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 |
|---|---|---|---|---|---|---|---|---|---|---|
Critic | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
class Critic(nn.Module):
def __init__(self, state_dim, action_dim):
super(Critic, self).__init__()
self.l1 = nn.Linear(state_dim + action_dim, 400)
self.l2 = nn.Linear(400, 300)
self.l3 = 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
import torch.nn as nn
import ... | Altriaex/d4rl_evaluations | Critic | false | 8,956 | [
"Apache-2.0"
] | 0 | ceb34c04e98af9332c6338a1414c0c2aa5fea68b | https://github.com/Altriaex/d4rl_evaluations/tree/ceb34c04e98af9332c6338a1414c0c2aa5fea68b |
Critic | import torch
import torch.nn as nn
import torch.nn.functional as F
class Critic(nn.Module):
"""
Args:
state_size: state dimension
action_size: action dimension
fc_units: number of neurons in one fully connected hidden layer
"""
def __init__(self, state_size, action_size, seed,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | LuckierDodge/ROS_Dockerfiles | Critic | false | 2,607 | [
"MIT"
] | 0 | 42fd0e7ecfef86d792fcc29197fcd79dcb789122 | https://github.com/LuckierDodge/ROS_Dockerfiles/tree/42fd0e7ecfef86d792fcc29197fcd79dcb789122 |
UpsampleBlock | import torch
import torch.nn as nn
import torch.optim
import torch.utils.data
import torch.backends.cudnn
class UpsampleBlock(nn.Module):
def __init__(self):
super().__init__()
self.conv = nn.Conv2d(64, 256, 3, 1, 1)
self.shuffle = nn.PixelShuffle(2)
self.relu = nn.ReLU()
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
import torch.nn as nn
import ... | Divyanshu23/model-zoo | UpsampleBlock | false | 8,114 | [
"MIT"
] | 43 | 2eea6df691d302e182bb1ff8ec5af3542de562ba | https://github.com/Divyanshu23/model-zoo/tree/2eea6df691d302e182bb1ff8ec5af3542de562ba |
layer_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
import numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | HyTruongSon/InvariantGraphNetworks-PyTorch | layer_basic | false | 17,435 | [
"Apache-2.0"
] | 7 | da9fdaa4f858d6fcae14b08a59d4b172a2aabaf8 | https://github.com/HyTruongSon/InvariantGraphNetworks-PyTorch/tree/da9fdaa4f858d6fcae14b08a59d4b172a2aabaf8 |
BothContextGate | # 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 ... | PiescesHusky/OpenNMT-py | BothContextGate | false | 11,779 | [
"MIT"
] | 0 | 7276cf94f989c50b3169742f64e64142897d1ec0 | https://github.com/PiescesHusky/OpenNMT-py/tree/7276cf94f989c50b3169742f64e64142897d1ec0 |
FusedLeakyReLU | # 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 import nn
from torch.nn import functional as F
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda... | Liamkuo/SAIR | FusedLeakyReLU | false | 17,570 | [
"MIT"
] | 6 | 0fb289cd975b5a196b58e7d16bac00e31fd41d39 | https://github.com/Liamkuo/SAIR/tree/0fb289cd975b5a196b58e7d16bac00e31fd41d39 |
ada_mask | import torch
import torch.nn as nn
import torch.nn.functional as F
class ResBlock(nn.Module):
def __init__(self, in_channel, out_channel, ker_size, stri, pad):
super(ResBlock, self).__init__()
self.conv1 = nn.Conv2d(in_channel, out_channel, 3, 1, 1)
self.conv2 = nn.Conv2d(out_channel, 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 import triton_helpers
import torch.nn as nn
import ... | NJUVISION/AWnet | ada_mask | false | 8,659 | [
"MIT"
] | 16 | f47a1692819a778b513b882d36ed727f7732d37b | https://github.com/NJUVISION/AWnet/tree/f47a1692819a778b513b882d36ed727f7732d37b |
TripletLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class TripletLoss(nn.Module):
"""
Triplet loss
Takes embeddings of an anchor sample, a positive sample and a negative sample
"""
def __init__(self, margin=4.0, size_average=True):
super(TripletLoss, self).__init__()
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | MikeLagunes/Supervised-Triplet-Network | TripletLoss | false | 17,713 | [
"MIT"
] | 6 | 575bcaf8f17affb0ff0e93212dde0f3f634c196f | https://github.com/MikeLagunes/Supervised-Triplet-Network/tree/575bcaf8f17affb0ff0e93212dde0f3f634c196f |
IDiv | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
@triton.jit
def triton_poi_fused_div_0(in_ptr0, in_ptr1, out_ptr1, xnumel,... | Ilyabasharov/torch2trt | IDiv | false | 2,529 | [
"MIT"
] | 0 | 76bf298b3da408509665e23e2494922b131afb10 | https://github.com/Ilyabasharov/torch2trt/tree/76bf298b3da408509665e23e2494922b131afb10 |
GeometryFeature | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.asser... | maciej-3/PENet_ICRA2021 | GeometryFeature | false | 15,986 | [
"MIT"
] | 155 | 40b5b20fb5d64455f8964045204fa9e7629d0c8c | https://github.com/maciej-3/PENet_ICRA2021/tree/40b5b20fb5d64455f8964045204fa9e7629d0c8c |
SequenceBias | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
import torch.utils.data.distributed
import torch.nn.parallel
from torch.nn.parameter import Pa... | adriansarstedt/opacus | SequenceBias | false | 12,056 | [
"Apache-2.0"
] | 0 | a6c89e3d6a3a4e3e4b82bc8c68d53265a9a7cba1 | https://github.com/adriansarstedt/opacus/tree/a6c89e3d6a3a4e3e4b82bc8c68d53265a9a7cba1 |
FeedForward | # 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_... | Daniangio/pheno_phases | FeedForward | false | 11,324 | [
"MIT"
] | 0 | c7229f4ec56fea42988768b02e8deb8615f683fa | https://github.com/Daniangio/pheno_phases/tree/c7229f4ec56fea42988768b02e8deb8615f683fa |
_DenseBlockInput | import torch
import torch.nn as nn
class _DenseLayer(nn.Sequential):
"""One dense layer within dense block, with bottleneck design.
Args:
in_features (int):
growth_rate (int): # out feature maps of every dense layer
drop_rate (float):
bn_size (int): Specifies maximum # feature... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | KyleDavisSA/pde-surrogate | _DenseBlockInput | false | 13,972 | [
"MIT"
] | 62 | 41ad2c9eb73c323e389174080f4b3df6cbd3c900 | https://github.com/KyleDavisSA/pde-surrogate/tree/41ad2c9eb73c323e389174080f4b3df6cbd3c900 |
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.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | andreas-hommel/glow | SimpleStackModel | false | 3,368 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
SuperPointNet | # 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.... | Merical/pytorch-superpoint | SuperPointNet | false | 2,697 | [
"MIT"
] | 0 | b1f6e587b0f68a8a647773e4128b4f504edb4d58 | https://github.com/Merical/pytorch-superpoint/tree/b1f6e587b0f68a8a647773e4128b4f504edb4d58 |
LatentAtten | import math
import torch
import torch.nn as nn
class LatentAtten(nn.Module):
"""
Attention on latent representation
"""
def __init__(self, h_dim, key_dim=None) ->None:
super(LatentAtten, self).__init__()
if key_dim is None:
key_dim = h_dim
self.key_dim = key_dim
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | AdityaLab/EpiFNP | LatentAtten | false | 4,799 | [
"MIT"
] | 1 | 476c7a40ee70fffb77b76c60c42a58adf82c62f6 | https://github.com/AdityaLab/EpiFNP/tree/476c7a40ee70fffb77b76c60c42a58adf82c62f6 |
Model | import torch
import torch.nn as nn
class Model(nn.Module):
def __init__(self, input_dim, hidden_dim, output_dim):
super(Model, self).__init__()
self.layer1 = nn.Linear(input_dim, hidden_dim)
self.sigmoid = nn.Sigmoid()
self.layer2 = nn.Linear(hidden_dim, output_dim)
def forwa... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | AyushSomani001/CreditCardFraud | Model | false | 11,223 | [
"MIT"
] | 0 | 015d4992e543889edb6a47ba13d997ace8d1c51c | https://github.com/AyushSomani001/CreditCardFraud/tree/015d4992e543889edb6a47ba13d997ace8d1c51c |
ChannelScale | import torch
import torch.nn as nn
def channel_scale(image):
img = image.flatten(2)
vmin = img.min(-1)[0][:, :, None, None]
vmax = img.max(-1)[0][:, :, None, None]
return (image - vmin) / (vmax - vmin + 1e-06)
class ChannelScale(nn.Module):
def forward(self, image):
return channel_scale... | 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... | rlmwang/torch-tools | ChannelScale | false | 10,796 | [
"MIT"
] | 0 | 822132534d73414f26045bad38a0a345661b057f | https://github.com/rlmwang/torch-tools/tree/822132534d73414f26045bad38a0a345661b057f |
TransposeGatedConv2d | import torch
import torch.nn as nn
from torch.nn import functional as F
from torch.nn import Parameter
def l2normalize(v, eps=1e-12):
return v / (v.norm() + eps)
class LayerNorm(nn.Module):
def __init__(self, num_features, eps=1e-08, affine=True):
super(LayerNorm, self).__init__()
self.num_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | piggy2303/DeepFillv2_Pytorch | TransposeGatedConv2d | false | 7,479 | [
"MIT"
] | 1 | dd35299f11704f878ed7a33e14ccd51a9d64baaf | https://github.com/piggy2303/DeepFillv2_Pytorch/tree/dd35299f11704f878ed7a33e14ccd51a9d64baaf |
ReduceMinModule | import torch
class ReduceMinModule(torch.nn.Module):
def __init__(self):
super(ReduceMinModule, self).__init__()
def forward(self, x):
return torch.min(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 import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | MichaelZhero/nncase | ReduceMinModule | false | 11,932 | [
"Apache-2.0"
] | 0 | 0fae6ce90d7adff386e1a286cd2b42422f4b850a | https://github.com/MichaelZhero/nncase/tree/0fae6ce90d7adff386e1a286cd2b42422f4b850a |
SplitCosineLinear | # 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.... | mhd-medfa/class-incremental-learning | SplitCosineLinear | false | 16,039 | [
"MIT"
] | 241 | c7c0a217d07b285f215672b3021beee52d4ef74f | https://github.com/mhd-medfa/class-incremental-learning/tree/c7c0a217d07b285f215672b3021beee52d4ef74f |
CosineBasisLinear | import torch
import numpy as np
import torch.nn as nn
def cosine_basis_functions(x, n_basis_functions=64):
"""Cosine basis functions used to embed quantile thresholds.
Args:
x (torch.Tensor): Input.
n_basis_functions (int): Number of cosine basis functions.
Returns:
ndarray: Embe... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | imatge-upc/pixelcoordEDL | CosineBasisLinear | false | 6,863 | [
"MIT"
] | 1 | 353632feed6ac8c93758c1a2a1b7a477e7ff053c | https://github.com/imatge-upc/pixelcoordEDL/tree/353632feed6ac8c93758c1a2a1b7a477e7ff053c |
TerConv2d | import torch
import numpy as np
from itertools import product as product
import torch.nn.functional as F
from torch import nn
import torch.optim
import torch.utils.data
def ternary_threshold(delta: 'float'=0.7, *ws):
"""Ternary threshold find in ws."""
assert isinstance(delta, float)
num_params = sum_w = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | ninfueng/a-PyTorch-Tutorial-to-Object-Detection | TerConv2d | false | 10,637 | [
"MIT"
] | 0 | fc7544720a7e939f5a56f4f7214e4965b7775f77 | https://github.com/ninfueng/a-PyTorch-Tutorial-to-Object-Detection/tree/fc7544720a7e939f5a56f4f7214e4965b7775f77 |
OuterProductLayer | import torch
import torch.nn as nn
class OuterProductLayer(nn.Module):
"""OuterProduct Layer used in PNN. This implementation is
adapted from code that the author of the paper published on https://github.com/Atomu2014/product-nets.
"""
def __init__(self, num_feature_field, embedding_size, device):
... | 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... | dreaming-qin/RecBole | OuterProductLayer | false | 12,329 | [
"MIT"
] | 0 | d6de39521484ded60c387ca604abaf86310acdbe | https://github.com/dreaming-qin/RecBole/tree/d6de39521484ded60c387ca604abaf86310acdbe |
Conv1d | # 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... | Jackson-Kang/VQVC-Pytorch | Conv1d | false | 8,318 | [
"MIT"
] | 13 | d2267b5c52253b6ae11a5767963a65320ae335c2 | https://github.com/Jackson-Kang/VQVC-Pytorch/tree/d2267b5c52253b6ae11a5767963a65320ae335c2 |
MaskNorm | # 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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | swpang/xray-align-AR | MaskNorm | false | 13,014 | [
"MIT"
] | 0 | 43cb0173ada9d1d71a6a923d605cb6fdae4d27aa | https://github.com/swpang/xray-align-AR/tree/43cb0173ada9d1d71a6a923d605cb6fdae4d27aa |
SelfAttentive | import torch
import torch.nn as nn
from sklearn.metrics import *
class SelfAttentive(nn.Module):
def __init__(self, hidden_size, att_hops=1, att_unit=200, dropout=0.2):
super(SelfAttentive, self).__init__()
self.drop = nn.Dropout(dropout)
self.ws1 = nn.Linear(hidden_size, att_unit, bias=F... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Dio990521/LSTM_emo_classifier | SelfAttentive | false | 5,192 | [
"MIT"
] | 1 | aaf2bf2d6a3e60c1acfcff5b82ab256f86ba0dbc | https://github.com/Dio990521/LSTM_emo_classifier/tree/aaf2bf2d6a3e60c1acfcff5b82ab256f86ba0dbc |
Bias | # 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... | SheldonTsui/Minus-Plus-Network | Bias | false | 17,909 | [
"Apache-2.0"
] | 5 | 7aa281b17f637a9f168aaf250039e560027a3817 | https://github.com/SheldonTsui/Minus-Plus-Network/tree/7aa281b17f637a9f168aaf250039e560027a3817 |
MSEScalarLoss | # 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... | Zhaoyi-Yan/PFDNet | MSEScalarLoss | false | 18,186 | [
"MIT"
] | 4 | 86798fbc4fadc673e7912c08492ea3611bc20154 | https://github.com/Zhaoyi-Yan/PFDNet/tree/86798fbc4fadc673e7912c08492ea3611bc20154 |
Decoder1 | # 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.... | MingSun-Tse/Collaborative-Distillation | Decoder1 | false | 14,016 | [
"MIT"
] | 172 | 915712674af82ff91d926d922c14988cce0430f3 | https://github.com/MingSun-Tse/Collaborative-Distillation/tree/915712674af82ff91d926d922c14988cce0430f3 |
FocalLoss | import torch
import torch.nn as nn
class FocalLoss(nn.Module):
def __init__(self, gamma=2, eps=1e-07, size_average=True):
super(FocalLoss, self).__init__()
self.gamma = gamma
self.eps = eps
self.size_average = size_average
def forward(self, prob, labels):
p_t = prob *... | 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
... | Dong-JinKim/ActionCooccurrencePriors | FocalLoss | false | 7,970 | [
"MIT"
] | 27 | 110dbeecf4c25955b5b0160bd7d31d25c759ef21 | https://github.com/Dong-JinKim/ActionCooccurrencePriors/tree/110dbeecf4c25955b5b0160bd7d31d25c759ef21 |
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
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
im... | autocomic/deepfillv2 | GatedConv2d | false | 12,136 | [
"MIT"
] | 0 | 4b0f565accbf20ee90093a4504b1cff0099d9cb9 | https://github.com/autocomic/deepfillv2/tree/4b0f565accbf20ee90093a4504b1cff0099d9cb9 |
SoftCrossEntropyLoss2d | # 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.... | hainguyen15/GLNet | SoftCrossEntropyLoss2d | false | 12,484 | [
"MIT"
] | 0 | dc5d2d000a37e9415f742ed04b7e99973a068279 | https://github.com/hainguyen15/GLNet/tree/dc5d2d000a37e9415f742ed04b7e99973a068279 |
Down | import torch
import torch.nn as nn
import torch.nn.functional as F
class Down(nn.Module):
def __init__(self, in_channels, out_channels, factor=2):
super(Down, self).__init__()
self.down = nn.Conv2d(in_channels, out_channels, kernel_size=3,
stride=factor, padding=1)
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.triton_helpers import libdevice
import torch.nn as ... | Smith42/unet-pytorch | Down | false | 9,551 | [
"MIT"
] | 0 | 45a0459da69cee7f57fb369a8e2fc58668d81167 | https://github.com/Smith42/unet-pytorch/tree/45a0459da69cee7f57fb369a8e2fc58668d81167 |
FilterResponseNormNd | import torch
import torch.nn as nn
import torch.utils.data.distributed
class FilterResponseNormNd(nn.Module):
def __init__(self, ndim, num_features, eps=1e-06, learnable_eps=False):
"""
Input Variables:
----------------
ndim: An integer indicating the number of dimensions of 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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | aouedions11/SSFL-Benchmarking-Semi-supervised-Federated-Learning | FilterResponseNormNd | false | 6,234 | [
"MIT"
] | 1 | 78aec81919bf95ed4677d0e0a4ebbbe3be455742 | https://github.com/aouedions11/SSFL-Benchmarking-Semi-supervised-Federated-Learning/tree/78aec81919bf95ed4677d0e0a4ebbbe3be455742 |
Classifier | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from abc import *
assert_size_stride = torch._C._dynamo.gu... | Slime0519/simple-faster-rcnn-pytorch | Classifier | false | 1,065 | [
"MIT"
] | 0 | 0503e9b4d07a24ae0bc1789a61ed937709f5304c | https://github.com/Slime0519/simple-faster-rcnn-pytorch/tree/0503e9b4d07a24ae0bc1789a61ed937709f5304c |
teacherNet | # 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_... | kamiyakenta/knowledge-distillation-pytorch | teacherNet | false | 3,798 | [
"MIT"
] | 0 | 749c6bb353961147718371b2b694046af0a6e3f1 | https://github.com/kamiyakenta/knowledge-distillation-pytorch/tree/749c6bb353961147718371b2b694046af0a6e3f1 |
ConvNCFBPRLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | dreaming-qin/RecBole | ConvNCFBPRLoss | false | 12,313 | [
"MIT"
] | 0 | d6de39521484ded60c387ca604abaf86310acdbe | https://github.com/dreaming-qin/RecBole/tree/d6de39521484ded60c387ca604abaf86310acdbe |
TwoMLPHead | import torch
from torch import nn
import torch.nn.functional as F
class TwoMLPHead(nn.Module):
"""
Standard heads for FPN-based models
Arguments:
in_channels (int): number of input channels
representation_size (int): size of the intermediate representation
"""
def __init__(self, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | GreenCUBIC/Gas-Prices-of-America | TwoMLPHead | false | 2,335 | [
"MIT"
] | 0 | e2a045db99d061b5d2acbe208da8cc19af12659d | https://github.com/GreenCUBIC/Gas-Prices-of-America/tree/e2a045db99d061b5d2acbe208da8cc19af12659d |
ReLUDeepLiftModel | # 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... | YNNEKUW/captum | ReLUDeepLiftModel | false | 11,981 | [
"BSD-3-Clause"
] | 0 | c8b5357b21f2ddf440e5f0ce25635977292aa5d1 | https://github.com/YNNEKUW/captum/tree/c8b5357b21f2ddf440e5f0ce25635977292aa5d1 |
Actor | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import numpy as np
... | SriramPingali/P3_collaborate_complete | Actor | false | 11,900 | [
"MIT"
] | 0 | 66df22c9eb7577b15adcaa7bbc1796dbd333af2e | https://github.com/SriramPingali/P3_collaborate_complete/tree/66df22c9eb7577b15adcaa7bbc1796dbd333af2e |
BatchNormDense | import torch
import torch.nn as nn
from torch.nn.parameter import Parameter
class BatchNormDense(nn.Module):
def __init__(self, num_features, eps=1e-08):
super().__init__()
self.num_features = num_features
self.eps = eps
self.gamma = Parameter(torch.Tensor(num_features))
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
from torch.nn.parameter import Parameter
assert_size_stri... | jkoscialkowski/dnn-exercises | BatchNormDense | false | 6,957 | [
"MIT"
] | 1 | 5d1616fce1b461e39858c68279d2fafefab00a56 | https://github.com/jkoscialkowski/dnn-exercises/tree/5d1616fce1b461e39858c68279d2fafefab00a56 |
GeneralRelu | import torch
from torch import nn
import torch.nn.functional as F
from typing import *
class GeneralRelu(nn.Module):
def __init__(self, leak=None, sub=None, maxv=None):
super().__init__()
self.leak, self.sub, self.maxv = leak, sub, maxv
def forward(self, x):
x = F.leaky_relu(x, 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 import triton_helpers
from torch import nn
from typing import *
assert_size_stride = torch._C._dynamo.guards.as... | ImadDabbura/fastai-courses | GeneralRelu | false | 17,430 | [
"Apache-2.0"
] | 3 | 053637a2dd3b4ad6c35f97a13f3fba87af1d3940 | https://github.com/ImadDabbura/fastai-courses/tree/053637a2dd3b4ad6c35f97a13f3fba87af1d3940 |
SPPblock | import torch
import torch.nn as nn
import torch.nn.functional as F
class SPPblock(nn.Module):
def __init__(self, in_channels):
super(SPPblock, self).__init__()
self.pool1 = nn.MaxPool2d(kernel_size=[2, 2], stride=2)
self.pool2 = nn.MaxPool2d(kernel_size=[3, 3], stride=3)
self.pool... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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_... | coolservices/rock-fracture-identification | SPPblock | false | 3,328 | [
"Apache-2.0"
] | 0 | 3e7349be7e76dc87800c630f53f8d1ad5673d28b | https://github.com/coolservices/rock-fracture-identification/tree/3e7349be7e76dc87800c630f53f8d1ad5673d28b |
GaussianSubnetBlock | # 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... | laitalaj/cvpce | GaussianSubnetBlock | false | 7,064 | [
"MIT"
] | 1 | 7509e7d7783039f39a88edc6e411333bcf6fb2af | https://github.com/laitalaj/cvpce/tree/7509e7d7783039f39a88edc6e411333bcf6fb2af |
VisErrorLossV3 | # 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... | gathierry/FashionAI-KeyPointsDetectionOfApparel | VisErrorLossV3 | false | 15,434 | [
"Apache-2.0"
] | 174 | 2e0942b42b4a9cd974cdddc151675738dc8a8cb4 | https://github.com/gathierry/FashionAI-KeyPointsDetectionOfApparel/tree/2e0942b42b4a9cd974cdddc151675738dc8a8cb4 |
Attention | import torch
import torch.nn as nn
import torch.utils
import torch.nn.functional as F
import torch.optim
import torch.utils.data
import torch.onnx.operators
class Attention(nn.Module):
def __init__(self, input_dim, source_dim=None, output_dim=None, bias=False
):
super(Attention, self).__init__()
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | PeterouZh/SemiNAS | Attention | false | 17,819 | [
"Apache-2.0"
] | 5 | 39731663271b994571160d43d796b2bb93386b3b | https://github.com/PeterouZh/SemiNAS/tree/39731663271b994571160d43d796b2bb93386b3b |
RobertaClassificationHead | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class RobertaClassificationHead(nn.Module):
"""Head for sentence-level classification tasks."""
def __init__(self, config):
super(RobertaClassificationHead, self).__init__()
self.dense = nn.Linear(config.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.triton_helpers import libdevice
import torch.nn as ... | AkariAsai/logic_guided_qa | RobertaClassificationHead | false | 14,568 | [
"MIT"
] | 69 | 96ae70f01b7267ef0b472b8497c903035d052fd9 | https://github.com/AkariAsai/logic_guided_qa/tree/96ae70f01b7267ef0b472b8497c903035d052fd9 |
MergeBlok | import torch
from torch import nn
import torch.nn.functional as F
class MergeBlok(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_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 | MergeBlok | false | 16,336 | [
"MIT"
] | 49 | 225844770e0107817be9fb86d53f873fa3eb07ae | https://github.com/robtu328/TextBPN/tree/225844770e0107817be9fb86d53f873fa3eb07ae |
kAttentionPooling | # 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.... | BELIEVEfxy/LightSANs | kAttentionPooling | false | 7,782 | [
"MIT"
] | 17 | 94ce7e59d144dbc787153b8c486cad334790ec6e | https://github.com/BELIEVEfxy/LightSANs/tree/94ce7e59d144dbc787153b8c486cad334790ec6e |
GlobalAveragePooling | import torch
import torch.nn as nn
class GlobalAveragePooling(nn.Module):
"""Global Average Pooling neck.
Note that we use `view` to remove extra channel after pooling. We do not
use `squeeze` as it will also remove the batch dimension when the tensor
has a batch dimension of size 1, which can lead 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | Jackqu/mmpose | GlobalAveragePooling | false | 8,368 | [
"Apache-2.0"
] | 38 | ad8acc5ff5da7993c6befdc4b1ced2c2ecb64533 | https://github.com/Jackqu/mmpose/tree/ad8acc5ff5da7993c6befdc4b1ced2c2ecb64533 |
SoftAttention | # 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.... | Doomski99/MarcCoru2019CropType | SoftAttention | false | 11,380 | [
"MIT"
] | 0 | 17db294ef51bdd39fd884e0052141d8092b98b86 | https://github.com/Doomski99/MarcCoru2019CropType/tree/17db294ef51bdd39fd884e0052141d8092b98b86 |
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... | connorlee77/kornia | Rot180 | false | 6,476 | [
"ECL-2.0",
"Apache-2.0"
] | 1 | af5b1f76bedf2a7fc0e0da2386b1be3032b6534f | https://github.com/connorlee77/kornia/tree/af5b1f76bedf2a7fc0e0da2386b1be3032b6534f |
SmallDecoder1_16x | import torch
import torch.nn as nn
class SmallDecoder1_16x(nn.Module):
def __init__(self, model=None, fixed=False):
super(SmallDecoder1_16x, self).__init__()
self.fixed = fixed
self.conv11 = nn.Conv2d(24, 3, 3, 1, 0, dilation=1)
self.relu = nn.ReLU(inplace=True)
self.pad =... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | MingSun-Tse/Collaborative-Distillation | SmallDecoder1_16x | false | 14,015 | [
"MIT"
] | 172 | 915712674af82ff91d926d922c14988cce0430f3 | https://github.com/MingSun-Tse/Collaborative-Distillation/tree/915712674af82ff91d926d922c14988cce0430f3 |
MLP3_clamp_train | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
class MLP3_clamp_train(nn.Module):
"""
For unary training, activation clamp is better to be after relu.
no difference for inference whe... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | RuokaiYin/UnarySim | MLP3_clamp_train | false | 5,781 | [
"MIT"
] | 1 | 343ff9abf356a63d526b1df8eb946ad528690a27 | https://github.com/RuokaiYin/UnarySim/tree/343ff9abf356a63d526b1df8eb946ad528690a27 |
ActorCriticMLP | import torch
from torch import Tensor
from torch import nn
from typing import Tuple
from torch.nn import functional as F
class ActorCriticMLP(nn.Module):
"""MLP network with heads for actor and critic."""
def __init__(self, input_shape: 'Tuple[int]', n_actions: 'int',
hidden_size: 'int'=128):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | kfirgedal/lightning-bolts | ActorCriticMLP | false | 12,665 | [
"Apache-2.0"
] | 0 | cbb8b6c21ca1de757d0f289fb840d59a3b6a10f5 | https://github.com/kfirgedal/lightning-bolts/tree/cbb8b6c21ca1de757d0f289fb840d59a3b6a10f5 |
MaskedInstanceNorm1d | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.cuda
from torch... | carolmanderson/NeMo | MaskedInstanceNorm1d | false | 6,394 | [
"Apache-2.0"
] | 1 | be7114e2d983af751e1af4119465c626682747b7 | https://github.com/carolmanderson/NeMo/tree/be7114e2d983af751e1af4119465c626682747b7 |
Unet | import torch
import torch.nn as nn
class ConvBlock(nn.Module):
def __init__(self, in_channels, out_channels, dropout=False, norm=
'batch', residual=True, activation='leakyrelu', transpose=False):
super(ConvBlock, self).__init__()
self.dropout = dropout
self.residual = residual
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | tim-vdl/noise2self | Unet | false | 11,056 | [
"MIT"
] | 0 | 2cf10d20d988dc7b6c1278150f170aa3e3335b28 | https://github.com/tim-vdl/noise2self/tree/2cf10d20d988dc7b6c1278150f170aa3e3335b28 |
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
from torch import nn
a... | h8c2/kaggle-landmark-recognition-2020-1st-place | FocalLoss | false | 10,158 | [
"MIT"
] | 0 | 3285b6c9548d100b14800ea3927f5974b25facd9 | https://github.com/h8c2/kaggle-landmark-recognition-2020-1st-place/tree/3285b6c9548d100b14800ea3927f5974b25facd9 |
FocalLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class FocalLoss(nn.modules.loss._WeightedLoss):
def __init__(self, weight=None, gamma=2, reduction='mean'):
super(FocalLoss, self).__init__(weight, reduction=reduction)
self.gamma = gamma
self.weight = weight
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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | aydindemircioglu/knee.lat | FocalLoss | false | 1,504 | [
"MIT"
] | 0 | 555725222f860d4ad8fea7452685803d9e323d43 | https://github.com/aydindemircioglu/knee.lat/tree/555725222f860d4ad8fea7452685803d9e323d43 |
ScaleNorm | # 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 math
import torch.nn ... | nigelnnk/MATCh-sensitivity | ScaleNorm | false | 7,341 | [
"MIT"
] | 1 | aaf2b924ac98c8c5925bbf431481724d11a102f8 | https://github.com/nigelnnk/MATCh-sensitivity/tree/aaf2b924ac98c8c5925bbf431481724d11a102f8 |
BoundSin | from _paritybench_helpers import _mock_config
import math
import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
from numbers import Number
from torch.nn import MSELoss
def isnan(x):
if isinstance(x, Patches):
return False
return torch.isnan(x).any()
class Perturbation... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import math
import numpy as np
import torch.nn as nn
import torch.nn.func... | Mahoumaru/auto_LiRPA | BoundSin | false | 11,758 | [
"BSD-3-Clause"
] | 0 | b03a6c36eb1b921726778359d6d2b94e0cd7e480 | https://github.com/Mahoumaru/auto_LiRPA/tree/b03a6c36eb1b921726778359d6d2b94e0cd7e480 |
SELU | # 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
from torch.autograd import Variable
import torch.nn.funct... | dearkafka/inferno | SELU | false | 1,829 | [
"Apache-2.0"
] | 0 | e9e3b863fd1fc97cf94d08ac6b4f8df7665f996a | https://github.com/dearkafka/inferno/tree/e9e3b863fd1fc97cf94d08ac6b4f8df7665f996a |
CQAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
def mask_logits(target, mask):
mask = mask.type(torch.float32)
return target * mask + (1 - mask) * -1e+30
class CQAttention(nn.Module):
def __init__(self, d_model, dropout=0.1):
super().__init__()
w4C = torch.empty(d_mod... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | timgianitsos/squad | CQAttention | false | 13,197 | [
"MIT"
] | 0 | 6ab502652e3528cfeeddfb8eba05221443a35294 | https://github.com/timgianitsos/squad/tree/6ab502652e3528cfeeddfb8eba05221443a35294 |
TwoLayerFCBodyWithAction | import torch
import torch.optim
import torch.nn as nn
import torch.nn.functional as F
def layer_init(layer, w_scale=1.0):
nn.init.orthogonal_(layer.weight.data)
layer.weight.data.mul_(w_scale)
nn.init.constant_(layer.bias.data, 0)
return layer
class TwoLayerFCBodyWithAction(nn.Module):
def __in... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.optim
import tor... | DMIU-ShELL/deeprl-shell | TwoLayerFCBodyWithAction | false | 9,096 | [
"Apache-2.0"
] | 0 | a7845ab1c4967ba2af9486625086c3d0b176d293 | https://github.com/DMIU-ShELL/deeprl-shell/tree/a7845ab1c4967ba2af9486625086c3d0b176d293 |
FBACompLoss | import functools
import torch
import torch.nn as nn
from torch.nn import functional as F
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Returns:
Tensor: Reduced lo... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import functools
impor... | yaochaorui/mmediting | FBACompLoss | false | 4,607 | [
"Apache-2.0"
] | 0 | e292abd1f86b1560856d8c4e8c40ababe8a90630 | https://github.com/yaochaorui/mmediting/tree/e292abd1f86b1560856d8c4e8c40ababe8a90630 |
Layer | # 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_... | kw-lee/VIforSDEs | Layer | false | 3,866 | [
"MIT"
] | 0 | dcba3832aaad0aebc921a3b0628c43046d651629 | https://github.com/kw-lee/VIforSDEs/tree/dcba3832aaad0aebc921a3b0628c43046d651629 |
Transform | # 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.... | TimandXiyu/SANet-style-transfer- | Transform | false | 5,911 | [
"MIT"
] | 1 | 91c3dd1344d1dded61aa2e79618240a49345b40e | https://github.com/TimandXiyu/SANet-style-transfer-/tree/91c3dd1344d1dded61aa2e79618240a49345b40e |
RealConvTranspose2d | # 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... | JamesLiao714/FullSubNet | RealConvTranspose2d | false | 613 | [
"MIT"
] | 0 | dad740bac35b5d7544c97740ae59101455acdc40 | https://github.com/JamesLiao714/FullSubNet/tree/dad740bac35b5d7544c97740ae59101455acdc40 |
GELU | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.... | Aunsiels/qagnn | GELU | false | 11,307 | [
"MIT"
] | 0 | d89a3dd650ac4b8b8aae34e0cce7cfc698892d80 | https://github.com/Aunsiels/qagnn/tree/d89a3dd650ac4b8b8aae34e0cce7cfc698892d80 |
ModConst | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | NVIDIA-AI-IOT-private/torch2trt | ModConst | false | 10,518 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
Generator | # 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... | Jh-SYSU/MolRep | Generator | false | 13,884 | [
"MIT"
] | 57 | b2c802d18d41d7db26c19c6dd644098f945e48a1 | https://github.com/Jh-SYSU/MolRep/tree/b2c802d18d41d7db26c19c6dd644098f945e48a1 |
Lambda3 | import torch
from typing import Tuple
from torch import nn
from abc import ABC
from abc import abstractmethod
class Regularizer(nn.Module, ABC):
@abstractmethod
def forward(self, factors: 'Tuple[torch.Tensor]'):
pass
class Lambda3(Regularizer):
def __init__(self, weight: 'float'):
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.triton_helpers import libdevice
from typing import Tuple
from torch import nn
from abc import ABC
from abc impo... | apoorvumang/Temporal_KGQA | Lambda3 | false | 14,885 | [
"MIT"
] | 49 | 3e2a7c31865235ee2511a7ae0ea0701c12896327 | https://github.com/apoorvumang/Temporal_KGQA/tree/3e2a7c31865235ee2511a7ae0ea0701c12896327 |
DenseBlock | import torch
from torch import nn
from torch.nn import functional as F
class CausalConv1d(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size=2, dilation=2):
super(CausalConv1d, self).__init__()
self.padding = dilation
self.causal_conv = nn.Conv1d(in_channels, out_channe... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | gaetangate/FewRel | DenseBlock | false | 12,410 | [
"MIT"
] | 0 | 150199d1060571315b1f370b3b3352d7a7c72dd5 | https://github.com/gaetangate/FewRel/tree/150199d1060571315b1f370b3b3352d7a7c72dd5 |
Decoder | import math
import torch
from torch import nn
def overlap_and_add(signal, frame_step):
outer_dimensions = signal.size()[:-2]
frames, frame_length = signal.size()[-2:]
subframe_length = math.gcd(frame_length, frame_step)
subframe_step = frame_step // subframe_length
subframes_per_frame = frame_leng... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.as... | PanagiotisP/demucs | Decoder | false | 11,799 | [
"MIT"
] | 0 | d115d0773ca08a081f5b6bfe274cf0e4ed9e2677 | https://github.com/PanagiotisP/demucs/tree/d115d0773ca08a081f5b6bfe274cf0e4ed9e2677 |
ContrastiveEmbeddingLoss | import torch
import torch.nn as nn
from torch.nn.modules.loss import *
from torch.nn.modules import *
from torch.optim import *
from torch.optim.lr_scheduler import *
import torch.distributed
class ContrastiveEmbeddingLoss(nn.Module):
"""
Contrastive embedding loss
paper: http://yann.lecun.com/exdb/publi... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
from t... | bbradt/catalyst | ContrastiveEmbeddingLoss | false | 3,183 | [
"Apache-2.0"
] | 0 | 38a503c8af040906e377b7485d7fe15a7bc1de19 | https://github.com/bbradt/catalyst/tree/38a503c8af040906e377b7485d7fe15a7bc1de19 |
GraphConvolution | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn import Module
i... | JinmiaoChenLab/SEDR | GraphConvolution | false | 17,491 | [
"MIT"
] | 5 | 18616dfe2ecb56e22225ffefe949d353e819a7d8 | https://github.com/JinmiaoChenLab/SEDR/tree/18616dfe2ecb56e22225ffefe949d353e819a7d8 |
ConcatELU | # 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_... | ashutoshml/lightning-tutorials | ConcatELU | false | 6,237 | [
"Apache-2.0"
] | 1 | 898b8b6f9852c0b80f034a3187bc1cd34dd521ce | https://github.com/ashutoshml/lightning-tutorials/tree/898b8b6f9852c0b80f034a3187bc1cd34dd521ce |
Loss_D | # 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
from numpy import *
assert_size_stride = torch._C._... | ducviet00/HMER | Loss_D | false | 6,619 | [
"MIT"
] | 1 | 0fa322ed35412737a24ec3955c9a3d96d1989bd4 | https://github.com/ducviet00/HMER/tree/0fa322ed35412737a24ec3955c9a3d96d1989bd4 |
MNISTConvNet | import torch
from random import *
import torch.nn.functional as F
import torch.nn as nn
class MNISTConvNet(torch.nn.Module):
def __init__(self, num_conv_layers, num_filters_1, num_filters_2,
num_filters_3, dropout_rate, num_fc_units, kernel_size):
super().__init__()
self.conv1 = nn.Conv2d... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | xinranzhu/GPTune-1 | MNISTConvNet | false | 13,118 | [
"BSD-3-Clause-LBNL"
] | 0 | 1e502295e790ab68990f657492243fd4fb3dfc0a | https://github.com/xinranzhu/GPTune-1/tree/1e502295e790ab68990f657492243fd4fb3dfc0a |
L1GradLoss | # 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
... | JaguAroo/SRResCGAN | L1GradLoss | false | 590 | [
"MIT"
] | 0 | 9aac612aff631f7fb9142e0a36de9559cfc1a62d | https://github.com/JaguAroo/SRResCGAN/tree/9aac612aff631f7fb9142e0a36de9559cfc1a62d |
Upconv | import math
import torch
import torch.nn.functional as F
from torch.nn import Conv2d
from torch.nn import Upsample
class PadSameConv2d(torch.nn.Module):
def __init__(self, kernel_size, stride=1):
"""
Imitates padding_mode="same" from tensorflow.
:param kernel_size: Kernelsize of the convo... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.functional as F
from torch.nn import Conv2d
from tor... | shlomi-amitai/monorec | Upconv | false | 10,905 | [
"MIT"
] | 0 | 74571c6cd8d06ae4fb15cbee5a41147c54c78556 | https://github.com/shlomi-amitai/monorec/tree/74571c6cd8d06ae4fb15cbee5a41147c54c78556 |
MaxNormConstraintConv2d | import torch
import torch.nn as nn
class MaxNormConstraintConv2d(nn.Conv2d):
def __init__(self, *args, max_norm_value=1, norm_axis=2, **kwargs):
self.max_norm_value = max_norm_value
self.norm_axis = norm_axis
super().__init__(*args, **kwargs)
def forward(self, input):
self.we... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | Mrswolf/brainda | MaxNormConstraintConv2d | false | 8,583 | [
"MIT"
] | 24 | cbd2fa6334d9e6243324dbaf086be4eb4047e801 | https://github.com/Mrswolf/brainda/tree/cbd2fa6334d9e6243324dbaf086be4eb4047e801 |
ActionMapper | # 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.... | KuangenZhang/StructuredRL | ActionMapper | false | 5,453 | [
"MIT"
] | 1 | 9b05e5034ff0e045aabf83786efb0859f08e989a | https://github.com/KuangenZhang/StructuredRL/tree/9b05e5034ff0e045aabf83786efb0859f08e989a |
SpatialGather_Module | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim
import torch._utils
import torch.nn
class SpatialGather_Module(nn.Module):
"""
Aggregate the context features according to the initial
predicted probability distribution.
Employ the soft-weighted method t... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | ModelTC/EOD | SpatialGather_Module | false | 14,064 | [
"Apache-2.0"
] | 196 | 164bff80486e9ae6a095a97667b365c46ceabd86 | https://github.com/ModelTC/EOD/tree/164bff80486e9ae6a095a97667b365c46ceabd86 |
GeneralRelu | import torch
import torch.nn as nn
import torch.nn.functional as F
from typing import *
class GeneralRelu(nn.Module):
def __init__(self, leak=None, sub=None, maxv=None):
super().__init__()
self.leak, self.sub, self.maxv = leak, sub, maxv
def forward(self, x):
x = F.leaky_relu(x, 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 import triton_helpers
import torch.nn as nn
from typing import *
assert_size_stride = torch._C._dynamo.guards.a... | Cedric-Perauer/DL_from_Foundations | GeneralRelu | false | 11,278 | [
"Apache-2.0"
] | 0 | c53722216a088cc9f67a2e1bf955d043023e6a85 | https://github.com/Cedric-Perauer/DL_from_Foundations/tree/c53722216a088cc9f67a2e1bf955d043023e6a85 |
ComparisonModule | # 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... | kdexd/probnmn-clevr | ComparisonModule | false | 15,794 | [
"MIT"
] | 69 | 9c1b2286cf30e9fb045370153c9242a39760e02e | https://github.com/kdexd/probnmn-clevr/tree/9c1b2286cf30e9fb045370153c9242a39760e02e |
SELayer | # 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_... | LEGO999/pytorch_image_classification | SELayer | false | 2,477 | [
"MIT"
] | 0 | 2b9901fdff0620e39becad4db6adb6f88d251352 | https://github.com/LEGO999/pytorch_image_classification/tree/2b9901fdff0620e39becad4db6adb6f88d251352 |
SelfGated | # 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.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size... | xdong73S/Match_LSTM_v2.0 | SelfGated | false | 4,578 | [
"MIT"
] | 0 | dfb8cfbc2a5dafc6655eecf151a7dbcf808cd729 | https://github.com/xdong73S/Match_LSTM_v2.0/tree/dfb8cfbc2a5dafc6655eecf151a7dbcf808cd729 |
PositionalEncoding | # AOT ID: ['1_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... | OpenNLPhub/MRC_NER | PositionalEncoding | false | 17,769 | [
"MIT"
] | 4 | 27ca063764aed9eb5f2ac672bb10052acbf374a5 | https://github.com/OpenNLPhub/MRC_NER/tree/27ca063764aed9eb5f2ac672bb10052acbf374a5 |
NormalSamples | import torch
import torch.nn as nn
import torch.utils.checkpoint
def norm(x, axis=None, eps=1e-05):
if axis is not None:
return (x - x.mean(axis, True)) / (x.std(axis, keepdim=True) + eps)
else:
return (x - x.mean()) / (x.std() + eps)
class NormalSamples(nn.Module):
"""The [reparameteriz... | import torch
from torch import device
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.utils.checkpoint
as... | Antipurity/sensor-network | NormalSamples | false | 173 | [
"MIT"
] | 0 | c5cc67dee408da831c3ab60a03374da3c4789bd2 | https://github.com/Antipurity/sensor-network/tree/c5cc67dee408da831c3ab60a03374da3c4789bd2 |
QConv2d | import torch
from torch import Tensor
import torch.nn as nn
import torch.autograd as A
from torch.autograd.function import once_differentiable
from torch.nn.parameter import Parameter
import torch.nn.parallel
import torch.optim
import torch.utils.data
class WeightQuantization(A.Function):
@staticmethod
def f... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import Tensor
import torch.nn as nn
import torch.autograd as A
from t... | i207M/pytorch-cifar | QConv2d | false | 10,229 | [
"MIT"
] | 0 | df4417b6d0a25515ac82b5aa6151ae2135b2cd5c | https://github.com/i207M/pytorch-cifar/tree/df4417b6d0a25515ac82b5aa6151ae2135b2cd5c |
InnerProductLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class InnerProductLoss(nn.Module):
"""This is the inner-product loss used in CFKG for optimization.
"""
def __init__(self):
super(InnerProductLoss, self).__init__()
def forward(self, anchor, positive, negative):
pos_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, math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.gu... | MIracleyin/RecBole-notebook | InnerProductLoss | false | 9,613 | [
"MIT"
] | 0 | ef32b3e57a297ff4889dec1f63c7984f8f901a23 | https://github.com/MIracleyin/RecBole-notebook/tree/ef32b3e57a297ff4889dec1f63c7984f8f901a23 |
DPLSTMCell | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import ... | ffuuugor/opacus | DPLSTMCell | false | 6,695 | [
"Apache-2.0"
] | 1 | 2048a6e92902685c2a735e9fb7c0d48b4846b494 | https://github.com/ffuuugor/opacus/tree/2048a6e92902685c2a735e9fb7c0d48b4846b494 |
TwoHiddenLayerFc | # 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_... | bokunwang/fedavgpy | TwoHiddenLayerFc | false | 9,799 | [
"MIT"
] | 0 | 22f2fae287f15025e953ab595aa6fd6faedf83d2 | https://github.com/bokunwang/fedavgpy/tree/22f2fae287f15025e953ab595aa6fd6faedf83d2 |
TverskyLoss | # 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... | Elameri/ivadomed | TverskyLoss | false | 9,309 | [
"MIT"
] | 0 | 76b5cea46f90f938aafd5ec26e072d559c764b43 | https://github.com/Elameri/ivadomed/tree/76b5cea46f90f938aafd5ec26e072d559c764b43 |
ParityPonderGRU | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch import device
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import Module
from torch import nn
import... | mcx/annotated_deep_learning_paper_implementations | ParityPonderGRU | false | 7,233 | [
"MIT"
] | 1 | f169f3a71dd2d36eb28ad31062d3475efa367b88 | https://github.com/mcx/annotated_deep_learning_paper_implementations/tree/f169f3a71dd2d36eb28ad31062d3475efa367b88 |
DiceBCELoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class DiceBCELoss(nn.Module):
def __init__(self, weight=None, size_average=True):
super(DiceBCELoss, self).__init__()
def forward(self, inputs, targets, smooth=1):
inputs = torch.sigmoid(inputs)
inputs = inputs.view(-... | 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... | ProfessorHuang/2D-UNet-Pytorch | DiceBCELoss | false | 8,653 | [
"MIT"
] | 11 | b3941e8dc0ac3e76b6eedb656f943f1bd66fa799 | https://github.com/ProfessorHuang/2D-UNet-Pytorch/tree/b3941e8dc0ac3e76b6eedb656f943f1bd66fa799 |
distLinear | import torch
import torch.nn as nn
from torch.nn.utils.weight_norm import WeightNorm
import torch.optim
class distLinear(nn.Module):
def __init__(self, indim, outdim):
super(distLinear, self).__init__()
self.L = nn.Linear(indim, outdim, bias=False)
self.class_wise_learnable_norm = True
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | prabhat1081/self-supervision-cs221 | distLinear | false | 7,494 | [
"Apache-2.0"
] | 1 | 41912c01dd7bf44d45a27d7c715a8db2ee9bbc28 | https://github.com/prabhat1081/self-supervision-cs221/tree/41912c01dd7bf44d45a27d7c715a8db2ee9bbc28 |
_ResampleNorm | import torch
import torch.nn as nn
import torch.nn.functional as F
class _TimeDistributedInterpolation(nn.Module):
def __init__(self, output_size: 'int', batch_first: 'bool'=False,
trainable: 'bool'=False):
super().__init__()
self.output_size = output_size
self.batch_first = batch... | 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.functional as F
assert_size_stride = torc... | Gian-Wiher/darts | _ResampleNorm | false | 5,208 | [
"Apache-2.0"
] | 1 | 0d267e08643e2e3f88163a5d955b8be75840c2f6 | https://github.com/Gian-Wiher/darts/tree/0d267e08643e2e3f88163a5d955b8be75840c2f6 |
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