entry_point stringlengths 1 65 | original_triton_python_code stringlengths 208 619k | optimised_triton_code stringlengths 1.15k 275k | repo_name stringlengths 7 115 | module_name stringlengths 1 65 | synthetic bool 1
class | uuid int64 0 18.5k | licenses listlengths 1 6 | stars int64 0 19.8k | sha stringlengths 40 40 | repo_link stringlengths 72 180 |
|---|---|---|---|---|---|---|---|---|---|---|
EqualLinear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.a... | ArdWang/GFPGAN | EqualLinear | false | 11,248 | [
"BSD-3-Clause"
] | 0 | f984ec32754190fad0b9b7a60d372aac84e57173 | https://github.com/ArdWang/GFPGAN/tree/f984ec32754190fad0b9b7a60d372aac84e57173 |
Qnet | import random
import torch
import torch.nn as nn
import torch.nn.functional as F
class Qnet(nn.Module):
def __init__(self):
super(Qnet, self).__init__()
self.fc1 = nn.Linear(4, 128)
self.fc2 = nn.Linear(128, 128)
self.fc3 = nn.Linear(128, 2)
def forward(self, x):
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 import triton_helpers
import random
import torch.nn... | co24428/minimalRL | Qnet | false | 1,730 | [
"MIT"
] | 0 | c758e733438fce1d8421551e75f2117ec3f82028 | https://github.com/co24428/minimalRL/tree/c758e733438fce1d8421551e75f2117ec3f82028 |
NeuralClassifier | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | JayWalker512/PacketGAN | NeuralClassifier | false | 17,460 | [
"MIT"
] | 5 | 93d4266ab9299c25ffd1f0aedf68fa4639f66572 | https://github.com/JayWalker512/PacketGAN/tree/93d4266ab9299c25ffd1f0aedf68fa4639f66572 |
BertPooler | from _paritybench_helpers import _mock_config
import torch
import torch.nn.functional
from torch import nn
class BertPooler(nn.Module):
def __init__(self, config):
super(BertPooler, self).__init__()
self.dense = nn.Linear(config.hidden_size, config.hidden_size)
self.activation = nn.GELU()... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.fun... | bj1103/FaST-VGS-Family | BertPooler | false | 6,345 | [
"BSD-3-Clause"
] | 1 | 824f987a5bd647fc17aa34b98eb1d9109441d64b | https://github.com/bj1103/FaST-VGS-Family/tree/824f987a5bd647fc17aa34b98eb1d9109441d64b |
RelRootDepthLoss | import torch
import torch.utils.data
import torch.nn as nn
class RelRootDepthLoss(nn.Module):
def __init__(self):
super(RelRootDepthLoss, self).__init__()
def forward(self, root_depth_out, root_depth_gt, root_valid):
loss = torch.abs(root_depth_out - root_depth_gt) * root_valid
retur... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.utils.data
import torch.nn as nn
assert_size_stride = torch.... | DuinoDu/InterHand2.6M.pl | RelRootDepthLoss | false | 5,086 | [
"MIT"
] | 1 | 2d216960cf95b066a197a9b49795840b1ecfd0c1 | https://github.com/DuinoDu/InterHand2.6M.pl/tree/2d216960cf95b066a197a9b49795840b1ecfd0c1 |
EncoderBlock | # 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.... | SVRTK/Segmentation_FetalMRI | EncoderBlock | false | 17,888 | [
"Apache-2.0"
] | 6 | 9344a2248cbe8e4cccbe05ca98214626dcf62805 | https://github.com/SVRTK/Segmentation_FetalMRI/tree/9344a2248cbe8e4cccbe05ca98214626dcf62805 |
PreNet | # 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... | padmalcom/AISpeechAssistant | PreNet | false | 7,439 | [
"Apache-2.0"
] | 1 | b7501a23a8f513acb5043f3c7bb06df129bdc2cc | https://github.com/padmalcom/AISpeechAssistant/tree/b7501a23a8f513acb5043f3c7bb06df129bdc2cc |
WeightQuantizer | # 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.... | RiccardoRuggiero/micronet | WeightQuantizer | false | 5,768 | [
"MIT"
] | 1 | bfdac2a50a5f0f8484a253b356c06a166bf7e6a0 | https://github.com/RiccardoRuggiero/micronet/tree/bfdac2a50a5f0f8484a253b356c06a166bf7e6a0 |
ConvNet64 | # 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_... | Neural-Diffusion-Research/normalized-autoencoders | ConvNet64 | false | 8,646 | [
"MIT"
] | 30 | 0c77f7e29289e336c0fe5e941aaec8baa4a4fb82 | https://github.com/Neural-Diffusion-Research/normalized-autoencoders/tree/0c77f7e29289e336c0fe5e941aaec8baa4a4fb82 |
TotalVariationLoss | # 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 typing import Optional
assert_size_stride = torch._C._dynamo.guards.assert... | daniilgaltsev/Neural-Style-Transfer | TotalVariationLoss | false | 6,524 | [
"MIT"
] | 1 | c781c34a591973afae1a6b7a40c7b31c43af63f7 | https://github.com/daniilgaltsev/Neural-Style-Transfer/tree/c781c34a591973afae1a6b7a40c7b31c43af63f7 |
MainClassifier | import torch
import torch.nn as nn
class MainClassifier(nn.Module):
def __init__(self, channel, num_classes=100):
super(MainClassifier, self).__init__()
self.pool = nn.AdaptiveAvgPool2d(1)
self.fc = nn.Linear(channel, num_classes)
def forward(self, x):
x = self.pool(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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | janhenriklambrechts/Task-Oriented-Feature-Distillation | MainClassifier | false | 12,602 | [
"MIT"
] | 0 | 87ab75677b02441bce045e76e96afb078e9df2ea | https://github.com/janhenriklambrechts/Task-Oriented-Feature-Distillation/tree/87ab75677b02441bce045e76e96afb078e9df2ea |
QPCnet | import torch
import torch.nn as nn
class QPCnet(nn.Module):
def __init__(self, num_classes=2):
super(QPCnet, self).__init__()
self.conv1 = nn.Conv2d(2, 8, 3, [1, 2], 1)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(8, 16, 3, 1, 1)
self.conv3 = nn.Conv2d(16, 32, 2, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | davidwangtgs/CNN_PAC | QPCnet | false | 3,403 | [
"MIT"
] | 0 | d3824fc269ad5c86a962336e140b222856f26a2c | https://github.com/davidwangtgs/CNN_PAC/tree/d3824fc269ad5c86a962336e140b222856f26a2c |
MNIST_Encoder | # 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 ... | mdiephuis/adversarial-autoencoders | MNIST_Encoder | false | 7,216 | [
"MIT"
] | 1 | a722239564362796774de21a64fd92e81dce4089 | https://github.com/mdiephuis/adversarial-autoencoders/tree/a722239564362796774de21a64fd92e81dce4089 |
LinearAttention | # 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.... | gchrupala/platalea | LinearAttention | false | 6,736 | [
"Apache-2.0"
] | 1 | 65833307bb6c5ad6cbdd6b17ad8ca59cf51fcd81 | https://github.com/gchrupala/platalea/tree/65833307bb6c5ad6cbdd6b17ad8ca59cf51fcd81 |
Envelope | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_... | shnhrtkyk/pytorch_geometric | Envelope | false | 10,807 | [
"MIT"
] | 0 | b971fd2ebba10736e6398d6305757be2d81ca681 | https://github.com/shnhrtkyk/pytorch_geometric/tree/b971fd2ebba10736e6398d6305757be2d81ca681 |
SAM_Module | # 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 torchvision.transforms import *
assert_size_stride = ... | Vill-Lab/IGOAS | SAM_Module | false | 18,043 | [
"MIT"
] | 8 | 42ca1d45e441f993c95b5e8f33c9f97ea3b916f3 | https://github.com/Vill-Lab/IGOAS/tree/42ca1d45e441f993c95b5e8f33c9f97ea3b916f3 |
Mish | import torch
import torch.nn as nn
class Mish(nn.Module):
def __init__(self):
super().__init__()
def forward(self, x):
return torch.mul(x, torch.tanh(torch.log(1 + torch.exp(x))))
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.gu... | mattroz/yatopi | Mish | false | 3,983 | [
"MIT"
] | 0 | 278bac6f3d2f13916ae9d43309b9f38b608426bd | https://github.com/mattroz/yatopi/tree/278bac6f3d2f13916ae9d43309b9f38b608426bd |
AttentionBlock | import math
import torch
import torch.cuda
from torch.nn import functional as F
from torch import nn
import torch.distributed
import torch.utils.data
import torch.optim
def convert_pad_shape(pad_shape):
"""
Used to get arguments for F.pad
"""
l = pad_shape[::-1]
pad_shape = [item for sublist in l ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Oreoluwa1234/NeMo | AttentionBlock | false | 9,724 | [
"Apache-2.0"
] | 0 | b01e3ceed34efe31fd43866685dbdd19a6b30928 | https://github.com/Oreoluwa1234/NeMo/tree/b01e3ceed34efe31fd43866685dbdd19a6b30928 |
ConvP4 | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cu... | claudio-unipv/groupcnn | ConvP4 | false | 12,231 | [
"MIT"
] | 0 | 2b1514f5a0fb9a78c6f646e1c075e5c3d5af9c0c | https://github.com/claudio-unipv/groupcnn/tree/2b1514f5a0fb9a78c6f646e1c075e5c3d5af9c0c |
VGGBase | # 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 torchvision
import tor... | ildoonet/ai-starthon-2019 | VGGBase | false | 15,740 | [
"MIT"
] | 69 | 148855adcb731741938a86545a2d3282287f0a50 | https://github.com/ildoonet/ai-starthon-2019/tree/148855adcb731741938a86545a2d3282287f0a50 |
AvgReducePool1d | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | Codle/texar-pytorch | AvgReducePool1d | false | 11,302 | [
"Apache-2.0"
] | 0 | d63556e7a8f48076c396467314a771d56552d595 | https://github.com/Codle/texar-pytorch/tree/d63556e7a8f48076c396467314a771d56552d595 |
decoder5 | import torch
import torch.nn as nn
class decoder5(nn.Module):
def __init__(self, d=None):
super(decoder5, self).__init__()
self.reflecPad15 = nn.ReflectionPad2d((1, 1, 1, 1))
self.conv15 = nn.Conv2d(512, 512, 3, 1, 0)
if d:
self.conv15.weight = torch.nn.Parameter(d.get... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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/PytorchWCT | decoder5 | false | 9,390 | [
"MIT"
] | 0 | 9d11cc0995c0610c129b78ff5f72a26f4d60e10a | https://github.com/MingSun-Tse/PytorchWCT/tree/9d11cc0995c0610c129b78ff5f72a26f4d60e10a |
SimpleCNN | # 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.... | D-X-Y/MSPLD-2018 | SimpleCNN | false | 13,614 | [
"MIT"
] | 63 | 71a6a75830ac84c7a861e63367ad3ace991fae77 | https://github.com/D-X-Y/MSPLD-2018/tree/71a6a75830ac84c7a861e63367ad3ace991fae77 |
LatentLoss | # 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
... | jinyeom/vae | LatentLoss | false | 3,734 | [
"MIT"
] | 0 | 861cb2edd5cebc9f56c2677d7b79f5ab0a05f874 | https://github.com/jinyeom/vae/tree/861cb2edd5cebc9f56c2677d7b79f5ab0a05f874 |
ShakeResNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import math
from torch import... | cdtalley/AutoML | ShakeResNet | false | 6,408 | [
"MIT"
] | 1 | 918cda6bb1bd55b4ca974bdcdd59e32b2e28399d | https://github.com/cdtalley/AutoML/tree/918cda6bb1bd55b4ca974bdcdd59e32b2e28399d |
GramMatrix | import torch
import torch.utils.data
import torch
import torch.nn as nn
class GramMatrix(nn.Module):
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.div_(h * w)
return G
def get_inputs():
return [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
import torch.utils.data
import torch
import torch.nn as nn
assert_size_stride = ... | ckxy/1d_expan | GramMatrix | false | 6,455 | [
"MIT"
] | 1 | 29cc294e0314d738e8e041f34c995fd22f9f980b | https://github.com/ckxy/1d_expan/tree/29cc294e0314d738e8e041f34c995fd22f9f980b |
FullyConnected | # 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... | qweas120/Active_VLN | FullyConnected | false | 7,520 | [
"MIT"
] | 1 | d5dabd5fe6127bcfec023b90f14a4ba5ac671f9b | https://github.com/qweas120/Active_VLN/tree/d5dabd5fe6127bcfec023b90f14a4ba5ac671f9b |
ItemInferenceNetwork | import torch
import torch.utils.data
import torch.nn as nn
class ItemInferenceNetwork(nn.Module):
def __init__(self, num_item, item_feat_dim):
super().__init__()
self.mu_lookup = nn.Embedding(num_item, item_feat_dim)
self.logvar_lookup = nn.Embedding(num_item, item_feat_dim)
def forw... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | BratChar/variational-item-response-theory-public | ItemInferenceNetwork | false | 13,406 | [
"MIT"
] | 52 | 12862157e99506a0ed7018f1b8a485d4e61fb5bf | https://github.com/BratChar/variational-item-response-theory-public/tree/12862157e99506a0ed7018f1b8a485d4e61fb5bf |
maximum_absolute_error | import torch
from torch import nn
class maximum_absolute_error(nn.Module):
def forward(self, yhat, y):
return torch.max(torch.abs(torch.sub(y, yhat)))
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
a... | JonasBrusokas/ModelarDB-ext | maximum_absolute_error | false | 9,158 | [
"Apache-2.0"
] | 0 | 354678994cc5fa2d2264436f1d33f250e11d990d | https://github.com/JonasBrusokas/ModelarDB-ext/tree/354678994cc5fa2d2264436f1d33f250e11d990d |
Net | import torch
class Net(torch.nn.Module):
"""Implementing two layer nn."""
def __init__(self, D_IN, H, D_OUT):
super().__init__()
self.linear1 = torch.nn.Linear(D_IN, H)
self.linear2 = torch.nn.Linear(H, D_OUT)
def forward(self, x):
h = self.linear1(x)
h_relu = tor... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | ImadDabbura/deep_learning_with_pytorch | Net | false | 5,348 | [
"MIT"
] | 1 | 0cac0614ab08b30654de192e540048cf4243a4e4 | https://github.com/ImadDabbura/deep_learning_with_pytorch/tree/0cac0614ab08b30654de192e540048cf4243a4e4 |
SigmoidDeepLiftModel | # 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_... | aravipati12/captum | SigmoidDeepLiftModel | false | 10,108 | [
"BSD-3-Clause"
] | 0 | ef3e81d89c8c4404a49c384cf0727f2e7d393f5f | https://github.com/aravipati12/captum/tree/ef3e81d89c8c4404a49c384cf0727f2e7d393f5f |
LinearModel | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | Azerrroth/spacetimeformer | LinearModel | false | 101 | [
"MIT"
] | 0 | e822444a6d696a1edb9e446d6f3482a70681be3c | https://github.com/Azerrroth/spacetimeformer/tree/e822444a6d696a1edb9e446d6f3482a70681be3c |
Value_estimate | # 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_... | pupupue/Deep-RL-atari | Value_estimate | false | 7,492 | [
"MIT"
] | 1 | 9b97157f87826feafcf272761d7eef9693a2b2c4 | https://github.com/pupupue/Deep-RL-atari/tree/9b97157f87826feafcf272761d7eef9693a2b2c4 |
AdaptiveInstanceNormPP | # 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 ... | ankmathur96/torchsupport | AdaptiveInstanceNormPP | false | 3,177 | [
"MIT"
] | 0 | 77bf4a90b8770a408665e2604428808c3ed2f979 | https://github.com/ankmathur96/torchsupport/tree/77bf4a90b8770a408665e2604428808c3ed2f979 |
SDNE_layer | import torch
import torch.utils.data
import torch.nn as nn
import torch.nn.functional as F
import torch as torch
class SDNE_layer(nn.Module):
def __init__(self, num_node, hidden_size1, hidden_size2, droput, alpha,
beta, nu1, nu2):
super(SDNE_layer, self).__init__()
self.num_node = num_nod... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | ckhui/cogdl | SDNE_layer | false | 12,666 | [
"MIT"
] | 0 | 93bea17c2dc7084857cd0a4af8178c174965127c | https://github.com/ckhui/cogdl/tree/93bea17c2dc7084857cd0a4af8178c174965127c |
SpatialPyramidPooling | import torch
import torch.nn as nn
class SpatialPyramidPooling(nn.Module):
def __init__(self, pool_sizes=[5, 9, 13]):
super(SpatialPyramidPooling, self).__init__()
self.maxpools = nn.ModuleList([nn.MaxPool2d(pool_size, 1, pool_size //
2) for pool_size in pool_sizes])
def forward(... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | janewen134/fyp | SpatialPyramidPooling | false | 10,377 | [
"Apache-2.0"
] | 0 | 8fb93ac22d21d5d862035ba794fe9d264add2e63 | https://github.com/janewen134/fyp/tree/8fb93ac22d21d5d862035ba794fe9d264add2e63 |
self_attn_mini | # 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.... | aryanbdps9/aml_music_generation | self_attn_mini | false | 1,487 | [
"MIT"
] | 0 | 42c8895128327a2884dbfeb8413e0060fef6e22f | https://github.com/aryanbdps9/aml_music_generation/tree/42c8895128327a2884dbfeb8413e0060fef6e22f |
ExpMSE | # 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... | dattientran/attorch | ExpMSE | false | 12,384 | [
"MIT"
] | 0 | 469b225846c6d8a7d833ebac19d040c7a407a0ff | https://github.com/dattientran/attorch/tree/469b225846c6d8a7d833ebac19d040c7a407a0ff |
WeightedCrossEntropyLoss | # 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
... | ElodieShan/OpenPCDet | WeightedCrossEntropyLoss | false | 9,037 | [
"Apache-2.0"
] | 0 | d23959d70c73b29f3f14462628fa8520a64f2eae | https://github.com/ElodieShan/OpenPCDet/tree/d23959d70c73b29f3f14462628fa8520a64f2eae |
encoder3 | import torch
import torch.nn
import torch
import torch.nn as nn
class encoder3(nn.Module):
def __init__(self, W, v2):
super(encoder3, self).__init__()
self.conv1 = nn.Conv2d(3, 3, 1, 1, 0)
self.reflecPad1 = nn.ZeroPad2d((1, 1, 1, 1))
self.conv2 = nn.Conv2d(3, 32 if v2 else int(64 ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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
... | kamieen03/style-transfer-server | encoder3 | false | 3,868 | [
"BSD-2-Clause"
] | 0 | 91727ec62080215a0b870ce043faf0657137b84b | https://github.com/kamieen03/style-transfer-server/tree/91727ec62080215a0b870ce043faf0657137b84b |
Netleaky | # 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_... | gautam-sharma1/Imitation-Learning | Netleaky | false | 3,529 | [
"MIT"
] | 0 | 20b6fcd2a8d6de8eb95e6831f5b379a083306361 | https://github.com/gautam-sharma1/Imitation-Learning/tree/20b6fcd2a8d6de8eb95e6831f5b379a083306361 |
Lambda | # 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.optim
assert_size_stride = torch._C._dynamo.guards.assert_si... | ai-in-motion/moai | Lambda | false | 18,325 | [
"Apache-2.0"
] | 10 | e38cac046c059d2e2331ef4883bbabc5a500a5cf | https://github.com/ai-in-motion/moai/tree/e38cac046c059d2e2331ef4883bbabc5a500a5cf |
Attention | # 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.... | rish-16/audio-tf-pytorch | Attention | false | 7,562 | [
"MIT"
] | 1 | 397a6e9f1a97cce774202d392eb9706f0483405c | https://github.com/rish-16/audio-tf-pytorch/tree/397a6e9f1a97cce774202d392eb9706f0483405c |
InceptionC | import torch
from torch.nn import functional as F
import torch.nn as nn
class Conv2d(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, batch_norm=
False, **kwargs):
super(Conv2d, self).__init__()
self.conv = nn.Conv2d(in_channels, out_channels, kernel_size, **kwargs)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | Hiroaki-Ozaki/modelib-classification | InceptionC | false | 17,415 | [
"WTFPL"
] | 10 | 11077704cc0bc9a42fc4b94da60b57d31ff0f65c | https://github.com/Hiroaki-Ozaki/modelib-classification/tree/11077704cc0bc9a42fc4b94da60b57d31ff0f65c |
Pointer | # 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... | mirbostani/QA-KD-AL | Pointer | false | 7,241 | [
"MIT"
] | 1 | 0ec8756ee06ae2a204a5e9110503bc697e9108fb | https://github.com/mirbostani/QA-KD-AL/tree/0ec8756ee06ae2a204a5e9110503bc697e9108fb |
OneLayerFCBodyWithAction | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.optim
import tor... | DMIU-ShELL/deeprl-shell | OneLayerFCBodyWithAction | false | 9,029 | [
"Apache-2.0"
] | 0 | a7845ab1c4967ba2af9486625086c3d0b176d293 | https://github.com/DMIU-ShELL/deeprl-shell/tree/a7845ab1c4967ba2af9486625086c3d0b176d293 |
Lookahead | # 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.distributed
import torch.nn as nn
assert_size_stride = t... | gbaril/End-to-end-E2E-Named-Entity-Recognition-from-English-Speech | Lookahead | false | 12,409 | [
"Apache-2.0"
] | 0 | 9760a4ec3ba1c55bb4740c12c4542f13dd028695 | https://github.com/gbaril/End-to-end-E2E-Named-Entity-Recognition-from-English-Speech/tree/9760a4ec3ba1c55bb4740c12c4542f13dd028695 |
SE | import torch
import torch.nn as nn
import torch.nn.functional as F
def swish(x):
return x * x.sigmoid()
class SE(nn.Module):
"""Squeeze-and-Excitation block with Swish."""
def __init__(self, in_planes, se_planes):
super(SE, self).__init__()
self.se1 = nn.Conv2d(in_planes, se_planes, ker... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | liormagram/pytorch-cifar | SE | false | 10,422 | [
"MIT"
] | 0 | 2ed0fabe6cbd4a468c5c4d155fb76c5b9ad4a764 | https://github.com/liormagram/pytorch-cifar/tree/2ed0fabe6cbd4a468c5c4d155fb76c5b9ad4a764 |
My_loss_focus2 | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | H-Liu1997/Pytorch_Pose_Estimation_Framework | My_loss_focus2 | false | 5,252 | [
"MIT"
] | 1 | 06616b3459ff639f8486e6ea4f93922597788b2a | https://github.com/H-Liu1997/Pytorch_Pose_Estimation_Framework/tree/06616b3459ff639f8486e6ea4f93922597788b2a |
DownsampleA | # 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... | gianlucagiudice/PyCIL | DownsampleA | false | 3,676 | [
"MIT"
] | 0 | 0db88f239b935ea6d0047918a2a55a703f707b04 | https://github.com/gianlucagiudice/PyCIL/tree/0db88f239b935ea6d0047918a2a55a703f707b04 |
ConcatPositionalEncoding | import torch
import torch.nn as nn
class ConcatPositionalEncoding(nn.Module):
def __init__(self, d_model=256, max_len=512):
super().__init__()
self.timing_table = nn.Parameter(torch.FloatTensor(max_len, d_model //
2))
nn.init.normal_(self.timing_table)
self.norm = nn.L... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | skulick/self-attentive-parser | ConcatPositionalEncoding | false | 4,353 | [
"MIT"
] | 0 | 04a91e80cc05bcfe8f48145517f58e85f0c8ade6 | https://github.com/skulick/self-attentive-parser/tree/04a91e80cc05bcfe8f48145517f58e85f0c8ade6 |
NormUpscaleConvBlock | import torch
import torch.nn as nn
import torch.nn.functional as F
class PixelNormLayer(nn.Module):
def __init__(self):
super(PixelNormLayer, self).__init__()
def forward(self, x):
return x / torch.sqrt(torch.mean(x ** 2, dim=1, keepdim=True) + 1e-08)
class WScaleLayer(nn.Module):
def... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | ChandreyeeB/Blind-Image-Deconvolution-using-Deep-Generative-Priors | NormUpscaleConvBlock | false | 7,878 | [
"MIT"
] | 24 | 4198bd2d325a32ffc4e714c486540e63440ab110 | https://github.com/ChandreyeeB/Blind-Image-Deconvolution-using-Deep-Generative-Priors/tree/4198bd2d325a32ffc4e714c486540e63440ab110 |
AvgPoolPad | import torch
from torch import nn
class AvgPoolPad(nn.Module):
def __init__(self, stride=2, padding=1):
super(AvgPoolPad, self).__init__()
self.pad = nn.ZeroPad2d((1, 0, 1, 0))
self.pool = nn.AvgPool2d(3, stride=stride, padding=padding,
count_include_pad=False)
def forwar... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | MarioProjects/pytorchlib | AvgPoolPad | false | 5,575 | [
"MIT"
] | 1 | 81ea32304d899fbd10ae1efe1d124c0d7bc96f5c | https://github.com/MarioProjects/pytorchlib/tree/81ea32304d899fbd10ae1efe1d124c0d7bc96f5c |
SoftmaxOutputLayer | import torch
import torch.nn as nn
import torch.nn.functional as F
class OutputLayer(nn.Module):
"""
Abstract base class for output layer.
Handles projection to output labels
"""
def __init__(self, hidden_size, output_size):
super(OutputLayer, self).__init__()
self.output_size = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Ravikiran2402/_MOEL | SoftmaxOutputLayer | false | 11,803 | [
"MIT"
] | 0 | 57e311712c67e1e554a3a9187709f8e2728d19be | https://github.com/Ravikiran2402/_MOEL/tree/57e311712c67e1e554a3a9187709f8e2728d19be |
Decoder | # 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... | AbinavRavi/VAE-KL | Decoder | false | 31 | [
"Apache-2.0"
] | 0 | af7a44b7952c2e5e1be4f3ffa12a3d859f4f4bdc | https://github.com/AbinavRavi/VAE-KL/tree/af7a44b7952c2e5e1be4f3ffa12a3d859f4f4bdc |
BertIntermediate | # 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 ... | RoshanTanisha/TVCaption | BertIntermediate | false | 1,892 | [
"MIT"
] | 0 | 8b14a340134ec69ed87426ee1f0e93e53f6456e5 | https://github.com/RoshanTanisha/TVCaption/tree/8b14a340134ec69ed87426ee1f0e93e53f6456e5 |
BboxHead | import torch
import torch.nn as nn
from itertools import product as product
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
import torch.nn as nn
from itertools import product as product
assert_size_strid... | Juggernaut93/InsightFace-v2 | BboxHead | false | 764 | [
"Apache-2.0"
] | 0 | 65e9b8d1f285a87472ffb913bec136d4e046798f | https://github.com/Juggernaut93/InsightFace-v2/tree/65e9b8d1f285a87472ffb913bec136d4e046798f |
SEModule | # 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_... | Alexis-Fab/mmaction2 | SEModule | false | 11,217 | [
"Apache-2.0"
] | 0 | 6f76bb465a7164f907318cf58f77fc3d613f8f0f | https://github.com/Alexis-Fab/mmaction2/tree/6f76bb465a7164f907318cf58f77fc3d613f8f0f |
Model | import torch
import torch.nn as nn
class Model(nn.Module):
def __init__(self, input_dim, output_class_num, **kwargs):
super(Model, self).__init__()
self.linear = nn.Linear(input_dim, output_class_num)
def forward(self, features):
pooled = features.mean(dim=1)
predicted = 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | triper1022/s3prl | Model | false | 13,045 | [
"MIT"
] | 0 | d48e9e1d062d6cb14b66048eb56193fb50c60c24 | https://github.com/triper1022/s3prl/tree/d48e9e1d062d6cb14b66048eb56193fb50c60c24 |
HuEtAl | # 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 ... | dikers/DeepHyper | HuEtAl | false | 12,408 | [
"Apache-2.0"
] | 0 | 827a8f3077e18b71cf448a2e56e49670428b1bfd | https://github.com/dikers/DeepHyper/tree/827a8f3077e18b71cf448a2e56e49670428b1bfd |
FastRCNNPredictor | import torch
import torch.nn.functional as F
from torch import nn
class FastRCNNPredictor(nn.Module):
def __init__(self, in_channels, mid_channels, num_classes):
super().__init__()
self.fc1 = nn.Linear(in_channels, mid_channels)
self.fc2 = nn.Linear(mid_channels, mid_channels)
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 import nn
assert_s... | Jaramies/PyTorch-Simple-MaskRCNN | FastRCNNPredictor | false | 5,370 | [
"MIT"
] | 1 | 21e6c6983b34061800280573ebe705ae17212972 | https://github.com/Jaramies/PyTorch-Simple-MaskRCNN/tree/21e6c6983b34061800280573ebe705ae17212972 |
InnerProductDecoder | import torch
import torch.utils.data
class InnerProductDecoder(torch.nn.Module):
"""The inner product decoder from the `"Variational Graph Auto-Encoders"
<https://arxiv.org/abs/1611.07308>`_ paper
.. math::
\\sigma(\\mathbf{Z}\\mathbf{Z}^{\\top})
where :math:`\\mathbf{Z} \\in \\mathbb{R}^{N ... | 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_... | CFF-Dream/pytorch_geometric | InnerProductDecoder | false | 2,030 | [
"MIT"
] | 0 | 7c19ad74957409ee9e07314ce81524b3113b9c84 | https://github.com/CFF-Dream/pytorch_geometric/tree/7c19ad74957409ee9e07314ce81524b3113b9c84 |
FullAttention | # 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.... | HaotianUpenn/scatterbrain | FullAttention | false | 13,754 | [
"Apache-2.0"
] | 49 | c026128d7362ae627641d11d4e5627bc1f400eb1 | https://github.com/HaotianUpenn/scatterbrain/tree/c026128d7362ae627641d11d4e5627bc1f400eb1 |
ModulatedConv2d | import math
import torch
import torch.utils.data
import torch
import torch.nn as nn
import torch.nn.functional as F
def make_kernel(k):
k = torch.tensor(k, dtype=torch.float32)
if len(k.shape) == 1:
k = k[None, :] * k[:, None]
k /= k.sum()
return k
def upfirdn2d_native(input, kernel, up_x, u... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | bomtorazek/contrastive-unpaired-translation | ModulatedConv2d | false | 12,223 | [
"BSD-3-Clause"
] | 0 | 07c048038375e1b9a4e464154b8dbc49f5e16ede | https://github.com/bomtorazek/contrastive-unpaired-translation/tree/07c048038375e1b9a4e464154b8dbc49f5e16ede |
SelfAttention | import torch
import torch.nn as nn
class SelfAttention(nn.Module):
def __init__(self, hidden):
super(SelfAttention, self).__init__()
self.W = nn.Linear(hidden, 1)
def forward(self, x):
hidden = self.W(x)
scores = hidden.bmm(hidden.transpose(1, 2))
alpha = nn.functiona... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | IAMZn1018/ccks2021-entity-linking | SelfAttention | false | 9,105 | [
"Apache-2.0"
] | 0 | 6596b0b16d8c1fc4400c736b30ff46158d1575e4 | https://github.com/IAMZn1018/ccks2021-entity-linking/tree/6596b0b16d8c1fc4400c736b30ff46158d1575e4 |
RewardCriterion | import torch
import torch.nn as nn
from torch.autograd import *
class RewardCriterion(nn.Module):
def __init__(self):
super(RewardCriterion, self).__init__()
def forward(self, input, seq, reward):
input = input.gather(2, seq.unsqueeze(2)).squeeze(2)
input = input.reshape(-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
import torch.nn as nn
from torch.autograd import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | Romero027/ImageCaptioning.pytorch | RewardCriterion | false | 2,784 | [
"MIT"
] | 0 | 069c95f5d343fb126afa8b10ec18e472f30b7b35 | https://github.com/Romero027/ImageCaptioning.pytorch/tree/069c95f5d343fb126afa8b10ec18e472f30b7b35 |
BCELoss | import torch
import torch.nn as nn
class BCELoss(nn.Module):
def __init__(self):
super(BCELoss, self).__init__()
self.bce = nn.BCEWithLogitsLoss()
def forward(self, y_pred, y_true, weights=None):
loss_0 = self.bce(y_pred[:, 0], y_true[:, 0])
loss_1 = self.bce(y_pred[:, 1], y_... | 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... | CarlosPena00/pytorch-unet | BCELoss | false | 199 | [
"MIT"
] | 0 | 8365bace23e4b04b9c5b75cd6720807ea8cac5ab | https://github.com/CarlosPena00/pytorch-unet/tree/8365bace23e4b04b9c5b75cd6720807ea8cac5ab |
DiceCE_Loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch ... | JoaoCarv/holistic_seg | DiceCE_Loss | false | 677 | [
"MIT"
] | 0 | ea4787e7e9a36dc5caf198d2be1bd1e71c06d440 | https://github.com/JoaoCarv/holistic_seg/tree/ea4787e7e9a36dc5caf198d2be1bd1e71c06d440 |
ReconstructionLoss | # 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 functools import reduce
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
e... | ppalaupuigdevall/moments-vae | ReconstructionLoss | false | 7,488 | [
"MIT"
] | 1 | 99384094b5b7213e7669ad492f1b56216045b190 | https://github.com/ppalaupuigdevall/moments-vae/tree/99384094b5b7213e7669ad492f1b56216045b190 |
DynamicsModel | import torch
class DynamicsModel(torch.nn.Module):
def __init__(self, D_in, D_out, hidden_unit_num):
None
super(DynamicsModel, self).__init__()
self.l1 = torch.nn.Linear(D_in, hidden_unit_num)
self.l2 = torch.nn.Linear(hidden_unit_num, D_out)
self.logvar = torch.nn.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
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride ... | numahha/wmopo | DynamicsModel | false | 7,360 | [
"MIT"
] | 1 | 1557dab2e8168c1f2e53ffbc435b4000680f1d28 | https://github.com/numahha/wmopo/tree/1557dab2e8168c1f2e53ffbc435b4000680f1d28 |
LinearWithGroupNorm | import torch
import torch.utils.data
from torch import nn
from math import gcd
import torch.cuda
class LinearWithGroupNorm(nn.Module):
def __init__(self, n_in: 'int', n_out: 'int', num_groups: 'int'=32,
activation: 'bool'=True) ->None:
"""
Linear layer used in LaneGCN.
:param n_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
from torch._inductor.runtime.... | bradyz/nuplan-devkit | LinearWithGroupNorm | false | 12,259 | [
"Apache-2.0"
] | 0 | 0a7a30e5d7fdf3787d9388676b7856fbd7d92992 | https://github.com/bradyz/nuplan-devkit/tree/0a7a30e5d7fdf3787d9388676b7856fbd7d92992 |
RingLoss | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.data
from torch import nn
assert_size_stride = torch._C._dyn... | Luxios22/Dual_Norm | RingLoss | false | 9,276 | [
"MIT"
] | 0 | b404a03b15fc05749e0c648d9e46ffe70f6b2a80 | https://github.com/Luxios22/Dual_Norm/tree/b404a03b15fc05749e0c648d9e46ffe70f6b2a80 |
BasicModel_ConvNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | ngduduong/captum | BasicModel_ConvNet | false | 4,090 | [
"BSD-3-Clause"
] | 0 | 6fe5f0f23ea975e73e0c0dee79bdc01b4223d283 | https://github.com/ngduduong/captum/tree/6fe5f0f23ea975e73e0c0dee79bdc01b4223d283 |
MultiscaleL1Loss | import torch
import torch.utils.data
import torch
import torch.nn as nn
class MultiscaleL1Loss(nn.Module):
def __init__(self, scale=5):
super(MultiscaleL1Loss, self).__init__()
self.criterion = nn.L1Loss()
self.downsample = nn.AvgPool2d(2, stride=2, count_include_pad=False)
self.w... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.utils.dat... | WeisiX/ITAS3D | MultiscaleL1Loss | false | 18,116 | [
"MIT"
] | 4 | fc861e0cb2d4516905bfadab5e5e880c2b021832 | https://github.com/WeisiX/ITAS3D/tree/fc861e0cb2d4516905bfadab5e5e880c2b021832 |
InnerProductLayer | import torch
import torch.nn as nn
from sklearn.metrics import *
class InnerProductLayer(nn.Module):
"""InnerProduct Layer used in PNN that compute the element-wise
product or inner product between feature vectors.
Input shape
- a list of 3D tensor with shape: ``(batch_size,1,embedding_size)``.
... | 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... | liyunrui/DeepCTR-Torch | InnerProductLayer | false | 12,951 | [
"Apache-2.0"
] | 0 | 392fd6d39d9ca0ac854022136cdb4d5c68e3a592 | https://github.com/liyunrui/DeepCTR-Torch/tree/392fd6d39d9ca0ac854022136cdb4d5c68e3a592 |
BasicBlock | import torch
import torch.nn as nn
from torch.nn import functional as F
def apply_init_(modules):
"""
Initialize NN modules
"""
for m in modules:
if isinstance(m, nn.Conv2d):
nn.init.xavier_uniform_(m.weight)
if m.bias is not None:
nn.init.constant_(m.bi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 to... | krg-nandu/prj-taxRL | BasicBlock | false | 7,062 | [
"MIT"
] | 1 | be65d004c196aff73714dcb346c814ae97db30e2 | https://github.com/krg-nandu/prj-taxRL/tree/be65d004c196aff73714dcb346c814ae97db30e2 |
AlexNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | FujitsuLaboratories/CAC | AlexNet | false | 17,418 | [
"Apache-2.0"
] | 8 | d12df8e47f61eaf7d7b0ed355e2d1aa296453f86 | https://github.com/FujitsuLaboratories/CAC/tree/d12df8e47f61eaf7d7b0ed355e2d1aa296453f86 |
LayerNormChannel | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | TranNhiem/MA_SSRL_Pytorch | LayerNormChannel | false | 1,150 | [
"MIT"
] | 0 | 87d946461850240fdd54de761603f13ef3710c2b | https://github.com/TranNhiem/MA_SSRL_Pytorch/tree/87d946461850240fdd54de761603f13ef3710c2b |
RefineLoss | import torch
import numpy as np
import torch.nn as nn
class RefineLoss(nn.Module):
def __init__(self, alpha=1.5, alpha1=0.5, reduction='mean'):
super(RefineLoss, self).__init__()
self.alpha = alpha
self.alpha1 = alpha1
self.reduction = reduction
self.fx = nn.Conv2d(1, 1, 3... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ForrestPi/SegDL | RefineLoss | false | 5,172 | [
"MIT"
] | 1 | 56f2ff229dfa7540704d6de50292c724693aac75 | https://github.com/ForrestPi/SegDL/tree/56f2ff229dfa7540704d6de50292c724693aac75 |
AddCoords | # 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... | NguyenTheAn/AdaptiveWingLoss | AddCoords | false | 9,362 | [
"Apache-2.0"
] | 0 | abaade9521c1382739a158f3ad5ce493948add1d | https://github.com/NguyenTheAn/AdaptiveWingLoss/tree/abaade9521c1382739a158f3ad5ce493948add1d |
L2Norm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.nn.init as init
import torch.utils.data
from... | Tony-Khor/PyTorch-From-Zero-to-All | L2Norm | false | 5,909 | [
"MIT"
] | 1 | d8f9b6d81fe390dee93a887f342dc818553e61b3 | https://github.com/Tony-Khor/PyTorch-From-Zero-to-All/tree/d8f9b6d81fe390dee93a887f342dc818553e61b3 |
IA_gate | # 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 ... | yoxu515/CFBI | IA_gate | false | 16,766 | [
"BSD-3-Clause"
] | 312 | 0bab1e3c9fc3e3ba0629f716d60221e8f8d9d586 | https://github.com/yoxu515/CFBI/tree/0bab1e3c9fc3e3ba0629f716d60221e8f8d9d586 |
Actor | import torch
import torch.nn.functional as F
import torch.nn as nn
class Actor(nn.Module):
def __init__(self, hidden_size, num_inputs, action_space):
super(Actor, self).__init__()
self.action_space = action_space
num_outputs = action_space.shape[0]
self.linear1 = nn.Linear(num_inp... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | icml2019-anonymous-author/Action-Robust-Reinforcement-Learning | Actor | false | 6,847 | [
"MIT"
] | 1 | 03f0a1dd5f4a0fc5230c0ad0b41f63161bae862b | https://github.com/icml2019-anonymous-author/Action-Robust-Reinforcement-Learning/tree/03f0a1dd5f4a0fc5230c0ad0b41f63161bae862b |
RobertaClassificationHead | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | frankxu2004/CodeT5 | RobertaClassificationHead | false | 10,080 | [
"BSD-3-Clause"
] | 0 | 454e30a40b833a5ed862a1942f5d545e6a06b2b1 | https://github.com/frankxu2004/CodeT5/tree/454e30a40b833a5ed862a1942f5d545e6a06b2b1 |
AddTensors | # 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.hub
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo... | azavea/keras-image-segmentation | AddTensors | false | 9,770 | [
"Apache-2.0"
] | 0 | eb67d12e1c88f04387873444c7c9b05f767280e6 | https://github.com/azavea/keras-image-segmentation/tree/eb67d12e1c88f04387873444c7c9b05f767280e6 |
DispConv | # 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.... | prstrive/EPCDepth | DispConv | false | 16,280 | [
"MIT"
] | 76 | 84119c806741334b652749ee953e3eab60a3718c | https://github.com/prstrive/EPCDepth/tree/84119c806741334b652749ee953e3eab60a3718c |
Attention | # 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.... | Prasath2001/commonsense-rl | Attention | false | 2,735 | [
"Apache-2.0"
] | 0 | ef3e83270d34cf211b2d2086120cccae0621477b | https://github.com/Prasath2001/commonsense-rl/tree/ef3e83270d34cf211b2d2086120cccae0621477b |
InvDepth | # 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... | aliasghar53/packnet-sfm | InvDepth | false | 9,782 | [
"MIT"
] | 0 | d07dcbf026194b618a2bd9fc05b599563611f9a3 | https://github.com/aliasghar53/packnet-sfm/tree/d07dcbf026194b618a2bd9fc05b599563611f9a3 |
Conv2dTransposeBlock | import torch
from torch.nn import functional as F
from torch import nn
from torch.nn.utils import spectral_norm
class AdaptiveInstanceNorm2d(nn.Module):
def __init__(self, num_features, eps=1e-05, momentum=0.1):
super().__init__()
self.num_features = num_features
self.eps = eps
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.nn import function... | CompVis/interactive-image2video-synthesis | Conv2dTransposeBlock | false | 7,928 | [
"MIT"
] | 20 | 05ea449d3a2704b6d79a5f08683035220d615576 | https://github.com/CompVis/interactive-image2video-synthesis/tree/05ea449d3a2704b6d79a5f08683035220d615576 |
LogisticRegressionBinaryClassifier | import torch
import torch.nn as nn
import torch.utils.data
class LogisticRegressionBinaryClassifier(nn.Module):
def __init__(self, input_size):
super(LogisticRegressionBinaryClassifier, self).__init__()
self.input_size = input_size
self.mapping = nn.Linear(input_size, 1)
def forward(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | JayWalker512/PacketGAN | LogisticRegressionBinaryClassifier | false | 17,464 | [
"MIT"
] | 5 | 93d4266ab9299c25ffd1f0aedf68fa4639f66572 | https://github.com/JayWalker512/PacketGAN/tree/93d4266ab9299c25ffd1f0aedf68fa4639f66572 |
SeparableConvBlock | import math
import torch
import torch.utils.data
import torch.nn.functional as F
from itertools import product as product
from math import sqrt as sqrt
class Conv2dSamePadding(torch.nn.Conv2d):
"""
A wrapper around :class:`torch.nn.Conv2d` to support "SAME" padding mode and more features.
"""
def __i... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.utils.data
import torch.nn.functional as F
from itertoo... | StevenGrove/DynamicHead | SeparableConvBlock | false | 14,438 | [
"Apache-2.0"
] | 69 | d62aa84e1d1c6a0c74d46258ad77b11413c10bef | https://github.com/StevenGrove/DynamicHead/tree/d62aa84e1d1c6a0c74d46258ad77b11413c10bef |
K1TemporalBlock | # 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.... | whdc/TCN | K1TemporalBlock | false | 10,980 | [
"MIT"
] | 0 | 182a57da7790a8ddb3a94cc3c33e1476551e0b54 | https://github.com/whdc/TCN/tree/182a57da7790a8ddb3a94cc3c33e1476551e0b54 |
mlp_3layer | import torch
import torch.nn as nn
import torch.nn.functional as F
class mlp_3layer(nn.Module):
def __init__(self, in_ch, in_dim, width=1):
super(mlp_3layer, self).__init__()
self.fc1 = nn.Linear(in_ch * in_dim * in_dim, 256 * width)
self.fc2 = nn.Linear(256 * width, 128 * width)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | mnmueller/auto_LiRPA | mlp_3layer | false | 7,261 | [
"BSD-3-Clause"
] | 1 | 55cb270b0b99f07b74541d55706c69fbb9daff66 | https://github.com/mnmueller/auto_LiRPA/tree/55cb270b0b99f07b74541d55706c69fbb9daff66 |
IndepAnisotropicGaussianUVLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import math... | AbirKhan96/facebook-detectron2 | IndepAnisotropicGaussianUVLoss | false | 16,867 | [
"Apache-2.0"
] | 5 | 6a3bf813353d74bbeb8674e3566e7bbb33eb5c87 | https://github.com/AbirKhan96/facebook-detectron2/tree/6a3bf813353d74bbeb8674e3566e7bbb33eb5c87 |
L1GradientLoss | # 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.... | RunqiuBao/Event_ESTRNN | L1GradientLoss | false | 14,351 | [
"MIT"
] | 180 | 6d156cc42a3a33bd0b4b7c4c4be98f943ff53acb | https://github.com/RunqiuBao/Event_ESTRNN/tree/6d156cc42a3a33bd0b4b7c4c4be98f943ff53acb |
Sigmoid | import torch
import torch.nn as nn
class Sigmoid(torch.nn.Module):
def __init__(self, a=1, max=10):
super().__init__()
self.a = a
self.max = max
def forward(self, v):
sig = nn.Sigmoid()
act = sig(self.a * v) * self.max
return act
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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | ElliotHYLee/MyPyTorchAPI | Sigmoid | false | 11,395 | [
"MIT"
] | 0 | edb25b724372367e96e3bd2f420c023c4efbfcd7 | https://github.com/ElliotHYLee/MyPyTorchAPI/tree/edb25b724372367e96e3bd2f420c023c4efbfcd7 |
SimpleGCN | import math
import torch
import torch.nn as nn
from torch.nn.parameter import Parameter
from torch.nn import Parameter
import torch.nn
import torch.autograd
class SimpleGCN(nn.Module):
"""A simple graph convolution layer, similar to the one defined in
Kipf et al. https://arxiv.org/abs/1609.02907
.. note:... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
from ... | akashgokul/kaolin | SimpleGCN | false | 3,056 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 6360c4f2bcdd81f461dfb4d96267e79d89d5e112 | https://github.com/akashgokul/kaolin/tree/6360c4f2bcdd81f461dfb4d96267e79d89d5e112 |
GatedConvTranspose | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | musyoku/ffjord | GatedConvTranspose | false | 7,304 | [
"MIT"
] | 1 | 9e431e122e59fa9a71f3f301dec8fdd3db51e0ce | https://github.com/musyoku/ffjord/tree/9e431e122e59fa9a71f3f301dec8fdd3db51e0ce |
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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | CityU-AIM-Group/PRR-Imbalance | DiceLoss | false | 8,914 | [
"MIT"
] | 0 | e893809c72697511897c9100c25f831087fc345f | https://github.com/CityU-AIM-Group/PRR-Imbalance/tree/e893809c72697511897c9100c25f831087fc345f |
ENC_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
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | amonod/udvd | ENC_Conv | false | 1,441 | [
"MIT"
] | 0 | a1ccb777d205255ac68c40efb93dd3996f562c45 | https://github.com/amonod/udvd/tree/a1ccb777d205255ac68c40efb93dd3996f562c45 |
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