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 |
|---|---|---|---|---|---|---|---|---|---|---|
conv_head_pooling | import torch
import torch.nn as nn
import torch.autograd
class conv_head_pooling(nn.Module):
def __init__(self, in_feature, out_feature, stride, padding_mode='zeros'):
super(conv_head_pooling, self).__init__()
self.maxpool = nn.MaxPool2d(3, 2, 1)
self.avgpool = nn.AvgPool2d(3, 2, 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
import torch.nn as nn
import ... | LeiZhang1998/TransReID | conv_head_pooling | false | 11,650 | [
"MIT"
] | 0 | 5a3f140633e3418c7cff2603ff2e814b9ab466ac | https://github.com/LeiZhang1998/TransReID/tree/5a3f140633e3418c7cff2603ff2e814b9ab466ac |
Gaussian_transform | import torch
import torch.nn as nn
class Gaussian_transform(nn.Module):
def __init__(self, output_dim):
"""
output dim is the number of t parameters in the Gaussian point transformation
"""
super().__init__()
self.output_dim = output_dim
self.t_param = torch.nn.Par... | 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... | BorgwardtLab/TOGL | Gaussian_transform | false | 17,009 | [
"BSD-3-Clause"
] | 6 | d0c986cf829ca6bbae1a23e5cdab1c99146503cd | https://github.com/BorgwardtLab/TOGL/tree/d0c986cf829ca6bbae1a23e5cdab1c99146503cd |
MSELoss | import torch
import torch.nn as nn
import torch.utils.data
class MSELoss(nn.Module):
def __init__(self):
super(self.__class__, self).__init__()
def forward(self, input, target):
return torch.mean(torch.sum((input - target) ** 2, 1))
def get_inputs():
return [torch.rand([4, 4, 4, 4]), t... | 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.... | klovbe/UnsupervisedDeepLearning-Pytorch | MSELoss | false | 7,045 | [
"MIT"
] | 1 | 35e8e49cd4024179db173f3dab2e6d1a5d037d35 | https://github.com/klovbe/UnsupervisedDeepLearning-Pytorch/tree/35e8e49cd4024179db173f3dab2e6d1a5d037d35 |
TransposeGatedConv2d | # 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 ... | autocomic/deepfillv2 | TransposeGatedConv2d | false | 12,147 | [
"MIT"
] | 0 | 4b0f565accbf20ee90093a4504b1cff0099d9cb9 | https://github.com/autocomic/deepfillv2/tree/4b0f565accbf20ee90093a4504b1cff0099d9cb9 |
Sine | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | Crazy-Jack/BigGAN-PyTorch | Sine | false | 312 | [
"MIT"
] | 0 | 1a5644e9c87cc399580c96cfeb180052076888da | https://github.com/Crazy-Jack/BigGAN-PyTorch/tree/1a5644e9c87cc399580c96cfeb180052076888da |
AmplitudeToDB | import math
import torch
from torch import Tensor
import torchaudio.functional as F
from typing import Optional
class AmplitudeToDB(torch.nn.Module):
"""Turn a tensor from the power/amplitude scale to the decibel scale.
This output depends on the maximum value in the input tensor, and so
may return diffe... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import math
from typing impo... | Nayef211/audio | AmplitudeToDB | false | 11,743 | [
"BSD-2-Clause"
] | 0 | 241ab1e8284e589262f510ee9411baf2bc374ded | https://github.com/Nayef211/audio/tree/241ab1e8284e589262f510ee9411baf2bc374ded |
GeometricMean | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = t... | Tahlor/glom-pytorch | GeometricMean | false | 1,127 | [
"MIT"
] | 0 | 45b2fc52af5288cd53611e497a70d53ffa303410 | https://github.com/Tahlor/glom-pytorch/tree/45b2fc52af5288cd53611e497a70d53ffa303410 |
BayesLinear | from torch.nn import Module
import math
import torch
from torch.nn import Parameter
import torch.nn.functional as F
class BayesLinear(Module):
"""
Applies Bayesian Linear
Arguments:
prior_mu (Float): mean of prior normal distribution.
prior_sigma (Float): sigma of prior normal distributio... | import torch
from torch import device
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math... | anaplasia29/Bayesian-Neural-Network | BayesLinear | false | 3,104 | [
"MIT"
] | 0 | d98df8039e52cd2505dc8a94ed3cd474c2056d9a | https://github.com/anaplasia29/Bayesian-Neural-Network/tree/d98df8039e52cd2505dc8a94ed3cd474c2056d9a |
BackProjection | import torch
import torch.nn as nn
import torch.utils.data
class BackProjection(nn.Module):
"""
forward method:
bbox3d: [N, 7] homo_x, homo_y, z, w, h, l, alpha
p2: [3, 4]
return [x3d, y3d, z, w, h, l, alpha]
"""
def forward(self, bbox3d, p2):
"""
... | 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.... | AIpakchoi/visualDet3D | BackProjection | false | 4,772 | [
"Apache-2.0"
] | 1 | 920f6f8ea44eac4c1896b7d157c015e039ac39f9 | https://github.com/AIpakchoi/visualDet3D/tree/920f6f8ea44eac4c1896b7d157c015e039ac39f9 |
TransformerEncoderLayer | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import TransformerEncoderLayer
from typing import Optional
from torch.nn.init import xavier_uniform_
class TransformerEncoderLayer(nn.Module):
def __init__(self, dim_model, nhead, dim_feedforward=2048, dropout=0.1,
activatio... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | d-michele/Graph-MPNN-transformer | TransformerEncoderLayer | false | 6,546 | [
"MIT"
] | 1 | 1aafc44e1433a61d1a6a7c9e35564635bb9f8afc | https://github.com/d-michele/Graph-MPNN-transformer/tree/1aafc44e1433a61d1a6a7c9e35564635bb9f8afc |
BasicModel_ConvNet_MaxPool1d | # 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.... | LMdeLiangMi/captum | BasicModel_ConvNet_MaxPool1d | false | 5,502 | [
"BSD-3-Clause"
] | 1 | 8bd9686013fe0ba8996e9b1cbeb0ea8e91512787 | https://github.com/LMdeLiangMi/captum/tree/8bd9686013fe0ba8996e9b1cbeb0ea8e91512787 |
Classifier | # 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
reinterpret_tensor = torch._C._dynamo.guards._reinterpr... | DuaneNielsen/atari-representation-learning | Classifier | false | 13,601 | [
"MIT"
] | 175 | fe34f389768416deaa6a6ff0bdebba3d05762a55 | https://github.com/DuaneNielsen/atari-representation-learning/tree/fe34f389768416deaa6a6ff0bdebba3d05762a55 |
Add | import torch
import torch.nn as nn
class Add(nn.Module):
def __init__(self):
super(Add, self).__init__()
def forward(self, x):
x = torch.add(x, 20)
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | yifanpu001/PytorchToCaffe | Add | false | 4,704 | [
"MIT"
] | 0 | 37c1ebfc3547e93b1c174721036d03c831c60e48 | https://github.com/yifanpu001/PytorchToCaffe/tree/37c1ebfc3547e93b1c174721036d03c831c60e48 |
SelfAttentionGated | # 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.... | jamaalhay/Final_Proj | SelfAttentionGated | false | 15,672 | [
"MIT"
] | 104 | 3f524a90fee5a3cb21466ab76f630d060792045d | https://github.com/jamaalhay/Final_Proj/tree/3f524a90fee5a3cb21466ab76f630d060792045d |
AdditiveAttention | import torch
import torch.utils.data
import torch.nn as nn
class AdditiveAttention(nn.Module):
def __init__(self, enc_hidden_dim, dec_hidden_dim):
super(AdditiveAttention, self).__init__()
self.attention_w1 = nn.Linear(enc_hidden_dim, enc_hidden_dim)
self.attention_w2 = nn.Linear(dec_hidd... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ErikHumphrey/sustain-seq2seq | AdditiveAttention | false | 17,274 | [
"Apache-2.0"
] | 4 | c4787f0ca1047d01385e4fa4ffde59c6a8ab4cc4 | https://github.com/ErikHumphrey/sustain-seq2seq/tree/c4787f0ca1047d01385e4fa4ffde59c6a8ab4cc4 |
ExtResNetBlock | import torch
import torch.nn as nn
def conv3d(in_channels, out_channels, kernel_size, bias, padding):
return nn.Conv3d(in_channels, out_channels, kernel_size, padding=
padding, bias=bias)
def create_conv(in_channels, out_channels, kernel_size, order, num_groups,
padding):
"""
Create a list o... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | bounesh/pytorch-3dunet | ExtResNetBlock | false | 14,979 | [
"MIT"
] | 1,236 | 60278d01eaacc69feee731979826a0c26e223427 | https://github.com/bounesh/pytorch-3dunet/tree/60278d01eaacc69feee731979826a0c26e223427 |
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
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.... | Koukyosyumei/secure_ml | Conv2d | false | 17,556 | [
"MIT"
] | 10 | 9da24f4ce4782ec2f6dd63b0437f657a0e190e40 | https://github.com/Koukyosyumei/secure_ml/tree/9da24f4ce4782ec2f6dd63b0437f657a0e190e40 |
FCGenerator | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.nn.functional as F
class FCGenerator(nn.Module):
def __init__(self, options):
"""
The fully connected generator is initialized by creating a chain of
fully connected layers that perform transform... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | unicredit/ganzo | FCGenerator | false | 16,641 | [
"Apache-2.0"
] | 73 | fb1d270f5091073e8f27da76ab508ab24e5d40e9 | https://github.com/unicredit/ganzo/tree/fb1d270f5091073e8f27da76ab508ab24e5d40e9 |
VAE | import torch
import torch.nn as nn
class VAE(nn.Module):
def __init__(self, x_dim, h_dim1, h_dim2, h_dim3, z_dim):
super(VAE, self).__init__()
self.x_dim = x_dim
self.fc1 = nn.Linear(x_dim, h_dim1)
self.fc2 = nn.Linear(h_dim1, h_dim2)
self.fc3 = nn.Linear(h_dim2, h_dim3)
... | import torch
from torch import device
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from... | Sumeer1/VAE_Impute | VAE | false | 9,532 | [
"MIT"
] | 0 | 803195af20fe54352aedf26147a84a470637d560 | https://github.com/Sumeer1/VAE_Impute/tree/803195af20fe54352aedf26147a84a470637d560 |
DAE_Module | import torch
import torch.nn as nn
class Encoder(nn.Module):
def __init__(self):
super(Encoder, self).__init__()
self.conv1 = torch.nn.Conv1d(1, 64, 3, padding=1)
self.maxp1 = torch.nn.MaxPool1d(2, padding=0)
self.conv2 = torch.nn.Conv1d(64, 128, 3, padding=1)
self.maxp2 =... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Koukyosyumei/Zatsuon | DAE_Module | false | 2,459 | [
"Apache-2.0"
] | 0 | d7f520a282cf00bfd19d2dec300701c21403cba1 | https://github.com/Koukyosyumei/Zatsuon/tree/d7f520a282cf00bfd19d2dec300701c21403cba1 |
MPJPELoss | import torch
import torch.nn as nn
class MPJPELoss(nn.Module):
"""MPJPE (Mean Per Joint Position Error) loss.
Args:
use_target_weight (bool): Option to use weighted MSE loss.
Different joint types may have different target weights.
loss_weight (float): Weight of the loss. Default:... | 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_... | atoaiari/mmpose | MPJPELoss | false | 6,275 | [
"Apache-2.0"
] | 1 | 256a9117767008e8c33b4038a346aca12233e300 | https://github.com/atoaiari/mmpose/tree/256a9117767008e8c33b4038a346aca12233e300 |
C3D | # 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 logging
import torch.n... | hushunda/mmaction | C3D | false | 10,365 | [
"Apache-2.0"
] | 0 | b599273ddb80fd74ecf51ef5fa0c81639ea723c5 | https://github.com/hushunda/mmaction/tree/b599273ddb80fd74ecf51ef5fa0c81639ea723c5 |
ATTA | import torch
import torch.nn as nn
class ATTA(nn.Module):
def __init__(self):
super(ATTA, self).__init__()
self.conv1 = nn.Conv2d(3, 3, 16, padding='same', groups=1, bias=False)
self.lr = nn.LeakyReLU(0.2)
self.conv2 = nn.Conv2d(3, 3, 3, padding='same', groups=1, bias=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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | dreamflake/ODI | ATTA | false | 6,601 | [
"MIT"
] | 1 | d58001b96821c8a74d6ebb5402bd2be2b524890a | https://github.com/dreamflake/ODI/tree/d58001b96821c8a74d6ebb5402bd2be2b524890a |
BCEWithLogitsLossWeighted | # 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... | Guangyun-Xu/uois | BCEWithLogitsLossWeighted | false | 13,726 | [
"MIT"
] | 106 | 00069af841dd3ea9a86e6e3a89c3b7222240e6e5 | https://github.com/Guangyun-Xu/uois/tree/00069af841dd3ea9a86e6e3a89c3b7222240e6e5 |
Conv2dBlock | import torch
import torch.nn as nn
import torch.nn.functional as F
class AdaptiveInstanceLayerNorm2d(nn.Module):
def __init__(self, num_features, eps=1e-05, momentum=0.9,
using_moving_average=True, using_bn=False):
super(AdaptiveInstanceLayerNorm2d, self).__init__()
self.eps = eps
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | belphegor2211/khoa_luan | Conv2dBlock | false | 9,994 | [
"MIT"
] | 0 | c9c163ebf3aff3005639ce7e4020e510295d1c75 | https://github.com/belphegor2211/khoa_luan/tree/c9c163ebf3aff3005639ce7e4020e510295d1c75 |
MaskedConv1d | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch
class MaskedConv1d(nn.Conv1d):
def __init__(self, in_channels, out_channels, kernel_size, dilation=1,
groups=1, bias=True, causal=True):
if causal:
padding = (kernel_size - 1) * dilation
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
a... | B0BBB/seq2seq.pytorch | MaskedConv1d | false | 114 | [
"MIT"
] | 0 | 54bb0e9f3e5c7db7f257841ed652e8ff447b8ee4 | https://github.com/B0BBB/seq2seq.pytorch/tree/54bb0e9f3e5c7db7f257841ed652e8ff447b8ee4 |
RMSNorm | # 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_... | ofooo/AI-Writer | RMSNorm | false | 12,849 | [
"BSD-3-Clause"
] | 0 | 1ba84894c15c9e5605d3c6cd7521d5c6dab6eb6d | https://github.com/ofooo/AI-Writer/tree/1ba84894c15c9e5605d3c6cd7521d5c6dab6eb6d |
Invertible1x1Conv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import functional as F
from torch.autograd import Variable
import ... | ishalyminov/shad_speech | Invertible1x1Conv | false | 15,611 | [
"MIT"
] | 83 | e1345d2de929e150b2683190b127a837fbcb34f3 | https://github.com/ishalyminov/shad_speech/tree/e1345d2de929e150b2683190b127a837fbcb34f3 |
GatedMaskedConv2d | # 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... | sbarham/lv-nlm-he-2019 | GatedMaskedConv2d | false | 10,836 | [
"MIT"
] | 0 | 6fd1ce680675759d0a58878ac1fde31122712752 | https://github.com/sbarham/lv-nlm-he-2019/tree/6fd1ce680675759d0a58878ac1fde31122712752 |
MinElementwise | import torch
class MinElementwise(torch.nn.Module):
def forward(self, x, y):
return torch.min(x, y)
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | bunderhi/torch2trt | MinElementwise | false | 1,598 | [
"MIT"
] | 0 | fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d | https://github.com/bunderhi/torch2trt/tree/fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d |
KLLoss | # 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
... | ForrestPi/VAEGAN | KLLoss | false | 17,272 | [
"MIT"
] | 8 | c2cfeedcc2dcfad6258468611536d9a8222eb8a3 | https://github.com/ForrestPi/VAEGAN/tree/c2cfeedcc2dcfad6258468611536d9a8222eb8a3 |
Norm | # 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... | vzinche/inferno | Norm | false | 4,509 | [
"Apache-2.0"
] | 0 | 91b22dfcd1b6a9ec415f0bbb6ae66caea42f4034 | https://github.com/vzinche/inferno/tree/91b22dfcd1b6a9ec415f0bbb6ae66caea42f4034 |
ReinforcedReceiver | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
import to... | Shawn-Guo-CN/EGG | ReinforcedReceiver | false | 2,885 | [
"MIT"
] | 0 | 0a5b258108e2cd1c873d7f67e8c92551bb3d809c | https://github.com/Shawn-Guo-CN/EGG/tree/0a5b258108e2cd1c873d7f67e8c92551bb3d809c |
ActorCritic | import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
def f_hard_swish(x):
return F.relu6(x + 3) / 6 * x
class ActorCritic(nn.Module):
def __init__(self, num_inputs, num_outputs, layer_norm=True):
super(ActorCritic, self).__init__()
mid_dim = 96
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 numpy as np
import tor... | GuanShiTing/DL_RL_Zoo | ActorCritic | false | 5,308 | [
"Apache-2.0"
] | 1 | 520cd92c1a28f64006d51444a0940cc645b95c6d | https://github.com/GuanShiTing/DL_RL_Zoo/tree/520cd92c1a28f64006d51444a0940cc645b95c6d |
MidNet4 | # 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... | sjmoran/CURL | MidNet4 | false | 16,473 | [
"BSD-3-Clause"
] | 125 | 919e519717b66e14d92ac6fa404c328ee3f254a5 | https://github.com/sjmoran/CURL/tree/919e519717b66e14d92ac6fa404c328ee3f254a5 |
TransitionModel | import torch
from torch import nn
def log_clamped(x, eps=0.0001):
clamped_x = torch.clamp(x, min=eps)
return torch.log(clamped_x)
def logsumexp(x, dim):
"""
Differentiable LogSumExp: Does not creates nan gradients when all the inputs are -inf
Args:
x : torch.Tensor - The input tensor
... | 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... | ishine/Neural-HMM | TransitionModel | false | 15,636 | [
"MIT"
] | 66 | c0bc23ab88f831173d2d4db29a84503b80c5cdc4 | https://github.com/ishine/Neural-HMM/tree/c0bc23ab88f831173d2d4db29a84503b80c5cdc4 |
ViTStemPatchify | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import Module
import torch.utils.data
import torch.nn as nn
assert... | om00839/pycls | ViTStemPatchify | false | 16,190 | [
"MIT"
] | 1,975 | 8c79a8e2adfffa7cae3a88aace28ef45e52aa7e5 | https://github.com/om00839/pycls/tree/8c79a8e2adfffa7cae3a88aace28ef45e52aa7e5 |
BertSelfAttention | # 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.... | Ahren09/FinerFact | BertSelfAttention | false | 18,052 | [
"MIT"
] | 9 | 68df3799fbfadd56fa69b019ca6fba0c482f21d3 | https://github.com/Ahren09/FinerFact/tree/68df3799fbfadd56fa69b019ca6fba0c482f21d3 |
Temp | import torch
import torch.nn as nn
import torch.nn.functional as F
class Temp(nn.Module):
def __init__(self, input_dim, output_dim):
super(Temp, self).__init__()
self.linear1 = nn.Linear(input_dim, 256)
self.linear2 = nn.Linear(256, 256)
self.linear3 = nn.Linear(256, 256)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | gautam-sharma1/openRL | Temp | false | 6,734 | [
"MIT"
] | 1 | 14310a97a328fe5682a01ee85d83a6b5e1ae29ca | https://github.com/gautam-sharma1/openRL/tree/14310a97a328fe5682a01ee85d83a6b5e1ae29ca |
KeyValueAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | haojiepan1/CrossWOZ | KeyValueAttention | false | 6,811 | [
"Apache-2.0"
] | 1 | 6d7b4c4cfb73a528b76074764687906abecc90b6 | https://github.com/haojiepan1/CrossWOZ/tree/6d7b4c4cfb73a528b76074764687906abecc90b6 |
Discriminator | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | akanametov/CycleGAN | Discriminator | false | 6,146 | [
"MIT"
] | 1 | a61e76134cfdda43306e326e3dbba38d8cb21163 | https://github.com/akanametov/CycleGAN/tree/a61e76134cfdda43306e326e3dbba38d8cb21163 |
ConstantODE | import torch
class ConstantODE(torch.nn.Module):
def __init__(self, device):
super(ConstantODE, self).__init__()
self.a = torch.nn.Parameter(torch.tensor(0.2))
self.b = torch.nn.Parameter(torch.tensor(3.0))
def forward(self, t, y):
return self.a + (y - (self.a * t + self.b)) ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | navaro1/parking_prediction | ConstantODE | false | 12,891 | [
"MIT"
] | 0 | c532a2f75155abc9c0d4be9c955eabe368591932 | https://github.com/navaro1/parking_prediction/tree/c532a2f75155abc9c0d4be9c955eabe368591932 |
Actor | # 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.... | simondlevy/pytorch-drl | Actor | false | 4,345 | [
"MIT"
] | 0 | b197bb93c2cc698971f98095d4e0180811c52042 | https://github.com/simondlevy/pytorch-drl/tree/b197bb93c2cc698971f98095d4e0180811c52042 |
RewardModelNetwork | # 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 ... | PaParaZz1/DI-engine | RewardModelNetwork | false | 11,865 | [
"Apache-2.0"
] | 0 | b38144117c1ebc6eb860d8637ec8866dfbcdf2de | https://github.com/PaParaZz1/DI-engine/tree/b38144117c1ebc6eb860d8637ec8866dfbcdf2de |
KLLoss | # 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... | CityU-AIM-Group/SIGMA | KLLoss | false | 17,670 | [
"MIT"
] | 5 | 19f89777db8d42f750a9b87756d3326c7efd18f5 | https://github.com/CityU-AIM-Group/SIGMA/tree/19f89777db8d42f750a9b87756d3326c7efd18f5 |
GlobalNonLocal | # 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.... | Galaxies99/alpha-protein | GlobalNonLocal | false | 17,334 | [
"MIT"
] | 4 | db4b77ab48d5905ade5d4a66004f8387773718fa | https://github.com/Galaxies99/alpha-protein/tree/db4b77ab48d5905ade5d4a66004f8387773718fa |
GumbelSoftmaxLayer | import torch
import torch.nn as nn
from torch.distributions import RelaxedOneHotCategorical
import torch.nn.parallel
import torch.utils.data
import torch.distributions
def gumbel_softmax_sample(logits: 'torch.Tensor', temperature: 'float'=1.0,
training: 'bool'=True, straight_through: 'bool'=False):
size = log... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.distributions import RelaxedOneHotCategorical
import torch.nn.parallel
import torch.utils.data
import torch... | vengalraoguttha/EGG | GumbelSoftmaxLayer | false | 16,664 | [
"MIT"
] | 254 | e4f8412f197543ec7f1f00cf89b5a364b038dc57 | https://github.com/vengalraoguttha/EGG/tree/e4f8412f197543ec7f1f00cf89b5a364b038dc57 |
CNN | import torch
from torch import nn
import torch.nn.functional as F
class CNN(nn.Module):
def __init__(self, last_layer_channels):
super().__init__()
self.conv1 = nn.Conv2d(1, 32, (3, 3), padding='same')
self.conv2 = nn.Conv2d(32, 32, (3, 3), padding='same')
self.pool1 = nn.MaxPool2... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | zitkat/transformer-HTR | CNN | false | 11,054 | [
"Apache-2.0"
] | 0 | fa14dc99f1050c022cd54bc82abe9bc8dbfbc95a | https://github.com/zitkat/transformer-HTR/tree/fa14dc99f1050c022cd54bc82abe9bc8dbfbc95a |
LunaBlock | import torch
import torch.nn as nn
class LunaBlock(nn.Module):
def __init__(self, in_channels, conv_channels):
super().__init__()
self.conv1 = nn.Conv3d(in_channels, conv_channels, kernel_size=3,
padding=1, bias=True)
self.relu1 = nn.ReLU(inplace=True)
self.conv2 = 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
assert_... | JulianKlug/scop | LunaBlock | false | 688 | [
"MIT"
] | 0 | b0d6a805a11ee8b4d0f53a4d6a5ec402988298e4 | https://github.com/JulianKlug/scop/tree/b0d6a805a11ee8b4d0f53a4d6a5ec402988298e4 |
LayerNormalization | # 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_... | alisure-fork/CONTA | LayerNormalization | false | 1,415 | [
"MIT"
] | 0 | dde3e5083f45598d859dde889de3ae85c7a416e9 | https://github.com/alisure-fork/CONTA/tree/dde3e5083f45598d859dde889de3ae85c7a416e9 |
Conv2dSame | import math
import torch
from torch import nn
from typing import List
from typing import Union
import torch.nn.functional as F
from typing import Optional
from typing import Tuple
from torch.nn.common_types import _size_2_t
def get_same_padding(x: 'int', k: 'int', s: 'int', d: 'int') ->int:
"""
Calculate asym... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
from typing import List
from typing import Unio... | L-Net-1992/towhee | Conv2dSame | false | 13,982 | [
"Apache-2.0"
] | 365 | 471de97bf9c5443efaf3b62fd440b3ebdb6d5903 | https://github.com/L-Net-1992/towhee/tree/471de97bf9c5443efaf3b62fd440b3ebdb6d5903 |
Block | import torch
import torch._C
import torch.serialization
from torch import nn
import torch.nn.functional as F
class DropPath(nn.Module):
"""Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).
"""
def __init__(self, drop_prob=None):
super(DropPath, self).__init... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | huazai-1994/24th-resolution-for-STAC-Overflow | Block | false | 6,848 | [
"Apache-2.0"
] | 1 | 80bb3b367a126264823ffc597dc01586c262f9d9 | https://github.com/huazai-1994/24th-resolution-for-STAC-Overflow/tree/80bb3b367a126264823ffc597dc01586c262f9d9 |
GAT | import torch
import torch.nn as nn
import torch.nn.functional as F
class GATLayer(nn.Module):
"""
Simple GAT layer, similar to https://arxiv.org/abs/1710.10903
"""
def __init__(self, in_features, out_features, alpha=0.2):
super(GATLayer, self).__init__()
self.in_features = in_features... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | JLUVicent/DAEGC | GAT | false | 644 | [
"MIT"
] | 0 | 9a4cc50e40e8521fafb00960d1adf8216674c8f6 | https://github.com/JLUVicent/DAEGC/tree/9a4cc50e40e8521fafb00960d1adf8216674c8f6 |
OutputBlock | import torch
class OutputBlock(torch.nn.Module):
"""Flatten output channels using 1x1x1 convolutions"""
def __init__(self, ks, channels_in, channels_out):
super(OutputBlock, self).__init__()
self.convflat = torch.nn.Conv3d(in_channels=channels_in,
out_channels=channels_out, kernel... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
reinterpret_tens... | conlain-k/RLN_elasticity | OutputBlock | false | 3,353 | [
"MIT"
] | 0 | d8574c83d62f675960a7f8b86ddb553e9a7b1ca7 | https://github.com/conlain-k/RLN_elasticity/tree/d8574c83d62f675960a7f8b86ddb553e9a7b1ca7 |
Net | import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
"""policy-value network module"""
def __init__(self, board_width, board_height):
super(Net, self).__init__()
self.board_width = board_width
self.board_height = board_height
self.conv1 = 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.... | ZiwenZhuang/AlphaZero_Gomoku | Net | false | 12,043 | [
"MIT"
] | 0 | 72db1c3eda1f6133da24c924da6032ea3569076e | https://github.com/ZiwenZhuang/AlphaZero_Gomoku/tree/72db1c3eda1f6133da24c924da6032ea3569076e |
Multi_Head_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.triton_helpers import libdevice, math as tl_math
im... | NTDXYG/Text-Classify-based-pytorch | Multi_Head_Attention | false | 8,593 | [
"Apache-2.0"
] | 20 | b12a264a0ea64b2f8b46fafd5383ef0a8025ef2f | https://github.com/NTDXYG/Text-Classify-based-pytorch/tree/b12a264a0ea64b2f8b46fafd5383ef0a8025ef2f |
SCAttention | import torch
import torch.utils.data
import torch.nn as nn
import torch.nn.functional as F
class BasicAtt(nn.Module):
def __init__(self, mid_dims: 'list', mid_dropout: 'float'):
super(BasicAtt, self).__init__()
sequential = []
for i in range(1, len(mid_dims) - 1):
sequential.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.... | YehLi/xmodaler | SCAttention | false | 14,705 | [
"Apache-2.0"
] | 830 | 5340054398c076cfa717317d151ca595c5e37198 | https://github.com/YehLi/xmodaler/tree/5340054398c076cfa717317d151ca595c5e37198 |
TokenEmbedding | import torch
import torch.nn as nn
class TokenEmbedding(nn.Module):
def __init__(self, c_in, d_model):
super(TokenEmbedding, self).__init__()
padding = 1 if torch.__version__ >= '1.5.0' else 2
self.tokenConv = nn.Conv1d(in_channels=c_in, out_channels=d_model,
kernel_size=3, pa... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | LeoYoung1996/Experiment | TokenEmbedding | false | 9,293 | [
"Apache-2.0"
] | 0 | e3e875e0fd9b0367b761c51d9862b9da5e448576 | https://github.com/LeoYoung1996/Experiment/tree/e3e875e0fd9b0367b761c51d9862b9da5e448576 |
AdaptiveAvgPool3dOutSize1 | import torch
import torch.nn as nn
import torch.utils.data
from abc import abstractmethod
from typing import Tuple
import torch.nn
class EfficientBlockBase(nn.Module):
"""
PyTorchVideo/accelerator provides a set of efficient blocks
that have optimal efficiency for each target hardware device.
Each ef... | 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
from abc import abstractmethod
from typing import Tuple
import torch.nn
assert_size_stride = t... | denred0/pytorchvideo | AdaptiveAvgPool3dOutSize1 | false | 1,828 | [
"Apache-2.0"
] | 0 | d874bfc9969895d2afcedea2e12bae5e1bcfb809 | https://github.com/denred0/pytorchvideo/tree/d874bfc9969895d2afcedea2e12bae5e1bcfb809 |
BertMixedLayer | from _paritybench_helpers import _mock_config
import math
import torch
import torch.nn
import torch.nn as nn
class BertAttention(nn.Module):
"""BERT attention layer.
Based on: BERT (pytorch-transformer)
https://github.com/huggingface/transformers
"""
def __init__(self, config) ->None:
sup... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Project-MONAI/MONAI | BertMixedLayer | false | 16,232 | [
"Apache-2.0"
] | 2,971 | 2bab12c67c3cc1d54a4847628ce1e879064be11c | https://github.com/Project-MONAI/MONAI/tree/2bab12c67c3cc1d54a4847628ce1e879064be11c |
SmoothL1Loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | liuhuaijjin/rpn_rois_proposals_layers | SmoothL1Loss | false | 7,106 | [
"MIT"
] | 1 | c5f9f09b3ae8c52e4b6fa3fda391f993cb7d42c1 | https://github.com/liuhuaijjin/rpn_rois_proposals_layers/tree/c5f9f09b3ae8c52e4b6fa3fda391f993cb7d42c1 |
Simple_AUG | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from to... | varun-jois/KAIR | Simple_AUG | false | 4,489 | [
"MIT"
] | 0 | 90c04671c6eb32a6765edfec94f7db3ba1f53f1e | https://github.com/varun-jois/KAIR/tree/90c04671c6eb32a6765edfec94f7db3ba1f53f1e |
LayerNormConv2d | # 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
from torch import nn
import torch.nn
assert_size_stride = torch._C._dynamo.guar... | Jack12xl/scene-representation-networks | LayerNormConv2d | false | 599 | [
"MIT"
] | 0 | 2691b23c956cf188a1fe4c84a888b19871cac8f4 | https://github.com/Jack12xl/scene-representation-networks/tree/2691b23c956cf188a1fe4c84a888b19871cac8f4 |
MultiheadAttention | import math
import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
import torch.jit
import torch.jit.quantized
import torch.onnx.operators
def combine_heads(X):
"""
Combine heads (the inverse of split heads):
1) Transpose X from (batch size, nheads, sequence length, d_head) ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | ROCmSoftwarePlatform/translate | MultiheadAttention | false | 984 | [
"BSD-3-Clause"
] | 0 | 32a6380d914ebe1a6c38c4992aac9600ed3d9810 | https://github.com/ROCmSoftwarePlatform/translate/tree/32a6380d914ebe1a6c38c4992aac9600ed3d9810 |
SoftQNetwork | import torch
import torch.nn.functional as F
import torch.nn as nn
class SoftQNetwork(nn.Module):
def __init__(self, num_inputs, num_actions, hidden_size=[400, 300],
init_w=0.003):
super(SoftQNetwork, self).__init__()
self.linear1 = nn.Linear(num_inputs + num_actions, hidden_size[0])
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | QasimWani/CityLearn | SoftQNetwork | false | 14,262 | [
"MIT"
] | 202 | ffc0584508dc9c796c97e6b908b75380b9bc6606 | https://github.com/QasimWani/CityLearn/tree/ffc0584508dc9c796c97e6b908b75380b9bc6606 |
GELU_ | import math
import torch
import torch.nn as nn
class GELU_(nn.Module):
def forward(self, x):
return 0.5 * x * (1 + torch.tanh(math.sqrt(2 / math.pi) * (x +
0.044715 * torch.pow(x, 3))))
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.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | AniketRajpoot/reformer-pytorch | GELU_ | false | 8,933 | [
"MIT"
] | 0 | 06b131eb383e7a3a184b7038ef20fe614958216f | https://github.com/AniketRajpoot/reformer-pytorch/tree/06b131eb383e7a3a184b7038ef20fe614958216f |
FeedForward | import torch
from torch import nn
from torch.nn import functional as F
class FeedForward(nn.Module):
def __init__(self, d_model, d_ff=64, dropout=0.1):
super().__init__()
self.linear_1 = nn.Linear(d_model, d_ff)
self.dropout = nn.Dropout(dropout)
self.linear_2 = nn.Linear(d_ff, d_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | aim-uofa/DyCo3D | FeedForward | false | 14,777 | [
"BSD-2-Clause"
] | 100 | 17d22c2d839c0a1043fb72df301e3935af5ca0e9 | https://github.com/aim-uofa/DyCo3D/tree/17d22c2d839c0a1043fb72df301e3935af5ca0e9 |
AUGRUCell | # 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 ... | liyunrui/DeepCTR-Torch | AUGRUCell | false | 12,735 | [
"Apache-2.0"
] | 0 | 392fd6d39d9ca0ac854022136cdb4d5c68e3a592 | https://github.com/liyunrui/DeepCTR-Torch/tree/392fd6d39d9ca0ac854022136cdb4d5c68e3a592 |
Standard | # 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.... | HEmile/KENN-PyTorch | Standard | false | 17,330 | [
"BSD-3-Clause"
] | 5 | e39386f298587ab70ecea88180121ef8cf6ff9bc | https://github.com/HEmile/KENN-PyTorch/tree/e39386f298587ab70ecea88180121ef8cf6ff9bc |
GatedFusion | # 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 scipy.sparse import *
assert_size_stride = torch._C._... | talha1503/RL-based-Graph2Seq-for-NQG | GatedFusion | false | 16,527 | [
"Apache-2.0"
] | 100 | 1039e0b6231ae7029ea6e4073b1e55df5ad2e928 | https://github.com/talha1503/RL-based-Graph2Seq-for-NQG/tree/1039e0b6231ae7029ea6e4073b1e55df5ad2e928 |
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.... | cocopambag/insightface | MultiheadAttention | false | 3,307 | [
"MIT"
] | 0 | c33102e4844520cda6c2b3df63278aed935e2f4e | https://github.com/cocopambag/insightface/tree/c33102e4844520cda6c2b3df63278aed935e2f4e |
LinearWeightNorm | # 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 ... | TRUMANCFY/wolf | LinearWeightNorm | false | 3,006 | [
"Apache-2.0"
] | 0 | 1a21479256e4f51885e2d2fdd449b1faa61277a6 | https://github.com/TRUMANCFY/wolf/tree/1a21479256e4f51885e2d2fdd449b1faa61277a6 |
Snake | # 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
import torch.nn as nn
from torch.nn import Parameter
from torch.distribut... | Juju-botu/diffeqml-research | Snake | false | 13,965 | [
"Apache-2.0"
] | 49 | aa796c87447e5299ec4f25a07fc4d032afb1f63e | https://github.com/Juju-botu/diffeqml-research/tree/aa796c87447e5299ec4f25a07fc4d032afb1f63e |
BasicModel | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | Europium248/captum | BasicModel | false | 421 | [
"BSD-3-Clause"
] | 0 | ac02fae2651b8d68a44bcb9d03b91cbb3959f2fc | https://github.com/Europium248/captum/tree/ac02fae2651b8d68a44bcb9d03b91cbb3959f2fc |
L2Norm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | bigh2000/torchcv_edit | L2Norm | false | 3,247 | [
"MIT"
] | 0 | 999da61b9b7441520280f7977239b6fc21c2f019 | https://github.com/bigh2000/torchcv_edit/tree/999da61b9b7441520280f7977239b6fc21c2f019 |
SpatialAttention | # 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_... | YeRen123455/Infrared-Small-Target-Detection | SpatialAttention | false | 14,689 | [
"MIT"
] | 62 | 23d84f436afb422d0d0b6cbf65305e1b53aea6db | https://github.com/YeRen123455/Infrared-Small-Target-Detection/tree/23d84f436afb422d0d0b6cbf65305e1b53aea6db |
BasicConvTestModel | import torch
from torch import nn
from torchvision import models as models
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
from torchvision.transforms import *
import torch.onnx
def fill_bias(module, value):
module.bias.data.fill_(value)
def fill_conv_weig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
from torchvision import models as models
import torch.nn.pa... | aalborov/openvino_training_extensions | BasicConvTestModel | false | 6,058 | [
"Apache-2.0"
] | 1 | a0bb39424151a98e1ca80c4aa5c865636d401785 | https://github.com/aalborov/openvino_training_extensions/tree/a0bb39424151a98e1ca80c4aa5c865636d401785 |
_SepConv1d | # 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... | thupchnsky/ModifiedBasesAnalysis | _SepConv1d | false | 4,425 | [
"MIT"
] | 0 | 904fab75eb5fdc67a050b3862d1432ecce8cf691 | https://github.com/thupchnsky/ModifiedBasesAnalysis/tree/904fab75eb5fdc67a050b3862d1432ecce8cf691 |
QuantizableHSwish | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.quantization
assert_size_stride = torch._C._dynamo.gua... | dhlee347/model_compression | QuantizableHSwish | false | 6,570 | [
"MIT"
] | 1 | 274b85ff56d81f0b7cf6907cbc1bd10e16cdb956 | https://github.com/dhlee347/model_compression/tree/274b85ff56d81f0b7cf6907cbc1bd10e16cdb956 |
DPLSTMCell | import math
import torch
import torch.nn as nn
import torch.utils.data
import torch.utils.data.distributed
import torch.nn.parallel
from typing import Tuple
class LSTMLinear(nn.Linear):
"""
This function is the same as a nn.Linear layer, except that in the backward pass
the grad_samples get accumulated (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 libdevice
import math
import ... | adriansarstedt/opacus | DPLSTMCell | false | 12,063 | [
"Apache-2.0"
] | 0 | a6c89e3d6a3a4e3e4b82bc8c68d53265a9a7cba1 | https://github.com/adriansarstedt/opacus/tree/a6c89e3d6a3a4e3e4b82bc8c68d53265a9a7cba1 |
C2 | import torch
import torch.nn as nn
from collections import OrderedDict
class C2(nn.Module):
def __init__(self):
super(C2, self).__init__()
self.c2 = nn.Sequential(OrderedDict([('c2', nn.Conv2d(6, 16,
kernel_size=(5, 5))), ('relu2', nn.ReLU()), ('s2', nn.MaxPool2d
(kernel_s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from co... | zjgbz/img_cls | C2 | false | 4,669 | [
"MIT"
] | 0 | 513d5ae423d95e008a82a6ffe443db49f8ed9ac2 | https://github.com/zjgbz/img_cls/tree/513d5ae423d95e008a82a6ffe443db49f8ed9ac2 |
Loss | # 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... | RandolphVI/HyperNet | Loss | false | 5,762 | [
"Apache-2.0"
] | 1 | e9f376f5eb087e57360ca41cca2533c3ca967e47 | https://github.com/RandolphVI/HyperNet/tree/e9f376f5eb087e57360ca41cca2533c3ca967e47 |
BCELoss | import torch
import torch.nn as nn
import torch.nn.functional as F
def binary_cross_entropy(inputs, target, weight=None, reduction='mean',
smooth_eps=None, from_logits=False):
"""cross entropy loss, with support for label smoothing https://arxiv.org/abs/1512.00567"""
smooth_eps = smooth_eps or 0
if sm... | 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... | schokoro/torchutils | BCELoss | false | 10,743 | [
"MIT"
] | 0 | bcab35e8c943a1fcd4550fbb023188fa5d688663 | https://github.com/schokoro/torchutils/tree/bcab35e8c943a1fcd4550fbb023188fa5d688663 |
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
from torch.optim.lr_schedule... | ChitienSun/NCTU_DLSR_final_project | ClippedLinearQuantization | false | 267 | [
"MIT"
] | 0 | 9d647426c274afc7651ea4fe9a11f2a0a0fd1fba | https://github.com/ChitienSun/NCTU_DLSR_final_project/tree/9d647426c274afc7651ea4fe9a11f2a0a0fd1fba |
ConstMult | import torch
import torch.nn as nn
class ConstMult(nn.Module):
def __init__(self, alpha=1.0):
super().__init__()
self.alpha = nn.Parameter(torch.Tensor(1))
nn.init.constant_(self.alpha, alpha)
def forward(self, x):
return self.alpha * x
def get_inputs():
return [torch.r... | 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... | RaoefTaki/MNTDP-forked | ConstMult | false | 8,686 | [
"MIT"
] | 15 | d9ea59a6638f6cdc93eca180ab02672f5bf5d2a1 | https://github.com/RaoefTaki/MNTDP-forked/tree/d9ea59a6638f6cdc93eca180ab02672f5bf5d2a1 |
BCEFocalLoss | import torch
class BCEFocalLoss(torch.nn.Module):
"""
二分类的Focalloss alpha 固定
"""
def __init__(self, gamma=2, alpha=0.25, reduction='elementwise_mean'):
super().__init__()
self.gamma = gamma
self.alpha = alpha
self.reduction = reduction
def forward(self, _input, ta... | 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... | CCChenhao997/CCL2020-Humor-Computation | BCEFocalLoss | false | 17,014 | [
"MIT"
] | 7 | 700e539588904da40a9db899668437188a6b4613 | https://github.com/CCChenhao997/CCL2020-Humor-Computation/tree/700e539588904da40a9db899668437188a6b4613 |
Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | fengjixuchui/EmbeddedSystem | Net | false | 15,423 | [
"MIT"
] | 228 | ae17e41bb120922a99f2d91818c381e38e868040 | https://github.com/fengjixuchui/EmbeddedSystem/tree/ae17e41bb120922a99f2d91818c381e38e868040 |
SigSoftmaxV1 | # 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
i... | DingYuan0118/DeepEMD | SigSoftmaxV1 | false | 5,070 | [
"MIT"
] | 1 | a91f77c3da16fecefa62b14aa8b2f195b0e49b84 | https://github.com/DingYuan0118/DeepEMD/tree/a91f77c3da16fecefa62b14aa8b2f195b0e49b84 |
GatedLinear | # 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... | ClaraBing/ffjord | GatedLinear | false | 13,521 | [
"MIT"
] | 518 | a97c34ff546a063316828f53bd041555e663428d | https://github.com/ClaraBing/ffjord/tree/a97c34ff546a063316828f53bd041555e663428d |
Feedforward | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C... | jacob-parnell-rozetta/longformer_coverage | Feedforward | false | 10,215 | [
"Apache-2.0"
] | 0 | 59268bc7ae7eeb962c43080e524eaf1e62100b6c | https://github.com/jacob-parnell-rozetta/longformer_coverage/tree/59268bc7ae7eeb962c43080e524eaf1e62100b6c |
GradualNoiseBlock | # 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.nn impor... | CTPLab/IID_representation_learning | GradualNoiseBlock | false | 4,973 | [
"MIT"
] | 1 | b9dc13536963f9af332b039f7cc772e2f1090c62 | https://github.com/CTPLab/IID_representation_learning/tree/b9dc13536963f9af332b039f7cc772e2f1090c62 |
GeneralizedDiceLoss | import collections
import torch
import warnings
from typing import Optional
from typing import Union
from typing import Any
from typing import Callable
from typing import Tuple
import torch.nn
from torch.nn.modules.loss import _Loss
from enum import Enum
import collections.abc
def issequenceiterable(obj: 'Any') ->boo... | 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 collections
from typi... | danielschulz/MONAI | GeneralizedDiceLoss | false | 1,811 | [
"Apache-2.0"
] | 0 | 54ef6e9e700f0de3d50184c0148f953be871a58e | https://github.com/danielschulz/MONAI/tree/54ef6e9e700f0de3d50184c0148f953be871a58e |
CosineBasisLinear | # 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 numpy ... | tarokiritani/pfrl | CosineBasisLinear | false | 11,051 | [
"MIT"
] | 0 | 284ed1f43b32654a2ec1569b16a0f6b9acbd5e79 | https://github.com/tarokiritani/pfrl/tree/284ed1f43b32654a2ec1569b16a0f6b9acbd5e79 |
PatchEmbedding | import torch
import torch.nn as nn
class PatchEmbedding(nn.Module):
"""PatchEmdedding class
Args:
image_size(int): size of the image. assume that image shape is square
in_channels(int): input channel of the image, 3 for RGB color channel
embed_size(int): output channel size. This is th... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | aiwizzard/vision-transformer | PatchEmbedding | false | 3,115 | [
"Apache-2.0"
] | 0 | f9dd2f720a595f02543aa9720204d8f8c6f58193 | https://github.com/aiwizzard/vision-transformer/tree/f9dd2f720a595f02543aa9720204d8f8c6f58193 |
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... | makarand-mac/continuous-control | Critic | false | 12,754 | [
"MIT"
] | 0 | 6563d652770551ad2773e76daa9d536e617df01a | https://github.com/makarand-mac/continuous-control/tree/6563d652770551ad2773e76daa9d536e617df01a |
PlainRefiner | import torch
import torch.nn as nn
class PlainRefiner(nn.Module):
"""Simple refiner from Deep Image Matting.
Args:
conv_channels (int): Number of channels produced by the three main
convolutional layer.
loss_refine (dict): Config of the loss of the refiner. Default: 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
import torch.nn as nn
assert_... | akimotty877/mmediting | PlainRefiner | false | 3,071 | [
"Apache-2.0"
] | 0 | cae872d6f3e867ba144c7c0dbc29a0ee1a29e5a6 | https://github.com/akimotty877/mmediting/tree/cae872d6f3e867ba144c7c0dbc29a0ee1a29e5a6 |
GroupedLinearLayer | import torch
from torch import nn
import torch.utils.checkpoint
class GroupedLinearLayer(nn.Module):
def __init__(self, input_size, output_size, num_groups):
super().__init__()
self.input_size = input_size
self.output_size = output_size
self.num_groups = num_groups
self.gr... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.utils.checkpoint
assert_size_stride = torch._C... | jxhe/unify-parameter-efficient-tuning | GroupedLinearLayer | false | 15,763 | [
"Apache-2.0"
] | 101 | 3222ce2c0079566a28043e22380eb4ab6ad14389 | https://github.com/jxhe/unify-parameter-efficient-tuning/tree/3222ce2c0079566a28043e22380eb4ab6ad14389 |
WeightNormConv2d | import torch
import torch.nn as nn
import torch.utils.data
class WeightNormConv2d(nn.Module):
def __init__(self, in_dim, out_dim, kernel_size, stride=1, padding=0,
bias=True, weight_norm=True, scale=False):
"""Intializes a Conv2d augmented with weight normalization.
(See torch.nn.utils.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 torch.nn as ... | eyalbetzalel/GlowGAN | WeightNormConv2d | false | 15,337 | [
"MIT"
] | 54 | 144b8fef60d9dc38ca66c178a18c0c9a2a17c23e | https://github.com/eyalbetzalel/GlowGAN/tree/144b8fef60d9dc38ca66c178a18c0c9a2a17c23e |
RelativeMSE | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | Mephisto405/WCMC-Public | RelativeMSE | false | 8,540 | [
"BSD-2-Clause"
] | 19 | bd54f218d5239db84f404fbe1b465f9497bcf9e4 | https://github.com/Mephisto405/WCMC-Public/tree/bd54f218d5239db84f404fbe1b465f9497bcf9e4 |
BPR | # 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 libdevice, math as tl_math
import torc... | kerengaiger/bpr | BPR | false | 12,662 | [
"MIT"
] | 0 | 66bfa57469a9c70ba5b9158fde5210abe1bd8d7b | https://github.com/kerengaiger/bpr/tree/66bfa57469a9c70ba5b9158fde5210abe1bd8d7b |
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