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 |
|---|---|---|---|---|---|---|---|---|---|---|
LexaAttention | # 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... | blackbawx/LEXA | LexaAttention | false | 3,222 | [
"Apache-2.0"
] | 0 | 75e5180ca61d3e0bd78c3b8b1ece0b21c8300026 | https://github.com/blackbawx/LEXA/tree/75e5180ca61d3e0bd78c3b8b1ece0b21c8300026 |
RelativeMultiHeadAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import math
i... | ishine/tfm-tts | RelativeMultiHeadAttention | false | 3,693 | [
"MIT"
] | 0 | a964736467851ddec8f8e8933b9550cbe7d7d7eb | https://github.com/ishine/tfm-tts/tree/a964736467851ddec8f8e8933b9550cbe7d7d7eb |
SpatialAttention | # 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... | abhirajasp/CDCN | SpatialAttention | false | 14,737 | [
"MIT"
] | 463 | c9863775b1c1bffd91f956b5b2c6c78abfc988ec | https://github.com/abhirajasp/CDCN/tree/c9863775b1c1bffd91f956b5b2c6c78abfc988ec |
EqualLinear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from torch import nn
from torch.nn.functional import leaky_relu
asse... | jchetboun/anycost-gan | EqualLinear | false | 10,388 | [
"MIT"
] | 0 | 7e0005e50b915e2dfeb90fe7a9846c5df38d7c06 | https://github.com/jchetboun/anycost-gan/tree/7e0005e50b915e2dfeb90fe7a9846c5df38d7c06 |
MultiHeadAttn | import torch
import torch.nn as nn
import torch.nn.functional as F
class MultiHeadAttn(nn.Module):
def __init__(self, query_dim, key_dim, value_dim, hidden_dim, num_head,
dropatt=0.0, act_func='softmax', add_zero_attn=False, pre_lnorm=
False, post_lnorm=False):
super(MultiHeadAttn, 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.... | HKUST-KnowComp/BMGF-RoBERTa | MultiHeadAttn | false | 8,243 | [
"MIT"
] | 16 | 8e9eebd7e9fb6cc2492131fc8eaa5b5b29d999fd | https://github.com/HKUST-KnowComp/BMGF-RoBERTa/tree/8e9eebd7e9fb6cc2492131fc8eaa5b5b29d999fd |
ConvHeadPooling | # 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... | Justin900429/vision-transformer | ConvHeadPooling | false | 5,411 | [
"MIT"
] | 1 | e149092efbb83c166449944137db0ee5200f9325 | https://github.com/Justin900429/vision-transformer/tree/e149092efbb83c166449944137db0ee5200f9325 |
ConvLayer | import torch
class ConvLayer(torch.nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, stride):
super(ConvLayer, self).__init__()
reflection_padding = kernel_size // 2
self.reflection_pad = torch.nn.ReflectionPad2d(reflection_padding)
self.conv2d = torch.nn.Conv... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | Aftaab99/pytorch-multiple-style-transfer | ConvLayer | false | 18,405 | [
"BSD-3-Clause"
] | 3 | 172d384d8ef06d005a49715a9c75fc8f26a4e4f9 | https://github.com/Aftaab99/pytorch-multiple-style-transfer/tree/172d384d8ef06d005a49715a9c75fc8f26a4e4f9 |
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._inductor.runtime.... | BruceWen120/neurips-reproducibility-challenge-2019 | Generator | false | 8,957 | [
"Apache-2.0"
] | 0 | b0635aefe83e3f895ce0991913824e861bb7d02d | https://github.com/BruceWen120/neurips-reproducibility-challenge-2019/tree/b0635aefe83e3f895ce0991913824e861bb7d02d |
GHMR | # 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... | AtticusJohnson/mmdetection | GHMR | false | 11,216 | [
"Apache-2.0"
] | 0 | d8d89bafcce13d3b32b1fb3366be3bb9830546c2 | https://github.com/AtticusJohnson/mmdetection/tree/d8d89bafcce13d3b32b1fb3366be3bb9830546c2 |
SimpleEncoder | import math
import torch
from torch import Tensor
import torch.nn as nn
class PositionalEncoding(nn.Module):
"""
Learnable position embeddings
Args:
pe_type (str): type of position embeddings,
which is chosen from ['fully_learnable', 'sinusoidal']
d_model (int): embed dim (req... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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 Tensor
import torch.nn as nn
assert_size_stride = ... | doiken23/mccformers.pytorch | SimpleEncoder | false | 6,590 | [
"MIT"
] | 1 | 678bd9448e3a2f35bd408e8c8e510e0ea1f9a19f | https://github.com/doiken23/mccformers.pytorch/tree/678bd9448e3a2f35bd408e8c8e510e0ea1f9a19f |
UniformBoxWarp | # 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... | HexagonPrime/pixel-nerf | UniformBoxWarp | false | 2,401 | [
"BSD-2-Clause"
] | 0 | 298aa7a3451c01e6f19f73f0c756672d3de54bf9 | https://github.com/HexagonPrime/pixel-nerf/tree/298aa7a3451c01e6f19f73f0c756672d3de54bf9 |
Downsample | import torch
import torchvision.transforms.functional as F
import torch.nn as nn
import torch.nn.functional as F
class Downsample(nn.Module):
def __init__(self, in_ch=None, out_ch=None, with_conv=False, fir=False,
fir_kernel=(1, 3, 3, 1)):
super().__init__()
out_ch = out_ch if out_ch else... | 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... | DeepTitan/PNDM | Downsample | false | 13,921 | [
"Apache-2.0"
] | 61 | 4037a4f40011c9a0d47b92303e64d47fcc7ed56a | https://github.com/DeepTitan/PNDM/tree/4037a4f40011c9a0d47b92303e64d47fcc7ed56a |
CharbonnierCompLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import functools
from torch.... | Jason-Khan/mmediting | CharbonnierCompLoss | false | 633 | [
"Apache-2.0"
] | 0 | d187f95a675dff3eb975a575bd9278d643b5b645 | https://github.com/Jason-Khan/mmediting/tree/d187f95a675dff3eb975a575bd9278d643b5b645 |
BasicBlock | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.utils import weight_norm
def conv3x3(in_planes, out_planes, stride=1):
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=0, bias=True)
class BasicBlock(nn.Module):
"""
Residual BasicBlock... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | RaoUmer/ISRResCNet | BasicBlock | false | 17,839 | [
"MIT"
] | 6 | 8175bb9efa5bba2cce4ad86616219209c20b7244 | https://github.com/RaoUmer/ISRResCNet/tree/8175bb9efa5bba2cce4ad86616219209c20b7244 |
PairwiseRankingLoss | # 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... | HUSTLyn/SentEval | PairwiseRankingLoss | false | 11,452 | [
"BSD-3-Clause"
] | 0 | 3aaa8c80681e44d641dccbc1267c2dc6b2e2609f | https://github.com/HUSTLyn/SentEval/tree/3aaa8c80681e44d641dccbc1267c2dc6b2e2609f |
L2Normalize | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn
import torch... | valeoai/obow | L2Normalize | false | 16,651 | [
"Apache-2.0"
] | 84 | 3758504f5e058275725c35ca7faca3731572b911 | https://github.com/valeoai/obow/tree/3758504f5e058275725c35ca7faca3731572b911 |
InvConvNear | import torch
from torch.nn import functional as F
from torch import nn
import torch.utils.data
import torch.optim
class InvConvNear(nn.Module):
def __init__(self, channels, n_split=4, no_jacobian=False, **kwargs):
super().__init__()
assert n_split % 2 == 0
self.channels = 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
from torch import nn
import torch.utils.data
import torch.optim
assert_size_stri... | Zenodia/NeMo | InvConvNear | false | 1,318 | [
"Apache-2.0"
] | 0 | 3c288d8a7caf667c95444c39434e3ebc5f53d911 | https://github.com/Zenodia/NeMo/tree/3c288d8a7caf667c95444c39434e3ebc5f53d911 |
AttentionConv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | Sam-limyr/End-to-end-ASR-Pytorch | AttentionConv | false | 1,011 | [
"MIT"
] | 0 | 623a50792f48218228549ea17b8ea5e8bb1b342f | https://github.com/Sam-limyr/End-to-end-ASR-Pytorch/tree/623a50792f48218228549ea17b8ea5e8bb1b342f |
ChannelMaxPool | # 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... | joeization/CycleGAN | ChannelMaxPool | false | 3,745 | [
"MIT"
] | 0 | 9635c8e3a7b1634b2e2eb5b5299f03a4e0786868 | https://github.com/joeization/CycleGAN/tree/9635c8e3a7b1634b2e2eb5b5299f03a4e0786868 |
AdditiveAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
class AdditiveAttention(nn.Module):
def __init__(self, encoder_hidden_state_dim, decoder_hidden_state_dim,
internal_dim=None):
super(AdditiveAttention, self).__init__()
if internal_dim is None:
internal_dim = 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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | fireofearth/Trajectron-plus-plus | AdditiveAttention | false | 3,509 | [
"MIT"
] | 0 | b39df025b62a8ce466266936198baee9bfa14e89 | https://github.com/fireofearth/Trajectron-plus-plus/tree/b39df025b62a8ce466266936198baee9bfa14e89 |
Reorg | import torch
from torch.optim.lr_scheduler import *
import torch.optim
import torch.nn as nn
import torch.utils.data
import torch.utils.model_zoo
class Reorg(nn.Module):
def __init__(self, stride=2):
super(Reorg, self).__init__()
self.stride = stride
def forward(self, x):
stride = 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.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 | Reorg | false | 252 | [
"MIT"
] | 0 | 9d647426c274afc7651ea4fe9a11f2a0a0fd1fba | https://github.com/ChitienSun/NCTU_DLSR_final_project/tree/9d647426c274afc7651ea4fe9a11f2a0a0fd1fba |
GHMC | # 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
... | Atten4Vis/DemystifyLocalViT | GHMC | false | 13,368 | [
"MIT"
] | 64 | 2e2327caec6d56ae2c8aa861b32bb62f3cdb786e | https://github.com/Atten4Vis/DemystifyLocalViT/tree/2e2327caec6d56ae2c8aa861b32bb62f3cdb786e |
Padding1 | import torch
import torch._utils
class Padding1(torch.nn.Module):
def __init__(self, input_channel):
super(Padding1, self).__init__()
self.requires_grad = False
self.conv = torch.nn.ConvTranspose2d(input_channel, input_channel,
1, stride=2, padding=0, groups=input_channel, bi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch._utils
assert_size_stride = torch._C._dynamo.guards.assert_size_str... | ijinjay/torch2mindspore | Padding1 | false | 3,656 | [
"MIT"
] | 0 | e4c06bd5e8a3b25b72bf158393a66c5cd1b572d2 | https://github.com/ijinjay/torch2mindspore/tree/e4c06bd5e8a3b25b72bf158393a66c5cd1b572d2 |
Hflip | import torch
import torch.nn as nn
def hflip(input: 'torch.Tensor') ->torch.Tensor:
return torch.flip(input, [-1])
class Hflip(nn.Module):
"""Horizontally flip a tensor image or a batch of tensor images. Input must
be a tensor of shape (C, H, W) or a batch of tensors :math:`(*, C, H, W)`.
Args:
... | 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... | JoanFM/kornia | Hflip | false | 11,556 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 808898887cde69074ca3e3df9b24dea9682aad90 | https://github.com/JoanFM/kornia/tree/808898887cde69074ca3e3df9b24dea9682aad90 |
BasicModel2 | # 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... | aravipati12/captum | BasicModel2 | false | 10,093 | [
"BSD-3-Clause"
] | 0 | ef3e81d89c8c4404a49c384cf0727f2e7d393f5f | https://github.com/aravipati12/captum/tree/ef3e81d89c8c4404a49c384cf0727f2e7d393f5f |
ReCoNet2 | import torch
import numpy as np
class SelectiveLoadModule(torch.nn.Module):
"""Only load layers in trained models with the same name."""
def __init__(self):
super(SelectiveLoadModule, self).__init__()
def forward(self, x):
return x
def load_state_dict(self, state_dict):
"""O... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | irsisyphus/reconet | ReCoNet2 | false | 15,690 | [
"MIT"
] | 56 | 863acf8dde4d45c8521634af27878fe04f3b2e56 | https://github.com/irsisyphus/reconet/tree/863acf8dde4d45c8521634af27878fe04f3b2e56 |
EmbeddingModel | import torch
import torch.nn.functional as F
from torch import nn
from torch import optim
class EmbeddingModel(nn.Module):
def __init__(self, obs_size, num_outputs):
super(EmbeddingModel, self).__init__()
self.obs_size = obs_size
self.num_outputs = num_outputs
self.fc1 = nn.Linear... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Deepest-Project/agent57_from_ngu | EmbeddingModel | false | 5,200 | [
"MIT"
] | 1 | 2f596024c7538cfaa5cf63cde1b77f8a1c22d208 | https://github.com/Deepest-Project/agent57_from_ngu/tree/2f596024c7538cfaa5cf63cde1b77f8a1c22d208 |
FC_Decoder | import torch
import torch.nn as nn
import torch.nn.functional as F
class FC_Decoder(nn.Module):
def __init__(self, embedding_size):
super(FC_Decoder, self).__init__()
self.fc3 = nn.Linear(embedding_size, 1024)
self.fc4 = nn.Linear(1024, 784)
def forward(self, z):
h3 = F.relu(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | saksham36/LangGrounding | FC_Decoder | false | 4,252 | [
"MIT"
] | 0 | 89ee9e5b8090e61e6bf7bf2b3e1dd45edf9664b7 | https://github.com/saksham36/LangGrounding/tree/89ee9e5b8090e61e6bf7bf2b3e1dd45edf9664b7 |
FCNet | # 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.... | animeshbchowdhury/robust-pnr-time | FCNet | false | 12,098 | [
"BSD-3-Clause"
] | 0 | 301c5d973b8c024a85fdab915986ecf257e7698b | https://github.com/animeshbchowdhury/robust-pnr-time/tree/301c5d973b8c024a85fdab915986ecf257e7698b |
BCE_loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | Jianrong-Lu/Head-and-Neck-Tumour-Segmentation-and-Prediction-of-Patient-Survival | BCE_loss | false | 642 | [
"MIT"
] | 0 | 257cf17ce6d405166dd8449f3b34e305cb5103b2 | https://github.com/Jianrong-Lu/Head-and-Neck-Tumour-Segmentation-and-Prediction-of-Patient-Survival/tree/257cf17ce6d405166dd8449f3b34e305cb5103b2 |
Model | # 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... | B06901052/s3prl | Model | false | 105 | [
"MIT"
] | 0 | 5f63d2df043d2d7c81580cd042fa2cea34746f48 | https://github.com/B06901052/s3prl/tree/5f63d2df043d2d7c81580cd042fa2cea34746f48 |
Net2 | # 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... | moritzschaefer/pavooc | Net2 | false | 7,265 | [
"MIT"
] | 1 | 735f5455f9a95a5734436a24e2aa92cf600c91af | https://github.com/moritzschaefer/pavooc/tree/735f5455f9a95a5734436a24e2aa92cf600c91af |
Fair | import torch
import torch.nn as nn
import torch.utils.model_zoo
class Fair(nn.Module):
def __init__(self):
super(Fair, self).__init__()
self.c = 1.0
def forward(self, X, Y):
r = torch.add(X, -Y)
ra = torch.abs(r)
error = self.c ** 2 * (ra / self.c - torch.log(1 + ra /... | 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
... | davefiorino/EDSR-PyTorch | Fair | false | 1,796 | [
"MIT"
] | 0 | 97ad32a09a71816a36c45d92cdb2ea7ab42ba685 | https://github.com/davefiorino/EDSR-PyTorch/tree/97ad32a09a71816a36c45d92cdb2ea7ab42ba685 |
Reverse | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | h0ngwen/torchaudio-augmentations | Reverse | false | 6,773 | [
"MIT"
] | 1 | d044f9d020e12032ab9280acf5f34a337e72d212 | https://github.com/h0ngwen/torchaudio-augmentations/tree/d044f9d020e12032ab9280acf5f34a337e72d212 |
Upsampler | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from torchvision.transforms import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch.... | EvgeneyZ/RBPN | Upsampler | false | 9,501 | [
"MIT"
] | 0 | acfe636cc48a4fbfea78f934a251c32e53367659 | https://github.com/EvgeneyZ/RBPN/tree/acfe636cc48a4fbfea78f934a251c32e53367659 |
Decoder | import torch
import torch.nn as nn
class Decoder(nn.Module):
def __init__(self, latent_dim=4, obs_dim=2, nhidden=20):
super(Decoder, self).__init__()
self.relu = nn.ReLU(inplace=True)
self.fc1 = nn.Linear(latent_dim, nhidden)
self.fc2 = nn.Linear(nhidden, obs_dim)
def forward... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | arnabgho/torchdiffeq | Decoder | false | 3,199 | [
"MIT"
] | 0 | d4f73440d0e714b87ea133610e61eefbd673e5f5 | https://github.com/arnabgho/torchdiffeq/tree/d4f73440d0e714b87ea133610e61eefbd673e5f5 |
LMCriterion | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
from torch.autograd import Variable
class LMCriterion(nn.Module):
def __init__(self):
super(LMCriterion, self).__init__()
def forward(self, input, target):
logprob_select = torch.gather(input, 1, 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
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty... | roma-ghewari/visDial.pytorch | LMCriterion | false | 16,339 | [
"MIT"
] | 123 | 03fe6e679170d54a985b6402f07fea4a5fb4dd73 | https://github.com/roma-ghewari/visDial.pytorch/tree/03fe6e679170d54a985b6402f07fea4a5fb4dd73 |
TransposeMultiheadAttention | # 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.... | TheShadow29/pytorchvideo | TransposeMultiheadAttention | false | 9,701 | [
"Apache-2.0"
] | 0 | 39a3e34e33fb0e1ec142288df08f6e8c3585961a | https://github.com/TheShadow29/pytorchvideo/tree/39a3e34e33fb0e1ec142288df08f6e8c3585961a |
C2 | # 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
from co... | zjgbz/img_cls | C2 | false | 4,669 | [
"MIT"
] | 0 | 513d5ae423d95e008a82a6ffe443db49f8ed9ac2 | https://github.com/zjgbz/img_cls/tree/513d5ae423d95e008a82a6ffe443db49f8ed9ac2 |
MultiHeadAttention | import math
import torch
from torch import nn
import torch.utils.data
import torch.optim
class MultiHeadAttention(nn.Module):
"""
Multi-head scaled dot-product attention layer.
Args:
hidden_size: size of the embeddings in the model, also known as d_model
num_attention_heads: number of hea... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Royeqiu/Nemo_ASR | MultiHeadAttention | false | 17,869 | [
"Apache-2.0"
] | 10 | 12b91b06dc5e4d0aa29d43bc7e701a93ee5eec4e | https://github.com/Royeqiu/Nemo_ASR/tree/12b91b06dc5e4d0aa29d43bc7e701a93ee5eec4e |
LxmertCrossAttentionLayer | from _paritybench_helpers import _mock_config
import math
import torch
from torch import nn
class LxmertAttention(nn.Module):
def __init__(self, config, ctx_dim=None):
super().__init__()
if config.hidden_size % config.num_attention_heads != 0:
raise ValueError(
'The hi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | rsgit95/med_kg_txt_multimodal | LxmertCrossAttentionLayer | false | 4,219 | [
"Apache-2.0"
] | 0 | 80355b0cf58e0571531ad6f9728c533110ca996d | https://github.com/rsgit95/med_kg_txt_multimodal/tree/80355b0cf58e0571531ad6f9728c533110ca996d |
Conv2dBlock | import torch
from torch import nn
class Conv2dBlock(nn.Module):
def __init__(self, input_dim, output_dim, kernel_size, stride, padding=
0, dilation=1, norm='weight', activation='relu', pad_type='zero',
use_bias=True, *args, **karg):
super(Conv2dBlock, self).__init__()
self.conv = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | google/dynamic-video-depth | Conv2dBlock | false | 15,453 | [
"Apache-2.0"
] | 144 | 7dab8f9e156fa35735301695ea020aee7221fb31 | https://github.com/google/dynamic-video-depth/tree/7dab8f9e156fa35735301695ea020aee7221fb31 |
DecoderLayer | # 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.... | aim-uofa/DyCo3D | DecoderLayer | false | 14,776 | [
"BSD-2-Clause"
] | 100 | 17d22c2d839c0a1043fb72df301e3935af5ca0e9 | https://github.com/aim-uofa/DyCo3D/tree/17d22c2d839c0a1043fb72df301e3935af5ca0e9 |
MaxMarginCriterion | # 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... | kmario23/MAttNet | MaxMarginCriterion | false | 7,047 | [
"MIT"
] | 1 | 0d66321eb5dc9c8523a5ebf45f608b0672b051ab | https://github.com/kmario23/MAttNet/tree/0d66321eb5dc9c8523a5ebf45f608b0672b051ab |
EncoderImagePrecomp | import torch
import numpy as np
from torch import nn
from collections import OrderedDict
import torch.nn.init
def l2norm(X):
"""L2-normalize columns of X
"""
norm = torch.pow(X, 2).sum(dim=1, keepdim=True).sqrt()
X = torch.div(X, norm)
return X
class EncoderImagePrecomp(nn.Module):
def __in... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import numpy as np
... | Shiyang-Yan/Discrete-continous-PG-for-Retrieval | EncoderImagePrecomp | false | 17,924 | [
"Apache-2.0"
] | 8 | 39fd7a81f732ae043c2ea20352a0c55b72834639 | https://github.com/Shiyang-Yan/Discrete-continous-PG-for-Retrieval/tree/39fd7a81f732ae043c2ea20352a0c55b72834639 |
BiaffineScorer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | a101269/Chinese_Semantic_Dependency_Parser_with_knowledge | BiaffineScorer | false | 6,040 | [
"MIT"
] | 1 | ca9998045c7789bc3ea5ad6a8ce7fe0af8308669 | https://github.com/a101269/Chinese_Semantic_Dependency_Parser_with_knowledge/tree/ca9998045c7789bc3ea5ad6a8ce7fe0af8308669 |
AverageAttention | import torch
import torch.nn as nn
import torch.cuda
import torch.distributed
class PositionwiseFeedForward(nn.Module):
""" A two-layer Feed-Forward-Network with residual layer norm.
Args:
d_model (int): the size of input for the first-layer of the FFN.
d_ff (int): the hidden layer size of th... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.cuda
import torch.distributed
assert_size_str... | GarrettNicolai/OpenNMT-py | AverageAttention | false | 9,108 | [
"MIT"
] | 0 | 9491d900ac1b50fe39da417bacc0b9d610331888 | https://github.com/GarrettNicolai/OpenNMT-py/tree/9491d900ac1b50fe39da417bacc0b9d610331888 |
GradLoss | # 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
... | d4l3k/crowds | GradLoss | false | 12,236 | [
"MIT"
] | 0 | a57eee80d66498474c86cec22dd77be9d627ad97 | https://github.com/d4l3k/crowds/tree/a57eee80d66498474c86cec22dd77be9d627ad97 |
Correlation | import torch
from torch import nn
class Correlation(nn.Module):
"""Correlation Congruence for Knowledge Distillation, ICCV 2019.
The authors nicely shared the code with me. I restructured their code to be
compatible with my running framework. Credits go to the original author"""
def __init__(self):
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_... | bobo0810/RepDistiller | Correlation | false | 10,156 | [
"BSD-2-Clause"
] | 0 | 0a4cea2142221b9b31c8e995920273f5619b37f8 | https://github.com/bobo0810/RepDistiller/tree/0a4cea2142221b9b31c8e995920273f5619b37f8 |
Model | # 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
assert_size_stride = torch._C... | stepan-krivanek/image-recognition | Model | false | 10,815 | [
"MIT"
] | 0 | 6c421e768e83db489e4caa22989f7dad95519578 | https://github.com/stepan-krivanek/image-recognition/tree/6c421e768e83db489e4caa22989f7dad95519578 |
GEGLU | import torch
import torch.nn as nn
class PositionWiseFeedForward(nn.Module):
"""
title: Position-wise Feed-Forward Network (FFN)
summary: Documented reusable implementation of the position wise feedforward network.
# Position-wise Feed-Forward Network (FFN)
This is a [PyTorch](https://pytorch.org... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | robburdon/pytorch_tabular | GEGLU | false | 16,332 | [
"MIT"
] | 560 | 9bf75f22c6e1b3033ad699713e77c283d55f3555 | https://github.com/robburdon/pytorch_tabular/tree/9bf75f22c6e1b3033ad699713e77c283d55f3555 |
RingLoss | import torch
import torch.nn as nn
class RingLoss(nn.Module):
"""Ring loss.
Reference:
Zheng et al. Ring loss: Convex Feature Normalization for Face Recognition. CVPR 2018.
"""
def __init__(self, weight_ring=1.0):
super(RingLoss, self).__init__()
self.radius = nn.Parameter(to... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | LT1st/ReID_Alined_beginer | RingLoss | false | 13,971 | [
"MIT"
] | 370 | 1a12403a32d99900451ac05cd3623a9b770f6d24 | https://github.com/LT1st/ReID_Alined_beginer/tree/1a12403a32d99900451ac05cd3623a9b770f6d24 |
LinearAdd | 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 LinearAdd(nn.Module):
def __init__(self, in_channels, out_channels, **kwargs):
super(LinearAdd, self).__init__()
seed = 2018
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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.cuda
import torch.backends.cudnn
import torch.... | yangw1234/intel-extension-for-pytorch | LinearAdd | false | 10,958 | [
"Apache-2.0"
] | 0 | 571e31578605ab3999dcebbb4d66a0ee2253a464 | https://github.com/yangw1234/intel-extension-for-pytorch/tree/571e31578605ab3999dcebbb4d66a0ee2253a464 |
Attention | import torch
def activation_func(name):
name = name.lower()
if name == 'sigmoid':
return torch.nn.Sigmoid()
elif name == 'tanh':
return torch.nn.Tanh()
elif name == 'relu':
return torch.nn.ReLU()
elif name == 'softmax':
return torch.nn.Softmax()
elif name == 'le... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | xu94-nlp/Code-for-MAMO | Attention | false | 11,029 | [
"Apache-2.0"
] | 0 | d9c6655e0660976c90c07fa096a1f5dc8328a60b | https://github.com/xu94-nlp/Code-for-MAMO/tree/d9c6655e0660976c90c07fa096a1f5dc8328a60b |
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 ... | adi0229/gpt-2-flask-api | MLP | false | 14,741 | [
"MIT"
] | 47 | 274d836ede9400566777893cea8662e61bbd5d8c | https://github.com/adi0229/gpt-2-flask-api/tree/274d836ede9400566777893cea8662e61bbd5d8c |
SoftNLL | # 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... | lehgtrung/gcn-over-pruned-trees | SoftNLL | false | 12,700 | [
"Apache-2.0"
] | 0 | ebf0de0948883009a9bebb8ff336e8d6fe50a26f | https://github.com/lehgtrung/gcn-over-pruned-trees/tree/ebf0de0948883009a9bebb8ff336e8d6fe50a26f |
PositionwiseFeedForward | import math
import torch
import torch.distributed
import torch
import torch.nn as nn
def gelu(x):
return 0.5 * x * (1 + torch.tanh(math.sqrt(2 / math.pi) * (x + 0.044715 *
torch.pow(x, 3))))
class PositionwiseFeedForward(nn.Module):
""" A two-layer Feed-Forward-Network with residual layer norm.
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import ... | dat821168/PreSumm | PositionwiseFeedForward | false | 1,804 | [
"MIT"
] | 0 | 3c84fc97f50a193a865ccef2300adf5683397539 | https://github.com/dat821168/PreSumm/tree/3c84fc97f50a193a865ccef2300adf5683397539 |
GEGLU | # 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 ... | Lawliet19189/squad-1 | GEGLU | false | 11,635 | [
"MIT"
] | 0 | 75531054d74e20838d8acff81749f335973b9ae3 | https://github.com/Lawliet19189/squad-1/tree/75531054d74e20838d8acff81749f335973b9ae3 |
SumLossModule | # 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
assert_size_stride = t... | pkalluri/specialized-conditional-pcnn | SumLossModule | false | 4,129 | [
"Apache-2.0"
] | 0 | ed94e47654ed749a7dd3492c4e074e2a8fb12df8 | https://github.com/pkalluri/specialized-conditional-pcnn/tree/ed94e47654ed749a7dd3492c4e074e2a8fb12df8 |
DAInsHead | import torch
import torch.utils.data
from torchvision.transforms import functional as F
from torch import nn
import torch.nn.functional as F
class DAInsHead(nn.Module):
"""
Adds a simple Instance-level Domain Classifier head
"""
def __init__(self, in_channels):
"""
Arguments:
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | thesuperorange/Domain-Adaptive-Faster-RCNN-PyTorch | DAInsHead | false | 13,072 | [
"MIT"
] | 0 | bcde744a486b25ec1d6e4b023da3ce0c8e5d72a7 | https://github.com/thesuperorange/Domain-Adaptive-Faster-RCNN-PyTorch/tree/bcde744a486b25ec1d6e4b023da3ce0c8e5d72a7 |
Mul | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | NehzUx/autodl | Mul | false | 8,594 | [
"Apache-2.0"
] | 25 | c80fdc4b297ed1ec2b9e6911d313f1fe31d83cb9 | https://github.com/NehzUx/autodl/tree/c80fdc4b297ed1ec2b9e6911d313f1fe31d83cb9 |
OutputTransition | # 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... | chenkarl/kits19 | OutputTransition | false | 12,213 | [
"MIT"
] | 0 | 7fa912320a23c6bf649566a1509aa493656b24c1 | https://github.com/chenkarl/kits19/tree/7fa912320a23c6bf649566a1509aa493656b24c1 |
ECAAttention | # 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
from torch.nn import init
assert_size_stride = torch._C._dy... | Nitin-Mane/External-Attention-pytorch | ECAAttention | false | 14,112 | [
"MIT"
] | 4,466 | 1ceda306c41063af11c956334747763444a4d83f | https://github.com/Nitin-Mane/External-Attention-pytorch/tree/1ceda306c41063af11c956334747763444a4d83f |
TopkMSELoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | alipay/Pyraformer | TopkMSELoss | false | 18,280 | [
"Apache-2.0"
] | 7 | 84af4dbd93b7b96975b5034f0dde412005260123 | https://github.com/alipay/Pyraformer/tree/84af4dbd93b7b96975b5034f0dde412005260123 |
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_... | DavyMorgan/invariant-risk-minimization | Net | false | 13,580 | [
"MIT"
] | 77 | d0fe48e75329561e6b2d47dbc97042aa740f77c2 | https://github.com/DavyMorgan/invariant-risk-minimization/tree/d0fe48e75329561e6b2d47dbc97042aa740f77c2 |
Actor | import torch
import torch.nn as nn
import torch.nn.functional as F
class Actor(nn.Module):
def __init__(self, state_dim, action_dim, max_action):
super(Actor, self).__init__()
self.l1 = nn.Linear(state_dim, 1024)
self.l2 = nn.Linear(1024, 512)
self.l3 = nn.Linear(512, 256)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ctoto93/TD3 | Actor | false | 9,965 | [
"MIT"
] | 0 | 88482b9f1fb4441d74426ece60d5da13414aeb77 | https://github.com/ctoto93/TD3/tree/88482b9f1fb4441d74426ece60d5da13414aeb77 |
LayerNorm | # 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
import torch.utils.data
import torch.optim
assert_size_str... | Royeqiu/Nemo_ASR | LayerNorm | false | 17,868 | [
"Apache-2.0"
] | 10 | 12b91b06dc5e4d0aa29d43bc7e701a93ee5eec4e | https://github.com/Royeqiu/Nemo_ASR/tree/12b91b06dc5e4d0aa29d43bc7e701a93ee5eec4e |
ResidualBlock | import torch
import torch.nn as nn
import torch.utils.data
class ResidualBlock(nn.Module):
def __init__(self, in_channels, out_channels, activation='relu'):
super().__init__()
self.in_channels, self.out_channels, self.activation = (in_channels,
out_channels, activation)
self.b... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guard... | Weiyuhong-1998/DI-engine | ResidualBlock | false | 14,573 | [
"Apache-2.0"
] | 464 | 88658ea358298c6e61e95a454284b8853a3e9484 | https://github.com/Weiyuhong-1998/DI-engine/tree/88658ea358298c6e61e95a454284b8853a3e9484 |
Binary | # 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.optim
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strid... | ai-in-motion/moai | Binary | false | 18,342 | [
"Apache-2.0"
] | 10 | e38cac046c059d2e2331ef4883bbabc5a500a5cf | https://github.com/ai-in-motion/moai/tree/e38cac046c059d2e2331ef4883bbabc5a500a5cf |
LMA_Merge | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | hmdliu/PCGNet | LMA_Merge | false | 3,599 | [
"MIT"
] | 0 | c03f25dc1b138afc52f612c1c517b61874baa02a | https://github.com/hmdliu/PCGNet/tree/c03f25dc1b138afc52f612c1c517b61874baa02a |
BertSelfAttention | from _paritybench_helpers import _mock_config
import math
import torch
import torch.nn as nn
class BertSelfAttention(nn.Module):
def __init__(self, config):
super(BertSelfAttention, self).__init__()
if config.hidden_size % config.num_attention_heads != 0:
raise ValueError(
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Andr3wis2Cool4School/AI-pro | BertSelfAttention | false | 1,304 | [
"MIT"
] | 0 | dfe5f5959bc187d899a86f13b84158c66f64d1cc | https://github.com/Andr3wis2Cool4School/AI-pro/tree/dfe5f5959bc187d899a86f13b84158c66f64d1cc |
ConvReg | # 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_... | Guru-Uni-siegen/Domain-Shifting-Network | ConvReg | false | 11,475 | [
"MIT"
] | 0 | dd9eb7bda07634874497a335151b5e967aaad874 | https://github.com/Guru-Uni-siegen/Domain-Shifting-Network/tree/dd9eb7bda07634874497a335151b5e967aaad874 |
TotalVariation | # 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... | NickleDave/kornia | TotalVariation | false | 2,684 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 5392651d0bc268da577fa0a49aa50f957289c7dd | https://github.com/NickleDave/kornia/tree/5392651d0bc268da577fa0a49aa50f957289c7dd |
Model | import torch
import torch.nn as nn
class Model(nn.Module):
def __init__(self, input_size, hidden_size, output_size):
super(Model, self).__init__()
self.layer1 = nn.Linear(input_size, hidden_size)
self.layer2 = nn.Linear(hidden_size, output_size)
def forward(self, x):
x = 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.... | mbrukman/machine-learning-book | Model | false | 7,195 | [
"MIT"
] | 1 | f29a0f8aafa63a77081f3bcec68866e33dd41776 | https://github.com/mbrukman/machine-learning-book/tree/f29a0f8aafa63a77081f3bcec68866e33dd41776 |
L1NormLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.asser... | Dogacel/mmfashion | L1NormLoss | false | 11,404 | [
"Apache-2.0"
] | 0 | e49613245c8501042edd7aeeaa8fb93e5ea13238 | https://github.com/Dogacel/mmfashion/tree/e49613245c8501042edd7aeeaa8fb93e5ea13238 |
SoftTarget | # 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... | wangxianliang/FaceX-Zoo | SoftTarget | false | 13,088 | [
"Apache-2.0"
] | 0 | b0555c88a0350fa7b59c317f3a171f551fef4e6e | https://github.com/wangxianliang/FaceX-Zoo/tree/b0555c88a0350fa7b59c317f3a171f551fef4e6e |
VertexDirectEmbedder | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.data
from... | YutouTaro/detectron2 | VertexDirectEmbedder | false | 12,026 | [
"Apache-2.0"
] | 0 | 29f90062fa2978a35f1d599bb30768a2370378ca | https://github.com/YutouTaro/detectron2/tree/29f90062fa2978a35f1d599bb30768a2370378ca |
MaskedMSELoss | # 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... | shrx11/M2H2-dataset | MaskedMSELoss | false | 16,430 | [
"MIT"
] | 206 | 8be80041fc0de04f2a6113e305f09f3b8d6279f4 | https://github.com/shrx11/M2H2-dataset/tree/8be80041fc0de04f2a6113e305f09f3b8d6279f4 |
DeltaGFit | # 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.... | sebaztiano/PyHDX | DeltaGFit | false | 10,749 | [
"MIT"
] | 0 | 12fc2b5f67200885706226823bd8e1f46e3b5db1 | https://github.com/sebaztiano/PyHDX/tree/12fc2b5f67200885706226823bd8e1f46e3b5db1 |
Symmetric | # 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.quantization
import torch.onnx
import torch.nn.parallel
import torch.utils.data
import torch.fx
import to... | Lezcano/tutorials | Symmetric | false | 5,519 | [
"BSD-3-Clause"
] | 1 | 24946b2e6d3d825afed6b35c1c4d618a70a88be8 | https://github.com/Lezcano/tutorials/tree/24946b2e6d3d825afed6b35c1c4d618a70a88be8 |
SDNE_layer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | ChengzhiPiao/cogdl | SDNE_layer | false | 5,017 | [
"MIT"
] | 1 | 182e0b95b3dfbe771570037c58aacd8f677b6500 | https://github.com/ChengzhiPiao/cogdl/tree/182e0b95b3dfbe771570037c58aacd8f677b6500 |
Reorg | import torch
import torch.nn as nn
class Reorg(nn.Module):
""" This layer reorganizes a tensor according to a stride.
The dimensions 2,3 will be sliced by the stride and then stacked in dimension 1. (input must have 4 dimensions)
Args:
stride (int): stride to divide the input tensor
"""
... | 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... | hilman-dayo/ObjectDetection-OneStageDet | Reorg | false | 15,531 | [
"MIT"
] | 331 | 44054ad335e24e99a98fdad0d18b9bf3a80c941c | https://github.com/hilman-dayo/ObjectDetection-OneStageDet/tree/44054ad335e24e99a98fdad0d18b9bf3a80c941c |
KarankEtAl | # 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_... | giorgosouz/HSI-classification-makantasis-cnn | KarankEtAl | false | 10,153 | [
"MIT"
] | 0 | 95f18274d7cb67babb971db71f358a73dee2affc | https://github.com/giorgosouz/HSI-classification-makantasis-cnn/tree/95f18274d7cb67babb971db71f358a73dee2affc |
BasicLinearNet | # 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 ... | dkrako/captum | BasicLinearNet | false | 10,032 | [
"BSD-3-Clause"
] | 0 | b5297bacbaec4e37f353a27de5e728bc2cbc1694 | https://github.com/dkrako/captum/tree/b5297bacbaec4e37f353a27de5e728bc2cbc1694 |
RegressionModel | # 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_... | glhr/swig | RegressionModel | false | 3,557 | [
"MIT"
] | 0 | d6465862ae9adaab6594f79ec8eed211b5d7e4d8 | https://github.com/glhr/swig/tree/d6465862ae9adaab6594f79ec8eed211b5d7e4d8 |
FeedForward | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | Misuzu-Kurenai/mlp-singer | FeedForward | false | 848 | [
"MIT"
] | 0 | 416451045bb9b3965aaf496e84a8b45332a6ba59 | https://github.com/Misuzu-Kurenai/mlp-singer/tree/416451045bb9b3965aaf496e84a8b45332a6ba59 |
CondInjection | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | dubtor/EditGAN-Robert | CondInjection | false | 15,239 | [
"BSD-2-Clause"
] | 110 | 8e6d80e7647c3536827f11cf0a9abf51c42794b2 | https://github.com/dubtor/EditGAN-Robert/tree/8e6d80e7647c3536827f11cf0a9abf51c42794b2 |
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.triton_helpers import libdevice
import torch.nn as ... | ccha23/miml | Generator | false | 6,400 | [
"MIT"
] | 1 | 6a41de1c0bb41d38e3cdc6e9c27363215b7729b9 | https://github.com/ccha23/miml/tree/6a41de1c0bb41d38e3cdc6e9c27363215b7729b9 |
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... | brandstetter-johannes/ocp | GaussianSmearing | false | 9,956 | [
"MIT",
"BSD-3-Clause"
] | 0 | 69cc90e6bed8aa09222cd77b926d7a34e96302ed | https://github.com/brandstetter-johannes/ocp/tree/69cc90e6bed8aa09222cd77b926d7a34e96302ed |
MobileViTv2Attention | # 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.... | weihaoxie/External-Attention-pytorch | MobileViTv2Attention | false | 4,526 | [
"MIT"
] | 0 | 9bec70f4ed8dd858c815e9bad240ab2f95a91a9f | https://github.com/weihaoxie/External-Attention-pytorch/tree/9bec70f4ed8dd858c815e9bad240ab2f95a91a9f |
TransformerLayer | import math
import torch
import uuid
from torch import Tensor
import torch.nn as nn
from typing import Tuple
import torch.nn.functional as F
from typing import Optional
from typing import Dict
from torch.nn import Parameter
def gelu(x):
"""Implementation of the gelu activation function.
For information: Open... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | leeharry92/esm | TransformerLayer | false | 12,728 | [
"MIT"
] | 0 | 7d0feccf03ebbdeba4e7ba0f21d934099a0223ce | https://github.com/leeharry92/esm/tree/7d0feccf03ebbdeba4e7ba0f21d934099a0223ce |
HighwayMLP | # 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.... | okcd00/glyce | HighwayMLP | false | 10,676 | [
"Apache-2.0"
] | 0 | 010d88ac5cff4969308d2f8d105831ddcb352a02 | https://github.com/okcd00/glyce/tree/010d88ac5cff4969308d2f8d105831ddcb352a02 |
TensorNearestPad | import torch
class TensorNearestPad(torch.nn.Module):
def __init__(self, lower=1, upper=1):
super().__init__()
assert isinstance(lower, int) and lower >= 0
assert isinstance(upper, int) and upper >= 0
self.lower = lower
self.upper = upper
def forward(self, 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | Minyus/pipelinex | TensorNearestPad | false | 14,039 | [
"Apache-2.0"
] | 188 | f35c524ec9c50751ee27d9a42d98317e16f1c544 | https://github.com/Minyus/pipelinex/tree/f35c524ec9c50751ee27d9a42d98317e16f1c544 |
SimpleClampMinModel | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleClampMinModel(torch.nn.Module):
def __init__(self, min):
super(SimpleClampMinModel, self).__init__()
self.min = min
def forward(self, input):
return torch.clamp_min(input, self.min)
def get_inputs():
re... | 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.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.... | YaronBenAtar/glow | SimpleClampMinModel | false | 14,654 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
WDV52LayerNormalization | # 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 numbers
impo... | Lollipop321/weight-distillation | WDV52LayerNormalization | false | 5,563 | [
"BSD-3-Clause"
] | 1 | cfc76ec58e3e88094dde1825287b2968f9718431 | https://github.com/Lollipop321/weight-distillation/tree/cfc76ec58e3e88094dde1825287b2968f9718431 |
MLP | import torch
import torch.nn as nn
import torch.nn.functional as F
class MLP(nn.Module):
def __init__(self):
super(MLP, self).__init__()
self.fc1 = nn.Linear(28 * 28, 512)
self.fc2 = nn.Linear(512, 256)
self.fc3 = nn.Linear(256, 64)
self.fc4 = nn.Linear(64, 10)
sel... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | lynfi/Classification | MLP | false | 10,451 | [
"MIT"
] | 0 | 691731629c6577432c8c9eee70b67911011a07b7 | https://github.com/lynfi/Classification/tree/691731629c6577432c8c9eee70b67911011a07b7 |
TFSamepaddingLayer | # 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.multiprocessing
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
e... | essential2189/Cell-Based-Model | TFSamepaddingLayer | false | 3,474 | [
"MIT"
] | 0 | f01c3fcb45e69baa4dc8216b8b5a092f56cfa38e | https://github.com/essential2189/Cell-Based-Model/tree/f01c3fcb45e69baa4dc8216b8b5a092f56cfa38e |
Copy | import torch
from torch import nn
class Copy(nn.Module):
def __init__(self, hidden_size, copy_weight=1.0):
super().__init__()
self.Wcopy = nn.Linear(hidden_size, hidden_size)
self.copy_weight = copy_weight
def forward(self, enc_out_hs, dec_hs):
"""
get unnormalized co... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | ChansongJo/DAMD | Copy | false | 7,863 | [
"Apache-2.0"
] | 39 | 9b0456d7e590fb5de77ec81e967e8010487eeb56 | https://github.com/ChansongJo/DAMD/tree/9b0456d7e590fb5de77ec81e967e8010487eeb56 |
Pow | import torch
class Pow(torch.nn.Module):
def __init__(self):
super(Pow, 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
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | PogChamper/torch2trt | Pow | false | 14,235 | [
"MIT"
] | 3,363 | 43b12627ec0de4d212efb6d02b07570205085ccc | https://github.com/PogChamper/torch2trt/tree/43b12627ec0de4d212efb6d02b07570205085ccc |
AlphaEntropy | import torch
import torch.nn as nn
class AlphaEntropy(nn.Module):
def __init__(self):
super().__init__()
self.v_loss = nn.MSELoss()
def forward(self, props, v, pi, reward):
v_loss = self.v_loss(v, reward)
p_loss = -torch.mean(torch.sum(props * pi, 1))
return p_loss + ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | Gromy1211/torch-light | AlphaEntropy | false | 11,455 | [
"MIT"
] | 0 | c7d7a9bc5ab1eab03d800a27d9325859516f01e6 | https://github.com/Gromy1211/torch-light/tree/c7d7a9bc5ab1eab03d800a27d9325859516f01e6 |
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