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 |
|---|---|---|---|---|---|---|---|---|---|---|
Backprojection | import torch
import torch.nn as nn
class Backprojection(nn.Module):
def __init__(self, batch_size, height, width):
super(Backprojection, self).__init__()
self.N, self.H, self.W = batch_size, height, width
yy, xx = torch.meshgrid([torch.arange(0.0, float(self.H)), torch.
arange... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | shlomi-amitai/monorec | Backprojection | false | 10,913 | [
"MIT"
] | 0 | 74571c6cd8d06ae4fb15cbee5a41147c54c78556 | https://github.com/shlomi-amitai/monorec/tree/74571c6cd8d06ae4fb15cbee5a41147c54c78556 |
Normalize | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | anianruoss/RIAI | Normalize | false | 3,105 | [
"MIT"
] | 0 | 2ac4ddcfb73c9678b1c4fe94fdaae82baceac4ea | https://github.com/anianruoss/RIAI/tree/2ac4ddcfb73c9678b1c4fe94fdaae82baceac4ea |
ResNetBlock | # 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.... | XiaoSanGit/talking-head-anime-landing | ResNetBlock | false | 6,004 | [
"MIT"
] | 1 | 36dbf1b8aef7357cda2a3524cb0c533f32670394 | https://github.com/XiaoSanGit/talking-head-anime-landing/tree/36dbf1b8aef7357cda2a3524cb0c533f32670394 |
NormalizeScale | # 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... | sibeiyang/sgmn | NormalizeScale | false | 16,436 | [
"MIT"
] | 130 | 00731b4f2202246d40a36d2a6727c599e6e649aa | https://github.com/sibeiyang/sgmn/tree/00731b4f2202246d40a36d2a6727c599e6e649aa |
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
from torch._inductor.select_algorithm import extern_kernels
import 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... | BruceWen120/neurips-reproducibility-challenge-2019 | Classifier | false | 8,955 | [
"Apache-2.0"
] | 0 | b0635aefe83e3f895ce0991913824e861bb7d02d | https://github.com/BruceWen120/neurips-reproducibility-challenge-2019/tree/b0635aefe83e3f895ce0991913824e861bb7d02d |
Classifier | import torch
import torch.nn.functional as F
from torch import nn
class Classifier(nn.Module):
"""
Inherits Class information from the nn.Module and creates a Classifier Class:
- Class has these attributes:
o fully connected layer with specified number of in_features and out_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.... | lukeahwilson/udacity-final-project | Classifier | false | 12,738 | [
"MIT"
] | 0 | c5df25e2135b1dfdb3458d82c562979432480f5d | https://github.com/lukeahwilson/udacity-final-project/tree/c5df25e2135b1dfdb3458d82c562979432480f5d |
FunnelClassificationHead | from _paritybench_helpers import _mock_config
import torch
from torch import nn
import torch.utils.checkpoint
class FunnelClassificationHead(nn.Module):
def __init__(self, config, n_labels):
super().__init__()
self.linear_hidden = nn.Linear(config.d_model, config.d_model)
self.dropout = n... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | Clemens123/transformers | FunnelClassificationHead | false | 11,807 | [
"Apache-2.0"
] | 0 | 22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 | https://github.com/Clemens123/transformers/tree/22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 |
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
import torch.nn as nn
import torch._utils
import torch.utils.data
import torch.utils.data... | fsImageries/video-to-pose3D | TripletLoss | false | 10,181 | [
"MIT"
] | 0 | 098c87ce19dc3331da03e6eac0b9744684eb66f6 | https://github.com/fsImageries/video-to-pose3D/tree/098c87ce19dc3331da03e6eac0b9744684eb66f6 |
LinearAverage | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
class LinearAverage(nn.Module):
def __init__(self, inputSize, outputSize, T=0.05, momentum=0.5):
super(LinearAverage, self).__init__()
self.nLem = outputSize
self.momentum = momentum
self.re... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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 as F
import torch.utils.data
as... | VisionLearningGroup/CDS | LinearAverage | false | 18,045 | [
"MIT"
] | 7 | 5b3644c286f19f76acdc03c6f6021a6f6e4ec4fc | https://github.com/VisionLearningGroup/CDS/tree/5b3644c286f19f76acdc03c6f6021a6f6e4ec4fc |
NetVLAD | import torch
import numpy as np
from sklearn.neighbors import NearestNeighbors
import torch.nn as nn
import torch.nn.functional as F
class NetVLAD(nn.Module):
"""NetVLAD layer implementation"""
def __init__(self, num_clusters=64, dim=128, normalize_input=True,
vladv2=False):
"""
Args:... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | NikV-JS/DualVPRUtil | NetVLAD | false | 8,759 | [
"MIT"
] | 31 | 6533e21641faa9156db6e8d95bb5c51cc4b7d377 | https://github.com/NikV-JS/DualVPRUtil/tree/6533e21641faa9156db6e8d95bb5c51cc4b7d377 |
ModulatedConv2d | from torch.autograd import Function
import math
import torch
import torch.utils.data
from torch.nn import functional as F
from torch.utils import data as data
import torch.nn as nn
from torch.nn import init as init
from torchvision.models import vgg as vgg
from torch import autograd as autograd
def pad(pad_type, padd... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.autograd... | achrefjarray/ESRGANplus-master | ModulatedConv2d | false | 1,374 | [
"Apache-2.0"
] | 0 | ba470ec5c565a6dc8b48575b1e185ef6b796aec6 | https://github.com/achrefjarray/ESRGANplus-master/tree/ba470ec5c565a6dc8b48575b1e185ef6b796aec6 |
ContextGate | # 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.cuda
import torch.distributed
assert_size_str... | ESCM-summarization/ESCM-summary-evaluation | ContextGate | false | 9,121 | [
"MIT"
] | 0 | 3780b51f0ed44cbbea3f163a871d875f1e5e9393 | https://github.com/ESCM-summarization/ESCM-summary-evaluation/tree/3780b51f0ed44cbbea3f163a871d875f1e5e9393 |
Curiosity | import torch
import torch.nn as nn
import torch.nn.functional as F
class Curiosity(nn.Module):
def __init__(self, state_dim):
super(Curiosity, self).__init__()
self.l1 = nn.Linear(state_dim, 400)
self.l2 = nn.Linear(400, 300)
self.l3 = nn.Linear(300, 1)
self.sigmoid = nn.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
assert_... | VasaKiDD/TD3-deep-rl-research | Curiosity | false | 2,939 | [
"Apache-2.0"
] | 0 | f75b2f86f3b7969a82fc4b7f9ea2b62de3616217 | https://github.com/VasaKiDD/TD3-deep-rl-research/tree/f75b2f86f3b7969a82fc4b7f9ea2b62de3616217 |
MatrixConv2dMultiResblock | # 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 ... | hirayamy/nngen | MatrixConv2dMultiResblock | false | 12,504 | [
"Apache-2.0"
] | 0 | 63f72be83e4bb1a697a969fb6a14d0335ec0316f | https://github.com/hirayamy/nngen/tree/63f72be83e4bb1a697a969fb6a14d0335ec0316f |
GCN_Linear | # 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... | Eudialyte/SepGAT | GCN_Linear | false | 432 | [
"MIT"
] | 0 | 6ea77714d1b2f2f5d0857cddcc9f1f5f9c0bcf50 | https://github.com/Eudialyte/SepGAT/tree/6ea77714d1b2f2f5d0857cddcc9f1f5f9c0bcf50 |
CELossWeightedMasked | # 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
... | Guangyun-Xu/uois | CELossWeightedMasked | false | 13,741 | [
"MIT"
] | 106 | 00069af841dd3ea9a86e6e3a89c3b7222240e6e5 | https://github.com/Guangyun-Xu/uois/tree/00069af841dd3ea9a86e6e3a89c3b7222240e6e5 |
EncoderBlock | # 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... | akanametov/CycleGAN | EncoderBlock | false | 6,137 | [
"MIT"
] | 1 | a61e76134cfdda43306e326e3dbba38d8cb21163 | https://github.com/akanametov/CycleGAN/tree/a61e76134cfdda43306e326e3dbba38d8cb21163 |
DistanceWeightedMSELoss | import torch
from torch import nn
import torch.utils.data
class DistanceWeightedMSELoss(nn.Module):
"""Weighted MSE loss for signed euclidean distance transform targets.
By setting ``fg_weight`` to a high value, the errors in foreground
regions are more strongly penalized.
If ``fg_weight=1``, this lo... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards... | ELEKTRONN/elektronn3 | DistanceWeightedMSELoss | false | 13,604 | [
"MIT"
] | 124 | 19c751855dffc67b744cd43e757aa4a5bd577d9b | https://github.com/ELEKTRONN/elektronn3/tree/19c751855dffc67b744cd43e757aa4a5bd577d9b |
FactorizedSynthesizerDense | # 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.... | leaderj1001/Synthesizer-Rethinking-Self-Attention-Transformer-Models | FactorizedSynthesizerDense | false | 15,878 | [
"MIT"
] | 58 | 3ee5829438a8f9c063ae485e77c9ce7649d24139 | https://github.com/leaderj1001/Synthesizer-Rethinking-Self-Attention-Transformer-Models/tree/3ee5829438a8f9c063ae485e77c9ce7649d24139 |
AdjustSigmoid | # 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 torch.nn import Module
from torch import Tensor
from typing import O... | YanivHollander/kornia | AdjustSigmoid | false | 14,628 | [
"ECL-2.0",
"Apache-2.0"
] | 418 | ccd258d0956da89b1feca96448eff8e4969d405a | https://github.com/YanivHollander/kornia/tree/ccd258d0956da89b1feca96448eff8e4969d405a |
gMLPBlock | # 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 ... | nima1999nikkhah/gMLP | gMLPBlock | false | 12,835 | [
"MIT"
] | 0 | 6e04a173bdb137680695fe55753d8b2284f03fa4 | https://github.com/nima1999nikkhah/gMLP/tree/6e04a173bdb137680695fe55753d8b2284f03fa4 |
FPNOutput | import torch
import torch.nn as nn
class ConvBNReLU(nn.Module):
def __init__(self, in_chan, out_chan, ks=1, stride=1, padding=0,
norm_layer=None, bias=True, *args, **kwargs):
super(ConvBNReLU, self).__init__()
self.conv = nn.Conv2d(in_chan, out_chan, kernel_size=ks, stride=
st... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | MarcosPampuch/TDNet_CARLA | FPNOutput | false | 808 | [
"MIT"
] | 0 | efc1c872966f1cef49b82723170586a6abcfb524 | https://github.com/MarcosPampuch/TDNet_CARLA/tree/efc1c872966f1cef49b82723170586a6abcfb524 |
Model | import torch
from torch import nn
import torch.nn.functional as F
class Model(nn.Module):
def __init__(self, input, hidden, output):
super(Model, self).__init__()
self.l1 = nn.Linear(input, hidden)
self.l2 = nn.Linear(hidden, hidden)
self.l3 = nn.Linear(hidden, 2)
def forward... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | akapoorx00/machinelearning-stuff | Model | false | 3,060 | [
"Apache-2.0"
] | 0 | 53184019b77d3387fd15b13d3bfa75529b8ed003 | https://github.com/akapoorx00/machinelearning-stuff/tree/53184019b77d3387fd15b13d3bfa75529b8ed003 |
UnaryBlock | import torch
import torch.utils.data
import torch.nn as nn
from torch.nn.parameter import Parameter
class BatchNormBlock(nn.Module):
def __init__(self, in_dim, use_bn, bn_momentum):
"""
Initialize a batch normalization block. If network does not use batch normalization, replace with biases.
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.... | wuxingzhe/OverPredactor | UnaryBlock | false | 11,036 | [
"MIT"
] | 0 | 3a0965f4c3fc84ec0dcba555ec7c460f265d9143 | https://github.com/wuxingzhe/OverPredactor/tree/3a0965f4c3fc84ec0dcba555ec7c460f265d9143 |
SourceContextGate | # 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 ... | PiescesHusky/OpenNMT-py | SourceContextGate | false | 11,782 | [
"MIT"
] | 0 | 7276cf94f989c50b3169742f64e64142897d1ec0 | https://github.com/PiescesHusky/OpenNMT-py/tree/7276cf94f989c50b3169742f64e64142897d1ec0 |
GELU | import torch
import numpy as np
from torch import nn
import torch.nn.functional as F
class GELU(nn.Module):
def __init__(self):
super(GELU, self).__init__()
def forward(self, x):
return 0.5 * x * (1 + F.tanh(np.sqrt(2 / np.pi) * (x + 0.044715 *
torch.pow(x, 3))))
def get_inputs... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | bubbliiiing/classification-pytorch | GELU | false | 14,973 | [
"MIT"
] | 88 | ee62c05bd3094c3fab48bada5a57cb2ed8b61c11 | https://github.com/bubbliiiing/classification-pytorch/tree/ee62c05bd3094c3fab48bada5a57cb2ed8b61c11 |
ConvLayer | import torch
class ConvLayer(torch.nn.Module):
"""
A small wrapper around nn.Conv2d, so as to make the code cleaner and allow for experimentation with padding
"""
def __init__(self, in_channels, out_channels, kernel_size, stride):
super().__init__()
self.conv2d = torch.nn.Conv2d(i... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_s... | gordicaleksa/pytorch-nst-feedforward | ConvLayer | false | 15,455 | [
"MIT"
] | 50 | 00c96e8e3f1b0b7fb4c14254fd0c6f1281a29598 | https://github.com/gordicaleksa/pytorch-nst-feedforward/tree/00c96e8e3f1b0b7fb4c14254fd0c6f1281a29598 |
DQN_RAM | # 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_... | yepw/DQN-Atari | DQN_RAM | false | 10,988 | [
"MIT"
] | 0 | 4ea9f687cbfdbc25a241e9b8f26b86d56291278b | https://github.com/yepw/DQN-Atari/tree/4ea9f687cbfdbc25a241e9b8f26b86d56291278b |
KnowledgeDistillationLoss | # 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
... | fcdl94/ModelingTheBackground | KnowledgeDistillationLoss | false | 15,342 | [
"MIT"
] | 105 | 1c589833ce5c1a7446469d4602ceab2cdeac1b0e | https://github.com/fcdl94/ModelingTheBackground/tree/1c589833ce5c1a7446469d4602ceab2cdeac1b0e |
VisErrorLossV3 | import torch
import torch.nn.functional as F
from torch import nn
class VisErrorLossV3(nn.Module):
def __init__(self):
super(VisErrorLossV3, self).__init__()
def compute_l1_weighted_loss(self, hm_targets, hm_preds, vismap, ohem=1.0):
"""
:param hm_targets: [batch size, keypoint numbe... | 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... | gathierry/FashionAI-KeyPointsDetectionOfApparel | VisErrorLossV3 | false | 15,434 | [
"Apache-2.0"
] | 174 | 2e0942b42b4a9cd974cdddc151675738dc8a8cb4 | https://github.com/gathierry/FashionAI-KeyPointsDetectionOfApparel/tree/2e0942b42b4a9cd974cdddc151675738dc8a8cb4 |
LabelSmoothingBCE | # 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... | kayburns/craftassist | LabelSmoothingBCE | false | 3,810 | [
"MIT"
] | 0 | 07909493d320afc2c9ff428d0891bc3acd4dc68f | https://github.com/kayburns/craftassist/tree/07909493d320afc2c9ff428d0891bc3acd4dc68f |
MultiLayerPerceptron | # 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.... | Oreoluwa1234/NeMo | MultiLayerPerceptron | false | 9,715 | [
"Apache-2.0"
] | 0 | b01e3ceed34efe31fd43866685dbdd19a6b30928 | https://github.com/Oreoluwa1234/NeMo/tree/b01e3ceed34efe31fd43866685dbdd19a6b30928 |
ResidualBlock | import math
import torch
import torch.nn as nn
class ConvNorm(nn.Module):
""" 1D Convolution """
def __init__(self, in_channels, out_channels, kernel_size=1, stride=1,
padding=None, dilation=1, bias=True, w_init_gain='linear'):
super(ConvNorm, self).__init__()
if padding is None:
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | keonlee9420/DiffSinger | ResidualBlock | false | 15,828 | [
"MIT"
] | 95 | 2bfcae4a78068c2061eae64ee675959a077aa54b | https://github.com/keonlee9420/DiffSinger/tree/2bfcae4a78068c2061eae64ee675959a077aa54b |
CEL | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | lartpang/MINet | CEL | false | 15,871 | [
"MIT"
] | 202 | 0f4ecf70010af83b432bebc614af90d86a4a6564 | https://github.com/lartpang/MINet/tree/0f4ecf70010af83b432bebc614af90d86a4a6564 |
MLPComposition | # 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.par... | XeniaOhmer/SystematicRepresentations | MLPComposition | false | 1,242 | [
"MIT"
] | 0 | 825208d1be659dc820e61f577cdb53afc47302f4 | https://github.com/XeniaOhmer/SystematicRepresentations/tree/825208d1be659dc820e61f577cdb53afc47302f4 |
AttentionGRUCell | # 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 ... | kirubarajan/Dynamic-Memory-Network-Plus | AttentionGRUCell | false | 12,684 | [
"Apache-2.0"
] | 0 | 0613287ef5a959c7b260afcea2c31afcfb0ea189 | https://github.com/kirubarajan/Dynamic-Memory-Network-Plus/tree/0613287ef5a959c7b260afcea2c31afcfb0ea189 |
GradScale | # 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 as t
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dyn... | HumberMe/lsq-net | GradScale | false | 565 | [
"MIT"
] | 0 | 7dcd75bff4aa7ff2d9c8a7902198fe411a38eb4c | https://github.com/HumberMe/lsq-net/tree/7dcd75bff4aa7ff2d9c8a7902198fe411a38eb4c |
Attn | import torch
import torch.nn as nn
import torch.nn.functional as F
class Attn(nn.Module):
def __init__(self, hidden_size):
super().__init__()
self.hidden_size = hidden_size
def forward(self, hidden, encoder_output):
attn_energies = torch.sum(hidden * encoder_output, dim=2)
at... | 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
... | RedisAI/redisai-examples | Attn | false | 14,288 | [
"MIT"
] | 51 | c85c755781d4c45443aee0d7d52c306bfda87121 | https://github.com/RedisAI/redisai-examples/tree/c85c755781d4c45443aee0d7d52c306bfda87121 |
MatrixTree | # 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
import torch.cuda
import torch.distributed
assert_s... | DenDen047/data2text-macro-plan-py | MatrixTree | false | 7,981 | [
"MIT"
] | 20 | bb01ec6e23dab28c1e969f23bd55776b597fb995 | https://github.com/DenDen047/data2text-macro-plan-py/tree/bb01ec6e23dab28c1e969f23bd55776b597fb995 |
SiQU | # 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... | Open-Catalyst-Project/baselines | SiQU | false | 17,800 | [
"MIT"
] | 10 | 89948582edfb8debb736406d54db9813a5f2c88d | https://github.com/Open-Catalyst-Project/baselines/tree/89948582edfb8debb736406d54db9813a5f2c88d |
Policy | import torch
import torch.nn as nn
import torch.nn.functional as F
class Policy(nn.Module):
def __init__(self, state_size, action_size):
super(Policy, self).__init__()
self.state_size = state_size
self.action_size = action_size
self.fc1 = nn.Linear(state_size, 125)
self.fc... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Brandon-Rozek/EvolutionaryAlgo | Policy | false | 8,886 | [
"MIT"
] | 0 | 9652327bd5aa7791dc7f2aa5b3e680f9df05638d | https://github.com/Brandon-Rozek/EvolutionaryAlgo/tree/9652327bd5aa7791dc7f2aa5b3e680f9df05638d |
CNNCifar | from _paritybench_helpers import _mock_config
import torch
from torch import nn
import torch.nn.functional as F
class CNNCifar(nn.Module):
def __init__(self, args):
super(CNNCifar, self).__init__()
self.conv1 = nn.Conv2d(3, 6, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ataML/Federated-Learning-PyTorch | CNNCifar | false | 12,133 | [
"MIT"
] | 0 | 1c28f3e4a2ce2fd4e56d249e358a69408f76e34b | https://github.com/ataML/Federated-Learning-PyTorch/tree/1c28f3e4a2ce2fd4e56d249e358a69408f76e34b |
GlobalAveragePooling2d | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | IljaManakov/Autoencoders | GlobalAveragePooling2d | false | 17,425 | [
"MIT"
] | 4 | bd2ccc6decda37a004cc57a41dcd406752c21d61 | https://github.com/IljaManakov/Autoencoders/tree/bd2ccc6decda37a004cc57a41dcd406752c21d61 |
ConvUpSample | # 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... | hadonga/PMF_MOD | ConvUpSample | false | 15,475 | [
"MIT"
] | 65 | 1875be9bd019a7e8a121d92831fa3cbd557e2ca1 | https://github.com/hadonga/PMF_MOD/tree/1875be9bd019a7e8a121d92831fa3cbd557e2ca1 |
FusedDownsample | # 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
from math import sqrt
assert_size_stride = torch._C._dynamo... | KUMartin77/AAA738_StyleGAN_pytorch | FusedDownsample | false | 11,628 | [
"BSD-2-Clause"
] | 0 | ed0689102c922d336f53e374e8be2ab532a84ccd | https://github.com/KUMartin77/AAA738_StyleGAN_pytorch/tree/ed0689102c922d336f53e374e8be2ab532a84ccd |
JSCriterion | import torch
import torch.nn.functional as F
from torch.nn.modules.loss import _Loss
from torch.optim.lr_scheduler import *
class Criterion(_Loss):
def __init__(self, alpha=1.0, name='criterion'):
super().__init__()
"""Alpha is used to weight each loss term
"""
self.alpha = alpha
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch.... | anlewy/mt-dnn | JSCriterion | false | 14,869 | [
"MIT"
] | 2,075 | eeb6f01ce0630e61a52b8c9c6f7537cd34978e45 | https://github.com/anlewy/mt-dnn/tree/eeb6f01ce0630e61a52b8c9c6f7537cd34978e45 |
SamePaddingConv1d | # 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... | Yotsuyubi/drumgan | SamePaddingConv1d | false | 2,984 | [
"MIT"
] | 0 | eb6a9aa8b5c0d64bad65e4dbd14d444b7a859a29 | https://github.com/Yotsuyubi/drumgan/tree/eb6a9aa8b5c0d64bad65e4dbd14d444b7a859a29 |
D_DownBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
from torchvision.transforms import *
assert_size_stride ... | RyanMoussouni/iSeeBetter | D_DownBlock | false | 14,358 | [
"MIT"
] | 327 | af193ae0852f8e477fcd6875dce874eb5092a24a | https://github.com/RyanMoussouni/iSeeBetter/tree/af193ae0852f8e477fcd6875dce874eb5092a24a |
ConvDownsample | # 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... | Jack-Hu-2001/UniverseNet | ConvDownsample | false | 13,862 | [
"Apache-2.0"
] | 314 | 03e7b8442286f951c65fe730ec86b9441005ac1b | https://github.com/Jack-Hu-2001/UniverseNet/tree/03e7b8442286f951c65fe730ec86b9441005ac1b |
EncoderLayer | # 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.... | msank00/miniTransformer | EncoderLayer | false | 12,826 | [
"MIT"
] | 0 | a264f30982d9e2dbf8c796d495f7a237c0dd53ef | https://github.com/msank00/miniTransformer/tree/a264f30982d9e2dbf8c796d495f7a237c0dd53ef |
Attention | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class Attention(nn.Module):
def __init__(self, embed_dim, hidden_dim=None, out_dim=None, n_head=1,
score_function='dot_product', dropout=0):
""" Attention Mechanism
:param embed_dim:
:param hidden_dim:
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | filkar/CASTLE | Attention | false | 3,502 | [
"MIT"
] | 0 | 128b316d24503875bcc298301c17b003e6d4599d | https://github.com/filkar/CASTLE/tree/128b316d24503875bcc298301c17b003e6d4599d |
ParsingRelationLoss | # 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.modules
import torch.nn as nn
assert_size_stride = torch.... | daveMcelf/Ultra-Fast-Lane-Detection | ParsingRelationLoss | false | 10,001 | [
"MIT"
] | 0 | 357f1f0f4538a125e9a9c1509e5f72ce2321f078 | https://github.com/daveMcelf/Ultra-Fast-Lane-Detection/tree/357f1f0f4538a125e9a9c1509e5f72ce2321f078 |
TwoWordBilinearLabelProbe | # 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.dataloader
assert_size_stride = to... | TimO96/NLP2 | TwoWordBilinearLabelProbe | false | 1,142 | [
"MIT"
] | 0 | 83f65a385457f68397c641f38b53df0110282578 | https://github.com/TimO96/NLP2/tree/83f65a385457f68397c641f38b53df0110282578 |
TorchSub | # 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 | TorchSub | false | 18,433 | [
"MIT"
] | 2 | 03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 | https://github.com/Akababa/torch2trt/tree/03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 |
mIoULoss | # 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
... | ozcell/ENet-SAD_Pytorch | mIoULoss | false | 16,216 | [
"MIT"
] | 53 | aaa79b5e96316e1bf24d3c2147ee622d4f17bc24 | https://github.com/ozcell/ENet-SAD_Pytorch/tree/aaa79b5e96316e1bf24d3c2147ee622d4f17bc24 |
BertSelfAttention | from _paritybench_helpers import _mock_config
import math
import torch
from torch import nn
class BertSelfAttention(nn.Module):
def __init__(self, config):
super(BertSelfAttention, self).__init__()
if config.hidden_size % config.num_attention_heads != 0:
raise ValueError(
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Albert-Ma/bert-fine-tuned-gain | BertSelfAttention | false | 18,451 | [
"Apache-2.0"
] | 2 | f752c1182f1c800f5f56998e13fd6115929df655 | https://github.com/Albert-Ma/bert-fine-tuned-gain/tree/f752c1182f1c800f5f56998e13fd6115929df655 |
ModelNet | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.init import kaiming_uniform_
import torch.utils.data
def weight_init(m):
if m.__class__.__name__ == 'Linear':
m.weight.data.copy_(kaiming_uniform_(m.weight.data))
m.bias.data.fill_(0)
class ModelNet(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
import torch.nn as nn
from to... | KtechB/machina | ModelNet | false | 2,470 | [
"MIT"
] | 0 | 24eca9cc9b89a0e0b9e026282f17c7b9fe2869ab | https://github.com/KtechB/machina/tree/24eca9cc9b89a0e0b9e026282f17c7b9fe2869ab |
Shifted_softplus | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torch.nn as nn
import torch.nn.parallel
assert_size_str... | JoseAntonioSiguenza/deepchem | Shifted_softplus | false | 9,212 | [
"MIT"
] | 0 | 05fe1b186ec154e18de9aa1b110e9258dc484e21 | https://github.com/JoseAntonioSiguenza/deepchem/tree/05fe1b186ec154e18de9aa1b110e9258dc484e21 |
SCConv_Layer | import torch
import torch.nn as nn
import torch.nn.functional as F
class SCConv_Layer(nn.Module):
def __init__(self, num_node_feats, num_edge_feats, num_triangle_feats,
output_size, bias=True, f=F.relu):
super().__init__()
self.n2n_weights = nn.Linear(num_node_feats, output_size, bias=bia... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | ggoh29/Simplicial-neural-network-benchmark | SCConv_Layer | false | 6,768 | [
"MIT"
] | 1 | 9a12bcd054251790d85e3971f5473dcffaa5664b | https://github.com/ggoh29/Simplicial-neural-network-benchmark/tree/9a12bcd054251790d85e3971f5473dcffaa5664b |
McDalNetLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
def discrepancy_slice_wasserstein(p1, p2):
s = p1.shape
if s[1] > 1:
proj = torch.randn(s[1], 128)
proj *= torch.rsqrt(torch.sum(torch.mul(proj, proj), 0, keepdim=True))
p1 = torch.matmul(p1, proj)
p2 = torch.ma... | 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
... | YBZh/MultiClassDA | McDalNetLoss | false | 14,615 | [
"MIT"
] | 53 | b0f61a5fe82f8b5414a14e8d77753fbf5d4bcb93 | https://github.com/YBZh/MultiClassDA/tree/b0f61a5fe82f8b5414a14e8d77753fbf5d4bcb93 |
Sub | import torch
class Sub(torch.nn.Module):
def __init__(self):
super(Sub, self).__init__()
def forward(self, x, y):
return x - y
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | Ilyabasharov/torch2trt | Sub | false | 2,546 | [
"MIT"
] | 0 | 76bf298b3da408509665e23e2494922b131afb10 | https://github.com/Ilyabasharov/torch2trt/tree/76bf298b3da408509665e23e2494922b131afb10 |
cnn_layer | # 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 ... | db-bionlp/CLNER | cnn_layer | false | 15,160 | [
"MIT"
] | 46 | 77910311acf0411252b9fea8c3e6efb7175eb21f | https://github.com/db-bionlp/CLNER/tree/77910311acf0411252b9fea8c3e6efb7175eb21f |
BalancedL1Loss | # 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 numpy as np
imp... | Xiangzhaohong/LidarNet | BalancedL1Loss | false | 5,988 | [
"Apache-2.0"
] | 1 | 42d025a7b629e387c9b9b01ead3558a8da81a3b0 | https://github.com/Xiangzhaohong/LidarNet/tree/42d025a7b629e387c9b9b01ead3558a8da81a3b0 |
LocallyConnected | import math
import torch
from torch import nn
class LocallyConnected(nn.Module):
"""
Local linear layer, i.e. Conv1dLocal() with filter size 1.
"""
def __init__(self, num_linear: 'int', input_features: 'int',
output_features: 'int', bias: 'bool'=True):
"""
Create local linear ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.as... | Rishab26/causalnex | LocallyConnected | false | 14,312 | [
"Apache-2.0"
] | 1,523 | 127d9324a3d68c1795299c7522f22cdea880f344 | https://github.com/Rishab26/causalnex/tree/127d9324a3d68c1795299c7522f22cdea880f344 |
LabelSmoothingCrossEntropy | # 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 ... | dumpmemory/Pytorch-NLU | LabelSmoothingCrossEntropy | false | 15,252 | [
"Apache-2.0"
] | 115 | 864fb9acc7751fc51abd3d05d24b5a9a7eab7110 | https://github.com/dumpmemory/Pytorch-NLU/tree/864fb9acc7751fc51abd3d05d24b5a9a7eab7110 |
RingLoss | # 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_... | linkserendipity/AlignedReID | RingLoss | false | 3,912 | [
"MIT"
] | 0 | 142a9ebdc200ef4da001f91c1f592e4ff02b2f77 | https://github.com/linkserendipity/AlignedReID/tree/142a9ebdc200ef4da001f91c1f592e4ff02b2f77 |
DiceLoss | import torch
import torch.nn as nn
class DiceLoss(nn.Module):
def __init__(self):
super(DiceLoss, self).__init__()
def forward(self, pred, target):
"""Cacluate dice loss
Parameters
----------
pred:
predictions from the model
targe... | 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... | MarouaJaoua/cells-nuclei-segmentation | DiceLoss | false | 9,349 | [
"MIT"
] | 0 | 09d65db104a7297ec6f4c975b668bb7ca93c7372 | https://github.com/MarouaJaoua/cells-nuclei-segmentation/tree/09d65db104a7297ec6f4c975b668bb7ca93c7372 |
Net | import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
def __init__(self, num_classes=8):
super(Net, self).__init__()
self.conv1 = nn.Conv2d(3, 10, kernel_size=(3, 3))
self.conv2 = nn.Conv2d(10, 20, kernel_size=(3, 3))
nn.init.xavier_uniform_(self... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | chapnitsky/DL | Net | false | 1,694 | [
"MIT"
] | 0 | a91e6abd7abc81261ba6797de9a2c6f95b4dcb71 | https://github.com/chapnitsky/DL/tree/a91e6abd7abc81261ba6797de9a2c6f95b4dcb71 |
GCT | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.utils.data.distributed
assert_size_stride = ... | Erfun76/insightface | GCT | false | 9,275 | [
"MIT"
] | 0 | 148cef36a43a055f68d2b6a475f4aa38625ad8b4 | https://github.com/Erfun76/insightface/tree/148cef36a43a055f68d2b6a475f4aa38625ad8b4 |
Normalize | # 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... | CiscoDevNet/vo-id | Normalize | false | 17,092 | [
"MIT"
] | 7 | 9a01f866c7539a9cd095d9627ba4f65ad540ea6b | https://github.com/CiscoDevNet/vo-id/tree/9a01f866c7539a9cd095d9627ba4f65ad540ea6b |
MatrixAttention | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guar... | immrz/qagnn | MatrixAttention | false | 3,739 | [
"MIT"
] | 0 | 0e695c6fcbefcf25da25c056c0bea1940b3e0f2b | https://github.com/immrz/qagnn/tree/0e695c6fcbefcf25da25c056c0bea1940b3e0f2b |
ImageNetNormalizer | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.autograd
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dy... | cassidylaidlaw/perceptual-advex | ImageNetNormalizer | false | 15,009 | [
"MIT"
] | 45 | d39136eb5b5e950442456ddade6b4f4fba3dd8f6 | https://github.com/cassidylaidlaw/perceptual-advex/tree/d39136eb5b5e950442456ddade6b4f4fba3dd8f6 |
CBR | import torch
import torch.nn as nn
class CBR(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size):
super(CBR, self).__init__()
self.cnn = nn.Conv2d(in_channels, out_channels, kernel_size, stride
=2, padding=2)
self.relu = nn.ReLU()
def forward(self, x):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | adamkrekorian/CI-UNet | CBR | false | 1,370 | [
"MIT"
] | 0 | fab0f8806540f5d79911bd81ba54dff135f9814f | https://github.com/adamkrekorian/CI-UNet/tree/fab0f8806540f5d79911bd81ba54dff135f9814f |
CausalConv2d | import torch
from torch import nn
class WNConv2d(nn.Module):
def __init__(self, in_channel, out_channel, kernel_size, stride=1,
padding=0, bias=True, activation=None):
super().__init__()
self.conv = nn.utils.weight_norm(nn.Conv2d(in_channel, out_channel,
kernel_size, stride=st... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | eric11220/vq-vae-2-pytorch | CausalConv2d | false | 12,368 | [
"MIT"
] | 0 | ac455ec8873428e16a361d49bf1dda30472ece13 | https://github.com/eric11220/vq-vae-2-pytorch/tree/ac455ec8873428e16a361d49bf1dda30472ece13 |
EqualLinear | # 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
from math import sqrt
assert_size_stride = torch._C._dynamo... | KUMartin77/AAA738_StyleGAN_pytorch | EqualLinear | false | 11,606 | [
"BSD-2-Clause"
] | 0 | ed0689102c922d336f53e374e8be2ab532a84ccd | https://github.com/KUMartin77/AAA738_StyleGAN_pytorch/tree/ed0689102c922d336f53e374e8be2ab532a84ccd |
BiaffineScorer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | NLPInBLCU/BiaffineDependencyParsing | BiaffineScorer | false | 14,074 | [
"MIT"
] | 67 | 40b133648c747957dacd59916add0403371fe680 | https://github.com/NLPInBLCU/BiaffineDependencyParsing/tree/40b133648c747957dacd59916add0403371fe680 |
ConConv | # 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... | karoly-hars/DE_hybrid_CNN | ConConv | false | 12,659 | [
"BSD-3-Clause"
] | 0 | d74ba4291d6db335151d5262ab96e8e3806a7587 | https://github.com/karoly-hars/DE_hybrid_CNN/tree/d74ba4291d6db335151d5262ab96e8e3806a7587 |
MonotonicMin | import torch
import torch.nn as nn
class MonotonicMin(nn.Module):
def __init__(self):
super().__init__()
def forward(self, x):
return torch.min(x, dim=1)[0].unsqueeze(1)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | tiwalayo/monotonic-mlp | MonotonicMin | false | 10,858 | [
"MIT"
] | 0 | 2f519797a753f7f297fac1365125c6da79f7b890 | https://github.com/tiwalayo/monotonic-mlp/tree/2f519797a753f7f297fac1365125c6da79f7b890 |
IoU | import torch
import torch.nn as nn
class IoU(nn.Module):
def __init__(self, mode='iou', axis=1, eps=0.0):
""" Return a matrix of [batch * num_classes].
Note: In order to separate from iou=0, function WILL return NaN if both
y_true and y_pred are 0. Need further treatment to remo... | 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... | sdw95927/deconvGAN | IoU | false | 12,956 | [
"MIT"
] | 0 | 49dbbfe4827ed8366242870877165482d4ec1e75 | https://github.com/sdw95927/deconvGAN/tree/49dbbfe4827ed8366242870877165482d4ec1e75 |
HeatmapLoss | # 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.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_... | NiranthS/pytorch_stacked_hourglass | HeatmapLoss | false | 904 | [
"BSD-3-Clause"
] | 0 | db9838eb13f6848ba3b9db844c1e023eb8688c3c | https://github.com/NiranthS/pytorch_stacked_hourglass/tree/db9838eb13f6848ba3b9db844c1e023eb8688c3c |
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_... | PacktPublishing/Hands-On-Computer-Vision-with-PyTorch-1.x | Net | false | 17,781 | [
"MIT"
] | 6 | bad073f7489792d3c4bc860a2d56fa133ba63617 | https://github.com/PacktPublishing/Hands-On-Computer-Vision-with-PyTorch-1.x/tree/bad073f7489792d3c4bc860a2d56fa133ba63617 |
WingLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import math
import torch.onnx
from torch.nn.modules.loss import _Loss
ass... | xuguozhi/Peppa-Facial-Landmark-PyTorch | WingLoss | false | 16,747 | [
"Apache-2.0"
] | 163 | 238063317fd31c4c21c5c43692e6a5d769970370 | https://github.com/xuguozhi/Peppa-Facial-Landmark-PyTorch/tree/238063317fd31c4c21c5c43692e6a5d769970370 |
VarifocalLoss | # 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... | NEUdeep/TileDetection | VarifocalLoss | false | 8,645 | [
"Apache-2.0"
] | 41 | f453ac868de195a7859b9bf07c813e46eb35d2d0 | https://github.com/NEUdeep/TileDetection/tree/f453ac868de195a7859b9bf07c813e46eb35d2d0 |
DeepHeadModule | import torch
import torch.nn as nn
import torch.nn.functional as F
class DeepHeadModule(nn.Module):
def __init__(self, input_channels, output_channels):
super(DeepHeadModule, self).__init__()
self._input_channels = input_channels
self._output_channels = output_channels
self._mid_c... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | DannyDannyDanny/DeepPrivacy | DeepHeadModule | false | 2,132 | [
"MIT"
] | 0 | 749e260bdcc28a0c12d526f24e4f5315d1b447ad | https://github.com/DannyDannyDanny/DeepPrivacy/tree/749e260bdcc28a0c12d526f24e4f5315d1b447ad |
SkipModule | import torch
import torch.nn
class SkipModule(torch.nn.Module):
def __init__(self, in_features, out_features, activation=torch.nn.ReLU()):
super(SkipModule, self).__init__()
self.linear1 = torch.nn.Linear(in_features, out_features, activation)
self.linear2 = torch.nn.Linear(out_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
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
... | ashwinpn/Computer-Vision | SkipModule | false | 6,261 | [
"MIT"
] | 1 | 9dc3abfe416385171b76e2bad6872e10f36a12b4 | https://github.com/ashwinpn/Computer-Vision/tree/9dc3abfe416385171b76e2bad6872e10f36a12b4 |
Net | import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
self.conv1 = nn.Conv2d(64, 64, 3, stride=1, padding=1)
self.fc1 = nn.Linear(65536, 10)
self.maxpool = nn.AdaptiveMaxPool2d(32)
def forward(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | surya00060/tvm | Net | false | 10,814 | [
"Zlib",
"Unlicense",
"Apache-2.0",
"BSD-2-Clause",
"MIT",
"ECL-2.0"
] | 0 | fd4601514aee1ecf080b74578849c60438f55b0c | https://github.com/surya00060/tvm/tree/fd4601514aee1ecf080b74578849c60438f55b0c |
RMSELoss | import torch
import torch as th
import torch.nn as nn
class RMSELoss(nn.Module):
def __init__(self, reduction='mean', eps=1e-06):
super().__init__()
self.mse = nn.MSELoss(reduction=reduction)
self.eps = eps
def forward(self, yhat, y):
loss = th.sqrt(self.mse(yhat, y) + self.e... | 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... | bio-ontology-research-group/OntoML | RMSELoss | false | 1,546 | [
"BSD-3-Clause"
] | 0 | 4cdc17dc7ee26464db96c67838c3e77dba5318f9 | https://github.com/bio-ontology-research-group/OntoML/tree/4cdc17dc7ee26464db96c67838c3e77dba5318f9 |
LBM | # 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
assert_size_stride = torch._C._dynamo.guards.assert... | QingkaiZeng/GenTaxo | LBM | false | 8,718 | [
"MIT"
] | 28 | 10257a1714d14c6a4c49cbfa0b507408f718cdf0 | https://github.com/QingkaiZeng/GenTaxo/tree/10257a1714d14c6a4c49cbfa0b507408f718cdf0 |
LxmertSelfAttentionLayer | from _paritybench_helpers import _mock_config
import math
import torch
from torch import nn
class LxmertAttention(nn.Module):
def __init__(self, config, ctx_dim=None):
super().__init__()
if config.hidden_size % config.num_attention_heads != 0:
raise ValueError(
'The hi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | rsgit95/med_kg_txt_multimodal | LxmertSelfAttentionLayer | false | 4,223 | [
"Apache-2.0"
] | 0 | 80355b0cf58e0571531ad6f9728c533110ca996d | https://github.com/rsgit95/med_kg_txt_multimodal/tree/80355b0cf58e0571531ad6f9728c533110ca996d |
Div | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | yifanpu001/PytorchToCaffe | Div | false | 4,707 | [
"MIT"
] | 0 | 37c1ebfc3547e93b1c174721036d03c831c60e48 | https://github.com/yifanpu001/PytorchToCaffe/tree/37c1ebfc3547e93b1c174721036d03c831c60e48 |
AvgPoolPad | import torch
import torch.utils.data
import torch.nn as nn
import torch.backends.cudnn
class AvgPoolPad(nn.Module):
def __init__(self, stride=2, padding=1):
super(AvgPoolPad, self).__init__()
self.pad = nn.ZeroPad2d((1, 0, 1, 0))
self.pool = nn.AvgPool2d(3, stride=stride, padding=padding,... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
import torch.nn as nn
import torch.backends.cudnn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
em... | CalebEverett/fastai-dl2 | AvgPoolPad | false | 17,140 | [
"Apache-2.0"
] | 4 | 64d23592eddca6ca1f3647e73c319e97c8eb392b | https://github.com/CalebEverett/fastai-dl2/tree/64d23592eddca6ca1f3647e73c319e97c8eb392b |
Pooling | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | Jack-Hu-2001/UniverseNet | Pooling | false | 13,863 | [
"Apache-2.0"
] | 314 | 03e7b8442286f951c65fe730ec86b9441005ac1b | https://github.com/Jack-Hu-2001/UniverseNet/tree/03e7b8442286f951c65fe730ec86b9441005ac1b |
SimpleMulModule | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleMulModule(torch.nn.Module):
def __init__(self):
super(SimpleMulModule, self).__init__()
def forward(self, left, right):
other = left.mul(right.item() if right.size() == torch.Size([]) else
right)
... | 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... | briancoutinho/glow | SimpleMulModule | false | 12,588 | [
"Apache-2.0"
] | 0 | 4c919d60b3c33296c4109aec8020a1733c98f5b5 | https://github.com/briancoutinho/glow/tree/4c919d60b3c33296c4109aec8020a1733c98f5b5 |
FeatureMapPairEncoderV2 | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | KH-Kyle/rmp_nav | FeatureMapPairEncoderV2 | false | 8,761 | [
"MIT"
] | 30 | d598fe70664a4cdc0e9b9dd4b52e84aa3de1b551 | https://github.com/KH-Kyle/rmp_nav/tree/d598fe70664a4cdc0e9b9dd4b52e84aa3de1b551 |
TransitionUp | # 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.onnx
import torch.nn.parallel
assert_size_stride = tor... | Ganzooo/soil_segmentation | TransitionUp | false | 2,293 | [
"MIT"
] | 0 | 56f410e3e184f24e52dd4b542ea309f0d203ca00 | https://github.com/Ganzooo/soil_segmentation/tree/56f410e3e184f24e52dd4b542ea309f0d203ca00 |
LinearTextualHead | # 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... | funnyzhou/REFERS | LinearTextualHead | false | 15,376 | [
"MIT"
] | 46 | 392eddf13cbf3c3a7dc0bf8bfffd108ca4a65a19 | https://github.com/funnyzhou/REFERS/tree/392eddf13cbf3c3a7dc0bf8bfffd108ca4a65a19 |
GatedLinear | import torch
from torch import nn
from torch.nn import init as init
class GatedLinear(nn.Module):
def __init__(self, in_ch, out_ch):
super().__init__()
self.lin1 = nn.Linear(in_ch, out_ch)
self.lin2 = nn.Linear(in_ch, out_ch)
self.sig = nn.Sigmoid()
self.tanh = nn.Tanh()
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | BaekduChoi/Halftoning_v2 | GatedLinear | false | 2,014 | [
"BSD-3-Clause"
] | 0 | fdb7040e1a4044f23ef9c92757bbb90c23685afe | https://github.com/BaekduChoi/Halftoning_v2/tree/fdb7040e1a4044f23ef9c92757bbb90c23685afe |
Classifier | import torch
import torch.nn.functional as F
import torch.nn as nn
class Classifier(nn.Module):
def __init__(self, dims):
"""
Single hidden layer classifier
with softmax output.
"""
super(Classifier, self).__init__()
[x_dim, h_dim, y_dim] = dims
self.dense ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | NightmareNyx/semi-supervised-pytorch | Classifier | false | 2,702 | [
"MIT"
] | 0 | 43bb86bc6757345bd7a4eb37d6948ee62a268f7e | https://github.com/NightmareNyx/semi-supervised-pytorch/tree/43bb86bc6757345bd7a4eb37d6948ee62a268f7e |
Scale | import torch
import torch.nn as nn
class Scale(nn.Module):
"""
A learnable scale parameter
"""
def __init__(self, scale=1.0):
super(Scale, self).__init__()
self.scale = nn.Parameter(torch.tensor(scale, dtype=torch.float))
def forward(self, x):
return x * self.scale
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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | BUPT-PRIV/BalancedGroupSoftmax | Scale | false | 13,372 | [
"Apache-2.0"
] | 333 | 90e04fd8ccecd2bc61bbe6053a741ae708da2794 | https://github.com/BUPT-PRIV/BalancedGroupSoftmax/tree/90e04fd8ccecd2bc61bbe6053a741ae708da2794 |
Network | import torch
import torch.nn as nn
class Network(nn.Module):
def __init__(self):
super().__init__()
self.conv = nn.Conv3d(in_channels=1, out_channels=3, kernel_size=3)
def forward(self, x):
return self.conv(x)
def get_inputs():
return [torch.rand([4, 1, 64, 64, 64])]
def get_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | NunoEdgarGFlowHub/torchio | Network | false | 5,666 | [
"MIT"
] | 1 | 656e96c8863ecff0bb29bf880af054675bbb30fd | https://github.com/NunoEdgarGFlowHub/torchio/tree/656e96c8863ecff0bb29bf880af054675bbb30fd |
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