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 |
|---|---|---|---|---|---|---|---|---|---|---|
Attention | import math
import torch
from torch import nn
class Attention(nn.Module):
"""A generic attention module for a decoder in seq2seq"""
def __init__(self, dim, use_tanh=False, C=10):
super(Attention, self).__init__()
self.use_tanh = use_tanh
self.project_query = nn.Linear(dim, 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.triton_helpers import libdevice
import math
from to... | BCHoagland/attention-learn-to-route | Attention | false | 4,886 | [
"MIT"
] | 1 | c411289c3b42be5b9c89240f665a029dfc51e034 | https://github.com/BCHoagland/attention-learn-to-route/tree/c411289c3b42be5b9c89240f665a029dfc51e034 |
SoftCrossEntropyLoss | # 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
... | Terminator8758/Precise-ICS-master | SoftCrossEntropyLoss | false | 17,988 | [
"MIT"
] | 4 | 9f4591fee6ab64d9dd91f551355d29562bf663cb | https://github.com/Terminator8758/Precise-ICS-master/tree/9f4591fee6ab64d9dd91f551355d29562bf663cb |
folder | import torch
from torch import nn
import torch.nn.functional as F
import torch.nn.parallel
class folder(nn.Module):
def __init__(self):
super().__init__()
def forward(self, feature_map):
N, _, H, W = feature_map.size()
feature_map = F.unfold(feature_map, kernel_size=3, padding=1)
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.nn.parallel
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | lbin/AdelaiDet | folder | false | 15,870 | [
"BSD-2-Clause"
] | 277 | 9bfb73c51d6e6cd1348cb9ed2174b1cb63bc662a | https://github.com/lbin/AdelaiDet/tree/9bfb73c51d6e6cd1348cb9ed2174b1cb63bc662a |
Argmax | # 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
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._... | ELEKTRONN/elektronn3 | Argmax | false | 13,594 | [
"MIT"
] | 124 | 19c751855dffc67b744cd43e757aa4a5bd577d9b | https://github.com/ELEKTRONN/elektronn3/tree/19c751855dffc67b744cd43e757aa4a5bd577d9b |
AdaFM | import torch
from torch import nn
import torch.utils.data
import torch.utils.data.distributed
class AdaFM(nn.Module):
def __init__(self, in_channel, out_channel, style_dim=0):
super().__init__()
self.style_gama = nn.Parameter(torch.ones(in_channel, out_channel,
1, 1))
self.st... | 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 |
D | import torch
import torch.nn as nn
import torch.nn.functional as F
class D(nn.Module):
def __init__(self):
super(D, self).__init__()
def forward(self, p, z):
z = z.detach()
p = F.normalize(p, p=2, dim=1)
z = F.normalize(z, p=2, dim=1)
return -(p * z).sum(dim=1).mean()... | 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... | leaderj1001/SimSiam | D | false | 15,874 | [
"MIT"
] | 53 | ed36348d3d5a8621674c78c3ed77c1188bd18e16 | https://github.com/leaderj1001/SimSiam/tree/ed36348d3d5a8621674c78c3ed77c1188bd18e16 |
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
from torch._inductor.runtime.... | AndrewZhe/Three-Sentences-Are-All-You-Need | MLP | false | 7,686 | [
"MIT"
] | 21 | afad6f9e700c9a95e03ef200718ebee8e18ca016 | https://github.com/AndrewZhe/Three-Sentences-Are-All-You-Need/tree/afad6f9e700c9a95e03ef200718ebee8e18ca016 |
CNN | # 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_... | NefeliTav/Stock-Prediction | CNN | false | 2,678 | [
"Apache-2.0"
] | 0 | b422a246c762685ceb94c9714a2322fce71186e1 | https://github.com/NefeliTav/Stock-Prediction/tree/b422a246c762685ceb94c9714a2322fce71186e1 |
LinearZeros | # 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.... | appuzanova/Glow-PyTorch | LinearZeros | false | 12,219 | [
"MIT"
] | 0 | 50316b1b242f0f345b2df9e3e4538cfab5a60895 | https://github.com/appuzanova/Glow-PyTorch/tree/50316b1b242f0f345b2df9e3e4538cfab5a60895 |
ResConv | # 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... | AIpakchoi/visualDet3D | ResConv | false | 4,784 | [
"Apache-2.0"
] | 1 | 920f6f8ea44eac4c1896b7d157c015e039ac39f9 | https://github.com/AIpakchoi/visualDet3D/tree/920f6f8ea44eac4c1896b7d157c015e039ac39f9 |
JaccardLoss | import torch
from torch.nn import functional as F
from torch.nn.modules.loss import _Loss
class JaccardLoss(_Loss):
def __init__(self):
super(JaccardLoss, self).__init__()
def forward(self, output, target):
output = F.sigmoid(output)
intersection = torch.sum(output * target)
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn.modules.loss import _Loss
assert_size_stride = torch._C._dynamo.guards.asse... | BloodAxe/segmentation-networks-benchmark | JaccardLoss | false | 7,852 | [
"MIT"
] | 34 | 2e3feb560102230be9369ab442b4a59cc86dff61 | https://github.com/BloodAxe/segmentation-networks-benchmark/tree/2e3feb560102230be9369ab442b4a59cc86dff61 |
ComplexActLayer | import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
class ComplexActLayer(nn.Module):
"""
Activation differently 'real' part and 'img' part
In implemented DCUnet on this repository, Real part is activated to log space.
And Phase(img) part, it is distributed in [-pi, p... | 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_... | ashishpatel26/source_separation | ComplexActLayer | false | 14,900 | [
"Apache-2.0"
] | 269 | 6f755889654d7207fc89ba03a2f49d9ba92df8ea | https://github.com/ashishpatel26/source_separation/tree/6f755889654d7207fc89ba03a2f49d9ba92df8ea |
FLogSigmoid | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | dawnclaude/onnx2keras | FLogSigmoid | false | 15,121 | [
"MIT"
] | 115 | 3d2a47c0a228b91fd434232274e216e491da36e3 | https://github.com/dawnclaude/onnx2keras/tree/3d2a47c0a228b91fd434232274e216e491da36e3 |
SinenetComponent | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_str... | moquan/22_Nov_2018 | SinenetComponent | false | 7,273 | [
"MIT"
] | 1 | eaa81bf5050d74612fe1322abcdb26a0a919e976 | https://github.com/moquan/22_Nov_2018/tree/eaa81bf5050d74612fe1322abcdb26a0a919e976 |
DenseSAGEConv | # 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.... | Cyanogenoid/fspool | DenseSAGEConv | false | 7,964 | [
"MIT"
] | 41 | 7525cb17992ec7a1bb7f92996c2b31a65aa8eba2 | https://github.com/Cyanogenoid/fspool/tree/7525cb17992ec7a1bb7f92996c2b31a65aa8eba2 |
D_DownBlock | # 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 torchvision.transforms import *
assert_size_stride = torch._C._dynamo.guard... | DengZeshuai/DBPN-Pytorch | D_DownBlock | false | 2,555 | [
"MIT"
] | 0 | a90d241a1c4b07830c6d812ad8389d13e8cf05d1 | https://github.com/DengZeshuai/DBPN-Pytorch/tree/a90d241a1c4b07830c6d812ad8389d13e8cf05d1 |
NormalizedPositionError | import torch
import torch.optim
def _normalised_position_error(gt: 'torch.Tensor', pred: 'torch.Tensor'):
l2_norm = torch.linalg.norm(gt - pred, ord=2, dim=-1)
return l2_norm / (torch.linalg.norm(gt, ord=2, dim=-1) + 1e-07)
class NormalizedPositionError(torch.nn.Module):
def __init__(self):
sup... | 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.optim
assert_size_stride = torch._C._dynamo.guards.assert_size_str... | ai-in-motion/moai | NormalizedPositionError | false | 18,340 | [
"Apache-2.0"
] | 10 | e38cac046c059d2e2331ef4883bbabc5a500a5cf | https://github.com/ai-in-motion/moai/tree/e38cac046c059d2e2331ef4883bbabc5a500a5cf |
L1Loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import functools
impor... | CityU-AIM-Group/HTD | L1Loss | false | 17,110 | [
"MIT"
] | 5 | 0be9fd844118c275abc6053b3cbd5ffb589e62ee | https://github.com/CityU-AIM-Group/HTD/tree/0be9fd844118c275abc6053b3cbd5ffb589e62ee |
Highway | # 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 ... | stxxllbu/CS224n-winter-together | Highway | false | 16,504 | [
"Apache-2.0"
] | 468 | eae158ed8e88dc7c8638e25bac4c4fc8eeddcc8c | https://github.com/stxxllbu/CS224n-winter-together/tree/eae158ed8e88dc7c8638e25bac4c4fc8eeddcc8c |
GreedySearch | # 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... | PaccMann/paccmann_chemistry | GreedySearch | false | 18,366 | [
"MIT"
] | 9 | f7e9735aafb936f837c38b5055c654be178f385f | https://github.com/PaccMann/paccmann_chemistry/tree/f7e9735aafb936f837c38b5055c654be178f385f |
Anomaly | import torch
import torch.utils.data
from torch import nn
class Anomaly(nn.Module):
def __init__(self, window=1024):
self.window = window
super(Anomaly, self).__init__()
self.layer1 = nn.Conv1d(window, window, kernel_size=1, stride=1,
padding=0)
self.layer2 = nn.Conv1d... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | G-santini/anomalydetector | Anomaly | false | 11,511 | [
"MIT"
] | 0 | f41be86d357cba7c164a02947b28d5c70ee3e451 | https://github.com/G-santini/anomalydetector/tree/f41be86d357cba7c164a02947b28d5c70ee3e451 |
Conv2dWithConstraint | # 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... | gzoumpourlis/braindecode | Conv2dWithConstraint | false | 12,478 | [
"BSD-3-Clause"
] | 0 | 6bd595a146d0854541ff02b4483c011a394fdf0a | https://github.com/gzoumpourlis/braindecode/tree/6bd595a146d0854541ff02b4483c011a394fdf0a |
SelfAttn | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
import torch.nn.init
import torch as th
class SelfAttn(nn.Module):
def __init__(self, hidden_size):
super(SelfAttn, self).__init__()
self.query = nn.Linear(hidden_size, 1)
def forward(self, keys, value... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ChrisGeishauser/ConvLab-2 | SelfAttn | false | 2,224 | [
"Apache-2.0"
] | 0 | 8f55d033c6e2453fdc092c4f504be3973a55e7ea | https://github.com/ChrisGeishauser/ConvLab-2/tree/8f55d033c6e2453fdc092c4f504be3973a55e7ea |
Vflip | import torch
import torch.nn as nn
def vflip(input: 'torch.Tensor') ->torch.Tensor:
return torch.flip(input, [-2])
class Vflip(nn.Module):
"""Vertically flip a tensor image or a batch of tensor images. Input must
be a tensor of shape (C, H, W) or a batch of tensors :math:`(*, C, H, W)`.
Args:
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | NickleDave/kornia | Vflip | false | 2,691 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 5392651d0bc268da577fa0a49aa50f957289c7dd | https://github.com/NickleDave/kornia/tree/5392651d0bc268da577fa0a49aa50f957289c7dd |
NeuralNetMultiplePositionalArgumentsMultiOutputsWithoutDependency | # 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.... | carefreekk/onnxruntime | NeuralNetMultiplePositionalArgumentsMultiOutputsWithoutDependency | false | 3,268 | [
"MIT"
] | 0 | 484e9de55c109dadbeb552cd6ede21bbdd63b830 | https://github.com/carefreekk/onnxruntime/tree/484e9de55c109dadbeb552cd6ede21bbdd63b830 |
PositionalEncoding1d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guar... | Nintorac/survae_experiments | PositionalEncoding1d | false | 901 | [
"MIT"
] | 0 | d68cc25e2604aab08b53617c1f3ffe4716f166c4 | https://github.com/Nintorac/survae_experiments/tree/d68cc25e2604aab08b53617c1f3ffe4716f166c4 |
AddNorm | import torch
import torch.nn.functional as F
import torch.nn as nn
import torch.functional as F
class TimeDistributedInterpolation(nn.Module):
def __init__(self, output_size: 'int', batch_first: 'bool'=False,
trainable: 'bool'=False):
super().__init__()
self.output_size = output_size
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn.functional as F
import torch.nn as nn
import torch.functional a... | GoldbergData/pytorch-forecasting | AddNorm | false | 2,343 | [
"MIT"
] | 0 | e2ef3794da5d996c9740d932a4f55269bb4003f2 | https://github.com/GoldbergData/pytorch-forecasting/tree/e2ef3794da5d996c9740d932a4f55269bb4003f2 |
DeepSet | # 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... | kiudee/cs-ranking | DeepSet | false | 15,845 | [
"Apache-2.0"
] | 65 | 47cf648fa286c37b9214bbad1926004d4d7d9796 | https://github.com/kiudee/cs-ranking/tree/47cf648fa286c37b9214bbad1926004d4d7d9796 |
Qnet | import random
import torch
import torch.nn as nn
import torch.nn.functional as F
class Qnet(nn.Module):
def __init__(self):
super(Qnet, self).__init__()
self.fc1 = nn.Linear(4, 128)
self.fc2 = nn.Linear(128, 128)
self.fc3 = nn.Linear(128, 2)
def forward(self, x):
x = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 random
import torch.nn... | jinPrelude/minimalRL | Qnet | false | 3,744 | [
"MIT"
] | 0 | 4eba82feac15bb29f4ad715c6c8fd7b11426b840 | https://github.com/jinPrelude/minimalRL/tree/4eba82feac15bb29f4ad715c6c8fd7b11426b840 |
TV_L1LOSS | import torch
import torch.nn as nn
import torch.utils.data
class TV_L1LOSS(nn.Module):
def __init__(self):
super(TV_L1LOSS, self).__init__()
def forward(self, x, y):
size = x.size()
h_tv_diff = torch.abs(x[:, :, 1:, :] - x[:, :, :-1, :] - (y[:, :, 1
:, :] - y[:, :, :-1, :... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch.... | alsgkals2/SRResCGAN | TV_L1LOSS | false | 14,813 | [
"MIT"
] | 81 | a71201a93e1819045f9c7711743812546d3a1f31 | https://github.com/alsgkals2/SRResCGAN/tree/a71201a93e1819045f9c7711743812546d3a1f31 |
SimpleMaxModule | # 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.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.... | YaronBenAtar/glow | SimpleMaxModule | false | 14,677 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
RAddFloat | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | Ilyabasharov/torch2trt | RAddFloat | false | 2,548 | [
"MIT"
] | 0 | 76bf298b3da408509665e23e2494922b131afb10 | https://github.com/Ilyabasharov/torch2trt/tree/76bf298b3da408509665e23e2494922b131afb10 |
SqueezeExcitation | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
asser... | yakhyo/MobileNetV3-pt | SqueezeExcitation | false | 4,599 | [
"MIT"
] | 0 | 1fbc966036ed9f036090b3efe3e700f057aa7dde | https://github.com/yakhyo/MobileNetV3-pt/tree/1fbc966036ed9f036090b3efe3e700f057aa7dde |
ConvBlock | import torch
import torch.nn as nn
class Conv3x3(nn.Module):
"""Layer to pad and convolve input
"""
def __init__(self, in_channels, out_channels, bias=True):
super(Conv3x3, self).__init__()
self.pad = nn.ZeroPad2d(1)
self.conv = nn.Conv2d(int(in_channels), int(out_channels), 3, bi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | HalleyJiang/UniFuse-Unidirectional-Fusion | ConvBlock | false | 8,222 | [
"MIT"
] | 30 | 27a4441fe3d3031d1c9f3eb2d72a3624407d19fc | https://github.com/HalleyJiang/UniFuse-Unidirectional-Fusion/tree/27a4441fe3d3031d1c9f3eb2d72a3624407d19fc |
Linear2 | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | Eudialyte/SepGAT | Linear2 | false | 434 | [
"MIT"
] | 0 | 6ea77714d1b2f2f5d0857cddcc9f1f5f9c0bcf50 | https://github.com/Eudialyte/SepGAT/tree/6ea77714d1b2f2f5d0857cddcc9f1f5f9c0bcf50 |
BCE_disc_sm_v5 | # AOT ID: ['1_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
... | Sampson-Lee/SIB-Net | BCE_disc_sm_v5 | false | 2,819 | [
"MIT"
] | 0 | 650399082e9237327fa38168ccfc7d48153a1db5 | https://github.com/Sampson-Lee/SIB-Net/tree/650399082e9237327fa38168ccfc7d48153a1db5 |
NormalDiagonalCovarianceLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
im... | BUTSpeechFIT/beer | NormalDiagonalCovarianceLayer | false | 16,982 | [
"MIT"
] | 6 | 43fb9027a859db28d2f2f8709260ca2ce9501e25 | https://github.com/BUTSpeechFIT/beer/tree/43fb9027a859db28d2f2f8709260ca2ce9501e25 |
ForegroundDTConsistency | import torch
from typing import Optional
import torch.utils.data
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
class ForegroundDTConsistency(nn.Module):
"""Consistency regularization between the binary foreground mask and
signed distance transform.
Args:
pred1 (to... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | Atharva-Peshkar/pytorch_connectomics | ForegroundDTConsistency | false | 13,315 | [
"MIT"
] | 99 | 8eccd9640a9a454d4df095a3529a030e58f882f5 | https://github.com/Atharva-Peshkar/pytorch_connectomics/tree/8eccd9640a9a454d4df095a3529a030e58f882f5 |
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
from torch import nn
a... | wanghao15536870732/plants_disease_classify | FocalLoss | false | 4,521 | [
"Apache-2.0"
] | 0 | 6d0d1d39f0ec15fc2bd523142c5c403a1577da84 | https://github.com/wanghao15536870732/plants_disease_classify/tree/6d0d1d39f0ec15fc2bd523142c5c403a1577da84 |
LinearModel | import torch
import torch.nn as nn
class LinearModel(nn.Module):
def __init__(self, input_size, output_size, hidden_size):
super(LinearModel, self).__init__()
self.linear1 = nn.Linear(input_size, hidden_size)
self.linear2 = nn.Linear(hidden_size, hidden_size)
self.linear3 = nn.Lin... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | VVKot/mlinseconds-vote-prediction | LinearModel | false | 2,940 | [
"MIT"
] | 0 | c869ae428fb8d5e83f0a47468722da968aed28c6 | https://github.com/VVKot/mlinseconds-vote-prediction/tree/c869ae428fb8d5e83f0a47468722da968aed28c6 |
StdConv2d | import torch
import torch.nn as nn
import torch.utils
import torch.nn.functional as F
class StdConv2d(nn.Conv2d):
def forward(self, x):
w = self.weight
v, m = torch.var_mean(w, dim=[1, 2, 3], keepdim=True, unbiased=False)
w = (w - m) / torch.sqrt(v + 1e-10)
return F.conv2d(x, w, 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 ... | dustasa/senior_software_HW | StdConv2d | false | 3,443 | [
"Apache-2.0"
] | 0 | 767d1d7bbd5e7d7414c17fa14b92b942e53d84ed | https://github.com/dustasa/senior_software_HW/tree/767d1d7bbd5e7d7414c17fa14b92b942e53d84ed |
L1 | # 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
... | B06901052/deep-stabilization | L1 | false | 99 | [
"Apache-2.0"
] | 0 | b6030b463cf1f1128660e900669f43e742aa2651 | https://github.com/B06901052/deep-stabilization/tree/b6030b463cf1f1128660e900669f43e742aa2651 |
KLDivLoss | import torch
from torchvision.transforms import *
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
class KLDivLoss(nn.Module):
def __init__(self):
super(KLDivLoss, self).__init__()
def forward(self, pred, label):
T = 3
predict = F.log_softmax(... | 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 torchvision.trans... | mangye16/Cross-Modal-Re-ID-baseline | KLDivLoss | false | 15,990 | [
"MIT"
] | 249 | 26bc0ce088eb97867ff489dceda386b8092b9fde | https://github.com/mangye16/Cross-Modal-Re-ID-baseline/tree/26bc0ce088eb97867ff489dceda386b8092b9fde |
Emitter | import torch
from torch import nn
class Emitter(nn.Module):
def __init__(self, input_dim, hidden_dim, output_dim):
super(Emitter, self).__init__()
self.lin_input_to_hidden = nn.Linear(input_dim, hidden_dim)
self.lin_hidden_to_hidden = nn.Linear(hidden_dim, hidden_dim)
self.lin_hid... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | abacoelho/variational-poisson-rnn | Emitter | false | 18,210 | [
"MIT"
] | 5 | abf77f79fc64be75ae9102ec8d537f77ed9c5f8f | https://github.com/abacoelho/variational-poisson-rnn/tree/abf77f79fc64be75ae9102ec8d537f77ed9c5f8f |
HLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from 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.autograd.gr... | HastingsGreer/mermaid | HLoss | false | 13,760 | [
"Apache-2.0"
] | 120 | bd13c5fc427eb8cd9054973a8eaaeb302078182d | https://github.com/HastingsGreer/mermaid/tree/bd13c5fc427eb8cd9054973a8eaaeb302078182d |
dnn | import torch
import torch.nn as nn
import torch.nn.functional as F
class dnn(nn.Module):
def weight_init(self):
nn.init.xavier_uniform_(self.fc1.weight)
nn.init.xavier_uniform_(self.fc2.weight)
nn.init.xavier_uniform_(self.fc3.weight)
nn.init.xavier_uniform_(self.out.weight)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | Harshitmalaviya/whisper-to-normal-speech-conversion | dnn | false | 8,265 | [
"MIT"
] | 23 | a6d411b27a3c5cc4ad12e3968350b22d88b9b4d9 | https://github.com/Harshitmalaviya/whisper-to-normal-speech-conversion/tree/a6d411b27a3c5cc4ad12e3968350b22d88b9b4d9 |
MSECompositionLoss | import functools
import torch
import torch.nn as nn
from torch.nn import functional as F
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Returns:
Tensor: Reduced lo... | 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 functools
import torch.nn as nn
from torch.nn import functional as F
assert_size_s... | Sardhendu/mmediting | MSECompositionLoss | false | 9,884 | [
"Apache-2.0"
] | 0 | 623b59ac758d856abc9fab7e845beeab61074d8f | https://github.com/Sardhendu/mmediting/tree/623b59ac758d856abc9fab7e845beeab61074d8f |
PositionWiseFFN | import torch
from torch import nn
from torch.nn.functional import relu
class PositionWiseFFN(nn.Module):
def __init__(self, model_dim, dropout=0.0):
super().__init__()
dff = model_dim * 4
self.l = nn.Linear(model_dim, dff)
self.o = nn.Linear(dff, model_dim)
self.dropout = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | richardzhangy26/NLP-Tutorials | PositionWiseFFN | false | 10,679 | [
"MIT"
] | 0 | ddf123853c53cef1142207c3a4fb9aa6ac87febd | https://github.com/richardzhangy26/NLP-Tutorials/tree/ddf123853c53cef1142207c3a4fb9aa6ac87febd |
Sentence_Maxpool | import torch
import torch as th
import torch.nn.functional as F
import torch.nn as nn
class Sentence_Maxpool(nn.Module):
def __init__(self, word_dimension, output_dim, relu=True):
super(Sentence_Maxpool, self).__init__()
self.fc = nn.Linear(word_dimension, output_dim)
self.out_dim = outpu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | ErinZhang1998/howto100m-erin | Sentence_Maxpool | false | 2,203 | [
"Apache-2.0"
] | 0 | 1152ea0fe328d20fcf2218a1d548644881632656 | https://github.com/ErinZhang1998/howto100m-erin/tree/1152ea0fe328d20fcf2218a1d548644881632656 |
OrientedIOUloss | # 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
import torch.utils.data
assert_size_stride = torch._C._dynamo.guard... | kuazhangxiaoai/YOLOX | OrientedIOUloss | false | 3,856 | [
"Apache-2.0"
] | 0 | 7aff49b25a8a80c4c33e941da416500eda72b1a2 | https://github.com/kuazhangxiaoai/YOLOX/tree/7aff49b25a8a80c4c33e941da416500eda72b1a2 |
Network | import torch
import torch.nn as nn
import torch.nn.functional as F
class Network(nn.Module):
def __init__(self):
nn.Module.__init__(self)
self.l1 = nn.Linear(4, 24)
self.l5 = nn.Linear(24, 2)
def forward(self, x):
x = F.relu(self.l1(x))
x = self.l5(x)
return x... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | alexljenkins/reinforcement-learning-agents | Network | false | 9,696 | [
"MIT"
] | 0 | d5bdfad56c9b095d5bb0ac22ca69e19553327416 | https://github.com/alexljenkins/reinforcement-learning-agents/tree/d5bdfad56c9b095d5bb0ac22ca69e19553327416 |
ResidualBlock | # 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
@triton.jit
def triton_poi_fused_add_0(in_ptr0, out_... | d222nguy/gcn_research | ResidualBlock | false | 3,369 | [
"MIT"
] | 0 | 83ced4f7d9f7840e48900e62c1eabec0444c5fa2 | https://github.com/d222nguy/gcn_research/tree/83ced4f7d9f7840e48900e62c1eabec0444c5fa2 |
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.... | chenxiaoyu523/FEAT3D | ScaledDotProductAttention | false | 1,685 | [
"MIT"
] | 0 | ba45ba7c26628a7cc0070b010f4f33893cdac926 | https://github.com/chenxiaoyu523/FEAT3D/tree/ba45ba7c26628a7cc0070b010f4f33893cdac926 |
MVloss | import torch
import torch.distributed
import torch.nn as nn
class MVloss(nn.Module):
def __init__(self):
super(MVloss, self).__init__()
def forward(self, xRA0, xRA20, xRA_20, target, wRA0, wRA20, wRA_20):
criterion_MV = torch.nn.CrossEntropyLoss()
loss_multiview = criterion_MV(wRA0 *... | 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.distribut... | muzammilbehzad/MultiviewTransformer | MVloss | false | 10,562 | [
"MIT"
] | 0 | c6c7c34c8d156e187a986e35268e1fc4a5d0175d | https://github.com/muzammilbehzad/MultiviewTransformer/tree/c6c7c34c8d156e187a986e35268e1fc4a5d0175d |
DecoderLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | chandar-lab/CriticalGradientOptimization | DecoderLayer | false | 6,451 | [
"MIT"
] | 1 | 1af4b1df40489991289bb50bb69859a00b2c97c6 | https://github.com/chandar-lab/CriticalGradientOptimization/tree/1af4b1df40489991289bb50bb69859a00b2c97c6 |
ConvNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | DenXX/fvcore | ConvNet | false | 2,217 | [
"Apache-2.0"
] | 0 | 4b91cf092f4f5d379b2c93398780a3b5755e7179 | https://github.com/DenXX/fvcore/tree/4b91cf092f4f5d379b2c93398780a3b5755e7179 |
PKTCosSim | import torch
import torch.nn as nn
import torch._utils
from itertools import product as product
import torch.utils.data.distributed
class PKTCosSim(nn.Module):
"""
Learning Deep Representations with Probabilistic Knowledge Transfer
http://openaccess.thecvf.com/content_ECCV_2018/papers/Nikolaos_Passalis_Learning... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
im... | wangxianliang/FaceX-Zoo | PKTCosSim | false | 13,095 | [
"Apache-2.0"
] | 0 | b0555c88a0350fa7b59c317f3a171f551fef4e6e | https://github.com/wangxianliang/FaceX-Zoo/tree/b0555c88a0350fa7b59c317f3a171f551fef4e6e |
RecursiveNet | import torch
import torch.nn as nn
class RecursiveNet(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(64, 64, 3, 1, 1)
def forward(self, x, args1=None, args2=None):
del args1, args2
for _ in range(3):
out = self.conv1(x)
out =... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | EarthLab-Luxembourg/torch-summary | RecursiveNet | false | 418 | [
"MIT"
] | 0 | 8ef25aea5e9fb075df27e1e0c77bad56a7254397 | https://github.com/EarthLab-Luxembourg/torch-summary/tree/8ef25aea5e9fb075df27e1e0c77bad56a7254397 |
SimpleFmodModule | # 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._... | andreas-hommel/glow | SimpleFmodModule | false | 3,323 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
Reorg | # 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... | ahmedelhodaiby/HandMesh | Reorg | false | 9,897 | [
"MIT"
] | 0 | d86ec322b7627c5756bd9ae9e152bcd4f2debfa6 | https://github.com/ahmedelhodaiby/HandMesh/tree/d86ec322b7627c5756bd9ae9e152bcd4f2debfa6 |
Linear3D | import math
import torch
import torch as th
from torch.nn import Parameter
def functional_linear3d(input, weight, bias=None):
"""
Apply a linear transformation to the incoming data: :math:`y = xA^T + b`.
Shape:
- Input: :math:`(N, *, in\\_features)` where `*` means any number of
additio... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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 as th
from torch.nn import Parameter
assert_size_stride... | TheSignPainter/CausalDiscoveryToolbox | Linear3D | false | 14,477 | [
"MIT"
] | 528 | 33eae18184905e505be978b08003b9477bf38e0c | https://github.com/TheSignPainter/CausalDiscoveryToolbox/tree/33eae18184905e505be978b08003b9477bf38e0c |
QuantizableHSwish | # 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
import torch.quantization
assert_size_stride = torch._C._dynamo.gua... | HwangJohn/model_compression | QuantizableHSwish | false | 13,834 | [
"MIT"
] | 216 | 1df40c8a531313cc9e79255f4477f39d66d9b849 | https://github.com/HwangJohn/model_compression/tree/1df40c8a531313cc9e79255f4477f39d66d9b849 |
VOC_VGG16_DeepLabV2 | import torch
from torch import nn
class FCReLUDrop(nn.Sequential):
def __init__(self, in_ch, out_ch, kernel_size, dilation, padding,
layer_idx, branch_idx):
super(FCReLUDrop, self).__init__()
self.add_module(f'fc{layer_idx}_{branch_idx}', nn.Conv2d(in_ch,
out_ch, 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
from torch import nn
assert_s... | HAL-42/DeepLabV2YQ | VOC_VGG16_DeepLabV2 | false | 706 | [
"Apache-2.0"
] | 0 | 96bfcf1055da7adeb4a7c1ed841f6ec29957be59 | https://github.com/HAL-42/DeepLabV2YQ/tree/96bfcf1055da7adeb4a7c1ed841f6ec29957be59 |
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.... | andreas-hommel/glow | SimpleMaxModule | false | 3,338 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
AUXModule | # 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_... | gorogoroyasu/mlcomp | AUXModule | false | 15,440 | [
"Apache-2.0"
] | 166 | fc6572ca5b226b35df97f13badd4420b30468a3b | https://github.com/gorogoroyasu/mlcomp/tree/fc6572ca5b226b35df97f13badd4420b30468a3b |
MetaAconC | import torch
import torch.nn as nn
class MetaAconC(nn.Module):
""" ACON activation (activate or not)
MetaAconC: (p1*x-p2*x) * sigmoid(beta*(p1*x-p2*x)) + p2*x, beta is generated by a small network
according to "Activate or Not: Learning Customized Activation" <https://arxiv.org/pdf/2009.04759.pdf>.
""... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | LTTBasic/lecttue-diagonosis | MetaAconC | false | 767 | [
"MIT"
] | 0 | a9573f79da1fa8dcdd649bfd819ffad67ecad309 | https://github.com/LTTBasic/lecttue-diagonosis/tree/a9573f79da1fa8dcdd649bfd819ffad67ecad309 |
ScaledDotProductAttention | # 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.... | LiChengChen666/DetectDee | ScaledDotProductAttention | false | 9,824 | [
"Apache-2.0"
] | 0 | 1e6aaa0d15b1fc12d1342d8a922004e372b5f437 | https://github.com/LiChengChen666/DetectDee/tree/1e6aaa0d15b1fc12d1342d8a922004e372b5f437 |
DenseGraphConv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from torch.nn import Parameter
import torch.utils.data
assert_size_s... | shnhrtkyk/pytorch_geometric | DenseGraphConv | false | 10,810 | [
"MIT"
] | 0 | b971fd2ebba10736e6398d6305757be2d81ca681 | https://github.com/shnhrtkyk/pytorch_geometric/tree/b971fd2ebba10736e6398d6305757be2d81ca681 |
NeuralNetMultiplePositionalArguments | # 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
import torch.... | thilow/onnxruntime | NeuralNetMultiplePositionalArguments | false | 11,019 | [
"MIT"
] | 0 | 1a3ddf0714e1bdf9b807a342eee5f6e160ad1ec9 | https://github.com/thilow/onnxruntime/tree/1a3ddf0714e1bdf9b807a342eee5f6e160ad1ec9 |
Net | import torch
class Net(torch.nn.Module):
def __init__(self, n_input, n_hidden, n_output):
super(Net, self).__init__()
self.layer1 = torch.nn.Linear(n_input, n_hidden)
self.layer2 = torch.nn.Linear(n_hidden, n_hidden)
self.layer3 = torch.nn.Linear(n_hidden, n_hidden)
self.l... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | kimukook/variable_length_oscillating_pendulum | Net | false | 3,837 | [
"MIT"
] | 0 | 486aa95fe4b9cbaa6cbeb542209259484f48e191 | https://github.com/kimukook/variable_length_oscillating_pendulum/tree/486aa95fe4b9cbaa6cbeb542209259484f48e191 |
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 import triton_helpers
from torch._inductor.runtime.... | eminem171333491/PaddleOCR2Pytorch | Encoder | false | 3,471 | [
"Apache-2.0"
] | 0 | ec466bb3a689eccb9290e9f80812a45301d3b030 | https://github.com/eminem171333491/PaddleOCR2Pytorch/tree/ec466bb3a689eccb9290e9f80812a45301d3b030 |
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
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | YiwenShaoStephen/snowfall | SeparableConv1D | false | 14,694 | [
"Apache-2.0"
] | 145 | 949226f35b29c629cb03cae36fa43da5993d27a3 | https://github.com/YiwenShaoStephen/snowfall/tree/949226f35b29c629cb03cae36fa43da5993d27a3 |
MultiHeadAttention | import math
import torch
from torch import nn
class ScaleDotProductAttention(nn.Module):
"""
compute scale dot product attention
Query : given sentence that we focused on (decoder)
Key : every sentence to check relationship with Qeury(encoder)
Value : every sentence same with Key (encoder)
""... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | bsgiovanini/transformer | MultiHeadAttention | false | 1,589 | [
"Apache-2.0"
] | 0 | e128fa862f1b3d17d7b92df169a2bbee3f08366f | https://github.com/bsgiovanini/transformer/tree/e128fa862f1b3d17d7b92df169a2bbee3f08366f |
ResidualAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | rushirajsherlocked/External-Attention-pytorch | ResidualAttention | false | 4,303 | [
"MIT"
] | 0 | 7d6814b2d90909adf81c62f3f8a89e30a59d6481 | https://github.com/rushirajsherlocked/External-Attention-pytorch/tree/7d6814b2d90909adf81c62f3f8a89e30a59d6481 |
Stack | # 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
from typing import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dyn... | HughMun/MultiBench | Stack | false | 13,803 | [
"MIT"
] | 148 | d5712a0815a9486b0e0c76b54cd63c880188fc8e | https://github.com/HughMun/MultiBench/tree/d5712a0815a9486b0e0c76b54cd63c880188fc8e |
SelfAttn | # 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.... | haojiepan1/CrossWOZ | SelfAttn | false | 6,789 | [
"Apache-2.0"
] | 1 | 6d7b4c4cfb73a528b76074764687906abecc90b6 | https://github.com/haojiepan1/CrossWOZ/tree/6d7b4c4cfb73a528b76074764687906abecc90b6 |
SoftKLDivLoss | import torch
from torch import Tensor
from torch.nn import functional as F
class SoftKLDivLoss(torch.nn.Module):
def __init__(self, temp=20.0, reduction='batchmean', log_target=False
) ->None:
super(SoftKLDivLoss, self).__init__()
self.temp = temp
self.reduction = reduction
... | 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
assert_size... | PiaCuk/KD_Lib | SoftKLDivLoss | false | 14,209 | [
"MIT"
] | 360 | 153299d484e4c6b33793749709dbb0f33419f190 | https://github.com/PiaCuk/KD_Lib/tree/153299d484e4c6b33793749709dbb0f33419f190 |
TensorSigmoid | import torch
class TensorSigmoid(torch.nn.Module):
def __init__(self):
super(TensorSigmoid, self).__init__()
def forward(self, x):
return x.sigmoid()
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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | PogChamper/torch2trt | TensorSigmoid | false | 14,273 | [
"MIT"
] | 3,363 | 43b12627ec0de4d212efb6d02b07570205085ccc | https://github.com/PogChamper/torch2trt/tree/43b12627ec0de4d212efb6d02b07570205085ccc |
T5DenseReluDense | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint
class T5DenseReluDense(nn.Module):
def __init__(self, config):
super().__init__()
self.wi = nn.Linear(config.d_model, config.d_ff, bias=False)
sel... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | Hzfinfdu/Black-Box-Tuning | T5DenseReluDense | false | 4,073 | [
"MIT"
] | 0 | 64eb5505875dc1b242c6f0a2a2f07e4000c24cb4 | https://github.com/Hzfinfdu/Black-Box-Tuning/tree/64eb5505875dc1b242c6f0a2a2f07e4000c24cb4 |
Encoder | import torch
import torch.nn as nn
import torch.nn.functional as F
class Scaled_Dot_Product_Attention(nn.Module):
"""Scaled Dot-Product Attention """
def __init__(self):
super(Scaled_Dot_Product_Attention, self).__init__()
def forward(self, Q, K, V, scale=None):
"""
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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | tianjiansmile/Chinese-Text-Classification-Pytorch | Encoder | false | 10,914 | [
"MIT"
] | 0 | 05cc211b161f61e6bb32ab185dadcffec2f5b5de | https://github.com/tianjiansmile/Chinese-Text-Classification-Pytorch/tree/05cc211b161f61e6bb32ab185dadcffec2f5b5de |
FirstNet | import torch
import torch.nn as nn
import torch.nn.functional as F
class FirstNet(nn.Module):
def __init__(self):
super(FirstNet, self).__init__()
self.conv1 = nn.Conv2d(in_channels=1, out_channels=64, kernel_size=
3, padding=1, stride=1)
self.conv2 = nn.Conv2d(64, 128, 3, pad... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | Koukyosyumei/AIJack | FirstNet | false | 8,442 | [
"MIT"
] | 24 | 9545d3828907b54965ede85e0e12cb32eef54294 | https://github.com/Koukyosyumei/AIJack/tree/9545d3828907b54965ede85e0e12cb32eef54294 |
Mnist_CNN | # 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 ... | Justin-A/PyTorch-tutorials-kr | Mnist_CNN | false | 5,427 | [
"BSD-3-Clause"
] | 1 | 0d8e407523e5e75de0081becf800b82b37eb912f | https://github.com/Justin-A/PyTorch-tutorials-kr/tree/0d8e407523e5e75de0081becf800b82b37eb912f |
ResidualBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | Miffyli/minecraft-bc-2020 | ResidualBlock | false | 8,570 | [
"MIT"
] | 11 | 94f8706e547474a2ed8cacd41bb20e59f672215f | https://github.com/Miffyli/minecraft-bc-2020/tree/94f8706e547474a2ed8cacd41bb20e59f672215f |
LCTGate | import torch
import torch.nn as nn
class LCTGate(nn.Module):
def __init__(self, channels, groups=16):
super(LCTGate, self).__init__()
assert channels > 0
assert groups > 0
while channels % groups != 0:
groups //= 2
self.gn = nn.GroupNorm(groups, channels, affin... | 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_... | daniil-lyakhov/deep-object-reid | LCTGate | false | 1,784 | [
"Apache-2.0"
] | 0 | b0f7d6a2d4cff8c417a66d82c09d16788d81ec67 | https://github.com/daniil-lyakhov/deep-object-reid/tree/b0f7d6a2d4cff8c417a66d82c09d16788d81ec67 |
ScaledTanh | import torch
from torch import Tensor
import torch.nn as nn
from torch import tanh
class ScaledTanh(nn.Module):
def __init__(self, factor):
super(ScaledTanh, self).__init__()
self.factor = factor
def forward(self, inputs: 'Tensor') ->Tensor:
return tanh(inputs) * self.factor
def ge... | 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_... | MhmdSyd/celldetection | ScaledTanh | false | 8,566 | [
"Apache-2.0"
] | 26 | 93e706953dc32eb694345179d5dcca5cfd9ff41b | https://github.com/MhmdSyd/celldetection/tree/93e706953dc32eb694345179d5dcca5cfd9ff41b |
Atten | # 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.... | NTDXYG/EL-CodeBert | Atten | false | 5,639 | [
"MIT"
] | 1 | 62a2364db567f8887a339c40e2c7f7807bedfd50 | https://github.com/NTDXYG/EL-CodeBert/tree/62a2364db567f8887a339c40e2c7f7807bedfd50 |
Gaussian | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.utils.tensorboard
import torch.utils.data
assert_size_stride... | isayev/torchani | Gaussian | false | 12,642 | [
"MIT"
] | 0 | f8edffe384e2cb2eebe3a7e04faa01b6f5e26b37 | https://github.com/isayev/torchani/tree/f8edffe384e2cb2eebe3a7e04faa01b6f5e26b37 |
MidNet2 | import torch
import torch.nn as nn
class MidNet2(nn.Module):
def forward(self, x_in):
"""Network with dilation rate 2
:param x_in: input convolutional features
:returns: processed convolutional features
:rtype: Tensor
"""
x = self.lrelu(self.conv1... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | sjmoran/CURL | MidNet2 | false | 16,480 | [
"BSD-3-Clause"
] | 125 | 919e519717b66e14d92ac6fa404c328ee3f254a5 | https://github.com/sjmoran/CURL/tree/919e519717b66e14d92ac6fa404c328ee3f254a5 |
RMulInt | import torch
class RMulInt(torch.nn.Module):
def __init__(self):
super(RMulInt, self).__init__()
def forward(self, x):
return 10 * 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | PogChamper/torch2trt | RMulInt | false | 14,205 | [
"MIT"
] | 3,363 | 43b12627ec0de4d212efb6d02b07570205085ccc | https://github.com/PogChamper/torch2trt/tree/43b12627ec0de4d212efb6d02b07570205085ccc |
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | huangzsdy/pytorch_basic_learning | Net | false | 3,686 | [
"Apache-2.0"
] | 0 | 7880bc3fcee1d38623d93fa2a36482ccde0e335a | https://github.com/huangzsdy/pytorch_basic_learning/tree/7880bc3fcee1d38623d93fa2a36482ccde0e335a |
ConvDropoutLayerNorm | # 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... | ncoop57/transformers | ConvDropoutLayerNorm | false | 4,058 | [
"Apache-2.0"
] | 0 | d7e156bd1ae2467e9ea1dbc44f31da0ed2296aee | https://github.com/ncoop57/transformers/tree/d7e156bd1ae2467e9ea1dbc44f31da0ed2296aee |
ConvDenoiser | import torch
import torch.nn.init
import torch.nn as nn
import torch.nn.functional as F
class ConvDenoiser(nn.Module):
def __init__(self):
super(ConvDenoiser, self).__init__()
self.conv1 = nn.Conv2d(3, 32, 3, padding=1)
self.conv2 = nn.Conv2d(32, 16, 3, padding=1)
self.conv3 = 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 import triton_helpers
import torch.nn.init
import t... | joydeba/autocount | ConvDenoiser | false | 3,791 | [
"MIT"
] | 0 | 52ddb47726fa34d5f54e2850dc6690b67c768728 | https://github.com/joydeba/autocount/tree/52ddb47726fa34d5f54e2850dc6690b67c768728 |
PropMaxPool | # 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.parallel
import torch.nn as nn
import torch.utils.data
import torch.backe... | MicroTensor-ai/episodic-memory | PropMaxPool | false | 13,215 | [
"MIT"
] | 0 | 295a3752ab94c7a6f45355aa2c54bffbf84b574f | https://github.com/MicroTensor-ai/episodic-memory/tree/295a3752ab94c7a6f45355aa2c54bffbf84b574f |
MockAccuracy | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | NestLakerJasonLIN/MusicTransformer-pytorch | MockAccuracy | false | 5,654 | [
"MIT"
] | 1 | 5f183374833ff6b7e17f3a24e3594dedd93a5fe5 | https://github.com/NestLakerJasonLIN/MusicTransformer-pytorch/tree/5f183374833ff6b7e17f3a24e3594dedd93a5fe5 |
MLP | import torch
from torch import nn
import torch.utils
class MLP(torch.nn.Module):
def __init__(self, input_dim, output_dim):
super(MLP, self).__init__()
self.d1 = torch.nn.Linear(input_dim, 32)
self.d2 = torch.nn.Linear(32, 16)
self.d3 = torch.nn.Linear(16, output_dim)
self... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | MichaelLee-ceo/FedSAUC | MLP | false | 5,596 | [
"Apache-2.0"
] | 1 | 8c00008772213562ff6a07bf9fa92c3831713118 | https://github.com/MichaelLee-ceo/FedSAUC/tree/8c00008772213562ff6a07bf9fa92c3831713118 |
GridReduction1 | import torch
from torch.nn import functional as F
import torch.nn as nn
class Conv2d(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, batch_norm=
False, **kwargs):
super(Conv2d, self).__init__()
self.conv = nn.Conv2d(in_channels, out_channels, kernel_size, **kwargs)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | Hiroaki-Ozaki/modelib-classification | GridReduction1 | false | 17,395 | [
"WTFPL"
] | 10 | 11077704cc0bc9a42fc4b94da60b57d31ff0f65c | https://github.com/Hiroaki-Ozaki/modelib-classification/tree/11077704cc0bc9a42fc4b94da60b57d31ff0f65c |
TorchMul | import torch
class TorchMul(torch.nn.Module):
def __init__(self):
super(TorchMul, self).__init__()
def forward(self, x, y):
return torch.mul(x, y)
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | ahangchen/torch2trt | TorchMul | false | 6,108 | [
"MIT"
] | 1 | 53c663f0e0570ef7ffd6771354ae3478f63bd328 | https://github.com/ahangchen/torch2trt/tree/53c663f0e0570ef7ffd6771354ae3478f63bd328 |
PyramidPoolingModule | # 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... | nassir90/ICNet-pytorch | PyramidPoolingModule | false | 16,140 | [
"MIT"
] | 83 | af6eec01a4419ce43c52d295bc502c366478fbd7 | https://github.com/nassir90/ICNet-pytorch/tree/af6eec01a4419ce43c52d295bc502c366478fbd7 |
GHMR | import torch
import torch.nn as nn
class GHMR(nn.Module):
"""GHM Regression Loss.
Details of the theorem can be viewed in the paper
`Gradient Harmonized Single-stage Detector
<https://arxiv.org/abs/1811.05181>`_.
Args:
mu (float): The parameter for the Authentic Smooth L1 loss.
b... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | ChengBo5/mask-text-detector | GHMR | false | 272 | [
"Apache-2.0"
] | 0 | ce93e45ed1d982ec0ef6ad977c02e49326bf255a | https://github.com/ChengBo5/mask-text-detector/tree/ce93e45ed1d982ec0ef6ad977c02e49326bf255a |
RAddFloat | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | Akababa/torch2trt | RAddFloat | false | 18,414 | [
"MIT"
] | 2 | 03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 | https://github.com/Akababa/torch2trt/tree/03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 |
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