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 |
|---|---|---|---|---|---|---|---|---|---|---|
LinModel | # 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.... | Lisennlp/distributed_train_pytorch | LinModel | false | 17,578 | [
"Apache-2.0"
] | 10 | da43ac6b5f4484b5f7bc92e3c778539b9017cb82 | https://github.com/Lisennlp/distributed_train_pytorch/tree/da43ac6b5f4484b5f7bc92e3c778539b9017cb82 |
MuLawEncoding | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_strid... | tbright17/audio | MuLawEncoding | false | 10,919 | [
"BSD-2-Clause"
] | 0 | 00d38203e401b8d9472a8f8394a10e2c309be02c | https://github.com/tbright17/audio/tree/00d38203e401b8d9472a8f8394a10e2c309be02c |
BboxHead | import torch
from itertools import product as product
import torch.nn as nn
class BboxHead(nn.Module):
def __init__(self, inchannels=512, num_anchors=3):
super(BboxHead, self).__init__()
self.conv1x1 = nn.Conv2d(inchannels, num_anchors * 4, kernel_size=(
1, 1), stride=1, padding=0)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from itertools import product as product
import torch.nn as nn
assert_size_strid... | Jung-Jun-Uk/UNPG | BboxHead | false | 17,542 | [
"Apache-2.0"
] | 7 | a6f9c1731a68fc035eb8fe8198f5a5c643825a5b | https://github.com/Jung-Jun-Uk/UNPG/tree/a6f9c1731a68fc035eb8fe8198f5a5c643825a5b |
StdConv2d | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
import torchvision.transforms.functional as F
from torch.nn import functional as F
class StdConv2d(nn.Conv2d):
def forward(self, x):
w = self.weight
s = w.std(dim=[1, 2, 3], keepdim=True)
m = w.mean... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | BigFishMaster/tnt | StdConv2d | false | 17,510 | [
"BSD-3-Clause"
] | 3 | 8b80bb3b194eb87ac18924428ef0924c2fb263c5 | https://github.com/BigFishMaster/tnt/tree/8b80bb3b194eb87ac18924428ef0924c2fb263c5 |
resBlock | # 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.... | SeokjaeLIM/DSSN_release-Pytorch | resBlock | false | 17,897 | [
"Apache-2.0"
] | 7 | fef1dac120d7b83367b4c69f239b089ab5f004d7 | https://github.com/SeokjaeLIM/DSSN_release-Pytorch/tree/fef1dac120d7b83367b4c69f239b089ab5f004d7 |
Network | import torch
import torch.nn as nn
import torch.nn.functional as F
class Network(nn.Module):
def __init__(self, n_feature, n_hidden, n_output):
super(Network, self).__init__()
self.fc = torch.nn.Linear(n_feature, n_hidden)
self.out = torch.nn.Linear(n_hidden, n_output)
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_... | ShiZhuming/ChallengeCup | Network | false | 5,818 | [
"MIT"
] | 1 | c422d1e9864e2bc663a3ddb5e3487a04a0525fcc | https://github.com/ShiZhuming/ChallengeCup/tree/c422d1e9864e2bc663a3ddb5e3487a04a0525fcc |
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
from torch import nn
from torch.optim.lr_scheduler import *
from torch.optim im... | Challyfilio/NAIC2021 | GELU | false | 231 | [
"MIT"
] | 0 | 11b38a920dcc902f9b798dc43ae360062862e6e4 | https://github.com/Challyfilio/NAIC2021/tree/11b38a920dcc902f9b798dc43ae360062862e6e4 |
HubertFeatureProjection | # 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... | sajastu/transformers-sent-curr | HubertFeatureProjection | false | 4,240 | [
"Apache-2.0"
] | 0 | 6dc41545c4ac298a010090fbca4b454c2eaf3dbb | https://github.com/sajastu/transformers-sent-curr/tree/6dc41545c4ac298a010090fbca4b454c2eaf3dbb |
MLP | import torch
import torch.nn as nn
from collections import OrderedDict
class MLP(nn.Module):
def __init__(self, input_dims, n_hiddens, n_class):
super(MLP, self).__init__()
assert isinstance(input_dims, int), 'Please provide int for input_dims'
self.input_dims = input_dims
current... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 co... | luk1684tw/Precision-Reduction | MLP | false | 12,843 | [
"MIT"
] | 0 | c782e9a121ed176b12eb9a081aa1960fabd40019 | https://github.com/luk1684tw/Precision-Reduction/tree/c782e9a121ed176b12eb9a081aa1960fabd40019 |
convnet | import torch
import torch.nn as nn
class convnet(nn.Module):
def __init__(self, in_channel, dim):
super(convnet, self).__init__()
self.conv1 = nn.Conv2d(in_channel, 32, kernel_size=3, padding=1)
self.conv2 = nn.Conv2d(32, 1, kernel_size=1)
def forward(self, x):
x = self.conv1... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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_... | lzz0007/pyGAT | convnet | false | 3,957 | [
"MIT"
] | 0 | ea09c56037185ec5924dcd20b9c09d151174d1a3 | https://github.com/lzz0007/pyGAT/tree/ea09c56037185ec5924dcd20b9c09d151174d1a3 |
TactileWeightModel | # 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.utils.data
import torch.nn as nn
from typing import Optional
import torch.linalg
assert_size_stride = torch._C._dynamo.guards.a... | jeffin07/theseus | TactileWeightModel | false | 15,676 | [
"MIT"
] | 236 | 3498bbddf9cca740c2703d0c1aa3a78a7264cb15 | https://github.com/jeffin07/theseus/tree/3498bbddf9cca740c2703d0c1aa3a78a7264cb15 |
Classifier3 | # 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.... | yuping1624/1082NCTU-Deep-Learning | Classifier3 | false | 4,739 | [
"MIT"
] | 0 | dc83e1c8709e9610a996f02091fe626f07b3c10f | https://github.com/yuping1624/1082NCTU-Deep-Learning/tree/dc83e1c8709e9610a996f02091fe626f07b3c10f |
Linker | # 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... | daniel03c1/audio_augment | Linker | false | 1,770 | [
"MIT"
] | 0 | ee73bb0844e22c57c9cbeb129560da4a3853f77d | https://github.com/daniel03c1/audio_augment/tree/ee73bb0844e22c57c9cbeb129560da4a3853f77d |
PatchMerging | import torch
import torch.nn as nn
import torch.nn.functional as F
from math import sqrt
from torch import optim as optim
class PatchMerging(nn.Module):
"""Patch Merging Layer.
Args:
input_resolution (tuple[int]): Resolution of input feature.
dim (int): Number of input channels.
norm_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | taokong/ibot | PatchMerging | false | 16,532 | [
"Apache-2.0"
] | 327 | a2ee1ae7495d4ea8fb9ba100434c062f1bd3d1f0 | https://github.com/taokong/ibot/tree/a2ee1ae7495d4ea8fb9ba100434c062f1bd3d1f0 |
ExpActivation | import torch
import torch.nn as nn
class ExpActivation(nn.Module):
def __init__(self):
super(ExpActivation, self).__init__()
def forward(self, x):
return torch.exp(-x ** 2)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | mahkons/orthogonal | ExpActivation | false | 3,955 | [
"MIT"
] | 0 | 19a69134ca9a01ef564eab624b8c1526291770aa | https://github.com/mahkons/orthogonal/tree/19a69134ca9a01ef564eab624b8c1526291770aa |
SelfAttentionUnit | # 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.... | dohnlee/qufa2021 | SelfAttentionUnit | false | 12,304 | [
"MIT"
] | 0 | 5fb42caee09ec228358e49768e32c75e3c0094ce | https://github.com/dohnlee/qufa2021/tree/5fb42caee09ec228358e49768e32c75e3c0094ce |
BinaryNLLEntropy | import torch
import torch.nn.functional as F
from torch.nn.modules.loss import _Loss
class BinaryNLLEntropy(_Loss):
def __init__(self, size_average=True):
super(BinaryNLLEntropy, self).__init__()
self.size_average = size_average
def forward(self, net_output, label_output):
"""
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch.... | Jupaoqq/Jupaoqq_LaRL | BinaryNLLEntropy | false | 673 | [
"Apache-2.0"
] | 0 | ae64adda5627987d71f2948f499daa11e9f309ad | https://github.com/Jupaoqq/Jupaoqq_LaRL/tree/ae64adda5627987d71f2948f499daa11e9f309ad |
Smooth_loss | import torch
import torch.nn as nn
import torch.nn.functional as F
class Smooth_loss(nn.Module):
def __init__(self, Smooth_weight=1):
super(Smooth_loss, self).__init__()
self.Smooth_weight = Smooth_weight
def forward(self, x):
_b, _c, h, w = x.size()
x_h = F.pad(x, (0, 0, 1, ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | SeokjaeLIM/DSLR-release | Smooth_loss | false | 8,753 | [
"Apache-2.0"
] | 14 | 861429482faf50ee3d6570948af8c48df1fc7f43 | https://github.com/SeokjaeLIM/DSLR-release/tree/861429482faf50ee3d6570948af8c48df1fc7f43 |
DilatedResConv | import torch
import torch.nn as nn
import torch.nn.functional as F
class DilatedResConv(nn.Module):
def __init__(self, channels, dilation=1, activation='relu', padding=1,
kernel_size=3, left_pad=0):
super().__init__()
in_channels = channels
if activation == 'relu':
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
import torch.nn as nn
import ... | ChesterHuynh/Wavenet-CPC-Music-Translation | DilatedResConv | false | 266 | [
"MIT"
] | 0 | 60632b0330a61a10bac1a129826c55372f685427 | https://github.com/ChesterHuynh/Wavenet-CPC-Music-Translation/tree/60632b0330a61a10bac1a129826c55372f685427 |
BertSelfAttention | # 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.... | MingjieWang0606/2021-Sohu-Text-Matching-TOP2 | BertSelfAttention | false | 18,080 | [
"MIT"
] | 5 | 830a286cc978cb285cb63ae5a457e1d3813fa68a | https://github.com/MingjieWang0606/2021-Sohu-Text-Matching-TOP2/tree/830a286cc978cb285cb63ae5a457e1d3813fa68a |
JustConvBody | import torch
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 JustConvBody(nn.Module):
def __init__(self, in_channels=4):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | Louis-Bagot/DeepRL | JustConvBody | false | 9,703 | [
"MIT"
] | 0 | 0b152c52bbba90362c8276c223fee3f9a464eb32 | https://github.com/Louis-Bagot/DeepRL/tree/0b152c52bbba90362c8276c223fee3f9a464eb32 |
Value | import torch
import torch.nn as nn
import torch.nn.functional as F
class Value(nn.Module):
def __init__(self, num_inputs):
super(Value, self).__init__()
self.affine1 = nn.Linear(num_inputs, 64)
self.affine2 = nn.Linear(64, 64)
self.value_head = nn.Linear(64, 1)
self.value_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | tpbarron/pytorch-ppo | Value | false | 16,608 | [
"MIT"
] | 47 | f73226865e34443f93dbec58939329c9278828e8 | https://github.com/tpbarron/pytorch-ppo/tree/f73226865e34443f93dbec58939329c9278828e8 |
PointerSwitch | import torch
import torch.nn as nn
class Linear(nn.Linear):
"""
Apply linear projection to the last dimention of a tensor.
"""
def forward(self, x):
size = x.size()
return super().forward(x.contiguous().view(-1, size[-1])).view(*
size[:-1], -1)
class ConcatAndProject(nn.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | CrafterKolyan/TabularSemanticParsing | PointerSwitch | false | 2,109 | [
"BSD-3-Clause"
] | 0 | 2d75a3b71fa4c58f2c14ac43a33916747e8f4d1f | https://github.com/CrafterKolyan/TabularSemanticParsing/tree/2d75a3b71fa4c58f2c14ac43a33916747e8f4d1f |
Conv2dTransposeBlock | # 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... | CompVis/interactive-image2video-synthesis | Conv2dTransposeBlock | false | 7,928 | [
"MIT"
] | 20 | 05ea449d3a2704b6d79a5f08683035220d615576 | https://github.com/CompVis/interactive-image2video-synthesis/tree/05ea449d3a2704b6d79a5f08683035220d615576 |
Highway | # 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_... | Kailianghu/Character-Aware-Neural-Language-Model | Highway | false | 8,386 | [
"MIT"
] | 35 | 6bd72ce00a3ac9eb152ba006bdae8a6922e0ad35 | https://github.com/Kailianghu/Character-Aware-Neural-Language-Model/tree/6bd72ce00a3ac9eb152ba006bdae8a6922e0ad35 |
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
import torch.utils.data
assert_size_stride = ... | ashutoshbaghel/tgifqa-lxmert | GeLU | false | 1,469 | [
"MIT"
] | 0 | 7969f478d20fbfbba1c0eaaf0b96891654bfcc26 | https://github.com/ashutoshbaghel/tgifqa-lxmert/tree/7969f478d20fbfbba1c0eaaf0b96891654bfcc26 |
MultiHeadAttentionBlock | import math
import torch
import torch.nn as nn
import torch.utils.data
import torch.backends.cudnn
def mask_logits(inputs, mask, mask_value=-1e+30):
mask = mask.type(torch.float32)
return inputs + (1.0 - mask) * mask_value
class Conv1D(nn.Module):
def __init__(self, in_dim, out_dim, kernel_size=1, stri... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | IsaacChanghau/VSLNet | MultiHeadAttentionBlock | false | 13,890 | [
"MIT"
] | 62 | 3793c625f2e251a5f19a0d59f0c83b12e386f808 | https://github.com/IsaacChanghau/VSLNet/tree/3793c625f2e251a5f19a0d59f0c83b12e386f808 |
HardSwish | import torch
from torch import nn
import torch.nn.functional as F
def hard_swish(x: 'torch.Tensor', inplace: 'bool'=False) ->torch.Tensor:
inner = F.relu6(x + 3.0).div_(6.0)
return x.mul_(inner) if inplace else x.mul(inner)
class HardSwish(nn.Module):
"""
HardSwish activiation layer.
Applies th... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import torch.nn.functional as F
assert_size_stride = torch._C._dynam... | SimonCqk/towhee | HardSwish | false | 9,623 | [
"Apache-2.0"
] | 0 | a187833b1411216106a80a71e6f2c6e68e1be330 | https://github.com/SimonCqk/towhee/tree/a187833b1411216106a80a71e6f2c6e68e1be330 |
ContrastiveLoss | # 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
assert_size_stride = torch._... | QTIM-Lab/SiameseChange | ContrastiveLoss | false | 8,654 | [
"MIT"
] | 14 | a58fe2a93487b3e164f1d7e0b27f5a3321bc2672 | https://github.com/QTIM-Lab/SiameseChange/tree/a58fe2a93487b3e164f1d7e0b27f5a3321bc2672 |
FastGRNNCell | import torch
import torch.nn as nn
import torch.onnx
from itertools import product as product
def gen_nonlinearity(A, nonlinearity):
"""
Returns required activation for a tensor based on the inputs
nonlinearity is either a callable or a value in
['tanh', 'sigmoid', 'relu', 'quantTanh', 'quantSigm... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | ShishirPatil/EdgeML-1 | FastGRNNCell | false | 1,076 | [
"MIT"
] | 0 | cbba9f8b989e545788427c004eb8450e7e4c1a21 | https://github.com/ShishirPatil/EdgeML-1/tree/cbba9f8b989e545788427c004eb8450e7e4c1a21 |
VAE | import torch
from torch import nn
from torch.nn import functional as F
class VAE(nn.Module):
def __init__(self):
super(VAE, self).__init__()
self.fc1 = nn.Linear(84 * 84, 400)
self.fc21 = nn.Linear(400, 20)
self.fc22 = nn.Linear(400, 20)
self.fc3 = nn.Linear(20, 400)
... | import torch
from torch import device
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from... | TannerSorensen/speech_production_manifolds | VAE | false | 5,884 | [
"MIT"
] | 1 | 0dcc2c099ad0e1e157c7f108e28f5957d4ac2f48 | https://github.com/TannerSorensen/speech_production_manifolds/tree/0dcc2c099ad0e1e157c7f108e28f5957d4ac2f48 |
MyMul | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
import torch.nn.parallel
import torch.optim
import t... | JurijsNazarovs/bayesian_nn | MyMul | false | 17,519 | [
"MIT"
] | 6 | 936bf55e0a1e620504d5159c100a74493bd16399 | https://github.com/JurijsNazarovs/bayesian_nn/tree/936bf55e0a1e620504d5159c100a74493bd16399 |
ContentLoss | import torch
from torch import nn
class ContentLoss(nn.Module):
def forward(self, content_weight, content_current, content_original):
"""
Compute the content loss for style transfer.
Inputs:
- content_weight: Scalar giving the weighting for the content loss.
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | Kuga23/Deep-Learning | ContentLoss | false | 2,483 | [
"MIT"
] | 0 | 86980338208c702b6bfcbcfffdb18498e389a56b | https://github.com/Kuga23/Deep-Learning/tree/86980338208c702b6bfcbcfffdb18498e389a56b |
Actor | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | mpgussert/fundamentalRL | Actor | false | 7,276 | [
"MIT"
] | 1 | 4f45436226e0823c21cac316dec8bbf1df697467 | https://github.com/mpgussert/fundamentalRL/tree/4f45436226e0823c21cac316dec8bbf1df697467 |
DuelingQNetwork | import torch
import torch.nn.functional as F
import torch.nn as nn
class DuelingQNetwork(nn.Module):
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed, fc1_units=48):
"""Initialize parameters and build model.
Params
======
state_size (int): Dimen... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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_... | bobiblazeski/navigation | DuelingQNetwork | false | 6,349 | [
"MIT"
] | 1 | bb863b4475a90ff26bede20af647ae4882a0f6fb | https://github.com/bobiblazeski/navigation/tree/bb863b4475a90ff26bede20af647ae4882a0f6fb |
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 math as tl_math
import torch.... | LenKerr/Semantic-Colorization-GAN | GatedConv2d | false | 5,500 | [
"MIT"
] | 1 | 2ce52406ca6fc92e69692b451b1c9ae66ba3b76f | https://github.com/LenKerr/Semantic-Colorization-GAN/tree/2ce52406ca6fc92e69692b451b1c9ae66ba3b76f |
Attention | import torch
from typing import Tuple
from torch import nn
class Attention(nn.Module):
"""
Attention network
Parameters
----------
rnn_size : int
Size of Bi-LSTM
"""
def __init__(self, rnn_size: 'int') ->None:
super(Attention, self).__init__()
self.w = nn.Linear(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._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Renovamen/Text-Classification | Attention | false | 14,279 | [
"MIT"
] | 72 | 4a4aa4001c402ed4371ebaabe1393b27794e5992 | https://github.com/Renovamen/Text-Classification/tree/4a4aa4001c402ed4371ebaabe1393b27794e5992 |
Temporal_Gated_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
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Zhangtianpu/GEE_Classification | Temporal_Gated_conv | false | 6,027 | [
"MIT"
] | 1 | 153356689b1cf3a9bffac1b0afd02891372295ca | https://github.com/Zhangtianpu/GEE_Classification/tree/153356689b1cf3a9bffac1b0afd02891372295ca |
RGBDiff | import torch
from torch import nn
from torchvision import models as models
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
from torchvision.transforms import *
import torch.onnx
class RGBDiff(nn.Module):
def __init__(self, dim=1):
super().__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 import nn
from torchvision import models as models
import torch.nn.parallel
import torch.optim
import torch.utils.data
import tor... | aalborov/openvino_training_extensions | RGBDiff | false | 6,034 | [
"Apache-2.0"
] | 1 | a0bb39424151a98e1ca80c4aa5c865636d401785 | https://github.com/aalborov/openvino_training_extensions/tree/a0bb39424151a98e1ca80c4aa5c865636d401785 |
StateActionEmbedding | import math
import torch
import numpy as np
from abc import ABC
from abc import abstractmethod
from abc import abstractproperty
from torch import nn
from enum import Enum
def tensor_to_numpy(tensor):
return tensor.detach().cpu().numpy()
class MLPParamHandler(ABC):
def __init__(self) ->None:
"""Inte... | 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
from abc import ABC
from abc import abstractmethod
from abc import abstractproperty
from torch import nn
from... | Sebastian-Griesbach/Improving-Policy-Conditioned-Value-Functions | StateActionEmbedding | false | 1,052 | [
"MIT"
] | 0 | ec4125c5e056753e507df0406fcd60b6b6c3dc25 | https://github.com/Sebastian-Griesbach/Improving-Policy-Conditioned-Value-Functions/tree/ec4125c5e056753e507df0406fcd60b6b6c3dc25 |
BertTextPooler | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class BertTextPooler(nn.Module):
def __init__(self, config):
super(BertTextPooler, self).__init__()
self.dense = nn.Linear(config.hidden_size, config.bi_hidden_size)
self.activation = nn.ReLU()
def 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
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | amitakamath/vilbert-multi-task | BertTextPooler | false | 12,086 | [
"MIT"
] | 0 | 5a11b8265fab3598fcdcd7f7c33453b914d8ff2c | https://github.com/amitakamath/vilbert-multi-task/tree/5a11b8265fab3598fcdcd7f7c33453b914d8ff2c |
DummyEmbedder | # 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... | HumaticsLAB/GTM-Transformer | DummyEmbedder | false | 17,402 | [
"MIT"
] | 7 | 94124d3246c7c22d8b952beeda53639a9ad170e3 | https://github.com/HumaticsLAB/GTM-Transformer/tree/94124d3246c7c22d8b952beeda53639a9ad170e3 |
MLP | import torch
from torch import nn
from torch.utils.data import *
import torch.nn.functional as F
class MLP(nn.Module):
def __init__(self):
super(MLP, self).__init__()
self.fc1 = nn.Linear(784, 512)
self.fc2 = nn.Linear(512, 128)
self.fc3 = nn.Linear(128, 10)
def forward(self,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Cjkkkk/nnfusion | MLP | false | 8,911 | [
"MIT"
] | 0 | 7ee61dfdd66fbf67eb178fcc5cfa1cddb99b3c13 | https://github.com/Cjkkkk/nnfusion/tree/7ee61dfdd66fbf67eb178fcc5cfa1cddb99b3c13 |
GramMatrix | import torch
import torch.nn as nn
class GramMatrix(nn.Module):
"""
Base Gram Matrix calculation as per Gatys et al. 2015
"""
def forward(self, input):
b, c, h, w = input.size()
F = input.view(b, c, h * w)
G = torch.bmm(F, F.transpose(1, 2))
G = G.div_(h * w)
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | ChuckHend/nst-zoo | GramMatrix | false | 2,098 | [
"MIT"
] | 0 | 130e485289c5a9417c3dc36980b87373f12f3697 | https://github.com/ChuckHend/nst-zoo/tree/130e485289c5a9417c3dc36980b87373f12f3697 |
AsymmetricLossOptimized | import torch
import torch.nn as nn
class AsymmetricLossOptimized(nn.Module):
""" Notice - optimized version, minimizes memory allocation and gpu uploading,
favors inplace operations"""
def __init__(self, gamma_neg=4, gamma_pos=1, clip=0.05, eps=1e-08,
disable_torch_grad_focal_loss=False):
... | 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... | imvladikon/pytorch-loss | AsymmetricLossOptimized | false | 6,869 | [
"MIT"
] | 1 | 6cfaabe1be898e1ff000b3dffb46d0ef09096f6b | https://github.com/imvladikon/pytorch-loss/tree/6cfaabe1be898e1ff000b3dffb46d0ef09096f6b |
DisConvModule | import torch
import torch.nn as nn
from torch.nn.utils import spectral_norm as spectral_norm_fn
from torch.nn.utils import weight_norm as weight_norm_fn
def dis_conv(input_dim, output_dim, kernel_size=5, stride=2, padding=0,
rate=1, activation='lrelu'):
return Conv2dBlock(input_dim, output_dim, kernel_size, 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
import torch.nn as nn
from torch.nn.utils import spectral_norm as spectral_norm_... | xy-gao/generative-inpainting-pytorch | DisConvModule | false | 13,135 | [
"MIT"
] | 0 | 24f2183a11fd48a0383c9862e3d1a6354fbb6cda | https://github.com/xy-gao/generative-inpainting-pytorch/tree/24f2183a11fd48a0383c9862e3d1a6354fbb6cda |
LocationEncoder | import torch
import torch.nn as nn
import torch.nn.functional as F
class NormalizeScale(nn.Module):
def __init__(self, dim, init_norm=20):
super(NormalizeScale, self).__init__()
self.init_norm = init_norm
self.weight = nn.Parameter(torch.ones(1, dim) * init_norm)
def forward(self, bo... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | sibeiyang/sgmn | LocationEncoder | false | 16,444 | [
"MIT"
] | 130 | 00731b4f2202246d40a36d2a6727c599e6e649aa | https://github.com/sibeiyang/sgmn/tree/00731b4f2202246d40a36d2a6727c599e6e649aa |
MidNet2 | import torch
import torch.nn as nn
class MidNet2(nn.Module):
def forward(self, x_in):
"""Network with dilation rate 2
:param x_in: input convolutional features
:returns: processed convolutional features
:rtype: Tensor
"""
x = self.lrelu(self.conv1... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | deshwalmahesh/CURL---cpu-gpu | MidNet2 | false | 3,409 | [
"BSD-3-Clause"
] | 0 | f4e87275b6cce556b9e04a188cf7ae13d810d82a | https://github.com/deshwalmahesh/CURL---cpu-gpu/tree/f4e87275b6cce556b9e04a188cf7ae13d810d82a |
LipSwish | import torch
class LipSwish(torch.nn.Module):
def forward(self, x):
return 0.909 * torch.nn.functional.silu(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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | Zymrael/torchsde | LipSwish | false | 6,028 | [
"Apache-2.0"
] | 1 | b31825280e50293bce327ae6d89a7b7e4f5bfce1 | https://github.com/Zymrael/torchsde/tree/b31825280e50293bce327ae6d89a7b7e4f5bfce1 |
Normalize | import torch
class Normalize(torch.nn.Module):
def __init__(self, *args, **kwargs):
super(Normalize, self).__init__()
self.args = args
self.kwargs = kwargs
def forward(self, x):
return torch.nn.functional.normalize(x, *self.args, **self.kwargs)
def get_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
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._... | Akababa/torch2trt | Normalize | false | 18,425 | [
"MIT"
] | 2 | 03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 | https://github.com/Akababa/torch2trt/tree/03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 |
Network | # 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... | gray-li/HalfRainbowDQN | Network | false | 12,473 | [
"MIT"
] | 0 | 43e2b12945c14e0e39eea3bbf56c7af785c48720 | https://github.com/gray-li/HalfRainbowDQN/tree/43e2b12945c14e0e39eea3bbf56c7af785c48720 |
DotAttention | # 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.... | zake7749/DeepToxic | DotAttention | false | 16,796 | [
"MIT"
] | 206 | 92710446c55fe60526099f808a7e1179402e199f | https://github.com/zake7749/DeepToxic/tree/92710446c55fe60526099f808a7e1179402e199f |
TriangleMultiplicativeModule | import torch
from torch import nn
from torch import einsum
from inspect import isfunction
def exists(val):
return val is not None
def default(val, d):
if exists(val):
return val
return d() if isfunction(d) else d
class TriangleMultiplicativeModule(nn.Module):
def __init__(self, *, dim, hi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | aced125/alphafold2 | TriangleMultiplicativeModule | false | 6,083 | [
"MIT"
] | 1 | c85682ece37d37c608773cef3ec342b9ddc7fca0 | https://github.com/aced125/alphafold2/tree/c85682ece37d37c608773cef3ec342b9ddc7fca0 |
LCCALayer | # 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 ... | Cai631/PMDN | LCCALayer | false | 195 | [
"Apache-2.0"
] | 0 | 3eca931fbef64f612572d24c856a91342bbdea59 | https://github.com/Cai631/PMDN/tree/3eca931fbef64f612572d24c856a91342bbdea59 |
MedianPool2d | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.utils import _pair
from torch.nn.modules.utils import _quadruple
class MedianPool2d(nn.Module):
"""Median pool (usable as median filter when stride=1) module.
Args:
kernel_size: size of pooling kernel, int or 2-... | 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 torch.nn.modules.utils import _pair
from torch... | Jiaqi0602/adversarial-attack-from-leakage | MedianPool2d | false | 17,473 | [
"BSD-3-Clause"
] | 9 | 90db721bed10094ac7d458b232ad5b1573884338 | https://github.com/Jiaqi0602/adversarial-attack-from-leakage/tree/90db721bed10094ac7d458b232ad5b1573884338 |
Invertible1x1Conv | import torch
import torch.nn.functional as F
from torch.autograd import Variable
import torch.utils.data
class Invertible1x1Conv(torch.nn.Module):
"""
The layer outputs both the convolution, and the log determinant
of its weight matrix. If reverse=True it does convolution with
inverse
"""
de... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.functional as F
from torch.autograd import Variable
import torch... | eba472/fastPitchPyTorch | Invertible1x1Conv | false | 10,041 | [
"BSD-3-Clause"
] | 0 | 0f946c05539102e6868f72f5bf2c461d9711e7d7 | https://github.com/eba472/fastPitchPyTorch/tree/0f946c05539102e6868f72f5bf2c461d9711e7d7 |
MaskedTransformerEncoderLayer | from torch.nn import Module
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Linear
from torch.nn import Dropout
from torch.nn import LayerNorm
from torch.nn import Identity
def drop_path(x, drop_prob: 'float'=0.0, training: 'bool'=False):
"""Drop paths (Stochastic Depth) pe... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | yifanc96/yifanc-DL | MaskedTransformerEncoderLayer | false | 11,123 | [
"MIT"
] | 0 | 25d56cec776fb151c8f6bcbd997bca94f07f3597 | https://github.com/yifanc96/yifanc-DL/tree/25d56cec776fb151c8f6bcbd997bca94f07f3597 |
DiceLoss | # 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... | HolyCrap96/mmocr-1 | DiceLoss | false | 9,181 | [
"Apache-2.0"
] | 0 | c6c4acd39b1c56fec1b87530b2d241fe8af4ceed | https://github.com/HolyCrap96/mmocr-1/tree/c6c4acd39b1c56fec1b87530b2d241fe8af4ceed |
PositionwiseFeedForward | # 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.... | wenh06/OpenAttack | PositionwiseFeedForward | false | 10,976 | [
"MIT"
] | 0 | 412d1b2777dea5009fe97ac264044bfda65dfa5d | https://github.com/wenh06/OpenAttack/tree/412d1b2777dea5009fe97ac264044bfda65dfa5d |
GeneratorLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch ... | akanametov/CycleGAN | GeneratorLoss | false | 6,130 | [
"MIT"
] | 1 | a61e76134cfdda43306e326e3dbba38d8cb21163 | https://github.com/akanametov/CycleGAN/tree/a61e76134cfdda43306e326e3dbba38d8cb21163 |
DeepCoxMixturesTorch | import torch
import torch.nn as nn
def create_representation(inputdim, layers, activation):
"""Helper function to generate the representation function for DSM.
Deep Survival Machines learns a representation (\\ Phi(X) \\) for the input
data. This representation is parameterized using a Non Linear Multilayer
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | mononitogoswami/auton-survival | DeepCoxMixturesTorch | false | 10,604 | [
"MIT"
] | 0 | 04739adac55e47d3d2c61101d92784a9fbb2dd86 | https://github.com/mononitogoswami/auton-survival/tree/04739adac55e47d3d2c61101d92784a9fbb2dd86 |
GraphConvolution | from torch.nn import Module
import torch
from torch.nn import functional as F
from torch.nn import Parameter
import torch.utils.data
import torch.multiprocessing
from torch.nn.parameter import Parameter
from torch.nn.modules.module import Module
import torch.nn.modules.loss
from scipy.sparse import *
def dropout(x, 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.nn import Module
f... | LucasAPayne/graph4nlp | GraphConvolution | false | 9,689 | [
"Apache-2.0"
] | 0 | 3b72308f6ed9ce04c535f78b4b21b6ae0a8f5421 | https://github.com/LucasAPayne/graph4nlp/tree/3b72308f6ed9ce04c535f78b4b21b6ae0a8f5421 |
StableLayerNorm | import torch
from torch import nn
class StableLayerNorm(nn.Module):
def __init__(self, dim):
super().__init__()
self.norm = nn.LayerNorm(dim)
def forward(self, x):
x = x / x.amax(dim=-1, keepdim=True).detach()
return self.norm(x)
def get_inputs():
return [torch.rand([4,... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_... | ryok/nuwa-pytorch | StableLayerNorm | false | 10,747 | [
"MIT"
] | 0 | 6bde90ee6d87bdce8c9aa52c6bbb2ad15a1f5f54 | https://github.com/ryok/nuwa-pytorch/tree/6bde90ee6d87bdce8c9aa52c6bbb2ad15a1f5f54 |
MlpMixer | import torch
import torch.nn as nn
import torch.nn.functional as F
class MlpBlock(nn.Module):
def __init__(self, features, hidden_dim):
super().__init__()
self.hidden_dim = hidden_dim
self.features = features
self.fc1 = nn.Linear(self.features, self.hidden_dim)
self.fc2 = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | amayuelas/NNKGReasoning | MlpMixer | false | 6,221 | [
"MIT"
] | 1 | 0e3623b344fd4e3088ece897f898ddbb1f80888d | https://github.com/amayuelas/NNKGReasoning/tree/0e3623b344fd4e3088ece897f898ddbb1f80888d |
Extractor | # 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.... | OlegJakushkin/FragmentVC | Extractor | false | 14,212 | [
"MIT"
] | 136 | 8aa673157b855bf3b67f06fdb6eb4b2a12ed0005 | https://github.com/OlegJakushkin/FragmentVC/tree/8aa673157b855bf3b67f06fdb6eb4b2a12ed0005 |
MultiHeadedAttention | # 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.... | rosinality/vision-transformers-pytorch | MultiHeadedAttention | false | 16,343 | [
"MIT"
] | 77 | b884b5da79900c96e4ce17fbb575cf1c5cb3cd5f | https://github.com/rosinality/vision-transformers-pytorch/tree/b884b5da79900c96e4ce17fbb575cf1c5cb3cd5f |
CAMMNISTClassifier | # 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 as nn
fr... | RobinMaas95/GTSRB_Visualization | CAMMNISTClassifier | false | 1,008 | [
"MIT"
] | 0 | fa837ff94e089a936ef4f4418970d262b35f70b6 | https://github.com/RobinMaas95/GTSRB_Visualization/tree/fa837ff94e089a936ef4f4418970d262b35f70b6 |
LayerScale_Block | import torch
import torch.nn as nn
class Mlp(nn.Module):
def __init__(self, in_features, hidden_features=None, out_features=None,
act_layer=nn.GELU, drop=0.0):
super().__init__()
out_features = out_features or in_features
hidden_features = hidden_features or in_features
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.... | Uzair-Khattak/deit | LayerScale_Block | false | 9,670 | [
"Apache-2.0"
] | 0 | 896004fc84d4ad2c4c9aa792822df7426af5903d | https://github.com/Uzair-Khattak/deit/tree/896004fc84d4ad2c4c9aa792822df7426af5903d |
h_sigmoid | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data... | SpectrePrediction/micronet | h_sigmoid | false | 2,838 | [
"MIT"
] | 0 | f56269c7a8744f750e9870f0baa9fb6e68f27b9c | https://github.com/SpectrePrediction/micronet/tree/f56269c7a8744f750e9870f0baa9fb6e68f27b9c |
Model | from torch.nn import Module
import torch
import torch.nn.functional
from torch.nn import Parameter
from torch.nn.parameter import Parameter
from torch.nn.modules import Module
import torch.nn.parallel
import torch.utils.data
import torch.optim
import torch.utils.data.distributed
from torch.nn import Module
class Mode... | 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.nn import Module
import torch.nn.functional
from torch.nn import Parameter
from torch.nn.parameter import Parameter
from torch.nn... | ROCmSoftwarePlatform/apex | Model | false | 18,394 | [
"BSD-3-Clause"
] | 6 | db92ee13ca55e284342bdca84bddc38c3812f1ed | https://github.com/ROCmSoftwarePlatform/apex/tree/db92ee13ca55e284342bdca84bddc38c3812f1ed |
SE | # 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 itertools import chain a... | billcai/SlowFast | SE | false | 1,557 | [
"Apache-2.0"
] | 0 | 778888e63351e55861801996b37c7ff9a3746587 | https://github.com/billcai/SlowFast/tree/778888e63351e55861801996b37c7ff9a3746587 |
attention2d | import torch
import torch.nn as nn
import torch.nn.functional as F
class attention2d(nn.Module):
def __init__(self, in_planes, ratios, K, temperature, init_weight=True):
super(attention2d, self).__init__()
assert temperature % 3 == 1
self.avgpool = nn.AdaptiveAvgPool2d(1)
if in_pl... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | PengJingchao/DFNet | attention2d | false | 954 | [
"MIT"
] | 0 | 49e83501f81515aebca211351e315896da7afc54 | https://github.com/PengJingchao/DFNet/tree/49e83501f81515aebca211351e315896da7afc54 |
EncoderLayer | import torch
import torch.nn as nn
import torch.nn.functional as F
class Lambda(nn.Module):
"""An easy way to create a pytorch layer for a simple `func`."""
def __init__(self, func):
"""create a layer that simply calls `func` with `x`"""
super().__init__()
self.func = func
def fo... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | BHD233/PaddleOCR2Pytorch | EncoderLayer | false | 13,393 | [
"Apache-2.0"
] | 364 | f114069b3e2669c6adf0adf9596756205f184c9c | https://github.com/BHD233/PaddleOCR2Pytorch/tree/f114069b3e2669c6adf0adf9596756205f184c9c |
SingleKaistAutoEncoder | # 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.... | DouCir/mmdetection | SingleKaistAutoEncoder | false | 392 | [
"Apache-2.0"
] | 0 | 44613202c379d85315ed47ca670fd9853f90c3a5 | https://github.com/DouCir/mmdetection/tree/44613202c379d85315ed47ca670fd9853f90c3a5 |
CRF | import torch
from torch import nn
import torch.nn.init
class CRF(nn.Module):
"""
Conditional Random Field.
"""
def __init__(self, hidden_dim, tagset_size):
"""
:param hidden_dim: size of word RNN/BLSTM's output
:param tagset_size: number of tags
"""
super(CRF, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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.init
assert_size_stride = torch._C._dynamo.... | sgrvinod/a-PyTorch-Tutorial-to-Sequence-Labeling | CRF | false | 16,391 | [
"MIT"
] | 334 | ee3f34b45a6e24dd748a144bfc25b1adf9e1f077 | https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Sequence-Labeling/tree/ee3f34b45a6e24dd748a144bfc25b1adf9e1f077 |
ShiftedSoftplus | import torch
import torch.nn.functional as F
class ShiftedSoftplus(torch.nn.Module):
def __init__(self):
super(ShiftedSoftplus, self).__init__()
self.shift = torch.log(torch.tensor(2.0)).item()
def forward(self, x):
return F.softplus(x) - self.shift
def get_inputs():
return [to... | 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
assert_size_stride = torch._C._dynamo.guards.assert_size_strid... | BaratiLab/AugLiChem | ShiftedSoftplus | false | 7,754 | [
"MIT"
] | 16 | 37258b5ce2c653436b3e819b58d2659052d6edcc | https://github.com/BaratiLab/AugLiChem/tree/37258b5ce2c653436b3e819b58d2659052d6edcc |
pixel_attention | import torch
from torch import nn
class pixel_attention(nn.Module):
def __init__(self, in_channels, feature_size):
super(pixel_attention, self).__init__()
self.fc1 = nn.Linear(feature_size * feature_size, feature_size,
bias=False)
self.relu1 = nn.ReLU(inplace=True)
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.... | SCUT-AILab/AFA | pixel_attention | false | 17,889 | [
"BSD-3-Clause"
] | 7 | acfb42236ce0114d63f22a821fc5954c8c149f45 | https://github.com/SCUT-AILab/AFA/tree/acfb42236ce0114d63f22a821fc5954c8c149f45 |
FM | # 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
from sklearn.metrics import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = tor... | Sunmyunghan/Final_Project | FM | false | 1,117 | [
"MIT"
] | 0 | 28cde293dc6d07521b2e1c5613b20444aea91d21 | https://github.com/Sunmyunghan/Final_Project/tree/28cde293dc6d07521b2e1c5613b20444aea91d21 |
CrossEntropyLossIIT | import torch
import torch.nn as nn
import torch.utils.data
class CrossEntropyLossIIT(nn.Module):
def __init__(self):
super().__init__()
self.loss = nn.CrossEntropyLoss(reduction='mean')
def forward(self, preds, labels):
return self.loss(preds[0], labels[:, 0]) + self.loss(preds[1],
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | atticusg/cs224u | CrossEntropyLossIIT | false | 1,493 | [
"Apache-2.0"
] | 0 | 66e0f2714e246dcb8836f706ae9ff5613c51ed34 | https://github.com/atticusg/cs224u/tree/66e0f2714e246dcb8836f706ae9ff5613c51ed34 |
Multi_Head_Attention | import torch
import torch.nn as nn
import torch.nn.functional as F
class Scaled_Dot_Product_Attention(nn.Module):
"""Scaled Dot-Product Attention """
def __init__(self):
super(Scaled_Dot_Product_Attention, self).__init__()
def forward(self, Q, K, V, scale=None):
"""
Args:
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | NTDXYG/Text-Classify-based-pytorch | Multi_Head_Attention | false | 8,593 | [
"Apache-2.0"
] | 20 | b12a264a0ea64b2f8b46fafd5383ef0a8025ef2f | https://github.com/NTDXYG/Text-Classify-based-pytorch/tree/b12a264a0ea64b2f8b46fafd5383ef0a8025ef2f |
FeatureMapPairEncoderV2 | import torch
from torch import nn
import torch.nn.functional as F
class FeatureMapPairEncoderV2(nn.Module):
def __init__(self, init_scale=1.0, no_weight_init=False):
super(FeatureMapPairEncoderV2, self).__init__()
self.conv1 = nn.Conv2d(96, 256, kernel_size=3, stride=1)
self.conv2 = nn.Co... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | KH-Kyle/rmp_nav | FeatureMapPairEncoderV2 | false | 8,761 | [
"MIT"
] | 30 | d598fe70664a4cdc0e9b9dd4b52e84aa3de1b551 | https://github.com/KH-Kyle/rmp_nav/tree/d598fe70664a4cdc0e9b9dd4b52e84aa3de1b551 |
LayerLeakyReLU | import random
import torch
import torch.nn as nn
class LayerLeakyReLU(nn.Module):
"""
Test for nn.layers based types
"""
def __init__(self):
super(LayerLeakyReLU, self).__init__()
self.negative_slope = random.random()
self.leaky_relu = nn.LeakyReLU(negative_slope=self.negative... | 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 random
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.gu... | dawnclaude/onnx2keras | LayerLeakyReLU | false | 15,142 | [
"MIT"
] | 115 | 3d2a47c0a228b91fd434232274e216e491da36e3 | https://github.com/dawnclaude/onnx2keras/tree/3d2a47c0a228b91fd434232274e216e491da36e3 |
InstanceNorm | import torch
import torch.nn as nn
class InstanceNorm(nn.Module):
def __init__(self, epsilon=1e-08):
""" avoid in-place ops.
https://discuss.pytorch.org/t/encounter-the-runtimeerror-one-of-the-variables-needed-for-gradient-computation-has-been-modified-by-an-inplace-operation/836/3 """
... | 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_... | Holmes-Alan/Photo2Sketch | InstanceNorm | false | 529 | [
"MIT"
] | 0 | 43a0ca6bb8a8e645b35a2ab23d11ed5efe117e09 | https://github.com/Holmes-Alan/Photo2Sketch/tree/43a0ca6bb8a8e645b35a2ab23d11ed5efe117e09 |
SEBlock | import torch
from torch import nn
import torch.nn.functional as F
class HardSigmoid(nn.Module):
def __init__(self, slope=0.2, offset=0.5):
super().__init__()
self.slope = slope
self.offset = offset
def forward(self, x):
x = self.slope * x + self.offset
x = F.threshold... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | DYF-AI/openvino-x | SEBlock | false | 5,047 | [
"Apache-2.0"
] | 1 | 0f18ebb240ea3394f7e461aca34fac158e686d95 | https://github.com/DYF-AI/openvino-x/tree/0f18ebb240ea3394f7e461aca34fac158e686d95 |
SFU | import torch
import torch.nn as nn
import torch.nn.functional as F
class SFU(nn.Module):
"""Semantic Fusion Unit
The ouput vector is expected to not only retrieve correlative information from fusion vectors,
but also retain partly unchange as the input vector
"""
def __init__(self, input_size, fu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | csarron/QAModels | SFU | false | 1,758 | [
"BSD-3-Clause"
] | 0 | 2db2d7b0f546b88211e111b42744408bbf9b6f35 | https://github.com/csarron/QAModels/tree/2db2d7b0f546b88211e111b42744408bbf9b6f35 |
GatedConv1d | import torch
import torch.nn as nn
import torch.onnx
class MaskedConv1d(nn.Conv1d):
def __init__(self, in_channels, out_channels, kernel_size, dilation=1,
groups=1, bias=True, causal=True):
if causal:
padding = (kernel_size - 1) * dilation
else:
padding = (kernel_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
import torch.nn as nn
import torch.onnx
assert_size_stride = torch._C._dynamo.gu... | jonndoe/Character-Level-Language-Modeling-with-Deeper-Self-Attention-pytorch | GatedConv1d | false | 3,771 | [
"MIT"
] | 0 | d27d2d390f0831330405c16bd29c7f331ad2007a | https://github.com/jonndoe/Character-Level-Language-Modeling-with-Deeper-Self-Attention-pytorch/tree/d27d2d390f0831330405c16bd29c7f331ad2007a |
ConformerFeedForward | import torch
from torch import nn
import torch.utils.data
import torch.optim
class Swish(nn.Module):
"""
Swish activation function introduced in 'https://arxiv.org/abs/1710.05941'
"""
def forward(self, x):
return x * torch.sigmoid(x)
class ConformerFeedForward(nn.Module):
"""
feed-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 nn
import torch.utils.data
import torch.optim
assert_size_stri... | Oktai15/NeMo | ConformerFeedForward | false | 5,673 | [
"Apache-2.0"
] | 1 | 5b6dd3850129898be47cf0d65587897ec45a5b59 | https://github.com/Oktai15/NeMo/tree/5b6dd3850129898be47cf0d65587897ec45a5b59 |
MaskedMSE | # 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... | dhruvramani/AccentTransfer | MaskedMSE | false | 1,832 | [
"MIT"
] | 0 | 63a35b4aa37bc41c1f66dfb4bae76e2924183d7c | https://github.com/dhruvramani/AccentTransfer/tree/63a35b4aa37bc41c1f66dfb4bae76e2924183d7c |
AttentionBlock | # 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.... | Oreoluwa1234/NeMo | AttentionBlock | false | 9,724 | [
"Apache-2.0"
] | 0 | b01e3ceed34efe31fd43866685dbdd19a6b30928 | https://github.com/Oreoluwa1234/NeMo/tree/b01e3ceed34efe31fd43866685dbdd19a6b30928 |
Self_Attentive_Pooling | import torch
import torch.nn as nn
import torch.nn.functional as F
class Self_Attentive_Pooling(nn.Module):
def __init__(self, dim):
"""SAP
Paper: Self-Attentive Speaker Embeddings for Text-Independent Speaker Verification
Link： https://danielpovey.com/files/2018_interspeech_xvector_atten... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | ikunsaikou/lhy_ML2021Spring | Self_Attentive_Pooling | false | 6,870 | [
"WTFPL"
] | 1 | 80d8922077e2f5abba6a440c17654a143ebc8c9c | https://github.com/ikunsaikou/lhy_ML2021Spring/tree/80d8922077e2f5abba6a440c17654a143ebc8c9c |
BertLayer | # 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.... | IsmaelElsharkawi/new_pororo_repo | BertLayer | false | 8,820 | [
"MIT"
] | 19 | 4617083b420615b8a3eb0f44d02e4e91a8f407f7 | https://github.com/IsmaelElsharkawi/new_pororo_repo/tree/4617083b420615b8a3eb0f44d02e4e91a8f407f7 |
TimeEncoding | # 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... | Tim-blo/ACTOR | TimeEncoding | false | 2,903 | [
"MIT"
] | 0 | f10d7534a34fa557ab6b1739217649ae4f654505 | https://github.com/Tim-blo/ACTOR/tree/f10d7534a34fa557ab6b1739217649ae4f654505 |
MVNormalNetwork | import torch
import torch.nn as nn
class MVNormalNetwork(nn.Module):
def __init__(self, latent_dim):
super().__init__()
self.mean = nn.Linear(latent_dim, latent_dim)
self.sc = nn.Linear(latent_dim, latent_dim)
def forward(self, x):
mean = self.mean(x)
sc = self.sc(x)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | mgb45/OC-notebooks | MVNormalNetwork | false | 7,223 | [
"MIT"
] | 1 | 67b1899d1fb3455ab3caab58f94429b9f432164b | https://github.com/mgb45/OC-notebooks/tree/67b1899d1fb3455ab3caab58f94429b9f432164b |
Gaussian | import torch
import torch.nn as nn
class Gaussian(nn.Module):
def forward(self, x):
return torch.exp(-x * x / 2.0)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | awlange/pysurvival | Gaussian | false | 14,925 | [
"Apache-2.0"
] | 242 | 841b9bc6ce700ba8898d2a1488aa9cd25ee7a8e6 | https://github.com/awlange/pysurvival/tree/841b9bc6ce700ba8898d2a1488aa9cd25ee7a8e6 |
_GateAddNorm | # 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 T... | gdevos010/darts | _GateAddNorm | false | 3,673 | [
"Apache-2.0"
] | 0 | 96c97c1e241500ae7b91d32bbfa21d811e4a7d71 | https://github.com/gdevos010/darts/tree/96c97c1e241500ae7b91d32bbfa21d811e4a7d71 |
SSWELoss | # 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... | Aurelius84/SPWE | SSWELoss | false | 16,954 | [
"MIT"
] | 9 | 5f9fc5495e879b5272c118271a69c5adad4ba260 | https://github.com/Aurelius84/SPWE/tree/5f9fc5495e879b5272c118271a69c5adad4ba260 |
HGNN_conv | import math
import torch
import torch.nn as nn
from torch.nn.parameter import Parameter
class HGNN_conv(nn.Module):
def __init__(self, in_ft, out_ft, bias=True):
super(HGNN_conv, self).__init__()
self.weight = Parameter(torch.Tensor(in_ft, out_ft))
if bias:
self.bias = Paramet... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
from torch.nn.parameter import Parameter
asser... | iMoonLab/HHDTI | HGNN_conv | false | 6,844 | [
"MIT"
] | 1 | b2dd0e78818888e676afc91af1425dada5b3258a | https://github.com/iMoonLab/HHDTI/tree/b2dd0e78818888e676afc91af1425dada5b3258a |
BertPSIHead | # 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... | Sologa/awesome-align | BertPSIHead | false | 14,424 | [
"BSD-3-Clause"
] | 173 | 62eaae7eac9bac06c10627fac6cc942c07a50e64 | https://github.com/Sologa/awesome-align/tree/62eaae7eac9bac06c10627fac6cc942c07a50e64 |
Critic | import torch
import torch.nn as nn
import torch.nn.functional as F
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.Linear(300, 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
import torch.nn as nn
import ... | jinPrelude/ksp-ai | Critic | false | 12,616 | [
"MIT"
] | 0 | d8b235d1ef77afe413fbff2e859e1210330bde37 | https://github.com/jinPrelude/ksp-ai/tree/d8b235d1ef77afe413fbff2e859e1210330bde37 |
ArcMarginProduct_subcenter | import math
import torch
import torch.nn.functional as F
import torch.nn as nn
class ArcMarginProduct_subcenter(nn.Module):
def __init__(self, in_features, out_features, k=3):
super().__init__()
self.weight = nn.Parameter(torch.FloatTensor(out_features * k,
in_features))
self.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Fkaneko/kaggle-hpa-single-cell-image-classification | ArcMarginProduct_subcenter | false | 5,170 | [
"MIT"
] | 1 | 52000cbf5c7eec6ace29274d9e85b5b24fac281b | https://github.com/Fkaneko/kaggle-hpa-single-cell-image-classification/tree/52000cbf5c7eec6ace29274d9e85b5b24fac281b |
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