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 |
|---|---|---|---|---|---|---|---|---|---|---|
PerceptronTanh | # 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.... | shi27feng/PDP-Solver | PerceptronTanh | false | 12,976 | [
"MIT"
] | 0 | bf6e392f72f8a3572e0987313230943d94d53c95 | https://github.com/shi27feng/PDP-Solver/tree/bf6e392f72f8a3572e0987313230943d94d53c95 |
BertAttention | # 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.... | Hzfinfdu/Black-Box-Tuning | BertAttention | false | 4,263 | [
"MIT"
] | 0 | 64eb5505875dc1b242c6f0a2a2f07e4000c24cb4 | https://github.com/Hzfinfdu/Black-Box-Tuning/tree/64eb5505875dc1b242c6f0a2a2f07e4000c24cb4 |
SigmaL1SmoothLoss | import torch
import torch.nn as nn
from typing import *
class SigmaL1SmoothLoss(nn.Module):
def forward(self, output, target):
reg_diff = torch.abs(target - output)
reg_loss = torch.where(torch.le(reg_diff, 1 / 9), 4.5 * torch.pow(
reg_diff, 2), reg_diff - 1 / 18)
return reg_l... | 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
... | DineshChauhan/fastai_docs | SigmaL1SmoothLoss | false | 11,370 | [
"Apache-2.0"
] | 0 | cf4d88073fb6f3ef7331b5360618b8dd95eb9345 | https://github.com/DineshChauhan/fastai_docs/tree/cf4d88073fb6f3ef7331b5360618b8dd95eb9345 |
ClassifierHead | import torch
import torch.utils.data
import torchvision.transforms.functional as F
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
from torch import optim as optim
def adaptive_avgmax_pool2d(x, output_size=1):
x_avg = F.adaptive_avg_pool2d(x, output_size)
x_max = F.adaptive_max_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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 torchvision.transforms.functional as F
import tor... | dumpmemory/NonDeepNetworks | ClassifierHead | false | 15,261 | [
"BSD-3-Clause"
] | 307 | 5513bf588f4e64c99583440507232675c2e21e34 | https://github.com/dumpmemory/NonDeepNetworks/tree/5513bf588f4e64c99583440507232675c2e21e34 |
CIFAR10ConvNet | import torch
from random import *
import torch.nn.functional as F
import torch.nn as nn
class CIFAR10ConvNet(torch.nn.Module):
def __init__(self, num_conv_layers, num_filters_1, num_filters_2,
num_filters_3, dropout_rate, num_fc_units, kernel_size):
super().__init__()
self.conv1 = 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.... | xinranzhu/GPTune-1 | CIFAR10ConvNet | false | 13,115 | [
"BSD-3-Clause-LBNL"
] | 0 | 1e502295e790ab68990f657492243fd4fb3dfc0a | https://github.com/xinranzhu/GPTune-1/tree/1e502295e790ab68990f657492243fd4fb3dfc0a |
CRF | # 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.utils.data.dataloader
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | adriensas/flair | CRF | false | 9,748 | [
"MIT"
] | 0 | f01b0e7ff9a87d3862acae50aeaffdc8e8b8ac21 | https://github.com/adriensas/flair/tree/f01b0e7ff9a87d3862acae50aeaffdc8e8b8ac21 |
AttentionPool2d | import math
import torch
import numpy as np
import torch.nn
import torch as th
import torch.nn as nn
def count_flops_attn(model, _x, y):
"""
A counter for the `thop` package to count the operations in an
attention operation.
Meant to be used like:
macs, params = thop.profile(
model... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | lukaszbinden/Diffusion-based-Segmentation | AttentionPool2d | false | 12,747 | [
"Apache-2.0"
] | 0 | 43a475e53320adac82838f87ff7fd71f78d8d004 | https://github.com/lukaszbinden/Diffusion-based-Segmentation/tree/43a475e53320adac82838f87ff7fd71f78d8d004 |
Attn | import math
import torch
import torch.nn.functional as F
import torch.nn as nn
class Attn(nn.Module):
def __init__(self, method, hidden_size):
super(Attn, self).__init__()
self.method = method
self.hidden_size = hidden_size
self.attn = nn.Linear(self.hidden_size * 2, hidden_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
from torch._inductor.runtime.... | marvinzh/ConvLab | Attn | false | 12,758 | [
"MIT"
] | 0 | 45ac46b805e064f783b3a1a409b0902ac81da661 | https://github.com/marvinzh/ConvLab/tree/45ac46b805e064f783b3a1a409b0902ac81da661 |
FieldAllTypeBilinear | # 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
from typing import Dic... | p768lwy3/torecsys | FieldAllTypeBilinear | false | 16,227 | [
"MIT"
] | 92 | 2251366268b4fbe6f8c3ab1628fa72a0db043dcd | https://github.com/p768lwy3/torecsys/tree/2251366268b4fbe6f8c3ab1628fa72a0db043dcd |
ScaledDotProductAttention | # 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.... | jahsylla/stochastic-cslr | ScaledDotProductAttention | false | 6,916 | [
"MIT"
] | 1 | d12d48ebec34183d939917cda2d54f38593dcddb | https://github.com/jahsylla/stochastic-cslr/tree/d12d48ebec34183d939917cda2d54f38593dcddb |
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
import torch.nn as nn
from co... | stankevich-mipt/pixiv-tags-to-image | EncoderBlock | false | 4,384 | [
"MIT"
] | 0 | 220a157956296c8a5b183ffe219e7c1929342c39 | https://github.com/stankevich-mipt/pixiv-tags-to-image/tree/220a157956296c8a5b183ffe219e7c1929342c39 |
HFM | # 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.model_zoo
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | NawaNae/ESRT-Huawei | HFM | false | 2,680 | [
"MIT"
] | 0 | edea1c0bafec940dc7ea8e5110c355a83188665c | https://github.com/NawaNae/ESRT-Huawei/tree/edea1c0bafec940dc7ea8e5110c355a83188665c |
FinalTanh | import torch
class FinalTanh(torch.nn.Module):
def __init__(self, input_channels, hidden_channels,
hidden_hidden_channels, num_hidden_layers):
super(FinalTanh, self).__init__()
self.input_channels = input_channels
self.hidden_channels = hidden_channels
self.hidden_hidden_c... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | athon-millane/NeuralCDE | FinalTanh | false | 12,125 | [
"Apache-2.0"
] | 0 | 4196890fe5bf7a69925a12ff35e86f212963be71 | https://github.com/athon-millane/NeuralCDE/tree/4196890fe5bf7a69925a12ff35e86f212963be71 |
Accuracy | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | jokingbear/DM | Accuracy | false | 6,979 | [
"MIT"
] | 1 | 9c4dada1756f3d866455a397511d4f3bacfadc60 | https://github.com/jokingbear/DM/tree/9c4dada1756f3d866455a397511d4f3bacfadc60 |
FermiDiracDecoder | from torch.nn import Module
import torch
from torch.nn.modules.module import Module
import torch.optim
import torch.nn.modules.loss
class FermiDiracDecoder(Module):
"""Fermi Dirac to compute edge probabilities based on distances."""
def __init__(self, r, t):
super(FermiDiracDecoder, self).__init__()
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch.nn import Module
from torch.nn.modules.module import Module
im... | Dee-chen/scGCN | FermiDiracDecoder | false | 7,941 | [
"MIT"
] | 24 | 604818fbaf32ef2fd6ee7bd601f4fe8eff26ac94 | https://github.com/Dee-chen/scGCN/tree/604818fbaf32ef2fd6ee7bd601f4fe8eff26ac94 |
ReactionDotProduction | import torch
import torch.nn as nn
class ReactionDotProduction(nn.Module):
""" Scaled Dot Productionss """
def __init__(self, temperature, attn_dropout=0.1):
super().__init__()
self.temperature = temperature
self.dropout = nn.Dropout(attn_dropout)
self.softmax = nn.Softmax(dim... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Jincheng-Sun/Kylearn-pytorch | ReactionDotProduction | false | 643 | [
"MIT"
] | 0 | e72f2ab45a3f4724e843a27bec37664d3612fdca | https://github.com/Jincheng-Sun/Kylearn-pytorch/tree/e72f2ab45a3f4724e843a27bec37664d3612fdca |
Aggregate | # 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 as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._emp... | AlexanderDKazakov/schnetpack | Aggregate | false | 13 | [
"MIT"
] | 0 | 97b82469d977981b500e439a6c93696d8dac8a3f | https://github.com/AlexanderDKazakov/schnetpack/tree/97b82469d977981b500e439a6c93696d8dac8a3f |
ExtractTensorPatches | # 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.functional as F
from typing import Tuple
from typing import Union
from typing import Optional
from tor... | ChristophReich1996/kornia | ExtractTensorPatches | false | 276 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 35f955b46e8015da1cb9faa28c6943ec2b09cc2a | https://github.com/ChristophReich1996/kornia/tree/35f955b46e8015da1cb9faa28c6943ec2b09cc2a |
CenConv2d | # 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... | Hsuxu/vnet_attention | CenConv2d | false | 13,783 | [
"MIT"
] | 45 | 6958932f3974d268e93bd6443369a3f43c497ed3 | https://github.com/Hsuxu/vnet_attention/tree/6958932f3974d268e93bd6443369a3f43c497ed3 |
gaussian_downsample | # 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
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.a... | Xmaster6y/wgenpatex | gaussian_downsample | false | 18,131 | [
"MIT"
] | 8 | 08079dc131cc2e9c74ee4f9e16cf9b58667f2b07 | https://github.com/Xmaster6y/wgenpatex/tree/08079dc131cc2e9c74ee4f9e16cf9b58667f2b07 |
Dice_Loss | import torch
class Dice_Loss(torch.nn.Module):
"""This is a custom Dice Similarity Coefficient loss function that we use
to the accuracy of the segmentation. it is defined as ;
DSC = 2 * (pred /intersect label) / (pred /union label) for the losss we use
1- DSC so gradient descent leads to better outpu... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | arjunsbalaji/oct | Dice_Loss | false | 1,464 | [
"Apache-2.0"
] | 0 | f21e11f6dda952cd914444512ddadb4141757951 | https://github.com/arjunsbalaji/oct/tree/f21e11f6dda952cd914444512ddadb4141757951 |
ODEfunc | import torch
import torch.nn as nn
def norm(dim):
return nn.GroupNorm(min(32, dim), dim)
class ConcatConv2d(nn.Module):
def __init__(self, dim_in, dim_out, ksize=3, stride=1, padding=0,
dilation=1, groups=1, bias=True, transpose=False):
super(ConcatConv2d, self).__init__()
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
from torch._inductor.runtime.... | gaozhihan/torchdiffeq | ODEfunc | false | 6,741 | [
"MIT"
] | 1 | 414781617d595ba01cc3f23382e25ab890f4ca66 | https://github.com/gaozhihan/torchdiffeq/tree/414781617d595ba01cc3f23382e25ab890f4ca66 |
CFRB | import torch
import torch.nn as nn
from collections import OrderedDict
import torch.nn.functional as F
def sequential(*args):
"""Advanced nn.Sequential.
Args:
nn.Sequential, nn.Module
Returns:
nn.Sequential
"""
if len(args) == 1:
if isinstance(args[0], OrderedDict):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from co... | wwjfsfs/wwjyyds | CFRB | false | 13,137 | [
"MIT"
] | 0 | 80cd6267fde7cd98838078a0d5178a557ceb7414 | https://github.com/wwjfsfs/wwjyyds/tree/80cd6267fde7cd98838078a0d5178a557ceb7414 |
Mean | import torch
class Mean(torch.nn.Module):
def __init__(self, dim):
super().__init__()
self.dim = dim
def forward(self, x):
_std, mean = torch.std_mean(x, self.dim)
return mean
def get_inputs():
return [torch.rand([4, 4, 4, 4, 4])]
def get_init_inputs():
return [[]... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
reinterpret... | Tahlor/glom-pytorch | Mean | false | 1,125 | [
"MIT"
] | 0 | 45b2fc52af5288cd53611e497a70d53ffa303410 | https://github.com/Tahlor/glom-pytorch/tree/45b2fc52af5288cd53611e497a70d53ffa303410 |
GatedRNNCell | import torch
from torch import nn
from functools import partial
def get_initializer(name, activation):
if activation in ['id', 'identity', 'linear', 'modrelu']:
nonlinearity = 'linear'
elif activation in ['relu', 'tanh', 'sigmoid']:
nonlinearity = activation
else:
assert False, f'g... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | tarepan/HiPPO | GatedRNNCell | false | 16,548 | [
"Apache-2.0"
] | 57 | bc23e2dba13da6c307cb5a4ae248c2d2c56d465f | https://github.com/tarepan/HiPPO/tree/bc23e2dba13da6c307cb5a4ae248c2d2c56d465f |
FocalLossBinary | import torch
import torch.jit
import torch.nn.functional as F
import torch.nn.functional
from functools import partial
from torch.nn.modules.loss import _Loss
def reduced_focal_loss(outputs: 'torch.Tensor', targets: 'torch.Tensor',
threshold: 'float'=0.5, gamma: 'float'=2.0, reduction='mean'):
"""
Compute... | 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... | ZhongYingMatrix/nnUNet | FocalLossBinary | false | 12,030 | [
"Apache-2.0"
] | 0 | c3f028e79d4d5c3f2eb58396ffd0ae54048c132b | https://github.com/ZhongYingMatrix/nnUNet/tree/c3f028e79d4d5c3f2eb58396ffd0ae54048c132b |
SequentialPolarizedSelfAttention | import torch
from torch import nn
class SequentialPolarizedSelfAttention(nn.Module):
def __init__(self, channel=512):
super().__init__()
self.ch_wv = nn.Conv2d(channel, channel // 2, kernel_size=(1, 1))
self.ch_wq = nn.Conv2d(channel, 1, kernel_size=(1, 1))
self.softmax_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._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | LiChengChen666/DetectDee | SequentialPolarizedSelfAttention | false | 9,851 | [
"Apache-2.0"
] | 0 | 1e6aaa0d15b1fc12d1342d8a922004e372b5f437 | https://github.com/LiChengChen666/DetectDee/tree/1e6aaa0d15b1fc12d1342d8a922004e372b5f437 |
ShallowConvNet | # 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 ... | CorentinChauvin/style-transfer-KD | ShallowConvNet | false | 5,080 | [
"MIT"
] | 1 | 87bcb2963dbb8d09faf94c74a744f358cafe5427 | https://github.com/CorentinChauvin/style-transfer-KD/tree/87bcb2963dbb8d09faf94c74a744f358cafe5427 |
ScalePredictor | import torch
import torch.nn as nn
class ScalePredictor(nn.Module):
def __init__(self, nz, scale_lr_decay=0.2, scale_bias=1.0):
super(ScalePredictor, self).__init__()
self.pred_layer = nn.Linear(nz, 1)
self.scale_bias = scale_bias
self.scale_lr_decay = scale_lr_decay
def forw... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | eldar/acsm | ScalePredictor | false | 15,297 | [
"Apache-2.0"
] | 52 | 04069e8bb4c12185473dc10c3355e5367fa98968 | https://github.com/eldar/acsm/tree/04069e8bb4c12185473dc10c3355e5367fa98968 |
criticAttention | import torch
import torch.nn as nn
class criticAttention(nn.Module):
"""Calculates attention over the input nodes given the current state."""
def __init__(self, hidden_size):
super(criticAttention, self).__init__()
self.v = nn.Parameter(torch.zeros((1, 1, hidden_size),
requires_gr... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Bachery/Shape-driven-Coordinate-Ordering | criticAttention | false | 16,983 | [
"MIT"
] | 6 | 6afa933a882cbe7a40ddf1de169537eccfe415b7 | https://github.com/Bachery/Shape-driven-Coordinate-Ordering/tree/6afa933a882cbe7a40ddf1de169537eccfe415b7 |
AugCNN | # 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.functional as F
assert_size_stride = torch... | joshnroy/contrastive-rl | AugCNN | false | 12,636 | [
"MIT"
] | 0 | d0e8cd8fd6963983dc62dd282b788002a892704e | https://github.com/joshnroy/contrastive-rl/tree/d0e8cd8fd6963983dc62dd282b788002a892704e |
GDN | # 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.... | AmigoLab/pytorch-msssim | GDN | false | 4,847 | [
"MIT"
] | 1 | 234fde137d8d1b4f9b7a2b94523ecc8f11f54c49 | https://github.com/AmigoLab/pytorch-msssim/tree/234fde137d8d1b4f9b7a2b94523ecc8f11f54c49 |
Conv2dWithConstraint | import torch
import torch.nn as nn
class Conv2dWithConstraint(nn.Conv2d):
def __init__(self, *config, max_norm=1, **kwconfig):
self.max_norm = max_norm
super(Conv2dWithConstraint, self).__init__(*config, **kwconfig)
def forward(self, x):
self.weight.data = torch.renorm(self.weight.da... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | High-East/BCI-ToolBox | Conv2dWithConstraint | false | 17,378 | [
"MIT"
] | 10 | 57015ae5fd008e8636889b9afba49c64c3a35ff3 | https://github.com/High-East/BCI-ToolBox/tree/57015ae5fd008e8636889b9afba49c64c3a35ff3 |
AsymmetricLossOptimized | # 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 torchv... | Coler1994/robust-loss-mlml | AsymmetricLossOptimized | false | 8,210 | [
"MIT"
] | 15 | a68718eba7efa82c3eca79031eeee444f8eb5fa3 | https://github.com/Coler1994/robust-loss-mlml/tree/a68718eba7efa82c3eca79031eeee444f8eb5fa3 |
TransformerLayer | # 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.... | qinwang-ai/Contact-Distil | TransformerLayer | false | 4,193 | [
"Apache-2.0"
] | 0 | 5e98389de70e0d9c4d16bd91ca1326689dc220a6 | https://github.com/qinwang-ai/Contact-Distil/tree/5e98389de70e0d9c4d16bd91ca1326689dc220a6 |
SE | import torch
from torch import nn
class SE(nn.Module):
def __init__(self, channels, se_ratio):
super(SE, self).__init__()
inter_channels = max(1, int(channels * se_ratio))
self.conv1 = nn.Conv2d(channels, inter_channels, (1, 1))
self.silu = nn.SiLU(inplace=True)
self.conv2... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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... | mengzhu0308/EfficientNetV2-PyTorch | SE | false | 12,777 | [
"Apache-2.0"
] | 0 | b9946a4372849d9231a044dcbf697ae17008b467 | https://github.com/mengzhu0308/EfficientNetV2-PyTorch/tree/b9946a4372849d9231a044dcbf697ae17008b467 |
LocallyConnected | import math
import torch
from torch import nn
class LocallyConnected(nn.Module):
"""Local linear layer, i.e. Conv1dLocal() with filter size 1.
Args:
num_linear: num of local linear layers, i.e.
in_features: m1
out_features: m2
bias: whether to include bias or not
Shape:
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.as... | atong01/Graphical-modelling-continuous-time | LocallyConnected | false | 3,142 | [
"MIT"
] | 0 | f1c8d9bc30a44c38fd504e4cce2f7886fc352f92 | https://github.com/atong01/Graphical-modelling-continuous-time/tree/f1c8d9bc30a44c38fd504e4cce2f7886fc352f92 |
Encoder | import torch
import torch.nn as nn
import torch.nn.functional as F
class Encoder(nn.Module):
def __init__(self, state_dim, action_dim):
super(Encoder, self).__init__()
self.encoder_1 = nn.Linear(state_dim, 400)
self.encoder_2 = nn.Linear(400, 300)
self.encoder_3 = nn.Linear(300, 2... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | KuangenZhang/StructuredRL | Encoder | false | 5,462 | [
"MIT"
] | 1 | 9b05e5034ff0e045aabf83786efb0859f08e989a | https://github.com/KuangenZhang/StructuredRL/tree/9b05e5034ff0e045aabf83786efb0859f08e989a |
TransformerDecoderLayer | import math
import torch
from torch import nn
import torch.nn.functional as F
def _normalize(tensor, norm_layer):
"""
Broadcast layer norm
"""
size = tensor.size()
return norm_layer(tensor.view(-1, size[-1])).view(size)
class MultiHeadAttention(nn.Module):
def __init__(self, n_heads, dim, d... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | lemon234071/oc_parlai | TransformerDecoderLayer | false | 3,911 | [
"MIT"
] | 0 | 33a0e57c48e58903cb1666e367a7bb9ef012de0c | https://github.com/lemon234071/oc_parlai/tree/33a0e57c48e58903cb1666e367a7bb9ef012de0c |
NoiseLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch import device
import triton
import 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.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_... | Qingyang-Xu/GANInversion_with_ConsecutiveImgs | NoiseLayer | false | 8,673 | [
"MIT"
] | 23 | 9078a48ec3474dacdd02693b051e3addef1c5697 | https://github.com/Qingyang-Xu/GANInversion_with_ConsecutiveImgs/tree/9078a48ec3474dacdd02693b051e3addef1c5697 |
SimpleASinModule | # 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.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._... | opti-mix/glow | SimpleASinModule | false | 7,378 | [
"Apache-2.0"
] | 1 | 4ba074df5da9822986a23a6679ab592c22660f6d | https://github.com/opti-mix/glow/tree/4ba074df5da9822986a23a6679ab592c22660f6d |
NodeClassifier | # 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... | kevin-kaixu/grass_pytorch | NodeClassifier | false | 15,810 | [
"Apache-2.0"
] | 85 | 1d8dc6dcc0ab3ca029e449f57c37ba3910a4f90a | https://github.com/kevin-kaixu/grass_pytorch/tree/1d8dc6dcc0ab3ca029e449f57c37ba3910a4f90a |
Net | import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(3, 12, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(12, 16, 5)
self.fc1 = nn.Linear(16 * 5 * 5, 120)
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
import torch.nn as nn
assert_... | neal2018/torch_learn | Net | false | 10,603 | [
"MIT"
] | 0 | 80bda3a44952aca6fce7156fe4aecb48ddd602ee | https://github.com/neal2018/torch_learn/tree/80bda3a44952aca6fce7156fe4aecb48ddd602ee |
Add | # 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... | Anon-Artist/kindle | Add | false | 1,947 | [
"MIT"
] | 0 | 7e62e370e0130e6c61db6cdd339a451d5f1f8985 | https://github.com/Anon-Artist/kindle/tree/7e62e370e0130e6c61db6cdd339a451d5f1f8985 |
CategoricalAccuracy | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = t... | Stillerman/MusicTransformer-pytorch | CategoricalAccuracy | false | 14,439 | [
"MIT"
] | 170 | 73abb7cab271beba042b7b6fc06a6a9aaee82e8c | https://github.com/Stillerman/MusicTransformer-pytorch/tree/73abb7cab271beba042b7b6fc06a6a9aaee82e8c |
Intensity | # 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 import device
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from torch.cuda.amp import autocast as aut... | PeppaCat/EfficientZero | Intensity | false | 5,707 | [
"MIT"
] | 1 | b0e98197abfc36ab34faac043ecea9b756b11d54 | https://github.com/PeppaCat/EfficientZero/tree/b0e98197abfc36ab34faac043ecea9b756b11d54 |
LINEAR_LOGSOFTMAX | import torch
import torch.nn as nn
class LINEAR_LOGSOFTMAX(nn.Module):
def __init__(self, input_dim, nclass):
super(LINEAR_LOGSOFTMAX, self).__init__()
self.fc = nn.Linear(input_dim, nclass)
self.logic = nn.LogSoftmax(dim=1)
self.lossfunction = nn.NLLLoss()
def forward(self, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Drkun/Lifelong-Zero-Shot-Learning | LINEAR_LOGSOFTMAX | false | 17,231 | [
"Apache-2.0"
] | 9 | 5cea07c25e14aed1c544c83863f4733a8213ddb0 | https://github.com/Drkun/Lifelong-Zero-Shot-Learning/tree/5cea07c25e14aed1c544c83863f4733a8213ddb0 |
TotalVariation | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | ChristophReich1996/kornia | TotalVariation | false | 283 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 35f955b46e8015da1cb9faa28c6943ec2b09cc2a | https://github.com/ChristophReich1996/kornia/tree/35f955b46e8015da1cb9faa28c6943ec2b09cc2a |
BertPooler | # 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 ... | aeloyq/EasyTransfer | BertPooler | false | 14,749 | [
"Apache-2.0"
] | 806 | f02b1f40109c4031632f3c51bce1cf3d1e906e34 | https://github.com/aeloyq/EasyTransfer/tree/f02b1f40109c4031632f3c51bce1cf3d1e906e34 |
EqualizedLinear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | hejj16/Landscape-StyleGAN | EqualizedLinear | false | 6,793 | [
"MIT"
] | 1 | a93cd32b588ab21da9d7589e705ca6f09db18408 | https://github.com/hejj16/Landscape-StyleGAN/tree/a93cd32b588ab21da9d7589e705ca6f09db18408 |
DPRNNCell | import math
import torch
from torch import Tensor
from torch import nn
import torch.utils.data
import torch.utils.data.distributed
from typing import Optional
class RNNLinear(nn.Linear):
"""Applies a linear transformation to the incoming data: :math:`y = xA^T + b`
This module is the same as a ``torch.nn.Line... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
from to... | bogdan-kulynych/opacus | DPRNNCell | false | 3,241 | [
"Apache-2.0"
] | 0 | e2d13003a179f64920835bc585f3729b8148279f | https://github.com/bogdan-kulynych/opacus/tree/e2d13003a179f64920835bc585f3729b8148279f |
DepthwiseSeparableConv | import torch
import torch.nn as nn
class DepthwiseSeparableConv(nn.Module):
def __init__(self, in_ch, out_ch, k, dim=1, bias=True):
super().__init__()
if dim == 1:
self.depthwise_conv = nn.Conv1d(in_channels=in_ch, out_channels
=in_ch, kernel_size=k, groups=in_ch, padd... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | AlanShaw-GitHub/video-temporal-localization | DepthwiseSeparableConv | false | 18,401 | [
"Apache-2.0"
] | 3 | 111b654970914305b1f74d26f8dcc32d9224aa22 | https://github.com/AlanShaw-GitHub/video-temporal-localization/tree/111b654970914305b1f74d26f8dcc32d9224aa22 |
GCNConv_diag | # 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 sklearn.metrics.pairwise import *
from torch.optim.lr_scheduler import *
as... | STK101/GRCN | GCNConv_diag | false | 17,921 | [
"MIT"
] | 4 | 7389000a13d5969bcc77dc4cf73a4107acc68403 | https://github.com/STK101/GRCN/tree/7389000a13d5969bcc77dc4cf73a4107acc68403 |
ConditionalBatchNorm2d | import torch
import torch.nn as nn
from torch.nn import Parameter
def l2normalize(v, eps=0.0001):
return v / (v.norm() + eps)
class SpectralNorm(nn.Module):
def __init__(self, module, name='weight', power_iterations=1):
super(SpectralNorm, self).__init__()
self.module = module
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 ... | Crazy-Jack/BigGAN-PyTorch | ConditionalBatchNorm2d | false | 351 | [
"MIT"
] | 0 | 1a5644e9c87cc399580c96cfeb180052076888da | https://github.com/Crazy-Jack/BigGAN-PyTorch/tree/1a5644e9c87cc399580c96cfeb180052076888da |
DPFP | # 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 import Module
from torch import nn
import torch.utils.data
import torch.nn.... | techthiyanes/annotated_deep_learning_paper_implementations | DPFP | false | 16,544 | [
"MIT"
] | 3,714 | 8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 | https://github.com/techthiyanes/annotated_deep_learning_paper_implementations/tree/8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 |
CoordConv | # 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... | NguyenTheAn/AdaptiveWingLoss | CoordConv | false | 9,358 | [
"Apache-2.0"
] | 0 | abaade9521c1382739a158f3ad5ce493948add1d | https://github.com/NguyenTheAn/AdaptiveWingLoss/tree/abaade9521c1382739a158f3ad5ce493948add1d |
SE | # 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_... | BoyuGuan/pytorch-cifar | SE | false | 9,046 | [
"MIT"
] | 0 | b96d0e325c614e8351449d63742fea5d085fdd8e | https://github.com/BoyuGuan/pytorch-cifar/tree/b96d0e325c614e8351449d63742fea5d085fdd8e |
ActionApproximation | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C... | Unn20/achtung_die_kurve | ActionApproximation | false | 2,920 | [
"MIT"
] | 0 | e2dbb1752c070cfc398e415d5a427384c0230f3c | https://github.com/Unn20/achtung_die_kurve/tree/e2dbb1752c070cfc398e415d5a427384c0230f3c |
KaggleAccuracy | # 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 Tensor
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | AlessandroRuzzi/Computational-Intelligence-Lab-2021 | KaggleAccuracy | false | 14 | [
"MIT"
] | 0 | ed9dae37618e0ca2f01c4e336df4354e77e00c1f | https://github.com/AlessandroRuzzi/Computational-Intelligence-Lab-2021/tree/ed9dae37618e0ca2f01c4e336df4354e77e00c1f |
BasicBlock | import torch
import torch.nn as nn
import torch.utils.data
class BasicBlock(nn.Module):
expansion = 1
def __init__(self, dim):
super(BasicBlock, self).__init__()
self.conv1 = nn.Conv2d(dim, dim, kernel_size=3, padding=1, bias=False)
self.bn1 = nn.GroupNorm(2, dim, eps=0.0001)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | D-hash-code/ffjord | BasicBlock | false | 11,367 | [
"MIT"
] | 0 | 3647ab35537a8bac3b4dc1e45a593819ac8e2c18 | https://github.com/D-hash-code/ffjord/tree/3647ab35537a8bac3b4dc1e45a593819ac8e2c18 |
DenseBlock | # 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 ... | sagelywizard/snail | DenseBlock | false | 16,353 | [
"MIT"
] | 100 | 1c64787aa970c82f65c3c9d253531d1c2b1bee08 | https://github.com/sagelywizard/snail/tree/1c64787aa970c82f65c3c9d253531d1c2b1bee08 |
BertLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | shrishabh/cs769-assignments | BertLayer | false | 13,002 | [
"MIT"
] | 0 | babce1def0d65728bf1d4e4a725d8939f1d5f9a7 | https://github.com/shrishabh/cs769-assignments/tree/babce1def0d65728bf1d4e4a725d8939f1d5f9a7 |
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.... | frknayk/Reinforcement-Learning-In-Control | PolicyNetwork | false | 6,703 | [
"MIT"
] | 1 | 24c7eb6fa6b6390ee2dd04f25036c37896ecd944 | https://github.com/frknayk/Reinforcement-Learning-In-Control/tree/24c7eb6fa6b6390ee2dd04f25036c37896ecd944 |
SimpleMaxModule | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleMaxModule(torch.nn.Module):
def __init__(self):
super(SimpleMaxModule, self).__init__()
def forward(self, a, b):
return torch.max(a + a, b + b)
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([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
from torch._inductor.runtime import triton_helpers
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.... | briancoutinho/glow | SimpleMaxModule | false | 12,578 | [
"Apache-2.0"
] | 0 | 4c919d60b3c33296c4109aec8020a1733c98f5b5 | https://github.com/briancoutinho/glow/tree/4c919d60b3c33296c4109aec8020a1733c98f5b5 |
CrossAttention | import torch
import torch.nn as nn
class MultiHeadAttention(nn.Module):
def __init__(self, num_q_channels: 'int', num_kv_channels: 'int',
num_heads: 'int', dropout: 'float'):
super().__init__()
self.attention = nn.MultiheadAttention(embed_dim=num_q_channels,
num_heads=num_head... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | krasserm/perceiver-io | CrossAttention | false | 15,857 | [
"Apache-2.0"
] | 133 | 16e1029300304b617c0b0ae8eb06129ec103c755 | https://github.com/krasserm/perceiver-io/tree/16e1029300304b617c0b0ae8eb06129ec103c755 |
compute_transform_losses | import torch
import torch.nn as nn
import torch.nn.functional as F
def _gather_feat(feat, ind, mask=None):
dim = feat.size(2)
ind = ind.unsqueeze(2).expand(ind.size(0), ind.size(1), dim)
feat = feat.gather(1, ind)
if mask is not None:
mask = mask.unsqueeze(2).expand_as(feat)
feat = fea... | 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
... | jaidevshriram/cross-view | compute_transform_losses | false | 15,658 | [
"MIT"
] | 75 | 844b4ded335e31fe3144adb412792221703d5246 | https://github.com/jaidevshriram/cross-view/tree/844b4ded335e31fe3144adb412792221703d5246 |
TinyConvNet3d | import torch
class TinyConvNet3d(torch.nn.Module):
def __init__(self, in_channels=1, out_channels=1):
super().__init__()
self.conv1 = torch.nn.Conv3d(in_channels, 16, 1)
self.nlin1 = torch.nn.ReLU()
self.conv2 = torch.nn.Conv3d(16, 64, 1)
self.nlin2 = torch.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
assert_size_stride = torch._C... | Tomaz-Vieira/tiktorch | TinyConvNet3d | false | 18,019 | [
"MIT"
] | 8 | 2d6803c4ba5e26e4b27bf8af6638040fa4fc5628 | https://github.com/Tomaz-Vieira/tiktorch/tree/2d6803c4ba5e26e4b27bf8af6638040fa4fc5628 |
EdgeFeaturesLayer | import torch
import torch.nn as nn
class EdgeFeaturesLayer(nn.Module):
def __init__(self, d_model, d_edge, h, dropout):
super(EdgeFeaturesLayer, self).__init__()
assert d_model % h == 0
d_model // h
self.linear = nn.Linear(d_edge, 1, bias=False)
with torch.no_grad():
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | odb9402/MAT | EdgeFeaturesLayer | false | 4,106 | [
"MIT"
] | 0 | 95d8083170da2c8ce1f5898b3a556bcf54eac8cc | https://github.com/odb9402/MAT/tree/95d8083170da2c8ce1f5898b3a556bcf54eac8cc |
SeparableConv1d | # 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... | WhiteTeaDragon/hw-asr | SeparableConv1d | false | 1,214 | [
"MIT"
] | 0 | 78a767ab00a743b8d28d1fdad795f066fc0795da | https://github.com/WhiteTeaDragon/hw-asr/tree/78a767ab00a743b8d28d1fdad795f066fc0795da |
CosineLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | vegetablejuiceftw/soft-pointer-networks | CosineLoss | false | 11,074 | [
"MIT"
] | 0 | 9705d9688b6b69db3948172771df4c367165c948 | https://github.com/vegetablejuiceftw/soft-pointer-networks/tree/9705d9688b6b69db3948172771df4c367165c948 |
CharbonnierLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
from t... | hduba/KAIR | CharbonnierLoss | false | 3,581 | [
"MIT"
] | 0 | dbd7596c7e4a4667b9b7baac369fc6c02571fa58 | https://github.com/hduba/KAIR/tree/dbd7596c7e4a4667b9b7baac369fc6c02571fa58 |
mlp | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | AliRoyat/MACS_IQA | mlp | false | 7,666 | [
"Apache-2.0"
] | 16 | d37ac72170dc0271065a7c54273b70ed52aee4b8 | https://github.com/AliRoyat/MACS_IQA/tree/d37ac72170dc0271065a7c54273b70ed52aee4b8 |
ResidualAttentionBlock | # 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.... | Holmes-Alan/TxST | ResidualAttentionBlock | false | 9,256 | [
"MIT"
] | 0 | c5b59a12bbb9e62244c3b608581d5cb9606525e0 | https://github.com/Holmes-Alan/TxST/tree/c5b59a12bbb9e62244c3b608581d5cb9606525e0 |
PixelNorm | import torch
import torch.nn as nn
def pixel_norm(x, eps=1e-06):
"""Pixel Normalization.
This normalization is proposed in:
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Args:
x (torch.Tensor): Tensor to be normalized.
eps (float, optional): Epsilon to av... | 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_... | jiangwenj02/mmgeneration | PixelNorm | false | 12,611 | [
"Apache-2.0"
] | 0 | da9ad377ae19260467fc332ddb88f505c38a915a | https://github.com/jiangwenj02/mmgeneration/tree/da9ad377ae19260467fc332ddb88f505c38a915a |
upsampleLayer | # 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... | GentleDell/DEBOR | upsampleLayer | false | 17,297 | [
"BSD-3-Clause"
] | 4 | cd566f173599fe7419e7baf312f63830c28d5de2 | https://github.com/GentleDell/DEBOR/tree/cd566f173599fe7419e7baf312f63830c28d5de2 |
SimMaxLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = t... | CVI-SZU/CLIMS | SimMaxLoss | false | 17,049 | [
"MIT"
] | 4 | 9d3d0123b625b2c6941069e8fb359019a5cabd59 | https://github.com/CVI-SZU/CLIMS/tree/9d3d0123b625b2c6941069e8fb359019a5cabd59 |
Cblock | # 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.functional
assert_size_stride = torch._C._... | junyuchen245/TransMorph_Transformer_for_Medical_Image_Registration | Cblock | false | 15,745 | [
"MIT"
] | 82 | dfa24a47a564a000aa9b4eea95a6e83a24568359 | https://github.com/junyuchen245/TransMorph_Transformer_for_Medical_Image_Registration/tree/dfa24a47a564a000aa9b4eea95a6e83a24568359 |
TensorClampMax | import torch
class TensorClampMax(torch.nn.Module):
def forward(self, x):
return x.clamp_max(0.1)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | NVIDIA-AI-IOT-private/torch2trt | TensorClampMax | false | 10,527 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
DeepNeuralNetwork | # 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.... | peacefighter1996/PlantRecognisionFromVoxels | DeepNeuralNetwork | false | 12,882 | [
"MIT"
] | 0 | 4cc9a05dbe499d5ccdc6f933c4340c283a938b29 | https://github.com/peacefighter1996/PlantRecognisionFromVoxels/tree/4cc9a05dbe499d5ccdc6f933c4340c283a938b29 |
Actor | 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 Actor(nn.Module):
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed, 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
from torch._inductor.runtime.... | ricklentz/deep-reinforcement-learning | Actor | false | 4,192 | [
"MIT"
] | 0 | 4a034a955c64a630e0fd72f4380d81e2c25a4c68 | https://github.com/ricklentz/deep-reinforcement-learning/tree/4a034a955c64a630e0fd72f4380d81e2c25a4c68 |
Envelope | # 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_... | EricAlcaide/pytorch_geometric | Envelope | false | 2,191 | [
"MIT"
] | 0 | 31cef566cfe22602459155fdf91e9b6ce398bfe7 | https://github.com/EricAlcaide/pytorch_geometric/tree/31cef566cfe22602459155fdf91e9b6ce398bfe7 |
Encoder | import torch
import torch.nn as nn
import torch.nn
import torch.nn.init
import torch.optim
class Model(nn.Module):
""" Class representing sampleable neural network model """
def num_params(self):
""" Get the number of model parameters. """
return sum(p.numel() for p in self.parameters())
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | CBIIT/NCI-DOE-Collab-Pilot2-Autoencoder_MD_Simulation_Data | Encoder | false | 13,430 | [
"MIT"
] | 51 | 2b1213f944cf5f2c60799099a469989a1f0a6d3a | https://github.com/CBIIT/NCI-DOE-Collab-Pilot2-Autoencoder_MD_Simulation_Data/tree/2b1213f944cf5f2c60799099a469989a1f0a6d3a |
GELU | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | SimonCqk/towhee | GELU | false | 9,627 | [
"Apache-2.0"
] | 0 | a187833b1411216106a80a71e6f2c6e68e1be330 | https://github.com/SimonCqk/towhee/tree/a187833b1411216106a80a71e6f2c6e68e1be330 |
LayerNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.optim
assert_size_stride = torch._C._dynamo.... | LouisCastricato/comet-commonsense | LayerNorm | false | 9,274 | [
"Apache-2.0"
] | 0 | dd27c0f1f4a5cc75a11329611721a21a0f5a049f | https://github.com/LouisCastricato/comet-commonsense/tree/dd27c0f1f4a5cc75a11329611721a21a0f5a049f |
Clamp | import torch
from torch import nn
class Clamp(nn.Module):
"""Clamp energy output"""
def forward(self, x):
x = torch.clamp(x, min=0, max=30)
return x
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | kmiec96/mlhep-2021-baseline-track_1 | Clamp | false | 12,678 | [
"Apache-2.0"
] | 0 | 6fd2aa1529734204c522c49dba40fdc4b2bce353 | https://github.com/kmiec96/mlhep-2021-baseline-track_1/tree/6fd2aa1529734204c522c49dba40fdc4b2bce353 |
DPSLTMAdapter | import math
import torch
from torch import Tensor
import torch.nn as nn
from torch.nn.utils.rnn import pad_sequence
import torch.utils.data
import torch.utils.data.distributed
import torch.nn.parallel
from typing import Union
from typing import List
from typing import Tuple
from typing import Optional
from torch.nn.uti... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
from to... | EXAPPAI/opacus | DPSLTMAdapter | false | 2,213 | [
"Apache-2.0"
] | 0 | 11e188a2f03a8a08be51fdf2367cc1387879312a | https://github.com/EXAPPAI/opacus/tree/11e188a2f03a8a08be51fdf2367cc1387879312a |
BERTEmbedding4 | import torch
import torch.nn as nn
from itertools import chain as chain
import torch.utils.data
import torch.hub
import torch.nn.parallel
import torch.optim
class LearnedPositionalEmbedding3(nn.Module):
def __init__(self, d_model, max_len=512):
super().__init__()
pe = torch.zeros(max_len, d_model... | 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 itertools import chain as chain
import torch.utils.data
import torch.hub
import torch.nn.parallel
import torch.op... | byeongjokim/LateTemporalModeling3DCNN_for_sign | BERTEmbedding4 | false | 1,648 | [
"MIT"
] | 0 | e3a802fcf91dc3930aea782464ee34d9b747d3ab | https://github.com/byeongjokim/LateTemporalModeling3DCNN_for_sign/tree/e3a802fcf91dc3930aea782464ee34d9b747d3ab |
ShakeResNeXt | # 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
from torch import... | cdtalley/AutoML | ShakeResNeXt | false | 6,406 | [
"MIT"
] | 1 | 918cda6bb1bd55b4ca974bdcdd59e32b2e28399d | https://github.com/cdtalley/AutoML/tree/918cda6bb1bd55b4ca974bdcdd59e32b2e28399d |
MixerBlock | import torch
import torch.nn.functional as F
from torch import nn
class FeedForward(nn.Module):
def __init__(self, num_features, expansion_factor, dropout):
super().__init__()
num_hidden = expansion_factor * num_features
self.fc1 = nn.Linear(num_features, num_hidden)
self.fc2 = nn... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn.fun... | GimmeSpoon/mlp-singer | MixerBlock | false | 5,240 | [
"MIT"
] | 1 | 36d10a23c46fa7400994ccd063de79ff089efd5e | https://github.com/GimmeSpoon/mlp-singer/tree/36d10a23c46fa7400994ccd063de79ff089efd5e |
SoftDiceLoss | import torch
from torch.nn.modules.loss import _Loss
class SoftDiceLoss(_Loss):
def __init__(self, size_average=None, reduce=None, reduction='mean'):
super(SoftDiceLoss, self).__init__(size_average, reduce, reduction)
def forward(self, y_pred, y_gt):
numerator = torch.sum(y_pred * y_gt)
... | 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... | Will3577/Medical-Transformer | SoftDiceLoss | false | 1,212 | [
"MIT"
] | 0 | e72bfe68fcd55268f57bc7c27b4cbce8029d1b81 | https://github.com/Will3577/Medical-Transformer/tree/e72bfe68fcd55268f57bc7c27b4cbce8029d1b81 |
Embbed2 | # 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.... | ashwinpn/Computer-Vision | Embbed2 | false | 6,260 | [
"MIT"
] | 1 | 9dc3abfe416385171b76e2bad6872e10f36a12b4 | https://github.com/ashwinpn/Computer-Vision/tree/9dc3abfe416385171b76e2bad6872e10f36a12b4 |
PointerAttention | # 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.... | DenDen047/data2text-macro-plan-py | PointerAttention | false | 7,954 | [
"MIT"
] | 20 | bb01ec6e23dab28c1e969f23bd55776b597fb995 | https://github.com/DenDen047/data2text-macro-plan-py/tree/bb01ec6e23dab28c1e969f23bd55776b597fb995 |
LayerNormChannels | # 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_... | onlyrico/lightning-tutorials | LayerNormChannels | false | 12,856 | [
"Apache-2.0"
] | 0 | b5d5c4015422f8c70411e57734d73bb6c1472999 | https://github.com/onlyrico/lightning-tutorials/tree/b5d5c4015422f8c70411e57734d73bb6c1472999 |
_ResampleNorm | # 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
import torch.nn.functional as F
assert_size_stride = torc... | amadejkocbek/darts | _ResampleNorm | false | 12,107 | [
"Apache-2.0"
] | 0 | 074be2a76eee11258da066878c564badf40834e9 | https://github.com/amadejkocbek/darts/tree/074be2a76eee11258da066878c564badf40834e9 |
CoxPHLossSorted | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = t... | nikolase90/pycox | CoxPHLossSorted | false | 7,348 | [
"BSD-2-Clause"
] | 1 | 1c780253da7bab7eba0dc02e1436a68a9b812a66 | https://github.com/nikolase90/pycox/tree/1c780253da7bab7eba0dc02e1436a68a9b812a66 |
Entropy | # 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
... | akira-l/online_mmdetection | Entropy | false | 3,076 | [
"Apache-2.0"
] | 0 | 10c60467a57a605b783486b7fbc508776394ea79 | https://github.com/akira-l/online_mmdetection/tree/10c60467a57a605b783486b7fbc508776394ea79 |
CriticNet | import torch
import torch.nn as nn
import torch.nn.functional as F
class CriticNet(nn.Module):
"""Critic (Value estimator) 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_... | danthe42/drlnd_p2 | CriticNet | false | 1,789 | [
"MIT"
] | 0 | 693813feb7c99f3e01da583e5b67e4f8904639c4 | https://github.com/danthe42/drlnd_p2/tree/693813feb7c99f3e01da583e5b67e4f8904639c4 |
get_loss | import torch
import torch.nn as nn
class get_loss(nn.Module):
def __init__(self):
super(get_loss, self).__init__()
def forward(self, pred, target):
weight = target + 1
loss = nn.BCELoss(weight=weight)(pred, target)
return loss
def get_inputs():
return [torch.rand([4, 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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | ChunhuiChen97/RetinalVesselSegmentation | get_loss | false | 8,930 | [
"MIT"
] | 0 | d291e23b1ad9814070897ef850d0117d67331d70 | https://github.com/ChunhuiChen97/RetinalVesselSegmentation/tree/d291e23b1ad9814070897ef850d0117d67331d70 |
BiReLU | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from torch.autograd.function import InplaceFunction
import torch.nn... | aparna-aketi/Low_Precision_DL | BiReLU | false | 3,119 | [
"MIT"
] | 0 | 5a2489cac5da8f43dd8490a9d871f1ce17f8e7f8 | https://github.com/aparna-aketi/Low_Precision_DL/tree/5a2489cac5da8f43dd8490a9d871f1ce17f8e7f8 |
SmallDecoder1_16x | # 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.... | MingSun-Tse/Collaborative-Distillation | SmallDecoder1_16x | false | 14,015 | [
"MIT"
] | 172 | 915712674af82ff91d926d922c14988cce0430f3 | https://github.com/MingSun-Tse/Collaborative-Distillation/tree/915712674af82ff91d926d922c14988cce0430f3 |
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