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 |
|---|---|---|---|---|---|---|---|---|---|---|
AE_big_2D_v2 | # 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 ... | gitter-badger/HEPAutoencoders | AE_big_2D_v2 | false | 12,459 | [
"Apache-2.0"
] | 0 | 43010cd66fa4335a04b30b87926148e1c8d92de9 | https://github.com/gitter-badger/HEPAutoencoders/tree/43010cd66fa4335a04b30b87926148e1c8d92de9 |
TTKernel | import torch
from torch import nn
import torch.nn.functional as F
class TTKernel(nn.Module):
def __init__(self, r_i, m, r_j):
super(TTKernel, self).__init__()
self.fc1 = nn.Bilinear(r_i, m, r_j, bias=False)
def forward(self, input_tensor_1, input_tensor_2):
tensor_transformed = self.... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | AndresOtero/TensorDecompositionMachineLearning | TTKernel | false | 16,905 | [
"MIT"
] | 3 | 455f16b405ec9d031999b0ebf9c5a68d3c20b233 | https://github.com/AndresOtero/TensorDecompositionMachineLearning/tree/455f16b405ec9d031999b0ebf9c5a68d3c20b233 |
ConvertPointsToHomogeneous | # 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... | JudyYe/frankmocap | ConvertPointsToHomogeneous | false | 9,175 | [
"BSD-3-Clause"
] | 0 | b6e63f344e852ebdbca0095643b5bc0466370891 | https://github.com/JudyYe/frankmocap/tree/b6e63f344e852ebdbca0095643b5bc0466370891 |
OrthogonalFusion | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | flrngel/DOLG-pytorch | OrthogonalFusion | false | 15,362 | [
"MIT"
] | 56 | 97732d2932ef6733f17cf8ac1aee990effe6fd64 | https://github.com/flrngel/DOLG-pytorch/tree/97732d2932ef6733f17cf8ac1aee990effe6fd64 |
BlendConv2d | import torch
import torch.nn as nn
class BlendConv2d(nn.Module):
def __init__(self, dim_in, dim_out, ksize=3, stride=1, padding=0,
dilation=1, groups=1, bias=True, transpose=False, **unused_kwargs):
super(BlendConv2d, self).__init__()
module = nn.ConvTranspose2d if transpose else nn.Conv2... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | D-hash-code/ffjord-rnode-finalweek-mnist | BlendConv2d | false | 2,150 | [
"MIT"
] | 0 | 4cabcbadda79c68df53ec25f1f8fe03cfeee78f9 | https://github.com/D-hash-code/ffjord-rnode-finalweek-mnist/tree/4cabcbadda79c68df53ec25f1f8fe03cfeee78f9 |
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... | Fkaneko/kaggle-hpa-single-cell-image-classification | FocalLoss | false | 5,164 | [
"MIT"
] | 1 | 52000cbf5c7eec6ace29274d9e85b5b24fac281b | https://github.com/Fkaneko/kaggle-hpa-single-cell-image-classification/tree/52000cbf5c7eec6ace29274d9e85b5b24fac281b |
ConvBlock | # 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 typing import List
from typing import Optional
from typing impo... | eivtho/PyLaia | ConvBlock | false | 15,292 | [
"MIT"
] | 89 | 2a7a6e2eeb9b5af68c0faed0c564b02063e72be0 | https://github.com/eivtho/PyLaia/tree/2a7a6e2eeb9b5af68c0faed0c564b02063e72be0 |
LogReg | import torch
import torch.nn as nn
class LogReg(nn.Module):
"""Logreg class."""
def __init__(self, num_features: 'int', num_classes: 'int'):
"""Initialize the class."""
super().__init__()
self.lin_layer = nn.Linear(in_features=num_features, out_features=
num_classes, bias=... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | BruceRayWilson/sambanova_starter | LogReg | false | 8,889 | [
"MIT"
] | 0 | be1b01369b040d00f174a0ee1fdb22e89ef40062 | https://github.com/BruceRayWilson/sambanova_starter/tree/be1b01369b040d00f174a0ee1fdb22e89ef40062 |
HingeDiscriminatorLossCutMix | import torch
from typing import Tuple
import torch.nn as nn
class HingeDiscriminatorLossCutMix(nn.Module):
"""
This class implements the hinge gan loss for the discriminator network when utilizing cut mix augmentation.
"""
def __init__(self) ->None:
"""
Constructor method
"""
... | 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... | ChristophReich1996/Multi-StyleGAN | HingeDiscriminatorLossCutMix | false | 17,112 | [
"MIT"
] | 7 | 988f2dfea85b3205126b40c61edfb28107eb3173 | https://github.com/ChristophReich1996/Multi-StyleGAN/tree/988f2dfea85b3205126b40c61edfb28107eb3173 |
CmapPafHead | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
import torch.nn
import torch.optim
assert_size_stride = ... | ajsampathk/trt_pose | CmapPafHead | false | 18,233 | [
"MIT"
] | 7 | 592e038cacaf43b6a502b759a035a4e7cae9db9e | https://github.com/ajsampathk/trt_pose/tree/592e038cacaf43b6a502b759a035a4e7cae9db9e |
PatchEmbedding | import torch
import torch.nn as nn
class PatchEmbedding(nn.Module):
def __init__(self, image_size, patch_size, embed_dim, channels):
super().__init__()
self.image_size = image_size
if image_size[0] % patch_size != 0 or image_size[1] % patch_size != 0:
raise ValueError(
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | shampooma/segmenter | PatchEmbedding | false | 16,395 | [
"MIT"
] | 418 | b08fd481da6758e37d108ba28676229b62f757aa | https://github.com/shampooma/segmenter/tree/b08fd481da6758e37d108ba28676229b62f757aa |
Feedforward | import torch
class Feedforward(torch.nn.Module):
def __init__(self, input_size, hidden_size):
super(Feedforward, self).__init__()
self.input_size = input_size
self.hidden_size = hidden_size
self.fc1 = torch.nn.Linear(self.input_size, self.hidden_size)
self.relu = torch.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
assert_size_stride = torch._C... | Orion34-lanbo/BladeDISC | Feedforward | false | 9,337 | [
"Apache-2.0"
] | 0 | 2310dfe6bd9e38bf28f4f4afd4189f30893c9249 | https://github.com/Orion34-lanbo/BladeDISC/tree/2310dfe6bd9e38bf28f4f4afd4189f30893c9249 |
ClassificationModel | # 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_... | alexrusciano/nms_free_retinanet | ClassificationModel | false | 9,746 | [
"Apache-2.0"
] | 0 | 3461a86e9dea71a756b92a434c62798bbf86b52d | https://github.com/alexrusciano/nms_free_retinanet/tree/3461a86e9dea71a756b92a434c62798bbf86b52d |
SimpleConvTranspose2dModule | # 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
import torch.jit
import torch... | opti-mix/glow | SimpleConvTranspose2dModule | false | 7,399 | [
"Apache-2.0"
] | 1 | 4ba074df5da9822986a23a6679ab592c22660f6d | https://github.com/opti-mix/glow/tree/4ba074df5da9822986a23a6679ab592c22660f6d |
LinearModel | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cu... | TDteach/SEAM | LinearModel | false | 1,126 | [
"MIT"
] | 0 | 231447dad15403e7620adcf6629b6e7fccc4b809 | https://github.com/TDteach/SEAM/tree/231447dad15403e7620adcf6629b6e7fccc4b809 |
InverseSigmoid | # 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.data
assert_size_stride = torch._C._dynamo.guards.asse... | khoehlein/fV-SRN | InverseSigmoid | false | 3,831 | [
"MIT"
] | 0 | 601f3e952b090df92e875c233c2c9ca646523948 | https://github.com/khoehlein/fV-SRN/tree/601f3e952b090df92e875c233c2c9ca646523948 |
Temperature | import torch
import torch.nn as nn
class Temperature(nn.Module):
"""Temperature wrapper for nn.Sequential."""
def __init__(self, temperature):
super(Temperature, self).__init__()
self.temperature = temperature
def forward(self, data):
return data / self.temperature
def get_inpu... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
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_predictor | Temperature | false | 8,636 | [
"MIT"
] | 19 | 58071311310c45c1efabb34a4003b96a1c58901a | https://github.com/PaccMann/paccmann_predictor/tree/58071311310c45c1efabb34a4003b96a1c58901a |
TriangleMultiplicativeModule | # 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... | aced125/alphafold2 | TriangleMultiplicativeModule | false | 6,083 | [
"MIT"
] | 1 | c85682ece37d37c608773cef3ec342b9ddc7fca0 | https://github.com/aced125/alphafold2/tree/c85682ece37d37c608773cef3ec342b9ddc7fca0 |
folder | # 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.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 |
RMSELoss | import torch
import torch.nn as nn
class RMSELoss(nn.Module):
def __init__(self):
super().__init__()
self.mse = nn.MSELoss()
def forward(self, x, y):
loss = torch.sqrt(self.mse(x, y))
return loss
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | Aquarium1222/Electricity-Forecasting | RMSELoss | false | 1,964 | [
"MIT"
] | 0 | 9f945d3fd8006e5d77da08ff7861577965109ec8 | https://github.com/Aquarium1222/Electricity-Forecasting/tree/9f945d3fd8006e5d77da08ff7861577965109ec8 |
RPN | import torch
from torch.nn import functional as F
from torch import nn
from torchvision import models as models
import torch.onnx
def conv(in_channels, out_channels, kernel_size=3, padding=1, bn=True,
dilation=1, stride=1, relu=True, bias=True):
modules = [nn.Conv2d(in_channels, out_channels, kernel_size, str... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | vadimadr/openvino_training_extensions | RPN | false | 11,040 | [
"Apache-2.0"
] | 0 | 5d64b8423c8eb7b374ed629fad938359d34a07d2 | https://github.com/vadimadr/openvino_training_extensions/tree/5d64b8423c8eb7b374ed629fad938359d34a07d2 |
SeqToSeqAtten | import torch
import torch.utils.data
def masked_softmax(x, m=None, dim=-1):
"""
Softmax with mask
:param x:
:param m:
:param dim:
:return:
"""
if m is not None:
m = m.float()
x = x * m
e_x = torch.exp(x - torch.max(x, dim=dim, keepdim=True)[0])
if m is not None:... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | xdong73S/Match_LSTM_v2.0 | SeqToSeqAtten | false | 4,572 | [
"MIT"
] | 0 | dfb8cfbc2a5dafc6655eecf151a7dbcf808cd729 | https://github.com/xdong73S/Match_LSTM_v2.0/tree/dfb8cfbc2a5dafc6655eecf151a7dbcf808cd729 |
Normalize | import torch
from torch import nn
import torch.nn.functional as F
import torch.utils.data.distributed
from torch.cuda.amp import autocast as autocast
class Normalize(nn.Module):
def __init__(self, p=2):
super(Normalize, self).__init__()
self.p = p
def forward(self, x):
return F.norma... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
import ... | ChongjianGE/CARE | Normalize | false | 13,499 | [
"MIT"
] | 57 | 3187afb0a2e56d40684bd5a83bf4eda145431e7b | https://github.com/ChongjianGE/CARE/tree/3187afb0a2e56d40684bd5a83bf4eda145431e7b |
N_TransE | import torch
import torch.nn.functional as F
class N_TransE(torch.nn.Module):
def __init__(self, p, params):
super(N_TransE, self).__init__()
self.p = p
self.params = params
def forward(self, e1, r, e2):
pred = -torch.norm(e1 + r - e2, p=self.p, dim=1)
return pred
... | 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
assert_size_stride = torch._C._dynamo.guards.as... | TMUITLab/EAFR | N_TransE | false | 1,115 | [
"MIT"
] | 0 | dadb6485d48711ccb8aa2f03760aeb437645f1ff | https://github.com/TMUITLab/EAFR/tree/dadb6485d48711ccb8aa2f03760aeb437645f1ff |
DiceBCELoss | # 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... | Latterlig96/DCUnet | DiceBCELoss | false | 8,456 | [
"MIT"
] | 11 | 87d1c137a60177d6daf1dfff0483678d5580fda0 | https://github.com/Latterlig96/DCUnet/tree/87d1c137a60177d6daf1dfff0483678d5580fda0 |
AdaptiveCos | # 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
from torch.nn.parameter import Parameter
assert_size_stride = torch._C._d... | ndem0/PINA | AdaptiveCos | false | 10,717 | [
"MIT"
] | 0 | 1812ddb8d96a9c8aeb80ce35002dbd115e7d7931 | https://github.com/ndem0/PINA/tree/1812ddb8d96a9c8aeb80ce35002dbd115e7d7931 |
FocalLoss | import torch
import torch.nn as nn
from time import *
class FocalLoss(nn.Module):
def __init__(self, gamma=2, eps=1e-07):
super(FocalLoss, self).__init__()
self.gamma = gamma
self.eps = eps
self.ce = nn.CrossEntropyLoss()
def forward(self, input, target):
logp = self.... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | BillKerman/FaceNetCustomized | FocalLoss | false | 16,988 | [
"MIT"
] | 4 | 30bb99b62f960034c4aa4206d7dc22de672a997f | https://github.com/BillKerman/FaceNetCustomized/tree/30bb99b62f960034c4aa4206d7dc22de672a997f |
MSELoss | # 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 functools
import torch.nn as nn
import torch.nn.functional as F
assert_size_stride... | AtticusJohnson/mmdetection | MSELoss | false | 11,231 | [
"Apache-2.0"
] | 0 | d8d89bafcce13d3b32b1fb3366be3bb9830546c2 | https://github.com/AtticusJohnson/mmdetection/tree/d8d89bafcce13d3b32b1fb3366be3bb9830546c2 |
SELoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | Benjamin-Etheredge/lightning-bolts | SELoss | false | 143 | [
"Apache-2.0"
] | 0 | 1971d6a924729940b98793aa7751bdf769350aca | https://github.com/Benjamin-Etheredge/lightning-bolts/tree/1971d6a924729940b98793aa7751bdf769350aca |
ResidualBlockNoBN | import torch
from torch import nn
class ResidualBlockNoBN(nn.Module):
def __init__(self, in_channels, out_channels, stride=1):
super(ResidualBlockNoBN, self).__init__()
self.conv1 = nn.Conv2d(in_channels=in_channels, out_channels=
out_channels, kernel_size=(3, 3), stride=stride, paddi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | Suvapna/ArtificialLaughter | ResidualBlockNoBN | false | 1,100 | [
"MIT"
] | 0 | a7114134b698f829e05e74cac30052e18b260f85 | https://github.com/Suvapna/ArtificialLaughter/tree/a7114134b698f829e05e74cac30052e18b260f85 |
SmoothNetResBlock | # 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... | ALISCIFP/mmpose | SmoothNetResBlock | false | 2,064 | [
"Apache-2.0"
] | 0 | 2433e3dbcc44baa2253e2a7c748ba0216937933e | https://github.com/ALISCIFP/mmpose/tree/2433e3dbcc44baa2253e2a7c748ba0216937933e |
CReLU | import torch
import torch.nn as nn
class Scale(nn.Module):
def __init__(self, nchannels, bias=True, init_scale=1.0):
super().__init__()
self.nchannels = nchannels
self.weight = nn.Parameter(torch.Tensor(1, nchannels, 1, 1))
if bias:
self.bias = nn.Parameter(torch.Tenso... | 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... | CuongNguyen218/ObjectDetection-OneStageDet | CReLU | false | 327 | [
"MIT"
] | 0 | 60efe8b0ee6782b2aea20a32264b2ce1fc21901f | https://github.com/CuongNguyen218/ObjectDetection-OneStageDet/tree/60efe8b0ee6782b2aea20a32264b2ce1fc21901f |
GCN_conv | import math
import torch
import torch.utils.data
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
class GCN_conv(nn.Module):
def __init__(self, in_ft, out_ft, bias=False, dropout=0.0, activation=F
.relu):
super(GCN_conv, self).__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
import math
import torch.util... | haoyfan/Dual-SVDAE | GCN_conv | false | 6,788 | [
"MIT"
] | 1 | 1fcb61960606d743438f33b740cb434dbfcfd727 | https://github.com/haoyfan/Dual-SVDAE/tree/1fcb61960606d743438f33b740cb434dbfcfd727 |
P_net | import torch
import torch.nn as nn
import torch.nn.functional as F
class P_net(nn.Module):
def __init__(self, X_dim, N, z_dim):
super(P_net, self).__init__()
self.lin1 = nn.Linear(z_dim, int(N / 2))
self.lin2 = nn.Linear(int(N / 2), N)
self.lin4 = nn.Linear(N, X_dim)
def forw... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | arnaghosh/VoxNet | P_net | false | 1,472 | [
"MIT"
] | 0 | 45fe8e9ff28b02f21b8991486317ff61cfa5d553 | https://github.com/arnaghosh/VoxNet/tree/45fe8e9ff28b02f21b8991486317ff61cfa5d553 |
GroupWiseLinear | # 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
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
as... | davidaderup/query2labels | GroupWiseLinear | false | 15,130 | [
"MIT"
] | 164 | 5a10c861dda85d94ba01ec6ad4119eef67a9f441 | https://github.com/davidaderup/query2labels/tree/5a10c861dda85d94ba01ec6ad4119eef67a9f441 |
Linear_dynamics | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._... | alanpaivaa/egnn | Linear_dynamics | false | 14,789 | [
"MIT"
] | 142 | e9ca6c0c3e1d30a7598efbd66034121b4af8dccc | https://github.com/alanpaivaa/egnn/tree/e9ca6c0c3e1d30a7598efbd66034121b4af8dccc |
StyleAdaptiveLayerNorm | import torch
import torch.nn as nn
import torch.utils.data.distributed
class AffineLinear(nn.Module):
def __init__(self, in_dim, out_dim):
super(AffineLinear, self).__init__()
affine = nn.Linear(in_dim, out_dim)
self.affine = affine
def forward(self, input):
return self.affin... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | ishine/StyleSpeech-1 | StyleAdaptiveLayerNorm | false | 15,625 | [
"MIT"
] | 106 | f939cf9cb981db7b738fa9c9c9a7fea2dfdd0766 | https://github.com/ishine/StyleSpeech-1/tree/f939cf9cb981db7b738fa9c9c9a7fea2dfdd0766 |
ConsensusAttention | # 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.... | Tahlor/glom-pytorch | ConsensusAttention | false | 1,130 | [
"MIT"
] | 0 | 45b2fc52af5288cd53611e497a70d53ffa303410 | https://github.com/Tahlor/glom-pytorch/tree/45b2fc52af5288cd53611e497a70d53ffa303410 |
ResidualAttention | import torch
from torch import nn
class ResidualAttention(nn.Module):
def __init__(self, channel=512, num_class=1000, la=0.2):
super().__init__()
self.la = la
self.fc = nn.Conv2d(in_channels=channel, out_channels=num_class,
kernel_size=1, stride=1, bias=False)
def forward... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | LeftAttention/Attention-Codebase | ResidualAttention | false | 17,639 | [
"Apache-2.0"
] | 6 | 348ec66233a7c0f95a3cb5f0f11641e2a7a9b9c3 | https://github.com/LeftAttention/Attention-Codebase/tree/348ec66233a7c0f95a3cb5f0f11641e2a7a9b9c3 |
LayerNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | karan-deepsync/FastSpeech2 | LayerNorm | false | 15,783 | [
"Apache-2.0"
] | 148 | 84ad261db4a865536b2e15dfb8346644c3192704 | https://github.com/karan-deepsync/FastSpeech2/tree/84ad261db4a865536b2e15dfb8346644c3192704 |
Hsigmoid | import torch
import torch.nn as nn
from torch.nn import functional as F
class Hsigmoid(nn.Module):
def __init__(self, inplace=True):
super(Hsigmoid, self).__init__()
self.inplace = inplace
def forward(self, x):
return F.relu6(x + 3.0, inplace=self.inplace) / 6.0
def get_inputs():
... | 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... | Alterith/Dense_Video_Captioning_Feature_Extraction_Model_Choice | Hsigmoid | false | 4,826 | [
"MIT"
] | 1 | 65d0f2d26698cc8f7a5ffb564936113e2bbec201 | https://github.com/Alterith/Dense_Video_Captioning_Feature_Extraction_Model_Choice/tree/65d0f2d26698cc8f7a5ffb564936113e2bbec201 |
LinearEncoder | # 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.... | RussellMcGrady/Multi-head-attention-based-MetaR | LinearEncoder | false | 2,787 | [
"Apache-2.0"
] | 0 | 4e47546da35bd57ff7ab16d0fed19be31c063563 | https://github.com/RussellMcGrady/Multi-head-attention-based-MetaR/tree/4e47546da35bd57ff7ab16d0fed19be31c063563 |
BinaryLogisticRegressionLoss | import torch
import torch.nn as nn
def binary_logistic_regression_loss(reg_score, label, threshold=0.5,
ratio_range=(1.05, 21), eps=1e-05):
"""Binary Logistic Regression Loss."""
label = label.view(-1)
reg_score = reg_score.contiguous().view(-1)
pmask = (label > threshold).float()
num_positive... | 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
... | giahaowjx/mmaction2 | BinaryLogisticRegressionLoss | false | 10,327 | [
"Apache-2.0"
] | 0 | 4f95e9b91354acdcae768ce94e01d3821bba0154 | https://github.com/giahaowjx/mmaction2/tree/4f95e9b91354acdcae768ce94e01d3821bba0154 |
LosslessRGB | import torch
import torch.nn.parallel
import torch.utils.data
from torch import nn
import torch.fft
class LosslessRGB(nn.Module):
def forward(self, ycbcr: 'torch.Tensor'):
return torch.cat([ycbcr[:, 2:3] + ycbcr[:, 0:1] - 0.25 * ycbcr[:, 1
:2] - 0.25 * ycbcr[:, 2:3], ycbcr[:, 0:1] - 0.25 * yc... | 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.parallel
import torch.utils.data
from torch import nn
import torch.fft
assert_size_stride = torch._C._dynamo.guards.assert_s... | KazutakaYamanouchi/bachelor-study | LosslessRGB | false | 2,618 | [
"Apache-2.0"
] | 0 | a5b8392459e7649cb8a35d09e65bd269d13b5297 | https://github.com/KazutakaYamanouchi/bachelor-study/tree/a5b8392459e7649cb8a35d09e65bd269d13b5297 |
ConcatSquashLinear | import torch
import torch.nn as nn
import torch.utils.data
class ConcatSquashLinear(nn.Module):
def __init__(self, dim_in, dim_out):
super(ConcatSquashLinear, self).__init__()
self._layer = nn.Linear(dim_in, dim_out)
self._hyper_bias = nn.Linear(1, dim_out, bias=False)
self._hyper... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | Justin-Tan/ffjord | ConcatSquashLinear | false | 695 | [
"MIT"
] | 0 | 2caf8a4ff84933672fe0d94255d665b3dd7a6791 | https://github.com/Justin-Tan/ffjord/tree/2caf8a4ff84933672fe0d94255d665b3dd7a6791 |
MaxPoolPad | import torch
import torch.nn as nn
import torch.nn.init
class MaxPoolPad(nn.Module):
def __init__(self):
super(MaxPoolPad, self).__init__()
self.pad = nn.ZeroPad2d((1, 0, 1, 0))
self.pool = nn.MaxPool2d(3, stride=2, padding=1)
def forward(self, x):
x = self.pad(x)
x =... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.nn.init
assert_size_stride = torch._C._dynamo.guards.a... | MichoelSnow/data_science | MaxPoolPad | false | 9,868 | [
"MIT"
] | 0 | 7f6c054624268308ec4126a601c9fa8bc5de157c | https://github.com/MichoelSnow/data_science/tree/7f6c054624268308ec4126a601c9fa8bc5de157c |
TEM | from _paritybench_helpers import _mock_config
import torch
import torch.nn.functional as F
import torch.nn as nn
from torch.nn import init
import torch.nn.parallel
class TEM(torch.nn.Module):
def __init__(self, opt):
super(TEM, self).__init__()
self.feat_dim = opt['tem_feat_dim']
self.tem... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from to... | NEUdeep/BSN | TEM | false | 5,634 | [
"MIT"
] | 1 | e987cc159976ebe54027b562d833a92a5aadf864 | https://github.com/NEUdeep/BSN/tree/e987cc159976ebe54027b562d833a92a5aadf864 |
Rescale | import torch
import torch.nn as nn
import torch.utils.data
class Rescale(nn.Module):
"""Per-channel rescaling. Need a proper `nn.Module` so we can wrap it
with `torch.nn.utils.weight_norm`.
Args:
num_channels (int): Number of channels in the input.
"""
def __init__(self, num_channels):
super(Res... | 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.... | Catherine0505/mar-scf-flow | Rescale | false | 17,083 | [
"Apache-2.0"
] | 10 | aa7c3564cb9f2967c5e580a633516dba1b597f98 | https://github.com/Catherine0505/mar-scf-flow/tree/aa7c3564cb9f2967c5e580a633516dba1b597f98 |
PrimaryCaps | import torch
import torch.nn as nn
class PrimaryCaps(nn.Module):
"""
输入:(B,C,H,W)=(B,256,20,20)
输出：(B,C_N,C_L)=(B,32*6*6, 8)=(B,1152,8)
C_N:capsule_num，胶囊的个数
C_L:capsule_length，每个胶囊的长度
"""
def __init__(self, capsule_length=8, in_channels=256, out_channels=32,
capsu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | daxiongpro/pytorch-tutorial | PrimaryCaps | false | 1,839 | [
"MIT"
] | 0 | abafc32f7ee1092024085f703e4ced51ce358a1b | https://github.com/daxiongpro/pytorch-tutorial/tree/abafc32f7ee1092024085f703e4ced51ce358a1b |
translatedSigmoid | import torch
from torch import nn
class translatedSigmoid(nn.Module):
def __init__(self):
super(translatedSigmoid, self).__init__()
self.beta = nn.Parameter(torch.tensor([-3.5]))
def forward(self, x):
beta = torch.nn.functional.softplus(self.beta)
alpha = -beta * 6.9077542789... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.gua... | MachineLearningLifeScience/What-is-a-meaningful-representation-of-protein-sequences | translatedSigmoid | false | 17,664 | [
"BSD-3-Clause"
] | 4 | 2c24db6ee8763b0b6098d7509cf3325647931c11 | https://github.com/MachineLearningLifeScience/What-is-a-meaningful-representation-of-protein-sequences/tree/2c24db6ee8763b0b6098d7509cf3325647931c11 |
Conv2D | # 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 import nn
assert_size_stride = torch._C._dynamo.guards.as... | Yusoi/mmdetection | Conv2D | false | 9,734 | [
"Apache-2.0"
] | 0 | cbb5fb00f6e124fbb2c15e7e3438d7fa76b8850a | https://github.com/Yusoi/mmdetection/tree/cbb5fb00f6e124fbb2c15e7e3438d7fa76b8850a |
ModulatedConv2d | import math
import torch
import torch.utils.data
import torch
import torch.nn as nn
import torch.nn.functional as F
def make_kernel(k):
k = torch.tensor(k, dtype=torch.float32)
if len(k.shape) == 1:
k = k[None, :] * k[:, None]
k /= k.sum()
return k
def upfirdn2d_native(input, kernel, up_x, u... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | a11isonliu/contrastive-unpaired-translation | ModulatedConv2d | false | 9,861 | [
"BSD-3-Clause"
] | 0 | 67651ed9877cae121d9398f46094ce8dbc678802 | https://github.com/a11isonliu/contrastive-unpaired-translation/tree/67651ed9877cae121d9398f46094ce8dbc678802 |
LinearActivation | from torch.nn import Module
import torch
import torch.nn as nn
class LinearActivation(Module):
def __init__(self, in_features, out_features, act='gelu', bias=True):
super(LinearActivation, self).__init__()
self.Linear = nn.Linear(in_features, out_features, bias=bias)
if act == 'relu':
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch.nn impor... | codecaution/Hetu | LinearActivation | false | 1,726 | [
"Apache-2.0"
] | 0 | e278732c2fe3554c8d576585f5bcbf79ade31b68 | https://github.com/codecaution/Hetu/tree/e278732c2fe3554c8d576585f5bcbf79ade31b68 |
MultiHeadAttention | import torch
import torch.nn as nn
class ScaledDotProductAttention(nn.Module):
def __init__(self, d_k):
super(ScaledDotProductAttention, self).__init__()
self.scale = d_k ** -0.5
def forward(self, q, k, v, mask):
x = torch.matmul(q, k.transpose(-2, -1))
x = x if mask is None ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | jaehyek/attention-is-all-you-need | MultiHeadAttention | false | 12,604 | [
"MIT"
] | 0 | 9b421f7c98414aeb9f397c5195e3a6a9080a4669 | https://github.com/jaehyek/attention-is-all-you-need/tree/9b421f7c98414aeb9f397c5195e3a6a9080a4669 |
InterModalityUpdate | # 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.... | Ruiver/CTCNet | InterModalityUpdate | false | 17,913 | [
"Apache-2.0"
] | 6 | 539e55ec9fed06028379d35dfd5cd4074755ffd8 | https://github.com/Ruiver/CTCNet/tree/539e55ec9fed06028379d35dfd5cd4074755ffd8 |
LinfDistance | import torch
from torch import nn
import torch.autograd
class LinfDistance(nn.Module):
def forward(self, img1, img2):
return (img1 - img2).reshape(img1.shape[0], -1).abs().max(dim=1)[0]
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
i... | cassidylaidlaw/perceptual-advex | LinfDistance | false | 15,008 | [
"MIT"
] | 45 | d39136eb5b5e950442456ddade6b4f4fba3dd8f6 | https://github.com/cassidylaidlaw/perceptual-advex/tree/d39136eb5b5e950442456ddade6b4f4fba3dd8f6 |
InvertedFactorScalar | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | billpsomas/incremental_learning.pytorch | InvertedFactorScalar | false | 14,959 | [
"MIT"
] | 277 | a401a6609fc61c74698739cf937c0ece1c10913f | https://github.com/billpsomas/incremental_learning.pytorch/tree/a401a6609fc61c74698739cf937c0ece1c10913f |
MNIST_FC | import torch
import torch.nn as nn
import torch.nn.functional as F
class MNIST_FC(nn.Module):
def __init__(self):
super().__init__()
self.fc1 = nn.Linear(28 * 28, 32)
self.fc2 = nn.Linear(32, 10)
def forward(self, xb):
xb = xb.view(-1, 28 * 28)
xb = F.relu(self.fc1(xb... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | lihebi/AdvAE | MNIST_FC | false | 7,084 | [
"MIT"
] | 1 | 56dea2a33c7da64bcc577b0c061a38406fdde101 | https://github.com/lihebi/AdvAE/tree/56dea2a33c7da64bcc577b0c061a38406fdde101 |
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
from torch import nn
assert_s... | HephaestusProject/pytorch-CharLM | Highway | false | 17,363 | [
"MIT"
] | 4 | ebe8b9a04c4ba4dcf78d1f2673edb90731a5f3ad | https://github.com/HephaestusProject/pytorch-CharLM/tree/ebe8b9a04c4ba4dcf78d1f2673edb90731a5f3ad |
Expand | import torch
import torch.nn as nn
class Expand(nn.Module):
def __init__(self, gain=2):
super().__init__()
self.gain = gain
def forward(self, x):
b, c, h, w = x.size()
s = self.gain
x = x.view(b, s, s, c // s ** 2, h, w)
x = x.permute(0, 3, 4, 1, 5, 2).contigu... | 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... | GoalballAnalysis/GUI | Expand | false | 2,304 | [
"MIT"
] | 0 | c7f1cc27f4fd7f861c3ca09f5ca25d1a3f19a8a7 | https://github.com/GoalballAnalysis/GUI/tree/c7f1cc27f4fd7f861c3ca09f5ca25d1a3f19a8a7 |
MaxPoolPad | import torch
from torch import nn
class MaxPoolPad(nn.Module):
def __init__(self):
super(MaxPoolPad, self).__init__()
self.pad = nn.ZeroPad2d((1, 0, 1, 0))
self.pool = nn.MaxPool2d(3, stride=2, padding=1)
def forward(self, x):
x = self.pad(x)
x = self.pool(x)
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | MarioProjects/pytorchlib | MaxPoolPad | false | 5,576 | [
"MIT"
] | 1 | 81ea32304d899fbd10ae1efe1d124c0d7bc96f5c | https://github.com/MarioProjects/pytorchlib/tree/81ea32304d899fbd10ae1efe1d124c0d7bc96f5c |
PositionwiseFeedForward | import torch
import torch.nn as nn
import torch.cuda
class Bottle(nn.Module):
def forward(self, input):
if len(input.size()) <= 2:
return super(Bottle, self).forward(input)
size = input.size()[:2]
out = super(Bottle, self).forward(input.view(size[0] * size[1], -1))
ret... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | wenh06/OpenAttack | PositionwiseFeedForward | false | 10,976 | [
"MIT"
] | 0 | 412d1b2777dea5009fe97ac264044bfda65dfa5d | https://github.com/wenh06/OpenAttack/tree/412d1b2777dea5009fe97ac264044bfda65dfa5d |
decoder3 | # 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.... | guswl8033/ARtists | decoder3 | false | 3,565 | [
"Apache-2.0"
] | 0 | d353195872c1ef1a1aa68659a32fb47779a416fc | https://github.com/guswl8033/ARtists/tree/d353195872c1ef1a1aa68659a32fb47779a416fc |
CifarDownsampling | import torch
import torch.nn as nn
import torch.nn.functional as F
class CifarDownsampling(nn.Module):
def __init__(self, planes):
super(CifarDownsampling, self).__init__()
self.planes = planes
def forward(self, x):
return F.pad(x[:, :, ::2, ::2], (0, 0, 0, 0, self.planes // 4, 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... | alechat/PLCiL | CifarDownsampling | false | 3,077 | [
"Apache-2.0"
] | 0 | f71fe92cb7781097d3320c28601e06add70f64f9 | https://github.com/alechat/PLCiL/tree/f71fe92cb7781097d3320c28601e06add70f64f9 |
MLP_Attention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Coldog2333/DGMN-pytorch | MLP_Attention | false | 2,124 | [
"Apache-2.0"
] | 0 | c34248afca516625c2ac2fc6d6f4ce8fe2988c99 | https://github.com/Coldog2333/DGMN-pytorch/tree/c34248afca516625c2ac2fc6d6f4ce8fe2988c99 |
EmissionModel | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.utils.dat... | dendisuhubdy/pytorch_HMM | EmissionModel | false | 15,156 | [
"Apache-2.0"
] | 88 | 3235326027328e1b0377b17f9dad8fcc56a3668c | https://github.com/dendisuhubdy/pytorch_HMM/tree/3235326027328e1b0377b17f9dad8fcc56a3668c |
DarknetMish | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn.functional as F
from torch import nn
assert_size_stride =... | cooked-sashimi/Yet-Another-YOLOv4-Pytorch | DarknetMish | false | 15,076 | [
"MIT"
] | 133 | c884ef8849987a75b0e17eba1b739c22d3782e90 | https://github.com/cooked-sashimi/Yet-Another-YOLOv4-Pytorch/tree/c884ef8849987a75b0e17eba1b739c22d3782e90 |
TanhDeepLiftModel | # 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_... | ngduduong/captum | TanhDeepLiftModel | false | 4,078 | [
"BSD-3-Clause"
] | 0 | 6fe5f0f23ea975e73e0c0dee79bdc01b4223d283 | https://github.com/ngduduong/captum/tree/6fe5f0f23ea975e73e0c0dee79bdc01b4223d283 |
SoftWingLoss | # 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 math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | ALISCIFP/mmpose | SoftWingLoss | false | 2,054 | [
"Apache-2.0"
] | 0 | 2433e3dbcc44baa2253e2a7c748ba0216937933e | https://github.com/ALISCIFP/mmpose/tree/2433e3dbcc44baa2253e2a7c748ba0216937933e |
MLP | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | adijo/ift6135-rnn | MLP | false | 9,657 | [
"Apache-2.0"
] | 0 | 88ebcd621cea4042f5ada688f2452ce25d02b761 | https://github.com/adijo/ift6135-rnn/tree/88ebcd621cea4042f5ada688f2452ce25d02b761 |
FusedUpsample | # 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
from math import sqrt
assert_size_stride = torch._C._dynam... | KwonGihyun/DiagonalGAN | FusedUpsample | false | 8,450 | [
"MIT"
] | 13 | 9e401c00e741d700f85df2c715ee11c1e66e1d1c | https://github.com/KwonGihyun/DiagonalGAN/tree/9e401c00e741d700f85df2c715ee11c1e66e1d1c |
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.... | luyu-fan/LRCM | MultiHeadAttention | false | 7,144 | [
"MIT"
] | 1 | 6b0e4d7998bc4969afa764eb753077e3f858f1ba | https://github.com/luyu-fan/LRCM/tree/6b0e4d7998bc4969afa764eb753077e3f858f1ba |
SoftMaxAvgPoolModel | import torch
import torch.cuda
import torch.nn
import torch.utils.data
import torch.fx
import torch.utils.tensorboard._pytorch_graph
import torch.onnx.symbolic_caffe2
class SoftMaxAvgPoolModel(torch.nn.Module):
def __init__(self):
super(SoftMaxAvgPoolModel, self).__init__()
self.sfmax = torch.nn.... | 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.cuda
impo... | quic-kyunggeu/aimet | SoftMaxAvgPoolModel | false | 13,208 | [
"BSD-3-Clause"
] | 0 | 877835d5aafcef17cf12864124977d3c128d4aca | https://github.com/quic-kyunggeu/aimet/tree/877835d5aafcef17cf12864124977d3c128d4aca |
SymKlCriterion | import torch
import torch.nn.functional as F
from torch.nn.modules.loss import _Loss
from torch.optim.lr_scheduler import *
class Criterion(_Loss):
def __init__(self, alpha=1.0, name='criterion'):
super().__init__()
"""Alpha is used to weight each loss term
"""
self.alpha = alpha
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch.... | kiminh/mt-dnn | SymKlCriterion | false | 7,038 | [
"MIT"
] | 1 | 133884b380244dbe74acc4d7507e551b2c5035b3 | https://github.com/kiminh/mt-dnn/tree/133884b380244dbe74acc4d7507e551b2c5035b3 |
CAE | # 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 ... | VincentYCYao/MVC-Net-pytorch | CAE | false | 9,597 | [
"MIT"
] | 0 | 31f826825cdfe862fbfe0fe19edc78c04d1dec55 | https://github.com/VincentYCYao/MVC-Net-pytorch/tree/31f826825cdfe862fbfe0fe19edc78c04d1dec55 |
MyBCEWithLogitsLoss | # 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... | huoxusg/ScenarioMeta | MyBCEWithLogitsLoss | false | 15,557 | [
"MIT"
] | 79 | ce753da45a3d46ac08961ffc71b2131ae3f7e551 | https://github.com/huoxusg/ScenarioMeta/tree/ce753da45a3d46ac08961ffc71b2131ae3f7e551 |
KLLoss | import torch
import torch.nn as nn
class KLLoss(nn.Module):
def forward(self, mu: 'torch.Tensor', sigma: 'torch.Tensor', target_mu:
'torch.Tensor', target_std: 'torch.Tensor'):
std1 = target_std
std2 = sigma
mean1 = target_mu
mean2 = mu
kl = torch.log(torch.abs(std... | 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
... | ncduy0303/wmt21-qe-task | KLLoss | false | 12,819 | [
"Apache-2.0"
] | 0 | 93082afd0c56fb8d60101457082116c79adeac50 | https://github.com/ncduy0303/wmt21-qe-task/tree/93082afd0c56fb8d60101457082116c79adeac50 |
ToRGB | import math
import torch
import torch.utils.data
import torch
import torch.nn as nn
import torch.nn.functional as F
def make_kernel(k):
k = torch.tensor(k, dtype=torch.float32)
if len(k.shape) == 1:
k = k[None, :] * k[:, None]
k /= k.sum()
return k
def upfirdn2d_native(input, kernel, up_x, u... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.utils.data
import torch
import torch.nn as nn
import to... | bomtorazek/contrastive-unpaired-translation | ToRGB | false | 12,203 | [
"BSD-3-Clause"
] | 0 | 07c048038375e1b9a4e464154b8dbc49f5e16ede | https://github.com/bomtorazek/contrastive-unpaired-translation/tree/07c048038375e1b9a4e464154b8dbc49f5e16ede |
GatedConv2d | import torch
import torch.nn as nn
import torch.utils.data
class GatedConv2d(nn.Module):
def __init__(self, input_channels, output_channels, kernel_size, stride,
padding, dilation=1, activation=None):
super(GatedConv2d, self).__init__()
self.activation = activation
self.sigmoid = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | Justin-Tan/ffjord | GatedConv2d | false | 693 | [
"MIT"
] | 0 | 2caf8a4ff84933672fe0d94255d665b3dd7a6791 | https://github.com/Justin-Tan/ffjord/tree/2caf8a4ff84933672fe0d94255d665b3dd7a6791 |
Critic | # 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 numpy as np
import tor... | moritzzzzz/Continuous_Control | Critic | false | 10,563 | [
"Apache-2.0"
] | 0 | 655530bdbbe77eb285c95246331be4636c0d076c | https://github.com/moritzzzzz/Continuous_Control/tree/655530bdbbe77eb285c95246331be4636c0d076c |
Normalize | import torch
import torch.nn as nn
class Normalize(nn.Module):
def __init__(self, power=2):
super(Normalize, self).__init__()
self.power = power
def forward(self, x):
norm = x.pow(self.power).sum(1, keepdim=True).pow(1.0 / self.power)
out = x.div(norm)
return out
de... | 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_... | Alice1820/CMC | Normalize | false | 2,081 | [
"BSD-2-Clause"
] | 0 | 4f4354b3a33ec9c0784baefd7d1d9798e191ead5 | https://github.com/Alice1820/CMC/tree/4f4354b3a33ec9c0784baefd7d1d9798e191ead5 |
MaxPoolStride1 | # 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
import torch.utils.data.distributed
import ... | accountcwd/pose-estimation-lite | MaxPoolStride1 | false | 6,067 | [
"MIT"
] | 1 | 36b6fa534c04a909d5722ace90a199c9590bb2eb | https://github.com/accountcwd/pose-estimation-lite/tree/36b6fa534c04a909d5722ace90a199c9590bb2eb |
Dummy | # 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... | Tomaz-Vieira/tiktorch | Dummy | false | 18,020 | [
"MIT"
] | 8 | 2d6803c4ba5e26e4b27bf8af6638040fa4fc5628 | https://github.com/Tomaz-Vieira/tiktorch/tree/2d6803c4ba5e26e4b27bf8af6638040fa4fc5628 |
ClippedLinearQuantization | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import... | Donfa1con/distiller | ClippedLinearQuantization | false | 11,531 | [
"Apache-2.0"
] | 0 | 645ee41bfebc463523b228ff087e41619607d8b2 | https://github.com/Donfa1con/distiller/tree/645ee41bfebc463523b228ff087e41619607d8b2 |
UpSampleBlock | # 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... | Qinaty/input-aware-backdoor-attack-release | UpSampleBlock | false | 2,743 | [
"MIT"
] | 0 | ce897adf4a3ce0d2badbd2b53233561fee6c7db7 | https://github.com/Qinaty/input-aware-backdoor-attack-release/tree/ce897adf4a3ce0d2badbd2b53233561fee6c7db7 |
_ScaledDotProductAttention | import torch
import torch.nn as nn
class _ScaledDotProductAttention(nn.Module):
def __init__(self, dropout: 'float'=None, scale: 'bool'=True):
super().__init__()
if dropout is not None:
self.dropout = nn.Dropout(p=dropout)
else:
self.dropout = dropout
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.... | Gian-Wiher/darts | _ScaledDotProductAttention | false | 5,201 | [
"Apache-2.0"
] | 1 | 0d267e08643e2e3f88163a5d955b8be75840c2f6 | https://github.com/Gian-Wiher/darts/tree/0d267e08643e2e3f88163a5d955b8be75840c2f6 |
FCLayer | # 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
fr... | dumpmemory/Pytorch-NLU | FCLayer | false | 15,260 | [
"Apache-2.0"
] | 115 | 864fb9acc7751fc51abd3d05d24b5a9a7eab7110 | https://github.com/dumpmemory/Pytorch-NLU/tree/864fb9acc7751fc51abd3d05d24b5a9a7eab7110 |
AvgPoolPad | import torch
import torch.utils.data
import torch.nn as nn
from torch import optim as optim
import torch.nn.parallel
class AvgPoolPad(nn.Module):
def __init__(self, stride=2, padding=1):
super(AvgPoolPad, self).__init__()
self.pad = nn.ZeroPad2d((1, 0, 1, 0))
self.pool = nn.AvgPool2d(3, s... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
import torch.nn as nn
from torch import optim as optim
import torch.nn.parallel
assert_size_stride = torch._C._dynam... | Exir-lxr/crldr-prune-pytorch | AvgPoolPad | false | 2,297 | [
"Apache-2.0"
] | 0 | adeb5e0b24ce66ff9531d4d947f72412c1b5c033 | https://github.com/Exir-lxr/crldr-prune-pytorch/tree/adeb5e0b24ce66ff9531d4d947f72412c1b5c033 |
ResidualPointnet | import torch
import torch.utils.data
import torch.nn as nn
class ResidualBlock(nn.Module):
def __init__(self, in_channels, out_channels, hidden_dim):
super().__init__()
self.fc_0 = nn.Conv1d(in_channels, hidden_dim, 1)
self.fc_1 = nn.Conv1d(hidden_dim, out_channels, 1)
self.activa... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | StructuralNeurobiologyLab/LightConvPoint | ResidualPointnet | false | 14,467 | [
"Apache-2.0"
] | 58 | 3f353f45e9e910fa390a74520dfd478e3e88f104 | https://github.com/StructuralNeurobiologyLab/LightConvPoint/tree/3f353f45e9e910fa390a74520dfd478e3e88f104 |
ReduceProd | # 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.onnx
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynam... | mil-tokyo/webdnn | ReduceProd | false | 16,090 | [
"MIT"
] | 1,967 | 38a60fd3e1a4e72bc01108189a3aa51e0752aecd | https://github.com/mil-tokyo/webdnn/tree/38a60fd3e1a4e72bc01108189a3aa51e0752aecd |
Net3 | # 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... | moritzschaefer/pavooc | Net3 | false | 7,274 | [
"MIT"
] | 1 | 735f5455f9a95a5734436a24e2aa92cf600c91af | https://github.com/moritzschaefer/pavooc/tree/735f5455f9a95a5734436a24e2aa92cf600c91af |
_TestNetStrided | import torch
import torch.cuda
import torch.nn.functional as F
import torch.nn
import torch.utils.data
import torch.fx
import torch.utils.tensorboard._pytorch_graph
class _TestNetStrided(torch.nn.Module):
def __init__(self):
super(_TestNetStrided, self).__init__()
self.conv1 = torch.nn.Conv2d(1, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | mikeseven/aimet | _TestNetStrided | false | 11,124 | [
"BSD-3-Clause"
] | 0 | 63211a4f259b6457c58dfae1097c70acb93319fe | https://github.com/mikeseven/aimet/tree/63211a4f259b6457c58dfae1097c70acb93319fe |
BertAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | hiaoxui/soft-prompts | BertAttention | false | 15,527 | [
"Apache-2.0"
] | 48 | 214dbedf735fe1c98ab2be3a26066d50ff0a86d8 | https://github.com/hiaoxui/soft-prompts/tree/214dbedf735fe1c98ab2be3a26066d50ff0a86d8 |
MaskLSTMCell | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class MaskLSTMCell(nn.Module):
def __init__(self, options):
super(MaskLSTMCell, self).__init__()
self.n_in = options['n_in']
self.n_out = options['n_out']
self.input = nn.Linear(self.n_in, self.n_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
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | KaiQiangSong/joint_parse_summ | MaskLSTMCell | false | 8,813 | [
"BSD-3-Clause"
] | 29 | 5d4a40d9a681bc8b06c847643d810846f3867216 | https://github.com/KaiQiangSong/joint_parse_summ/tree/5d4a40d9a681bc8b06c847643d810846f3867216 |
ModulatedConv2d | # 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 math
import ... | a11isonliu/contrastive-unpaired-translation | ModulatedConv2d | false | 9,861 | [
"BSD-3-Clause"
] | 0 | 67651ed9877cae121d9398f46094ce8dbc678802 | https://github.com/a11isonliu/contrastive-unpaired-translation/tree/67651ed9877cae121d9398f46094ce8dbc678802 |
Critic | # 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 ... | dlrudco/pg_travel | Critic | false | 1,849 | [
"MIT"
] | 0 | 33733b624894095096af8201f7597c3244d3480d | https://github.com/dlrudco/pg_travel/tree/33733b624894095096af8201f7597c3244d3480d |
SigmoidFocalLoss | # 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... | YinlinHu/fcos-pytorch | SigmoidFocalLoss | false | 12,008 | [
"MIT"
] | 0 | a0f8b321a7330710e5e8ce5adb92364f381e9e85 | https://github.com/YinlinHu/fcos-pytorch/tree/a0f8b321a7330710e5e8ce5adb92364f381e9e85 |
AFMLayer | import itertools
import torch
import torch.nn as nn
import torch.nn.functional as F
from sklearn.metrics import *
class AFMLayer(nn.Module):
"""Attentonal Factorization Machine models pairwise (order-2) feature
interactions without linear term and bias.
Input shape
- A list of 3D tensor with sha... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Fanxingye/DeepRS | AFMLayer | false | 13,822 | [
"Apache-2.0"
] | 1,770 | 06b98cf2cb2781656805eafc577fbd088f37d17d | https://github.com/Fanxingye/DeepRS/tree/06b98cf2cb2781656805eafc577fbd088f37d17d |
BertAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | axiserr/Hetu | BertAttention | false | 14,944 | [
"Apache-2.0"
] | 82 | 0052f727488db0570d6b37f63549b43b0920bc29 | https://github.com/axiserr/Hetu/tree/0052f727488db0570d6b37f63549b43b0920bc29 |
MaxPoolStride1 | # 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
import torch.utils.data.distributed
import ... | Humoon/motion_reconstruction | MaxPoolStride1 | false | 2,354 | [
"BSD-3-Clause"
] | 0 | 9f0d0af3aeafa97455ec19dc4988f1577005c294 | https://github.com/Humoon/motion_reconstruction/tree/9f0d0af3aeafa97455ec19dc4988f1577005c294 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.