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 |
|---|---|---|---|---|---|---|---|---|---|---|
PatchSequential | import math
import torch
import warnings
from typing import Dict
from typing import Optional
from typing import Tuple
import torch.nn as nn
import torch.nn.functional as F
from typing import cast
from typing import List
from typing import Union
from torch.distributions import Bernoulli
from itertools import zip_longest... | 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 warnings
from typing import Dict
from typing import Optional
from typing import Tuple
import torch.nn as nn
import torch.... | JoanFM/kornia | PatchSequential | false | 11,576 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 808898887cde69074ca3e3df9b24dea9682aad90 | https://github.com/JoanFM/kornia/tree/808898887cde69074ca3e3df9b24dea9682aad90 |
Critic | import torch
import torch.nn as nn
class Critic(nn.Module):
def __init__(self, state_dim, hidden_dim=64):
super(Critic, self).__init__()
self.l1 = nn.Linear(state_dim, hidden_dim)
self.l2 = nn.Linear(hidden_dim, hidden_dim)
self.l3 = nn.Linear(hidden_dim, 1)
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.triton_helpers import libdevice
import torch.nn as ... | LQNew/LWDRL | Critic | false | 8,420 | [
"MIT"
] | 11 | 0e4fab077a0cfbd27590b840557f4fda033c74ff | https://github.com/LQNew/LWDRL/tree/0e4fab077a0cfbd27590b840557f4fda033c74ff |
ZeroPad1d | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
import torch.onnx.operators
import torch.optim
import torch.optim.lr_scheduler
assert_size_str... | GT-SALT/FormalityStyleTransfer | ZeroPad1d | false | 17,332 | [
"MIT"
] | 8 | a86d287d0c48238f7cd39f6f34b465b0b7ccb2f4 | https://github.com/GT-SALT/FormalityStyleTransfer/tree/a86d287d0c48238f7cd39f6f34b465b0b7ccb2f4 |
SpectrogramMasker | import torch
import torch.nn as nn
import torch.nn.functional as F
class SpectrogramMasker(nn.Module):
def __init__(self, win_length: 'int'=400, hop_length: 'int'=200):
super().__init__()
self.win_length = win_length
self.conv = nn.Conv1d(1, 1, self.win_length, stride=hop_length,
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | AppleHolic/2020AIChallengeSpeechRecognition | SpectrogramMasker | false | 16,941 | [
"MIT"
] | 9 | 62002f036a4bb4ab23f7bdba73f19e97e0ac7087 | https://github.com/AppleHolic/2020AIChallengeSpeechRecognition/tree/62002f036a4bb4ab23f7bdba73f19e97e0ac7087 |
GlobalAvgPool2d | # 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.optim.lr_scheduler import *
import torch.optim
import torch.nn as nn
import torch.utils.data
import torch.utils.model_zoo
assert_... | ChitienSun/NCTU_DLSR_final_project | GlobalAvgPool2d | false | 265 | [
"MIT"
] | 0 | 9d647426c274afc7651ea4fe9a11f2a0a0fd1fba | https://github.com/ChitienSun/NCTU_DLSR_final_project/tree/9d647426c274afc7651ea4fe9a11f2a0a0fd1fba |
BasicCNN1 | import torch
import torch.nn as nn
import torch.nn.functional as F
class BasicCNN1(nn.Module):
def __init__(self):
super().__init__()
self.layer_names = ['conv1', 'conv2', 'conv3', 'fc1', 'output_layer']
self.conv1 = nn.Conv2d(3, 32, 3, padding=1)
self.conv2 = nn.Conv2d(32, 64, 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
import torch.nn as nn
assert_... | fnc11/CosDefence | BasicCNN1 | false | 10,119 | [
"MIT"
] | 0 | 94f451b7d4b36cb3b9fcc85098dae242f311532b | https://github.com/fnc11/CosDefence/tree/94f451b7d4b36cb3b9fcc85098dae242f311532b |
PatchEmbed | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | daniel347x/dino | PatchEmbed | false | 10,016 | [
"Apache-2.0"
] | 0 | bb96d041de246ad0dc9672471911467fe635b018 | https://github.com/daniel347x/dino/tree/bb96d041de246ad0dc9672471911467fe635b018 |
Attention | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import *
class Attention(nn.Module):
def __init__(self, opt):
super(Attention, self).__init__()
self.rnn_size = opt.rnn_size
self.att_hid_size = opt.att_hid... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | SunZongdi/self-critical.pytorch | Attention | false | 5,864 | [
"MIT"
] | 1 | 6cecbeb949e68007b72e84198cf74f9fb288aeda | https://github.com/SunZongdi/self-critical.pytorch/tree/6cecbeb949e68007b72e84198cf74f9fb288aeda |
GaussianSmearing | import torch
import torch.nn as nn
class GaussianSmearing(nn.Module):
def __init__(self, in_features, start=0, end=1, num_freqs=50):
super(GaussianSmearing, self).__init__()
self.num_freqs = num_freqs
offset = torch.linspace(start, end, num_freqs)
self.coeff = -0.5 / (offset[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.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | RolnickLab/ocp | GaussianSmearing | false | 2,779 | [
"MIT"
] | 0 | e120c3b90203a46f5fc7626f0b5c8979e4944765 | https://github.com/RolnickLab/ocp/tree/e120c3b90203a46f5fc7626f0b5c8979e4944765 |
mlp | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | EuphoriaYan/sales_pred | mlp | false | 2,221 | [
"MIT"
] | 0 | cc39c32a3387285f3561aeeea7a133810069dc98 | https://github.com/EuphoriaYan/sales_pred/tree/cc39c32a3387285f3561aeeea7a133810069dc98 |
IOUloss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | LSH9832/MyPythonModules | IOUloss | false | 741 | [
"MIT"
] | 0 | 442566a0fbd6ebe2bc20b6914686a1e2663d10c0 | https://github.com/LSH9832/MyPythonModules/tree/442566a0fbd6ebe2bc20b6914686a1e2663d10c0 |
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... | Elameri/ivadomed | DiceLoss | false | 9,310 | [
"MIT"
] | 0 | 76b5cea46f90f938aafd5ec26e072d559c764b43 | https://github.com/Elameri/ivadomed/tree/76b5cea46f90f938aafd5ec26e072d559c764b43 |
SoftClDiceLoss | # 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 numpy as np
from torch import nn
import torch.jit
import torch.nn.functional as F
... | CamilaGL/nnUNet | SoftClDiceLoss | false | 1,175 | [
"Apache-2.0"
] | 0 | 471ab73a6e4f67fc72d476183b5344be4cccf7ca | https://github.com/CamilaGL/nnUNet/tree/471ab73a6e4f67fc72d476183b5344be4cccf7ca |
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.... | Abhimanyu08/minbert-assignment | BertLayer | false | 13,211 | [
"Apache-2.0"
] | 0 | 1610364213b1aab2d5446175dffabd7e1742833b | https://github.com/Abhimanyu08/minbert-assignment/tree/1610364213b1aab2d5446175dffabd7e1742833b |
FlawDetectorCriterion | # 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... | ZHKKKe/PixelSSL | FlawDetectorCriterion | false | 14,706 | [
"Apache-2.0"
] | 223 | ce192034355ae6a77e47d2983d9c9242df60802a | https://github.com/ZHKKKe/PixelSSL/tree/ce192034355ae6a77e47d2983d9c9242df60802a |
SpatialTransformerPooled2d | import torch
from torch import nn
from torch.nn import Parameter
from torch.nn import functional as F
def positive(weight, cache=None):
weight.data *= weight.data.ge(0).float()
return cache
class SpatialTransformerPooled2d(nn.Module):
def __init__(self, in_shape, outdims, pool_steps=1, positive=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 import nn
from torch.nn import Parameter
assert_size_stride = torch._C._dynamo... | dattientran/attorch | SpatialTransformerPooled2d | false | 12,402 | [
"MIT"
] | 0 | 469b225846c6d8a7d833ebac19d040c7a407a0ff | https://github.com/dattientran/attorch/tree/469b225846c6d8a7d833ebac19d040c7a407a0ff |
FeatureCorrelation | import torch
import torch.nn as nn
import torch.nn
def featureL2Norm(feature):
epsilon = 1e-06
norm = torch.pow(torch.sum(torch.pow(feature, 2), 1) + epsilon, 0.5
).unsqueeze(1).expand_as(feature)
return torch.div(feature, norm)
class FeatureCorrelation(torch.nn.Module):
def __init__(self, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | JiwonCocoder/-Joint-Learning-of-Feature-Extraction-and-Cost-Aggregation-for-Semantic-Matching | FeatureCorrelation | false | 5,408 | [
"MIT"
] | 1 | b79e0e20fd5a1a9ddc0ffa9d7a92e0ebd21018b9 | https://github.com/JiwonCocoder/-Joint-Learning-of-Feature-Extraction-and-Cost-Aggregation-for-Semantic-Matching/tree/b79e0e20fd5a1a9ddc0ffa9d7a92e0ebd21018b9 |
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.... | RyanWangZf/SurvTRACE | BertLayer | false | 18,392 | [
"MIT"
] | 8 | d55299a28629d233f49ad1feaea7ed00835f0dd0 | https://github.com/RyanWangZf/SurvTRACE/tree/d55299a28629d233f49ad1feaea7ed00835f0dd0 |
ConvElu | # 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... | Observer007/intel-extension-for-pytorch | ConvElu | false | 5,690 | [
"Apache-2.0"
] | 1 | f8ab25c305c89d5aaf06190a4fec0727aeb4dcd7 | https://github.com/Observer007/intel-extension-for-pytorch/tree/f8ab25c305c89d5aaf06190a4fec0727aeb4dcd7 |
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
... | Chuxwa/OpenPCDet | WeightedCrossEntropyLoss | false | 5,010 | [
"Apache-2.0"
] | 1 | be064eafee68cb23f4bbe7decf2286ef13a94ebb | https://github.com/Chuxwa/OpenPCDet/tree/be064eafee68cb23f4bbe7decf2286ef13a94ebb |
ISAB | # 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.... | AntonValk/BagGraph-Graph-MIL | ISAB | false | 16,957 | [
"MIT"
] | 8 | 1447b52b32995cf6c71e731dd1261104cd66ced0 | https://github.com/AntonValk/BagGraph-Graph-MIL/tree/1447b52b32995cf6c71e731dd1261104cd66ced0 |
Block | # 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.fun... | CarnoZhao/mmdetection | Block | false | 17,091 | [
"Apache-2.0"
] | 10 | b85eaffdf1af28eaffcc2263110a059237cf5b23 | https://github.com/CarnoZhao/mmdetection/tree/b85eaffdf1af28eaffcc2263110a059237cf5b23 |
Generator | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | cclaypool/pytorch-dcgan | Generator | false | 6,399 | [
"MIT"
] | 1 | a2096daf7bb75bf95e189bb3d2f820c51147b61c | https://github.com/cclaypool/pytorch-dcgan/tree/a2096daf7bb75bf95e189bb3d2f820c51147b61c |
LayerNorm | import torch
import torch.nn as nn
class LayerNorm(nn.Module):
def __init__(self, num_features, eps=1e-05, affine=True):
super(LayerNorm, self).__init__()
self.num_features = num_features
self.affine = affine
self.eps = eps
if self.affine:
self.gamma = nn.Param... | 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_... | AnnanShu/gan | LayerNorm | false | 8,988 | [
"MIT"
] | 0 | 0c6409872ce65fe046e620fca053cff553bba9ef | https://github.com/AnnanShu/gan/tree/0c6409872ce65fe046e620fca053cff553bba9ef |
GlobalpoolFC | import torch
import torch.nn as nn
class GlobalpoolFC(nn.Module):
def __init__(self, num_in, num_class):
super(GlobalpoolFC, self).__init__()
self.pool = nn.AdaptiveAvgPool2d(output_size=1)
self.fc = nn.Linear(num_in, num_class)
def forward(self, x):
y = 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... | blackcow/pytorch-cifar-master | GlobalpoolFC | false | 3,218 | [
"MIT"
] | 0 | c571c8fd7fe521907755ca2eacb6aa877abe3493 | https://github.com/blackcow/pytorch-cifar-master/tree/c571c8fd7fe521907755ca2eacb6aa877abe3493 |
FullyConnectedHead | # 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 typing import Any
from typing import Dict
from typing import Optional
impor... | dendisuhubdy/ClassyVision | FullyConnectedHead | false | 10,011 | [
"MIT"
] | 0 | c7f8de4615181b5a14dd5ec44fa72bebb790e886 | https://github.com/dendisuhubdy/ClassyVision/tree/c7f8de4615181b5a14dd5ec44fa72bebb790e886 |
LipschitzCube | import torch
from torch import nn
import torch.utils.data.distributed
class LipschitzCube(nn.Module):
def forward(self, x):
return (x >= 1) * (x - 2 / 3) + (x <= -1) * (x + 2 / 3) + (x > -1) * (x
< 1) * x ** 3 / 3
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_input... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.utils.data.distributed
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda ... | rh-ia/color-information | LipschitzCube | false | 4,281 | [
"MIT"
] | 0 | e912a1667e4fffb339dbc574c85020ec6cf78b02 | https://github.com/rh-ia/color-information/tree/e912a1667e4fffb339dbc574c85020ec6cf78b02 |
GraphConvolution | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn import Module
i... | PatriciaXiao/gae-pytorch | GraphConvolution | false | 11,777 | [
"MIT"
] | 0 | eb0e9bdf9a2f23d38941ac731bd481bd6da737b9 | https://github.com/PatriciaXiao/gae-pytorch/tree/eb0e9bdf9a2f23d38941ac731bd481bd6da737b9 |
FeatureSelect | import torch
import torch.optim
import torch.nn as nn
class FeatureSelect(nn.Module):
def __init__(self, in_dim=84, ratio=0.5):
"""
Feature Select via Sorting
Args:
in_dim: the number of dimensions of raw features
ratio: the portion of selected features
""... | 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.optim
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.ass... | Fyy10/UESTC-Thesis-DA | FeatureSelect | false | 498 | [
"MIT"
] | 0 | 6cb16efd1f80aa569c90874a806a62dec8afaec4 | https://github.com/Fyy10/UESTC-Thesis-DA/tree/6cb16efd1f80aa569c90874a806a62dec8afaec4 |
L1Loss | import functools
import torch
import torch.nn as nn
import torch.cuda.comm
from torch.nn import functional as F
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
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
import functools
impor... | JasonBoy1/mmhuman3d | L1Loss | false | 5,378 | [
"Apache-2.0"
] | 1 | 79b2665191115f3ed905e6afdf09990a8d484362 | https://github.com/JasonBoy1/mmhuman3d/tree/79b2665191115f3ed905e6afdf09990a8d484362 |
CosineAngularLoss | import torch
import torch.nn as nn
import torch.nn.parallel
class CosineAngularLoss(nn.Module):
def __init__(self):
super(CosineAngularLoss, self).__init__()
def forward(self, preds, truths):
preds_norm = torch.nn.functional.normalize(preds, p=2, dim=1)
truths_norm = torch.nn.functio... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import... | princeton-vl/oasis | CosineAngularLoss | false | 16,281 | [
"BSD-3-Clause"
] | 59 | 5835d24c331d78e91becba29f7e4a53ccd3e376e | https://github.com/princeton-vl/oasis/tree/5835d24c331d78e91becba29f7e4a53ccd3e376e |
FusedLeakyReLU | import torch
import torch.utils.data
import torch
from torch import nn
import torch.nn.functional as F
def fused_leaky_relu(input, bias, negative_slope=0.2, scale=2 ** 0.5):
return F.leaky_relu(input + bias, negative_slope) * scale
class FusedLeakyReLU(nn.Module):
def __init__(self, channel, negative_slope... | 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
from torch import nn
import torch.nn.functional as F
assert_size_stride = torch._C._dynamo.guards.asser... | guyii54/Contrastive-I2I | FusedLeakyReLU | false | 6,769 | [
"BSD-3-Clause"
] | 1 | e73daa0f9d3770c2280a304c39678d5b22440647 | https://github.com/guyii54/Contrastive-I2I/tree/e73daa0f9d3770c2280a304c39678d5b22440647 |
ScaleNorm | import torch
from torch import nn
class ScaleNorm(nn.Module):
def __init__(self, dim, eps=1e-05):
super().__init__()
self.scale = dim ** -0.5
self.g = nn.Parameter(torch.ones(1))
self.eps = eps
def forward(self, x):
n = torch.norm(x, dim=-1, keepdim=True).clamp(min=se... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_... | Azerrroth/spacetimeformer | ScaleNorm | false | 92 | [
"MIT"
] | 0 | e822444a6d696a1edb9e446d6f3482a70681be3c | https://github.com/Azerrroth/spacetimeformer/tree/e822444a6d696a1edb9e446d6f3482a70681be3c |
Clump | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | antigab/LightAutoML | Clump | false | 14,873 | [
"Apache-2.0"
] | 766 | 51a4e2bd0ebffbe0817fb50434280f8e7c40fa4c | https://github.com/antigab/LightAutoML/tree/51a4e2bd0ebffbe0817fb50434280f8e7c40fa4c |
CriticNetwork | # 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 numpy as np
import tor... | Yang2581/Behavioral-Cloning | CriticNetwork | false | 1,881 | [
"MIT"
] | 0 | 426e68a639e3e341f5547cfe40fb03ed8e87f3c8 | https://github.com/Yang2581/Behavioral-Cloning/tree/426e68a639e3e341f5547cfe40fb03ed8e87f3c8 |
combLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class combLoss(nn.Module):
def __init__(self, margin, l=1):
super(combLoss, self).__init__()
self.margin = margin
self.l = l
def forward(self, anchor, pos, neg):
distance_pos = (anchor - pos).pow(2).sum(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... | MingzheWu418/plastering | combLoss | false | 9,321 | [
"MIT"
] | 0 | 322531e934c3acf2ecc8f520b37a6d255b9959c2 | https://github.com/MingzheWu418/plastering/tree/322531e934c3acf2ecc8f520b37a6d255b9959c2 |
ycbcr_to_rgb_jpeg | import torch
import numpy as np
from torch import nn
class ycbcr_to_rgb_jpeg(nn.Module):
""" Converts YCbCr image to RGB JPEG
Input:
image(tensor): batch x height x width x 3
Outpput:
result(tensor): batch x 3 x height x width
"""
def __init__(self):
super(ycbcr_to_rgb_jpe... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import numpy as np
from torch import nn
assert_size_stride = torch._C._dynamo.gu... | Liamkuo/SAIR | ycbcr_to_rgb_jpeg | false | 17,572 | [
"MIT"
] | 6 | 0fb289cd975b5a196b58e7d16bac00e31fd41d39 | https://github.com/Liamkuo/SAIR/tree/0fb289cd975b5a196b58e7d16bac00e31fd41d39 |
outconv | import torch
import torch.nn as nn
class outconv(nn.Module):
def __init__(self, in_ch, out_ch):
super(outconv, self).__init__()
self.conv = nn.Conv2d(in_ch, out_ch, 1)
def forward(self, x):
x = self.conv(x)
return x
def get_inputs():
return [torch.rand([4, 4, 4, 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | AnonymousAuthors444/VEC_VAD | outconv | false | 13,309 | [
"MIT"
] | 67 | 0072bf857030e621e2f9c12689407b81e45ed603 | https://github.com/AnonymousAuthors444/VEC_VAD/tree/0072bf857030e621e2f9c12689407b81e45ed603 |
SamePadConv3d | import torch
import torch.nn as nn
import torch.nn.functional as F
class SamePadConv3d(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, stride=1,
bias=True):
super().__init__()
if isinstance(kernel_size, int):
kernel_size = (kernel_size,) * 3
if 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 torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | pointoflight/VideoGPT | SamePadConv3d | false | 7,485 | [
"MIT"
] | 1 | 85f19d8cb0d251238f295f0294e69b9299c13e21 | https://github.com/pointoflight/VideoGPT/tree/85f19d8cb0d251238f295f0294e69b9299c13e21 |
DDPGActor | import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
def fanin_init(size, fanin=None):
"""
Initilise network weights
"""
fanin = fanin or size[0]
v = 1.0 / np.sqrt(fanin)
return torch.Tensor(size).uniform_(-v, v)
class DDPGActor(nn.Module):
"""
Pytorc... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Nikhil-Paleti/sawyer_analysis_reinforcement_learning | DDPGActor | false | 4,370 | [
"MIT"
] | 0 | dc774c9a162fabb98493b69d7656cb14cb37f094 | https://github.com/Nikhil-Paleti/sawyer_analysis_reinforcement_learning/tree/dc774c9a162fabb98493b69d7656cb14cb37f094 |
Linear3D | import math
import torch
import torch as th
from torch.nn import Parameter
def functional_linear3d(input, weight, bias=None):
"""
Apply a linear transformation to the incoming data: :math:`y = xA^T + b`.
Shape:
- Input: :math:`(N, *, in\\_features)` where `*` means any number of
additio... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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 as th
from torch.nn import Parameter
assert_size_stride... | edgarvardanyan/CausalDiscoveryToolbox | Linear3D | false | 10,249 | [
"MIT"
] | 0 | 5497a400440b49a3af14a0c7512bcdd307c9285d | https://github.com/edgarvardanyan/CausalDiscoveryToolbox/tree/5497a400440b49a3af14a0c7512bcdd307c9285d |
ContentLoss | import torch
from torch import nn
class ContentLoss(nn.Module):
"""Module to compute the content loss. Allows arbitrary size style images
during initialization and updating the content target.
Usage: During loss network definition set compute_loss to False, to allow,
after initialization iterate throu... | 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... | RicCu/NeuralStyle | ContentLoss | false | 5,763 | [
"MIT"
] | 1 | 97dc6aec6b2072a9a187276e047aea885566e1be | https://github.com/RicCu/NeuralStyle/tree/97dc6aec6b2072a9a187276e047aea885566e1be |
DecoderLayer | import math
import torch
import torch.utils.data
import torch.nn as nn
import torch.nn.functional as F
class MultiHeadAttention(nn.Module):
def __init__(self, heads, d_model):
super(MultiHeadAttention, self).__init__()
assert d_model % heads == 0
self.d_k = d_model // heads
self.h... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | sd2001/seqModeling | DecoderLayer | false | 13,003 | [
"MIT"
] | 0 | 393f680de711ea8477e5450633b492298d253368 | https://github.com/sd2001/seqModeling/tree/393f680de711ea8477e5450633b492298d253368 |
NormLayer | import torch
import torch.nn as nn
class NormLayer(nn.Module):
def __init__(self, mean, std, n=None, eps=1e-08) ->None:
super().__init__()
self.mean = mean
self.std = std
self.eps = eps
def forward(self, x):
return (x - self.mean) / (self.std + self.eps)
def get_inp... | 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... | YNNEKUW/captum | NormLayer | false | 12,019 | [
"BSD-3-Clause"
] | 0 | c8b5357b21f2ddf440e5f0ce25635977292aa5d1 | https://github.com/YNNEKUW/captum/tree/c8b5357b21f2ddf440e5f0ce25635977292aa5d1 |
MV_Softmax | # 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.... | cavalleria/FaceX-Zoo | MV_Softmax | false | 6,405 | [
"Apache-2.0"
] | 1 | c4bf8924f1858928f8cf83efabf8ad237c67f620 | https://github.com/cavalleria/FaceX-Zoo/tree/c4bf8924f1858928f8cf83efabf8ad237c67f620 |
MultiLayeredConv1d | # 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.utils.data.distr... | MarkWuNLP/StreamingTransformer | MultiLayeredConv1d | false | 813 | [
"Apache-2.0"
] | 0 | df9bfe348608b7e55ef1ff70464070c0055ea799 | https://github.com/MarkWuNLP/StreamingTransformer/tree/df9bfe348608b7e55ef1ff70464070c0055ea799 |
Categorical | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
from matplotlib.font_manager import *
assert_size_s... | zifeiyu0531/TSP_DRL_PtrNet | Categorical | false | 4,686 | [
"MIT"
] | 0 | c62fab73347556173d301c1561edf927e6fbe1d7 | https://github.com/zifeiyu0531/TSP_DRL_PtrNet/tree/c62fab73347556173d301c1561edf927e6fbe1d7 |
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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | soffiafdz/nma-dl-modality-mongoose | diceloss | false | 12,993 | [
"MIT"
] | 0 | 41ac1f2e0e818538bafedae93e5c68f8857411bd | https://github.com/soffiafdz/nma-dl-modality-mongoose/tree/41ac1f2e0e818538bafedae93e5c68f8857411bd |
BipolarSigmoid | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | awlange/pysurvival | BipolarSigmoid | false | 14,918 | [
"Apache-2.0"
] | 242 | 841b9bc6ce700ba8898d2a1488aa9cd25ee7a8e6 | https://github.com/awlange/pysurvival/tree/841b9bc6ce700ba8898d2a1488aa9cd25ee7a8e6 |
TokenEmbedding | import torch
import torch.nn as nn
class TokenEmbedding(nn.Module):
def __init__(self, c_in, d_model):
super(TokenEmbedding, self).__init__()
padding = 1 if torch.__version__ >= '1.5.0' else 2
self.tokenConv = nn.Conv1d(in_channels=c_in, out_channels=d_model,
kernel_size=3, pa... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | Fanxingye/Informer2020 | TokenEmbedding | false | 440 | [
"Apache-2.0"
] | 0 | 94fd05f82ff0882681a9716ae3e980a574fdcbed | https://github.com/Fanxingye/Informer2020/tree/94fd05f82ff0882681a9716ae3e980a574fdcbed |
NoiseLayer | import torch
import torch.nn as nn
class NoiseLayer(nn.Module):
"""adds noise. noise is per pixel (constant over channels) with per-channel weight"""
def __init__(self, channels):
super().__init__()
self.weight = nn.Parameter(torch.zeros(channels))
self.noise = None
def forward(s... | import torch
from torch import device
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C... | AleksiKnuutila/ganspace | NoiseLayer | false | 1,917 | [
"Apache-2.0"
] | 0 | 23471a07c8b0d693fa7f1f2dfbb8b34ce22d9d38 | https://github.com/AleksiKnuutila/ganspace/tree/23471a07c8b0d693fa7f1f2dfbb8b34ce22d9d38 |
TripletSoftmaxLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class TripletSoftmaxLoss(nn.Module):
def __init__(self, margin=0.0, lambda_factor=0.01):
super(TripletSoftmaxLoss, self).__init__()
self.margin = margin
self.loss_fn = nn.CrossEntropyLoss()
self.lambda_factor = lam... | 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
... | Lm0079/MetricLearningIdentification | TripletSoftmaxLoss | false | 2,526 | [
"MIT"
] | 0 | 3c2c0512fe2fbbb6aacb958106d5f6a03baedc35 | https://github.com/Lm0079/MetricLearningIdentification/tree/3c2c0512fe2fbbb6aacb958106d5f6a03baedc35 |
PVABlock | import torch
import torch.nn as nn
def constant_init(module, val, bias=0):
nn.init.constant_(module.weight, val)
if hasattr(module, 'bias') and module.bias is not None:
nn.init.constant_(module.bias, bias)
def kaiming_init(module, a=0, is_rnn=False, mode='fan_in', nonlinearity=
'leaky_relu', bia... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | wu0004in/vedastr | PVABlock | false | 4,561 | [
"Apache-2.0"
] | 0 | 83511a408b68c264561a30daff5154cd0148bebd | https://github.com/wu0004in/vedastr/tree/83511a408b68c264561a30daff5154cd0148bebd |
ADD | import torch
import torch.nn as nn
import torch.utils.data
class ADD(nn.Module):
def __init__(self, alpha=0.5):
super(ADD, self).__init__()
self.a = alpha
def forward(self, x):
return torch.add(x, self.a)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | COEN-390/YOLOv5-Lite | ADD | false | 11,263 | [
"MIT"
] | 0 | 06a53f5d001c5d37729f55f47cbd46cc8eb63f84 | https://github.com/COEN-390/YOLOv5-Lite/tree/06a53f5d001c5d37729f55f47cbd46cc8eb63f84 |
BatchSpectralShrinkage | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | XianyuanLiu/Transfer-Learning-Library | BatchSpectralShrinkage | false | 10,138 | [
"MIT"
] | 0 | 25f83f32437032df88ca6101ecd1f63ec7a0aa2c | https://github.com/XianyuanLiu/Transfer-Learning-Library/tree/25f83f32437032df88ca6101ecd1f63ec7a0aa2c |
BertMixedLayer | from _paritybench_helpers import _mock_config
import math
import torch
import torch.nn
import torch.nn as nn
class BertAttention(nn.Module):
"""BERT attention layer.
Based on: BERT (pytorch-transformer)
https://github.com/huggingface/transformers
"""
def __init__(self, config) ->None:
sup... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | bamf-health/MONAI | BertMixedLayer | false | 1,542 | [
"Apache-2.0"
] | 0 | 6a2086d21baf4b60c2ab3d400ed5c97cf24a0da9 | https://github.com/bamf-health/MONAI/tree/6a2086d21baf4b60c2ab3d400ed5c97cf24a0da9 |
Reorg | import torch
import torch.nn as nn
import torch.utils.data
class Reorg(nn.Module):
def __init__(self, stride=2):
super(Reorg, self).__init__()
self.stride = stride
def forward(self, x):
stride = self.stride
assert x.data.dim() == 4
B = x.data.size(0)
C = x.dat... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | AP-EPFL/DA-segmentation-driven-pose | Reorg | false | 4,761 | [
"MIT"
] | 1 | 451b8ee3619b16db152ac37ba2b64f7ebf5e2832 | https://github.com/AP-EPFL/DA-segmentation-driven-pose/tree/451b8ee3619b16db152ac37ba2b64f7ebf5e2832 |
GlobalAvgPool2d | import torch
import torch.nn as nn
import torch.nn.functional as F
class GlobalAvgPool2d(nn.Module):
def __init__(self):
super(GlobalAvgPool2d, self).__init__()
def forward(self, x):
N = x.data.size(0)
C = x.data.size(1)
H = x.data.size(2)
W = x.data.size(3)
x... | 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... | Zhang-Jack/adversarial_yolo2 | GlobalAvgPool2d | false | 18,190 | [
"MIT"
] | 8 | 91c2a4793047f656482cebf0309984db823e8030 | https://github.com/Zhang-Jack/adversarial_yolo2/tree/91c2a4793047f656482cebf0309984db823e8030 |
Attention | import math
import torch
from torch import nn
from torch.nn import Linear
import torch as t
from torch.autograd import Variable
class MultiheadAttention(nn.Module):
"""Multihead attention mechanism (dot attention)."""
def __init__(self, num_hidden_k):
""":param num_hidden_k: dimension of hidden."""
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | pppku/SVS_system | Attention | false | 16,290 | [
"Apache-2.0"
] | 78 | 95ef1076c51bfc0b74349b8058a9c918ff24c500 | https://github.com/pppku/SVS_system/tree/95ef1076c51bfc0b74349b8058a9c918ff24c500 |
MutualInfoLoss | import torch
from torch import nn
class MutualInfoLoss(nn.Module):
"""
Mutual Information Loss derived from ss-with-RIM that also applied in
this work.
First term enforces to generate a sparse nSpixel dimension vector for
each pixel; Second term indicates the cardinality of each sp... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_... | yueyu-stu/EdgeAwareSpixel | MutualInfoLoss | false | 11,061 | [
"MIT"
] | 0 | f7f9fcb15bfa8e31bd4ad9473f9058c44a8391d7 | https://github.com/yueyu-stu/EdgeAwareSpixel/tree/f7f9fcb15bfa8e31bd4ad9473f9058c44a8391d7 |
Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | Daiver/torch_fuze | Net | false | 5,043 | [
"MIT"
] | 1 | 6b7ad568e2d7549c7f0c0d4c309532ac1b92881d | https://github.com/Daiver/torch_fuze/tree/6b7ad568e2d7549c7f0c0d4c309532ac1b92881d |
SoftmaxModule | import torch
import torch.nn as nn
class SoftmaxModule(nn.Module):
def __init__(self, axis):
super().__init__()
self.axis = axis
def forward(self, v):
return v.softmax(self.axis)
def get_inputs():
return [torch.rand([4, 4, 4, 4, 4])]
def get_init_inputs():
return [[], {'a... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | finalgruntgit/diautils | SoftmaxModule | false | 10,276 | [
"MIT"
] | 0 | b9d7666ed5023700db01a4295430c52721acfc25 | https://github.com/finalgruntgit/diautils/tree/b9d7666ed5023700db01a4295430c52721acfc25 |
LocalDictionaryLoss | import torch
import torch.nn
class LocalDictionaryLoss(torch.nn.Module):
def __init__(self, penalty):
super(LocalDictionaryLoss, self).__init__()
self.penalty = penalty
def forward(self, A, y, x):
return self.forward_detailed(A, y, x)[2]
def forward_detailed(self, A, y, 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
... | pbt17/manifold-learning-with-simplex-constraints | LocalDictionaryLoss | false | 7,452 | [
"MIT"
] | 1 | 36609e2d05600965ee1331823547a077ba7b5a51 | https://github.com/pbt17/manifold-learning-with-simplex-constraints/tree/36609e2d05600965ee1331823547a077ba7b5a51 |
TorchModule | import torch
import torch.nn
class TorchLinearModule(torch.nn.Module):
def __init__(self, in_size, out_size):
super(TorchLinearModule, self).__init__()
self._linear = torch.nn.Linear(in_size, out_size)
def forward(self, x):
return self._linear(x)
class TorchModule(torch.nn.Module):... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn
ass... | Cher-B/ivy | TorchModule | false | 13,494 | [
"Apache-2.0"
] | 161 | 95273172201071ebf7b83d56bb314450ebe41071 | https://github.com/Cher-B/ivy/tree/95273172201071ebf7b83d56bb314450ebe41071 |
Upsample2d | # 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 functools
import typing
import torch.optim
assert_size_stride = torch._C._dynamo.g... | ai-in-motion/moai | Upsample2d | false | 18,330 | [
"Apache-2.0"
] | 10 | e38cac046c059d2e2331ef4883bbabc5a500a5cf | https://github.com/ai-in-motion/moai/tree/e38cac046c059d2e2331ef4883bbabc5a500a5cf |
GRUCell | # 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_... | ayjabri/DeepRL | GRUCell | false | 1,512 | [
"MIT"
] | 0 | 0be095e3a3d04f60b4cdc97ed330dffc17b3024a | https://github.com/ayjabri/DeepRL/tree/0be095e3a3d04f60b4cdc97ed330dffc17b3024a |
ClassificationModel | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | DerekGloudemans/temporary-repo | ClassificationModel | false | 5,101 | [
"MIT"
] | 1 | f278e9c7c9c7c1f362a64aec492ddb8fb1f984ad | https://github.com/DerekGloudemans/temporary-repo/tree/f278e9c7c9c7c1f362a64aec492ddb8fb1f984ad |
ContourDTConsistency | # 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... | Atharva-Peshkar/pytorch_connectomics | ContourDTConsistency | false | 13,308 | [
"MIT"
] | 99 | 8eccd9640a9a454d4df095a3529a030e58f882f5 | https://github.com/Atharva-Peshkar/pytorch_connectomics/tree/8eccd9640a9a454d4df095a3529a030e58f882f5 |
DistilMHAScoresCalculation_v2 | # 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.... | JudeDavis1/intel-extension-for-pytorch | DistilMHAScoresCalculation_v2 | false | 2,579 | [
"Apache-2.0"
] | 0 | 364e34cb4917a709f5108c07d4005bf82f3d5067 | https://github.com/JudeDavis1/intel-extension-for-pytorch/tree/364e34cb4917a709f5108c07d4005bf82f3d5067 |
ISAB | # 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.... | KohavTal/SCAE_Project | ISAB | false | 8,416 | [
"Apache-2.0"
] | 40 | bc6d1c3697fcb9327dd96e9657c3299b47cf355e | https://github.com/KohavTal/SCAE_Project/tree/bc6d1c3697fcb9327dd96e9657c3299b47cf355e |
Self_Attention | import torch
import torch.nn as nn
import torch.nn.parallel
from torch.nn import Parameter
def l2normalize(v, eps=1e-12):
return v / (v.norm() + eps)
class SpectralNorm(nn.Module):
def __init__(self, module, name='weight', power_iterations=1):
super(SpectralNorm, self).__init__()
self.modul... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | qiyuqianxai/debvc | Self_Attention | false | 10,798 | [
"MIT"
] | 0 | 1d919019a3191d1c6a7da9b8f16e47bca6b3aef9 | https://github.com/qiyuqianxai/debvc/tree/1d919019a3191d1c6a7da9b8f16e47bca6b3aef9 |
AttLuong | # 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.... | ishine/NISQA | AttLuong | false | 15,639 | [
"MIT"
] | 223 | 2c8917f30c4e4bbca3a48e9852301f1e2480a741 | https://github.com/ishine/NISQA/tree/2c8917f30c4e4bbca3a48e9852301f1e2480a741 |
ModelRegressionGex2Atac | import torch
import torch.utils.data
import torch.nn.functional as F
import torch.nn as nn
class ModelRegressionGex2Atac(nn.Module):
def __init__(self, dim_mod1, dim_mod2):
super(ModelRegressionGex2Atac, self).__init__()
self.input_ = nn.Linear(dim_mod1, 1024)
self.fc = nn.Linear(1024, 25... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.... | Permoment-95/neurips2021_multimodal_topmethods | ModelRegressionGex2Atac | false | 9,488 | [
"MIT"
] | 0 | 017bc23b366a80ba9b1c2a47ea6c44124f77a7ca | https://github.com/Permoment-95/neurips2021_multimodal_topmethods/tree/017bc23b366a80ba9b1c2a47ea6c44124f77a7ca |
SpatialCGNL | # 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.... | zj1008/GALD-DGCNet | SpatialCGNL | false | 16,853 | [
"MIT"
] | 127 | be7ebfe2b3d28ea28a2b4714852999d4af2a785e | https://github.com/zj1008/GALD-DGCNet/tree/be7ebfe2b3d28ea28a2b4714852999d4af2a785e |
WeighedL1Loss | # 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.nn import L... | UT-ADL/lidar-as-camera | WeighedL1Loss | false | 1,178 | [
"Apache-2.0"
] | 0 | daccb2ae21b4899ecfd8611b7a27f91681617383 | https://github.com/UT-ADL/lidar-as-camera/tree/daccb2ae21b4899ecfd8611b7a27f91681617383 |
GANLossDiscriminator | # 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... | ChristophReich1996/Mode_Collapse | GANLossDiscriminator | false | 7,920 | [
"MIT"
] | 14 | 937ee8bf96510fbf4070fc7e14b78276ab036b8c | https://github.com/ChristophReich1996/Mode_Collapse/tree/937ee8bf96510fbf4070fc7e14b78276ab036b8c |
VarifocalLoss | # 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... | MatthewInkawhich/object_localization_network | VarifocalLoss | false | 5,583 | [
"Apache-2.0"
] | 1 | 3fddaacfcef33f03af48b746e95ebd7d74dbb27f | https://github.com/MatthewInkawhich/object_localization_network/tree/3fddaacfcef33f03af48b746e95ebd7d74dbb27f |
DAModule | # 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.... | LeftAttention/Attention-Codebase | DAModule | false | 17,635 | [
"Apache-2.0"
] | 6 | 348ec66233a7c0f95a3cb5f0f11641e2a7a9b9c3 | https://github.com/LeftAttention/Attention-Codebase/tree/348ec66233a7c0f95a3cb5f0f11641e2a7a9b9c3 |
MSELoss2d | # 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... | giannifranchi/deeplabv3-superpixelmix | MSELoss2d | false | 6,742 | [
"MIT"
] | 1 | db52bf83b3b242af05bde5e39ee3de896e44c264 | https://github.com/giannifranchi/deeplabv3-superpixelmix/tree/db52bf83b3b242af05bde5e39ee3de896e44c264 |
SimpleNet | # 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.... | SpencerLo-CMU/pytorch-rl-suite | SimpleNet | false | 5,847 | [
"MIT"
] | 1 | 52b215f38cbb4c39a0ccfff48ab8262b1c9ef4a0 | https://github.com/SpencerLo-CMU/pytorch-rl-suite/tree/52b215f38cbb4c39a0ccfff48ab8262b1c9ef4a0 |
MLP | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | KoichiYasuoka/diaparser | MLP | false | 9,247 | [
"MIT"
] | 0 | ca11e65ef890cee2fbb23f42ae9c711c89767158 | https://github.com/KoichiYasuoka/diaparser/tree/ca11e65ef890cee2fbb23f42ae9c711c89767158 |
SiameseCNN | # 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
from tor... | EE559DeepLearningEPFL/Project1 | SiameseCNN | false | 408 | [
"MIT"
] | 0 | cbafdfee26771ae0ba3cd36375e68d92e9f108b2 | https://github.com/EE559DeepLearningEPFL/Project1/tree/cbafdfee26771ae0ba3cd36375e68d92e9f108b2 |
SevenLayerFC_Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Darkhunter9/10-605_cifar100 | SevenLayerFC_Net | false | 389 | [
"MIT"
] | 0 | 97c171c7b3ad74bcb0376c2ec23083f1a0b9417d | https://github.com/Darkhunter9/10-605_cifar100/tree/97c171c7b3ad74bcb0376c2ec23083f1a0b9417d |
LINEAR_LOGSOFTMAX | # 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.... | Huihui-z/CE-GZSL | LINEAR_LOGSOFTMAX | false | 13,817 | [
"MIT"
] | 58 | 7bf5358ac4727ea1dc2dc9dec2f453b014500bd8 | https://github.com/Huihui-z/CE-GZSL/tree/7bf5358ac4727ea1dc2dc9dec2f453b014500bd8 |
Optimizable_Temperature | import torch
import torch.utils.data
class Optimizable_Temperature(torch.nn.Module):
def __init__(self, initial_temperature=None):
super(Optimizable_Temperature, self).__init__()
self.log_temperature = torch.nn.Parameter(data=torch.zeros([1]).
type(torch.DoubleTensor))
if init... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_siz... | kingsj0405/Explorable-Super-Resolution | Optimizable_Temperature | false | 15,838 | [
"Apache-2.0"
] | 54 | 6582477ec1e2b0c6f4bd781552ac880fabdb4496 | https://github.com/kingsj0405/Explorable-Super-Resolution/tree/6582477ec1e2b0c6f4bd781552ac880fabdb4496 |
LearnedPositionalEmbedding | import torch
import torch.utils.data
from torch import nn
def create_position_ids_from_input_ids(input_ids, padding_idx):
""" Replace non-padding symbols with their position numbers. Position numbers begin at
padding_idx+1. Padding symbols are ignored. This is modified from fairseq's
`utils.make_positions... | 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
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._... | JuruoMP/gap-exp | LearnedPositionalEmbedding | false | 9,228 | [
"Apache-2.0"
] | 0 | 2d7af8a1da2f0ff8f9d3a2c6e15cc6383c716c05 | https://github.com/JuruoMP/gap-exp/tree/2d7af8a1da2f0ff8f9d3a2c6e15cc6383c716c05 |
SigSoftmaxV1 | import torch
from torch import nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
def logsigsoftmax_v1(logits, dim=1):
"""
Computes sigsoftmax from the paper - https://arxiv.org/pdf/1805.10829.pdf
"""
max_values = torch.max(logits, dim, keepdim=T... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
i... | DingYuan0118/DeepEMD | SigSoftmaxV1 | false | 5,070 | [
"MIT"
] | 1 | a91f77c3da16fecefa62b14aa8b2f195b0e49b84 | https://github.com/DingYuan0118/DeepEMD/tree/a91f77c3da16fecefa62b14aa8b2f195b0e49b84 |
Invertible1x1Conv | import torch
import torch.nn.functional as F
from torch.autograd import Variable
import torch.utils.data
import torch.nn
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... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | malithj/TensorRT | Invertible1x1Conv | false | 12,764 | [
"Apache-2.0"
] | 0 | 48605d4b5673df89110cf41249ad007259d7c34a | https://github.com/malithj/TensorRT/tree/48605d4b5673df89110cf41249ad007259d7c34a |
CausalConv1d | import torch
import torch.nn as nn
import torch.nn.functional as F
class CausalConv1d(nn.Conv1d):
def __init__(self, input_size, hidden_size, kernel_size, stride=1,
dilation=1, groups=1, bias=True, sigmoid=None, tanh=None):
self.left_padding = (kernel_size - 1) * dilation
super(CausalConv... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | jpeg729/pytorch-bits | CausalConv1d | false | 15,737 | [
"MIT"
] | 73 | 5d107094042c27472dfb7dee77506b603f5d3e45 | https://github.com/jpeg729/pytorch-bits/tree/5d107094042c27472dfb7dee77506b603f5d3e45 |
ScaledDotProductAttention | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class ScaledDotProductAttention(nn.Module):
"""
Compute 'Scaled Dot Product Attention'
"""
def __init__(self, dropout=0.0):
"""
:param dropout: attention dropout rate
"""
super().__init__()
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | timgianitsos/squad | ScaledDotProductAttention | false | 13,186 | [
"MIT"
] | 0 | 6ab502652e3528cfeeddfb8eba05221443a35294 | https://github.com/timgianitsos/squad/tree/6ab502652e3528cfeeddfb8eba05221443a35294 |
ComplexMaxPool1d | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import torch.utils
assert_size_stride = torch._C._dynamo.guards.asse... | muqiaoy/dl_signal | ComplexMaxPool1d | false | 16,120 | [
"MIT"
] | 54 | 3a30d14982016644bfc96a7d1ca0109b441f17fd | https://github.com/muqiaoy/dl_signal/tree/3a30d14982016644bfc96a7d1ca0109b441f17fd |
AdaptiveInstanceNorm | import torch
from torch import nn
from math import sqrt
def equal_lr(module, name='weight'):
EqualLR.apply(module, name)
return module
class EqualLR:
def __init__(self, name):
self.name = name
def compute_weight(self, module):
weight = getattr(module, self.name + '_orig')
f... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | jeromepl/style-based-gan-pytorch | AdaptiveInstanceNorm | false | 10,350 | [
"MIT"
] | 0 | 97c13e54316dc57a7cb44c0cb910c29aaed11738 | https://github.com/jeromepl/style-based-gan-pytorch/tree/97c13e54316dc57a7cb44c0cb910c29aaed11738 |
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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | colincen/coach | Conv | false | 15,064 | [
"MIT"
] | 72 | 2b1b543851cc7ba359f48dac6a5c72f1ced9b530 | https://github.com/colincen/coach/tree/2b1b543851cc7ba359f48dac6a5c72f1ced9b530 |
PCBActiv | # 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.... | marcelsan/Deep-HdrReconstruction | PCBActiv | false | 16,015 | [
"BSD-3-Clause"
] | 80 | 7cb0d93938baa6fbe029116451a661c18dfba49e | https://github.com/marcelsan/Deep-HdrReconstruction/tree/7cb0d93938baa6fbe029116451a661c18dfba49e |
EmbeddingLayer | # 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.... | cthoyt/chemicalx | EmbeddingLayer | false | 6,496 | [
"Apache-2.0"
] | 1 | f48d70bc88e89e9605a5b1c2f006fb8d37b42922 | https://github.com/cthoyt/chemicalx/tree/f48d70bc88e89e9605a5b1c2f006fb8d37b42922 |
DepthWiseSeparableConvBlock | # 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... | pppyykknen/LFDisplay-PyTorch | DepthWiseSeparableConvBlock | false | 4,135 | [
"MIT"
] | 0 | d19261dac1717a799bb5ba5f96563be1d2383340 | https://github.com/pppyykknen/LFDisplay-PyTorch/tree/d19261dac1717a799bb5ba5f96563be1d2383340 |
LayerNorm1D | # 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_... | codeislife99/pytorch-meta-optimizer | LayerNorm1D | false | 9,941 | [
"MIT"
] | 0 | 24f00be05e6e173efa67fe953e466bdf1dcb50e9 | https://github.com/codeislife99/pytorch-meta-optimizer/tree/24f00be05e6e173efa67fe953e466bdf1dcb50e9 |
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
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | WdBlink/AugMix-3DOCUNet-Brats2019 | DiceLoss | false | 5,958 | [
"MIT"
] | 1 | 125c6c8682b51a550eeac9173d13d0a211576abc | https://github.com/WdBlink/AugMix-3DOCUNet-Brats2019/tree/125c6c8682b51a550eeac9173d13d0a211576abc |
DiceLoss | import torch
from torch import nn
class DiceLoss(nn.Module):
"""
Loss function from https://arxiv.org/abs/1707.03237,
where iou computation is introduced heatmap manner to measure the
diversity bwtween tow heatmaps.
"""
def __init__(self, eps=1e-06):
super(DiceLoss, self).__init__()
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | Vivianyzw/Dual.DBNet.pytorch | DiceLoss | false | 1,182 | [
"Apache-2.0",
"MIT"
] | 0 | 19d823ed7c05076c087a3f7ad1127c71c1c0d692 | https://github.com/Vivianyzw/Dual.DBNet.pytorch/tree/19d823ed7c05076c087a3f7ad1127c71c1c0d692 |
TransposedConvModel | # 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.... | arjunsuresh/aimet | TransposedConvModel | false | 12,706 | [
"BSD-3-Clause"
] | 0 | f6e09cb07a91eed3a5e6b8e19e6b065303af5a39 | https://github.com/arjunsuresh/aimet/tree/f6e09cb07a91eed3a5e6b8e19e6b065303af5a39 |
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