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 |
|---|---|---|---|---|---|---|---|---|---|---|
MSELoss | 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
import functools
import torch.nn as nn
import torch.nn.functional as F
assert_size_stride... | Min-Sheng/mmregression | MSELoss | false | 841 | [
"Apache-2.0"
] | 0 | 6d70383d89ccb3dea7f425b665c2a184d014a99f | https://github.com/Min-Sheng/mmregression/tree/6d70383d89ccb3dea7f425b665c2a184d014a99f |
GramMatrix | # 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 torch.nn as nn
import torch.onnx
assert_size_stride = torch._C._dynamo.gu... | adi-horowitz/final-project | GramMatrix | false | 1,377 | [
"MIT"
] | 0 | 0fd864663e92a6bcaa5f068e3e45b2a76460d335 | https://github.com/adi-horowitz/final-project/tree/0fd864663e92a6bcaa5f068e3e45b2a76460d335 |
NormalProposal | import torch
from torch import nn
from torch.distributions import Normal
class NormalProposal(nn.Module):
def __init__(self, sigma):
super(NormalProposal, self).__init__()
self.sigma = sigma
def forward(self, x):
return Normal(x, self.sigma).sample()
def get_inputs():
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
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | BrettLeroux/GRIPS-MCMC | NormalProposal | false | 168 | [
"MIT"
] | 0 | 154457acfc47977e25870aed76c7dc49d70608af | https://github.com/BrettLeroux/GRIPS-MCMC/tree/154457acfc47977e25870aed76c7dc49d70608af |
_FakeMegatronMLP | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.nn.functional as F
class _FakeMegatronMLP(nn.Module):
"""
A fake mlp without model parallelism for correctness testing
"""
def __init__(self, args, _):
super().__init__()
self.fc1 = nn.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
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | xxchenxx/fastmoe | _FakeMegatronMLP | false | 13,131 | [
"Apache-2.0"
] | 0 | f60dd0e1f9f0447e56ff265c9ede304b88d0556b | https://github.com/xxchenxx/fastmoe/tree/f60dd0e1f9f0447e56ff265c9ede304b88d0556b |
StyledConv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
from to... | YotamNitzan/pixel2style2pixel | StyledConv | false | 2,995 | [
"MIT"
] | 0 | b943f9e6de046a54b901eea1d8714cb02a71605f | https://github.com/YotamNitzan/pixel2style2pixel/tree/b943f9e6de046a54b901eea1d8714cb02a71605f |
ResBlk | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
def normalize(x, eps=1e-06):
"""Apply min-max normalization."""
x = x.contiguous()
N, C, H, W = x.size()
x_ = x.view(N * C, -1)
max_val = torch.max(x_, dim=1, keepdim=True)[0]
min_val = torch.min(x_, dim=1, keepdim=... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
assert_size_stride = torch... | fpaupier/stargan-v2 | ResBlk | false | 6,701 | [
"MIT"
] | 1 | 18d2e04ed6e6df963b84345e798d94383757aaa2 | https://github.com/fpaupier/stargan-v2/tree/18d2e04ed6e6df963b84345e798d94383757aaa2 |
MaxPool2d | import torch
import torch.nn as nn
import torch.nn.functional as F
class _SpikeMaxPoolNd(nn.Module):
def __init__(self, kernel_size, stride=None, padding=0, dilation=1,
ceil_mode=False):
super(_SpikeMaxPoolNd, self).__init__()
self.kernel_size = kernel_size
self.stride = stride or... | 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... | tomking/PySNN | MaxPool2d | false | 16,598 | [
"MIT"
] | 175 | c99ba6cd28a518dc07cab765acac9b69ac6fe36b | https://github.com/tomking/PySNN/tree/c99ba6cd28a518dc07cab765acac9b69ac6fe36b |
Linear_tanh | import torch
import torch.nn as nn
class Linear_tanh(nn.Module):
def __init__(self, dim_in, dim_out, bias=True):
super().__init__()
self.linear = nn.Linear(dim_in, dim_out, bias=bias)
self.activation = nn.Tanh()
def forward(self, x):
out = self.linear(x)
out = self.ac... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | Armand-Morin/AutoML | Linear_tanh | false | 64 | [
"MIT"
] | 0 | 189867e2c7734d9afb87a9f51fd42bd6cc527a64 | https://github.com/Armand-Morin/AutoML/tree/189867e2c7734d9afb87a9f51fd42bd6cc527a64 |
BertOutput | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class BertOutput(nn.Module):
def __init__(self, config):
super(BertOutput, self).__init__()
self.dense = nn.Linear(config.intermediate_size, config.hidden_size)
self.LayerNorm = nn.LayerNorm(config.hidden_siz... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | IsaacChanghau/ReLoCLNet | BertOutput | false | 8,783 | [
"MIT"
] | 31 | 56cb666ce516cce9acbcfce78fb4e95d81e11e54 | https://github.com/IsaacChanghau/ReLoCLNet/tree/56cb666ce516cce9acbcfce78fb4e95d81e11e54 |
AddCoords | import torch
import torch.nn as nn
class AddCoords(nn.Module):
def __init__(self, with_r=False):
super().__init__()
self.with_r = with_r
def forward(self, input_tensor):
"""
Args:
input_tensor: shape(batch, channel, x_dim, y_dim)
"""
batch_size, _,... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | NguyenTheAn/AdaptiveWingLoss | AddCoords | false | 9,362 | [
"Apache-2.0"
] | 0 | abaade9521c1382739a158f3ad5ce493948add1d | https://github.com/NguyenTheAn/AdaptiveWingLoss/tree/abaade9521c1382739a158f3ad5ce493948add1d |
NormKLLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.utils.data
import torch.nn.init
from torch.nn.modules.loss i... | ljw23/ConvLab-2 | NormKLLoss | false | 15,953 | [
"Apache-2.0"
] | 339 | 13d48ea0e441701bd66100689b6c25b561f15525 | https://github.com/ljw23/ConvLab-2/tree/13d48ea0e441701bd66100689b6c25b561f15525 |
BasicConvTestModel | # 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 torchvision import models as models
import torch.nn.pa... | aalborov/openvino_training_extensions | BasicConvTestModel | false | 6,058 | [
"Apache-2.0"
] | 1 | a0bb39424151a98e1ca80c4aa5c865636d401785 | https://github.com/aalborov/openvino_training_extensions/tree/a0bb39424151a98e1ca80c4aa5c865636d401785 |
SpatialGroupEnhance | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
from torch.nn import init
assert_size_stride = torch._C._d... | LiChengChen666/DetectDee | SpatialGroupEnhance | false | 9,809 | [
"Apache-2.0"
] | 0 | 1e6aaa0d15b1fc12d1342d8a922004e372b5f437 | https://github.com/LiChengChen666/DetectDee/tree/1e6aaa0d15b1fc12d1342d8a922004e372b5f437 |
BertAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | caldoe/BERT-NL2SPARQL | BertAttention | false | 6,386 | [
"MIT"
] | 1 | 2e09c1aeffc855bc7f1dc8c182e21153b2bc73a8 | https://github.com/caldoe/BERT-NL2SPARQL/tree/2e09c1aeffc855bc7f1dc8c182e21153b2bc73a8 |
FocalLoss | import torch
import torch.nn.functional as F
class FocalLoss(torch.nn.Module):
def __init__(self, gamma=2):
super().__init__()
self.gamma = gamma
def forward(self, input, target):
if not target.size() == input.size():
raise ValueError(
'Target size ({}) mu... | 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... | rskmoi/kaggle-imet | FocalLoss | false | 7,582 | [
"MIT"
] | 1 | 483e9e6dbae5b1d8e023e0812c4b990afca874bc | https://github.com/rskmoi/kaggle-imet/tree/483e9e6dbae5b1d8e023e0812c4b990afca874bc |
SoftAttention | import torch
import numpy as np
import torch.nn as nn
class SoftAttention(nn.Module):
"""
https://arxiv.org/abs/1803.10916
"""
def __init__(self, emb_dim, attn_dim):
super().__init__()
self.attn_dim = attn_dim
self.emb_dim = emb_dim
self.W = torch.nn.Linear(self.emb_di... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | shangeth/wavencoder | SoftAttention | false | 16,399 | [
"MIT"
] | 56 | cd1a277c2cc44075c9f4506e344b3a725ad5b9fe | https://github.com/shangeth/wavencoder/tree/cd1a277c2cc44075c9f4506e344b3a725ad5b9fe |
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 math
import ... | minjoong507/Image-Captioning-Transformer | BertPredictionHeadTransform | false | 7,239 | [
"MIT"
] | 1 | 813060f0bb656e336154173f11e99a80362c8c2a | https://github.com/minjoong507/Image-Captioning-Transformer/tree/813060f0bb656e336154173f11e99a80362c8c2a |
Hflip | # 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... | lyhyl/kornia | Hflip | false | 12,742 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 5bd3aeb0d54dedac01e6eaf8bac37779bab0bec5 | https://github.com/lyhyl/kornia/tree/5bd3aeb0d54dedac01e6eaf8bac37779bab0bec5 |
GumbelQuantize | import torch
from torch import nn
from torch import einsum
import torch.nn.functional as F
class GumbelQuantize(nn.Module):
"""
Gumbel Softmax trick quantizer
Categorical Reparameterization with Gumbel-Softmax, Jang et al. 2016
https://arxiv.org/abs/1611.01144
"""
def __init__(self, num_hidde... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | baudm/deep-vector-quantization | GumbelQuantize | false | 1,547 | [
"MIT"
] | 0 | 211bda99a6c750c1e65aff082aa865fed8677b8a | https://github.com/baudm/deep-vector-quantization/tree/211bda99a6c750c1e65aff082aa865fed8677b8a |
Hardtanh | import torch
import torch.nn as nn
class Hardtanh(nn.Module):
def __init__(self):
super(Hardtanh, self).__init__()
self.layer = nn.Hardtanh(-2, 2)
def forward(self, x):
x = self.layer(x)
return x
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 import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | yifanpu001/PytorchToCaffe | Hardtanh | false | 4,710 | [
"MIT"
] | 0 | 37c1ebfc3547e93b1c174721036d03c831c60e48 | https://github.com/yifanpu001/PytorchToCaffe/tree/37c1ebfc3547e93b1c174721036d03c831c60e48 |
AdaptiveFilterResponseNorm | import torch
import torch.nn as nn
import torch.nn.functional as func
import torch.jit
import torch.nn
class AdaptiveFilterResponseNorm(nn.Module):
def __init__(self, in_size, ada_size, eps=1e-16):
super().__init__()
self.eps = eps
self.in_size = in_size
self.scale = nn.Linear(ada... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ankmathur96/torchsupport | AdaptiveFilterResponseNorm | false | 3,168 | [
"MIT"
] | 0 | 77bf4a90b8770a408665e2604428808c3ed2f979 | https://github.com/ankmathur96/torchsupport/tree/77bf4a90b8770a408665e2604428808c3ed2f979 |
TensorClampOptionMax | import torch
class TensorClampOptionMax(torch.nn.Module):
def forward(self, x):
return x.clamp(max=0.1)
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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | ahangchen/torch2trt | TensorClampOptionMax | false | 6,116 | [
"MIT"
] | 1 | 53c663f0e0570ef7ffd6771354ae3478f63bd328 | https://github.com/ahangchen/torch2trt/tree/53c663f0e0570ef7ffd6771354ae3478f63bd328 |
AdversarialNetwork | # 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_... | caozhangjie/kinetics_i3d_pytorch | AdversarialNetwork | false | 9,917 | [
"MIT"
] | 0 | 237713bb76cf71b6d60d1a4df98f00df3a489cc3 | https://github.com/caozhangjie/kinetics_i3d_pytorch/tree/237713bb76cf71b6d60d1a4df98f00df3a489cc3 |
focal_BCELoss | import torch
import torch.nn as nn
class focal_BCELoss(nn.Module):
def __init__(self, alpha=10, gamma=2):
super(focal_BCELoss, self).__init__()
self.alpha = alpha
self.gamma = gamma
def forward(self, input, target, eps=1e-07):
input = torch.clamp(input, eps, 1 - eps)
... | 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
... | DRL-CASIA/Perception | focal_BCELoss | false | 7,925 | [
"MIT"
] | 39 | a0e7d3957267ce92a82b03ab3eca96916d22c4f2 | https://github.com/DRL-CASIA/Perception/tree/a0e7d3957267ce92a82b03ab3eca96916d22c4f2 |
SingleHiddenLayer | import torch
class SingleHiddenLayer(torch.nn.Module):
def __init__(self, input_channels, hidden_channels):
super(SingleHiddenLayer, self).__init__()
self.input_channels = input_channels
self.hidden_channels = hidden_channels
self.linear1 = torch.nn.Linear(hidden_channels, 128)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | lysuk96/rl_representations | SingleHiddenLayer | false | 15,985 | [
"MIT"
] | 438 | 19de69305e40c9b3a1d746a7af26d232c9fb3f6f | https://github.com/lysuk96/rl_representations/tree/19de69305e40c9b3a1d746a7af26d232c9fb3f6f |
RAddFloat | # 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... | NVIDIA-AI-IOT-private/torch2trt | RAddFloat | false | 10,525 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
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
from torch._inductor.runtime.... | ferodia/MichiGAN | BasicBlock | false | 15,351 | [
"MIT"
] | 235 | a49acb49f9659d7538e62faa3ed08e46afb0ddae | https://github.com/ferodia/MichiGAN/tree/a49acb49f9659d7538e62faa3ed08e46afb0ddae |
FocalLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class FocalSigmoidLossFunc(torch.autograd.Function):
"""
compute backward directly for better numeric stability
"""
@staticmethod
def forward(ctx, logits, label, alpha, gamma):
logits = logits.float()
coeff = 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 libdevice, math as tl_math
import torc... | jaredaevans/UltrafastNST | FocalLoss | false | 6,923 | [
"MIT"
] | 1 | 6671c6b618ce6bb4920b15f782be962e484a5423 | https://github.com/jaredaevans/UltrafastNST/tree/6671c6b618ce6bb4920b15f782be962e484a5423 |
MaskedInstanceNorm1d | import torch
import torch.cuda
from torch import nn
import torch.distributed
import torch.utils.data
import torch.optim
class MaskedInstanceNorm1d(nn.Module):
"""Instance norm + masking."""
MAX_CNT = 100000.0
def __init__(self, d_channel: 'int', unbiased: 'bool'=True, affine:
'bool'=False):
... | 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.cuda
from torch... | hamjam/NeMo | MaskedInstanceNorm1d | false | 15,487 | [
"Apache-2.0"
] | 4,145 | b3484d32e1317666151f931bfa39867d88ed8658 | https://github.com/hamjam/NeMo/tree/b3484d32e1317666151f931bfa39867d88ed8658 |
SuperPointNet | import torch
import torch.optim
import torch.utils.data
class SuperPointNet(torch.nn.Module):
""" Pytorch definition of SuperPoint Network. """
def __init__(self):
super(SuperPointNet, self).__init__()
self.relu = torch.nn.ReLU(inplace=True)
self.pool = torch.nn.MaxPool2d(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
from torch._inductor.runtime.... | KimSinjeong/SuperPoint_URP | SuperPointNet | false | 9,330 | [
"MIT"
] | 0 | 11e6203f6b651f1f32067e85058f8961b556f85c | https://github.com/KimSinjeong/SuperPoint_URP/tree/11e6203f6b651f1f32067e85058f8961b556f85c |
NearestNeighbourx4 | # 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_... | wsdea/EfficientSR | NearestNeighbourx4 | false | 4,548 | [
"MIT"
] | 0 | 077dea18c90e0d5bed722c609a776033c09f80e6 | https://github.com/wsdea/EfficientSR/tree/077dea18c90e0d5bed722c609a776033c09f80e6 |
Net | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import tanh
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
self.a1 = nn.Conv2d(5, 16, kernel_size=3, padding=1)
self.a2 = nn.Conv2d(16, 16, kernel_size=3, padding=1)
self.a3 = nn.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
from torch._inductor.runtime.... | srivarshan-s/Neural-Chess-2D | Net | false | 4,411 | [
"MIT"
] | 0 | 81ec7eb9b4c3c82dc7f6ba5bd4313bd6ede9994e | https://github.com/srivarshan-s/Neural-Chess-2D/tree/81ec7eb9b4c3c82dc7f6ba5bd4313bd6ede9994e |
ContentLoss | # 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... | Enigmatisms/NeuralStyle | ContentLoss | false | 5,130 | [
"Apache-2.0"
] | 1 | 27b435b5c51b41427e9f465793a0b81ad7248ab8 | https://github.com/Enigmatisms/NeuralStyle/tree/27b435b5c51b41427e9f465793a0b81ad7248ab8 |
Mish | # 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
assert_size_stride = torch._C._dynamo.gu... | absallh/A_yolov3 | Mish | false | 18,215 | [
"Apache-2.0"
] | 6 | 550ec41de42b8efe638e887c51a568189947e049 | https://github.com/absallh/A_yolov3/tree/550ec41de42b8efe638e887c51a568189947e049 |
TestNet | import torch
import torch.nn as nn
class ScaleLayer(nn.Module):
def __init__(self, init_value=0.001):
super().__init__()
self.scale = nn.Parameter(torch.FloatTensor([init_value]))
def forward(self, input):
return input * self.scale
class TestNet(nn.Module):
def __init__(self):... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | dizzyvn/torch-tcav | TestNet | false | 1,846 | [
"Apache-2.0"
] | 0 | c9795e817d1104923ef7422f5575607e6b835abc | https://github.com/dizzyvn/torch-tcav/tree/c9795e817d1104923ef7422f5575607e6b835abc |
AngleMultipleLinear | import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Parameter
def normalize(x, dim, p=2, eps=1e-12):
if torch.onnx.is_in_onnx_export():
return OnnxLpNormalization.apply(x, dim, p, eps)
else:
return F.normalize(x, dim=dim)
class OnnxLpNor... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | sovrasov/mmaction2 | AngleMultipleLinear | false | 4,432 | [
"Apache-2.0"
] | 0 | 055625bf6d6e06e9f811cc4f8b0332c18cebc98c | https://github.com/sovrasov/mmaction2/tree/055625bf6d6e06e9f811cc4f8b0332c18cebc98c |
GatedConvTranspose | # 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 | GatedConvTranspose | false | 736 | [
"MIT"
] | 0 | 2caf8a4ff84933672fe0d94255d665b3dd7a6791 | https://github.com/Justin-Tan/ffjord/tree/2caf8a4ff84933672fe0d94255d665b3dd7a6791 |
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
from torch._inductor.runtime.... | LouisCaixuran/gomoku | Net | false | 5,585 | [
"Apache-2.0"
] | 1 | c1b6d508522d9e8c78be827f326bbee54c4dfd8b | https://github.com/LouisCaixuran/gomoku/tree/c1b6d508522d9e8c78be827f326bbee54c4dfd8b |
UpdateFunc | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import Module
import torch.nn as nn
from torch.nn.modules.module i... | HAXRD/PIC | UpdateFunc | false | 8,197 | [
"MIT"
] | 28 | 658b4dd6b01e64413d5f8f0107d9167f1bd78546 | https://github.com/HAXRD/PIC/tree/658b4dd6b01e64413d5f8f0107d9167f1bd78546 |
L1RankLoss | import torch
import torch.nn.functional as F
import torch.onnx
class L1RankLoss(torch.nn.Module):
"""
L1 loss + Rank loss
"""
def __init__(self, **kwargs):
super(L1RankLoss, self).__init__()
self.l1_w = kwargs.get('l1_w', 1)
self.rank_w = kwargs.get('rank_w', 1)
self.h... | 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.onnx
asse... | usutdzxych/CenseoQoE | L1RankLoss | false | 16,658 | [
"BSD-3-Clause"
] | 75 | 3f653296b223da6190e1e1781e7b9b54ff877102 | https://github.com/usutdzxych/CenseoQoE/tree/3f653296b223da6190e1e1781e7b9b54ff877102 |
Agent | import torch
import torch.nn.functional as F
import torch.nn as nn
class Agent(torch.nn.Module):
def __init__(self, numObs, numActions):
super(Agent, self).__init__()
self.critic_input = nn.Linear(numObs, 32)
self.critic_fc1 = nn.Linear(32, 32)
self.critic_output = nn.Linear(32, 1... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | mpgussert/fundamentalRL | Agent | false | 7,277 | [
"MIT"
] | 1 | 4f45436226e0823c21cac316dec8bbf1df697467 | https://github.com/mpgussert/fundamentalRL/tree/4f45436226e0823c21cac316dec8bbf1df697467 |
VarifocalLoss | import torch
import torch.nn.functional as F
import torch.nn as nn
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Return:
Tensor: Reduced loss tensor.
"""
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | Guoning-Chen/mmdetection | VarifocalLoss | false | 496 | [
"Apache-2.0"
] | 0 | f1d1c5a19dbe6aa2e74fc9ca2e9578db4532fc64 | https://github.com/Guoning-Chen/mmdetection/tree/f1d1c5a19dbe6aa2e74fc9ca2e9578db4532fc64 |
FCDiscriminator | # 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... | JohanVer/heatnet | FCDiscriminator | false | 17,529 | [
"MIT"
] | 7 | a2de9ec918fbbc6d9433aba344cbbcb2a2cdc85e | https://github.com/JohanVer/heatnet/tree/a2de9ec918fbbc6d9433aba344cbbcb2a2cdc85e |
KLNormCriterion | # 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
... | PaperCodeSubmission/ICML2020-697 | KLNormCriterion | false | 8,667 | [
"MIT"
] | 12 | 00f7732c236b9c6234e76a47dfebe5de314d5c01 | https://github.com/PaperCodeSubmission/ICML2020-697/tree/00f7732c236b9c6234e76a47dfebe5de314d5c01 |
KLDLoss | from _paritybench_helpers import _mock_config
import torch
from torch import nn
class KLDLoss(nn.Module):
def __init__(self, opt):
super().__init__()
def forward(self, mu, logvar):
kld_loss = torch.mean(-0.5 * torch.sum(1 + logvar - mu.pow(2) -
logvar.exp(), dim=1), dim=0)
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_... | DSciLab/VAE-Lab | KLDLoss | false | 3,721 | [
"MIT"
] | 0 | ab37cc1399e3ece28ce426d8bd31149b8f492f82 | https://github.com/DSciLab/VAE-Lab/tree/ab37cc1399e3ece28ce426d8bd31149b8f492f82 |
SAB | import math
import torch
import torch.nn.functional as F
import torch.nn as nn
class MAB(nn.Module):
def __init__(self, dim_Q, dim_K, dim_V, num_heads, ln=False):
super(MAB, self).__init__()
self.dim_V = dim_V
self.num_heads = num_heads
self.fc_q = nn.Linear(dim_Q, dim_V)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | AntonValk/BagGraph-Graph-MIL | SAB | false | 16,960 | [
"MIT"
] | 8 | 1447b52b32995cf6c71e731dd1261104cd66ced0 | https://github.com/AntonValk/BagGraph-Graph-MIL/tree/1447b52b32995cf6c71e731dd1261104cd66ced0 |
BoxOffsetIntersection | import torch
import torch.nn as nn
import torch.nn.functional as F
class BoxOffsetIntersection(nn.Module):
def __init__(self, dim):
super(BoxOffsetIntersection, self).__init__()
self.dim = dim
self.layers = nn.Parameter(torch.zeros(self.dim * 2 + 2, self.dim))
nn.init.xavier_unifo... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | google-research/smore | BoxOffsetIntersection | false | 15,460 | [
"Apache-2.0"
] | 78 | e4ba95a7466ef7d018987bce7688b77bf2ea7e4f | https://github.com/google-research/smore/tree/e4ba95a7466ef7d018987bce7688b77bf2ea7e4f |
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.... | ZfSangkuan/ASER | PositionwiseFeedForward | false | 14,728 | [
"MIT"
] | 256 | c34d6f2432b181bae9f4ee4fa70ce270dbc1dee7 | https://github.com/ZfSangkuan/ASER/tree/c34d6f2432b181bae9f4ee4fa70ce270dbc1dee7 |
Blockdown | import torch
import torch.utils.data
import torch
import torch.nn as nn
class conv_bn_relu(nn.Module):
def __init__(self, in_channel, out_channel, stride=1, has_relu=True):
super(conv_bn_relu, self).__init__()
self.conv = nn.Conv2d(in_channel, out_channel, 3, stride=stride,
padding=1,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
impor... | SeanChenxy/GAN_RS | Blockdown | false | 8,746 | [
"BSD-3-Clause"
] | 17 | a1786b946caf7bd24c83cea4c7a9bb74445cc381 | https://github.com/SeanChenxy/GAN_RS/tree/a1786b946caf7bd24c83cea4c7a9bb74445cc381 |
SoftmaxOutputLayer | # 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.... | oya163/torchnlp | SoftmaxOutputLayer | false | 4,112 | [
"Apache-2.0"
] | 0 | 361caa24d741e47b8bd92af122ae281d6ad72d9d | https://github.com/oya163/torchnlp/tree/361caa24d741e47b8bd92af122ae281d6ad72d9d |
BertSelfAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Andr3wis2Cool4School/AI-pro | BertSelfAttention | false | 1,304 | [
"MIT"
] | 0 | dfe5f5959bc187d899a86f13b84158c66f64d1cc | https://github.com/Andr3wis2Cool4School/AI-pro/tree/dfe5f5959bc187d899a86f13b84158c66f64d1cc |
Attention | from _paritybench_helpers import _mock_config
from torch.nn import Module
import math
import torch
from torch import nn
from torch.nn import Parameter
from torch.nn.parameter import Parameter
class Conv1D(nn.Module):
def __init__(self, nf, nx):
super(Conv1D, self).__init__()
self.nf = nf
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | mandaltanmoy1938/VisualGPT | Attention | false | 16,009 | [
"MIT"
] | 86 | 9ba78948282fdca502d5030f4eccc3df562982c3 | https://github.com/mandaltanmoy1938/VisualGPT/tree/9ba78948282fdca502d5030f4eccc3df562982c3 |
MSE | # 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.checkpoint
assert_size_stride = torch._C._dynamo... | byamao1/MMSA | MSE | false | 14,984 | [
"MIT"
] | 198 | 1a894d042144c9ac75b3465d38871ce8c2987251 | https://github.com/byamao1/MMSA/tree/1a894d042144c9ac75b3465d38871ce8c2987251 |
PositionwiseFeedForwardNet | # 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_... | ozzieba/pytorch-original-transformer | PositionwiseFeedForwardNet | false | 16,212 | [
"MIT"
] | 654 | 4c1e17a701fae050e362e962284fb99547636f75 | https://github.com/ozzieba/pytorch-original-transformer/tree/4c1e17a701fae050e362e962284fb99547636f75 |
vd_linear_1L_hetero | import math
import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
def calculate_kl(log_alpha):
return 0.5 * torch.sum(torch.log1p(torch.exp(-log_alpha)))
class VdLinear(nn.Module):
"""
variational dropout
"""
def __init__(self, n_in, n_ou... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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/Bayesian-neural-networks | vd_linear_1L_hetero | false | 17,780 | [
"MIT"
] | 4 | 9d7f781f5c2dfa8fadf26300b4b5b64366c939cd | https://github.com/Neronjust2017/Bayesian-neural-networks/tree/9d7f781f5c2dfa8fadf26300b4b5b64366c939cd |
GatedFusion | import torch
import torch.nn as nn
from scipy.sparse import *
class GatedFusion(nn.Module):
def __init__(self, hidden_size):
super(GatedFusion, self).__init__()
"""GatedFusion module"""
self.fc_z = nn.Linear(4 * hidden_size, hidden_size, bias=True)
def forward(self, h_state, input):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from scipy.sparse import *
assert_size_stride = torch._C._... | talha1503/RL-based-Graph2Seq-for-NQG | GatedFusion | false | 16,527 | [
"Apache-2.0"
] | 100 | 1039e0b6231ae7029ea6e4073b1e55df5ad2e928 | https://github.com/talha1503/RL-based-Graph2Seq-for-NQG/tree/1039e0b6231ae7029ea6e4073b1e55df5ad2e928 |
BertSelfAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | minjoong507/Image-Captioning-Transformer | BertSelfAttention | false | 7,247 | [
"MIT"
] | 1 | 813060f0bb656e336154173f11e99a80362c8c2a | https://github.com/minjoong507/Image-Captioning-Transformer/tree/813060f0bb656e336154173f11e99a80362c8c2a |
Fair | # 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
... | davefiorino/EDSR-PyTorch | Fair | false | 1,796 | [
"MIT"
] | 0 | 97ad32a09a71816a36c45d92cdb2ea7ab42ba685 | https://github.com/davefiorino/EDSR-PyTorch/tree/97ad32a09a71816a36c45d92cdb2ea7ab42ba685 |
SE_Connect | import torch
import torch.nn as nn
import torch.nn.functional as F
class SE_Connect(nn.Module):
def __init__(self, channels, s=2):
super().__init__()
assert channels % s == 0, '{} % {} != 0'.format(channesl, s)
self.linear1 = nn.Linear(channels, channels // s)
self.linear2 = nn.Li... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | SecretKeyTeam/voxceleb_trainer | SE_Connect | false | 9,573 | [
"MIT"
] | 0 | e235cbc2961d32395d30cf606ee830cd47716383 | https://github.com/SecretKeyTeam/voxceleb_trainer/tree/e235cbc2961d32395d30cf606ee830cd47716383 |
DAInsHead | # 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.utils.data
from ... | FengJunJian/Domain-Adaptive-Faster-RCNN-PyTorch | DAInsHead | false | 9,318 | [
"MIT"
] | 0 | 35aa8d208fec22af8c502f8d6d2f562e857d4175 | https://github.com/FengJunJian/Domain-Adaptive-Faster-RCNN-PyTorch/tree/35aa8d208fec22af8c502f8d6d2f562e857d4175 |
VAE | # 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 import device
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from... | benedictquartey/softgym_wm | VAE | false | 12,200 | [
"BSD-3-Clause"
] | 0 | 0aef75fed207b11029f6052c656a679c105b4677 | https://github.com/benedictquartey/softgym_wm/tree/0aef75fed207b11029f6052c656a679c105b4677 |
CReLU_IN | # 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_... | cnzeki/PSENet | CReLU_IN | false | 3,305 | [
"Apache-2.0"
] | 0 | c7e0785404e12866171e9da678736abae9cdb8cb | https://github.com/cnzeki/PSENet/tree/c7e0785404e12866171e9da678736abae9cdb8cb |
MultiHeadAttention | import torch
import torch.nn as nn
import torch.utils.data
import torch.nn.functional as F
class MultiHeadAttention(nn.Module):
"""
input:
query --- [N, T_q, query_dim]
key --- [N, T_k, key_dim]
output:
out --- [N, T_q, num_units]
"""
def __init__(self, query_dim, key_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.... | CookiePPP/mellotron | MultiHeadAttention | false | 9,062 | [
"BSD-3-Clause"
] | 0 | 488425981c19cd0eddddea13d1348da4bfef8d26 | https://github.com/CookiePPP/mellotron/tree/488425981c19cd0eddddea13d1348da4bfef8d26 |
GaussionConvF | import torch
import torch.nn.functional as F
import torch.nn as nn
class GaussionConvF(nn.Module):
"""The first layer in `RobustGCN` that conver node features to distribution (mean, var)"""
def __init__(self, in_features, out_features, bias=False, gamma=1.0):
super().__init__()
self.in_featur... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | EdisonLeeeee/Graphgallery | GaussionConvF | false | 5,103 | [
"MIT"
] | 1 | 8ae9ef57d44f073d0ceaf3f33a3a998546f960a8 | https://github.com/EdisonLeeeee/Graphgallery/tree/8ae9ef57d44f073d0ceaf3f33a3a998546f960a8 |
MultinomialNLLLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
import torch.onnx
def _reduce(x, reduction='elementwise_mean'):
if reduction == 'none':
return x
elif reduction == 'elementwise_mea... | 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
... | akshayka/gavel | MultinomialNLLLoss | false | 14,795 | [
"MIT"
] | 67 | 40a22a725f2e70478483e98c9b07c6fc588e0c40 | https://github.com/akshayka/gavel/tree/40a22a725f2e70478483e98c9b07c6fc588e0c40 |
GIoU_loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | debrouchovea/ReproduceGoturn | GIoU_loss | false | 3,411 | [
"MIT"
] | 0 | d60f13c781ca612cacc17536530bbee989bdfa45 | https://github.com/debrouchovea/ReproduceGoturn/tree/d60f13c781ca612cacc17536530bbee989bdfa45 |
SimpleSliceModel | import torch
import torch.onnx
import torch.nn
class SimpleSliceModel(torch.nn.Module):
def __init__(self):
super(SimpleSliceModel, self).__init__()
def forward(self, tensor):
other = (tensor + tensor)[1:]
return other[0][1:]
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
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guar... | geoffberry/glow | SimpleSliceModel | false | 12,412 | [
"Apache-2.0"
] | 0 | 24b2827c830eb58af56a0704e899968026832e9c | https://github.com/geoffberry/glow/tree/24b2827c830eb58af56a0704e899968026832e9c |
BertOutput | from _paritybench_helpers import _mock_config
import torch
from torch import nn
class BertOutput(nn.Module):
def __init__(self, model_config):
super().__init__()
self.dense = nn.Linear(model_config.intermediate_size, model_config
.hidden_size)
self.LayerNorm = nn.LayerNorm(mod... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | HS-YN/PanoAVQA | BertOutput | false | 18,391 | [
"MIT"
] | 3 | 657b83421ce64ea18b3e79fb580afc7034403ccc | https://github.com/HS-YN/PanoAVQA/tree/657b83421ce64ea18b3e79fb580afc7034403ccc |
Contracting_Block | import torch
import torch.nn as nn
import torch.nn.functional as F
class Contracting_Block(nn.Module):
def __init__(self, in_channels, out_channels):
super(Contracting_Block, self).__init__()
self.conv1 = nn.Conv2d(in_channels, out_channels, kernel_size=3)
self.conv2 = nn.Conv2d(out_chann... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | parth2035/U-Net-Implementation | Contracting_Block | false | 7,461 | [
"MIT"
] | 1 | 36ed8d140ef8a0031f63f2d1f577dcef92c4dab6 | https://github.com/parth2035/U-Net-Implementation/tree/36ed8d140ef8a0031f63f2d1f577dcef92c4dab6 |
UpdateNodeEmbeddingLayer | # 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_... | NinaMaz/eco-dqn | UpdateNodeEmbeddingLayer | false | 5,671 | [
"MIT"
] | 1 | d9ea164c59014e4209ae069005029af818372ade | https://github.com/NinaMaz/eco-dqn/tree/d9ea164c59014e4209ae069005029af818372ade |
TorchDiceLoss | import torch
from torch import nn
def soft_dice_loss(outputs, targets, per_image=False):
batch_size = outputs.size()[0]
eps = 1e-05
if not per_image:
batch_size = 1
dice_target = targets.contiguous().view(batch_size, -1).float()
dice_output = outputs.contiguous().view(batch_size, -1)
i... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | Spiruel/solaris | TorchDiceLoss | false | 11,944 | [
"Apache-2.0"
] | 0 | eb2ce05265a462d69b01ee2b621a85a3e9082402 | https://github.com/Spiruel/solaris/tree/eb2ce05265a462d69b01ee2b621a85a3e9082402 |
Vgg16 | # 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... | Arthur1511/CAD-COVID | Vgg16 | false | 186 | [
"MIT"
] | 0 | daab5d70b9f811da41f702e92179a15ca4809fa5 | https://github.com/Arthur1511/CAD-COVID/tree/daab5d70b9f811da41f702e92179a15ca4809fa5 |
CoralLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cu... | Raschka-research-group/coral-pytorch | CoralLayer | false | 8,678 | [
"MIT"
] | 32 | 6b85e287118476095bac85d6f3dabc6ffb89a326 | https://github.com/Raschka-research-group/coral-pytorch/tree/6b85e287118476095bac85d6f3dabc6ffb89a326 |
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.... | YunjieJi/attention-is-all-you-need-pytorch | PositionwiseFeedForward | false | 12,018 | [
"MIT"
] | 0 | 636117b438d584ccba0ae5d6998fc02f3888f46e | https://github.com/YunjieJi/attention-is-all-you-need-pytorch/tree/636117b438d584ccba0ae5d6998fc02f3888f46e |
MegatronGelu | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn
import torch.onnx
import torch.utils.checkpoint
assert_size_str... | almiliMSFT/onnxruntime | MegatronGelu | false | 14,799 | [
"MIT"
] | 6,036 | c002dc86a364852859ca9642698fcfc5edf22c9d | https://github.com/almiliMSFT/onnxruntime/tree/c002dc86a364852859ca9642698fcfc5edf22c9d |
_Logit | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cu... | IKACE/DifferentialByzantine-1 | _Logit | false | 5,313 | [
"MIT"
] | 1 | 809fd6e070fedeb87a6dbff6f883e93e3c5c8e09 | https://github.com/IKACE/DifferentialByzantine-1/tree/809fd6e070fedeb87a6dbff6f883e93e3c5c8e09 |
AE_big_2D_v3 | import torch
import torch.nn as nn
import torch.utils.data
class AE_big_2D_v3(nn.Module):
def __init__(self, n_features=4):
super(AE_big_2D_v3, self).__init__()
self.en1 = nn.Linear(n_features, 8)
self.en2 = nn.Linear(8, 6)
self.en3 = nn.Linear(6, 2)
self.de1 = nn.Linear(2... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | gitter-badger/HEPAutoencoders | AE_big_2D_v3 | false | 12,451 | [
"Apache-2.0"
] | 0 | 43010cd66fa4335a04b30b87926148e1c8d92de9 | https://github.com/gitter-badger/HEPAutoencoders/tree/43010cd66fa4335a04b30b87926148e1c8d92de9 |
UNet | # 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.functional as... | Remosy/v2e | UNet | false | 11,938 | [
"MIT"
] | 0 | efc81cbcc113ca55d1631603323150be5ef8eb30 | https://github.com/Remosy/v2e/tree/efc81cbcc113ca55d1631603323150be5ef8eb30 |
Sub | # 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... | ahangchen/torch2trt | Sub | false | 6,111 | [
"MIT"
] | 1 | 53c663f0e0570ef7ffd6771354ae3478f63bd328 | https://github.com/ahangchen/torch2trt/tree/53c663f0e0570ef7ffd6771354ae3478f63bd328 |
ResBlock | import torch
from torch import nn
import torch.nn.functional as F
class ResBlock(nn.Module):
def __init__(self, dim, dropout=0):
super(ResBlock, self).__init__()
self.dim = dim
self.dropout = nn.Dropout(dropout)
self.linear1 = nn.Linear(self.dim, self.dim)
self.linear2 = 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 import triton_helpers
from torch._inductor.runtime.... | JiwanChung/tapm | ResBlock | false | 8,388 | [
"MIT"
] | 14 | ec42b139d1c012daccc55f85e67744488d526476 | https://github.com/JiwanChung/tapm/tree/ec42b139d1c012daccc55f85e67744488d526476 |
BertNonFusedLayerNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Og-ChRoNiC/FasterTransformer | BertNonFusedLayerNorm | false | 5,674 | [
"Apache-2.0"
] | 1 | 05c7e3db209064efec4798a570a488ce08ad211c | https://github.com/Og-ChRoNiC/FasterTransformer/tree/05c7e3db209064efec4798a570a488ce08ad211c |
GAT | # 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.... | OuYangg/GNNs | GAT | false | 9,518 | [
"Apache-2.0"
] | 0 | ef5b1944490507684d603de3ae0b2aa7b5168f47 | https://github.com/OuYangg/GNNs/tree/ef5b1944490507684d603de3ae0b2aa7b5168f47 |
ClippedLinearQuantization | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
from torch.optim.lr_schedule... | Chih-Ling-Hsu/distiller | ClippedLinearQuantization | false | 13,512 | [
"Apache-2.0"
] | 94 | 33d1697298c6e3a7f7bfa615741fd0cda61d2794 | https://github.com/Chih-Ling-Hsu/distiller/tree/33d1697298c6e3a7f7bfa615741fd0cda61d2794 |
WeightedSmoothL1Loss | import torch
import numpy as np
import torch.nn as nn
import torch.utils.data
import torch.autograd
class WeightedSmoothL1Loss(nn.Module):
"""
Code-wise Weighted Smooth L1 Loss modified based on fvcore.nn.smooth_l1_loss
https://github.com/facebookresearch/fvcore/blob/master/fvcore/nn/smooth_l1_loss.py
... | 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 numpy as np
import torch.nn as nn
import torch.utils.da... | LaudateCorpus1/LIGA-Stereo | WeightedSmoothL1Loss | false | 13,983 | [
"Apache-2.0"
] | 56 | aee3731a24a0ab1667e633e520cc89be2f135272 | https://github.com/LaudateCorpus1/LIGA-Stereo/tree/aee3731a24a0ab1667e633e520cc89be2f135272 |
MyInstanceNorm2d | import torch
from torch import nn
class AffineChannelwise(nn.Module):
def __init__(self, num_channels):
super().__init__()
self.num_channels = num_channels
self.register_parameter('weight', nn.Parameter(torch.ones(
num_channels)))
self.register_parameter('bias', nn.Par... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | dniku/dl-norms | MyInstanceNorm2d | false | 6,581 | [
"MIT"
] | 1 | 0f1eef942bd318ac988ec7dfa9caea300d17e82a | https://github.com/dniku/dl-norms/tree/0f1eef942bd318ac988ec7dfa9caea300d17e82a |
PSLoss | import torch
import torch.nn as nn
import torch.fft
class PSLoss(nn.Module):
def __init__(self):
super().__init__()
self.l1_loss = torch.nn.L1Loss()
def forward(self, x, y):
x_power = torch.abs(torch.fft.fftn(x, dim=[2, 3]))
y_power = torch.abs(torch.fft.fftn(y, dim=[2, 3]))
... | 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
... | NejcHirci/material-addon | PSLoss | false | 17,767 | [
"MIT"
] | 4 | c08e2081413c3319b712c2f7193ac8013f601382 | https://github.com/NejcHirci/material-addon/tree/c08e2081413c3319b712c2f7193ac8013f601382 |
DownsampleA | import torch
import torch.nn as nn
import torch.utils.data.distributed
class DownsampleA(nn.Module):
def __init__(self, nIn, nOut, stride):
super(DownsampleA, self).__init__()
assert stride == 2
self.avg = nn.AvgPool2d(kernel_size=1, stride=stride)
def forward(self, x):
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
import torch.utils.data.distributed
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda... | HKBU-HPML/gtopkssgd | DownsampleA | false | 8,190 | [
"Apache-2.0"
] | 33 | 6f57343f3749939b0345d36fcb2c24470942aefd | https://github.com/HKBU-HPML/gtopkssgd/tree/6f57343f3749939b0345d36fcb2c24470942aefd |
EPELoss | import torch
import torch.nn as nn
class EPELoss(nn.Module):
def __init__(self):
super(EPELoss, self).__init__()
def forward(self, output, target):
lossvalue = torch.norm(output - target + 1e-16, p=2, dim=1).mean()
return lossvalue
def get_inputs():
return [torch.rand([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 libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | haochen23/GeoProj | EPELoss | false | 10,180 | [
"MIT"
] | 0 | 4b31f51789f9cc41ea7dc977cee057b8bc8a83cc | https://github.com/haochen23/GeoProj/tree/4b31f51789f9cc41ea7dc977cee057b8bc8a83cc |
InteractionLayer | import math
import torch
import torchvision.transforms.functional as F
from torch import nn
import torch.nn.functional as F
class InteractionLayer(nn.Module):
def __init__(self, d_model, d_feature, dropout=0.1):
super().__init__()
self.d_feature = d_feature
self.det_tfm = nn.Linear(d_mode... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | yoyomimi/AS-Net | InteractionLayer | false | 16,782 | [
"MIT"
] | 49 | 85ce753707c6d1838c3983111ccbba4b1861f438 | https://github.com/yoyomimi/AS-Net/tree/85ce753707c6d1838c3983111ccbba4b1861f438 |
XnorConv | import torch
import torch.multiprocessing
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
import torch.autograd as autograd
import torch.nn.functional as F
class BinarizeWeight(autograd.Function):
@staticmethod
def forward(ctx, sco... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.multiprocessing
import torch.nn as nn
import torch.nn.parallel
impo... | adityakusupati/LLC-2.0 | XnorConv | false | 18,235 | [
"MIT"
] | 10 | 38608bbaa425b15dcf5c971000b7a1b08120fb5c | https://github.com/adityakusupati/LLC-2.0/tree/38608bbaa425b15dcf5c971000b7a1b08120fb5c |
Conv3x3 | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | Sid1057/sid1057.github.io | Conv3x3 | false | 17,964 | [
"MIT"
] | 4 | 623d1731e308b42b6f86304dcfd671a061b414bf | https://github.com/Sid1057/sid1057.github.io/tree/623d1731e308b42b6f86304dcfd671a061b414bf |
Triaffine | import torch
import torch.nn as nn
class Triaffine(nn.Module):
"""
Triaffine layer for second-order scoring :cite:`zhang-etal-2020-efficient,wang-etal-2019-second`.
This function has a tensor of weights :math:`W` and bias terms if needed.
The score :math:`s(x, y, z)` of the vector triple :math:`(x, y... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | yzhangcs/parser | Triaffine | false | 16,785 | [
"MIT"
] | 439 | 3abebde1c9fe0bf2e99adce845aaf2a04b194f8a | https://github.com/yzhangcs/parser/tree/3abebde1c9fe0bf2e99adce845aaf2a04b194f8a |
FeatureResizer | # 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.utils.... | mmaaz60/mdetr | FeatureResizer | false | 10,485 | [
"Apache-2.0"
] | 0 | fe1394c67e76a6c7e521bbda77d8294714038a3a | https://github.com/mmaaz60/mdetr/tree/fe1394c67e76a6c7e521bbda77d8294714038a3a |
BeitPooler | from _paritybench_helpers import _mock_config
import torch
from torch import nn
import torch.utils.checkpoint
class BeitPooler(nn.Module):
def __init__(self, config):
super().__init__()
self.layernorm = nn.LayerNorm(config.hidden_size, eps=config.
layer_norm_eps) if config.use_mean_po... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
import torch.utils.checkpoint
assert_size_stride = torch._... | Clemens123/transformers | BeitPooler | false | 13,203 | [
"Apache-2.0"
] | 0 | 22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 | https://github.com/Clemens123/transformers/tree/22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 |
ContrastiveLoss | # 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
assert... | AytacKahveci/siamese-triplet | ContrastiveLoss | false | 11,230 | [
"BSD-3-Clause"
] | 0 | 09860e36d934bb1773a4d49dbad183a5152cb0b0 | https://github.com/AytacKahveci/siamese-triplet/tree/09860e36d934bb1773a4d49dbad183a5152cb0b0 |
PyConv2 | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
def conv(in_planes, out_planes, kernel_size=3, stride=1, padding=1,
dilation=1, groups=1):
"""standard convolution with padding"""
return nn.Conv2d(in_planes, out_plan... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.u... | lkf59553/pyconv | PyConv2 | false | 15,943 | [
"MIT"
] | 295 | d8b39cf43014b8fd277dcefc9eb7f8880511e977 | https://github.com/lkf59553/pyconv/tree/d8b39cf43014b8fd277dcefc9eb7f8880511e977 |
GAT | import torch
import torch.nn as nn
import torch.nn.functional as F
class GraphAttentionLayer(nn.Module):
"""
Simple GAT layer, similar to https://arxiv.org/abs/1710.10903
"""
def __init__(self, in_features, out_features, dropout, alpha, concat=True):
super(GraphAttentionLayer, self).__init__(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Prasath2001/commonsense-rl | GAT | false | 2,763 | [
"Apache-2.0"
] | 0 | ef3e83270d34cf211b2d2086120cccae0621477b | https://github.com/Prasath2001/commonsense-rl/tree/ef3e83270d34cf211b2d2086120cccae0621477b |
Reorg | import torch
import torch.nn as nn
class Reorg(nn.Module):
def __init__(self, stride=2):
super(Reorg, self).__init__()
self.stride = stride
def forward(self, x):
assert x.data.dim() == 4
B = x.data.size(0)
C = x.data.size(1)
H = x.data.size(2)
W = x.da... | 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... | CharlesPikachu/YOLO | Reorg | false | 13,460 | [
"MIT"
] | 57 | 950b11c35517c1c3d7d7856b5768c4023c1f89eb | https://github.com/CharlesPikachu/YOLO/tree/950b11c35517c1c3d7d7856b5768c4023c1f89eb |
BasicModel | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | aravipati12/captum | BasicModel | false | 10,088 | [
"BSD-3-Clause"
] | 0 | ef3e81d89c8c4404a49c384cf0727f2e7d393f5f | https://github.com/aravipati12/captum/tree/ef3e81d89c8c4404a49c384cf0727f2e7d393f5f |
Network | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | alexljenkins/reinforcement-learning-agents | Network | false | 9,696 | [
"MIT"
] | 0 | d5bdfad56c9b095d5bb0ac22ca69e19553327416 | https://github.com/alexljenkins/reinforcement-learning-agents/tree/d5bdfad56c9b095d5bb0ac22ca69e19553327416 |
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