entry_point stringlengths 1 65 | original_triton_python_code stringlengths 208 619k | optimised_triton_code stringlengths 1.15k 275k | repo_name stringlengths 7 115 | module_name stringlengths 1 65 | synthetic bool 1
class | uuid int64 0 18.5k | licenses listlengths 1 6 | stars int64 0 19.8k | sha stringlengths 40 40 | repo_link stringlengths 72 180 |
|---|---|---|---|---|---|---|---|---|---|---|
EqualLinear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
import torch.nn.functional as F
import torch.u... | HappyBelief/ContraD | EqualLinear | false | 13,757 | [
"MIT"
] | 168 | abb72562ddac8d8ab37fe9af6ac4c44c61e8ea0f | https://github.com/HappyBelief/ContraD/tree/abb72562ddac8d8ab37fe9af6ac4c44c61e8ea0f |
ParsingRelationLoss | import torch
import torch.nn.modules
import torch.nn as nn
class ParsingRelationLoss(nn.Module):
def __init__(self):
super(ParsingRelationLoss, self).__init__()
def forward(self, logits):
_n, _c, h, _w = logits.shape
loss_all = []
for i in range(0, h - 1):
loss_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.modules
import torch.nn as nn
assert_size_stride = torch.... | daveMcelf/Ultra-Fast-Lane-Detection | ParsingRelationLoss | false | 10,001 | [
"MIT"
] | 0 | 357f1f0f4538a125e9a9c1509e5f72ce2321f078 | https://github.com/daveMcelf/Ultra-Fast-Lane-Detection/tree/357f1f0f4538a125e9a9c1509e5f72ce2321f078 |
TVLoss | import torch
import torch.nn as nn
import torch.nn.init
class TVLoss(nn.Module):
def __init__(self):
super(TVLoss, self).__init__()
def forward(self, x):
"""
Arguments:
x: a float tensor with shape [b, 3, h, w].
It represents a RGB image with pixel values in [... | 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.init
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dy... | TropComplique/WESPE | TVLoss | false | 18,017 | [
"MIT"
] | 5 | 84738f1ed802a3f6a4a0549677d8137997fac617 | https://github.com/TropComplique/WESPE/tree/84738f1ed802a3f6a4a0549677d8137997fac617 |
ResConv2dLayer | import torch
import torch.nn as nn
from torch.nn import Parameter
def l2normalize(v, eps=1e-12):
return v / (v.norm() + eps)
class LayerNorm(nn.Module):
def __init__(self, num_features, eps=1e-08, affine=True):
super(LayerNorm, self).__init__()
self.num_features = num_features
self.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | Sheroa/Video_Colorization | ResConv2dLayer | false | 2,853 | [
"MIT"
] | 0 | 5c772ac0ec944814cd8be0a94b0746116b11ac01 | https://github.com/Sheroa/Video_Colorization/tree/5c772ac0ec944814cd8be0a94b0746116b11ac01 |
HyperDecoder | # 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.... | LXie502/point_based_pcgc | HyperDecoder | false | 2,488 | [
"MIT"
] | 0 | 9c4b577d35276c8674b568efc0b9d2473bb00a70 | https://github.com/LXie502/point_based_pcgc/tree/9c4b577d35276c8674b568efc0b9d2473bb00a70 |
FirstBlock | # 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
assert_size_stride = torch._C._dynamo.g... | lelechen63/idinvert_pytorch | FirstBlock | false | 10,449 | [
"MIT"
] | 0 | 0469e1e5460ee4dd626c05bd35a83d52f9dc2cac | https://github.com/lelechen63/idinvert_pytorch/tree/0469e1e5460ee4dd626c05bd35a83d52f9dc2cac |
JointsMSELoss | # 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
import torch.utils.data.distributed
import torch.m... | CHUNYUWANG/imu-human-pose-pytorch | JointsMSELoss | false | 13,425 | [
"MIT"
] | 72 | f4813336571789f46eabdfb520e7ed5b20ac04ea | https://github.com/CHUNYUWANG/imu-human-pose-pytorch/tree/f4813336571789f46eabdfb520e7ed5b20ac04ea |
ECA | import torch
import torch._C
import torch.serialization
from torch import nn
from typing import *
def int_size(x):
size = tuple(int(s) for s in x.size())
return size
class ECA(nn.Module):
"""Constructs a ECA module.
Args:
channel: Number of channels of the input feature map
k_size: A... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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._C
import torch.serialization
from torch import nn
from typing impo... | shuaizzZ/mmsegmentation | ECA | false | 4,322 | [
"Apache-2.0"
] | 0 | a6c6b348dbf8c4a0a39ffbdb832a1e82309c533c | https://github.com/shuaizzZ/mmsegmentation/tree/a6c6b348dbf8c4a0a39ffbdb832a1e82309c533c |
DenseGCNConv | import math
import torch
from torch.nn import Parameter
import torch.utils.data
def glorot(tensor):
if tensor is not None:
stdv = math.sqrt(6.0 / (tensor.size(-2) + tensor.size(-1)))
tensor.data.uniform_(-stdv, stdv)
def zeros(tensor):
if tensor is not None:
tensor.data.fill_(0)
cl... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | cshjin/pytorch_geometric | DenseGCNConv | false | 1,765 | [
"MIT"
] | 0 | 8dd0e76beb72135949a275edd851f80f7b97648f | https://github.com/cshjin/pytorch_geometric/tree/8dd0e76beb72135949a275edd851f80f7b97648f |
SquaredErrorBayesRisk | from torch.nn import Module
import torch
import torch.utils.data
import torch.nn.functional
import torch.autograd
class SquaredErrorBayesRisk(Module):
"""
<a id="SquaredErrorBayesRisk"></a>
## Bayes Risk with Squared Error Loss
Here the cost function is squared error,
$$\\sum_{k=1}^K (y_k - p_k)... | 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
import torch.utils.data
import torch.nn.functional
import torch.autograd
assert_size_stride = torch._C._dynamo.g... | mcx/annotated_deep_learning_paper_implementations | SquaredErrorBayesRisk | false | 7,214 | [
"MIT"
] | 1 | f169f3a71dd2d36eb28ad31062d3475efa367b88 | https://github.com/mcx/annotated_deep_learning_paper_implementations/tree/f169f3a71dd2d36eb28ad31062d3475efa367b88 |
QNetwork | import torch
import torch.nn as nn
import torch.nn.functional as F
class QNetwork(nn.Module):
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed, fc1_units=64,
fc2_units=64):
"""Initialize parameters and build model.
Params
======
state_si... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | DiegelD/Deep-Reinforcement-Learning-ND | QNetwork | false | 11,349 | [
"MIT"
] | 0 | 15a91da352414718bb83fdc538d73ac576472cb8 | https://github.com/DiegelD/Deep-Reinforcement-Learning-ND/tree/15a91da352414718bb83fdc538d73ac576472cb8 |
DWT | # 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.... | KazutakaYamanouchi/bachelor-study | DWT | false | 2,653 | [
"Apache-2.0"
] | 0 | a5b8392459e7649cb8a35d09e65bd269d13b5297 | https://github.com/KazutakaYamanouchi/bachelor-study/tree/a5b8392459e7649cb8a35d09e65bd269d13b5297 |
LogCosh | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch ... | dattientran/attorch | LogCosh | false | 12,389 | [
"MIT"
] | 0 | 469b225846c6d8a7d833ebac19d040c7a407a0ff | https://github.com/dattientran/attorch/tree/469b225846c6d8a7d833ebac19d040c7a407a0ff |
StackedAutoencoder | # 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... | pemami4911/ppi-with-stacked-autoencoders | StackedAutoencoder | false | 7,448 | [
"MIT"
] | 1 | c09aba827ac6991da3dbf1b2628ac5d0f5041548 | https://github.com/pemami4911/ppi-with-stacked-autoencoders/tree/c09aba827ac6991da3dbf1b2628ac5d0f5041548 |
InvConv | import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
class InvConv(nn.Module):
"""Invertible 1x1 Convolution for 2D inputs. Originally described in Glow
(https://arxiv.org/abs/1807.03039). Does not support LU-decomposed version.
Args:
num_channels (int): Number of... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | ClaraBing/flow | InvConv | false | 294 | [
"MIT"
] | 0 | 00290326a97235e7d83303f1efff2e14214d0c36 | https://github.com/ClaraBing/flow/tree/00290326a97235e7d83303f1efff2e14214d0c36 |
_ImpalaCNN | import torch
from typing import Tuple
from torch import nn
class _ImpalaResBlock(nn.Module):
def __init__(self, n_channels: 'int'):
super().__init__()
self.n_channels = n_channels
kernel_size = 3
padding = 1
self.relu = nn.ReLU()
self.relu_inplace = nn.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
from typing import Tuple
from... | nrfulton/vsrl-framework | _ImpalaCNN | false | 7,445 | [
"MIT"
] | 1 | c778824b3285e3e994a4c5846c7b1c2ac03c669b | https://github.com/nrfulton/vsrl-framework/tree/c778824b3285e3e994a4c5846c7b1c2ac03c669b |
TransformerEncoderLayer | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
import torch.utils.data
import torch.distributions
class TransformerEncoderLayer(nn.Module):
def __init__(self, embed_dim, num_heads, hidden_size, dropout=0.0,
attention_dropout=0.0, activation_dropout=0.0):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Slowika/GameBias-EmeCom2020 | TransformerEncoderLayer | false | 17,980 | [
"MIT"
] | 5 | 5b94c47559f8202bca99c26fc1bcb078dd0509a6 | https://github.com/Slowika/GameBias-EmeCom2020/tree/5b94c47559f8202bca99c26fc1bcb078dd0509a6 |
MaskedInstanceNorm1d | # 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
from torch import nn
import ... | PiotrDabkowski/NeMo | MaskedInstanceNorm1d | false | 11,789 | [
"Apache-2.0"
] | 0 | 7c251e9035b24136cf130f3caf760087e5ccf07c | https://github.com/PiotrDabkowski/NeMo/tree/7c251e9035b24136cf130f3caf760087e5ccf07c |
L2Distance | import torch
from torch import nn
import torch.autograd
class L2Distance(nn.Module):
def forward(self, img1, img2):
return (img1 - img2).reshape(img1.shape[0], -1).norm(dim=1)
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
from torch import nn
import torch.autograd
assert_size_stride = torch._C._dynam... | cassidylaidlaw/perceptual-advex | L2Distance | false | 15,010 | [
"MIT"
] | 45 | d39136eb5b5e950442456ddade6b4f4fba3dd8f6 | https://github.com/cassidylaidlaw/perceptual-advex/tree/d39136eb5b5e950442456ddade6b4f4fba3dd8f6 |
TemporalFusion | # 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... | myeldib/Simple-SR | TemporalFusion | false | 12,822 | [
"MIT"
] | 0 | 583456b1f231574d9e0b45c29266cf41603d161d | https://github.com/myeldib/Simple-SR/tree/583456b1f231574d9e0b45c29266cf41603d161d |
L2Norm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | CCC-123/ECCVC | L2Norm | false | 11,265 | [
"MIT"
] | 0 | 322009a3423dba831cb3ae4182e7129be3441e70 | https://github.com/CCC-123/ECCVC/tree/322009a3423dba831cb3ae4182e7129be3441e70 |
depthwise_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
import torch.utils.data
assert_size_stride = torch._C._dyn... | whiteking64/lang-seg | depthwise_conv | false | 16,715 | [
"MIT"
] | 202 | 9d063b126f1b64e38ddb20cc75fc74435bfdcbd3 | https://github.com/whiteking64/lang-seg/tree/9d063b126f1b64e38ddb20cc75fc74435bfdcbd3 |
ASPP | import torch
from torch import nn
import torch.nn.functional as F
class ASPP(nn.Module):
"""
Atrous spatial pyramid pooling used in object detection and segmentation.
"""
def __init__(self, in_channel=512, depth=256):
super().__init__()
self.mean = nn.AdaptiveAvgPool2d((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 import nn
assert_s... | SimonCqk/towhee | ASPP | false | 9,654 | [
"Apache-2.0"
] | 0 | a187833b1411216106a80a71e6f2c6e68e1be330 | https://github.com/SimonCqk/towhee/tree/a187833b1411216106a80a71e6f2c6e68e1be330 |
myLoss2 | import torch
import torch.nn.functional as F
import torch.nn as nn
class myLoss2(nn.Module):
def __init__(self, alpha=1.0):
super(myLoss2, self).__init__()
self.alpha = alpha
def forward(self, sent_probs, doc_probs, sent_targets, doc_targets):
loss_1 = F.mse_loss(sent_probs, sent_tar... | 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... | PKULiuHui/LiveBlogSum | myLoss2 | false | 914 | [
"MIT"
] | 0 | b6a22521ee454e649981d70ddca6c89a1bac5a4c | https://github.com/PKULiuHui/LiveBlogSum/tree/b6a22521ee454e649981d70ddca6c89a1bac5a4c |
ApplyStyle | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
import torch
from torch import nn
import torch.nn.functi... | siyuhuang/PoseStylizer | ApplyStyle | false | 16,466 | [
"BSD-3-Clause"
] | 75 | d1d832781ddfd3efde24bf32b36a4074fafebcc1 | https://github.com/siyuhuang/PoseStylizer/tree/d1d832781ddfd3efde24bf32b36a4074fafebcc1 |
GemanMcClure | # 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 | GemanMcClure | false | 18,317 | [
"Apache-2.0"
] | 10 | e38cac046c059d2e2331ef4883bbabc5a500a5cf | https://github.com/ai-in-motion/moai/tree/e38cac046c059d2e2331ef4883bbabc5a500a5cf |
FTanh | # 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.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | dawnclaude/onnx2keras | FTanh | false | 15,146 | [
"MIT"
] | 115 | 3d2a47c0a228b91fd434232274e216e491da36e3 | https://github.com/dawnclaude/onnx2keras/tree/3d2a47c0a228b91fd434232274e216e491da36e3 |
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
import ... | Diego999/Global-Encoding | maxout | false | 5,068 | [
"MIT"
] | 1 | d3a4af9459ac3192686c94de6f2693afd6083638 | https://github.com/Diego999/Global-Encoding/tree/d3a4af9459ac3192686c94de6f2693afd6083638 |
DotRole | from _paritybench_helpers import _mock_config
import torch
import torch as th
import torch.nn as nn
class DotRole(nn.Module):
def __init__(self, args):
super(DotRole, self).__init__()
self.args = args
self.n_actions = args.n_actions
self.q_fc = nn.Linear(args.rnn_hidden_dim, args.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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 as th
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | NagisaZj/RODE | DotRole | false | 11,118 | [
"Apache-2.0"
] | 0 | f7f6831fee58a7910e1d7c3a8ae19cef82ab8d03 | https://github.com/NagisaZj/RODE/tree/f7f6831fee58a7910e1d7c3a8ae19cef82ab8d03 |
FocalLoss | # 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
... | ChristophReich1996/Cell-DETR | FocalLoss | false | 13,488 | [
"MIT"
] | 55 | 4d0c3a2d3ffd19184c8443e5b3a6dccc053c77ea | https://github.com/ChristophReich1996/Cell-DETR/tree/4d0c3a2d3ffd19184c8443e5b3a6dccc053c77ea |
UFOAttention | import torch
from torch import nn
from torch.nn import init
def XNorm(x, gamma):
norm_tensor = torch.norm(x, 2, -1, True)
return x * gamma / norm_tensor
class UFOAttention(nn.Module):
"""
Scaled dot-product attention
"""
def __init__(self, d_model, d_k, d_v, h, dropout=0.1):
"""
... | 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.triton_helpers import libdevice
from torch import n... | LiChengChen666/DetectDee | UFOAttention | false | 9,835 | [
"Apache-2.0"
] | 0 | 1e6aaa0d15b1fc12d1342d8a922004e372b5f437 | https://github.com/LiChengChen666/DetectDee/tree/1e6aaa0d15b1fc12d1342d8a922004e372b5f437 |
ComplexConv2d | # 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.nn import Module
from torch.nn import Conv2d
assert_size_stride = tor... | drydenwiebe/complexPyTorch | ComplexConv2d | false | 12,323 | [
"MIT"
] | 0 | cea88ba7ee5692dfa1b40f0ba609ef14160d5073 | https://github.com/drydenwiebe/complexPyTorch/tree/cea88ba7ee5692dfa1b40f0ba609ef14160d5073 |
BasicModel_MaxPool_ReLU | # 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... | Europium248/captum | BasicModel_MaxPool_ReLU | false | 430 | [
"BSD-3-Clause"
] | 0 | ac02fae2651b8d68a44bcb9d03b91cbb3959f2fc | https://github.com/Europium248/captum/tree/ac02fae2651b8d68a44bcb9d03b91cbb3959f2fc |
TemporalAttention | # 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.... | STRCSussex-UbiCompSiegen/dl_har_model | TemporalAttention | false | 2,866 | [
"MIT"
] | 0 | caac0f87fc7dd08a5d6ad3e4455ee25b35f5e7b4 | https://github.com/STRCSussex-UbiCompSiegen/dl_har_model/tree/caac0f87fc7dd08a5d6ad3e4455ee25b35f5e7b4 |
Upsample | import torch
import torch.nn as nn
import torch.nn.functional as F
class Upsample(nn.Module):
""" nn.Upsample is deprecated """
def __init__(self, scale_factor, mode='nearest'):
super(Upsample, self).__init__()
self.scale_factor = scale_factor
self.mode = mode
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | DRL-CASIA/Perception | Upsample | false | 7,935 | [
"MIT"
] | 39 | a0e7d3957267ce92a82b03ab3eca96916d22c4f2 | https://github.com/DRL-CASIA/Perception/tree/a0e7d3957267ce92a82b03ab3eca96916d22c4f2 |
DDM_Encoder | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import numpy as np
... | lysuk96/rl_representations | DDM_Encoder | false | 15,984 | [
"MIT"
] | 438 | 19de69305e40c9b3a1d746a7af26d232c9fb3f6f | https://github.com/lysuk96/rl_representations/tree/19de69305e40c9b3a1d746a7af26d232c9fb3f6f |
PositionwiseFeedForward | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
class PositionwiseFeedForward(nn.Module):
"""Implements FFN equation."""
def __init__(self, d_model, d_ff, dropout=0.1):
super(PositionwiseFeedForward, self).__init__()
self.w_1 = nn.Linear(d_model, d_f... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | RerRayne/learn3d | PositionwiseFeedForward | false | 14,285 | [
"MIT"
] | 335 | 83e4ac657c6538fb4cbed6e00b2e3ed6cbf43555 | https://github.com/RerRayne/learn3d/tree/83e4ac657c6538fb4cbed6e00b2e3ed6cbf43555 |
WSConv2d | # 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
import torch.utils.data
assert_size_stride = torch._C._dyna... | jiazhi412/Machine-Learning-Collection | WSConv2d | false | 3,729 | [
"MIT"
] | 0 | 1c30faf1e27a79eeca966c017e956df8f7f6ef17 | https://github.com/jiazhi412/Machine-Learning-Collection/tree/1c30faf1e27a79eeca966c017e956df8f7f6ef17 |
Gated_Recurrent_Unit | import torch
from torchvision.transforms import functional as F
import torch.utils.data
from torch import nn
import torch.nn.functional as F
class Gated_Recurrent_Unit(nn.Module):
def __init__(self, fea_size, dropout):
super(Gated_Recurrent_Unit, self).__init__()
self.wih = nn.Linear(fea_size, fe... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | champon1020/scene_graph_benchmark | Gated_Recurrent_Unit | false | 9,975 | [
"MIT"
] | 0 | 970a7499f8fa2854810bd650f6c991bcad5748db | https://github.com/champon1020/scene_graph_benchmark/tree/970a7499f8fa2854810bd650f6c991bcad5748db |
stage_n_block | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from to... | H-Liu1997/Pytorch_Pose_Estimation_Framework | stage_n_block | false | 5,271 | [
"MIT"
] | 1 | 06616b3459ff639f8486e6ea4f93922597788b2a | https://github.com/H-Liu1997/Pytorch_Pose_Estimation_Framework/tree/06616b3459ff639f8486e6ea4f93922597788b2a |
duelingDQNnetwork | import torch
import torch.nn.functional as F
import torch.nn as nn
class duelingDQNnetwork(nn.Module):
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed, fc1_units=64,
fc2_units=64):
"""Initialize parameters and build model.
Params
======
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | beibeiJ/deep-reinforcement-learning | duelingDQNnetwork | false | 1,528 | [
"MIT"
] | 0 | ab1b0f4ada8da69af2e38d3e2e82e3ae55837c60 | https://github.com/beibeiJ/deep-reinforcement-learning/tree/ab1b0f4ada8da69af2e38d3e2e82e3ae55837c60 |
SELoss | # 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... | kfirgedal/lightning-bolts | SELoss | false | 12,661 | [
"Apache-2.0"
] | 0 | cbb8b6c21ca1de757d0f289fb840d59a3b6a10f5 | https://github.com/kfirgedal/lightning-bolts/tree/cbb8b6c21ca1de757d0f289fb840d59a3b6a10f5 |
ScaleNorm | import math
import torch
import torch.nn as nn
class ScaleNorm(nn.Module):
"""ScaleNorm"""
"""All g’s in SCALE NORM are initialized to sqrt(d)"""
def __init__(self, scale, eps=1e-05):
super(ScaleNorm, self).__init__()
self.scale = nn.Parameter(torch.tensor(math.sqrt(scale)))
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 import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import math
import torch.nn ... | eweiner/MAT_Extension | ScaleNorm | false | 12,356 | [
"MIT"
] | 0 | 505884a67f97bf54e1198077d15a48531fcac7a5 | https://github.com/eweiner/MAT_Extension/tree/505884a67f97bf54e1198077d15a48531fcac7a5 |
RSoftmax | # 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
... | ChengBo5/mask-text-detector | RSoftmax | false | 244 | [
"Apache-2.0"
] | 0 | ce93e45ed1d982ec0ef6ad977c02e49326bf255a | https://github.com/ChengBo5/mask-text-detector/tree/ce93e45ed1d982ec0ef6ad977c02e49326bf255a |
Mod | # 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... | Ilyabasharov/torch2trt | Mod | false | 2,565 | [
"MIT"
] | 0 | 76bf298b3da408509665e23e2494922b131afb10 | https://github.com/Ilyabasharov/torch2trt/tree/76bf298b3da408509665e23e2494922b131afb10 |
TorchFloorDiv | # 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... | NVIDIA-AI-IOT-private/torch2trt | TorchFloorDiv | false | 10,542 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
AR | import torch
import torch.nn as nn
class AR(nn.Module):
def __init__(self, window: 'int', hidden_size: 'int'):
super(AR, self).__init__()
self.linear = nn.Linear(window, hidden_size)
def forward(self, x):
x = torch.transpose(x, 1, 2)
x = self.linear(x)
x = torch.trans... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | lucianolorenti/rul_pm | AR | false | 7,125 | [
"MIT"
] | 1 | da9dfad79129dd47d24923cfd6c833869ef7b6a7 | https://github.com/lucianolorenti/rul_pm/tree/da9dfad79129dd47d24923cfd6c833869ef7b6a7 |
RNNAgent | # 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_... | johnson7788/pymarl2 | RNNAgent | false | 3,907 | [
"Apache-2.0"
] | 0 | 8ec3e58fc3325ae82165cae0a5ea8a391ce42bd5 | https://github.com/johnson7788/pymarl2/tree/8ec3e58fc3325ae82165cae0a5ea8a391ce42bd5 |
CutMixCrossEntropyLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch.nn import M... | bottlenome/cutmix | CutMixCrossEntropyLoss | false | 9,791 | [
"MIT"
] | 0 | d18c2bda47e7d1786819420edbb2c8e5ad43385f | https://github.com/bottlenome/cutmix/tree/d18c2bda47e7d1786819420edbb2c8e5ad43385f |
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_... | jiwidi/lightning-tutorials | ConcatELU | false | 15,697 | [
"Apache-2.0"
] | 114 | 70ba437447f345d4d6ba089d5b30fd1da2cbc04b | https://github.com/jiwidi/lightning-tutorials/tree/70ba437447f345d4d6ba089d5b30fd1da2cbc04b |
MatchRNNAttention | # 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.... | xdong73S/Match_LSTM_v2.0 | MatchRNNAttention | false | 4,575 | [
"MIT"
] | 0 | dfb8cfbc2a5dafc6655eecf151a7dbcf808cd729 | https://github.com/xdong73S/Match_LSTM_v2.0/tree/dfb8cfbc2a5dafc6655eecf151a7dbcf808cd729 |
SetConv | # 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_... | dacasals/learnedcardinalities | SetConv | false | 1,791 | [
"MIT"
] | 0 | ee9741ce1a7b55ed18c33fbd6047484e50068037 | https://github.com/dacasals/learnedcardinalities/tree/ee9741ce1a7b55ed18c33fbd6047484e50068037 |
RankingLoss | # 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 abc import abstractmethod
import torch.utils.data.dataloader
import torch.nn as nn
i... | bogdankostic/flair | RankingLoss | false | 6,351 | [
"MIT"
] | 1 | 8cf03eab19512e94c1bcb4a30409bb065d37fe25 | https://github.com/bogdankostic/flair/tree/8cf03eab19512e94c1bcb4a30409bb065d37fe25 |
Upsample | # 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.... | BCV-Uniandes/SAMA | Upsample | false | 124 | [
"BSD-3-Clause"
] | 0 | 4c732c71486af17efed17480e363298cb65c851f | https://github.com/BCV-Uniandes/SAMA/tree/4c732c71486af17efed17480e363298cb65c851f |
convBlock | import torch
import torch.nn as nn
import torch.nn.functional
class convBlock(nn.Module):
"""
A convolutional block including conv, BN, nonliear activiation, residual connection
"""
def __init__(self, in_channels, out_channels, kernel_size=3, stride=1,
padding=1, bias=True, batchnorm=False, r... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.functional
assert_size_stride = torch._C._... | junyuchen245/TransMorph_Transformer_for_Medical_Image_Registration | convBlock | false | 15,751 | [
"MIT"
] | 82 | dfa24a47a564a000aa9b4eea95a6e83a24568359 | https://github.com/junyuchen245/TransMorph_Transformer_for_Medical_Image_Registration/tree/dfa24a47a564a000aa9b4eea95a6e83a24568359 |
Conv2DHighwayLayer | # 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_... | avinashsai/Highway-Networks | Conv2DHighwayLayer | false | 3,152 | [
"MIT"
] | 0 | fe30629e47b919776f981eaa2bea7d21e648a17f | https://github.com/avinashsai/Highway-Networks/tree/fe30629e47b919776f981eaa2bea7d21e648a17f |
VAE | import torch
import torch.nn as nn
def reparametrize(mu, logsigma):
sigma = logsigma.exp()
eps = torch.randn_like(sigma)
z = eps.mul(sigma).add_(mu)
return z
class Decoder(nn.Module):
def __init__(self, latent_size, m):
super(Decoder, self).__init__()
self.latent_size = latent_s... | 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... | lshoek/creative-evo-controller | VAE | false | 10,533 | [
"MIT"
] | 0 | a5f1742c172255cca2338b76ae1c5b4db277bb0d | https://github.com/lshoek/creative-evo-controller/tree/a5f1742c172255cca2338b76ae1c5b4db277bb0d |
Generator | import torch
import torch.nn as nn
import torch.nn.functional as F
class Generator(nn.Module):
def __init__(self, embed_size, max_size, nlayers=0, activation_type='tanh'
):
super(Generator, self).__init__()
hidden = max_size * embed_size
if activation_type == 'tanh':
a... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ConstantineLignos/ersatz | Generator | false | 7,906 | [
"Apache-2.0"
] | 16 | 7d1b8f2e0904503a24615777520837bc8633cd0c | https://github.com/ConstantineLignos/ersatz/tree/7d1b8f2e0904503a24615777520837bc8633cd0c |
AttnGCNLayer | # 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.... | Fenkail/hgr_v2t | AttnGCNLayer | false | 13,696 | [
"MIT"
] | 190 | d8cc1c18cdaae54fd1878d6dc7b8e9c60d83fcbb | https://github.com/Fenkail/hgr_v2t/tree/d8cc1c18cdaae54fd1878d6dc7b8e9c60d83fcbb |
LayerNorm | import torch
class LayerNorm(torch.nn.Module):
def __init__(self, input_dim):
super(LayerNorm, self).__init__()
self.gamma = torch.nn.Parameter(torch.ones(input_dim))
self.beta = torch.nn.Parameter(torch.zeros(input_dim))
self.eps = 1e-06
def forward(self, x, mask):
m... | 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... | watchernyu/MatchLSTM-Analyze-Adversarial-Training | LayerNorm | false | 16,698 | [
"MIT"
] | 50 | 00bd33d3dd22d5291dc2c1ec5feef5eb93b59b3a | https://github.com/watchernyu/MatchLSTM-Analyze-Adversarial-Training/tree/00bd33d3dd22d5291dc2c1ec5feef5eb93b59b3a |
AdaIN | import torch
import torch.nn as nn
class AdaIN(nn.Module):
def __init__(self, style_dim, num_features):
super().__init__()
self.norm = nn.InstanceNorm2d(num_features, affine=False)
self.fc = nn.Linear(style_dim, num_features * 2)
def forward(self, x, s):
h = self.fc(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
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | innerverz/CodeTemplate | AdaIN | false | 3,668 | [
"MIT"
] | 0 | a20f5d24b0b79871aa39b5cde33e3bb4d2507d13 | https://github.com/innerverz/CodeTemplate/tree/a20f5d24b0b79871aa39b5cde33e3bb4d2507d13 |
ResidualDenseBlock_5C | # 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... | Geeta-Landmark/Super-Resolution-Image | ResidualDenseBlock_5C | false | 11,468 | [
"Apache-2.0"
] | 0 | fb5d71ec9a4673409ecd28189e97056943ca308b | https://github.com/Geeta-Landmark/Super-Resolution-Image/tree/fb5d71ec9a4673409ecd28189e97056943ca308b |
ShearY | # 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 libdevice
import torch.nn as ... | Hayoung93/UDA | ShearY | false | 955 | [
"Apache-2.0"
] | 0 | a587b01c76141d64e7cead55b62e0f3ed75890bf | https://github.com/Hayoung93/UDA/tree/a587b01c76141d64e7cead55b62e0f3ed75890bf |
AttentivePooling | # 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.... | czlwang/s3prl | AttentivePooling | false | 12,281 | [
"Apache-2.0"
] | 0 | 81d4bb8d051cee20fa87c083b8478999e1766172 | https://github.com/czlwang/s3prl/tree/81d4bb8d051cee20fa87c083b8478999e1766172 |
SILogLoss | import torch
import torch.utils.data.distributed
import torch.nn as nn
import torch.nn
class SILogLoss(nn.Module):
def __init__(self):
super(SILogLoss, self).__init__()
self.name = 'SILog'
def forward(self, input, target, mask=None, interpolate=True):
if interpolate:
inpu... | 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... | rosivbus/aphantasia | SILogLoss | false | 16,341 | [
"MIT"
] | 579 | e739f21721222c3ea99aff3324f293fa5c5dd36d | https://github.com/rosivbus/aphantasia/tree/e739f21721222c3ea99aff3324f293fa5c5dd36d |
HyperpriorSynthesisDLMM | import torch
import torch.nn as nn
import torch.nn.functional as F
def get_num_DLMM_channels(C, K=4, params=['mu', 'scale', 'mix']):
"""
C: Channels of latent representation (L3C uses 5).
K: Number of mixture coefficients.
"""
return C * K * len(params)
class HyperpriorSynthesisDLMM(nn.Module)... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | ali-zafari/high-fidelity-generative-compression | HyperpriorSynthesisDLMM | false | 9,784 | [
"Apache-2.0"
] | 0 | 37ab8d6727df48f8ebf4577db0986ccd0ffe404b | https://github.com/ali-zafari/high-fidelity-generative-compression/tree/37ab8d6727df48f8ebf4577db0986ccd0ffe404b |
Attention | import torch
import torch.nn as nn
class Attention(nn.Module):
def __init__(self):
super().__init__()
self.softmax = nn.Softmax(dim=-1)
def forward(self, Q, K, V, mask=None, dk=64):
w = torch.bmm(Q, K.transpose(1, 2))
if mask is not None:
assert w.size() == mask.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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | iml1111/machine-translation | Attention | false | 6,866 | [
"MIT"
] | 1 | a7dd673efbe8a172c1df49e0d50482dc84008c37 | https://github.com/iml1111/machine-translation/tree/a7dd673efbe8a172c1df49e0d50482dc84008c37 |
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.triton_helpers import libdevice
import torch.nn as ... | MSU-MLSys-Lab/CATE | Net | false | 8,526 | [
"Apache-2.0"
] | 15 | 654c393d7df888d2c3f3b90f9e6752faa061157e | https://github.com/MSU-MLSys-Lab/CATE/tree/654c393d7df888d2c3f3b90f9e6752faa061157e |
SmoothL1LossWithIgnore | # 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.functi... | drivendataorg/DrivenData-2021-Geopose-Solution | SmoothL1LossWithIgnore | false | 6,607 | [
"MIT"
] | 1 | fc1dead0aeb1ade9e9d87b55f56e631c57e966a6 | https://github.com/drivendataorg/DrivenData-2021-Geopose-Solution/tree/fc1dead0aeb1ade9e9d87b55f56e631c57e966a6 |
PairwiseBilinear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.a... | andhikayusup/biaffineparser | PairwiseBilinear | false | 14,835 | [
"Apache-2.0"
] | 46 | 30180b805bdb6c0f1e0386ceb090ba83d6ab2621 | https://github.com/andhikayusup/biaffineparser/tree/30180b805bdb6c0f1e0386ceb090ba83d6ab2621 |
NTN | # 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 ... | aryaman4/TaxoExpan | NTN | false | 9,805 | [
"Apache-2.0"
] | 0 | 3d9b9a21ba7cdd872dc62181dd14ff271e20b245 | https://github.com/aryaman4/TaxoExpan/tree/3d9b9a21ba7cdd872dc62181dd14ff271e20b245 |
Discriminator | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
import torch.utils.data
assert_size_stride = t... | Bawaw/pytorch_geometric | Discriminator | false | 13,388 | [
"MIT"
] | 62 | 868548d4396fc66e39b08e2ff19091a367ddac13 | https://github.com/Bawaw/pytorch_geometric/tree/868548d4396fc66e39b08e2ff19091a367ddac13 |
make_dilation_dense | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
class make_dilation_dense(nn.Module):
def __init__(self, nChannels, growthRate, kernel_size=3):
super(make_dilation_dense, self).__init__()
self.conv = nn.Conv2d(nChannels, growthRate, kernel_size=
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | cestcedric/TSSR-GAN | make_dilation_dense | false | 1,661 | [
"BSD-2-Clause",
"MIT"
] | 0 | d6e1b50409e0f0591660552993e6d5b70d41e766 | https://github.com/cestcedric/TSSR-GAN/tree/d6e1b50409e0f0591660552993e6d5b70d41e766 |
MLP_G | # 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_... | tasfia/BMCoGAN | MLP_G | false | 13,102 | [
"MIT"
] | 0 | 0d400c2c71dbfb69af422afc487f65afb98de8af | https://github.com/tasfia/BMCoGAN/tree/0d400c2c71dbfb69af422afc487f65afb98de8af |
TorchAdd | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
class TorchAdd(nn.Module):
"""
TorchAdd Module.
"""
def forward(self, input_list):
return input_list[0] + input_list[1]
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_in... | 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... | HarshCasper/nni | TorchAdd | false | 5,277 | [
"MIT"
] | 1 | 291bbbba9f296382015a77b2c88eb5db5b44bf94 | https://github.com/HarshCasper/nni/tree/291bbbba9f296382015a77b2c88eb5db5b44bf94 |
ResidualConvUnit | import torch
import torch.fft
import torch.nn as nn
import torch.utils.cpp_extension
class ResidualConvUnit(nn.Module):
def __init__(self, cin, activation, bn):
super().__init__()
self.conv = nn.Conv2d(cin, cin, kernel_size=3, stride=1, padding=1,
bias=True)
self.skip_add = nn... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.fft
import torch.nn as nn
import torch.utils.cpp_extension
assert_s... | CeciLyu/projected_gan | ResidualConvUnit | false | 11,578 | [
"MIT"
] | 0 | 5e86ee0c88d47164c30ede37448e7ba7f010fa7b | https://github.com/CeciLyu/projected_gan/tree/5e86ee0c88d47164c30ede37448e7ba7f010fa7b |
ConvReluPool | # 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 Conv2d
f... | smearle/neural-mmo | ConvReluPool | false | 12,994 | [
"MIT"
] | 0 | 7f1e98857cb32bdb59a273eb71ec43bbd9793b34 | https://github.com/smearle/neural-mmo/tree/7f1e98857cb32bdb59a273eb71ec43bbd9793b34 |
AdaFM | # 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
import torch.utils.data
import torch.utils.data.distributed
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | MiaoyunZhao/GANTransferLimitedData | AdaFM | false | 8,536 | [
"MIT"
] | 41 | 5545bc37a1d7d4f28a9c3588aaa12a616bbddd88 | https://github.com/MiaoyunZhao/GANTransferLimitedData/tree/5545bc37a1d7d4f28a9c3588aaa12a616bbddd88 |
OutConv | # 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 ... | iabd/Dereverbify | OutConv | false | 10,261 | [
"MIT"
] | 0 | e0c2e40c6813cf5528c3e0a1d697085444fb23b2 | https://github.com/iabd/Dereverbify/tree/e0c2e40c6813cf5528c3e0a1d697085444fb23b2 |
Conv_Q | # 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_... | cedesu/BCQ | Conv_Q | false | 12,212 | [
"MIT"
] | 0 | 424548510349a85c31809431494dcc6f64b611ba | https://github.com/cedesu/BCQ/tree/424548510349a85c31809431494dcc6f64b611ba |
EncoderBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | dukeNashor/CaptainStony | EncoderBlock | false | 1,885 | [
"MIT"
] | 0 | 6320a27420e686666a4d7172437cf55fe42de2b6 | https://github.com/dukeNashor/CaptainStony/tree/6320a27420e686666a4d7172437cf55fe42de2b6 |
ToRGB | from torch.autograd import Function
import math
import random
import torch
from torch import nn
from torch.nn import functional as F
def upsample(in_tens, out_H=64):
in_H = in_tens.shape[2]
scale_factor = 1.0 * out_H / in_H
return nn.Upsample(scale_factor=scale_factor, mode='bilinear',
align_corne... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.autograd import Function
import math
import random
from torch import ... | SavvaI/stylegan2-pytorch | ToRGB | false | 9,522 | [
"MIT",
"BSD-2-Clause",
"Apache-2.0"
] | 0 | b8e4b605bd951283ef2c9a784e7afa0a486975bb | https://github.com/SavvaI/stylegan2-pytorch/tree/b8e4b605bd951283ef2c9a784e7afa0a486975bb |
CONV1d_FusionBlock | import torch
import torch.nn.parallel
import torch.optim
import torch
import torch.nn as nn
class CONV1d_FusionBlock(nn.Module):
def __init__(self, in_channels, n_segment, n_div):
super(CONV1d_FusionBlock, self).__init__()
self.n_div = n_div
self.fold = in_channels // n_div
self.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
import torch.nn.parallel
import torch.optim
import torch
import torch.nn as nn
a... | RongchangLi/DEN | CONV1d_FusionBlock | false | 17,884 | [
"MIT"
] | 4 | f8b744f96a3a68cf0784080ffd561a5279715727 | https://github.com/RongchangLi/DEN/tree/f8b744f96a3a68cf0784080ffd561a5279715727 |
RingLoss | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.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 |
SeqKD | import torch
import torch.nn as nn
import torch.nn.functional as F
class SeqKD(nn.Module):
"""
NLL loss with label smoothing.
"""
def __init__(self, T=1):
super(SeqKD, self).__init__()
self.kdloss = nn.KLDivLoss(reduction='batchmean')
self.T = T
def forward(self, predicti... | 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... | ardasatata/SLR | SeqKD | false | 1,467 | [
"Apache-2.0"
] | 0 | a001a19775646cf7bab92f59e0d40019efb909c6 | https://github.com/ardasatata/SLR/tree/a001a19775646cf7bab92f59e0d40019efb909c6 |
ConvNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.optim
import tor... | stanbiryukov/PyTorch-LBFGS | ConvNet | false | 16,496 | [
"MIT"
] | 451 | ea0ca553797b38d47682ce8ff553a4f53ec8c15c | https://github.com/stanbiryukov/PyTorch-LBFGS/tree/ea0ca553797b38d47682ce8ff553a4f53ec8c15c |
CrossEmbeddings | # 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... | amirziai/CLIP4Clip | CrossEmbeddings | false | 14,836 | [
"MIT"
] | 294 | d1f31c881ed897a513c29e62512cd56c482420e6 | https://github.com/amirziai/CLIP4Clip/tree/d1f31c881ed897a513c29e62512cd56c482420e6 |
ExpandNetLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch ... | jongwookyi/hdr-expandnet | ExpandNetLoss | false | 3,767 | [
"BSD-3-Clause-Clear"
] | 0 | 0594605c8f2041bc592c20c1e7fd8615994c6b01 | https://github.com/jongwookyi/hdr-expandnet/tree/0594605c8f2041bc592c20c1e7fd8615994c6b01 |
GAT | # 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.... | omsrisagar/KG-A2C | GAT | false | 12,883 | [
"MIT"
] | 0 | c3ea64eabbfe090c2bb9f68999d0a68946f94b85 | https://github.com/omsrisagar/KG-A2C/tree/c3ea64eabbfe090c2bb9f68999d0a68946f94b85 |
Shifted_softplus | import torch
import torch.nn as nn
import torch.nn.parallel
class Shifted_softplus(nn.Module):
"""
Performs a Shifter softplus loss, which modifies with a value of log(2)
"""
def __init__(self):
super(Shifted_softplus, self).__init__()
self.act = nn.Softplus()
self.shift = nn.Para... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torch.nn as nn
import torch.nn.parallel
assert_size_str... | Chahalprincy/deepchem | Shifted_softplus | false | 223 | [
"MIT"
] | 0 | 9d1a6a879cc74b065694b3ddb763d52151d57b7a | https://github.com/Chahalprincy/deepchem/tree/9d1a6a879cc74b065694b3ddb763d52151d57b7a |
SobelConv2d | # 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... | workingcoder/EDCNN | SobelConv2d | false | 16,730 | [
"Apache-2.0"
] | 117 | 68305f465d2b731b60ce78bd0c95c7742d9f52d1 | https://github.com/workingcoder/EDCNN/tree/68305f465d2b731b60ce78bd0c95c7742d9f52d1 |
GatedConvTranspose | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | D-hash-code/ffjord | GatedConvTranspose | false | 11,355 | [
"MIT"
] | 0 | 3647ab35537a8bac3b4dc1e45a593819ac8e2c18 | https://github.com/D-hash-code/ffjord/tree/3647ab35537a8bac3b4dc1e45a593819ac8e2c18 |
Attention | import torch
import torch.nn as nn
class Attention(nn.Module):
def __init__(self, n_h):
super(Attention, self).__init__()
self.linear = nn.Linear(n_h * 2, 1)
self.softmax = nn.Softmax(dim=2)
def forward(self, x):
curr_node = x[:, :, 0, :].unsqueeze(2).expand_as(x)
sta... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | CrowdDynamicsLab/InfoMotif | Attention | false | 17,195 | [
"BSD-3-Clause"
] | 7 | cca1ffa14cc94408a5c4c50b7b1707c608e3bc9b | https://github.com/CrowdDynamicsLab/InfoMotif/tree/cca1ffa14cc94408a5c4c50b7b1707c608e3bc9b |
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.... | zijian-hu/pytorchvideo | TransposeMultiheadAttention | false | 4,713 | [
"Apache-2.0"
] | 0 | 51589b100437af2285c56ce2ccc7ccecb7f9b18b | https://github.com/zijian-hu/pytorchvideo/tree/51589b100437af2285c56ce2ccc7ccecb7f9b18b |
TransformerEncoderLayer | # 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.... | johnjosephmorgan/snowfall | TransformerEncoderLayer | false | 12,761 | [
"Apache-2.0"
] | 0 | 604d789c0aed035626d6745e6d7a427168063cae | https://github.com/johnjosephmorgan/snowfall/tree/604d789c0aed035626d6745e6d7a427168063cae |
ToTensor | # 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... | alinavalinav/finn | ToTensor | false | 6,198 | [
"BSD-3-Clause"
] | 1 | e443a5859066a410a63c08dcfec4a90527ca24be | https://github.com/alinavalinav/finn/tree/e443a5859066a410a63c08dcfec4a90527ca24be |
ImagenetNorm | # 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... | jokingbear/DM | ImagenetNorm | false | 6,975 | [
"MIT"
] | 1 | 9c4dada1756f3d866455a397511d4f3bacfadc60 | https://github.com/jokingbear/DM/tree/9c4dada1756f3d866455a397511d4f3bacfadc60 |
Mish | from torch.nn import Module
import torch
from torch import Tensor
import torch.optim
class Mish(Module):
"""
Mish Activation Layer
Applies a Mish activation function to the input
Inherits from:
Module (nn.module.Module)
"""
def __init__(self) ->None:
super().... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch.nn import Module
import torch.optim
assert_size_str... | PABannier/nanograd | Mish | false | 8,609 | [
"MIT"
] | 18 | 5acd355c638885cbfc0fd0f1c4903964e7fb7de9 | https://github.com/PABannier/nanograd/tree/5acd355c638885cbfc0fd0f1c4903964e7fb7de9 |
Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | pfontana96/smart-sailboat | Net | false | 12,881 | [
"MIT"
] | 0 | 25b2a524b2601b3f8e72092d7a34beb849b617db | https://github.com/pfontana96/smart-sailboat/tree/25b2a524b2601b3f8e72092d7a34beb849b617db |
Actor | import torch
import torch.nn.functional as F
import torch.nn as nn
class Actor(nn.Module):
def __init__(self, state_dim, action_dim, max_action, nhid):
super(Actor, self).__init__()
self.l1 = nn.Linear(state_dim, nhid)
self.l2 = nn.Linear(nhid, nhid)
self.l3 = nn.Linear(nhid, acti... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | simondlevy/pytorch-drl | Actor | false | 4,345 | [
"MIT"
] | 0 | b197bb93c2cc698971f98095d4e0180811c52042 | https://github.com/simondlevy/pytorch-drl/tree/b197bb93c2cc698971f98095d4e0180811c52042 |
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