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 |
|---|---|---|---|---|---|---|---|---|---|---|
PPMConcat | # 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._C
import torch.serialization
from torch import optim as optim
assert_size_stride = torch._C._dynamo.guar... | Atten4Vis/DemystifyLocalViT | PPMConcat | false | 13,376 | [
"MIT"
] | 64 | 2e2327caec6d56ae2c8aa861b32bb62f3cdb786e | https://github.com/Atten4Vis/DemystifyLocalViT/tree/2e2327caec6d56ae2c8aa861b32bb62f3cdb786e |
PopArt | # 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 numpy as np
import to... | rainwangphy/TRPO-in-MARL | PopArt | false | 4,170 | [
"MIT"
] | 0 | 22229abba417708922ecf6455c1c5180dbe80391 | https://github.com/rainwangphy/TRPO-in-MARL/tree/22229abba417708922ecf6455c1c5180dbe80391 |
Critic | import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
from math import *
def hidden_init(layer):
fan_in = layer.weight.data.size()[0]
lim = 1.0 / np.sqrt(fan_in)
return -lim, lim
class Critic(nn.Module):
"""Critic (Value) Model."""
def __init__(self, state_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
import numpy as np
import torch.nn as nn
from math import *
assert_size_stride =... | albimc/deep-reinforcement-learning | Critic | false | 1,410 | [
"MIT"
] | 0 | e11a6c9d4c8991cf229e686b645ae22ec4cff4f5 | https://github.com/albimc/deep-reinforcement-learning/tree/e11a6c9d4c8991cf229e686b645ae22ec4cff4f5 |
GlobalAttention | # 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.... | MaxatTezekbayev/OpenNMT-py-lexical | GlobalAttention | false | 5,593 | [
"MIT"
] | 1 | 44182999b863fc4074d67e0281c5bdab19abddfe | https://github.com/MaxatTezekbayev/OpenNMT-py-lexical/tree/44182999b863fc4074d67e0281c5bdab19abddfe |
CMlp | import torch
import torch.nn as nn
import torch._C
import torch.serialization
class CMlp(nn.Module):
def __init__(self, in_features, hidden_features=None, out_features=None,
act_layer=nn.GELU, drop=0.0):
super().__init__()
out_features = out_features or in_features
hidden_features... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | pprp/mmsegmentation | CMlp | false | 12,905 | [
"Apache-2.0"
] | 0 | 5d615401358dea2d6527a033bef505a9c7e0f034 | https://github.com/pprp/mmsegmentation/tree/5d615401358dea2d6527a033bef505a9c7e0f034 |
SpatialAttn | import torch
import torch.nn as nn
class SpatialAttn(nn.Module):
"""Spatial Attention Layer"""
def __init__(self):
super(SpatialAttn, self).__init__()
def forward(self, x):
x = x.mean(1, keepdim=True)
h = x.size(2)
w = x.size(3)
x = x.view(x.size(0), -1)
z... | 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... | wangminjie920705/Part-reid | SpatialAttn | false | 4,520 | [
"MIT"
] | 0 | 34a1e968a2eab692ba810332f309e82b441793f6 | https://github.com/wangminjie920705/Part-reid/tree/34a1e968a2eab692ba810332f309e82b441793f6 |
SuperPointNet | # 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.... | Dai-z/pytorch-superpoint | SuperPointNet | false | 13,572 | [
"MIT"
] | 390 | 90e71045238fdcce13f9f0d02bdd0e1126145a10 | https://github.com/Dai-z/pytorch-superpoint/tree/90e71045238fdcce13f9f0d02bdd0e1126145a10 |
PredLayer | import torch
import torch.nn as nn
def module_test_print(var_input, var_inmed, var_ouput):
for var in (var_input, var_inmed, var_ouput):
None
for key, value in var.items():
None
None
class PredLayer(nn.Module):
def __init__(self, module_test=False):
super(Pre... | 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... | xlx0010/HGNN | PredLayer | false | 4,583 | [
"MIT"
] | 0 | 219352405db021c1f435f3aa55961adcf2a6df19 | https://github.com/xlx0010/HGNN/tree/219352405db021c1f435f3aa55961adcf2a6df19 |
ConvNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn
import torch.utils.data.distributed
import torch.nn as nn
import... | lipovsek/bagua | ConvNet | false | 12,717 | [
"MIT"
] | 0 | d8b03333ab6cf3745279311b9da76e99d5c2c00a | https://github.com/lipovsek/bagua/tree/d8b03333ab6cf3745279311b9da76e99d5c2c00a |
Conv2dZeros | # 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.... | Catherine0505/mar-scf-flow | Conv2dZeros | false | 17,086 | [
"Apache-2.0"
] | 10 | aa7c3564cb9f2967c5e580a633516dba1b597f98 | https://github.com/Catherine0505/mar-scf-flow/tree/aa7c3564cb9f2967c5e580a633516dba1b597f98 |
AvgPool2d | # 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.nn import Module
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._em... | NiWaRe/PySyft | AvgPool2d | false | 11,746 | [
"Apache-2.0"
] | 0 | b5abe66ea949d60be14a08d2e4e32e9587c7bf5c | https://github.com/NiWaRe/PySyft/tree/b5abe66ea949d60be14a08d2e4e32e9587c7bf5c |
PositionwiseFeedForward | import torch
import torch.nn as nn
import torch.nn.functional as F
class PositionwiseFeedForward(nn.Module):
""" A two-feed-forward-layer module """
def __init__(self, d_in, d_hid, dropout=0.1):
super().__init__()
self.w_1 = nn.Linear(d_in, d_hid)
self.w_2 = nn.Linear(d_hid, d_in)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | PINE4PPLE/transformer-lm | PositionwiseFeedForward | false | 9,434 | [
"MIT"
] | 0 | da76a4afd29d1fd023ba866ccc21a49901ad46f2 | https://github.com/PINE4PPLE/transformer-lm/tree/da76a4afd29d1fd023ba866ccc21a49901ad46f2 |
LayerNormalization | # 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_... | lz-chen/ner-bert | LayerNormalization | false | 7,147 | [
"MIT"
] | 1 | 86e73c1e7124a4fb6ee65d42b72333573841fe5b | https://github.com/lz-chen/ner-bert/tree/86e73c1e7124a4fb6ee65d42b72333573841fe5b |
ConcatELU | import torch
import torch.nn as nn
import torch.nn.functional as F
class ConcatELU(nn.Module):
"""Activation function that applies ELU in both direction (inverted and plain).
Allows non-linearity while providing strong gradients for any input (important for final convolution)
"""
def forward(self, x... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | ashutoshml/lightning-tutorials | ConcatELU | false | 6,237 | [
"Apache-2.0"
] | 1 | 898b8b6f9852c0b80f034a3187bc1cd34dd521ce | https://github.com/ashutoshml/lightning-tutorials/tree/898b8b6f9852c0b80f034a3187bc1cd34dd521ce |
InnerProductLayer | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from sklearn.metrics import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = tor... | Fanxingye/DeepRS | InnerProductLayer | false | 14,024 | [
"Apache-2.0"
] | 1,770 | 06b98cf2cb2781656805eafc577fbd088f37d17d | https://github.com/Fanxingye/DeepRS/tree/06b98cf2cb2781656805eafc577fbd088f37d17d |
Attn | import torch
import torch.nn as nn
import torch.nn.functional as F
class Attn(nn.Module):
def __init__(self, hidden_size):
super().__init__()
self.hidden_size = hidden_size
self.attn = nn.Linear(self.hidden_size * 2, hidden_size)
self.v = nn.Linear(hidden_size, 1, bias=False)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Verylovenlp/MinTL-SKKU | Attn | false | 14,566 | [
"MIT"
] | 60 | 15b5cb870c7d6dcd0f5d895aac2806539cc5101f | https://github.com/Verylovenlp/MinTL-SKKU/tree/15b5cb870c7d6dcd0f5d895aac2806539cc5101f |
depthwise_separable_conv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | mirayyuce/Neural-Architecture-Search | depthwise_separable_conv | false | 7,238 | [
"BSD-3-Clause"
] | 1 | e294816c85200f4301376c8b355634c6cca81816 | https://github.com/mirayyuce/Neural-Architecture-Search/tree/e294816c85200f4301376c8b355634c6cca81816 |
sum_squared_error | # 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.nn.modules.loss import _Loss
assert_size_stride = torch._C._dynamo.guards.asse... | ORNL/AADL | sum_squared_error | false | 17,760 | [
"BSD-3-Clause"
] | 6 | 8a509676d0a0a78f1f334a3dc93e92721cfcfe90 | https://github.com/ORNL/AADL/tree/8a509676d0a0a78f1f334a3dc93e92721cfcfe90 |
CapsuleLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class MarginLoss(nn.Module):
def __init__(self, size_average=False, loss_lambda=0.5):
"""
Margin loss for digit existence
Eq. (4): L_k = T_k * max(0, m+ - ||v_k||)^2 + lambda * (1 - T_k) * max(0, ||v_k|| - m-)^2
Args:
size_ave... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.nn.functional as F
assert_size_stride = torch._C._dyna... | jjcao/capsule-network | CapsuleLoss | false | 15,711 | [
"MIT"
] | 171 | 0c2d9976b25d64720a90d3db71e5869d2592ab71 | https://github.com/jjcao/capsule-network/tree/0c2d9976b25d64720a90d3db71e5869d2592ab71 |
CmapPafHeadAttention | # 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.utils.... | ajsampathk/trt_pose | CmapPafHeadAttention | false | 18,263 | [
"MIT"
] | 7 | 592e038cacaf43b6a502b759a035a4e7cae9db9e | https://github.com/ajsampathk/trt_pose/tree/592e038cacaf43b6a502b759a035a4e7cae9db9e |
LossAnneal | # 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... | xenbaloch/efficientderain | LossAnneal | false | 16,745 | [
"MIT"
] | 109 | d5646815fd14a5a03c859102ecd2f298db7e53be | https://github.com/xenbaloch/efficientderain/tree/d5646815fd14a5a03c859102ecd2f298db7e53be |
FPNSegHead | # 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 ... | hoangnguyen11291/Kuril-DeBlur | FPNSegHead | false | 12,506 | [
"BSD-3-Clause"
] | 0 | 7c36fc50780e3dda82eb42443d5623d34e6b02a6 | https://github.com/hoangnguyen11291/Kuril-DeBlur/tree/7c36fc50780e3dda82eb42443d5623d34e6b02a6 |
BCL | # 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
from torch import nn
assert_size_stride = torch._C._... | cuicaihao/STANet | BCL | false | 15,089 | [
"BSD-2-Clause"
] | 220 | 4c644e2a65bc9516f1d97b29b12ca864638c0c7e | https://github.com/cuicaihao/STANet/tree/4c644e2a65bc9516f1d97b29b12ca864638c0c7e |
ncm_output | # 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_... | RafLaf/easy | ncm_output | false | 8,687 | [
"MIT"
] | 25 | 3e3603aef7dfb1cf469820330d695b93ba76dfd4 | https://github.com/RafLaf/easy/tree/3e3603aef7dfb1cf469820330d695b93ba76dfd4 |
IdentityMessage | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_... | MINATILO/pytroch-geometric | IdentityMessage | false | 9,392 | [
"MIT"
] | 0 | 706aba3b4a6477a83a1fb73eb3cf0ee9661b70e4 | https://github.com/MINATILO/pytroch-geometric/tree/706aba3b4a6477a83a1fb73eb3cf0ee9661b70e4 |
SALayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.model_zoo
assert_size_stride = torch._C... | iariav/EDSR-PyTorch | SALayer | false | 3,661 | [
"MIT"
] | 0 | c709b3d43adb6c2457cf87c37c1f34a7bcfc48bb | https://github.com/iariav/EDSR-PyTorch/tree/c709b3d43adb6c2457cf87c37c1f34a7bcfc48bb |
DiceLoss | import torch
from torch import nn
from torch.autograd import Variable
def compute_per_channel_dice(input, target, epsilon=1e-05, ignore_index=
None, weight=None):
assert input.size() == target.size(
), "'input' and 'target' must have the same shape"
if ignore_index is not None:
mask = targ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | WdBlink/AugMix-3DOCUNet-Brats2019 | DiceLoss | false | 5,958 | [
"MIT"
] | 1 | 125c6c8682b51a550eeac9173d13d0a211576abc | https://github.com/WdBlink/AugMix-3DOCUNet-Brats2019/tree/125c6c8682b51a550eeac9173d13d0a211576abc |
ReflectPad2d | # 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... | jaredaevans/UltrafastNST | ReflectPad2d | false | 6,930 | [
"MIT"
] | 1 | 6671c6b618ce6bb4920b15f782be962e484a5423 | https://github.com/jaredaevans/UltrafastNST/tree/6671c6b618ce6bb4920b15f782be962e484a5423 |
DownsampleA | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data.distributed
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda... | HKBU-HPML/gtopkssgd | DownsampleA | false | 8,190 | [
"Apache-2.0"
] | 33 | 6f57343f3749939b0345d36fcb2c24470942aefd | https://github.com/HKBU-HPML/gtopkssgd/tree/6f57343f3749939b0345d36fcb2c24470942aefd |
MSE_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... | BennyZhang-Codes/LDCT-denoising-with-DL-Methods-and-Dicom-Viewer-by-Benny | MSE_Loss | false | 16,994 | [
"MIT"
] | 7 | 07e3dc1e3c6dcdea314b2a9e3cf9ac1036cf5eb6 | https://github.com/BennyZhang-Codes/LDCT-denoising-with-DL-Methods-and-Dicom-Viewer-by-Benny/tree/07e3dc1e3c6dcdea314b2a9e3cf9ac1036cf5eb6 |
StyleResidual | import torch
from torch import nn
import torch.utils.data
import torch.optim
class StyleResidual(nn.Module):
"""Styling."""
def __init__(self, d_channel: 'int', d_style: 'int', kernel_size: 'int'=1):
super().__init__()
self.rs = nn.Conv1d(in_channels=d_style, out_channels=d_channel,
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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... | taufique74/nemotest | StyleResidual | false | 4,406 | [
"Apache-2.0"
] | 0 | 812f201913cb9922bedc1b225dff844ffc765bf1 | https://github.com/taufique74/nemotest/tree/812f201913cb9922bedc1b225dff844ffc765bf1 |
NeuralNet | import torch
import torch.nn as nn
class NeuralNet(nn.Module):
def __init__(self, input_size, hidden_size, num_classes, p=0.5):
super(NeuralNet, self).__init__()
self.fc1 = nn.Linear(input_size, hidden_size)
self.fc2 = nn.Linear(hidden_size, num_classes)
self.dropout = nn.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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | AWebZen/FunctionalPrediction5000species | NeuralNet | false | 4,779 | [
"MIT"
] | 1 | 6d351da7f85ff9d23f5465c9bd6ea47eccec9771 | https://github.com/AWebZen/FunctionalPrediction5000species/tree/6d351da7f85ff9d23f5465c9bd6ea47eccec9771 |
ShakeResNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import math
import torch.nn a... | DensoITLab/TeachAugment | ShakeResNet | false | 7,992 | [
"BSD-2-Clause"
] | 20 | 66ec099a0afab99e18531c5437182cfe17dc30c8 | https://github.com/DensoITLab/TeachAugment/tree/66ec099a0afab99e18531c5437182cfe17dc30c8 |
AttnLayer | # 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.... | WiseDoge/Text-Classification-PyTorch | AttnLayer | false | 18,070 | [
"MIT"
] | 6 | 9371eeed6bd7ecf1d529c8f2a6c997fcde67a559 | https://github.com/WiseDoge/Text-Classification-PyTorch/tree/9371eeed6bd7ecf1d529c8f2a6c997fcde67a559 |
CompActor | import torch
class CompActor(torch.nn.Module):
def __init__(self, state_dim: 'int', hidden_dim: 'int', action_dim: 'int'):
super(CompActor, self).__init__()
self.fc1 = torch.nn.Linear(state_dim, hidden_dim)
self.fc2 = torch.nn.Linear(hidden_dim, hidden_dim)
self.fc3 = torch.nn.Lin... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | andreabradpitto/turtlex | CompActor | false | 1,433 | [
"Apache-2.0"
] | 0 | 37a2315450f896d10dcb9ebc8968207e476dcf82 | https://github.com/andreabradpitto/turtlex/tree/37a2315450f896d10dcb9ebc8968207e476dcf82 |
ResizeCat | # 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... | GunjanChourasia/WS_DAN_PyTorch | ResizeCat | false | 2,316 | [
"MIT"
] | 0 | 6c12a1b5b0b8980e3b69d44474e0b5edb455570c | https://github.com/GunjanChourasia/WS_DAN_PyTorch/tree/6c12a1b5b0b8980e3b69d44474e0b5edb455570c |
SummaryNet | import torch
import torch.nn as nn
import torch.nn.functional as F
class SummaryNet(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv1d(in_channels=1, out_channels=6, kernel_size=5,
padding=2)
self.pool = nn.MaxPool1d(kernel_size=10, stride=10)
se... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | Wrede/BNN-LFI | SummaryNet | false | 2,960 | [
"MIT"
] | 0 | 8c5094f01c1eef286bdd84613c7259d534d2eb7e | https://github.com/Wrede/BNN-LFI/tree/8c5094f01c1eef286bdd84613c7259d534d2eb7e |
InvertibleLinearFlow | # 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 numpy as np
import torch.nn as nn
from typing import Tuple
assert_size_st... | Tiamat-Tech/VAENAR-TTS | InvertibleLinearFlow | false | 14,493 | [
"MIT"
] | 62 | 69b6b5be1ab5168cfd3c6ab902075638e76a3b8d | https://github.com/Tiamat-Tech/VAENAR-TTS/tree/69b6b5be1ab5168cfd3c6ab902075638e76a3b8d |
AtteMatchLay | # 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.nn as nn
assert... | shinoyuki222/torch-light | AtteMatchLay | false | 16,415 | [
"MIT"
] | 310 | 4799805d9bcae82a9f12a574dcf9fdd838c92ee9 | https://github.com/shinoyuki222/torch-light/tree/4799805d9bcae82a9f12a574dcf9fdd838c92ee9 |
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.... | johnpaulbin/glide-text2im | MultiheadAttention | false | 12,638 | [
"MIT"
] | 0 | 4897050c4c540316dfb1ec7e6ff95698bcb20487 | https://github.com/johnpaulbin/glide-text2im/tree/4897050c4c540316dfb1ec7e6ff95698bcb20487 |
ResidualBlock | 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 import triton_helpers
from torch._inductor.runtime.... | Bartolo1024/ignite | ResidualBlock | false | 4,905 | [
"BSD-3-Clause"
] | 1 | b087fef0bc5f97cda415c1c56f1cd589383c54be | https://github.com/Bartolo1024/ignite/tree/b087fef0bc5f97cda415c1c56f1cd589383c54be |
Attention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | santhnm2/TASO | Attention | false | 10,735 | [
"Apache-2.0"
] | 0 | f8025dda00922e4313ba6efbca6573421d95cbba | https://github.com/santhnm2/TASO/tree/f8025dda00922e4313ba6efbca6573421d95cbba |
GDL | import torch
import torch.nn as nn
import torch._C
import torch.serialization
def get_tp_fp_fn_tn(net_output, gt, axes=None, mask=None, square=False):
"""
net_output must be (b, c, x, y(, z)))
gt must be a label map (shape (b, 1, x, y(, z)) OR shape (b, x, y(, z))) or one hot encoding (b, c, x, y(, z))
... | 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._C
import torch.serialization
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strid... | dkswxd/Swin-Transformer-Semantic-Segmentation | GDL | false | 1,858 | [
"Apache-2.0"
] | 0 | 6af19736e5492a01d8952d4ee86a6d59b21c2ae1 | https://github.com/dkswxd/Swin-Transformer-Semantic-Segmentation/tree/6af19736e5492a01d8952d4ee86a6d59b21c2ae1 |
SpatialRescaler | # 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 functools import partial
import torch.nn as nn
assert_size_stride = torch._C._dynamo... | samedii/latent-diffusion | SpatialRescaler | false | 16,357 | [
"MIT"
] | 563 | f13bf9bf463d95b5a16aeadd2b02abde31f769f8 | https://github.com/samedii/latent-diffusion/tree/f13bf9bf463d95b5a16aeadd2b02abde31f769f8 |
_BoundaryRefineModule | import torch
import torch.nn as nn
from torch.optim.lr_scheduler import *
class _BoundaryRefineModule(nn.Module):
def __init__(self, dim):
super(_BoundaryRefineModule, self).__init__()
self.relu = nn.ReLU(inplace=True)
self.conv1 = nn.Conv2d(dim, dim, kernel_size=3, padding=1)
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
from to... | Rocketbase-AI/rockets-mobilepose | _BoundaryRefineModule | false | 5,775 | [
"MIT"
] | 1 | be7273dff7fcf7d1023f431f4b63ac8d82978182 | https://github.com/Rocketbase-AI/rockets-mobilepose/tree/be7273dff7fcf7d1023f431f4b63ac8d82978182 |
SelfAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
def mask_(matrices, maskval=0.0, mask_diagonal=True):
_b, h, w = matrices.size()
indices = torch.triu_indices(h, w, offset=0 if mask_diagonal else 1)
matrices[:, indices[0], indices[1]] = maskval
class SelfAttention(nn.Module):
def ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | ouyangshixiong/UPDeT | SelfAttention | false | 16,224 | [
"MIT"
] | 90 | e6010ff8a8a3ce064900f3f040a9a34218c97e0e | https://github.com/ouyangshixiong/UPDeT/tree/e6010ff8a8a3ce064900f3f040a9a34218c97e0e |
IIDIsotropicGaussianUVLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import math... | BUPT-PRIV/detectron2 | IIDIsotropicGaussianUVLoss | false | 11,238 | [
"Apache-2.0"
] | 0 | 3163664cd5f43d50ea1966f410dc82410b9ccbf4 | https://github.com/BUPT-PRIV/detectron2/tree/3163664cd5f43d50ea1966f410dc82410b9ccbf4 |
FusedDownsample | import torch
from torch import nn
from torch.nn import functional as F
from math import sqrt
class FusedDownsample(nn.Module):
def __init__(self, in_channel, out_channel, kernel_size, padding=0):
super().__init__()
weight = torch.randn(out_channel, in_channel, kernel_size, kernel_size)
bi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
from math import sqrt
assert_size_stride = torch._C._dynamo... | celdeldel/style_conditionnal_gan | FusedDownsample | false | 1,654 | [
"MIT"
] | 0 | 3a4623560af1e12d46e2f9ffa9726c29df9d5680 | https://github.com/celdeldel/style_conditionnal_gan/tree/3a4623560af1e12d46e2f9ffa9726c29df9d5680 |
IIDIsotropicGaussianUVLoss | import math
import torch
import torch.utils.data
from torch import nn
import torch.nn.functional as F
class IIDIsotropicGaussianUVLoss(nn.Module):
"""
Loss for the case of iid residuals with isotropic covariance:
$Sigma_i = sigma_i^2 I$
The loss (negative log likelihood) is then:
$1/2 sum_{i=1}^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 libdevice, math as tl_math
import math... | JHMeusener/detectron2-ResNeSt | IIDIsotropicGaussianUVLoss | false | 581 | [
"Apache-2.0"
] | 0 | 6abab6fb9496a528f6aa2d4e1e27f3e7ceb42685 | https://github.com/JHMeusener/detectron2-ResNeSt/tree/6abab6fb9496a528f6aa2d4e1e27f3e7ceb42685 |
MultiHeadAttention | import torch
import torch.nn as nn
class MultiHeadAttention(nn.Module):
def __init__(self, hidden_state, num_heads=1):
super().__init__()
self.q_linear = nn.Linear(hidden_state, hidden_state)
self.v_linear = nn.Linear(hidden_state, hidden_state)
self.k_linear = nn.Linear(hidden_st... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | qinyiwei/MuTual | MultiHeadAttention | false | 4,157 | [
"MIT"
] | 0 | 3bdd13c1388d6136b8944666dfd434870760cc93 | https://github.com/qinyiwei/MuTual/tree/3bdd13c1388d6136b8944666dfd434870760cc93 |
FirstOctaveConv | # 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.utils.data.distribut... | SSusantAchary/OctaveConv_pytorch | FirstOctaveConv | false | 14,362 | [
"MIT"
] | 633 | 079f7da29d55c2eeed8985d33f0b2f765d7a469e | https://github.com/SSusantAchary/OctaveConv_pytorch/tree/079f7da29d55c2eeed8985d33f0b2f765d7a469e |
Policy | import torch
import numpy as np
from torch import Tensor
import torch.nn.functional as F
from torch import nn
from torch.nn import Linear
from torch.autograd import Variable
from torch.distributions import Categorical
class Policy(nn.Module):
def __init__(self, in_sz, hidden_sz, out_sz):
super(Policy, 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.... | mabirck/CS294-DeepRL | Policy | false | 12,753 | [
"MIT"
] | 0 | 0445808fa62ae8a22b13c598c998e3aea7632e79 | https://github.com/mabirck/CS294-DeepRL/tree/0445808fa62ae8a22b13c598c998e3aea7632e79 |
SEModule | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn import Module
f... | DeepVoodooFX/pixel2style2pixel | SEModule | false | 11,343 | [
"Apache-2.0",
"BSD-2-Clause",
"MIT"
] | 0 | 0254c32400d55f7e400ead15b02ad6a992ba1e21 | https://github.com/DeepVoodooFX/pixel2style2pixel/tree/0254c32400d55f7e400ead15b02ad6a992ba1e21 |
ResidualDenseBlock | import torch
import torch.utils.data
from torch.utils import data as data
from torch import nn as nn
from torch.nn import init as init
from torch.nn.modules.batchnorm import _BatchNorm
from torchvision.models import vgg as vgg
from torch import autograd as autograd
@torch.no_grad()
def default_init_weights(module_lis... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
from torch.utils import data as data
from torch import n... | WoojunePark/BasicSR | ResidualDenseBlock | false | 18,175 | [
"Apache-2.0"
] | 9 | e0910b022b924bb913045fc412a5470dc2242cf0 | https://github.com/WoojunePark/BasicSR/tree/e0910b022b924bb913045fc412a5470dc2242cf0 |
WeightedCE | # 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
... | Shray64/pytorch_connectomics | WeightedCE | false | 1,070 | [
"MIT"
] | 0 | d6c814f11ac2f8418ede5ae220a93016f50214fc | https://github.com/Shray64/pytorch_connectomics/tree/d6c814f11ac2f8418ede5ae220a93016f50214fc |
ChanNorm | import torch
from torch import nn
class ChanNorm(nn.Module):
def __init__(self, dim, eps=1e-05):
super().__init__()
self.eps = eps
self.g = nn.Parameter(torch.ones(1, dim, 1, 1))
self.b = nn.Parameter(torch.zeros(1, dim, 1, 1))
def forward(self, x):
var = torch.var(x,... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Rexiome/lightweight-gan | ChanNorm | false | 2,745 | [
"MIT"
] | 0 | 4e5c18046fc105129c33995e0bffeb5f14963f4c | https://github.com/Rexiome/lightweight-gan/tree/4e5c18046fc105129c33995e0bffeb5f14963f4c |
LinearTextualHead | import torch
from torch import nn
from typing import Optional
class TextualHead(nn.Module):
"""
Base class for all textual heads. All child classes can simply inherit
from :class:`~torch.nn.Module`, however this is kept here for uniform
type annotations.
Args:
visual_feature_size: Size (n... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | GeorgeBatch/arch-pre-training | LinearTextualHead | false | 482 | [
"MIT"
] | 0 | 7ed75868689e9283d61d11360fdbf4e77d4ebd2e | https://github.com/GeorgeBatch/arch-pre-training/tree/7ed75868689e9283d61d11360fdbf4e77d4ebd2e |
ScalarMix | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | KoichiYasuoka/SuPar | ScalarMix | false | 11,617 | [
"MIT"
] | 0 | 9bcf10fb946cae75b6a311d4cd19bec5bb1a9487 | https://github.com/KoichiYasuoka/SuPar/tree/9bcf10fb946cae75b6a311d4cd19bec5bb1a9487 |
ComplexCnnQAHead | import torch
from torch import nn
class ComplexCnnQAHead(nn.Module):
def __init__(self, input_size):
super().__init__()
self.relu = nn.ReLU()
self.conv_1 = nn.Conv1d(in_channels=input_size, out_channels=256,
kernel_size=1, padding=0)
self.conv_3 = nn.Conv1d(in_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._inductor.runtime import triton_helpers
from torch import nn
assert_s... | park-sungmoo/odqa_baseline_code | ComplexCnnQAHead | false | 16,228 | [
"Apache-2.0"
] | 67 | 45954be766e5f987bef18e5b8a2e47f1508742cd | https://github.com/park-sungmoo/odqa_baseline_code/tree/45954be766e5f987bef18e5b8a2e47f1508742cd |
NetWidth | import torch
import torch.nn as nn
import torch.utils
import torch.nn.functional as F
class NetWidth(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(3, 32, kernel_size=3, padding=1)
self.conv2 = nn.Conv2d(32, 16, kernel_size=3, padding=1)
self.fc1 = nn.Li... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | dustasa/senior_software_HW | NetWidth | false | 3,451 | [
"Apache-2.0"
] | 0 | 767d1d7bbd5e7d7414c17fa14b92b942e53d84ed | https://github.com/dustasa/senior_software_HW/tree/767d1d7bbd5e7d7414c17fa14b92b942e53d84ed |
AlignQuestionEmbedding | # 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.... | gustavhartz/legal-contract-elements | AlignQuestionEmbedding | false | 6,758 | [
"MIT"
] | 1 | 7a1e1f0024f9d336c7166f51b4325acf03db86a2 | https://github.com/gustavhartz/legal-contract-elements/tree/7a1e1f0024f9d336c7166f51b4325acf03db86a2 |
LinearAttention | from torch.nn import Module
import torch
def elu_feature_map(x):
return torch.nn.functional.elu(x) + 1
class LinearAttention(Module):
def __init__(self, eps=1e-06):
super().__init__()
self.feature_map = elu_feature_map
self.eps = eps
def forward(self, queries, keys, values, q_m... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.nn impor... | francescodisalvo05/LoFTR | LinearAttention | false | 12,406 | [
"Apache-2.0"
] | 0 | 66372ebbe1ea97d57fe6cb8b5acf5cd92a87ef8d | https://github.com/francescodisalvo05/LoFTR/tree/66372ebbe1ea97d57fe6cb8b5acf5cd92a87ef8d |
KLDivergence | # 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 as th
ass... | v-a-s-a/diffvg | KLDivergence | false | 4,470 | [
"Apache-2.0"
] | 0 | 3685f3d47a5a4e5c76c68643ebf383f809ba59ed | https://github.com/v-a-s-a/diffvg/tree/3685f3d47a5a4e5c76c68643ebf383f809ba59ed |
Mix | import torch
import torch.nn as nn
class Mix(nn.Module):
def __init__(self, m=-0.8):
super(Mix, self).__init__()
w = torch.nn.Parameter(torch.FloatTensor([m]), requires_grad=True)
w = torch.nn.Parameter(w, requires_grad=True)
self.w = w
self.mix_block = nn.Sigmoid()
d... | 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... | ShenZheng2000/Syn2Real-Pytorch | Mix | false | 5,815 | [
"MIT"
] | 1 | 214c800914e2bcd57d4ca74a4c8476a11e1b5905 | https://github.com/ShenZheng2000/Syn2Real-Pytorch/tree/214c800914e2bcd57d4ca74a4c8476a11e1b5905 |
MatchingTensor | # 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.... | Ambitioner-c/MatchZoo-py | MatchingTensor | false | 13,273 | [
"Apache-2.0"
] | 468 | bb088edce8e01c2c2326ca1a8ac647f0d23f088d | https://github.com/Ambitioner-c/MatchZoo-py/tree/bb088edce8e01c2c2326ca1a8ac647f0d23f088d |
patch_extractor | # 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... | johertrich/Wasserstein_Patch_Prior | patch_extractor | false | 6,968 | [
"MIT"
] | 1 | 70877a6f1031e51b7868984b97027951d1d190d3 | https://github.com/johertrich/Wasserstein_Patch_Prior/tree/70877a6f1031e51b7868984b97027951d1d190d3 |
SpatialGather_Module | # 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.... | ModelTC/EOD | SpatialGather_Module | false | 14,064 | [
"Apache-2.0"
] | 196 | 164bff80486e9ae6a095a97667b365c46ceabd86 | https://github.com/ModelTC/EOD/tree/164bff80486e9ae6a095a97667b365c46ceabd86 |
ScalarScaleBias | # 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
from torch.nn.parameter import Parameter
from torch.nn import init
assert_size_stride = torch._C._dynamo.guards.assert... | Ali-Homsi/githubrepo | ScalarScaleBias | false | 40 | [
"Apache-2.0"
] | 0 | 7163f110193142a97ec05f76ff7d897c6cedb915 | https://github.com/Ali-Homsi/githubrepo/tree/7163f110193142a97ec05f76ff7d897c6cedb915 |
TVLoss | # 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... | hjk0918/style-transfer-pytorch | TVLoss | false | 3,590 | [
"MIT"
] | 0 | acbc054c734aa9c723a3a9bb36e33afb9bd7833b | https://github.com/hjk0918/style-transfer-pytorch/tree/acbc054c734aa9c723a3a9bb36e33afb9bd7833b |
WNConv2d | # 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... | eric11220/vq-vae-2-pytorch | WNConv2d | false | 12,369 | [
"MIT"
] | 0 | ac455ec8873428e16a361d49bf1dda30472ece13 | https://github.com/eric11220/vq-vae-2-pytorch/tree/ac455ec8873428e16a361d49bf1dda30472ece13 |
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_... | AlexTaguchi/ml-tutorial | Net | false | 11,161 | [
"MIT"
] | 0 | 5b2693cd1648a72e9bcd6cee1223eedadba4b837 | https://github.com/AlexTaguchi/ml-tutorial/tree/5b2693cd1648a72e9bcd6cee1223eedadba4b837 |
DistanceMatrixLoss | import torch
import torch.nn as nn
class DistanceMatrixLoss(nn.Module):
def __init__(self):
super().__init__()
def forward(self, scores, labels, mask):
sq_lengths = mask.view(mask.size(0), -1).sum(1)
l1_diff = (mask * torch.abs(scores - labels)).view(labels.size(0), -1
).... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | daemon/vizbert | DistanceMatrixLoss | false | 1,773 | [
"MIT"
] | 0 | e40b7d1529f8857050313f8d87ff03b1b7226c9e | https://github.com/daemon/vizbert/tree/e40b7d1529f8857050313f8d87ff03b1b7226c9e |
AppendDim | import torch
from torch import nn
class AppendDim(nn.Module):
"""
Append a new dim to states with size out_dim
"""
def __init__(self, out_dim=1):
super().__init__()
self.out_dim = out_dim
def forward(self, states, **kwargs):
x = states.unsqueeze(len(states.size()))
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | C-SUNSHINE/TOQ-Nets-PyTorch-Release | AppendDim | false | 17,116 | [
"MIT"
] | 6 | 05e06bf633fb3c6b610dda9a5126ecd7af1db02f | https://github.com/C-SUNSHINE/TOQ-Nets-PyTorch-Release/tree/05e06bf633fb3c6b610dda9a5126ecd7af1db02f |
BasicConv2d | # 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_... | K-ona/template | BasicConv2d | false | 2,447 | [
"Apache-2.0"
] | 0 | a9ea81695b8d7eb512ac7bd54c76f14c7dcb30c4 | https://github.com/K-ona/template/tree/a9ea81695b8d7eb512ac7bd54c76f14c7dcb30c4 |
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... | TheShadow29/MAttNet | MaxMarginCriterion | false | 11,926 | [
"MIT"
] | 0 | 2fe44667bc9254daef8be77bb4c896f10c2f665b | https://github.com/TheShadow29/MAttNet/tree/2fe44667bc9254daef8be77bb4c896f10c2f665b |
AffineConstantFlow | import torch
from torch import Tensor
from torch import nn
class FlowBlock(nn.Module):
"""
Abstract base class for any flow blocks.
"""
def __init__(self, dimension):
super(FlowBlock, self).__init__()
self.dimension = dimension
def forward(self, x: 'Tensor') ->(Tensor, 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
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import Tensor
from torch import nn
assert_size_stride = torch.... | lleonart1984/generative_modeling | AffineConstantFlow | false | 10,408 | [
"MIT"
] | 0 | d47c53d34b9eb704b6e8b2c334262b53fe7f4f32 | https://github.com/lleonart1984/generative_modeling/tree/d47c53d34b9eb704b6e8b2c334262b53fe7f4f32 |
Gaussian | # 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.utils.tensorboard
import torch.utils.data
assert_size_stride... | raimis/torchani | Gaussian | false | 7,628 | [
"MIT"
] | 1 | 19882c6e18174e08423706a536366f89029a740a | https://github.com/raimis/torchani/tree/19882c6e18174e08423706a536366f89029a740a |
MaxOut | # 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_... | aisolab/nlp_implementation | MaxOut | false | 14,773 | [
"MIT"
] | 181 | 21ea6e3f5737e7074bdd8dd190e5f5172f86f6bf | https://github.com/aisolab/nlp_implementation/tree/21ea6e3f5737e7074bdd8dd190e5f5172f86f6bf |
SmoothL1Loss | # 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 functools
impor... | AllenPeng0209/SaccadeNet | SmoothL1Loss | false | 7,651 | [
"Apache-2.0"
] | 30 | 0fce4266cbffc9a2c5f70335efa636da849ce70c | https://github.com/AllenPeng0209/SaccadeNet/tree/0fce4266cbffc9a2c5f70335efa636da849ce70c |
PolicyNetwork | # 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.... | NiccoloSacchi/rlcard | PolicyNetwork | false | 885 | [
"MIT"
] | 0 | 046129e8616b12e25652957869a94ab5fd838ae1 | https://github.com/NiccoloSacchi/rlcard/tree/046129e8616b12e25652957869a94ab5fd838ae1 |
GramMatrix | import torch
from torchvision.datasets import *
import torch.nn as nn
from torchvision.transforms import *
class GramMatrix(nn.Module):
""" Gram Matrix for a 4D convolutional featuremaps as a mini-batch
.. math::
\\mathcal{G} = \\sum_{h=1}^{H_i}\\sum_{w=1}^{W_i} \\mathcal{F}_{h,w}\\mathcal{F}_{h,w}^T... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torchvision.datasets import *
import torch.nn as nn
from torchvision.transf... | JJavierga/PyTorch-Encoding | GramMatrix | false | 9,470 | [
"MIT"
] | 0 | 207254b2a60276a31ffa24b76ae84df27c6ebf94 | https://github.com/JJavierga/PyTorch-Encoding/tree/207254b2a60276a31ffa24b76ae84df27c6ebf94 |
LocalConv2d | import torch
import torch.nn as nn
import torch.nn.functional as F
class LocalConv2d(nn.Module):
def __init__(self, num_rows, num_feats_in, num_feats_out, kernel=1,
padding=0):
super(LocalConv2d, self).__init__()
self.num_rows = num_rows
self.out_channels = num_feats_out
s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | AnuragSahu/M3D-RPN | LocalConv2d | false | 13,270 | [
"MIT"
] | 245 | 078ddfa0a7c48dc1d23e8da679997239ac62a72a | https://github.com/AnuragSahu/M3D-RPN/tree/078ddfa0a7c48dc1d23e8da679997239ac62a72a |
Attention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | VISLANG-Lab/MGCL | Attention | false | 1,893 | [
"MIT"
] | 0 | 22da06ffa7410d9632bfda8eefb1b79e4f660de0 | https://github.com/VISLANG-Lab/MGCL/tree/22da06ffa7410d9632bfda8eefb1b79e4f660de0 |
FuseUnit | import torch
import torch.nn as nn
class FuseUnit(nn.Module):
def __init__(self, channels):
super(FuseUnit, self).__init__()
self.proj1 = nn.Conv2d(2 * channels, channels, (1, 1))
self.proj2 = nn.Conv2d(channels, channels, (1, 1))
self.proj3 = nn.Conv2d(channels, channels, (1, 1))... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | sugi-san/PAMA | FuseUnit | false | 13,005 | [
"MIT"
] | 0 | 95141ebf0d3b61828a0e545f989f96b8ef569f34 | https://github.com/sugi-san/PAMA/tree/95141ebf0d3b61828a0e545f989f96b8ef569f34 |
Invertible1x1Conv | import torch
import torch.nn.functional as F
from torch.autograd import Variable
import torch.utils.data
import torch.nn
class Invertible1x1Conv(torch.nn.Module):
"""
The layer outputs both the convolution, and the log determinant
of its weight matrix. If reverse=True it does convolution with
inverse... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn.functional as F
from torch.autograd import Variable
import torch... | drostifrosti/TensorRT | Invertible1x1Conv | false | 6,620 | [
"Apache-2.0"
] | 1 | 76d673366139538fcb47a67e08734ff429306162 | https://github.com/drostifrosti/TensorRT/tree/76d673366139538fcb47a67e08734ff429306162 |
GroupedChannelNorm | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.data
import torch
import torch.nn as nn
assert_size_stride =... | a11isonliu/contrastive-unpaired-translation | GroupedChannelNorm | false | 9,840 | [
"BSD-3-Clause"
] | 0 | 67651ed9877cae121d9398f46094ce8dbc678802 | https://github.com/a11isonliu/contrastive-unpaired-translation/tree/67651ed9877cae121d9398f46094ce8dbc678802 |
SPPblock | import torch
import torch.nn as nn
import torch.nn.functional as F
class SPPblock(nn.Module):
def __init__(self, in_channels):
super(SPPblock, self).__init__()
self.pool1 = nn.MaxPool2d(kernel_size=[2, 2], stride=2)
self.pool2 = nn.MaxPool2d(kernel_size=[3, 3], stride=3)
self.pool... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | zxg3017/CUSE-Net | SPPblock | false | 13,207 | [
"MIT"
] | 0 | ea1d07027f89130a8a40465de94528f23eb9f5d1 | https://github.com/zxg3017/CUSE-Net/tree/ea1d07027f89130a8a40465de94528f23eb9f5d1 |
GlobalMaxPool | import torch
from torch import nn
class GlobalMaxPool(nn.Module):
"""
Max pooling in an equivariant network
"""
def __init__(self):
"""
"""
super().__init__()
def forward(self, x):
"""
"""
mx = torch.max(torch.max(x, dim=-1, keepdim=True)[0], dim=-... | 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... | BeomyeolYu/symmetrizer | GlobalMaxPool | false | 152 | [
"MIT"
] | 0 | 4617c82dc8ab05ac02ac50846799e0b820ff51ce | https://github.com/BeomyeolYu/symmetrizer/tree/4617c82dc8ab05ac02ac50846799e0b820ff51ce |
Expand | import torch
import torch.nn as nn
import torch.onnx
class Expand(nn.Module):
def __init__(self, gain=2):
super().__init__()
self.gain = gain
def forward(self, x):
b, c, h, w = x.size()
s = self.gain
x = x.view(b, s, s, c // s ** 2, h, w)
x = x.permute(0, 3, 4... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.onnx
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynam... | DDGRCF/YOLOX_OBB | Expand | false | 7,943 | [
"Apache-2.0"
] | 39 | 27b80953306492b8bc83b86b1353d8cee01ef9b6 | https://github.com/DDGRCF/YOLOX_OBB/tree/27b80953306492b8bc83b86b1353d8cee01ef9b6 |
RemoveChannelMeanStd | # 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... | cadurosar/graph_kd_dense_cifar100 | RemoveChannelMeanStd | false | 1,624 | [
"MIT"
] | 0 | 84054ab4f8f61c9db3460993661ba7bf1d951b36 | https://github.com/cadurosar/graph_kd_dense_cifar100/tree/84054ab4f8f61c9db3460993661ba7bf1d951b36 |
DIoULoss | # 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.distributed
import torch
import torch.nn as nn
import torch.nn.functional
im... | zhangzhengde0225/SwinTrack | DIoULoss | false | 16,798 | [
"MIT"
] | 143 | 526be17f8ef266cb924c6939bd8dda23e9b73249 | https://github.com/zhangzhengde0225/SwinTrack/tree/526be17f8ef266cb924c6939bd8dda23e9b73249 |
WSConv2d | import torch
from torchvision.transforms import functional as F
from torch import nn
from torch.nn import functional as F
class WSConv2d(nn.Conv2d):
def __init__(self, in_channels, out_channels, kernel_size, stride=1,
padding=0, dilation=1, groups=1, bias=True, eps=1e-05):
super().__init__(in_cha... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | rosinality/vision-transformers-pytorch | WSConv2d | false | 16,409 | [
"MIT"
] | 77 | b884b5da79900c96e4ce17fbb575cf1c5cb3cd5f | https://github.com/rosinality/vision-transformers-pytorch/tree/b884b5da79900c96e4ce17fbb575cf1c5cb3cd5f |
Sum | # 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... | Lalihoo/yolov5-detect | Sum | false | 9,615 | [
"MIT"
] | 0 | 265c3137ea3586d913541501a1562488fbe59e9e | https://github.com/Lalihoo/yolov5-detect/tree/265c3137ea3586d913541501a1562488fbe59e9e |
NSGANLossGenerator | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | ChristophReich1996/Mode_Collapse | NSGANLossGenerator | false | 7,912 | [
"MIT"
] | 14 | 937ee8bf96510fbf4070fc7e14b78276ab036b8c | https://github.com/ChristophReich1996/Mode_Collapse/tree/937ee8bf96510fbf4070fc7e14b78276ab036b8c |
LayerNorm | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.data
import torch.nn as nn
assert_size_stride = torch._C._dy... | BingjieTang/DepthAwareCNN | LayerNorm | false | 164 | [
"MIT"
] | 0 | 9d72a7dc921d1dd550507018d4b51968ef89bbb7 | https://github.com/BingjieTang/DepthAwareCNN/tree/9d72a7dc921d1dd550507018d4b51968ef89bbb7 |
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(in_features=28 * 28, out_features=500)
self.fc2 = nn.Linear(in_features=500, out_features=200)
self.fc3 = nn.Linear(in_feat... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | stjordanis/ml-cheatsheet | MLP | false | 16,508 | [
"MIT"
] | 1,031 | d34e096032b7ae826868be8808aee01699cec491 | https://github.com/stjordanis/ml-cheatsheet/tree/d34e096032b7ae826868be8808aee01699cec491 |
PolicyNetwork | import torch
import numpy as np
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from torch.autograd import Variable
class PolicyNetwork(nn.Module):
def __init__(self, num_inputs, num_actions, hidden_size, learning_rate=
0.0003):
super(PolicyNetwork, 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.... | xuzhiyuan1528/tf2basic | PolicyNetwork | false | 13,122 | [
"Apache-2.0"
] | 0 | 52ed7d8bcc72f16e198754f5f92a583fe16d544e | https://github.com/xuzhiyuan1528/tf2basic/tree/52ed7d8bcc72f16e198754f5f92a583fe16d544e |
PyTorchSSRU | import torch
from typing import Tuple
from abc import abstractmethod
import torch as pt
import torch.distributed
import torch.distributed.elastic.multiprocessing.errors
class AutoregressiveLayer(pt.nn.Module):
@property
@abstractmethod
def num_state_tensors(self) ->int:
""" Number of state tensor... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 typing import Tuple
from... | SamuelLarkin/sockeye | PyTorchSSRU | false | 9,538 | [
"Apache-2.0"
] | 0 | 7fcf6c96b15a887897aa712903ecf93c665ebddf | https://github.com/SamuelLarkin/sockeye/tree/7fcf6c96b15a887897aa712903ecf93c665ebddf |
Critic | import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
def hidden_init(layer):
fan_in = layer.weight.data.size()[0]
lim = 1.0 / np.sqrt(fan_in)
return -lim, lim
class Critic(nn.Module):
"""Critic (Value) Model."""
def __init__(self, state_size, action_size, seed, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import numpy as np
import tor... | makarand-mac/continuous-control | Critic | false | 12,754 | [
"MIT"
] | 0 | 6563d652770551ad2773e76daa9d536e617df01a | https://github.com/makarand-mac/continuous-control/tree/6563d652770551ad2773e76daa9d536e617df01a |
VAE | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
import torch.nn.functional as F
import torch.onnx
import torch.optim
import torch.utils.data.distributed
class VAE(nn.Module):
def __init__(self):
super(VAE, self).__init__()
self.fc1 = nn.Linear(784, 400)
... | import torch
from torch import device
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from... | Arjuna197/examples | VAE | false | 11,381 | [
"BSD-3-Clause"
] | 0 | f504ea2aafc8a8baa5effb659fc1c20a70aabdda | https://github.com/Arjuna197/examples/tree/f504ea2aafc8a8baa5effb659fc1c20a70aabdda |
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