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 |
|---|---|---|---|---|---|---|---|---|---|---|
SimpleModel | import torch
import torch.nn as nn
import torch.nn.functional
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
class SimpleModel(nn.Module):
def __init__(self):
super(SimpleModel, self).__init__()
def forward(self, x):
return x * 2
def... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.functional
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data... | ZVK/jukebox | SimpleModel | false | 18,192 | [
"MIT"
] | 5 | 23fd6753f2892214ad3d97f6f2b59f8cc8d0c57a | https://github.com/ZVK/jukebox/tree/23fd6753f2892214ad3d97f6f2b59f8cc8d0c57a |
MomentumNetSide | import torch
import torch.utils.data
import torch.utils.data.dataloader
class MomentumNetSide(torch.nn.Module):
def __init__(self, beta: 'float'):
super(MomentumNetSide, self).__init__()
self.beta = beta
def forward(self, inp: 'torch.Tensor'):
return inp * self.beta
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
import torch.utils.data
import torch.utils.data.dataloader
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cud... | ClashLuke/HomebrewNLP | MomentumNetSide | false | 281 | [
"BSD-2-Clause"
] | 0 | 18d9a9a32af4e5e5672a9261ef6ac613dc9194c0 | https://github.com/ClashLuke/HomebrewNLP/tree/18d9a9a32af4e5e5672a9261ef6ac613dc9194c0 |
SimpleStackModel | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleStackModel(torch.nn.Module):
def __init__(self, dim):
super(SimpleStackModel, self).__init__()
self.dim = dim
def forward(self, a, b):
c = b + b
return torch.stack((a, c), dim=self.dim)
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.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | YaronBenAtar/glow | SimpleStackModel | false | 14,688 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
PoswiseFeedForwardNet | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.nn.functional as F
class PoswiseFeedForwardNet(nn.Module):
def __init__(self, config):
super().__init__()
self.config = config
self.conv1 = nn.Conv1d(in_channels=self.config.d_hidn, out_channels
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | star14ms/transformer-evolution | PoswiseFeedForwardNet | false | 4,409 | [
"Apache-2.0"
] | 0 | 95b57485f59a0cee4528af62e5010002e6a3448a | https://github.com/star14ms/transformer-evolution/tree/95b57485f59a0cee4528af62e5010002e6a3448a |
ycbcr_to_rgb_jpeg | # 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 numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | foxtrotmike/DiffJPEG | ycbcr_to_rgb_jpeg | false | 12,394 | [
"MIT"
] | 0 | 7dbc44b1e921f20a213a7206a8578d6a1c8131b4 | https://github.com/foxtrotmike/DiffJPEG/tree/7dbc44b1e921f20a213a7206a8578d6a1c8131b4 |
FirstResBlockDiscriminator | # 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
from torch... | ldlasso2/hologan-pytorch | FirstResBlockDiscriminator | false | 15,890 | [
"BSD-3-Clause"
] | 61 | baec67d3673cc68e51434516d19465f3d6dd0a1b | https://github.com/ldlasso2/hologan-pytorch/tree/baec67d3673cc68e51434516d19465f3d6dd0a1b |
GeneratorLoss | import torch
from torch import nn
class GeneratorLoss(nn.Module):
def __init__(self, alpha=100):
super().__init__()
self.alpha = alpha
self.bce = nn.BCEWithLogitsLoss()
self.l1 = nn.L1Loss()
def forward(self, fake, real, fake_pred):
fake_target = torch.ones_like(fake_... | 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 ... | akanametov/Pix2Pix-new | GeneratorLoss | false | 6,142 | [
"MIT"
] | 1 | 46aaefc506655dbf918ffdbd1c79174d76a748d0 | https://github.com/akanametov/Pix2Pix-new/tree/46aaefc506655dbf918ffdbd1c79174d76a748d0 |
TemporalBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | AdamLohSg/GTA | TemporalBlock | false | 16,898 | [
"Apache-2.0"
] | 8 | bf6a745a6e28e365466e76360a15ca10ce61e009 | https://github.com/AdamLohSg/GTA/tree/bf6a745a6e28e365466e76360a15ca10ce61e009 |
MultiHeadAttention | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class MultiHeadAttention(nn.Module):
"""Multi-headed Attention for input Query, Key, Value
Multi-headed Attention is a module for attention mechanisms which runs through attention in several times in
parallel, then the multiple... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | UdbhavPrasad072300/CPS843_Final_Project | MultiHeadAttention | false | 9,731 | [
"MIT"
] | 0 | 042f0bad48c7e49b71ab8efbc4ac5a9e6a6cf31c | https://github.com/UdbhavPrasad072300/CPS843_Final_Project/tree/042f0bad48c7e49b71ab8efbc4ac5a9e6a6cf31c |
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.... | dimitrijejankov/vits | MultiHeadAttention | false | 3,426 | [
"MIT"
] | 0 | d2f6385c7946c2355433804796b541ffae0a3d9f | https://github.com/dimitrijejankov/vits/tree/d2f6385c7946c2355433804796b541ffae0a3d9f |
Q_Critic | import torch
import torch.nn as nn
import torch.nn.functional as F
class Q_Critic(nn.Module):
def __init__(self, state_dim, action_dim, net_width):
super(Q_Critic, self).__init__()
self.l1 = nn.Linear(state_dim + action_dim, net_width)
self.l2 = nn.Linear(net_width, net_width)
sel... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | XinJingHao/RL | Q_Critic | false | 18,100 | [
"MIT"
] | 6 | eed54d6602b173e45ede722b0fcf82b5a203f14a | https://github.com/XinJingHao/RL/tree/eed54d6602b173e45ede722b0fcf82b5a203f14a |
Encoding | # 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.nn as nn
... | AlexanderDokuchaev/mmsegmentation | Encoding | false | 11,189 | [
"Apache-2.0"
] | 0 | 0c443ee370cce6227661b802184072174c4e3f64 | https://github.com/AlexanderDokuchaev/mmsegmentation/tree/0c443ee370cce6227661b802184072174c4e3f64 |
SelfAttentionPooling | import torch
import torch.nn as nn
class SelfAttentionPooling(nn.Module):
"""
Implementation of SelfAttentionPooling
Original Paper: Self-Attention Encoding and Pooling for Speaker Recognition
https://arxiv.org/pdf/2008.01077v1.pdf
"""
def __init__(self, input_dim):
super(SelfAttenti... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | B06901052/s3prl | SelfAttentionPooling | false | 121 | [
"MIT"
] | 0 | 5f63d2df043d2d7c81580cd042fa2cea34746f48 | https://github.com/B06901052/s3prl/tree/5f63d2df043d2d7c81580cd042fa2cea34746f48 |
eSEModule | import torch
from torch import nn
import torch.nn.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
class eSEModule(nn.Module... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import t... | UWO-CCPL/AdelaiDet | eSEModule | false | 9,565 | [
"BSD-2-Clause"
] | 0 | 29a59575697dbbb4cfe7b7ab821805913348cf61 | https://github.com/UWO-CCPL/AdelaiDet/tree/29a59575697dbbb4cfe7b7ab821805913348cf61 |
LogCoshLoss | # 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
assert_size... | CSID-DGU/-2020-1-OSSP1-ninetynine-2 | LogCoshLoss | false | 4,940 | [
"MIT"
] | 1 | b1824254882eeea0ee44e4e60896b72c51ef1d2c | https://github.com/CSID-DGU/-2020-1-OSSP1-ninetynine-2/tree/b1824254882eeea0ee44e4e60896b72c51ef1d2c |
Encoder | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | hcgcarry/usad | Encoder | false | 3,594 | [
"BSD-3-Clause"
] | 0 | 4e99a6acd43ef109be4d89b80e96978b9ad61c2f | https://github.com/hcgcarry/usad/tree/4e99a6acd43ef109be4d89b80e96978b9ad61c2f |
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
import ... | BradleyBrown19/CustomObjectDetector | ClassificationModel | false | 2,127 | [
"Apache-2.0"
] | 0 | 11c14ec6127c553ac365703c768b75dde33d9a4d | https://github.com/BradleyBrown19/CustomObjectDetector/tree/11c14ec6127c553ac365703c768b75dde33d9a4d |
AvgPoolPad | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.init
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dy... | MichoelSnow/data_science | AvgPoolPad | false | 9,866 | [
"MIT"
] | 0 | 7f6c054624268308ec4126a601c9fa8bc5de157c | https://github.com/MichoelSnow/data_science/tree/7f6c054624268308ec4126a601c9fa8bc5de157c |
ConditionalBatchNorm2d | # 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 ... | samuelemarro/anne | ConditionalBatchNorm2d | false | 4,267 | [
"MIT"
] | 0 | 918022eb029a46fbfd1589369e9817f570d5651c | https://github.com/samuelemarro/anne/tree/918022eb029a46fbfd1589369e9817f570d5651c |
RSubInt | import torch
class RSubInt(torch.nn.Module):
def __init__(self):
super(RSubInt, self).__init__()
def forward(self, x):
return 1 - x
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | PogChamper/torch2trt | RSubInt | false | 14,219 | [
"MIT"
] | 3,363 | 43b12627ec0de4d212efb6d02b07570205085ccc | https://github.com/PogChamper/torch2trt/tree/43b12627ec0de4d212efb6d02b07570205085ccc |
RankScaledGaussianPrior | # 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... | dmoebius-dm/prototorch_models | RankScaledGaussianPrior | false | 3,436 | [
"MIT"
] | 0 | 71602bf38a09148eab13d98c9f89589b345ac570 | https://github.com/dmoebius-dm/prototorch_models/tree/71602bf38a09148eab13d98c9f89589b345ac570 |
BCL | import torch
import torch.utils.data
import torch
from torch import nn
class BCL(nn.Module):
"""
batch-balanced contrastive loss
no-change，1
change，-1
"""
def __init__(self, margin=2.0):
super(BCL, self).__init__()
self.margin = margin
def forward(self, distance, label):
... | 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.utils.data
import torch
from torch import nn
assert_size_stride = torch._C._... | cuicaihao/STANet | BCL | false | 15,089 | [
"BSD-2-Clause"
] | 220 | 4c644e2a65bc9516f1d97b29b12ca864638c0c7e | https://github.com/cuicaihao/STANet/tree/4c644e2a65bc9516f1d97b29b12ca864638c0c7e |
UpsampleConv | import torch
import torch.nn.functional as F
import torch.nn as nn
def l2normalize(v, esp=1e-08):
return v / (v.norm() + esp)
def sn_weight(weight, u, height, n_power_iterations):
weight.requires_grad_(False)
for _ in range(n_power_iterations):
v = l2normalize(torch.mv(weight.view(height, -1).t(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn.functional as F
import torch.nn as nn
assert_size_stride = torch... | tsirif/cortex | UpsampleConv | false | 16,620 | [
"BSD-3-Clause"
] | 109 | 2837b220f9fb73279df3815bb18b274106412c08 | https://github.com/tsirif/cortex/tree/2837b220f9fb73279df3815bb18b274106412c08 |
Decoder | # 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... | XIAOYEJIAYOU/GSAN | Decoder | false | 18,090 | [
"MIT"
] | 6 | 8ca4fdf4c3d615af9cc10e1f9f22ceb7e27fe196 | https://github.com/XIAOYEJIAYOU/GSAN/tree/8ca4fdf4c3d615af9cc10e1f9f22ceb7e27fe196 |
RobertaClassificationHead | import torch
import torch.nn as nn
from typing import Optional
class RobertaClassificationHead(nn.Module):
def __init__(self, num_classes, input_dim, inner_dim: 'Optional[int]'=
None, dropout: 'float'=0.1, activation=nn.ReLU):
super().__init__()
if not inner_dim:
inner_dim = i... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from ty... | abhinavarora/text | RobertaClassificationHead | false | 6,062 | [
"BSD-3-Clause"
] | 1 | 69f67f3a775f3d3c6f85cfaa4ac3819500b90696 | https://github.com/abhinavarora/text/tree/69f67f3a775f3d3c6f85cfaa4ac3819500b90696 |
Swish | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
@triton.jit
def triton_poi_fused_mul_sigmoid_0(in_pt... | minhduc0711/labelImg | Swish | false | 12,781 | [
"MIT"
] | 0 | 5030721bb6a59424bfed1d7c09b56e01d08662a1 | https://github.com/minhduc0711/labelImg/tree/5030721bb6a59424bfed1d7c09b56e01d08662a1 |
PANNsLoss | # 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... | Gopi-Durgaprasad/Kaggle-Cornell-Birdcall-Identification | PANNsLoss | false | 2,306 | [
"Apache-2.0"
] | 0 | 9eafbcba3323c29b0f9271911debc2f18af78f23 | https://github.com/Gopi-Durgaprasad/Kaggle-Cornell-Birdcall-Identification/tree/9eafbcba3323c29b0f9271911debc2f18af78f23 |
SAB | import math
import torch
import torch.nn.functional as F
import torch.nn as nn
class MAB(nn.Module):
def __init__(self, dim_X, dim_Y, dim, num_heads=4, ln=False, p=None):
super().__init__()
self.num_heads = num_heads
self.fc_q = nn.Linear(dim_X, dim)
self.fc_k = nn.Linear(dim_Y, d... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | OpenXAIProject/dac | SAB | false | 8,642 | [
"MIT"
] | 17 | 652776e21b56dcb68839363bb077d5c5ea28d81e | https://github.com/OpenXAIProject/dac/tree/652776e21b56dcb68839363bb077d5c5ea28d81e |
GaussianFocalLoss | import functools
import torch
import torch.nn as nn
import torch.nn.functional as F
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Return:
Tensor: Reduced loss ten... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import functools
impor... | Andrew-Zhu/DyFPN | GaussianFocalLoss | false | 7,729 | [
"Apache-2.0"
] | 32 | a74463b59c4ce28253c2449a07c0f6692a0147a1 | https://github.com/Andrew-Zhu/DyFPN/tree/a74463b59c4ce28253c2449a07c0f6692a0147a1 |
AGELU | import math
import torch
import torch.utils.data
import torch.cuda
import torch.utils.checkpoint
def agelu(x):
SQRT_M2_PI = math.sqrt(2 / math.pi)
COEFF = 0.044715
return 0.5 * x * (1.0 + torch.tanh(SQRT_M2_PI * (x + COEFF * torch.pow(
x, 3))))
class AGELU(torch.nn.Module):
def forward(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.triton_helpers import libdevice
import math
import torch.utils.data
import torch.cuda
import torch.utils.checkp... | Dan-hbd/NMTGMinor | AGELU | false | 5,146 | [
"MIT"
] | 1 | 84e59ac8391ee78852d7c71afc60c3c8b8e3d44d | https://github.com/Dan-hbd/NMTGMinor/tree/84e59ac8391ee78852d7c71afc60c3c8b8e3d44d |
SmallNN | import torch
from torch import nn
import torch.nn.functional as F
class SmallNN(nn.Module):
def __init__(self, in_channels, out_channels):
super().__init__()
self.l1 = nn.Linear(in_channels, 32)
self.l2 = nn.Linear(32, 32)
self.l3 = nn.Linear(32, out_channels)
def forward(sel... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | AustinCai/gmaxup-augmentation | SmallNN | false | 100 | [
"MIT"
] | 0 | a64ca0a76eb333e5ce6b217c301d27ca04d73bce | https://github.com/AustinCai/gmaxup-augmentation/tree/a64ca0a76eb333e5ce6b217c301d27ca04d73bce |
Net | import torch
import torch.nn.functional as F
from torch import nn
import torch.utils.data
class Net(nn.Module):
def __init__(self, in_dim):
super().__init__()
self.fc1 = nn.Linear(in_dim, 120, bias=False)
nn.init.normal_(self.fc1.weight, mean=0, std=1)
self.fc2 = nn.Linear(120, 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 import nn
import t... | nmichlo/msc-research | Net | false | 7,352 | [
"MIT"
] | 1 | 625e57eca77bbfbc4728ccebdb0733e1613bd258 | https://github.com/nmichlo/msc-research/tree/625e57eca77bbfbc4728ccebdb0733e1613bd258 |
BartClassificationHead | # 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 ... | Elvisambition/bert_seq2seq | BartClassificationHead | false | 5,126 | [
"Apache-2.0"
] | 1 | 643ac537c16872f0d13200de06001d8201a54fbb | https://github.com/Elvisambition/bert_seq2seq/tree/643ac537c16872f0d13200de06001d8201a54fbb |
RingLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
from torch.nn.modules.loss import CrossEntropyLoss
class RingLoss(nn.Module):
def __init__(self, type='auto', loss_weight=1.0, softmax_loss_weight=1.0):
"""
:param type: type of loss ('l1',... | 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... | gorogoroyasu/mlcomp | RingLoss | false | 15,456 | [
"Apache-2.0"
] | 166 | fc6572ca5b226b35df97f13badd4420b30468a3b | https://github.com/gorogoroyasu/mlcomp/tree/fc6572ca5b226b35df97f13badd4420b30468a3b |
SuperLoss | import torch
import torch.utils.data
from torch import nn
import torch
class netMSELoss(nn.Module):
def __init__(self):
super().__init__()
def forward(self, output, target):
return self.computeLoss(output, target)
def computeLoss(self, output, target):
loss = torch.mean((output ... | 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.utils.data
from torch import nn
import torch
assert_size_stride = torch._C._... | brown-ivl/beacon | SuperLoss | false | 6,372 | [
"MIT"
] | 1 | 66a1714473b362294f787f261561e39c52f00e42 | https://github.com/brown-ivl/beacon/tree/66a1714473b362294f787f261561e39c52f00e42 |
GCN | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
class GraphConvolution(nn.Module):
"""
Simple GCN layer, similar to https://arxiv.org/abs/1609.02907
"""
def __init__(self, in_features, out_features, bias=True):
super(Grap... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.nn a... | BrunoKM/rhoana_graph_tools | GCN | false | 4,923 | [
"MIT"
] | 1 | 7150f4bc6337ecf51dd9123cf03561a57d655160 | https://github.com/BrunoKM/rhoana_graph_tools/tree/7150f4bc6337ecf51dd9123cf03561a57d655160 |
BasicBlock | # 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 ... | EgonFerri/Final_project_Aml_ARC | BasicBlock | false | 2,188 | [
"MIT"
] | 0 | d5290a0bfef5e1aa0feb5988cdfe6de704180485 | https://github.com/EgonFerri/Final_project_Aml_ARC/tree/d5290a0bfef5e1aa0feb5988cdfe6de704180485 |
TVLoss | import torch
import torch.nn as nn
class TVLoss(nn.Module):
def __init__(self, TVLoss_weight=1):
super(TVLoss, self).__init__()
self.TVLoss_weight = TVLoss_weight
def forward(self, x):
batch_size = x.size()[0]
h_x = x.size()[2]
w_x = x.size()[3]
count_h = (x.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.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | Axrid/cv_template | TVLoss | false | 13,335 | [
"MIT"
] | 69 | 5c344692a1fcfb08b75d7104bcc78307b5640ecf | https://github.com/Axrid/cv_template/tree/5c344692a1fcfb08b75d7104bcc78307b5640ecf |
RelationNonLocal | # 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... | luozn15/FloorplanGAN | RelationNonLocal | false | 3,946 | [
"MIT"
] | 0 | 113813c2e857c5cd4e64c92626d359e5746e9eab | https://github.com/luozn15/FloorplanGAN/tree/113813c2e857c5cd4e64c92626d359e5746e9eab |
AMSoftmaxLoss | # 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.... | gcambara/s3prl | AMSoftmaxLoss | false | 15,407 | [
"MIT"
] | 856 | 33284ebde3a903ed8604d6dae85669d0174ae1d3 | https://github.com/gcambara/s3prl/tree/33284ebde3a903ed8604d6dae85669d0174ae1d3 |
AttCeLoss | # 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
... | Raiselimit/TorchBlocks | AttCeLoss | false | 5,745 | [
"MIT"
] | 1 | a5baecb9a2470ff175087475630f2b7db3f7ef51 | https://github.com/Raiselimit/TorchBlocks/tree/a5baecb9a2470ff175087475630f2b7db3f7ef51 |
MultiplicativeLinear | import collections
import torch
import torch.utils.data
from torch import nn
class SummaryWriterNamespaceNoLoggingScope:
def __init__(self, writer):
self._writer = writer
def __enter__(self):
self._writer._logging_enabled = False
def __exit__(self, type, value, traceback):
self.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import collec... | hoedt/stable-nalu | MultiplicativeLinear | false | 3,610 | [
"MIT"
] | 0 | 64b3d240db8bff4da857d955f213ef3c7e38e035 | https://github.com/hoedt/stable-nalu/tree/64b3d240db8bff4da857d955f213ef3c7e38e035 |
BertImagePooler | from _paritybench_helpers import _mock_config
import torch
import torch.optim
import torch.utils.data
from torch import nn
import torch
class BertImagePooler(nn.Module):
def __init__(self, config):
super(BertImagePooler, self).__init__()
self.dense = nn.Linear(config.v_hidden_size, config.bi_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
import torch.optim
import tor... | ChoiIseungil/vilbert-multi-task | BertImagePooler | false | 7,610 | [
"MIT"
] | 1 | 37d14b9aed9c48117a820e05157c7ccd3dd20d5b | https://github.com/ChoiIseungil/vilbert-multi-task/tree/37d14b9aed9c48117a820e05157c7ccd3dd20d5b |
PositionwiseFeedForward | # 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.... | PINE4PPLE/transformer-lm | PositionwiseFeedForward | false | 9,434 | [
"MIT"
] | 0 | da76a4afd29d1fd023ba866ccc21a49901ad46f2 | https://github.com/PINE4PPLE/transformer-lm/tree/da76a4afd29d1fd023ba866ccc21a49901ad46f2 |
DecoderLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | muberraozmen/MrMP | DecoderLayer | false | 4,053 | [
"MIT"
] | 0 | da6bcccbad85a682c848ff4aa1121c773d779e57 | https://github.com/muberraozmen/MrMP/tree/da6bcccbad85a682c848ff4aa1121c773d779e57 |
NaiveGroupNorm | from torch.nn import Module
import torch
from torch.nn import Parameter
from torch.nn import init
import torch.nn.parallel
class NaiveGroupNorm(Module):
"""NaiveGroupNorm implements Group Normalization with the high-level matrix operations in PyTorch.
It is a temporary solution to export GN by ONNX before the... | 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.nn import Module
from torch.nn import Parameter
from torch.nn import... | Tanveer81/BoxVOS | NaiveGroupNorm | false | 17,982 | [
"BSD-2-Clause"
] | 4 | c30aa319f18f3fbee2a25e0ed25cb006a4598300 | https://github.com/Tanveer81/BoxVOS/tree/c30aa319f18f3fbee2a25e0ed25cb006a4598300 |
SaAdaIN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.optim
import torch.utils.data
assert_size_st... | VITA-Group/Sandwich-Batch-Normalization | SaAdaIN | false | 14,541 | [
"MIT"
] | 46 | 25e7df6e64a67cebd7e70b911f874cfc1bd19df0 | https://github.com/VITA-Group/Sandwich-Batch-Normalization/tree/25e7df6e64a67cebd7e70b911f874cfc1bd19df0 |
SimpleAndModule | # 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.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | opti-mix/glow | SimpleAndModule | false | 7,389 | [
"Apache-2.0"
] | 1 | 4ba074df5da9822986a23a6679ab592c22660f6d | https://github.com/opti-mix/glow/tree/4ba074df5da9822986a23a6679ab592c22660f6d |
ConvMeanPool | import torch
import torch.nn as nn
class ConvMeanPool(nn.Module):
def __init__(self, input_dim, output_dim, kernel_size=3, biases=True,
adjust_padding=False):
super().__init__()
if not adjust_padding:
conv = nn.Conv2d(input_dim, output_dim, kernel_size, stride=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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | DeepTitan/PNDM | ConvMeanPool | false | 13,583 | [
"Apache-2.0"
] | 61 | 4037a4f40011c9a0d47b92303e64d47fcc7ed56a | https://github.com/DeepTitan/PNDM/tree/4037a4f40011c9a0d47b92303e64d47fcc7ed56a |
Transition | # 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_... | mnmueller/auto_LiRPA | Transition | false | 7,256 | [
"BSD-3-Clause"
] | 1 | 55cb270b0b99f07b74541d55706c69fbb9daff66 | https://github.com/mnmueller/auto_LiRPA/tree/55cb270b0b99f07b74541d55706c69fbb9daff66 |
SimpleSoftmaxModel | # 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.jit
impor... | YaronBenAtar/glow | SimpleSoftmaxModel | false | 14,683 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
BasicBlock | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
def conv3x3(in_planes, out_planes, stride=1, dilation=1):
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=dilation, dilation=dilation, bias=False)
class BasicBlock(nn.Module):
expansion ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | JiazeWang/6-PACK | BasicBlock | false | 11,546 | [
"MIT"
] | 0 | bce910213cfbf89b4ed7b59ff6c70a59a7c19b99 | https://github.com/JiazeWang/6-PACK/tree/bce910213cfbf89b4ed7b59ff6c70a59a7c19b99 |
LatentAtten | # 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.... | kage08/CAMul | LatentAtten | false | 10,376 | [
"MIT"
] | 0 | 79f8a27f472943229fb087bae8e405e38e5e0b47 | https://github.com/kage08/CAMul/tree/79f8a27f472943229fb087bae8e405e38e5e0b47 |
BiliAttnReduction | import torch
from torch import nn
import torch as t
from torch.nn import functional as F
def getMaskFromLens(lens, max_seq_len=200, expand_feature_dim=None):
if type(lens) == list:
lens = t.LongTensor(lens)
batch_size = len(lens)
idx_matrix = t.arange(0, max_seq_len, 1).repeat((batch_size, 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.... | Asichurter/MalFusionFSL | BiliAttnReduction | false | 16,989 | [
"MIT"
] | 4 | 713bf64cc07a3489f42941fd2299837075575ac0 | https://github.com/Asichurter/MalFusionFSL/tree/713bf64cc07a3489f42941fd2299837075575ac0 |
Conv2dDynamicSamePadding | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class Conv2dDynamicSamePadding(nn.Conv2d):
"""2D Convolutions like TensorFlow, for a dynamic image size.
The padding is operated in forward function by calculating dynamically.
"""
def __init__(self, in_channels, out_ch... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | Exdenta/torchsat | Conv2dDynamicSamePadding | false | 13,660 | [
"MIT"
] | 316 | 70ea3db758757104fb3ba618ddf7997f0f3a75b4 | https://github.com/Exdenta/torchsat/tree/70ea3db758757104fb3ba618ddf7997f0f3a75b4 |
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... | Justin-Tan/ffjord | GatedLinear | false | 699 | [
"MIT"
] | 0 | 2caf8a4ff84933672fe0d94255d665b3dd7a6791 | https://github.com/Justin-Tan/ffjord/tree/2caf8a4ff84933672fe0d94255d665b3dd7a6791 |
ConvTranspose2dBlock | import torch
import torch.utils.data
import torch
from torch.nn import functional as F
import torch.nn as nn
class AdaptiveInstanceNorm2d(nn.Module):
def __init__(self, num_features, eps=1e-05, momentum=0.1):
super(AdaptiveInstanceNorm2d, self).__init__()
self.num_features = num_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
import torch.utils.data
impor... | ast0414/semit | ConvTranspose2dBlock | false | 3,141 | [
"MIT"
] | 0 | c221222ba06f14611e3d030969cdb9f7c17ff98f | https://github.com/ast0414/semit/tree/c221222ba06f14611e3d030969cdb9f7c17ff98f |
TripletLoss | # 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 import nn
assert_... | SeungHeonDoh/music_zeroshot_models | TripletLoss | false | 5,823 | [
"MIT"
] | 1 | 38f80df868da357f3cb30522ad2e2031f0bc184e | https://github.com/SeungHeonDoh/music_zeroshot_models/tree/38f80df868da357f3cb30522ad2e2031f0bc184e |
LanguageModelCriterion | import torch
import torch.nn as nn
from torch.autograd import *
class LanguageModelCriterion(nn.Module):
def __init__(self):
super(LanguageModelCriterion, self).__init__()
def forward(self, input, target, mask):
target = target[:, :input.size(1)]
mask = mask[:, :input.size(1)]
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.autograd import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | anonymous2021hello/transformer-cil | LanguageModelCriterion | false | 3,117 | [
"MIT"
] | 0 | aed4017b61afaf4d9d21d40a078eefb4c7031cd1 | https://github.com/anonymous2021hello/transformer-cil/tree/aed4017b61afaf4d9d21d40a078eefb4c7031cd1 |
JSCriterion | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch.... | kiminh/mt-dnn | JSCriterion | false | 7,033 | [
"MIT"
] | 1 | 133884b380244dbe74acc4d7507e551b2c5035b3 | https://github.com/kiminh/mt-dnn/tree/133884b380244dbe74acc4d7507e551b2c5035b3 |
SilogLoss | # 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... | Fatmangh/VIDEO-ACTION-CLASSIFICATION-USING-PRETAINED-SELF-SUPERVISED-DEPTH-AWARE-DENSE-PREDICTIVE-CODING- | SilogLoss | false | 2,230 | [
"MIT"
] | 0 | 13fac05601efed16ae8b29989aad487e04cd90a7 | https://github.com/Fatmangh/VIDEO-ACTION-CLASSIFICATION-USING-PRETAINED-SELF-SUPERVISED-DEPTH-AWARE-DENSE-PREDICTIVE-CODING-/tree/13fac05601efed16ae8b29989aad487e04cd90a7 |
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.triton_helpers import math as tl_math
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_str... | edwardzhou130/Panoptic-PolarNet | FocalLoss | false | 15,289 | [
"BSD-3-Clause"
] | 90 | 3a72f2380a4e505e191b69da596f521a9d9f1a71 | https://github.com/edwardzhou130/Panoptic-PolarNet/tree/3a72f2380a4e505e191b69da596f521a9d9f1a71 |
C3D_td5 | # 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_... | pingaowang/pytorch-video-recognition | C3D_td5 | false | 16,754 | [
"MIT"
] | 946 | 096267f88d96a77a74ff743fb0115d997e2cdafd | https://github.com/pingaowang/pytorch-video-recognition/tree/096267f88d96a77a74ff743fb0115d997e2cdafd |
MLP | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | JoonseoKang/mcan-cap | MLP | false | 11,582 | [
"Apache-2.0"
] | 0 | 788e21fc1bc712018166aa44cc3298264f493f3b | https://github.com/JoonseoKang/mcan-cap/tree/788e21fc1bc712018166aa44cc3298264f493f3b |
ToLongTensor | import torch
from torch import Tensor
from typing import List
import torch.nn as nn
class ToLongTensor(nn.Module):
"""Convert a list of integers to long tensor
"""
def __init__(self):
super(ToLongTensor, self).__init__()
def forward(self, tokens: 'List[List[int]]') ->Tensor:
return 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | LaudateCorpus1/text-1 | ToLongTensor | false | 9,265 | [
"BSD-3-Clause"
] | 0 | 8808e7eee5a2df79b9566a4a348889dc2722fcfb | https://github.com/LaudateCorpus1/text-1/tree/8808e7eee5a2df79b9566a4a348889dc2722fcfb |
TransformerEncoderLayer | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
import torch.utils.data
import torch.distributions
class TransformerEncoderLayer(nn.Module):
def __init__(self, embed_dim, num_heads, hidden_size, dropout=0.0,
attention_dropout=0.0, activation_dropout=0.0):
... | 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.... | cjlovering/EGG | TransformerEncoderLayer | false | 10,064 | [
"MIT"
] | 0 | cce146e035decbc410e981f8bc7ada32979f3b6d | https://github.com/cjlovering/EGG/tree/cce146e035decbc410e981f8bc7ada32979f3b6d |
ChannelAttentionModule | # 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.... | rushirajsherlocked/External-Attention-pytorch | ChannelAttentionModule | false | 4,233 | [
"MIT"
] | 0 | 7d6814b2d90909adf81c62f3f8a89e30a59d6481 | https://github.com/rushirajsherlocked/External-Attention-pytorch/tree/7d6814b2d90909adf81c62f3f8a89e30a59d6481 |
DistillationLoss | import torch
from torch import Tensor
from torch import nn
from typing import Union
class DistillationLoss(nn.Module):
"""Distilling the Knowledge in a Neural Network
https://arxiv.org/pdf/1503.02531.pdf
"""
def __init__(self, alpha: 'float'=0.95, temp: 'Union[float, int]'=6
) ->None:
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch ... | sithu31296/image_classification | DistillationLoss | false | 16,468 | [
"MIT"
] | 57 | 6b8cbce96100225621cee3166a73e852ba216cc3 | https://github.com/sithu31296/image_classification/tree/6b8cbce96100225621cee3166a73e852ba216cc3 |
C3D | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
from torch.nn.init import *
class C3D(nn.Module):
"""
The C3D network.
"""
def __init__(self, num_classes, pretrained=False, path=None):
super(C3D, self).__init__()
self.conv1 = nn.Conv3d(3, 64, kernel_size... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | Luoyadan/MM2020_ABG | C3D | false | 17,825 | [
"MIT"
] | 8 | d74cf915deea7bb425518f5bd40e64a9a7341981 | https://github.com/Luoyadan/MM2020_ABG/tree/d74cf915deea7bb425518f5bd40e64a9a7341981 |
WeldonPooling | import torch
import torch.nn as nn
class WeldonPooling(nn.Module):
def __init__(self, nMax=1, nMin=None):
super(WeldonPooling, self).__init__()
self.nMax = nMax
if nMin is None:
self.nMin = nMax
else:
self.nMin = nMin
self.input = torch.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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | maxgreat/dsve-loc | WeldonPooling | false | 16,024 | [
"BSD-3-Clause-Clear"
] | 56 | dd6807d02c0d5fd3e215be8e5c7a88e73102e561 | https://github.com/maxgreat/dsve-loc/tree/dd6807d02c0d5fd3e215be8e5c7a88e73102e561 |
gaussian_layer | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.a... | Xmaster6y/wgenpatex | gaussian_layer | false | 18,120 | [
"MIT"
] | 8 | 08079dc131cc2e9c74ee4f9e16cf9b58667f2b07 | https://github.com/Xmaster6y/wgenpatex/tree/08079dc131cc2e9c74ee4f9e16cf9b58667f2b07 |
BCELoss | import torch
import torch.nn as nn
import torch.utils.data
class BCELoss(nn.Module):
def __init__(self):
super(self.__class__, self).__init__()
def forward(self, input, target):
return -torch.mean(torch.sum(target * torch.log(torch.clamp(input,
min=1e-10)) + (1 - target) * torch.... | 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
... | klovbe/UnsupervisedDeepLearning-Pytorch | BCELoss | false | 7,046 | [
"MIT"
] | 1 | 35e8e49cd4024179db173f3dab2e6d1a5d037d35 | https://github.com/klovbe/UnsupervisedDeepLearning-Pytorch/tree/35e8e49cd4024179db173f3dab2e6d1a5d037d35 |
PairwiseDistanceMatrix | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
class PairwiseDistanceMatrix(nn.Module):
def __init__(self):
super(PairwiseDistanceMatrix, self).__init__()
def forward(self, X, Y):
X2 = (X ** 2).sum(1).view(-1, 1)
Y2 = (Y ** 2).sum(1).view(1, -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
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
assert_si... | DreamBlack/APCNet | PairwiseDistanceMatrix | false | 379 | [
"MIT"
] | 0 | d76bc9e46c3b631035c5c67e2367b6fb80621333 | https://github.com/DreamBlack/APCNet/tree/d76bc9e46c3b631035c5c67e2367b6fb80621333 |
MultiHeadAttention | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class MultiHeadAttention(nn.Module):
def __init__(self, heads, d_model, dropout=0.1):
super().__init__()
self.d_model = d_model
self.d_k = d_model // heads
self.h = heads
self.q_linear = nn.Line... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | CS-savvy/Transformer-for-Parkinsons-disease | MultiHeadAttention | false | 2,091 | [
"MIT"
] | 0 | 42ef54071092f4aab74c8b9ec82c52e944806a5b | https://github.com/CS-savvy/Transformer-for-Parkinsons-disease/tree/42ef54071092f4aab74c8b9ec82c52e944806a5b |
Noise_injector | # 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... | EliasKassapis/CAR | Noise_injector | false | 8,067 | [
"Apache-2.0"
] | 17 | ff7ec86aab68c4b9ff8aea171244991bd132d487 | https://github.com/EliasKassapis/CAR/tree/ff7ec86aab68c4b9ff8aea171244991bd132d487 |
SubsequentSpanEncoder | import torch
from torch import Tensor
from torch.nn.modules.transformer import TransformerEncoderLayer
class SubsequentSpanEncoder(TransformerEncoderLayer):
"""
The subsequent layers for the Segmental Transformer Encoder. The encoded
representations from previous layers attend over all unmasked positions ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | cmdowney88/XLSLM | SubsequentSpanEncoder | false | 3,326 | [
"MIT"
] | 0 | 7fe266bd0f0ad8a79a30052a18104b974d1c32e8 | https://github.com/cmdowney88/XLSLM/tree/7fe266bd0f0ad8a79a30052a18104b974d1c32e8 |
MNIST_CNN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Neronjust2017/DomainBed | MNIST_CNN | false | 11,757 | [
"MIT"
] | 0 | 42be49a316a74799b95d6a5e29bb210477c7f828 | https://github.com/Neronjust2017/DomainBed/tree/42be49a316a74799b95d6a5e29bb210477c7f828 |
ScaledDotProductAtten | # 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.... | LinXueyuanStdio/scRNN-seq | ScaledDotProductAtten | false | 2,510 | [
"Apache-2.0"
] | 0 | 87e11a56acb18a86fa4fb309d33a1bc02bf38b39 | https://github.com/LinXueyuanStdio/scRNN-seq/tree/87e11a56acb18a86fa4fb309d33a1bc02bf38b39 |
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
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | Ziaf007/Machine-Learning | Net | false | 6,031 | [
"MIT"
] | 1 | 144b819b12cbf963f6a22de7701de7fa7965147d | https://github.com/Ziaf007/Machine-Learning/tree/144b819b12cbf963f6a22de7701de7fa7965147d |
TransposeLayer | import torch
class TransposeLayer(torch.nn.Module):
"""Transpose the input."""
def forward(self, data):
return data.t().contiguous()
def get_inputs():
return [torch.rand([4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | bolajiy/beer | TransposeLayer | false | 14,963 | [
"MIT"
] | 46 | 6fe968c7ca4864437890aa6bd705755c2580696e | https://github.com/bolajiy/beer/tree/6fe968c7ca4864437890aa6bd705755c2580696e |
SmallDecoder4_16x | import torch
import torch.nn as nn
class SmallDecoder4_16x(nn.Module):
def __init__(self, model=None, fixed=False):
super(SmallDecoder4_16x, self).__init__()
self.fixed = fixed
self.conv41 = nn.Conv2d(128, 64, 3, 1, 0)
self.conv34 = nn.Conv2d(64, 64, 3, 1, 0)
self.conv33 =... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | EndyWon/Texture-Reformer | SmallDecoder4_16x | false | 8,161 | [
"MIT"
] | 11 | f84f95accb3574c7b759a7f03c0b0b4e150314b5 | https://github.com/EndyWon/Texture-Reformer/tree/f84f95accb3574c7b759a7f03c0b0b4e150314b5 |
MODEL | # 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... | cuis15/xorder | MODEL | false | 9,991 | [
"MIT"
] | 0 | 6dde5a18552ffa07f29100038464a38c49495527 | https://github.com/cuis15/xorder/tree/6dde5a18552ffa07f29100038464a38c49495527 |
CauchyLoss | # 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
from typing import *
import torch.nn as nn
assert_size_stride = torch._C.... | ciwanceylan/gated-gradient-flow | CauchyLoss | false | 6,442 | [
"Apache-2.0"
] | 1 | c4f6c0c987f428697336e4514099aa7ef2351388 | https://github.com/ciwanceylan/gated-gradient-flow/tree/c4f6c0c987f428697336e4514099aa7ef2351388 |
TorchMul | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | Akababa/torch2trt | TorchMul | false | 18,440 | [
"MIT"
] | 2 | 03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 | https://github.com/Akababa/torch2trt/tree/03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 |
BertPredictionHeadTransform | # 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 ... | PKU-DAIR/2021_CCF_BDCI_LargeBERT_Rank1st | BertPredictionHeadTransform | false | 17,784 | [
"Apache-2.0"
] | 4 | 6382433cda69c655f03c3cc284dc076407f18dc9 | https://github.com/PKU-DAIR/2021_CCF_BDCI_LargeBERT_Rank1st/tree/6382433cda69c655f03c3cc284dc076407f18dc9 |
Sine | import torch
import torch.nn as nn
class Sine(nn.Module):
"""
A wrapper for PyTorch sine function.
"""
def __init__(self, w0=1.0):
super().__init__()
self.w0 = w0
@staticmethod
def forward(x):
return torch.sin(x)
def get_inputs():
return [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.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | FinbarArgus/phynn | Sine | false | 2,238 | [
"Apache-2.0"
] | 0 | 436bfd6fa4ad86692bf12b4f76c92bc177626c40 | https://github.com/FinbarArgus/phynn/tree/436bfd6fa4ad86692bf12b4f76c92bc177626c40 |
EdgeFeaturesLayer | # 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_... | Jh-SYSU/MolRep | EdgeFeaturesLayer | false | 13,877 | [
"MIT"
] | 57 | b2c802d18d41d7db26c19c6dd644098f945e48a1 | https://github.com/Jh-SYSU/MolRep/tree/b2c802d18d41d7db26c19c6dd644098f945e48a1 |
MyGlobalAvgPool2d | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
import torch.nn.parallel
import torch.optim
assert_size_stride = torch._C._dynamo.guards.asser... | AlbertiPot/once-for-all | MyGlobalAvgPool2d | false | 8,946 | [
"MIT"
] | 0 | 092b9e6184be353383396761ea5ec61d67152645 | https://github.com/AlbertiPot/once-for-all/tree/092b9e6184be353383396761ea5ec61d67152645 |
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... | Ergtou/TextWord | Multi_Head_Attention | false | 2,192 | [
"MIT"
] | 0 | f05cc5a630fc8d05357b8a9bc0da3ec5cc255a30 | https://github.com/Ergtou/TextWord/tree/f05cc5a630fc8d05357b8a9bc0da3ec5cc255a30 |
GCN | # 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.nn import Module
i... | wangzefan666/pygcn | GCN | false | 13,089 | [
"MIT"
] | 0 | 2a5e4f299e3c9d3eafe3014622e8ec3742ba365c | https://github.com/wangzefan666/pygcn/tree/2a5e4f299e3c9d3eafe3014622e8ec3742ba365c |
BCEDiceLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from typing... | abbiyanaila/torchwisdom | BCEDiceLoss | false | 6,050 | [
"MIT"
] | 1 | 56dc95ebca3f6861c7009cb4fa0c034e260236b1 | https://github.com/abbiyanaila/torchwisdom/tree/56dc95ebca3f6861c7009cb4fa0c034e260236b1 |
SimpleAbsModule | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleAbsModule(torch.nn.Module):
def __init__(self):
super(SimpleAbsModule, self).__init__()
def forward(self, a):
return torch.abs(a + a)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_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.triton_helpers import math as tl_math
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = t... | andreas-hommel/glow | SimpleAbsModule | false | 3,312 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
TinyConvNet3d | # 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... | Tomaz-Vieira/tiktorch | TinyConvNet3d | false | 18,019 | [
"MIT"
] | 8 | 2d6803c4ba5e26e4b27bf8af6638040fa4fc5628 | https://github.com/Tomaz-Vieira/tiktorch/tree/2d6803c4ba5e26e4b27bf8af6638040fa4fc5628 |
AllReduceLinear | import torch
from torch import Tensor
import torch.distributed as dist
import torch.nn as nn
from torch.nn import Linear
class ParallelModule(nn.Module):
"""Parents of all parallel layer classes"""
def __init__(self):
super().__init__()
self.mp_group = None
def allreduce(self, outputs):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.distributed as dist
import torch.nn as nn
from torch.nn import Line... | dobbytk/parallelformers | AllReduceLinear | false | 6,588 | [
"Apache-2.0"
] | 1 | a05780b1d178b4ac5100e42c2b6eec7aedc7dd33 | https://github.com/dobbytk/parallelformers/tree/a05780b1d178b4ac5100e42c2b6eec7aedc7dd33 |
TextureLoss | import torch
import torch.utils.data
import torch.nn as nn
import torch.nn.functional as F
def gram_matrix(input):
a, b, c, d = input.size()
features = input.view(a, b, c * d)
G = torch.bmm(features, torch.transpose(features, 1, 2))
return G.div(b * c * d)
class TextureLoss(nn.Module):
def __in... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
import torch.nn as nn
assert_size_stride = torch._C._dyn... | qwopqwop200/Fast-Invertible-Rescaling-Net | TextureLoss | false | 7,522 | [
"MIT"
] | 1 | 871733f2eee7929d6b37c4d1d6a27347b39b67a9 | https://github.com/qwopqwop200/Fast-Invertible-Rescaling-Net/tree/871733f2eee7929d6b37c4d1d6a27347b39b67a9 |
BeitSelfAttention | # 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.... | Clemens123/transformers | BeitSelfAttention | false | 12,775 | [
"Apache-2.0"
] | 0 | 22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 | https://github.com/Clemens123/transformers/tree/22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 |
Dice | # 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.functi... | HelenGuohx/cv-ferattn-code | Dice | false | 5,301 | [
"MIT"
] | 1 | faa9b7850fe2a0f8c08193bb129b5fec4639d616 | https://github.com/HelenGuohx/cv-ferattn-code/tree/faa9b7850fe2a0f8c08193bb129b5fec4639d616 |
CriterionAT | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
from t... | yubin1219/Semantic-Seg | CriterionAT | false | 4,641 | [
"BSD-2-Clause"
] | 0 | c40bd43d3d7e44bc995b8d041736580dec084251 | https://github.com/yubin1219/Semantic-Seg/tree/c40bd43d3d7e44bc995b8d041736580dec084251 |
FocalLoss | import torch
from torch import nn
import torch.nn.functional as F
class FocalLoss(nn.Module):
def __init__(self, alpha=0.25, gamma=2, with_logits=True, reduction:
'str'='mean'):
"""
https://github.com/mathiaszinnen/focal_loss_torch/blob/main/focal_loss/focal_loss.py
https://arxiv.... | 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... | alexander-soare/PyTorch-Custom | FocalLoss | false | 1,404 | [
"Apache-2.0"
] | 0 | f4f9865f960806f7e05d55ea259e861ee2d7c6dc | https://github.com/alexander-soare/PyTorch-Custom/tree/f4f9865f960806f7e05d55ea259e861ee2d7c6dc |
CrossEntropyLossWithAuxiliary | import torch
import torch.nn as nn
import torch.nn.parallel
from torch.optim.lr_scheduler import *
from torchvision.models import *
from torchvision.transforms import *
class CrossEntropyLossWithAuxiliary(nn.CrossEntropyLoss):
"""Cross-entropy loss that can add auxiliary loss if present."""
def forward(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
... | dani3l125/torchprune | CrossEntropyLossWithAuxiliary | false | 15,110 | [
"MIT"
] | 74 | f2589ec7514bd531ddaa7da3aed6388bb13712d3 | https://github.com/dani3l125/torchprune/tree/f2589ec7514bd531ddaa7da3aed6388bb13712d3 |
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