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 |
|---|---|---|---|---|---|---|---|---|---|---|
DispConv | import torch
import torch.nn as nn
class Conv3x3(nn.Module):
def __init__(self, in_channels, out_channels, use_refl=True):
super(Conv3x3, self).__init__()
if use_refl:
self.pad = nn.ReflectionPad2d(1)
else:
self.pad = nn.ZeroPad2d(1)
self.conv = nn.Conv2d(i... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | prstrive/EPCDepth | DispConv | false | 16,280 | [
"MIT"
] | 76 | 84119c806741334b652749ee953e3eab60a3718c | https://github.com/prstrive/EPCDepth/tree/84119c806741334b652749ee953e3eab60a3718c |
Network | # 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 ... | markosej11/Image-Claasification | Network | false | 3,986 | [
"MIT"
] | 0 | 0fea42726f36b582829a44e6fcebf8af89b518fc | https://github.com/markosej11/Image-Claasification/tree/0fea42726f36b582829a44e6fcebf8af89b518fc |
Split | # 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... | Schwartz-Zha/My-invertible-resnet | Split | false | 1,029 | [
"MIT"
] | 0 | 5415975bb0d640f3bf3ef4a7b986563e84109270 | https://github.com/Schwartz-Zha/My-invertible-resnet/tree/5415975bb0d640f3bf3ef4a7b986563e84109270 |
LayerNorm2d | # 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_... | HumberMe/mmclassification | LayerNorm2d | false | 561 | [
"Apache-2.0"
] | 0 | 68f1542068d3af4db932c97e6a728181432fff0c | https://github.com/HumberMe/mmclassification/tree/68f1542068d3af4db932c97e6a728181432fff0c |
DummyModelWithSharedSubmodule | # 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 ... | Emily0219/distiller | DummyModelWithSharedSubmodule | false | 5,127 | [
"Apache-2.0"
] | 1 | 445ed35b671fb54586acc280b53d951f18bf97ae | https://github.com/Emily0219/distiller/tree/445ed35b671fb54586acc280b53d951f18bf97ae |
Zeros | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.optim
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strid... | ai-in-motion/moai | Zeros | false | 18,344 | [
"Apache-2.0"
] | 10 | e38cac046c059d2e2331ef4883bbabc5a500a5cf | https://github.com/ai-in-motion/moai/tree/e38cac046c059d2e2331ef4883bbabc5a500a5cf |
Transpose | import torch
import torch.nn as nn
class Transpose(nn.Module):
def __init__(self, dim1=0, dim2=1):
super(Transpose, self).__init__()
self.dim1 = dim1
self.dim2 = dim2
def forward(self, input):
return input.transpose(self.dim1, self.dim2).contiguous()
def __repr__(self):
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | SwaggyZhang/Geometry-aware | Transpose | false | 1,105 | [
"Apache-2.0"
] | 0 | a750c00aa2f0bda5160dfdeee2eef5230fd9d993 | https://github.com/SwaggyZhang/Geometry-aware/tree/a750c00aa2f0bda5160dfdeee2eef5230fd9d993 |
WeightedCrossEntropyLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class WeightedCrossEntropyLoss(nn.Module):
"""
Transform input to fit the fomation of PyTorch offical cross entropy loss
with anchor-wise weighting.
"""
def __init__(self):
super(WeightedCrossEntropyLoss, 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 import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | CSL-KU/OpenPCDet | WeightedCrossEntropyLoss | false | 2,093 | [
"Apache-2.0"
] | 0 | 2c5fca0da1521add4b40e6cdfe75d02d4285b83f | https://github.com/CSL-KU/OpenPCDet/tree/2c5fca0da1521add4b40e6cdfe75d02d4285b83f |
ConditionTime | # 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... | lukeleeai/metnet | ConditionTime | false | 12,743 | [
"MIT"
] | 0 | 1dc0bf11780f413f3d55207866e0fa921b8aa60d | https://github.com/lukeleeai/metnet/tree/1dc0bf11780f413f3d55207866e0fa921b8aa60d |
BertOutput | from _paritybench_helpers import _mock_config
import torch
from torch import nn
import torch.utils.data
class BertLayerNorm(nn.Module):
def __init__(self, hidden_size, eps=1e-05):
"""Construct a layernorm module in the TF style (epsilon inside the square root)."""
super(BertLayerNorm, self).__ini... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | zdxdsw/WebQA_VLP | BertOutput | false | 11,053 | [
"Apache-2.0"
] | 0 | 443bcd7e9b36db47e2ab4502abaaa3724800f394 | https://github.com/zdxdsw/WebQA_VLP/tree/443bcd7e9b36db47e2ab4502abaaa3724800f394 |
MultiHeadAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Kyumin-Park/mellotron | MultiHeadAttention | false | 2,482 | [
"BSD-3-Clause"
] | 0 | 330081d4c23664686e8c68d74a9222ec4633ffa6 | https://github.com/Kyumin-Park/mellotron/tree/330081d4c23664686e8c68d74a9222ec4633ffa6 |
AuxMLP | import torch
from torch import nn
from torch.nn import functional as F
class AuxMLP(nn.Module):
"""
basic structure similar to the MLP
input is splited into two 1*14*14 images for separating training, use different parameters
softmax for the auxiliary output layers
"""
def __init__(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 import nn
assert_s... | EE559DeepLearningEPFL/Project1 | AuxMLP | false | 397 | [
"MIT"
] | 0 | cbafdfee26771ae0ba3cd36375e68d92e9f108b2 | https://github.com/EE559DeepLearningEPFL/Project1/tree/cbafdfee26771ae0ba3cd36375e68d92e9f108b2 |
BiAvg | import torch
from torch import nn
class BiAvg(nn.AvgPool1d):
def forward(self, x):
x = x.transpose(1, 2)
x = super().forward(x)
return x.transpose(1, 2)
def get_inputs():
return [torch.rand([4, 4, 4])]
def get_init_inputs():
return [[], {'kernel_size': 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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | urchade/urchade-byte_search | BiAvg | false | 10,891 | [
"MIT"
] | 0 | 5155adb1550dcab873db4e9b124c42da24c99b8e | https://github.com/urchade/urchade-byte_search/tree/5155adb1550dcab873db4e9b124c42da24c99b8e |
Decoder2 | # 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 | Decoder2 | false | 14,021 | [
"MIT"
] | 172 | 915712674af82ff91d926d922c14988cce0430f3 | https://github.com/MingSun-Tse/Collaborative-Distillation/tree/915712674af82ff91d926d922c14988cce0430f3 |
L2Loss | import torch
from torch import nn
import torch as th
from functools import *
class L2Loss(nn.Module):
def __init__(self):
super(L2Loss, self).__init__()
def forward(self, grad_fake, grad_real):
num_pixels = reduce(lambda x, y: x * y, grad_real.size())
return th.sum(th.pow(grad_real -... | 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
from functools import *
assert_size_stride = torch._C._dynamo.guards... | JaviBite/TFG | L2Loss | false | 2,399 | [
"MIT"
] | 0 | e406580697132f53b63a7c983daaa098af45b52c | https://github.com/JaviBite/TFG/tree/e406580697132f53b63a7c983daaa098af45b52c |
UPChannelBAN | import torch
import torch.nn.functional as F
import torch.nn as nn
def xcorr_fast(x, kernel):
"""group conv2d to calculate cross correlation, fast version
"""
batch = kernel.size()[0]
pk = kernel.view(-1, x.size()[1], kernel.size()[2], kernel.size()[3])
px = x.view(1, -1, x.size()[2], x.size()[3])... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn.functional as F
import torch.nn as nn
assert_size_stride = torch... | IRLSCU/siamban | UPChannelBAN | false | 2,574 | [
"Apache-2.0"
] | 0 | abb12d028e93aaee74efc5042a5bb305c7805053 | https://github.com/IRLSCU/siamban/tree/abb12d028e93aaee74efc5042a5bb305c7805053 |
SpecialEncoderLayer | # 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.... | wukevin/RoseTTAFold | SpecialEncoderLayer | false | 4,571 | [
"MIT"
] | 0 | e3c15dbf4bc1e4f8726e26c63aca1625188da803 | https://github.com/wukevin/RoseTTAFold/tree/e3c15dbf4bc1e4f8726e26c63aca1625188da803 |
SDR | # 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.... | Marc-Demoustier/demixr | SDR | false | 17,662 | [
"MIT"
] | 4 | cb3bb1606670d2e705b36f09e9a4a4394f8303da | https://github.com/Marc-Demoustier/demixr/tree/cb3bb1606670d2e705b36f09e9a4a4394f8303da |
CombinedTargetMSELoss | # 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... | carolchenyx/mmpose | CombinedTargetMSELoss | false | 15,001 | [
"Apache-2.0"
] | 367 | cd74bf1d0b13954188cc678415fd0ef98a74b46b | https://github.com/carolchenyx/mmpose/tree/cd74bf1d0b13954188cc678415fd0ef98a74b46b |
Classify | # 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... | ChaokunChang/SVAS | Classify | false | 259 | [
"Apache-2.0"
] | 0 | 61af6eb39269edff8ea5147311628b3200c3a3d2 | https://github.com/ChaokunChang/SVAS/tree/61af6eb39269edff8ea5147311628b3200c3a3d2 |
GaussianFocalLoss | import functools
import torch
import torch.nn.functional as F
import torch.nn as nn
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Return:
Tensor: Reduced loss ten... | 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 | GaussianFocalLoss | false | 17,121 | [
"MIT"
] | 5 | 0be9fd844118c275abc6053b3cbd5ffb589e62ee | https://github.com/CityU-AIM-Group/HTD/tree/0be9fd844118c275abc6053b3cbd5ffb589e62ee |
SelfExpression | # 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... | Xanadu12138/DSCN-superpixels | SelfExpression | false | 18,092 | [
"MIT"
] | 4 | babe16edde9c61699ef203effbfc9f03246765f3 | https://github.com/Xanadu12138/DSCN-superpixels/tree/babe16edde9c61699ef203effbfc9f03246765f3 |
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... | abdalazizrashid/idao-21-baseline | Clamp | false | 18,229 | [
"Apache-2.0"
] | 7 | 649c2c70a1754b09fa06bf2264d7e8217b3e10f0 | https://github.com/abdalazizrashid/idao-21-baseline/tree/649c2c70a1754b09fa06bf2264d7e8217b3e10f0 |
AddCoords | import torch
from torch import nn
class AddCoords(nn.Module):
def __init__(self, with_r=False):
super().__init__()
self.with_r = with_r
def forward(self, input_tensor):
"""
Args:
input_tensor: shape(batch, channel, x_dim, y_dim)
"""
batch_size, _, ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | MingSungChao/IPN-hand | AddCoords | false | 14,011 | [
"MIT"
] | 54 | 0b061e4438f159e3e312af4959cb424917b5c367 | https://github.com/MingSungChao/IPN-hand/tree/0b061e4438f159e3e312af4959cb424917b5c367 |
CircleLoss | # 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 typing... | IntelLabs/MICSAS | CircleLoss | false | 17,429 | [
"MIT",
"BSD-3-Clause"
] | 7 | 4124991a683cc10004e403f3f3eb442f58616519 | https://github.com/IntelLabs/MICSAS/tree/4124991a683cc10004e403f3f3eb442f58616519 |
TCB | # 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 it... | SaralaSewwandi/refinedet-pytorch | TCB | false | 8,743 | [
"MIT"
] | 43 | d1eb9f84216085858562d816f19aeb77c2ab604a | https://github.com/SaralaSewwandi/refinedet-pytorch/tree/d1eb9f84216085858562d816f19aeb77c2ab604a |
L2Norm | import torch
import torch.nn as nn
import torch.nn.init as init
import torch.utils.data
from numpy.random import *
class L2Norm(nn.Module):
def __init__(self, n_channels, scale):
super(L2Norm, self).__init__()
self.n_channels = n_channels
self.gamma = scale or None
self.eps = 1e-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 libdevice
import torch.nn as nn
import torch.nn.init as init
import torch.utils.data
from... | Tony-Khor/PyTorch-From-Zero-to-All | L2Norm | false | 5,909 | [
"MIT"
] | 1 | d8f9b6d81fe390dee93a887f342dc818553e61b3 | https://github.com/Tony-Khor/PyTorch-From-Zero-to-All/tree/d8f9b6d81fe390dee93a887f342dc818553e61b3 |
DiceLoss | # 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... | hongxuenong/mmocr | DiceLoss | false | 15,532 | [
"Apache-2.0"
] | 2,261 | e8e3a059f8f2e4fca96af37751c33563fc48e2ba | https://github.com/hongxuenong/mmocr/tree/e8e3a059f8f2e4fca96af37751c33563fc48e2ba |
TCB | import torch
import torch.nn as nn
from itertools import product as product
import torch.onnx.symbolic_helper
class TCB(nn.Module):
"""
Transfer Connection Block Architecture
This block
"""
def __init__(self, lateral_channels, channles, internal_channels=256,
is_batchnorm=False):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from it... | SaralaSewwandi/refinedet-onnxvalidation | TCB | false | 9,469 | [
"MIT"
] | 0 | 5b71c994fc6ca183dc6cb30b7e21d201c15da490 | https://github.com/SaralaSewwandi/refinedet-onnxvalidation/tree/5b71c994fc6ca183dc6cb30b7e21d201c15da490 |
GCN | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class GCNLayer(nn.Module):
def __init__(self, input_features, output_features, bias=False):
super(GCNLayer, self).__init__()
self.input_features = input_features
self.output_features = output_features
s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | OuYangg/GNNs | GCN | false | 9,461 | [
"Apache-2.0"
] | 0 | ef5b1944490507684d603de3ae0b2aa7b5168f47 | https://github.com/OuYangg/GNNs/tree/ef5b1944490507684d603de3ae0b2aa7b5168f47 |
FeatureFusion | import torch
import torch.distributed
import torch
import torch.nn as nn
import torch.nn.functional
import torch.utils.data
import torch.optim
import torch.optim.lr_scheduler
class Mlp(nn.Module):
""" Multilayer perceptron."""
def __init__(self, in_features, hidden_features=None, out_features=None,
a... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | zhangzhengde0225/SwinTrack | FeatureFusion | false | 16,842 | [
"MIT"
] | 143 | 526be17f8ef266cb924c6939bd8dda23e9b73249 | https://github.com/zhangzhengde0225/SwinTrack/tree/526be17f8ef266cb924c6939bd8dda23e9b73249 |
Early_StyleConv_Block | import math
import torch
import torch.nn as nn
def quick_scale(module, name='weight'):
ScaleW.apply(module, name)
return module
class ScaleW:
"""
Constructor: name - name of attribute to be scaled
"""
def __init__(self, name):
self.name = name
def scale(self, module):
w... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import ... | sergkuzn148/stg | Early_StyleConv_Block | false | 16,412 | [
"MIT"
] | 96 | 84d9f53ae3665c423836a4d0176dc3b22de62b19 | https://github.com/sergkuzn148/stg/tree/84d9f53ae3665c423836a4d0176dc3b22de62b19 |
MaxMarginRankingLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class MaxMarginRankingLoss(nn.Module):
def __init__(self, margin=1):
super(MaxMarginRankingLoss, self).__init__()
self.margin = margin
def forward(self, x):
n = x.size()[0]
x1 = torch.diag(x)
x1 = x1.u... | 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... | Worm4047/TVR | MaxMarginRankingLoss | false | 14,589 | [
"MIT"
] | 106 | 2a8ce2edbdc0966aef3b84c28872267039f01700 | https://github.com/Worm4047/TVR/tree/2a8ce2edbdc0966aef3b84c28872267039f01700 |
StatsPool | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.optim
assert_size_stride = torch._C._dynamo.... | clmpt/pyannote-audio | StatsPool | false | 6,461 | [
"MIT"
] | 1 | 7d1b7959ca5f817e08176e44d52a7499bbd3149c | https://github.com/clmpt/pyannote-audio/tree/7d1b7959ca5f817e08176e44d52a7499bbd3149c |
ValueFunction | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import numpy as np
... | RajGhugare19/VE-principle-for-model-based-RL | ValueFunction | false | 8,688 | [
"MIT"
] | 16 | a9f94dfc9317a0ccc60bc7c558dcec1ebc6d0c63 | https://github.com/RajGhugare19/VE-principle-for-model-based-RL/tree/a9f94dfc9317a0ccc60bc7c558dcec1ebc6d0c63 |
LogDepthL1Loss | # 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... | ezxzeng/FFB6D | LogDepthL1Loss | false | 15,333 | [
"MIT"
] | 145 | fd0ea6471532ab1dc68f9a58b52d9a63f8fb76f2 | https://github.com/ezxzeng/FFB6D/tree/fd0ea6471532ab1dc68f9a58b52d9a63f8fb76f2 |
L2Norm | import torch
from torch import nn
class L2Norm(nn.Module):
def forward(self, x, eps=1e-06):
norm = x.norm(dim=1, keepdim=True).clamp(min=eps)
return x / norm
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._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_... | onlyrico/vit-pytorch | L2Norm | false | 7,365 | [
"MIT"
] | 1 | e52ac4195550faa9c3372533d325bf649f7354ad | https://github.com/onlyrico/vit-pytorch/tree/e52ac4195550faa9c3372533d325bf649f7354ad |
WeightedCrossEntropyLoss | # 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
... | Jiaolong/trajectory-prediction | WeightedCrossEntropyLoss | false | 17,479 | [
"Apache-2.0"
] | 6 | 3fd4e6253b44dfdc86e7c08e93c002baf66f2e46 | https://github.com/Jiaolong/trajectory-prediction/tree/3fd4e6253b44dfdc86e7c08e93c002baf66f2e46 |
InceptionB | 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 | InceptionB | false | 17,396 | [
"WTFPL"
] | 10 | 11077704cc0bc9a42fc4b94da60b57d31ff0f65c | https://github.com/Hiroaki-Ozaki/modelib-classification/tree/11077704cc0bc9a42fc4b94da60b57d31ff0f65c |
HingeLoss | import torch
import torch.nn as nn
class HingeLoss(nn.Module):
def __init__(self):
super(HingeLoss, self).__init__()
self.margin = 1.0
def hinge_loss(self, input, target):
output = self.margin - input.mul(target)
output[output.le(0)] = 0
return output.mean()
def ... | 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... | Siraj-Qazi/BNN-PYNQ | HingeLoss | false | 2,834 | [
"BSD-3-Clause"
] | 0 | b942fe92b3c62b0b877b0a9d5c13e7eb3a234685 | https://github.com/Siraj-Qazi/BNN-PYNQ/tree/b942fe92b3c62b0b877b0a9d5c13e7eb3a234685 |
RegLoss | import torch
import torch.nn as nn
class RegLoss(nn.Module):
""" RegLoss, L2 regularization on model parameters
"""
def __init__(self):
super(RegLoss, self).__init__()
def forward(self, parameters):
reg_loss = None
for W in parameters:
if reg_loss is None:
... | 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_... | geekinglcq/HRec | RegLoss | false | 15,414 | [
"MIT"
] | 49 | b3a67f7721e6e73a7af37d308b5b00e9df68d495 | https://github.com/geekinglcq/HRec/tree/b3a67f7721e6e73a7af37d308b5b00e9df68d495 |
Value | # 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 ... | aranganath/pytorch-trpo | Value | false | 9,753 | [
"MIT"
] | 0 | a85bc48261eb4ed5833209da706379e9dc84592f | https://github.com/aranganath/pytorch-trpo/tree/a85bc48261eb4ed5833209da706379e9dc84592f |
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 ... | evazhang612/honygenerator | Highway | false | 6,662 | [
"MIT"
] | 1 | cafcf1736faba978ecaed624b949ebc1498477ee | https://github.com/evazhang612/honygenerator/tree/cafcf1736faba978ecaed624b949ebc1498477ee |
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 libdevice, math as tl_math
import torc... | Alicegaz/torchok | FocalLoss | false | 16,926 | [
"Apache-2.0"
] | 8 | 7b8f95df466a25b1ad8ee93bed1a3c7516440cf4 | https://github.com/Alicegaz/torchok/tree/7b8f95df466a25b1ad8ee93bed1a3c7516440cf4 |
FeedForward | import torch
import torch.utils.data
import torch.nn as nn
from torch.nn.functional import relu
from torch.nn.functional import dropout
class FeedForward(nn.Module):
def __init__(self, input_size):
super(FeedForward, self).__init__()
self.fc1 = nn.Linear(input_size, 16)
self.fc2 = 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 import triton_helpers
import torch.utils.data
impor... | ibraheem-moosa/protein-bvalue-prediction | FeedForward | false | 12,518 | [
"MIT"
] | 0 | 9d0607ade30d8877ea89c5f24184d3af0580f912 | https://github.com/ibraheem-moosa/protein-bvalue-prediction/tree/9d0607ade30d8877ea89c5f24184d3af0580f912 |
FactoredAttention | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.functional
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
import torch as t
def checkpoint(func, inputs, params, flag):
if flag:
args = inputs + tuple(par... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ZVK/jukebox | FactoredAttention | false | 18,200 | [
"MIT"
] | 5 | 23fd6753f2892214ad3d97f6f2b59f8cc8d0c57a | https://github.com/ZVK/jukebox/tree/23fd6753f2892214ad3d97f6f2b59f8cc8d0c57a |
PPMConcat | import torch
import torch.nn as nn
import torch._C
import torch.serialization
class PPMConcat(nn.ModuleList):
"""Pyramid Pooling Module that only concat the features of each layer.
Args:
pool_scales (tuple[int]): Pooling scales used in Pooling Pyramid
Module.
"""
def __init__(sel... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch._C
import torch.serialization
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strid... | CVIU-CSU/M2MRF-Lesion-Segmentation | PPMConcat | false | 17,065 | [
"Apache-2.0"
] | 10 | 13af87927f4cdeca70e35d570edd1aec43b387b6 | https://github.com/CVIU-CSU/M2MRF-Lesion-Segmentation/tree/13af87927f4cdeca70e35d570edd1aec43b387b6 |
_GRU_ODE | # 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
assert_size_stride ... | athon-millane/NeuralCDE | _GRU_ODE | false | 12,126 | [
"Apache-2.0"
] | 0 | 4196890fe5bf7a69925a12ff35e86f212963be71 | https://github.com/athon-millane/NeuralCDE/tree/4196890fe5bf7a69925a12ff35e86f212963be71 |
DQN_xy1 | # 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 ... | CoAxLab/azad | DQN_xy1 | false | 17,190 | [
"MIT"
] | 6 | d1498069dd8856e93ae077b34dd7c9f1c7ce80e6 | https://github.com/CoAxLab/azad/tree/d1498069dd8856e93ae077b34dd7c9f1c7ce80e6 |
LinearClassifier | # 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.... | godweiyang/ParaGen | LinearClassifier | false | 15,450 | [
"Apache-2.0"
] | 50 | 9665d1244ea38a41fc06b4e0a7f6411985e2221f | https://github.com/godweiyang/ParaGen/tree/9665d1244ea38a41fc06b4e0a7f6411985e2221f |
TemporalBlock | # 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
import t... | verashira/TSPNet | TemporalBlock | false | 16,671 | [
"MIT"
] | 83 | ee454165dcc61cdbbff19565364e2221727ed2b8 | https://github.com/verashira/TSPNet/tree/ee454165dcc61cdbbff19565364e2221727ed2b8 |
SoftmaxLayer | # 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.... | Sy-Zhang/ELMoForManyLangs | SoftmaxLayer | false | 14,452 | [
"MIT"
] | 1,414 | f82bf0fef80df617e39d34baa3e46d9857e94e65 | https://github.com/Sy-Zhang/ELMoForManyLangs/tree/f82bf0fef80df617e39d34baa3e46d9857e94e65 |
FakeRKHSConvNet | import math
import torch
import numpy as np
import torch.nn as nn
class MaybeBatchNorm2d(nn.Module):
def __init__(self, n_ftr, affine, use_bn):
super(MaybeBatchNorm2d, self).__init__()
self.bn = nn.BatchNorm2d(n_ftr, affine=affine)
self.use_bn = use_bn
def forward(self, x):
i... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | bartolkaruza/pytorch-lightning-bolts | FakeRKHSConvNet | false | 9,997 | [
"Apache-2.0"
] | 0 | 2e903c333c37ea83394c7da2ce826de1b82fb356 | https://github.com/bartolkaruza/pytorch-lightning-bolts/tree/2e903c333c37ea83394c7da2ce826de1b82fb356 |
SelfAttention | # 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.... | Thibaud-Ardoin/Dial-a-Ride | SelfAttention | false | 5,896 | [
"MIT"
] | 1 | 7d9b3cd904d3194dccad31fec2533e2cf58cad0c | https://github.com/Thibaud-Ardoin/Dial-a-Ride/tree/7d9b3cd904d3194dccad31fec2533e2cf58cad0c |
DQNetwork | from torch.nn import Module
import torch
import torch.nn as nn
class DQNetwork(Module):
def __init__(self, num_states, num_actions):
super(DQNetwork, self).__init__()
self.relu = nn.ReLU()
self.fc_layer1 = nn.Linear(num_states, 256)
self.fc_layer2 = nn.Linear(256, 256)
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
from torch.nn import Module
i... | Devanshu-singh-VR/Reinforcement-Learning_Mixed | DQNetwork | false | 9,004 | [
"MIT"
] | 0 | 6b8b23977864f918ab8958b729d0faabcca720e4 | https://github.com/Devanshu-singh-VR/Reinforcement-Learning_Mixed/tree/6b8b23977864f918ab8958b729d0faabcca720e4 |
RefModel3d2 | # 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.... | shuohan/pytorch-layers | RefModel3d2 | false | 4,367 | [
"MIT"
] | 0 | 020846fd02d501cf477552179c19ba4b5e9a0695 | https://github.com/shuohan/pytorch-layers/tree/020846fd02d501cf477552179c19ba4b5e9a0695 |
SeparableBlock | from torch.nn import Module
import torch
from torch.nn import Linear
class SeparableBlock(Module):
def __init__(self, input_size, kernel_channels_in, kernel_channels_out,
kernel_size):
super(SeparableBlock, self).__init__()
self.input_size = input_size
self.kernel_size = kernel_si... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import Module
from torch.nn import Linear
assert_size_stride = tor... | Kiberchaika/hyperstyle | SeparableBlock | false | 11,693 | [
"MIT"
] | 0 | b67e5ca9c67dfdfa18f1d6cda6e8eff5da07db7b | https://github.com/Kiberchaika/hyperstyle/tree/b67e5ca9c67dfdfa18f1d6cda6e8eff5da07db7b |
FlowHead | # 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_... | Etienne-Meunier/FGVC | FlowHead | false | 11,419 | [
"MIT"
] | 0 | a7c6d4b6583ad3a380b0359fde9223dccc8e9c66 | https://github.com/Etienne-Meunier/FGVC/tree/a7c6d4b6583ad3a380b0359fde9223dccc8e9c66 |
BoundReciprocal | # 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 math
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
from numbers import Number
assert_size_stride = torch._... | Mahoumaru/auto_LiRPA | BoundReciprocal | false | 13,227 | [
"BSD-3-Clause"
] | 0 | b03a6c36eb1b921726778359d6d2b94e0cd7e480 | https://github.com/Mahoumaru/auto_LiRPA/tree/b03a6c36eb1b921726778359d6d2b94e0cd7e480 |
TorchModule | import torch
import torch.nn
class TorchLinearModule(torch.nn.Module):
def __init__(self, in_size, out_size):
super(TorchLinearModule, self).__init__()
self._linear = torch.nn.Linear(in_size, out_size)
def forward(self, x):
return self._linear(x)
class TorchModule(torch.nn.Module):... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn
ass... | amit828as/ivy | TorchModule | false | 9,706 | [
"Apache-2.0"
] | 0 | fd12e513c58e337cc3775e456ad26a942a501c65 | https://github.com/amit828as/ivy/tree/fd12e513c58e337cc3775e456ad26a942a501c65 |
HighwayNetwork | # 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_... | Dacrol/WaveRNN-server | HighwayNetwork | false | 11,320 | [
"MIT"
] | 0 | 5189829cec71938ff7ec2e3eb59e73af1382430a | https://github.com/Dacrol/WaveRNN-server/tree/5189829cec71938ff7ec2e3eb59e73af1382430a |
HighwayLayer | # 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 ... | anoushkt/craftassist | HighwayLayer | false | 6,215 | [
"MIT"
] | 1 | c200af65e52e800f0f0cc540fe836b644383349d | https://github.com/anoushkt/craftassist/tree/c200af65e52e800f0f0cc540fe836b644383349d |
BernoulliLogProb | import torch
import torch.nn as nn
import torch.utils
import torch.utils.data
class BernoulliLogProb(nn.Module):
def __init__(self):
super().__init__()
self.bce_with_logits = nn.BCEWithLogitsLoss(reduction='none')
def forward(self, logits, target):
return -self.bce_with_logits(logits... | 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... | msunardi/vae_experiment | BernoulliLogProb | false | 7,290 | [
"MIT"
] | 1 | e3ce39e586f1189d157e753370a90c07713658b3 | https://github.com/msunardi/vae_experiment/tree/e3ce39e586f1189d157e753370a90c07713658b3 |
_Transition | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
from torchvision.transforms import *
class _Transition(nn.Module):
def __init__(self, in_channels, args):
super(_Transit... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
from torchvisi... | HelenR6/robustness-1 | _Transition | false | 11,142 | [
"Apache-2.0"
] | 0 | 5527250df02195dff37628a9d76ae7d76c3c51d1 | https://github.com/HelenR6/robustness-1/tree/5527250df02195dff37628a9d76ae7d76c3c51d1 |
Generator | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | PhilippeW83440/conv-social-pooling | Generator | false | 17,813 | [
"MIT"
] | 4 | 93d3a08af8678c3309d75a9bfb37df500da5cc46 | https://github.com/PhilippeW83440/conv-social-pooling/tree/93d3a08af8678c3309d75a9bfb37df500da5cc46 |
distLinear | # 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 ... | prabhat1081/self-supervision-cs221 | distLinear | false | 7,494 | [
"Apache-2.0"
] | 1 | 41912c01dd7bf44d45a27d7c715a8db2ee9bbc28 | https://github.com/prabhat1081/self-supervision-cs221/tree/41912c01dd7bf44d45a27d7c715a8db2ee9bbc28 |
SeparableBlock | from torch.nn import Module
import torch
from torch.nn import Linear
class SeparableBlock(Module):
def __init__(self, input_size, kernel_channels_in, kernel_channels_out,
kernel_size):
super(SeparableBlock, self).__init__()
self.input_size = input_size
self.kernel_size = kernel_si... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import Module
from torch.nn import Linear
assert_size_stride = tor... | Kiberchaika/StyleGAN-nada | SeparableBlock | false | 722 | [
"MIT"
] | 0 | b25a6061933d3d56fbc0af493a7765f316bdd513 | https://github.com/Kiberchaika/StyleGAN-nada/tree/b25a6061933d3d56fbc0af493a7765f316bdd513 |
BehaviorAggregator | # 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... | byzhang/OpenMatch | BehaviorAggregator | false | 10,036 | [
"Apache-2.0"
] | 0 | 28b2d49a5eec2e1dc3934767c747ff0ca6c93d96 | https://github.com/byzhang/OpenMatch/tree/28b2d49a5eec2e1dc3934767c747ff0ca6c93d96 |
SimpleSumModule | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleSumModule(torch.nn.Module):
def __init__(self, dtype=None):
super(SimpleSumModule, self).__init__()
self.dtype = dtype
def forward(self, a):
b = a + a
return torch.sum(b, dtype=self.dtype)
def get_i... | 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 | SimpleSumModule | false | 14,687 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
SpatialTokenGen | # 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 ... | SeungoneKim/sgMLP_Implementation | SpatialTokenGen | false | 9,474 | [
"Apache-2.0"
] | 0 | 5c5e623577a7ada3b200d99e77dc707a10cb1195 | https://github.com/SeungoneKim/sgMLP_Implementation/tree/5c5e623577a7ada3b200d99e77dc707a10cb1195 |
EncModel | import torch
import torch.utils.data
class EncModel(torch.nn.Module):
def __init__(self, num_input, num_hid, num_out):
super(EncModel, self).__init__()
self.in_hid = torch.nn.Linear(num_input, num_hid)
self.hid_out = torch.nn.Linear(num_hid, num_out)
def forward(self, input):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.... | Spacider/comp9444_assignment | EncModel | false | 2,849 | [
"Apache-2.0"
] | 0 | 149db9a562c579d03b3ea06c9de2020c8f3ef310 | https://github.com/Spacider/comp9444_assignment/tree/149db9a562c579d03b3ea06c9de2020c8f3ef310 |
PoseMap | # 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... | MrChenFeng/Project-Template | PoseMap | false | 860 | [
"MIT"
] | 0 | 42a335c6abb710bbae6407cbb0ca461533bc12f9 | https://github.com/MrChenFeng/Project-Template/tree/42a335c6abb710bbae6407cbb0ca461533bc12f9 |
DiceLoss | # 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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | joowlim/pytorch-3dunet | DiceLoss | false | 10,400 | [
"MIT"
] | 0 | d08049f60b619627521efd0fb171247e1536b262 | https://github.com/joowlim/pytorch-3dunet/tree/d08049f60b619627521efd0fb171247e1536b262 |
EPELoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | aishmittal/DocProj | EPELoss | false | 14,786 | [
"MIT"
] | 246 | 761e27927ab7a83f48e347921dc023d45a9d394f | https://github.com/aishmittal/DocProj/tree/761e27927ab7a83f48e347921dc023d45a9d394f |
_ChannelAttentionModule | import torch
import torch.nn as nn
from itertools import product as product
class _ChannelAttentionModule(nn.Module):
"""Channel attention module"""
def __init__(self, **kwargs):
super(_ChannelAttentionModule, self).__init__()
self.beta = nn.Parameter(torch.zeros(1))
self.softmax = 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
from torch._inductor.runtime.... | maoweinuaa/FaceParsing | _ChannelAttentionModule | false | 15,998 | [
"MIT"
] | 138 | 5e153b636e7e57b20d3079b2e0f15aa02dc4046d | https://github.com/maoweinuaa/FaceParsing/tree/5e153b636e7e57b20d3079b2e0f15aa02dc4046d |
GCN | from torch.nn import Module
import math
import torch
from torch.nn.parameter import Parameter
from torch.nn.modules.module import Module
import torch.nn as nn
import torch.nn.functional as F
class GCLayer(Module):
def __init__(self, dim_in, dim_out):
super(GCLayer, self).__init__()
self.dim_in = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | spacemanidol/CS512DM | GCN | false | 4,375 | [
"MIT"
] | 0 | fa664ceb7526e27b9cccd372b65b15c587095c49 | https://github.com/spacemanidol/CS512DM/tree/fa664ceb7526e27b9cccd372b65b15c587095c49 |
ChannelSqueeze | import torch
import torch.nn as nn
def channel_squeeze(x, groups):
"""
Channel squeeze operation.
Parameters:
----------
x : Tensor
Input tensor.
groups : int
Number of groups.
Returns
-------
Tensor
Resulted tensor.
"""
batch, channels, height, wi... | 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... | iofthetiger/pkuad | ChannelSqueeze | false | 6,891 | [
"Apache-2.0"
] | 1 | 07496d108c614c84be028f344830becc9cac8fe5 | https://github.com/iofthetiger/pkuad/tree/07496d108c614c84be028f344830becc9cac8fe5 |
AdaptiveInstanceNorm2d | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | LenKerr/Semantic-Colorization-GAN | AdaptiveInstanceNorm2d | false | 5,497 | [
"MIT"
] | 1 | 2ce52406ca6fc92e69692b451b1c9ae66ba3b76f | https://github.com/LenKerr/Semantic-Colorization-GAN/tree/2ce52406ca6fc92e69692b451b1c9ae66ba3b76f |
NegativeScaledDotProduct | import torch
import torch.utils.data.dataloader
import torch.nn
def dot_product(a: 'torch.Tensor', b: 'torch.Tensor', normalize=False):
"""
Computes dot product for pairs of vectors.
:param normalize: Vectors are normalized (leads to cosine similarity)
:return: Matrix with res[i][j] = dot_product(a[i... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data.dataloader
import torch.nn
assert_size_stride = torch._C... | chen-yuxuan/flair | NegativeScaledDotProduct | false | 12,255 | [
"MIT"
] | 0 | 480d2c9afd66ab8d3bf40a676917e84dba3c4cee | https://github.com/chen-yuxuan/flair/tree/480d2c9afd66ab8d3bf40a676917e84dba3c4cee |
SoftL1 | import torch
class SoftL1(torch.nn.Module):
def __init__(self):
super(SoftL1, self).__init__()
def forward(self, input, target, eps=0.0):
l1 = torch.abs(input - target)
ret = l1 - eps
ret = torch.clamp(ret, min=0.0, max=100.0)
return ret, torch.mean(l1.detach())
def... | 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... | Tiamat-Tech/npms | SoftL1 | false | 14,509 | [
"MIT"
] | 96 | 2d1bce8c98b0f24aa69273975c52b2fbdb101c29 | https://github.com/Tiamat-Tech/npms/tree/2d1bce8c98b0f24aa69273975c52b2fbdb101c29 |
GlobalAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | BurakaKrishna/Question-Generation | GlobalAttention | false | 17,026 | [
"MIT"
] | 4 | 4614bf07243ab1b3df337fc1cb22175947c71a14 | https://github.com/BurakaKrishna/Question-Generation/tree/4614bf07243ab1b3df337fc1cb22175947c71a14 |
ResBlock | import torch
import torch.nn as nn
def conv3x3(in_planes, out_planes, stride=1):
"""3x3 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=1, bias=False)
def norm(dim):
return nn.GroupNorm(min(32, dim), dim)
class ResBlock(nn.Module):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Lauu1023/torchdiffeq | ResBlock | false | 9,344 | [
"MIT"
] | 0 | f4f3184a4c1b657da959c7d15bc8f727f1c25bd8 | https://github.com/Lauu1023/torchdiffeq/tree/f4f3184a4c1b657da959c7d15bc8f727f1c25bd8 |
EqualConv2d | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class EqualConv2d(nn.Module):
def __init__(self, in_channel, out_channel, kernel_size, stride=1,
padding=0, bias=True):
super().__init__()
self.weight = nn.Parameter(torch.randn(out_channel, in_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
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.a... | AsianZeus/Diverse-Facial-Edit | EqualConv2d | false | 9,403 | [
"Apache-2.0"
] | 0 | 3d4b1b41546a08a1fa3cb164ade33e319806b12b | https://github.com/AsianZeus/Diverse-Facial-Edit/tree/3d4b1b41546a08a1fa3cb164ade33e319806b12b |
LBM | import torch
import torch.nn as nn
class LBM(nn.Module):
def __init__(self, l_dim, r_dim):
super(LBM, self).__init__()
self.W = nn.Bilinear(l_dim, r_dim, 1, bias=False)
def forward(self, e1, e2):
"""
e1: tensor of size (*, l_dim)
e2: tensor of size (*, r_dim)
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | jinfenglin/TaxoExpan | LBM | false | 15,688 | [
"Apache-2.0"
] | 55 | 86bd3f805508d03367539f2fdd43889fc0a4f6b2 | https://github.com/jinfenglin/TaxoExpan/tree/86bd3f805508d03367539f2fdd43889fc0a4f6b2 |
ResConnectionLayer | import math
import torch
import torch.nn as nn
class LayerNorm(nn.Module):
"""Construct a layernorm module (See citation for details)."""
def __init__(self, features, eps=1e-06):
super(LayerNorm, self).__init__()
self.a_2 = nn.Parameter(torch.ones(features))
self.b_2 = nn.Parameter(to... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import ... | MobtgZhang/MWMLNet | ResConnectionLayer | false | 5,603 | [
"MIT"
] | 1 | 125bb39935916b6b4be505c51cb6a04eb49b96d0 | https://github.com/MobtgZhang/MWMLNet/tree/125bb39935916b6b4be505c51cb6a04eb49b96d0 |
ArcBiaffine | import torch
from torch import nn
import torch.utils.data
import torch.nn.init as init
def initial_parameter(net, initial_method=None):
"""A method used to initialize the weights of PyTorch models.
:param net: a PyTorch model
:param initial_method: str, one of the following initializations
-... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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.nn.init as init
assert... | FengZiYjun/fastNLP | ArcBiaffine | false | 5,157 | [
"Apache-2.0"
] | 1 | 3ae73ab0a05d1ceef4a5181516891a8057d7f719 | https://github.com/FengZiYjun/fastNLP/tree/3ae73ab0a05d1ceef4a5181516891a8057d7f719 |
CReLU | # 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... | dipikakhullar/ocr | CReLU | false | 15,179 | [
"MIT"
] | 284 | a55e70d82f42803be5ed63f8f59e4fa597fcf8d6 | https://github.com/dipikakhullar/ocr/tree/a55e70d82f42803be5ed63f8f59e4fa597fcf8d6 |
Encoder_H | # 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_... | KinWaiCheuk/Beta-VAE | Encoder_H | false | 5,669 | [
"MIT"
] | 1 | 57f538320fed76b54e8489656b11dc83c06d1584 | https://github.com/KinWaiCheuk/Beta-VAE/tree/57f538320fed76b54e8489656b11dc83c06d1584 |
Fp32LayerNorm | # 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.utils.data
import torch.onnx.operators
impor... | Ashprakash/roberta | Fp32LayerNorm | false | 11,465 | [
"MIT"
] | 0 | 5ee7abda64d752a467218c247855ddc20c09a779 | https://github.com/Ashprakash/roberta/tree/5ee7abda64d752a467218c247855ddc20c09a779 |
WeightedSoftDiceLoss | import torch
import torch.nn.functional as F
import torch.nn as nn
import torch.backends.cudnn
import torch.utils.data
class WeightedSoftDiceLoss(nn.Module):
def __init__(self):
super(WeightedSoftDiceLoss, self).__init__()
def forward(self, logits, labels, weights):
probs = F.sigmoid(logits)... | 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.backends.cudnn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
em... | ArmenGhambaryan/kaggle_carvana_segmentation | WeightedSoftDiceLoss | false | 13,297 | [
"MIT"
] | 447 | 648a6b5c807cb69011316fe6501241dacc027db2 | https://github.com/ArmenGhambaryan/kaggle_carvana_segmentation/tree/648a6b5c807cb69011316fe6501241dacc027db2 |
SIMPA | import torch
from typing import Optional
from typing import Tuple
import torch.nn as nn
from torch.nn.parameter import Parameter
from typing import Union
class SIMPA(nn.Module):
"""The signed mixed-path aggregation model.
Args:
hop (int): Number of hops to consider.
directed (bool, optional):... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.nn.parameter import Parameter
assert_size_strid... | SherylHYX/SSSNET_Signed_Clustering | SIMPA | false | 17,918 | [
"MIT"
] | 5 | 85736c18e86b396d64177d22b8c7f9859dfd794c | https://github.com/SherylHYX/SSSNET_Signed_Clustering/tree/85736c18e86b396d64177d22b8c7f9859dfd794c |
Discriminator | import torch
import torch.nn as nn
from numpy import *
class Discriminator(nn.Module):
"""docstring for Discriminator"""
def __init__(self, in_dim, out_dim):
super(Discriminator, self).__init__()
self.Linear1 = nn.Linear(in_dim, out_dim)
self.Relu = nn.ReLU()
self.Linear2 = 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 as nn
from nu... | ducviet00/HMER | Discriminator | false | 6,627 | [
"MIT"
] | 1 | 0fa322ed35412737a24ec3955c9a3d96d1989bd4 | https://github.com/ducviet00/HMER/tree/0fa322ed35412737a24ec3955c9a3d96d1989bd4 |
SpatialAttention | import torch
import torch.utils.data
from torch import nn
class SpatialAttention(nn.Module):
def __init__(self, kernel_size=3):
super(SpatialAttention, self).__init__()
assert kernel_size in (3, 7), 'kernel size must be 3 or 7'
padding = 3 if kernel_size == 7 else 1
self.conv = 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.utils.data
from ... | ljjyxz123/CenterMask | SpatialAttention | false | 7,112 | [
"BSD-2-Clause"
] | 1 | 443eebde30e209eeb3b953f7ef35d3f7f14aaca5 | https://github.com/ljjyxz123/CenterMask/tree/443eebde30e209eeb3b953f7ef35d3f7f14aaca5 |
DrugDrugAttentionLayer | # 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.fun... | YuWVandy/chemicalx | DrugDrugAttentionLayer | false | 1,275 | [
"Apache-2.0"
] | 0 | c02f979a502409c26700e6d5a1b2e6c0aa77e64c | https://github.com/YuWVandy/chemicalx/tree/c02f979a502409c26700e6d5a1b2e6c0aa77e64c |
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... | SeunghwanByun/Real-Time-Road-Detection-Network | CoordConv | false | 1,054 | [
"MIT"
] | 0 | bc46615adef0e2b1a9a03dd4951559ca5849e6e1 | https://github.com/SeunghwanByun/Real-Time-Road-Detection-Network/tree/bc46615adef0e2b1a9a03dd4951559ca5849e6e1 |
Expand | import torch
import torch.nn as nn
import torch.utils.data
class Expand(nn.Module):
def __init__(self, gain=2):
super().__init__()
self.gain = gain
def forward(self, x):
N, C, H, W = x.size()
s = self.gain
x = x.view(N, s, s, C // s ** 2, H, W)
x = x.permute(0... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | ChaokunChang/SVAS | Expand | false | 248 | [
"Apache-2.0"
] | 0 | 61af6eb39269edff8ea5147311628b3200c3a3d2 | https://github.com/ChaokunChang/SVAS/tree/61af6eb39269edff8ea5147311628b3200c3a3d2 |
NoiseInjection | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | celdeldel/style_conditionnal_gan | NoiseInjection | false | 1,652 | [
"MIT"
] | 0 | 3a4623560af1e12d46e2f9ffa9726c29df9d5680 | https://github.com/celdeldel/style_conditionnal_gan/tree/3a4623560af1e12d46e2f9ffa9726c29df9d5680 |
PixelNormLayer | import torch
import torch.nn as nn
class PixelNormLayer(nn.Module):
def __init__(self):
super(PixelNormLayer, self).__init__()
def forward(self, x):
return x / torch.sqrt(torch.mean(x ** 2, dim=1, keepdim=True) + 1e-08)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_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 libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | AleksiKnuutila/ganspace | PixelNormLayer | false | 1,913 | [
"Apache-2.0"
] | 0 | 23471a07c8b0d693fa7f1f2dfbb8b34ce22d9d38 | https://github.com/AleksiKnuutila/ganspace/tree/23471a07c8b0d693fa7f1f2dfbb8b34ce22d9d38 |
Warp | # 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 Tensor
import torch.nn as nn
assert_size_stride = torch._C._d... | dimagrshk/opt_flow_attack | Warp | false | 12,286 | [
"Apache-2.0"
] | 0 | 6bfad92abcf3eaae1a6ca05b865be072361636ed | https://github.com/dimagrshk/opt_flow_attack/tree/6bfad92abcf3eaae1a6ca05b865be072361636ed |
KLMutualLoss | # 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... | LT1st/ReID_Alined_beginer | KLMutualLoss | false | 13,990 | [
"MIT"
] | 370 | 1a12403a32d99900451ac05cd3623a9b770f6d24 | https://github.com/LT1st/ReID_Alined_beginer/tree/1a12403a32d99900451ac05cd3623a9b770f6d24 |
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