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 |
|---|---|---|---|---|---|---|---|---|---|---|
FakeRKHSConvNet | import math
import torch
import numpy as np
from torch import nn as nn
from torch import optim as optim
class MaybeBatchNorm2d(nn.Module):
def __init__(self, n_ftr, affine, use_bn):
super(MaybeBatchNorm2d, self).__init__()
self.bn = nn.BatchNorm2d(n_ftr, affine=affine)
self.use_bn = use_b... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | oke-aditya/pytorch-lightning-bolts | FakeRKHSConvNet | false | 7,362 | [
"Apache-2.0"
] | 1 | 268df20bb442e7385b709b1488d37fd2767aba3c | https://github.com/oke-aditya/pytorch-lightning-bolts/tree/268df20bb442e7385b709b1488d37fd2767aba3c |
FocalLoss | import torch
from torch import nn
import torch.nn.functional as F
class FocalLoss(nn.Module):
def __init__(self, gamma):
super().__init__()
self.gamma = gamma
def forward(self, input, target):
if not target.size() == input.size():
raise ValueError(
'Target... | 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 ... | dainis-boumber/nlp-loss-functions | FocalLoss | false | 12,241 | [
"Apache-2.0"
] | 0 | 735d1e74bf9b9705a56cbb718b85448575efb5ee | https://github.com/dainis-boumber/nlp-loss-functions/tree/735d1e74bf9b9705a56cbb718b85448575efb5ee |
SigmoidFocalClassificationLoss | # 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... | hlesmqh/WS3D | SigmoidFocalClassificationLoss | false | 15,528 | [
"MIT"
] | 100 | 6816eeb135923a59de34ee5d94be2d0fd3ec83f9 | https://github.com/hlesmqh/WS3D/tree/6816eeb135923a59de34ee5d94be2d0fd3ec83f9 |
Acosh | import torch
import torch.onnx
import torch.nn as nn
class Acosh(nn.Module):
def forward(self, x):
return torch.acosh(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
import torch.onnx
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | mil-tokyo/webdnn | Acosh | false | 16,058 | [
"MIT"
] | 1,967 | 38a60fd3e1a4e72bc01108189a3aa51e0752aecd | https://github.com/mil-tokyo/webdnn/tree/38a60fd3e1a4e72bc01108189a3aa51e0752aecd |
EqualConv2d | # 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
from torch import nn
assert_size_stride = torch._C._dynamo.guards.as... | ArashVahabpour/encoder4editing-contrastive | EqualConv2d | false | 13,282 | [
"MIT"
] | 1,051 | 1b91afe1693e01a41118e1ce2451b7d14bec51f4 | https://github.com/ArashVahabpour/encoder4editing-contrastive/tree/1b91afe1693e01a41118e1ce2451b7d14bec51f4 |
Mean | import torch
import torch.nn as nn
class Mean(nn.Module):
def __init__(self, dim, keep_dim=False):
super(Mean, self).__init__()
self.dim = dim
self.keep_dim = keep_dim
def forward(self, input):
return input.mean(self.dim, self.keep_dim)
def get_inputs():
return [torch.r... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | WillyChen123/CDFNet | Mean | false | 1,230 | [
"MIT"
] | 0 | 12d6b288aa2a8301683395a75bd44a7be44b7f2a | https://github.com/WillyChen123/CDFNet/tree/12d6b288aa2a8301683395a75bd44a7be44b7f2a |
BSConvU | import torch
class BSConvU(torch.nn.Module):
def __init__(self, in_channels, out_channels, kernel_size=3, stride=1,
padding=1, dilation=1, bias=True, padding_mode='zeros', with_norm=
True, bn_kwargs=None):
super().__init__()
self.with_norm = with_norm
if bn_kwargs is None:... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | YingqiLiulll/scrips_for_SR | BSConvU | false | 1,263 | [
"MIT"
] | 0 | 04fa6fdaf157e913d3e2521cd80315a10a2ccedc | https://github.com/YingqiLiulll/scrips_for_SR/tree/04fa6fdaf157e913d3e2521cd80315a10a2ccedc |
TripletLoss | import torch
from torchvision.transforms import functional as F
import torch.utils.data
from torch import nn
import torch.nn.functional as F
class TripletLoss(nn.Module):
"""
Triplet loss
Takes embeddings [N*dim_embed] of an anchor sample, a positive sample and a negative sample
"""
def __init__(... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
from torch import nn
assert_size_stride = torch._C._dynamo.guards... | Sigma10010/nuclei_cells_det | TripletLoss | false | 17,927 | [
"MIT"
] | 4 | c074175fec8938472bb4cddabd83d1d0ea78f230 | https://github.com/Sigma10010/nuclei_cells_det/tree/c074175fec8938472bb4cddabd83d1d0ea78f230 |
ToRGB | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.autograd import Function
import math
from torch import nn as nn
from ... | hyunobae/BasicSR | ToRGB | false | 12,529 | [
"Apache-2.0"
] | 0 | f2c2fc6cf28933658816c808f55c95fa20b16483 | https://github.com/hyunobae/BasicSR/tree/f2c2fc6cf28933658816c808f55c95fa20b16483 |
Conv2dSame | # 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
import torch.utils.data.distributed
from torch import nn... | Adlik/zen_nas | Conv2dSame | false | 16,879 | [
"Apache-2.0"
] | 7 | d820d5c7d5bbb6fd66a76d5f16513647d6ea7a57 | https://github.com/Adlik/zen_nas/tree/d820d5c7d5bbb6fd66a76d5f16513647d6ea7a57 |
MultiHeadAttention | # 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.... | Sobsz/uberduck-ml-dev | MultiHeadAttention | false | 1,092 | [
"Apache-2.0"
] | 0 | f099238f6f2e3f600d72d89dea3c883c59d91387 | https://github.com/Sobsz/uberduck-ml-dev/tree/f099238f6f2e3f600d72d89dea3c883c59d91387 |
PriorDiscriminator | # 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_... | Crazy-Jack/HCL | PriorDiscriminator | false | 13,524 | [
"MIT"
] | 275 | dd2aae0c525859c8498205a791058287f86ab111 | https://github.com/Crazy-Jack/HCL/tree/dd2aae0c525859c8498205a791058287f86ab111 |
PairwiseBCELoss | import torch
from abc import abstractmethod
import torch.utils.data.dataloader
import torch.nn.functional as F
import torch.nn as nn
import torch.nn
import torch.optim.optimizer
class SimilarityLoss(nn.Module):
def __init__(self):
super(SimilarityLoss, self).__init__()
@abstractmethod
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._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from abc im... | bogdankostic/flair | PairwiseBCELoss | false | 6,339 | [
"MIT"
] | 1 | 8cf03eab19512e94c1bcb4a30409bb065d37fe25 | https://github.com/bogdankostic/flair/tree/8cf03eab19512e94c1bcb4a30409bb065d37fe25 |
KeypointRCNNPredictor | # 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
from ... | Jack-XHP/LabPicV2-MaskRCNN | KeypointRCNNPredictor | false | 9,163 | [
"MIT"
] | 0 | b0586b2827000c7b7337d5110b2b1fd6185053a8 | https://github.com/Jack-XHP/LabPicV2-MaskRCNN/tree/b0586b2827000c7b7337d5110b2b1fd6185053a8 |
ContrastiveDistanceLoss | # 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
from torch.nn.modules.loss import *
from torch.nn.modules import *
... | asmekal/catalyst | ContrastiveDistanceLoss | false | 12,117 | [
"MIT"
] | 0 | e11365c0a9812649ceaef14e53061cd5117d8684 | https://github.com/asmekal/catalyst/tree/e11365c0a9812649ceaef14e53061cd5117d8684 |
Actor | import torch
import torch.nn as nn
import torch as t
class Actor(nn.Module):
def __init__(self, state_dim, action_dim, action_range):
super().__init__()
self.fc1 = nn.Linear(state_dim, 16)
self.fc2 = nn.Linear(16, 16)
self.fc3 = nn.Linear(16, action_dim)
self.action_range ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | LeonLester/Machin-title-in-progress- | Actor | false | 11,647 | [
"MIT"
] | 0 | 777479d47b520dcdc6b09c247591b5fe1d6cbe8c | https://github.com/LeonLester/Machin-title-in-progress-/tree/777479d47b520dcdc6b09c247591b5fe1d6cbe8c |
TanhHyperSolver | import torch
import torch.nn as nn
class TanhHyperSolver(nn.Module):
def __init__(self, in_dim, out_dim, hidden_dim=32):
super().__init__()
self.fc1 = nn.Linear(in_dim, hidden_dim)
self.fc2 = nn.Linear(hidden_dim, hidden_dim)
self.fc3 = nn.Linear(hidden_dim, out_dim)
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 ... | Juju-botu/diffeqml-research | TanhHyperSolver | false | 13,919 | [
"Apache-2.0"
] | 49 | aa796c87447e5299ec4f25a07fc4d032afb1f63e | https://github.com/Juju-botu/diffeqml-research/tree/aa796c87447e5299ec4f25a07fc4d032afb1f63e |
ClassificationHead | # 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
assert_size_stride ... | mlfoundations/wise-ft | ClassificationHead | false | 16,098 | [
"MIT"
] | 79 | 58b7a4b343b09dc06606aa929c2ef51accced8d1 | https://github.com/mlfoundations/wise-ft/tree/58b7a4b343b09dc06606aa929c2ef51accced8d1 |
Net1 | # 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 ... | Yixiao99/deep-learning-containers | Net1 | false | 14,702 | [
"Apache-2.0"
] | 383 | 01f078adf5abfb92e802b326511981bdd4a8c85c | https://github.com/Yixiao99/deep-learning-containers/tree/01f078adf5abfb92e802b326511981bdd4a8c85c |
NextSentencePrediction | # 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.... | LogIntelligence/LogADEmpirical | NextSentencePrediction | false | 8,479 | [
"MIT"
] | 11 | 48458aee65c1c84466b04dd4092fae79a7f341fd | https://github.com/LogIntelligence/LogADEmpirical/tree/48458aee65c1c84466b04dd4092fae79a7f341fd |
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.triton_helpers import libdevice
import math
import ... | albertkx/GeDi | MLP | false | 12,111 | [
"BSD-3-Clause"
] | 0 | 27532eb6ac5dd42d817d25a905401504e916f9fb | https://github.com/albertkx/GeDi/tree/27532eb6ac5dd42d817d25a905401504e916f9fb |
CRF | import torch
import torch.utils.data.dataloader
import torch.nn
class CRF(torch.nn.Module):
"""
Conditional Random Field Implementation according to sgrvinod (https://github.com/sgrvinod).
Classifier which predicts single tag / class / label for given word based on not just the word,
but also on previ... | 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.dataloader
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | marleneDebatin/flair | CRF | false | 7,162 | [
"MIT"
] | 1 | 4d17509f358158f66d43e85db1b6990523b0b095 | https://github.com/marleneDebatin/flair/tree/4d17509f358158f66d43e85db1b6990523b0b095 |
Shifted_softplus | import torch
import torch.nn as nn
import torch.nn.parallel
class Shifted_softplus(nn.Module):
"""
Performs a Shifter softplus loss, which modifies with a value of log(2)
"""
def __init__(self):
super(Shifted_softplus, self).__init__()
self.act = nn.Softplus()
self.shift = nn.Para... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torch.nn as nn
import torch.nn.parallel
assert_size_str... | QMrpy/deepchem | Shifted_softplus | false | 2,736 | [
"MIT"
] | 0 | f38a21c71e7bc4fd1fa59601be2b79ce7d744bd6 | https://github.com/QMrpy/deepchem/tree/f38a21c71e7bc4fd1fa59601be2b79ce7d744bd6 |
NLKDifferenceCenter | import torch
from torch import nn
import torch.nn.functional as F
class NLKDifferenceCenter(nn.Module):
def __init__(self, dim, hidden_dim):
super(NLKDifferenceCenter, self).__init__()
self.dim = dim
self.hidden_dim = hidden_dim
self.layer1 = nn.Linear(self.dim, self.hidden_dim)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | HKUST-KnowComp/EFO-1-QA-benchmark | NLKDifferenceCenter | false | 17,358 | [
"MIT"
] | 9 | 600fb02c76ab631f93ee362ceb789216ec085790 | https://github.com/HKUST-KnowComp/EFO-1-QA-benchmark/tree/600fb02c76ab631f93ee362ceb789216ec085790 |
BertPreTrainingHeads | import math
import torch
import torch.nn as nn
import torch.cuda
import torch.distributed
def get_activation_fn(activation):
"""Return an activation function Module according to its name."""
if activation == 'gelu':
fn = GELU()
elif activation == 'relu':
fn = nn.ReLU()
elif activation ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | SivilTaram/dialogue-utterance-rewriter-pytorch | BertPreTrainingHeads | false | 2,930 | [
"MIT"
] | 0 | 92c2254958b7a1ee9199836f7f2236575270983f | https://github.com/SivilTaram/dialogue-utterance-rewriter-pytorch/tree/92c2254958b7a1ee9199836f7f2236575270983f |
GatedConv2d | import torch
import torch.nn as nn
from torch.nn import Parameter
def l2normalize(v, eps=1e-12):
return v / (v.norm() + eps)
class LayerNorm(nn.Module):
def __init__(self, num_features, eps=1e-08, affine=True):
super(LayerNorm, self).__init__()
self.num_features = num_features
self.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
im... | piggy2303/DeepFillv2_Pytorch | GatedConv2d | false | 7,473 | [
"MIT"
] | 1 | dd35299f11704f878ed7a33e14ccd51a9d64baaf | https://github.com/piggy2303/DeepFillv2_Pytorch/tree/dd35299f11704f878ed7a33e14ccd51a9d64baaf |
MixtureSynthesizers | # 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.... | leaderj1001/Synthesizer-Rethinking-Self-Attention-Transformer-Models | MixtureSynthesizers | false | 15,877 | [
"MIT"
] | 58 | 3ee5829438a8f9c063ae485e77c9ce7649d24139 | https://github.com/leaderj1001/Synthesizer-Rethinking-Self-Attention-Transformer-Models/tree/3ee5829438a8f9c063ae485e77c9ce7649d24139 |
GlobalAttention | import torch
import torch.nn as nn
import torch.cuda
def aeq(*args):
"""
Assert all arguments have the same value
"""
arguments = (arg for arg in args)
first = next(arguments)
assert all(arg == first for arg in arguments
), 'Not all arguments have the same value: ' + str(args)
def se... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | kurianbenoy/QG-Net | GlobalAttention | false | 3,875 | [
"MIT"
] | 0 | 074c697530aaaa259a3e16467a020846b1085af1 | https://github.com/kurianbenoy/QG-Net/tree/074c697530aaaa259a3e16467a020846b1085af1 |
FakeReLUM | # 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... | Jay-Roberts/FW-Perturbations | FakeReLUM | false | 9,113 | [
"MIT"
] | 0 | 0960f6116125307cc986f9f19b3c5ab4c15ed535 | https://github.com/Jay-Roberts/FW-Perturbations/tree/0960f6116125307cc986f9f19b3c5ab4c15ed535 |
HighwayLayer | import torch
import torch.nn.functional as F
import torch.nn as nn
import torch.jit
import torch.jit.quantized
import torch.onnx.operators
class HighwayLayer(nn.Module):
def __init__(self, input_dim, transform_activation=F.relu,
gate_activation=F.softmax, gate_bias=-2):
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.... | Ayansam1152/translate | HighwayLayer | false | 13,396 | [
"BSD-3-Clause"
] | 748 | 33d397fc25fb1072abd2975c77c602a2d031c6c4 | https://github.com/Ayansam1152/translate/tree/33d397fc25fb1072abd2975c77c602a2d031c6c4 |
SpatialGate | import math
import torch
import torch.nn as nn
import torch.utils.data
from itertools import product as product
from math import sqrt as sqrt
class SpatialGate(nn.Module):
def __init__(self, in_channels: 'int', num_groups: 'int'=1, kernel_size:
'int'=1, padding: 'int'=0, stride: 'int'=1, gate_activation:... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | lingtengqiu/LearnableTreeFilterV2 | SpatialGate | false | 7,095 | [
"Apache-2.0"
] | 1 | 3814a5a84c0a5c33d6538749eaf5aed4827366de | https://github.com/lingtengqiu/LearnableTreeFilterV2/tree/3814a5a84c0a5c33d6538749eaf5aed4827366de |
QNetwork | import torch
import torch.nn.functional as F
import torch.nn as nn
class QNetwork(nn.Module):
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed, fc1_units=64,
fc2_units=64):
"""Initialize parameters and build model.
Params
======
state_si... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | AmineKheldouni/Graphs-in-Machine-Learning | QNetwork | false | 4,858 | [
"MIT"
] | 1 | 003217495c624eaa33d44d679a0bc2164ca1f3d2 | https://github.com/AmineKheldouni/Graphs-in-Machine-Learning/tree/003217495c624eaa33d44d679a0bc2164ca1f3d2 |
Snake | import torch
import torch.nn as nn
from torch import sin
from torch import pow
from torch.nn import Parameter
from torch.distributions.exponential import Exponential
class Snake(nn.Module):
"""
Implementation of the serpentine-like sine-based periodic activation function
.. math::
S... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
from torch.nn import Parameter
from torch.distribut... | Juju-botu/diffeqml-research | Snake | false | 13,965 | [
"Apache-2.0"
] | 49 | aa796c87447e5299ec4f25a07fc4d032afb1f63e | https://github.com/Juju-botu/diffeqml-research/tree/aa796c87447e5299ec4f25a07fc4d032afb1f63e |
ResizeTransform | # 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... | NingAnMe/voxelmorph | ResizeTransform | false | 2,699 | [
"Apache-2.0"
] | 0 | 3a1a4c2f456af2dba5552efc1b08c68af38e54dc | https://github.com/NingAnMe/voxelmorph/tree/3a1a4c2f456af2dba5552efc1b08c68af38e54dc |
SpatialPurity | # 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.triton_helpers import math as tl_math
import torch.... | BIT-DA/RIPU | SpatialPurity | false | 16,970 | [
"MIT"
] | 9 | 125edf112c9ded1e7497aedb2a092331824df100 | https://github.com/BIT-DA/RIPU/tree/125edf112c9ded1e7497aedb2a092331824df100 |
FeatureAssembler | # 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 typing import Optional
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch... | ZhuangweiKang/pytorch-ts | FeatureAssembler | false | 2,991 | [
"Apache-2.0",
"MIT"
] | 0 | 076d456358fd1bac96becba4f1ba38ec5a5fcf4d | https://github.com/ZhuangweiKang/pytorch-ts/tree/076d456358fd1bac96becba4f1ba38ec5a5fcf4d |
SimpleTypeasModel | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | YaronBenAtar/glow | SimpleTypeasModel | false | 14,685 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
Convlayer | import torch
class Convlayer(torch.nn.Module):
def __init__(self, in_channels, out_channels, kernel_size=1, stride=1):
super().__init__()
padding = kernel_size // 2
self.refl = torch.nn.ReflectionPad2d(padding)
self.conv = torch.nn.Conv2d(in_channels, out_channels, kernel_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.triton_helpers import math as tl_math
assert_size_s... | bruchano/ImageStyler | Convlayer | false | 9,925 | [
"MIT"
] | 0 | 7bde13bc954566088c477065adb5c4e4214c28bb | https://github.com/bruchano/ImageStyler/tree/7bde13bc954566088c477065adb5c4e4214c28bb |
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
import torch.nn as nn
import torch._C
import torch.serialization
assert_size_str... | dkswxd/Swin-Transformer-Semantic-Segmentation | PatchEmbed | false | 1,861 | [
"Apache-2.0"
] | 0 | 6af19736e5492a01d8952d4ee86a6d59b21c2ae1 | https://github.com/dkswxd/Swin-Transformer-Semantic-Segmentation/tree/6af19736e5492a01d8952d4ee86a6d59b21c2ae1 |
Net | import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
self.fc = nn.Linear(28 * 28, 200)
self.fc2 = nn.Linear(200, 10)
def forward(self, x):
x = x.view((-1, 28 * 28))
x = F.relu(self.fc(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | anianruoss/RIAI | Net | false | 3,108 | [
"MIT"
] | 0 | 2ac4ddcfb73c9678b1c4fe94fdaae82baceac4ea | https://github.com/anianruoss/RIAI/tree/2ac4ddcfb73c9678b1c4fe94fdaae82baceac4ea |
StateInitZero | import torch
from torch import nn
from torchvision import models as models
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
import torch.onnx
class StateInitZero(nn.Module):
def __init__(self, hidden_size, num_layers=1, batch_first=False):
super(Stat... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
from torchvision import models as models
import torch.nn.parallel
import torch.optim
import torch.utils.data
import tor... | JinYAnGHe/openvino_training_extensions | StateInitZero | false | 3,025 | [
"Apache-2.0"
] | 0 | a0b4456a3c9fe6c1b7eabc9d5eb4e74d01453dee | https://github.com/JinYAnGHe/openvino_training_extensions/tree/a0b4456a3c9fe6c1b7eabc9d5eb4e74d01453dee |
BinConv2d | import torch
from itertools import product as product
import torch.nn.functional as F
from torch import nn
import torch.optim
import torch.utils.data
class BinQuant(torch.autograd.Function):
"""BinaryConnect quantization.
Refer:
https://pytorch.org/tutorials/beginner/examples_autograd/two_layer_net_cu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from itertools import product as product
from torch import nn
import torch.optim... | ninfueng/a-PyTorch-Tutorial-to-Object-Detection | BinConv2d | false | 10,638 | [
"MIT"
] | 0 | fc7544720a7e939f5a56f4f7214e4965b7775f77 | https://github.com/ninfueng/a-PyTorch-Tutorial-to-Object-Detection/tree/fc7544720a7e939f5a56f4f7214e4965b7775f77 |
ANNDigitDetect | # 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_... | Quest2GM/timestamp_detection_algorithm | ANNDigitDetect | false | 5,732 | [
"MIT"
] | 1 | 8a5a7fba5a924a37402d7daece90fdf626a6a905 | https://github.com/Quest2GM/timestamp_detection_algorithm/tree/8a5a7fba5a924a37402d7daece90fdf626a6a905 |
LinearBlock | # 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.... | aylagulcu/TripletMAML | LinearBlock | false | 9,904 | [
"MIT"
] | 0 | 98cb4a23847ec24937963292cd6f162bcbf724ba | https://github.com/aylagulcu/TripletMAML/tree/98cb4a23847ec24937963292cd6f162bcbf724ba |
Conv_Block_gn | # 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 ... | MRLoghmani/Separate_to_Adapt | Conv_Block_gn | false | 5,580 | [
"MIT"
] | 1 | 09c734448aa22b3879186f59952d9fd596d4a1f8 | https://github.com/MRLoghmani/Separate_to_Adapt/tree/09c734448aa22b3879186f59952d9fd596d4a1f8 |
tofp16 | # 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
import torch
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cud... | Icep2020/CrowdGAN | tofp16 | false | 17,424 | [
"MIT"
] | 7 | 4adebaa09460f2f8296d368ffeba03f32c963d4d | https://github.com/Icep2020/CrowdGAN/tree/4adebaa09460f2f8296d368ffeba03f32c963d4d |
BinaryDiceLoss | # 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... | MIPT-Oulu/3D-Histo-Grading | BinaryDiceLoss | false | 5,570 | [
"MIT"
] | 1 | b779a154d0e5b104fc152c8952124768fb7b1dc6 | https://github.com/MIPT-Oulu/3D-Histo-Grading/tree/b779a154d0e5b104fc152c8952124768fb7b1dc6 |
Critic | # 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_... | ZY-KK/panda | Critic | false | 1,315 | [
"MIT"
] | 0 | 48fcbd65d563ef74aab2554be8de7662560c43da | https://github.com/ZY-KK/panda/tree/48fcbd65d563ef74aab2554be8de7662560c43da |
TernaryLinear | import torch
from torch import nn
import torch.nn.functional as F
from torch.nn import init
class Ternary(nn.Module):
"""
Ternarize the input activations to -1, 0, 1.
"""
def __init__(self, left=-0.25, right=0.25):
super().__init__()
self.left = left
self.right = right
de... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
from torch.nn import init
assert_size_stride = torch._C._dy... | C-SUNSHINE/TOQ-Nets-PyTorch-Release | TernaryLinear | false | 17,145 | [
"MIT"
] | 6 | 05e06bf633fb3c6b610dda9a5126ecd7af1db02f | https://github.com/C-SUNSHINE/TOQ-Nets-PyTorch-Release/tree/05e06bf633fb3c6b610dda9a5126ecd7af1db02f |
GeneralizedMeanPoolingFpn | import torch
from abc import ABC
from torch import nn
class GeneralizedMeanPoolingFpn(nn.Module, ABC):
"""Applies a 2D power-average adaptive pooling over an input signal composed of
several input planes.
The function computed is: :math:`f(X) = pow(sum(pow(X, p)), 1/p)`
- At p = infinity, one gets... | 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 abc import ABC
from tor... | catcodee/cluster-contrast-reid | GeneralizedMeanPoolingFpn | false | 3,279 | [
"MIT"
] | 0 | f6359990a4326375f23c3fd654df3fc6dcc9c579 | https://github.com/catcodee/cluster-contrast-reid/tree/f6359990a4326375f23c3fd654df3fc6dcc9c579 |
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_... | The-very-most-awesome-team-of-cool-kids/02463_Active_Learning | Net | false | 1,882 | [
"MIT"
] | 0 | abc35a31996de1c2e3275cf946b6a44f62abb781 | https://github.com/The-very-most-awesome-team-of-cool-kids/02463_Active_Learning/tree/abc35a31996de1c2e3275cf946b6a44f62abb781 |
Sub | import torch
class Sub(torch.nn.Module):
def __init__(self):
super(Sub, self).__init__()
def forward(self, x, y):
return x - y
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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | bunderhi/torch2trt | Sub | false | 1,610 | [
"MIT"
] | 0 | fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d | https://github.com/bunderhi/torch2trt/tree/fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d |
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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | JessyLee/Jessy_Dive_into_DL_Pytorch | GlobalAvgPool2d | false | 11,542 | [
"MIT"
] | 0 | 40b7921637b13507057f41485d928f3b59cc6f6a | https://github.com/JessyLee/Jessy_Dive_into_DL_Pytorch/tree/40b7921637b13507057f41485d928f3b59cc6f6a |
BPRLoss | import torch
import torch.nn as nn
class BPRLoss(nn.Module):
""" BPRLoss, based on Bayesian Personalized Ranking
Args:
- gamma(float): Small value to avoid division by zero
Shape:
- Pos_score: (N)
- Neg_score: (N), same shape as the Pos_score
- Output: scalar.
Exampl... | 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
... | BELIEVEfxy/LightSANs | BPRLoss | false | 7,767 | [
"MIT"
] | 17 | 94ce7e59d144dbc787153b8c486cad334790ec6e | https://github.com/BELIEVEfxy/LightSANs/tree/94ce7e59d144dbc787153b8c486cad334790ec6e |
SelfAttentionBatch | import torch
from torch import nn
import torch.nn.functional as F
class SelfAttentionBatch(nn.Module):
def __init__(self, dim, da, alpha=0.2, dropout=0.5):
super(SelfAttentionBatch, self).__init__()
self.dim = dim
self.da = da
self.alpha = alpha
self.dropout = dropout
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | RUCAIBox/WSDM2022-C2CRS | SelfAttentionBatch | false | 17,847 | [
"MIT"
] | 4 | 8ef2fa7c44bdba1799ab79f379ae7394bd468c02 | https://github.com/RUCAIBox/WSDM2022-C2CRS/tree/8ef2fa7c44bdba1799ab79f379ae7394bd468c02 |
NormedLinear | import torch
import torch.utils.data
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Parameter
class NormedLinear(nn.Module):
def __init__(self, in_features, out_features):
super(NormedLinear, self).__init__()
self.weight = Parameter(torch.Tensor(in_feature... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Data-Designer/Feature-Space-Augmentation-for-Long-Tailed-Data | NormedLinear | false | 17,219 | [
"MIT"
] | 9 | ac6bced6269d6ebaa3fc0935603d905a7f11a6fa | https://github.com/Data-Designer/Feature-Space-Augmentation-for-Long-Tailed-Data/tree/ac6bced6269d6ebaa3fc0935603d905a7f11a6fa |
MultiHeadAttention | import math
import torch
from torch import nn
class ScaledDotProduct(nn.Module):
def __init__(self, attentionHeadSize, dropOutProb=0.1):
super(ScaledDotProduct, self).__init__()
self.attentionHeadSize = attentionHeadSize
self.dropout = nn.Dropout(dropOutProb)
def forward(self, Q, K, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | simonepreite/QABERT | MultiHeadAttention | false | 4,349 | [
"MIT"
] | 0 | ed3e49f6619f3ff660068291231909693cb8f5d5 | https://github.com/simonepreite/QABERT/tree/ed3e49f6619f3ff660068291231909693cb8f5d5 |
Critic | import torch
import torch.nn as nn
import torch.nn.functional as F
class Critic(nn.Module):
def __init__(self, state_dim, action_dim):
super(Critic, self).__init__()
self.l1 = nn.Linear(state_dim + action_dim, 7)
self.l2 = nn.Linear(7, 6)
self.l3 = nn.Linear(6, 1)
self.l4 ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | chenbq1234/CityLearn | Critic | false | 6,426 | [
"MIT"
] | 1 | baa162435954ecd58e7f4769a46fa9046f4d2cf6 | https://github.com/chenbq1234/CityLearn/tree/baa162435954ecd58e7f4769a46fa9046f4d2cf6 |
InteractingLayer | import torch
import torch.nn as nn
import torch.nn.functional as F
from sklearn.metrics import *
class InteractingLayer(nn.Module):
"""A Layer used in AutoInt that model the correlations between different feature fields by multi-head self-attention mechanism.
Input shape
- A 3D tensor with shape... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | zzz123xyz/DeepCTR-Torch | InteractingLayer | false | 4,750 | [
"Apache-2.0"
] | 0 | d6b880cc6b3761dbef90920a28182ef6737dd665 | https://github.com/zzz123xyz/DeepCTR-Torch/tree/d6b880cc6b3761dbef90920a28182ef6737dd665 |
ModulatedConv2d | import math
import torch
from torch import nn
from torch.nn import functional as F
def fused_leaky_relu(input, bias, negative_slope=0.2, scale=2 ** 0.5):
rest_dim = [1] * (input.ndim - bias.ndim - 1)
input = input
if input.ndim == 3:
return F.leaky_relu(input + bias.view(1, *rest_dim, bias.shape[0... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
from to... | ozmig77/StyleCLIP-1 | ModulatedConv2d | false | 16,220 | [
"MIT"
] | 2,732 | 57b887bba971ef86c107f4805785ce44fca3efef | https://github.com/ozmig77/StyleCLIP-1/tree/57b887bba971ef86c107f4805785ce44fca3efef |
PositionwiseFeedForward | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
import torch.multiprocessing
class PositionwiseFeedForward(nn.Module):
""" A two-feed-forward-layer module """
def __init__(self, d_in, d_hid, dropout=0.1):
super(PositionwiseFeedForward, self).__init__()
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Caiyuan-Zheng/Consistency_Regularization_STR | PositionwiseFeedForward | false | 2,089 | [
"MIT"
] | 0 | 7c7ce69390c429974cb2d1969b0d9d6707e6723f | https://github.com/Caiyuan-Zheng/Consistency_Regularization_STR/tree/7c7ce69390c429974cb2d1969b0d9d6707e6723f |
CosNorm_Classifier | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
from to... | HoganZhang/OpenLongTailRecognition-OLTR | CosNorm_Classifier | false | 11,486 | [
"BSD-3-Clause"
] | 0 | 94b7e9fc93e7c96218e801007aa4d09a3f5fc69d | https://github.com/HoganZhang/OpenLongTailRecognition-OLTR/tree/94b7e9fc93e7c96218e801007aa4d09a3f5fc69d |
Accuracy | # 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... | cms-flash/beauty-net | Accuracy | false | 15,052 | [
"MIT"
] | 155 | 668210a95ccb4462d7beff10505e4e83532682f2 | https://github.com/cms-flash/beauty-net/tree/668210a95ccb4462d7beff10505e4e83532682f2 |
ClipGlobalAvgPool2d | # 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... | hfyer/NAIC2020_ReID_R1 | ClipGlobalAvgPool2d | false | 6,805 | [
"Apache-2.0"
] | 1 | 240f0c9f65e482e6b0090f01d9f9e3373a337033 | https://github.com/hfyer/NAIC2020_ReID_R1/tree/240f0c9f65e482e6b0090f01d9f9e3373a337033 |
NetVLAD | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class NetVLAD(nn.Module):
def __init__(self, dims, num_clusters, outdims=None):
super(NetVLAD, self).__init__()
self.num_clusters = num_clusters
self.dims = dims
self.centroids = nn.Parameter(torch.rand... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | glee1228/segment_temporal_context_aggregation | NetVLAD | false | 6,760 | [
"Apache-2.0"
] | 1 | e5778f848f1cfd89bd1f77beb5e1b38a66a2f13d | https://github.com/glee1228/segment_temporal_context_aggregation/tree/e5778f848f1cfd89bd1f77beb5e1b38a66a2f13d |
HLoss | # 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.... | lemon234071/oc_parlai | HLoss | false | 3,883 | [
"MIT"
] | 0 | 33a0e57c48e58903cb1666e367a7bb9ef012de0c | https://github.com/lemon234071/oc_parlai/tree/33a0e57c48e58903cb1666e367a7bb9ef012de0c |
MaxPoolPad | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
import torch.nn as nn
import torch.backends.cudnn
assert_size_str... | CalebEverett/fastai-dl2 | MaxPoolPad | false | 17,152 | [
"Apache-2.0"
] | 4 | 64d23592eddca6ca1f3647e73c319e97c8eb392b | https://github.com/CalebEverett/fastai-dl2/tree/64d23592eddca6ca1f3647e73c319e97c8eb392b |
GHMC | import torch
import torch.nn as nn
import torch.nn.functional as F
def _expand_onehot_labels(labels, label_weights, label_channels):
bin_labels = labels.new_full((labels.size(0), label_channels), 0)
inds = torch.nonzero((labels >= 0) & (labels < label_channels),
as_tuple=False).squeeze()
if inds.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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | CK-er/mmdet | GHMC | false | 2,072 | [
"Apache-2.0"
] | 0 | 9bea4068efbcf7bf739dbe41917a68d525c29868 | https://github.com/CK-er/mmdet/tree/9bea4068efbcf7bf739dbe41917a68d525c29868 |
AttentionVasvani | import torch
from torch import nn
class AttentionVasvani(nn.Module):
def __init__(self, encoder_dim=128, decoder_dim=128):
super(AttentionVasvani, self).__init__()
def forward(self, k, q):
x = torch.sum(k * q, dim=1, keepdim=True)
x /= torch.sqrt(torch.norm(k, p=1, dim=1, keepdim=Tru... | 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
from torch import nn
assert_size_stride = torch._C._dynamo.gua... | a1247418/MT18_LH_human-sleep-classification | AttentionVasvani | false | 1,333 | [
"MIT"
] | 0 | c4a40571390aaa14b1cc8a458100e21252fe05d2 | https://github.com/a1247418/MT18_LH_human-sleep-classification/tree/c4a40571390aaa14b1cc8a458100e21252fe05d2 |
LDEPooling | import torch
import torch.nn
class LDEPooling(torch.nn.Module):
"""A novel learnable dictionary encoding layer.
Reference: Weicheng Cai, etc., "A NOVEL LEARNABLE DICTIONARY ENCODING LAYER FOR END-TO-END
LANGUAGE IDENTIFICATION", icassp, 2018
"""
def __init__(self, input_dim, c_num=64,... | 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
assert... | qlindazm/asv-subtools | LDEPooling | false | 4,234 | [
"Apache-2.0"
] | 0 | fe1d31db9f3268622016babe944201f6ff81ed56 | https://github.com/qlindazm/asv-subtools/tree/fe1d31db9f3268622016babe944201f6ff81ed56 |
Net | import torch
import torch.nn as nn
class ConvBlock(nn.Module):
def __init__(self, in_size, out_size, kernel=3, stride=1, padding=1,
activ='relu', norm=None):
super(ConvBlock, self).__init__()
self.conv = nn.Conv2d(in_size, out_size, kernel, stride, padding)
self.norm = norm
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | jth1011/ECE539-Project | Net | false | 12,653 | [
"MIT"
] | 0 | bce6ffd75da92e862d8fda3852be247602b1567e | https://github.com/jth1011/ECE539-Project/tree/bce6ffd75da92e862d8fda3852be247602b1567e |
DownsampleB | # 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
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.g... | gpleiss/aum | DownsampleB | false | 15,452 | [
"MIT"
] | 45 | 3c710662d74cdad9b299f541170070c0cb292042 | https://github.com/gpleiss/aum/tree/3c710662d74cdad9b299f541170070c0cb292042 |
InstanceNormLayer | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | tylerwilliams/InterFaceGAN | InstanceNormLayer | false | 4,463 | [
"MIT"
] | 0 | 120babcc0dc777aa902ef0dcdeaec7c528369dbc | https://github.com/tylerwilliams/InterFaceGAN/tree/120babcc0dc777aa902ef0dcdeaec7c528369dbc |
UpsampleConvLayer | import torch
class UpsampleConvLayer(torch.nn.Module):
"""UpsampleConvLayer
Upsamples the input and then does a convolution. This method gives better results
compared to ConvTranspose2d.
ref: http://distill.pub/2016/deconv-checkerboard/
"""
def __init__(self, in_channels, out_channels, kernel... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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
assert_size_s... | EdenBD/MultiModalStory-demo | UpsampleConvLayer | false | 13,625 | [
"Apache-2.0"
] | 154 | 5e95e2aca766ca7c850e8db4973b8d51dfdba7f8 | https://github.com/EdenBD/MultiModalStory-demo/tree/5e95e2aca766ca7c850e8db4973b8d51dfdba7f8 |
FirstBlock | import torch
import numpy as np
import torch.nn as nn
class BatchNormLayer(nn.Module):
"""Implements batch normalization layer."""
def __init__(self, channels, gamma=False, beta=True, decay=0.9, epsilon
=1e-05):
"""Initializes with basic settings.
Args:
channels: Number of channels... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | thunguyenphuoc/idinvert_pytorch | FirstBlock | false | 13,129 | [
"MIT"
] | 0 | bf8a81e75d193c22a05d9c4457907dc468389766 | https://github.com/thunguyenphuoc/idinvert_pytorch/tree/bf8a81e75d193c22a05d9c4457907dc468389766 |
Contrast_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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | LiuChaoXD/Remote-Sensing-Image-Retrieval-Models | Contrast_Loss | false | 17,582 | [
"MIT"
] | 4 | c135562263102080716e35260f111dcff7762264 | https://github.com/LiuChaoXD/Remote-Sensing-Image-Retrieval-Models/tree/c135562263102080716e35260f111dcff7762264 |
ATOCAttentionUnit | # 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_... | PaParaZz1/DI-engine | ATOCAttentionUnit | false | 11,855 | [
"Apache-2.0"
] | 0 | b38144117c1ebc6eb860d8637ec8866dfbcdf2de | https://github.com/PaParaZz1/DI-engine/tree/b38144117c1ebc6eb860d8637ec8866dfbcdf2de |
LandmarkHead | # 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 itertools import product as product
assert_size_strid... | Akshobhya2018eeb1137/Attendance_System_Using_Face_Recognition | LandmarkHead | false | 18,446 | [
"MIT"
] | 2 | a52ca53e15332ab706f6ed23045b38ea6d38dfd9 | https://github.com/Akshobhya2018eeb1137/Attendance_System_Using_Face_Recognition/tree/a52ca53e15332ab706f6ed23045b38ea6d38dfd9 |
Accuracy | import torch
import torch.nn as nn
class Accuracy(nn.Module):
def __init__(self, binary=False):
super().__init__()
self.binary = binary
def forward(self, preds, trues):
if self.binary:
preds = preds >= 0.5
else:
preds = preds.argmax(dim=1)
resu... | 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... | jokingbear/DM | Accuracy | false | 6,979 | [
"MIT"
] | 1 | 9c4dada1756f3d866455a397511d4f3bacfadc60 | https://github.com/jokingbear/DM/tree/9c4dada1756f3d866455a397511d4f3bacfadc60 |
ScaledDotProductAttention | import torch
import torch.nn as nn
class ScaledDotProductAttention(nn.Module):
""" Scaled Dot-Product Attention """
def __init__(self, temperature, attn_dropout=0.1):
super().__init__()
self.temperature = temperature
self.dropout = nn.Dropout(attn_dropout)
self.softmax = nn.So... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | LithiumH/cs224u-final-project | ScaledDotProductAttention | false | 771 | [
"Apache-2.0"
] | 0 | 6049ccca3a2c33a77d9a6d5f44b2755301e18891 | https://github.com/LithiumH/cs224u-final-project/tree/6049ccca3a2c33a77d9a6d5f44b2755301e18891 |
ChamferLoss | import torch
import torch.nn as nn
class ChamferLoss(nn.Module):
"""
Torch implementation of chamferLoss for n-dimensional geometries
"""
def __init__(self):
self.init__ = super(ChamferLoss, self).__init__()
self.use_cuda = torch.cuda.is_available()
def batch_pairwise_dist(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
import torch.nn as nn
assert_... | GitMarco27/GitMarco | ChamferLoss | false | 9,249 | [
"MIT"
] | 0 | 2d9dd93a73a6d7b68d63222512a646cdd988909e | https://github.com/GitMarco27/GitMarco/tree/2d9dd93a73a6d7b68d63222512a646cdd988909e |
TLU | import torch
from torch import nn
class TLU(nn.Module):
def __init__(self, num_features):
"""max(y, tau) = max(y - tau, 0) + tau = ReLU(y - tau) + tau"""
super(TLU, self).__init__()
self.num_features = num_features
self.tau = nn.parameter.Parameter(torch.Tensor(1, num_features, 1,... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | ildoonet/pytorch-filter-response-norm | TLU | false | 12,522 | [
"MIT"
] | 0 | e6885f2b2272fa6cde0a131d3b3a0e42b8c6d579 | https://github.com/ildoonet/pytorch-filter-response-norm/tree/e6885f2b2272fa6cde0a131d3b3a0e42b8c6d579 |
VAE | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch import device
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from... | mcabbott/Avalon.jl | VAE | false | 10,466 | [
"MIT"
] | 0 | 6885bcc8204952a2396e762ce51432d9969c4138 | https://github.com/mcabbott/Avalon.jl/tree/6885bcc8204952a2396e762ce51432d9969c4138 |
SqrtModule | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | mirecta/nncase | SqrtModule | false | 4,174 | [
"Apache-2.0"
] | 0 | d2efa59677a26f4259b3b6a5b6ec05ea16d4e40c | https://github.com/mirecta/nncase/tree/d2efa59677a26f4259b3b6a5b6ec05ea16d4e40c |
PyConv4 | # 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.nn.parallel
import torch.optim
import torch.u... | lkf59553/pyconv | PyConv4 | false | 15,946 | [
"MIT"
] | 295 | d8b39cf43014b8fd277dcefc9eb7f8880511e977 | https://github.com/lkf59553/pyconv/tree/d8b39cf43014b8fd277dcefc9eb7f8880511e977 |
ProtoNN | import torch
import numpy as np
import torch.nn as nn
import torch.onnx
class ProtoNN(nn.Module):
def __init__(self, inputDimension, projectionDimension, numPrototypes,
numOutputLabels, gamma, W=None, B=None, Z=None):
"""
Forward computation graph for ProtoNN.
inputDimension: 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 math as tl_math
import numpy ... | adityakusupati/EdgeML | ProtoNN | false | 3,023 | [
"MIT"
] | 0 | 65933a6fdfc38945f4311043a62e120784b2b0bf | https://github.com/adityakusupati/EdgeML/tree/65933a6fdfc38945f4311043a62e120784b2b0bf |
ConvElu | import torch
from torch import nn
import torch.cuda
import torch.backends.cudnn
import torch.backends.mkl
import torch.backends.cuda
import torch.backends.quantized
class ConvElu(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, image_size,
inplace=False):
super(ConvElu, 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
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 |
PA | # 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... | SLKaMiHi/ResT-UNet-unsupervised-medical-image-registration-network-based-on-Transformer-and-CNN | PA | false | 5,790 | [
"MIT"
] | 1 | 728624f978f345a1e713046a7dde12d6f84fd3dd | https://github.com/SLKaMiHi/ResT-UNet-unsupervised-medical-image-registration-network-based-on-Transformer-and-CNN/tree/728624f978f345a1e713046a7dde12d6f84fd3dd |
ScalableTanh | import torch
from torch import nn
class ScalableTanh(nn.Module):
def __init__(self, input_size):
super(ScalableTanh, self).__init__()
self.scale = nn.Parameter(torch.zeros(input_size), requires_grad=True)
def forward(self, x):
return self.scale * torch.tanh(x)
def get_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
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | hongyehu/NeuralRG | ScalableTanh | false | 15,550 | [
"Apache-2.0"
] | 65 | ff4eb18f7f9e083dac6f3da3995f3f69ecf381e8 | https://github.com/hongyehu/NeuralRG/tree/ff4eb18f7f9e083dac6f3da3995f3f69ecf381e8 |
psi | import torch
import torch.nn as nn
class psi(nn.Module):
def __init__(self, block_size):
super(psi, self).__init__()
self.block_size = block_size
self.block_size_sq = block_size * block_size
def inverse(self, input):
output = input.permute(0, 2, 3, 1)
batch_size, d_he... | 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... | LuckMonkeys/ATSPrivacy | psi | false | 8,481 | [
"MIT"
] | 14 | 6b580942c6b98b6348d313f2bf90202ec19cefce | https://github.com/LuckMonkeys/ATSPrivacy/tree/6b580942c6b98b6348d313f2bf90202ec19cefce |
DilatedResidualLayer | import torch
import torch.nn as nn
import torch.nn.functional as F
class DilatedResidualLayer(nn.Module):
def __init__(self, dilation, in_channels, out_channels):
super(DilatedResidualLayer, self).__init__()
self.conv_dilated = nn.Conv1d(in_channels, out_channels, 3, padding
=dilation... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | MarahGamdou/sign-segmentation | DilatedResidualLayer | false | 2,620 | [
"MIT"
] | 0 | f6ef1f23b252d09b66031bfb802f18cfb4b1f4c6 | https://github.com/MarahGamdou/sign-segmentation/tree/f6ef1f23b252d09b66031bfb802f18cfb4b1f4c6 |
EncoderLayer | # 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.... | Adelashl6/mask_transformers | EncoderLayer | false | 4,842 | [
"MIT"
] | 1 | 2a2e4d1b40ae3ed546cb850d041af246806b63e7 | https://github.com/Adelashl6/mask_transformers/tree/2a2e4d1b40ae3ed546cb850d041af246806b63e7 |
REINFORCE | # 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.... | exe1023/GA-final | REINFORCE | false | 10,176 | [
"MIT"
] | 0 | dad84cda665ef24e9568a79a2e7ff0a00edf5851 | https://github.com/exe1023/GA-final/tree/dad84cda665ef24e9568a79a2e7ff0a00edf5851 |
AddNorm | # 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
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | lucmertins/CapDeepLearningBook | AddNorm | false | 12,760 | [
"MIT"
] | 0 | e5959b552c8716e7fc65a21ae9c13c58509544c1 | https://github.com/lucmertins/CapDeepLearningBook/tree/e5959b552c8716e7fc65a21ae9c13c58509544c1 |
MLPSoftQNetwork | import torch
import torch.nn as nn
import torch.nn.functional as F
class MLPSoftQNetwork(nn.Module):
def __init__(self, num_inputs, num_actions, hidden_size1=1400,
hidden_size2=1024, hidden_size3=256, init_w=0.003):
super(MLPSoftQNetwork, self).__init__()
self.linear1 = nn.Linear(num_inpu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | SAMMiCA/DL_based_E2E_Driving | MLPSoftQNetwork | false | 17,886 | [
"MIT"
] | 4 | 01f7d74a0db7ed745cf27b9a1ebab0246015ecbd | https://github.com/SAMMiCA/DL_based_E2E_Driving/tree/01f7d74a0db7ed745cf27b9a1ebab0246015ecbd |
srcEncoder | # 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_... | qbhan/pathembed | srcEncoder | false | 7,504 | [
"MIT"
] | 1 | c21823529840593bf606e10696f5879e5adb51b2 | https://github.com/qbhan/pathembed/tree/c21823529840593bf606e10696f5879e5adb51b2 |
CLNLayer | import torch
import torch.nn.functional as F
from torch import nn
class CLN(nn.Module):
def __init__(self, in_dim, use_style_fc=False, style_dim=None,
which_linear=nn.Linear, spectral_norm=False, eps=1e-05, **kwargs):
super(CLN, self).__init__()
self.in_dim = in_dim
self.use_style... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | PeterouZh/CIPS-3D | CLNLayer | false | 14,170 | [
"MIT"
] | 308 | 9b8bfa0fb23f642af042e150ccd70408f9d137c6 | https://github.com/PeterouZh/CIPS-3D/tree/9b8bfa0fb23f642af042e150ccd70408f9d137c6 |
ResUnit | import torch
import torch.nn as nn
class ResUnit(nn.Module):
def __init__(self, in_channels, out_channels, dilation=1):
super().__init__()
self.norm_1 = nn.InstanceNorm2d(in_channels)
self.norm_2 = nn.InstanceNorm2d(out_channels)
self.activation = nn.ELU()
self.conv_1 = nn... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | MRSAIL-Mini-Robotics-Software-AI-Lab/GANVAS-models | ResUnit | false | 17,668 | [
"MIT"
] | 5 | 9bc1530d5998da3908929152da2a3120832ca104 | https://github.com/MRSAIL-Mini-Robotics-Software-AI-Lab/GANVAS-models/tree/9bc1530d5998da3908929152da2a3120832ca104 |
GroupNorm | # 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_... | generall/Torchlite | GroupNorm | false | 6,735 | [
"MIT"
] | 1 | 2eb3e2a20b7619bd58b0b0fca120e2aefca0e79a | https://github.com/generall/Torchlite/tree/2eb3e2a20b7619bd58b0b0fca120e2aefca0e79a |
ConvBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
im... | Fatmangh/VIDEO-ACTION-CLASSIFICATION-USING-PRETAINED-SELF-SUPERVISED-DEPTH-AWARE-DENSE-PREDICTIVE-CODING- | ConvBlock | false | 2,236 | [
"MIT"
] | 0 | 13fac05601efed16ae8b29989aad487e04cd90a7 | https://github.com/Fatmangh/VIDEO-ACTION-CLASSIFICATION-USING-PRETAINED-SELF-SUPERVISED-DEPTH-AWARE-DENSE-PREDICTIVE-CODING-/tree/13fac05601efed16ae8b29989aad487e04cd90a7 |
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