.init
assert_size_strid... | BruceW91/CVSE | Multi_feature_fusing | false | 13,426 | [
"MIT"
] | 152 | 20fa1ff50d1dcb4a7b3799071fa78038e52db804 | https://github.com/BruceW91/CVSE/tree/20fa1ff50d1dcb4a7b3799071fa78038e52db804 |
NormedLinear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | LiuXiaoxuanPKU/mmdetection | NormedLinear | false | 11,645 | [
"Apache-2.0"
] | 0 | 05b46eccbe5c4953d5a406f545fe529ce4e146d3 | https://github.com/LiuXiaoxuanPKU/mmdetection/tree/05b46eccbe5c4953d5a406f545fe529ce4e146d3 |
AndAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
class AndAttention(nn.Module):
def __init__(self, n_layers, entity_dim, temperature, attn_dropout=0.1):
super(AndAttention, self).__init__()
self.temperature = temperature
self.dropout = nn.Dropout(attn_dropout)
se... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | amayuelas/NNKGReasoning | AndAttention | false | 6,186 | [
"MIT"
] | 1 | 0e3623b344fd4e3088ece897f898ddbb1f80888d | https://github.com/amayuelas/NNKGReasoning/tree/0e3623b344fd4e3088ece897f898ddbb1f80888d |
FeedForward | import math
import torch
import numpy as np
import torch.nn as nn
def gelu(x):
return 0.5 * x * (1 + torch.tanh(math.sqrt(2 / math.pi) * (x + 0.044715 *
torch.pow(x, 3))))
class 全连接层(nn.Module):
def __init__(self, 输入_接口, 输出_接口):
super().__init__()
np.random.seed(1)
self.weig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import ... | chenjun-110/WZCQ | FeedForward | false | 1,681 | [
"Apache-2.0"
] | 0 | e2de7743ad671e8632cfa084638555d7f1deb42f | https://github.com/chenjun-110/WZCQ/tree/e2de7743ad671e8632cfa084638555d7f1deb42f |
MultiHeadAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
class MultiHeadAttention(nn.Module):
"""
Multi-Head Attention
"""
def __init__(self, d_key, d_value, d_model, n_head=1, dropout_rate=0.0):
super(MultiHeadAttention, self).__init__()
self.n_head = n_head
self.d_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | eminem171333491/PaddleOCR2Pytorch | MultiHeadAttention | false | 3,459 | [
"Apache-2.0"
] | 0 | ec466bb3a689eccb9290e9f80812a45301d3b030 | https://github.com/eminem171333491/PaddleOCR2Pytorch/tree/ec466bb3a689eccb9290e9f80812a45301d3b030 |
GraphGaussianBlock | # 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 a... | bouracha/Gen_Motion | GraphGaussianBlock | false | 9,931 | [
"MIT"
] | 0 | 873caa496d14c9a9723581cdf1464f44db4cf358 | https://github.com/bouracha/Gen_Motion/tree/873caa496d14c9a9723581cdf1464f44db4cf358 |
TemperatureHolder | import torch
from torch import nn
class TemperatureHolder(nn.Module):
"""Module that holds a temperature as a learnable value.
Args:
initial_log_temperature (float): Initial value of log(temperature).
"""
def __init__(self, initial_log_temperature=0):
super().__init__()
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 torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_... | tarokiritani/pfrl | TemperatureHolder | false | 11,018 | [
"MIT"
] | 0 | 284ed1f43b32654a2ec1569b16a0f6b9acbd5e79 | https://github.com/tarokiritani/pfrl/tree/284ed1f43b32654a2ec1569b16a0f6b9acbd5e79 |
Attention | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class Attention(nn.Module):
def forward(self, query, key, value, mask=None, dropout=None):
"""Compute 'Scaled Dot Product Attention'"""
d_k = query.size(-1)
scores = torch.matmul(query, key.transpose(-2, -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.... | Moymix/BERT-pytorch | Attention | false | 5,599 | [
"Apache-2.0"
] | 1 | f0b9c3ae53e05c00adcc761e0422e4222d8b5619 | https://github.com/Moymix/BERT-pytorch/tree/f0b9c3ae53e05c00adcc761e0422e4222d8b5619 |
DecoderLayer | # 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.... | RogerTsai917/attention-is-all-you-need-pytorch | DecoderLayer | false | 2,795 | [
"MIT"
] | 0 | 64197e55d275e5c819bc786a9ff19849cdf2f6b9 | https://github.com/RogerTsai917/attention-is-all-you-need-pytorch/tree/64197e55d275e5c819bc786a9ff19849cdf2f6b9 |
ChannelAttention_a | import torch
from torch import nn
class ChannelAttention_a(nn.Module):
def __init__(self, in_planes, ratio=8):
super(ChannelAttention_a, self).__init__()
self.avg_pool = nn.AdaptiveAvgPool2d(1)
self.max_pool = nn.AdaptiveMaxPool2d(1)
self.fc1 = nn.Conv2d(in_planes, ratio, 1, bias=... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | HT-hlf/mmdetection_miner-2.22.0 | ChannelAttention_a | false | 2,324 | [
"Apache-2.0"
] | 0 | 76eb94d6547f9f95cd58f41bb5c91941e82322b9 | https://github.com/HT-hlf/mmdetection_miner-2.22.0/tree/76eb94d6547f9f95cd58f41bb5c91941e82322b9 |
NormedLinear | import torch
import torch.nn.functional as F
from torch import nn
import torch.onnx
class NormedLinear(nn.Linear):
"""Normalized Linear Layer.
Args:
tempeature (float, optional): Tempeature term. Default to 20.
power (int, optional): Power term. Default to 1.0.
eps (float, optional): ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | ENOT-AutoDL/mmdetection-enot | NormedLinear | false | 5,111 | [
"Apache-2.0"
] | 1 | f541749554436e3327bac00eee89b84f66c03551 | https://github.com/ENOT-AutoDL/mmdetection-enot/tree/f541749554436e3327bac00eee89b84f66c03551 |
RpowFloat | import torch
class RpowFloat(torch.nn.Module):
def __init__(self):
super(RpowFloat, self).__init__()
def forward(self, x):
return 2.0 ** x
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | bunderhi/torch2trt | RpowFloat | false | 1,615 | [
"MIT"
] | 0 | fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d | https://github.com/bunderhi/torch2trt/tree/fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d |
BCEBlurWithLogitsLoss | import torch
import torch.nn as nn
class BCEBlurWithLogitsLoss(nn.Module):
def __init__(self, alpha=0.05):
super(BCEBlurWithLogitsLoss, self).__init__()
self.loss_fcn = nn.BCEWithLogitsLoss(reduction='none')
self.alpha = alpha
def forward(self, pred, true):
loss = self.loss_f... | 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... | AsakusaRinne/tensorrt_yolov5_tracker | BCEBlurWithLogitsLoss | false | 7,734 | [
"MIT"
] | 22 | b9a3a6fc94710e8291d6a614ed2b04cbc4c56599 | https://github.com/AsakusaRinne/tensorrt_yolov5_tracker/tree/b9a3a6fc94710e8291d6a614ed2b04cbc4c56599 |
Rodrigues | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torch.nn as nn
import torch.utils.data
assert_size_stri... | zhuhao-nju/mofanerf | Rodrigues | false | 16,825 | [
"MIT"
] | 55 | 0206526e25aab3dd8f0cc789f290c7559642676b | https://github.com/zhuhao-nju/mofanerf/tree/0206526e25aab3dd8f0cc789f290c7559642676b |
_GlobalConvModule | # 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... | BloodAxe/segmentation-networks-benchmark | _GlobalConvModule | false | 7,877 | [
"MIT"
] | 34 | 2e3feb560102230be9369ab442b4a59cc86dff61 | https://github.com/BloodAxe/segmentation-networks-benchmark/tree/2e3feb560102230be9369ab442b4a59cc86dff61 |
FocalLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | umairjavaid/staff-employee-classification | FocalLoss | false | 13,061 | [
"MIT"
] | 0 | fc5fe32acfbde2b188094df90d888eeb0f4f4acd | https://github.com/umairjavaid/staff-employee-classification/tree/fc5fe32acfbde2b188094df90d888eeb0f4f4acd |
ToRGB | from torch.autograd import Function
import math
import torch
import torch.utils.data
from torch.nn import functional as F
from torch.utils import data as data
import torch.nn as nn
from torch.nn import init as init
from torchvision.models import vgg as vgg
from torch import autograd as autograd
def pad(pad_type, padd... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.autograd import Function
import math
import torch.utils.data
from tor... | achrefjarray/ESRGANplus-master | ToRGB | false | 1,375 | [
"Apache-2.0"
] | 0 | ba470ec5c565a6dc8b48575b1e185ef6b796aec6 | https://github.com/achrefjarray/ESRGANplus-master/tree/ba470ec5c565a6dc8b48575b1e185ef6b796aec6 |
GumbelSoftmaxLayer | import torch
import torch.nn as nn
from torch.distributions import RelaxedOneHotCategorical
import torch.nn.parallel
import torch.utils.data
import torch.distributions
def gumbel_softmax_sample(logits: 'torch.Tensor', temperature: 'float'=1.0,
training: 'bool'=True, straight_through: 'bool'=False):
size = log... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.distributions import RelaxedOneHotCategorical
import torch.nn.parallel
import torch.utils.data
import torch... | Slowika/GameBias-EmeCom2020 | GumbelSoftmaxLayer | false | 17,957 | [
"MIT"
] | 5 | 5b94c47559f8202bca99c26fc1bcb078dd0509a6 | https://github.com/Slowika/GameBias-EmeCom2020/tree/5b94c47559f8202bca99c26fc1bcb078dd0509a6 |
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
from torch._inductor.runtime.... | acrididcheng/pytorch_geometric | DenseSAGEConv | false | 6,086 | [
"MIT"
] | 1 | 50dad4a6b6dc958ad68b9a3c2bc3decfa3516737 | https://github.com/acrididcheng/pytorch_geometric/tree/50dad4a6b6dc958ad68b9a3c2bc3decfa3516737 |
ToRGB | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import numpy as np
from torch import nn
import torch.nn.functional a... | Aarsh2001/annotated_deep_learning_paper_implementations | ToRGB | false | 4,792 | [
"MIT"
] | 1 | ff0d5c065da1a46769f5f66fddc252c178f8fa37 | https://github.com/Aarsh2001/annotated_deep_learning_paper_implementations/tree/ff0d5c065da1a46769f5f66fddc252c178f8fa37 |
KarankEtAl | import torch
import torch.nn as nn
import torch.nn.functional as F
class KarankEtAl(nn.Module):
def __init__(self, input_channels, n_classes, patch_size=5):
super(KarankEtAl, self).__init__()
self.patch_size = patch_size
self.input_channels = input_channels
self.n_classes = n_clas... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | giorgosouz/HSI-classification-makantasis-cnn | KarankEtAl | false | 10,153 | [
"MIT"
] | 0 | 95f18274d7cb67babb971db71f358a73dee2affc | https://github.com/giorgosouz/HSI-classification-makantasis-cnn/tree/95f18274d7cb67babb971db71f358a73dee2affc |
MseCriterion | import torch
import torch.nn.functional as F
from torch.nn.modules.loss import _Loss
from torch.optim.lr_scheduler import *
class Criterion(_Loss):
def __init__(self, alpha=1.0, name='criterion'):
super().__init__()
"""Alpha is used to weight each loss term
"""
self.alpha = alpha
... | 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.nn.modules.loss import _Loss
from torch.optim.lr_scheduler import *
assert_siz... | anlewy/mt-dnn | MseCriterion | false | 14,863 | [
"MIT"
] | 2,075 | eeb6f01ce0630e61a52b8c9c6f7537cd34978e45 | https://github.com/anlewy/mt-dnn/tree/eeb6f01ce0630e61a52b8c9c6f7537cd34978e45 |
TotalVariation | import torch
import torch.nn as nn
class TotalVariation(nn.Module):
"""TotalVariation: calculates the total variation of a patch.
Module providing the functionality necessary to calculate the total vatiation (TV) of an adversarial patch.
"""
def __init__(self):
super(TotalVariation, 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 torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | Zhang-Jack/adversarial_yolo2 | TotalVariation | false | 18,176 | [
"MIT"
] | 8 | 91c2a4793047f656482cebf0309984db823e8030 | https://github.com/Zhang-Jack/adversarial_yolo2/tree/91c2a4793047f656482cebf0309984db823e8030 |
MyGlobalAvgPool2d | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
import torch.nn.parallel
import torch.optim
assert_size_stride = torch._C._dynamo.guards.asser... | xmyqsh/once-for-all | MyGlobalAvgPool2d | false | 4,585 | [
"MIT"
] | 0 | 0bca1778b106d33460fc8d0f7d7e6ca4e1e937d9 | https://github.com/xmyqsh/once-for-all/tree/0bca1778b106d33460fc8d0f7d7e6ca4e1e937d9 |
ProdAttention | # 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
... | wgfi110/speech | ProdAttention | false | 10,943 | [
"Apache-2.0"
] | 0 | 59a3e2d8d2d99d31cf32e06c1a0751eb36a3c02b | https://github.com/wgfi110/speech/tree/59a3e2d8d2d99d31cf32e06c1a0751eb36a3c02b |
MultiHeadedAttention | import math
import torch
from torch import nn
class MultiHeadedAttention(nn.Module):
def __init__(self, dim, n_head, bias=True, dropout=0):
super().__init__()
self.dim_head = dim // n_head
self.n_head = n_head
self.qkv = nn.Linear(dim, dim * 3, bias=bias)
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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | rosinality/vision-transformers-pytorch | MultiHeadedAttention | false | 16,343 | [
"MIT"
] | 77 | b884b5da79900c96e4ce17fbb575cf1c5cb3cd5f | https://github.com/rosinality/vision-transformers-pytorch/tree/b884b5da79900c96e4ce17fbb575cf1c5cb3cd5f |
PrecomputedNorm | # 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... | gcambara/s3prl | PrecomputedNorm | false | 15,405 | [
"MIT"
] | 856 | 33284ebde3a903ed8604d6dae85669d0174ae1d3 | https://github.com/gcambara/s3prl/tree/33284ebde3a903ed8604d6dae85669d0174ae1d3 |
SimpleReciprocalModel | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleReciprocalModel(torch.nn.Module):
def __init__(self, inplace=False):
super(SimpleReciprocalModel, self).__init__()
self.inplace = inplace
def forward(self, tensor):
other = tensor + tensor
return othe... | 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... | andreas-hommel/glow | SimpleReciprocalModel | false | 3,360 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
FiLMLayerEqualFC | import math
import torch
import torch.nn.functional as F
from torch import nn
class EqualLinear(nn.Module):
def __init__(self, in_dim, out_dim, bias=True, bias_init=0, lr_mul=1.0,
activation=None):
"""
:param in_dim:
:param out_dim:
:param bias:
:param bias_init:
:param lr_mu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | xh-liu-tech/CIPS-3D | FiLMLayerEqualFC | false | 11,107 | [
"MIT"
] | 0 | 8910dfcf19bb86aab2287d652ae4e3666806b511 | https://github.com/xh-liu-tech/CIPS-3D/tree/8910dfcf19bb86aab2287d652ae4e3666806b511 |
TemporalEmbedding | # 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 math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guar... | Xianchao-Wu/informer | TemporalEmbedding | false | 5,991 | [
"Apache-2.0"
] | 1 | bb9cb3c6ff9e7e76c8dbbf3bcc7924df1f18982d | https://github.com/Xianchao-Wu/informer/tree/bb9cb3c6ff9e7e76c8dbbf3bcc7924df1f18982d |
RevPaddingLayer | # 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... | RKorzeniowski/BigBiGAN-PyTorch | RevPaddingLayer | false | 17,832 | [
"MIT"
] | 5 | caaaf69b094ae45e9fa3608577fde32dafa1f16e | https://github.com/RKorzeniowski/BigBiGAN-PyTorch/tree/caaaf69b094ae45e9fa3608577fde32dafa1f16e |
BasicModel3 | import torch
import torch.nn as nn
import torch.nn.functional as F
class BasicModel3(nn.Module):
"""
Example model two from the paper
https://arxiv.org/pdf/1703.01365.pdf
f(x1, x2) = RELU(ReLU(x1 - 1) - ReLU(x2))
"""
def __init__(self):
super().__init__()
def forward... | 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... | Europium248/captum | BasicModel3 | false | 410 | [
"BSD-3-Clause"
] | 0 | ac02fae2651b8d68a44bcb9d03b91cbb3959f2fc | https://github.com/Europium248/captum/tree/ac02fae2651b8d68a44bcb9d03b91cbb3959f2fc |
ZeroConv2d | import torch
from torch import nn
from torch.nn import functional as F
class ZeroConv2d(nn.Module):
def __init__(self, in_channel, out_channel, padding=1):
super().__init__()
self.conv = nn.Conv2d(in_channel, out_channel, 3, padding=0)
self.conv.weight.data.zero_()
self.conv.bias.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch im... | AvivNavon/glow-pytorch | ZeroConv2d | false | 8,857 | [
"MIT"
] | 0 | de0fb2c1d8a4000337b2fbd1215df68530070431 | https://github.com/AvivNavon/glow-pytorch/tree/de0fb2c1d8a4000337b2fbd1215df68530070431 |
SpatialCrossMapLRN | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.nn.parallel
assert_size_stride = torch._C._d... | vfdev-5/models-comparison.pytorch | SpatialCrossMapLRN | false | 16,674 | [
"BSD-3-Clause"
] | 174 | 6a09c41c1ed6160af0734924700a9150249c3df6 | https://github.com/vfdev-5/models-comparison.pytorch/tree/6a09c41c1ed6160af0734924700a9150249c3df6 |
BertAttention | from _paritybench_helpers import _mock_config
from torch.nn import Module
import math
import torch
import torch.nn.functional as F
import torch.nn as nn
class BertLayerNorm(Module):
def __init__(self, hidden_size, eps=1e-12):
super(BertLayerNorm, self).__init__()
self.shape = torch.Size((hidden_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._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | codecaution/Hetu | BertAttention | false | 1,745 | [
"Apache-2.0"
] | 0 | e278732c2fe3554c8d576585f5bcbf79ade31b68 | https://github.com/codecaution/Hetu/tree/e278732c2fe3554c8d576585f5bcbf79ade31b68 |
WNConv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | MioChiu/vqvae2 | WNConv2d | false | 2,657 | [
"MIT"
] | 0 | e57cc7546d3bd02c61387367936f7cd76b75eaae | https://github.com/MioChiu/vqvae2/tree/e57cc7546d3bd02c61387367936f7cd76b75eaae |
LayerNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | NeilWangziyu/torch_light | LayerNorm | false | 5,644 | [
"MIT"
] | 1 | daf8fd62f57885cf182f1b3edc3152156d229ef3 | https://github.com/NeilWangziyu/torch_light/tree/daf8fd62f57885cf182f1b3edc3152156d229ef3 |
ActorCritic | import math
import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
def log_normal_density(x, mean, log_std, std):
"""returns guassian density given x on log scale"""
variance = std.pow(2)
log_density = -(x - mean).pow(2) / (2 * variance) - 0.5 * np.log(2 * np.pi
) - ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | Tzenthin/pytorch-ppo-sac-HalfCheetah-v2 | ActorCritic | false | 5,927 | [
"MIT"
] | 1 | 282a4104ec577056a141909e29dc97ed425a566c | https://github.com/Tzenthin/pytorch-ppo-sac-HalfCheetah-v2/tree/282a4104ec577056a141909e29dc97ed425a566c |
BertOutput | # 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 ... | MikeWangWZHL/BLIP | BertOutput | false | 1,883 | [
"BSD-3-Clause"
] | 0 | b82134f1892a54c8f63b0f4b51bdcb8684e1dc6d | https://github.com/MikeWangWZHL/BLIP/tree/b82134f1892a54c8f63b0f4b51bdcb8684e1dc6d |
Pad_Conv2d | # 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 math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guard... | Hullimulli/EEGEyeNet | Pad_Conv2d | false | 551 | [
"MIT"
] | 0 | 677a791b39800f44dc254553b16ee2f92e62c423 | https://github.com/Hullimulli/EEGEyeNet/tree/677a791b39800f44dc254553b16ee2f92e62c423 |
cSE | # 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_... | Soo95/segmentation_models.pytorch | cSE | false | 2,843 | [
"MIT"
] | 0 | 9131b336d6939dfabbadecd0d56d382283f46803 | https://github.com/Soo95/segmentation_models.pytorch/tree/9131b336d6939dfabbadecd0d56d382283f46803 |
RNN | import torch
import torch.nn as nn
from torch.autograd import Variable
class RNN(nn.Module):
def __init__(self, input_size, hidden_size, output_size):
super(RNN, self).__init__()
self.hidden_size = hidden_size
self.i2h = nn.Linear(input_size + hidden_size, hidden_size)
self.i2o = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | chenyuntc/practical-pytorch | RNN | false | 12,214 | [
"MIT"
] | 0 | 42cbde5275d37bf3f3623a85fd71f13069d95089 | https://github.com/chenyuntc/practical-pytorch/tree/42cbde5275d37bf3f3623a85fd71f13069d95089 |
MultiheadConvAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | amaurySabran/fairseq | MultiheadConvAttention | false | 18,291 | [
"BSD-3-Clause"
] | 4 | e6d5dd36678224e8b06aa0e97749f7a1c20a9949 | https://github.com/amaurySabran/fairseq/tree/e6d5dd36678224e8b06aa0e97749f7a1c20a9949 |
CosineLinear | # 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.... | QingquanBao/Spear-Shield | CosineLinear | false | 983 | [
"Apache-2.0"
] | 0 | d57b8f4412c3d651b6f7e056c9c45cfd0dc950c3 | https://github.com/QingquanBao/Spear-Shield/tree/d57b8f4412c3d651b6f7e056c9c45cfd0dc950c3 |
CombineSlices | import torch
from torch import nn
import torch.utils.data
import torch.utils.data.distributed
import torch.optim
class CombineSlices(nn.Module):
def __init__(self, slice_dim=2):
super().__init__()
self.slice_dim = slice_dim
def forward(self, x):
return torch.index_select(x, dim=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 torch import nn
import torch.utils.data
import torch.utils.data.distributed
import torch.optim
assert_size_stride = torch._C._dynamo.gu... | gbosdet/fastMRI | CombineSlices | false | 6,716 | [
"MIT"
] | 1 | 7f94f8006f8919d98fb87788b6dadec9a58d1a3a | https://github.com/gbosdet/fastMRI/tree/7f94f8006f8919d98fb87788b6dadec9a58d1a3a |
softmax | # 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
... | yifanpu001/PytorchToCaffe | softmax | false | 4,727 | [
"MIT"
] | 0 | 37c1ebfc3547e93b1c174721036d03c831c60e48 | https://github.com/yifanpu001/PytorchToCaffe/tree/37c1ebfc3547e93b1c174721036d03c831c60e48 |
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 import nn
import t... | chenyangh/tensor2struct-public | MLP | false | 15,020 | [
"MIT"
] | 69 | d3257cba6d76d3c658a58a78f687d986bdc755cf | https://github.com/chenyangh/tensor2struct-public/tree/d3257cba6d76d3c658a58a78f687d986bdc755cf |
UFOAttention | import torch
from torch import nn
from torch.nn import init
def XNorm(x, gamma):
norm_tensor = torch.norm(x, 2, -1, True)
return x * gamma / norm_tensor
class UFOAttention(nn.Module):
"""
Scaled dot-product attention
"""
def __init__(self, d_model, d_k, d_v, h, dropout=0.1):
"""
... | 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.triton_helpers import libdevice
from torch import n... | weihaoxie/External-Attention-pytorch | UFOAttention | false | 4,532 | [
"MIT"
] | 0 | 9bec70f4ed8dd858c815e9bad240ab2f95a91a9f | https://github.com/weihaoxie/External-Attention-pytorch/tree/9bec70f4ed8dd858c815e9bad240ab2f95a91a9f |
NeuralNetMultiplePositionalArgumentsVarKeyword | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn
import torch.... | RyanUnderhill/onnxruntime | NeuralNetMultiplePositionalArgumentsVarKeyword | false | 11,828 | [
"MIT"
] | 0 | 6df4e293ffbb47d739d2dedfbb87fa6234b8c37c | https://github.com/RyanUnderhill/onnxruntime/tree/6df4e293ffbb47d739d2dedfbb87fa6234b8c37c |
CoordConv2D | import torch
from torch import nn
class CoordConv2D(nn.Module):
def __init__(self, in_channels: 'int', out_channels: 'int', kernel_size:
'int'=3, stride: 'int'=1, padding: 'int'=1, with_r: 'bool'=False):
super().__init__()
self.in_channel = in_channels
self.with_r = with_r
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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... | EasternJournalist/pi-GAN | CoordConv2D | false | 17,247 | [
"MIT"
] | 4 | 3d57611e1c8fca2f3cd00fde1989ec1f9dd94d55 | https://github.com/EasternJournalist/pi-GAN/tree/3d57611e1c8fca2f3cd00fde1989ec1f9dd94d55 |
AlignQuestionEmbedding | # 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.... | HuyTu7/dl_optimizers | AlignQuestionEmbedding | false | 9,137 | [
"MIT"
] | 0 | 245242718324cebcabe657bdbc704aa54ad0b8d2 | https://github.com/HuyTu7/dl_optimizers/tree/245242718324cebcabe657bdbc704aa54ad0b8d2 |
ParallelPolarizedSelfAttention | import torch
from torch import nn
class ParallelPolarizedSelfAttention(nn.Module):
def __init__(self, channel=512):
super().__init__()
self.ch_wv = nn.Conv2d(channel, channel // 2, kernel_size=(1, 1))
self.ch_wq = nn.Conv2d(channel, 1, kernel_size=(1, 1))
self.softmax_channel = 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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Nitin-Mane/External-Attention-pytorch | ParallelPolarizedSelfAttention | false | 14,150 | [
"MIT"
] | 4,466 | 1ceda306c41063af11c956334747763444a4d83f | https://github.com/Nitin-Mane/External-Attention-pytorch/tree/1ceda306c41063af11c956334747763444a4d83f |
Q_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_... | arnaghosh/VoxNet | Q_net | false | 1,479 | [
"MIT"
] | 0 | 45fe8e9ff28b02f21b8991486317ff61cfa5d553 | https://github.com/arnaghosh/VoxNet/tree/45fe8e9ff28b02f21b8991486317ff61cfa5d553 |
MarginRankingLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data... | Dogacel/mmfashion | MarginRankingLoss | false | 11,412 | [
"Apache-2.0"
] | 0 | e49613245c8501042edd7aeeaa8fb93e5ea13238 | https://github.com/Dogacel/mmfashion/tree/e49613245c8501042edd7aeeaa8fb93e5ea13238 |
ResNetBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.utils.data
import torch.nn.parallel
import tor... | Sarah20187/X-StereoLab | ResNetBlock | false | 14,387 | [
"MIT"
] | 192 | 9ae8c1413307e7df91b14a7f31e8a95f9e5754f9 | https://github.com/Sarah20187/X-StereoLab/tree/9ae8c1413307e7df91b14a7f31e8a95f9e5754f9 |
JSCriterion | import torch
import torch.nn.functional as F
from torch.nn.modules.loss import _Loss
from torch.optim.lr_scheduler import *
class Criterion(_Loss):
def __init__(self, alpha=1.0, name='criterion'):
super().__init__()
"""Alpha is used to weight each loss term
"""
self.alpha = alpha
... | 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.... | johnson7788/mt-dnn | JSCriterion | false | 3,900 | [
"MIT"
] | 0 | 26e5c4a5bfdbf1a1dd1c903e606db1c070568237 | https://github.com/johnson7788/mt-dnn/tree/26e5c4a5bfdbf1a1dd1c903e606db1c070568237 |
SplAtConv2d | import logging
import torch
import torch.nn.functional as F
from torch import nn
from torch.nn import ReLU
from torch.nn import Conv2d
from torch.nn.modules.utils import _pair
def get_norm(norm, out_channels, num_splits=1, **kwargs):
"""
Args:
norm (str or callable):
Returns:
nn.Module or ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | DengpanFu/fast-reid-v0 | SplAtConv2d | false | 9,095 | [
"Apache-2.0"
] | 0 | e444c0187ccb6ef3b8348f8c5f0c5a0814b3683e | https://github.com/DengpanFu/fast-reid-v0/tree/e444c0187ccb6ef3b8348f8c5f0c5a0814b3683e |
VAE | import torch
from torch import nn
import torch.nn.functional as F
class VAE(nn.Module):
def __init__(self):
super().__init__()
self.fc1 = nn.Linear(784, 400)
self.fc21 = nn.Linear(400, 20)
self.fc22 = nn.Linear(400, 20)
self.fc3 = nn.Linear(20, 400)
self.fc4 = nn.L... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | nd1511/argus | VAE | false | 7,323 | [
"MIT"
] | 1 | 00aaed41ac1321d669ac7060f4d21b24cc3456f0 | https://github.com/nd1511/argus/tree/00aaed41ac1321d669ac7060f4d21b24cc3456f0 |
JSD | # 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... | pudumagico/deepproblog | JSD | false | 16,285 | [
"Apache-2.0"
] | 54 | 6d38e783990551f4030780a1d69c7138fada2020 | https://github.com/pudumagico/deepproblog/tree/6d38e783990551f4030780a1d69c7138fada2020 |
BoundNot | # 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 math
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
from numbers import Number
assert_size_stride = torch._... | Mahoumaru/auto_LiRPA | BoundNot | false | 13,223 | [
"BSD-3-Clause"
] | 0 | b03a6c36eb1b921726778359d6d2b94e0cd7e480 | https://github.com/Mahoumaru/auto_LiRPA/tree/b03a6c36eb1b921726778359d6d2b94e0cd7e480 |
SqueezeInitBlock | # 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 ... | earhian/imgclsmob | SqueezeInitBlock | false | 6,634 | [
"MIT"
] | 1 | c87c0942420876941868c016211073dec4392e4d | https://github.com/earhian/imgclsmob/tree/c87c0942420876941868c016211073dec4392e4d |
Hsigmoid | import torch
import torch.nn as nn
import torch.utils.data
import torch.nn.functional as F
import torch.nn.parallel
import torch.optim
class Hsigmoid(nn.Module):
def __init__(self, inplace=True):
super(Hsigmoid, self).__init__()
self.inplace = inplace
def forward(self, x):
return F.r... | 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.utils.data
import torch.nn.parallel
import torch.optim... | AlbertiPot/once-for-all | Hsigmoid | false | 8,942 | [
"MIT"
] | 0 | 092b9e6184be353383396761ea5ec61d67152645 | https://github.com/AlbertiPot/once-for-all/tree/092b9e6184be353383396761ea5ec61d67152645 |
GCNAutoencoder | 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.nn.modules.loss
class GraphConvolutionDecoder(Module):
"""
Simple GCN layer, similar to https://arxiv.org/... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn import Module
i... | HongyiZhu/EHI | GCNAutoencoder | false | 559 | [
"MIT"
] | 0 | 9fbbc6046546dd7fc6de5d831b4c941bc4404e02 | https://github.com/HongyiZhu/EHI/tree/9fbbc6046546dd7fc6de5d831b4c941bc4404e02 |
depthwise_clipseg_conv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | Zacchaeus14/lang-seg | depthwise_clipseg_conv | false | 9,759 | [
"MIT"
] | 0 | ad1196a4d33830f3219dbe2260a69364a745f094 | https://github.com/Zacchaeus14/lang-seg/tree/ad1196a4d33830f3219dbe2260a69364a745f094 |
PatchEmbed | # 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 itertools import chain as chain
import torch.utils.data
import torch.nn as ... | Drill-D/SlowFast | PatchEmbed | false | 2,231 | [
"Apache-2.0"
] | 0 | d55ae1cf30a9415858a9bd5da983790a2b418653 | https://github.com/Drill-D/SlowFast/tree/d55ae1cf30a9415858a9bd5da983790a2b418653 |
LandmarkHead | import torch
import torch.nn as nn
from itertools import product as product
class LandmarkHead(nn.Module):
def __init__(self, inchannels=512, num_anchors=3):
super(LandmarkHead, self).__init__()
self.conv1x1 = nn.Conv2d(inchannels, num_anchors * 10, kernel_size=
(1, 1), stride=1, padd... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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 itertools import product as product
assert_size_strid... | Juggernaut93/InsightFace-v2 | LandmarkHead | false | 743 | [
"Apache-2.0"
] | 0 | 65e9b8d1f285a87472ffb913bec136d4e046798f | https://github.com/Juggernaut93/InsightFace-v2/tree/65e9b8d1f285a87472ffb913bec136d4e046798f |
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