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 |
|---|---|---|---|---|---|---|---|---|---|---|
Encoder | import torch
import torch.nn as nn
class Encoder(nn.Module):
def __init__(self, input_dim, hidden_dim, latent_dim):
super(Encoder, self).__init__()
self.FC_input = nn.Linear(input_dim, hidden_dim)
self.FC_mean = nn.Linear(hidden_dim, latent_dim)
self.FC_var = nn.Linear(hidden_dim,... | 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... | CsekM8/dtu_mlops | Encoder | false | 11,329 | [
"Apache-2.0"
] | 0 | 5c96a9afac0298fab57b7d47e4c08497f4a5d8d9 | https://github.com/CsekM8/dtu_mlops/tree/5c96a9afac0298fab57b7d47e4c08497f4a5d8d9 |
AvgReadout | import torch
import torch.nn as nn
class AvgReadout(nn.Module):
"""
Considering the efficiency of the method, we simply employ average pooling, computing the average of the set of embedding matrices
.. math::
\\begin{equation}
\\mathbf{H}=\\mathcal{Q}\\left(\\left\\{\\mathbf{H}^{(r)} \\mid ... | 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... | BUPTlfq/OpenHGNN | AvgReadout | false | 1,997 | [
"Apache-2.0"
] | 0 | 77041e68c33a8a42a2c187c6e42d85b81cbb25d3 | https://github.com/BUPTlfq/OpenHGNN/tree/77041e68c33a8a42a2c187c6e42d85b81cbb25d3 |
TokenEmbedding | import torch
import torch.nn as nn
class TokenEmbedding(nn.Module):
def __init__(self, c_in, d_model):
super(TokenEmbedding, self).__init__()
padding = 1 if torch.__version__ >= '1.5.0' else 2
self.tokenConv = nn.Conv1d(in_channels=c_in, out_channels=d_model,
kernel_size=3, pa... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Xianchao-Wu/informer | TokenEmbedding | false | 5,986 | [
"Apache-2.0"
] | 1 | bb9cb3c6ff9e7e76c8dbbf3bcc7924df1f18982d | https://github.com/Xianchao-Wu/informer/tree/bb9cb3c6ff9e7e76c8dbbf3bcc7924df1f18982d |
Attention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Anshul044/Project-NN | Attention | false | 71 | [
"MIT"
] | 0 | ef080846715a95b735f0381e4f60742e40791630 | https://github.com/Anshul044/Project-NN/tree/ef080846715a95b735f0381e4f60742e40791630 |
HierarchicalPolicy | # 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.... | hanhanAnderson/LSF-SAC | HierarchicalPolicy | false | 6,780 | [
"MIT"
] | 1 | 3e2daf0da23b0ea08e92948c87f7e583f3fb1ed9 | https://github.com/hanhanAnderson/LSF-SAC/tree/3e2daf0da23b0ea08e92948c87f7e583f3fb1ed9 |
GCN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn.functional as F
from torch import nn
import torch.nn.parallel
as... | gist-ailab/uoais | GCN | false | 15,430 | [
"BSD-2-Clause"
] | 52 | fb42d9a96cd54daad61c956d8d9d65dd0ebef4c7 | https://github.com/gist-ailab/uoais/tree/fb42d9a96cd54daad61c956d8d9d65dd0ebef4c7 |
SoftArgMax | import torch
import torch.nn as nn
import torch.nn.functional as F
class SoftArgMax(nn.Module):
def __init__(self):
super().__init__()
def forward(self, x, labels, kernel_size=0):
"""
Args
x: [B, C, Nd]
labels: [Nd]
Returns
[B, C]
"... | 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... | hcyz33/PlaneSweepPose | SoftArgMax | false | 3,579 | [
"MIT"
] | 0 | 4ae3a4e7e939fa74c060eb1b354c34ea0fb55248 | https://github.com/hcyz33/PlaneSweepPose/tree/4ae3a4e7e939fa74c060eb1b354c34ea0fb55248 |
MemoryEfficientSwish | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
assert_size_st... | BradleyBrown19/CustomObjectDetector | MemoryEfficientSwish | false | 2,078 | [
"Apache-2.0"
] | 0 | 11c14ec6127c553ac365703c768b75dde33d9a4d | https://github.com/BradleyBrown19/CustomObjectDetector/tree/11c14ec6127c553ac365703c768b75dde33d9a4d |
ReRegualizedLinearMNACLayer | # 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
import collections
import math
import torch.utils.data
assert_size_stride = torch._C._dyn... | wlm2019/Neural-Arithmetic-Units | ReRegualizedLinearMNACLayer | false | 16,720 | [
"MIT"
] | 147 | f9de9d004bb2dc2ee28577cd1760d0a00c185836 | https://github.com/wlm2019/Neural-Arithmetic-Units/tree/f9de9d004bb2dc2ee28577cd1760d0a00c185836 |
DownsampleB | import torch
import torch.nn as nn
class DownsampleB(nn.Module):
def __init__(self, nIn, nOut, stride):
super(DownsampleB, self).__init__()
self.avg = nn.AvgPool2d(stride)
self.expand_ratio = nOut // nIn
def forward(self, x):
x = self.avg(x)
return torch.cat([x] + [x.... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | andyqmongo/InstAParam | DownsampleB | false | 18,332 | [
"MIT"
] | 3 | 00494d5367ec32b4ce90d01778cba9d4f1166833 | https://github.com/andyqmongo/InstAParam/tree/00494d5367ec32b4ce90d01778cba9d4f1166833 |
Critic | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | linsats/GRAC2.0 | Critic | false | 3,919 | [
"MIT"
] | 0 | 2fde25103b2316a3435ef0ebdbf471ec4e204fbe | https://github.com/linsats/GRAC2.0/tree/2fde25103b2316a3435ef0ebdbf471ec4e204fbe |
Attention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | KaiQiangSong/joint_parse_summ | Attention | false | 8,799 | [
"BSD-3-Clause"
] | 29 | 5d4a40d9a681bc8b06c847643d810846f3867216 | https://github.com/KaiQiangSong/joint_parse_summ/tree/5d4a40d9a681bc8b06c847643d810846f3867216 |
TripletSoftmaxLoss | # 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
... | Lm0079/MetricLearningIdentification | TripletSoftmaxLoss | false | 2,526 | [
"MIT"
] | 0 | 3c2c0512fe2fbbb6aacb958106d5f6a03baedc35 | https://github.com/Lm0079/MetricLearningIdentification/tree/3c2c0512fe2fbbb6aacb958106d5f6a03baedc35 |
BertAttention | from _paritybench_helpers import _mock_config
import math
import torch
import torch.nn as nn
import torch.utils.data
class BertLayerNorm(nn.Module):
def __init__(self, hidden_size, eps=1e-05):
"""Construct a layernorm module in the TF style (epsilon inside the square root)."""
super(BertLayerNorm... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | shubham-gupta-iitr/mmmlX | BertAttention | false | 4,339 | [
"Apache-2.0"
] | 0 | 3485e6191e0e45bf1c8168e4e928a36ab9264d22 | https://github.com/shubham-gupta-iitr/mmmlX/tree/3485e6191e0e45bf1c8168e4e928a36ab9264d22 |
Temporal_Attention_layer | import torch
from torch import nn
import torch.nn.functional as F
class Temporal_Attention_layer(nn.Module):
def __init__(self, DEVICE, in_channels, num_of_vertices, num_of_timesteps):
super(Temporal_Attention_layer, self).__init__()
self.U1 = nn.Parameter(torch.FloatTensor(num_of_vertices))
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | abcdefg-dev-dd/asxdcvfg | Temporal_Attention_layer | false | 6,065 | [
"Apache-2.0"
] | 1 | 83421d4a133810968d6e04b256a9312895452941 | https://github.com/abcdefg-dev-dd/asxdcvfg/tree/83421d4a133810968d6e04b256a9312895452941 |
MixedLoss | # 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... | xkp793003821/kaggle-tgs-salt | MixedLoss | false | 4,586 | [
"MIT"
] | 0 | 4acd7f8b6aff914e2c8558677d6dac8b5ddc1f30 | https://github.com/xkp793003821/kaggle-tgs-salt/tree/4acd7f8b6aff914e2c8558677d6dac8b5ddc1f30 |
DiceLoss | # 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... | phenixcxz/DeepGlobe-Road-Extraction-Challenge | DiceLoss | false | 10,667 | [
"MIT"
] | 0 | 4dee0f0866ff6f06b888afd28a60940b75a8eadd | https://github.com/phenixcxz/DeepGlobe-Road-Extraction-Challenge/tree/4dee0f0866ff6f06b888afd28a60940b75a8eadd |
node_encoder | import torch
import torch.nn as nn
import torch.nn.functional as F
class node_encoder(nn.Module):
def __init__(self, num_in_node, num_hidden, dropout, act=F.tanh):
super(node_encoder, self).__init__()
self.num_in_node = num_in_node
self.num_hidden = num_hidden
self.dropout = dropo... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | iMoonLab/HHDTI | node_encoder | false | 6,841 | [
"MIT"
] | 1 | b2dd0e78818888e676afc91af1425dada5b3258a | https://github.com/iMoonLab/HHDTI/tree/b2dd0e78818888e676afc91af1425dada5b3258a |
MaxPoolWithMask | import torch
import torch.nn as nn
class MaxPoolWithMask(nn.Module):
"""
带mask矩阵的max pooling。在做max-pooling的时候不会考虑mask值为0的位置。
"""
def __init__(self):
super(MaxPoolWithMask, self).__init__()
self.inf = 10000000000000.0
def forward(self, tensor, mask, dim=1):
"""
:pa... | 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... | lonePatient/TorchBlocks | MaxPoolWithMask | false | 15,958 | [
"MIT"
] | 82 | 4a65d746cc8a396cb7df73ed4644d97ddf843e29 | https://github.com/lonePatient/TorchBlocks/tree/4a65d746cc8a396cb7df73ed4644d97ddf843e29 |
get_loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | ChunhuiChen97/RetinalVesselSegmentation | get_loss | false | 8,930 | [
"MIT"
] | 0 | d291e23b1ad9814070897ef850d0117d67331d70 | https://github.com/ChunhuiChen97/RetinalVesselSegmentation/tree/d291e23b1ad9814070897ef850d0117d67331d70 |
cal_L2Norm | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | RiyaoDong/HGSL | cal_L2Norm | false | 2,765 | [
"Apache-2.0"
] | 0 | 19fa984b3bfde0e3b7acbce87dd40177cd64f9b0 | https://github.com/RiyaoDong/HGSL/tree/19fa984b3bfde0e3b7acbce87dd40177cd64f9b0 |
CrossEntropyLoss | # 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
... | AlphaLFC/mmdetection | CrossEntropyLoss | false | 4,834 | [
"Apache-2.0"
] | 1 | 45619c5b8aca0ca3e6ddc211210a8946c94694d8 | https://github.com/AlphaLFC/mmdetection/tree/45619c5b8aca0ca3e6ddc211210a8946c94694d8 |
LxmertAttentionOutput | import torch
import torch.utils.data
import torch.nn as nn
import torch
import torch.nn.parallel
class LxmertAttentionOutput(nn.Module):
def __init__(self, hidden_size, hidden_dropout_prob):
super().__init__()
self.dense = nn.Linear(hidden_size, hidden_size)
self.LayerNorm = nn.LayerNorm(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | IsmaelElsharkawi/new_pororo_repo | LxmertAttentionOutput | false | 8,335 | [
"MIT"
] | 19 | 4617083b420615b8a3eb0f44d02e4e91a8f407f7 | https://github.com/IsmaelElsharkawi/new_pororo_repo/tree/4617083b420615b8a3eb0f44d02e4e91a8f407f7 |
RewardCriterion | import torch
import torch.nn as nn
from torch.autograd import *
class RewardCriterion(nn.Module):
def __init__(self):
super(RewardCriterion, self).__init__()
def forward(self, input, seq, reward):
input = input.gather(2, seq.unsqueeze(2)).squeeze(2)
input = input.reshape(-1)
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.autograd import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | linzhlalala/self-critical.pytorch | RewardCriterion | false | 7,109 | [
"MIT"
] | 1 | b856250ac52ba63656b1b03cdc3d7e830ed43f68 | https://github.com/linzhlalala/self-critical.pytorch/tree/b856250ac52ba63656b1b03cdc3d7e830ed43f68 |
SigmoidFocalClassificationLoss | import torch
import torch.nn as nn
class SigmoidFocalClassificationLoss(nn.Module):
"""
Sigmoid focal cross entropy loss.
"""
def __init__(self, gamma: 'float'=2.0, alpha: 'float'=0.25):
"""
Args:
gamma: Weighting parameter to balance loss for hard and easy examples.
... | 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... | AbangLZU/OpenPCDet | SigmoidFocalClassificationLoss | false | 7,642 | [
"Apache-2.0"
] | 29 | eeea3f24d392f692228c1ad4e28c0dc9d0e25665 | https://github.com/AbangLZU/OpenPCDet/tree/eeea3f24d392f692228c1ad4e28c0dc9d0e25665 |
Actor | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | saman-aghazadeh/distiller | Actor | false | 4,255 | [
"Apache-2.0"
] | 0 | 7e8d3e6193c807f7c55d8453f64e1bc3c02eee30 | https://github.com/saman-aghazadeh/distiller/tree/7e8d3e6193c807f7c55d8453f64e1bc3c02eee30 |
CrossEntropy | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn.functi... | SHI-Labs/Semi-Supervised-Transfer-Learning | CrossEntropy | false | 14,349 | [
"MIT"
] | 81 | f206750824ffe10f88a2b418b2b671da61b999f6 | https://github.com/SHI-Labs/Semi-Supervised-Transfer-Learning/tree/f206750824ffe10f88a2b418b2b671da61b999f6 |
Decoder | import torch
import torch.nn as nn
class Decoder(nn.Module):
def __init__(self, latent_size, m):
super(Decoder, self).__init__()
self.latent_size = latent_size
self.fc = nn.Linear(latent_size, m)
self.deconv1 = nn.ConvTranspose2d(m, 128, 5, stride=2)
self.deconv2 = 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
import torch.nn as nn
assert_... | lshoek/creative-evo-controller | Decoder | false | 10,454 | [
"MIT"
] | 0 | a5f1742c172255cca2338b76ae1c5b4db277bb0d | https://github.com/lshoek/creative-evo-controller/tree/a5f1742c172255cca2338b76ae1c5b4db277bb0d |
CameraPriorLoss | # 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.comm
assert_size_stride = torch._... | JasonBoy1/mmhuman3d | CameraPriorLoss | false | 5,376 | [
"Apache-2.0"
] | 1 | 79b2665191115f3ed905e6afdf09990a8d484362 | https://github.com/JasonBoy1/mmhuman3d/tree/79b2665191115f3ed905e6afdf09990a8d484362 |
IOU | import torch
def _iou(pred, target, size_average=True):
b = pred.shape[0]
IoU = 0.0
for i in range(0, b):
Iand1 = torch.sum(target[i, :, :, :] * pred[i, :, :, :])
Ior1 = torch.sum(target[i, :, :, :]) + torch.sum(pred[i, :, :, :]
) - Iand1
IoU1 = Iand1 / Ior1
IoU... | 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... | DoJing/BASNet | IOU | false | 2,162 | [
"MIT"
] | 0 | 46bd3462326e6c7a02c90273c15da6fa71cec0e2 | https://github.com/DoJing/BASNet/tree/46bd3462326e6c7a02c90273c15da6fa71cec0e2 |
Conv2dTime | # 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... | BeeQC/ANODE-reproducibility | Conv2dTime | false | 146 | [
"MIT"
] | 0 | 9d6b5a297302cdaa0bbc3908de1a94f3c28c0606 | https://github.com/BeeQC/ANODE-reproducibility/tree/9d6b5a297302cdaa0bbc3908de1a94f3c28c0606 |
Gradient | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | RunqiuBao/Event_ESTRNN | Gradient | false | 14,339 | [
"MIT"
] | 180 | 6d156cc42a3a33bd0b4b7c4c4be98f943ff53acb | https://github.com/RunqiuBao/Event_ESTRNN/tree/6d156cc42a3a33bd0b4b7c4c4be98f943ff53acb |
KeypointsMSESmoothLoss | # 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
import torch
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cud... | yihui-he2020/epipolar-transformers | KeypointsMSESmoothLoss | false | 16,762 | [
"MIT"
] | 360 | 6824f4345b2998500fbacd0f4e30f67f8e3da7b8 | https://github.com/yihui-he2020/epipolar-transformers/tree/6824f4345b2998500fbacd0f4e30f67f8e3da7b8 |
Copy | # 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... | ChansongJo/DAMD | Copy | false | 7,863 | [
"Apache-2.0"
] | 39 | 9b0456d7e590fb5de77ec81e967e8010487eeb56 | https://github.com/ChansongJo/DAMD/tree/9b0456d7e590fb5de77ec81e967e8010487eeb56 |
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.... | markheimann/fgc | GAT | false | 12,773 | [
"MIT"
] | 0 | 909d4f0a84c9b61a8030f9f3f50b17f143576007 | https://github.com/markheimann/fgc/tree/909d4f0a84c9b61a8030f9f3f50b17f143576007 |
AveragePooling | import torch
import torch.nn as nn
class AveragePooling(nn.Module):
def __init__(self):
super(AveragePooling, self).__init__()
"""
(item, subitem) can be (word, characters), or (sentence, words)
x: num_items x max_subitem_size x input_size
x_mask: num_items x max_subitem_size
retu... | 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... | mpandeydev/SDnetmod | AveragePooling | false | 7,272 | [
"MIT"
] | 1 | c8cdf6150e3cd28330359a7d81df236729522a69 | https://github.com/mpandeydev/SDnetmod/tree/c8cdf6150e3cd28330359a7d81df236729522a69 |
decoderVH | # 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.... | Miles629/TransparentShapeRealData | decoderVH | false | 14,077 | [
"MIT"
] | 91 | b81098a2d1882f5fd33fba6167d7258dbe02d6d2 | https://github.com/Miles629/TransparentShapeRealData/tree/b81098a2d1882f5fd33fba6167d7258dbe02d6d2 |
ProjectionInputPose | # 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_... | aliyun/dro-sfm | ProjectionInputPose | false | 14,818 | [
"MIT"
] | 147 | 8707e2e0ef799d7d47418a018060f503ef449fe3 | https://github.com/aliyun/dro-sfm/tree/8707e2e0ef799d7d47418a018060f503ef449fe3 |
BellMembFunc | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | samxu0823/anfis-pytorch | BellMembFunc | false | 4,265 | [
"MIT"
] | 0 | b4ec3f0e8259963800e9e0a2904a580d1e56cc1c | https://github.com/samxu0823/anfis-pytorch/tree/b4ec3f0e8259963800e9e0a2904a580d1e56cc1c |
SineODE | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stri... | navaro1/parking_prediction | SineODE | false | 12,888 | [
"MIT"
] | 0 | c532a2f75155abc9c0d4be9c955eabe368591932 | https://github.com/navaro1/parking_prediction/tree/c532a2f75155abc9c0d4be9c955eabe368591932 |
MLP | import torch
import torch.nn as nn
class MLP(nn.Module):
"""
Create a multilayer perceptron model with variable hidden layers.
The network will have the specified number of layers and neurons,
with each layer using the leaky ReLU activation function.
Parameters
----------
input_dim : int... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | wfondrie/wefpy | MLP | false | 13,094 | [
"Apache-2.0"
] | 0 | 00691d453048203e1e3b1daea53879067ee4a395 | https://github.com/wfondrie/wefpy/tree/00691d453048203e1e3b1daea53879067ee4a395 |
DRRN | import torch
import torch.nn as nn
from math import sqrt
class DRRN(nn.Module):
def __init__(self):
super(DRRN, self).__init__()
self.input = nn.Conv2d(in_channels=1, out_channels=128, kernel_size
=3, stride=1, padding=1, bias=False)
self.conv1 = nn.Conv2d(in_channels=128, out... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from ma... | loyo1990/DRRN-pytorch | DRRN | false | 10,425 | [
"MIT"
] | 0 | 63d7dfd4c6bcb4f7b668fc2f5b4e2031cbba6619 | https://github.com/loyo1990/DRRN-pytorch/tree/63d7dfd4c6bcb4f7b668fc2f5b4e2031cbba6619 |
Permute | import torch
import torch.nn as nn
class Permute(nn.Module):
def __init__(self, permutation=[2, 1, 0]):
super().__init__()
self.permutation = permutation
def forward(self, input):
return input[:, self.permutation]
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_in... | 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... | beibuwandeluori/Attack-ImageNet-tianchi | Permute | false | 3,196 | [
"MIT"
] | 0 | 85294952ac1a190c26bba5e8f141b1c68e72668a | https://github.com/beibuwandeluori/Attack-ImageNet-tianchi/tree/85294952ac1a190c26bba5e8f141b1c68e72668a |
CrossEntropy | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
i... | uncharted-distil/d3m-primitives | CrossEntropy | false | 13,057 | [
"Apache-2.0"
] | 0 | e8d37dbe302c0f2bae4e7f7fa241a46faebc9b79 | https://github.com/uncharted-distil/d3m-primitives/tree/e8d37dbe302c0f2bae4e7f7fa241a46faebc9b79 |
Lambda | import torch
import torch.nn as nn
class Lambda(nn.Module):
def forward(self, t, y):
t = t.unsqueeze(0)
equation = -1000 * y + 3000 - 2000 * torch.exp(-t)
return equation
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_inputs():
retur... | 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... | arnabgho/torchdiffeq | Lambda | false | 3,192 | [
"MIT"
] | 0 | d4f73440d0e714b87ea133610e61eefbd673e5f5 | https://github.com/arnabgho/torchdiffeq/tree/d4f73440d0e714b87ea133610e61eefbd673e5f5 |
DRRN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from ma... | loyo1990/DRRN-pytorch | DRRN | false | 10,425 | [
"MIT"
] | 0 | 63d7dfd4c6bcb4f7b668fc2f5b4e2031cbba6619 | https://github.com/loyo1990/DRRN-pytorch/tree/63d7dfd4c6bcb4f7b668fc2f5b4e2031cbba6619 |
ReOrgLayer | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
import torch.utils.data.distributed
import torch._utils
assert_size_stride = torch._C._dynamo.... | Humoon/motion_reconstruction | ReOrgLayer | false | 2,351 | [
"BSD-3-Clause"
] | 0 | 9f0d0af3aeafa97455ec19dc4988f1577005c294 | https://github.com/Humoon/motion_reconstruction/tree/9f0d0af3aeafa97455ec19dc4988f1577005c294 |
BertSelfAttention | from _paritybench_helpers import _mock_config
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class BertSelfAttention(nn.Module):
def __init__(self, config):
super().__init__()
self.num_attention_heads = config.num_attention_heads
self.attention_head_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.... | sleepope/cs769-assignments | BertSelfAttention | false | 13,000 | [
"MIT"
] | 0 | 36c7a75d39507b7fe7b2b1bf1de6b8033b110da5 | https://github.com/sleepope/cs769-assignments/tree/36c7a75d39507b7fe7b2b1bf1de6b8033b110da5 |
BilinearClassifyBlock | # 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.... | caijh33/I3D_CTC | BilinearClassifyBlock | false | 9,920 | [
"Apache-2.0"
] | 0 | dd73ece2b810eed775fc847b7017080902e9c260 | https://github.com/caijh33/I3D_CTC/tree/dd73ece2b810eed775fc847b7017080902e9c260 |
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.triton_helpers import math... | Hassan-Lee/FusionModelingOfUser-GeneratedReviewDataOfComplexHeterogeneousTypes | VAE | false | 5,280 | [
"MIT"
] | 1 | b863e3fbf8058ecb06246a843e3fd2568bbbf260 | https://github.com/Hassan-Lee/FusionModelingOfUser-GeneratedReviewDataOfComplexHeterogeneousTypes/tree/b863e3fbf8058ecb06246a843e3fd2568bbbf260 |
InteractingLayer | # 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.... | dulvqingyunLT/DeepCTR-Torch | InteractingLayer | false | 10,427 | [
"Apache-2.0"
] | 0 | f40cf08f3469aa471f9ca69e44c5de51180341cc | https://github.com/dulvqingyunLT/DeepCTR-Torch/tree/f40cf08f3469aa471f9ca69e44c5de51180341cc |
GlobalAvgPool2d | import torch
import torch.nn as nn
import torch.nn.functional as F
class GlobalAvgPool2d(nn.Module):
def __init__(self):
super(GlobalAvgPool2d, self).__init__()
def forward(self, x):
N = x.data.size(0)
C = x.data.size(1)
H = x.data.size(2)
W = x.data.size(3)
x... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | CoDaS-Lab/Contextual-Adversarial-Patches | GlobalAvgPool2d | false | 2,100 | [
"MIT"
] | 0 | ffbd897174fc381ba7c3ba1e6f827b84ccb30fd4 | https://github.com/CoDaS-Lab/Contextual-Adversarial-Patches/tree/ffbd897174fc381ba7c3ba1e6f827b84ccb30fd4 |
MultiHeadAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cu... | igorvlnascimento/open-nre | MultiHeadAttention | false | 12,521 | [
"MIT"
] | 0 | a6e42ef074d62be4d3ceb571f412d5be8c0502d7 | https://github.com/igorvlnascimento/open-nre/tree/a6e42ef074d62be4d3ceb571f412d5be8c0502d7 |
Critic | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | gntoni/pytorch-ddpg-naf | Critic | false | 12,466 | [
"MIT"
] | 0 | d208d0c0c38a9d2d2041f1e7e95695359eba430e | https://github.com/gntoni/pytorch-ddpg-naf/tree/d208d0c0c38a9d2d2041f1e7e95695359eba430e |
SFT_torch | # 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.... | CoinCheung/SFT-ReID | SFT_torch | false | 8,186 | [
"MIT"
] | 22 | 2df67554732393df5a231b7281e12fc3435f1e8c | https://github.com/CoinCheung/SFT-ReID/tree/2df67554732393df5a231b7281e12fc3435f1e8c |
L2Distance | # 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
from torch import nn
import torch.autograd
assert_size_stride = torch._C._dynam... | cassidylaidlaw/perceptual-advex | L2Distance | false | 15,010 | [
"MIT"
] | 45 | d39136eb5b5e950442456ddade6b4f4fba3dd8f6 | https://github.com/cassidylaidlaw/perceptual-advex/tree/d39136eb5b5e950442456ddade6b4f4fba3dd8f6 |
GRULRCell | import torch
import torch.nn as nn
import torch.onnx
from itertools import product as product
def gen_nonlinearity(A, nonlinearity):
"""
Returns required activation for a tensor based on the inputs
nonlinearity is either a callable or a value in
['tanh', 'sigmoid', 'relu', 'quantTanh', 'quantSigm... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | ShishirPatil/EdgeML-1 | GRULRCell | false | 1,073 | [
"MIT"
] | 0 | cbba9f8b989e545788427c004eb8450e7e4c1a21 | https://github.com/ShishirPatil/EdgeML-1/tree/cbba9f8b989e545788427c004eb8450e7e4c1a21 |
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
import math
from torch import Tensor
from torch.nn import Parameter
import torch... | pwycl/pytorch_geometric | Linear | false | 10,774 | [
"MIT"
] | 0 | ef7b1add2bb5a36a3a68cae7639c42000f629cac | https://github.com/pwycl/pytorch_geometric/tree/ef7b1add2bb5a36a3a68cae7639c42000f629cac |
ValueNetwork | import torch
import torch.nn as nn
import torch.nn.functional as F
class ValueNetwork(nn.Module):
def __init__(self, state_dim, hidden_dim, init_w=0.003):
super(ValueNetwork, self).__init__()
self.linear1 = nn.Linear(state_dim, hidden_dim)
self.linear2 = nn.Linear(hidden_dim, 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
import torch.nn as nn
assert_... | FTC-8856/SAC | ValueNetwork | false | 9,042 | [
"MIT"
] | 0 | 98898d2c4b2ae99b74a8b5a6934d5d3cb91fe5f4 | https://github.com/FTC-8856/SAC/tree/98898d2c4b2ae99b74a8b5a6934d5d3cb91fe5f4 |
Hardsigmoid | import torch
from torch import Tensor
from torch import nn
class Hardsigmoid(nn.Module):
def __init__(self) ->None:
super().__init__()
def forward(self, x: 'Tensor') ->Tensor:
x = (0.2 * x + 0.5).clamp(min=0.0, max=1.0)
return x
def get_inputs():
return [torch.rand([4, 4, 4, 4]... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | Jo951128/2021-2-MIP | Hardsigmoid | false | 2,429 | [
"MIT"
] | 0 | 511e0a38816d16fdba9631f76cf913ba51c43138 | https://github.com/Jo951128/2021-2-MIP/tree/511e0a38816d16fdba9631f76cf913ba51c43138 |
LocallyConnected | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.a... | FrankTianTT/notears | LocallyConnected | false | 9,028 | [
"Apache-2.0"
] | 0 | ead1e4fa966e29343a393d637320f98ee0cada7c | https://github.com/FrankTianTT/notears/tree/ead1e4fa966e29343a393d637320f98ee0cada7c |
ScaledLeakyReLU | # 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... | BinahHu/stylegan2-pytorch | ScaledLeakyReLU | false | 155 | [
"MIT",
"BSD-2-Clause",
"Apache-2.0"
] | 0 | 9975707ffd93872fce02f7e3654eb588a09e23e4 | https://github.com/BinahHu/stylegan2-pytorch/tree/9975707ffd93872fce02f7e3654eb588a09e23e4 |
InnerProductDecoder | # 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 import nn
import torch.nn.modules.loss
from scipy.sparse import *
ass... | IBM/graph4nlp | InnerProductDecoder | false | 8,338 | [
"Apache-2.0"
] | 18 | a9bf20b23fa1ec368d9bd40cc8c557f86a9f8297 | https://github.com/IBM/graph4nlp/tree/a9bf20b23fa1ec368d9bd40cc8c557f86a9f8297 |
_DualSpanningAvgPool | import torch
from torch import nn
from typing import *
class _DualSpanningAvgPool(nn.Module):
"""Module with two average pools: one that spans the full height of the image and
another the spans the full width. Outputs are flattened and concatenated.
Args:
rows (int): Number of rows in image.
... | 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
from typing import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dyn... | HughMun/MultiBench | _DualSpanningAvgPool | false | 13,799 | [
"MIT"
] | 148 | d5712a0815a9486b0e0c76b54cd63c880188fc8e | https://github.com/HughMun/MultiBench/tree/d5712a0815a9486b0e0c76b54cd63c880188fc8e |
CecaModule | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
import torch.nn.parallel
assert_size_stride = ... | Fanzhongjie/ARFE | CecaModule | false | 459 | [
"Apache-2.0"
] | 0 | 4b96b8c5bc0895d3d30acec2a490f81a860fe860 | https://github.com/Fanzhongjie/ARFE/tree/4b96b8c5bc0895d3d30acec2a490f81a860fe860 |
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_... | arcada-uas/intro-to-dl | Net | false | 1,481 | [
"MIT"
] | 0 | 675741ad123e88158ecab88f887ea31113c99e7a | https://github.com/arcada-uas/intro-to-dl/tree/675741ad123e88158ecab88f887ea31113c99e7a |
ResidualBlock | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guard... | Weiyuhong-1998/DI-engine | ResidualBlock | false | 14,573 | [
"Apache-2.0"
] | 464 | 88658ea358298c6e61e95a454284b8853a3e9484 | https://github.com/Weiyuhong-1998/DI-engine/tree/88658ea358298c6e61e95a454284b8853a3e9484 |
Critic | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | jordiriu/MP-DQN | Critic | false | 15,774 | [
"MIT"
] | 75 | eec13eb9b4e2c0099649e0639f2a8b93d7d0d5be | https://github.com/jordiriu/MP-DQN/tree/eec13eb9b4e2c0099649e0639f2a8b93d7d0d5be |
Mul | import torch
import torch as ch
class Mul(ch.nn.Module):
def __init__(self, weight):
super(Mul, self).__init__()
self.weight = weight
def forward(self, x):
return x * self.weight
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {'weig... | 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 ch
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strid... | njwfish/ffcv | Mul | false | 10,598 | [
"Apache-2.0"
] | 0 | 3c219787da2fb8dbdaab24e75f34b3398ad7b7d1 | https://github.com/njwfish/ffcv/tree/3c219787da2fb8dbdaab24e75f34b3398ad7b7d1 |
PoswiseFeedForwardNet | # 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 ... | star14ms/transformer-evolution | PoswiseFeedForwardNet | false | 4,409 | [
"Apache-2.0"
] | 0 | 95b57485f59a0cee4528af62e5010002e6a3448a | https://github.com/star14ms/transformer-evolution/tree/95b57485f59a0cee4528af62e5010002e6a3448a |
BertOutput | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.utils.checkpoint
class BertOutput(nn.Module):
def __init__(self, config):
super().__init__()
self.dense = nn.Linear(config.intermediate_size, config.hidden_size)
self.LayerNorm = nn.LayerNorm(con... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | MikeWangWZHL/BLIP | BertOutput | false | 1,883 | [
"BSD-3-Clause"
] | 0 | b82134f1892a54c8f63b0f4b51bdcb8684e1dc6d | https://github.com/MikeWangWZHL/BLIP/tree/b82134f1892a54c8f63b0f4b51bdcb8684e1dc6d |
DQN | # 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_... | Ourdin/Phantom-of-the-Opera | DQN | false | 5,715 | [
"MIT"
] | 1 | c1ade346fadd40f6ca79033b8c6f3f74ce949d08 | https://github.com/Ourdin/Phantom-of-the-Opera/tree/c1ade346fadd40f6ca79033b8c6f3f74ce949d08 |
FeedForward | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | aim-uofa/DyCo3D | FeedForward | false | 14,777 | [
"BSD-2-Clause"
] | 100 | 17d22c2d839c0a1043fb72df301e3935af5ca0e9 | https://github.com/aim-uofa/DyCo3D/tree/17d22c2d839c0a1043fb72df301e3935af5ca0e9 |
Fusion3_FCLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | RUCAIBox/WSDM2022-C2CRS | Fusion3_FCLayer | false | 17,845 | [
"MIT"
] | 4 | 8ef2fa7c44bdba1799ab79f379ae7394bd468c02 | https://github.com/RUCAIBox/WSDM2022-C2CRS/tree/8ef2fa7c44bdba1799ab79f379ae7394bd468c02 |
Attention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | ppujol76/-Pere_Transformers | Attention | false | 12,916 | [
"MIT"
] | 0 | e267bcc6559c998accaed647cacbff253031f8b0 | https://github.com/ppujol76/-Pere_Transformers/tree/e267bcc6559c998accaed647cacbff253031f8b0 |
BridgeConnection | # 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.... | Harbar-Inbound/BMT | BridgeConnection | false | 11,861 | [
"MIT"
] | 0 | ec8826f0633db754c7ea8d206672aa0b6b6048fd | https://github.com/Harbar-Inbound/BMT/tree/ec8826f0633db754c7ea8d206672aa0b6b6048fd |
TwoMLPHead | import torch
import torch.utils.data
from torch import nn
from torchvision.transforms import functional as F
import torch.nn.functional as F
class TwoMLPHead(nn.Module):
"""
Heads for FPN for classification
"""
def __init__(self, in_channels, representation_size):
super(TwoMLPHead, self).__in... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
from ... | billchenxi/vision | TwoMLPHead | false | 1,548 | [
"BSD-3-Clause"
] | 0 | 5608b06a6fbc9c84284dad9f07a16df61da10f85 | https://github.com/billchenxi/vision/tree/5608b06a6fbc9c84284dad9f07a16df61da10f85 |
SelfAttention | import torch
import torch.nn as nn
from torch.nn import functional as F
def mask_fn(x, mask_diagonal=False):
_b, h, w = x.size()
indices = torch.triu_indices(h, w, offset=0 if mask_diagonal else 1)
mask = torch.zeros_like(x)
mask[:, indices[0], indices[1]] = 1
final_mask = (mask == 1) & (x == 0)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | MukundhMurthy/viral-mutation | SelfAttention | false | 9,335 | [
"MIT"
] | 0 | 371422e418e8adc1ab9e68d2f09bd2f8aa5f00f0 | https://github.com/MukundhMurthy/viral-mutation/tree/371422e418e8adc1ab9e68d2f09bd2f8aa5f00f0 |
CPUForgetMult | # 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.init
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | FurKan7/resim_renklendirme-colorizing-of-picture- | CPUForgetMult | false | 17,290 | [
"MIT"
] | 8 | a431a42cd00a60f85948795bc872a272897fbc76 | https://github.com/FurKan7/resim_renklendirme-colorizing-of-picture-/tree/a431a42cd00a60f85948795bc872a272897fbc76 |
ArcMarginProduct_subcenter | # 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.... | Fkaneko/kaggle-hpa-single-cell-image-classification | ArcMarginProduct_subcenter | false | 5,170 | [
"MIT"
] | 1 | 52000cbf5c7eec6ace29274d9e85b5b24fac281b | https://github.com/Fkaneko/kaggle-hpa-single-cell-image-classification/tree/52000cbf5c7eec6ace29274d9e85b5b24fac281b |
RSoftmax | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
a... | Bo396543018/Picodet_Pytorch | RSoftmax | false | 7,791 | [
"Apache-2.0"
] | 16 | 276ecbf6f4f7eefbf046d1bccc25293acf28ba25 | https://github.com/Bo396543018/Picodet_Pytorch/tree/276ecbf6f4f7eefbf046d1bccc25293acf28ba25 |
GaussianMixtureReconstructionLoss | import torch
import numpy as np
import torch as th
def gaussian_pdfs(dx, dy, params):
"""Returns the pdf at (dx, dy) for each Gaussian in the mixture.
"""
dx = dx.unsqueeze(-1)
dy = dy.unsqueeze(-1)
mu_x = params[..., 0]
mu_y = params[..., 1]
sigma_x = params[..., 2].exp()
sigma_y = pa... | 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 nump... | v-a-s-a/diffvg | GaussianMixtureReconstructionLoss | false | 4,479 | [
"Apache-2.0"
] | 0 | 3685f3d47a5a4e5c76c68643ebf383f809ba59ed | https://github.com/v-a-s-a/diffvg/tree/3685f3d47a5a4e5c76c68643ebf383f809ba59ed |
UNet | import torch
import torch.nn as nn
import torch.nn.functional as F
def Conv(in_channels, out_channels):
return nn.Conv2d(in_channels, out_channels, 3, padding=1)
def concat(a, b):
return torch.cat((a, b), 1)
def pool(x):
return F.max_pool2d(x, 2, 2)
def relu(x):
return F.relu(x, inplace=True)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | arpan-dhatt/oidn | UNet | false | 14,956 | [
"Apache-2.0"
] | 1,206 | 9419411ba4b343b475b53587cadd44c83d68dc2a | https://github.com/arpan-dhatt/oidn/tree/9419411ba4b343b475b53587cadd44c83d68dc2a |
AngleError | # 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.... | ai-in-motion/moai | AngleError | false | 18,328 | [
"Apache-2.0"
] | 10 | e38cac046c059d2e2331ef4883bbabc5a500a5cf | https://github.com/ai-in-motion/moai/tree/e38cac046c059d2e2331ef4883bbabc5a500a5cf |
HardSigmoid | import torch
import torch.nn as nn
class HardSigmoid(nn.Module):
def __init__(self, bias=1.0, divisor=2.0, min_value=0.0, max_value=1.0):
super(HardSigmoid, self).__init__()
assert divisor != 0, 'divisor is not allowed to be equal to zero'
self.bias = bias
self.divisor = divisor
... | 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... | CharlesPikachu/mcibi | HardSigmoid | false | 7,885 | [
"MIT"
] | 41 | 6ce453504741c2eed1d290306055258a377a4094 | https://github.com/CharlesPikachu/mcibi/tree/6ce453504741c2eed1d290306055258a377a4094 |
BertSelfAttention | from _paritybench_helpers import _mock_config
import math
import torch
import torch.optim
import torch
import torch.nn as nn
class BertSelfAttention(nn.Module):
def __init__(self, config):
super(BertSelfAttention, self).__init__()
if config.hidden_size % config.num_attention_heads != 0:
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | DengBoCong/text-sim | BertSelfAttention | false | 8,779 | [
"MIT"
] | 21 | 2c6c323649aa259a7b3d5c6d3714bd1860114826 | https://github.com/DengBoCong/text-sim/tree/2c6c323649aa259a7b3d5c6d3714bd1860114826 |
Add | # 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 | Add | false | 4,704 | [
"MIT"
] | 0 | 37c1ebfc3547e93b1c174721036d03c831c60e48 | https://github.com/yifanpu001/PytorchToCaffe/tree/37c1ebfc3547e93b1c174721036d03c831c60e48 |
BertAttention | from _paritybench_helpers import _mock_config
import math
import torch
import torch.utils.data
import torch.nn as nn
import torch.nn
import torch as torch
import torch.sparse
class BertSelfAttention(nn.Module):
def __init__(self, config):
super(BertSelfAttention, self).__init__()
if config.hidden... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Somefive/cogdl | BertAttention | false | 5,848 | [
"MIT"
] | 1 | 1c5ab88aafc27529495d0d22f781055619e27cb2 | https://github.com/Somefive/cogdl/tree/1c5ab88aafc27529495d0d22f781055619e27cb2 |
GlobalAvgPool2d | import torch
from torch import nn
from torch.nn import functional as F
class GlobalAvgPool2d(nn.Module):
def __init__(self):
"""
Global Average pooling module
"""
super(GlobalAvgPool2d, self).__init__()
def forward(self, x):
"""
The forward function of the Glo... | 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... | UniSerj/ai-research | GlobalAvgPool2d | false | 14,521 | [
"Apache-2.0"
] | 46 | 79f0093c93408cc5dd7d3f56aafd7dc1f901421c | https://github.com/UniSerj/ai-research/tree/79f0093c93408cc5dd7d3f56aafd7dc1f901421c |
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.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Alan-Paul/ECN | Normalize | false | 11,147 | [
"Apache-2.0"
] | 0 | 5e9a9081ff0c1e36cc0381df3ce9038a79a537e9 | https://github.com/Alan-Paul/ECN/tree/5e9a9081ff0c1e36cc0381df3ce9038a79a537e9 |
ExpMSE | import torch
from torch import nn
def _assert_no_grad(tensor):
assert not tensor.requires_grad
class ExpMSE(nn.Module):
def __init__(self, lam):
super().__init__()
self.lam = lam
def forward(self, output, target):
_assert_no_grad(target)
loss = (output - target).pow(2)
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
a... | dattientran/attorch | ExpMSE | false | 12,384 | [
"MIT"
] | 0 | 469b225846c6d8a7d833ebac19d040c7a407a0ff | https://github.com/dattientran/attorch/tree/469b225846c6d8a7d833ebac19d040c7a407a0ff |
GELU | import torch
import numpy as np
import torch.nn as nn
class GELU(nn.Module):
"""Gaussian Error Linear Unit.
Dan Hendrycks∗, Kevin Gimpel
GAUSSIAN ERROR LINEAR UNITS (GELUS), 2016
Args:
x: float Tensor to perform activation.
Returns:
`x` with the GELU activation applied.
"""
... | 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_... | joeization/CycleGAN | GELU | false | 3,748 | [
"MIT"
] | 0 | 9635c8e3a7b1634b2e2eb5b5299f03a4e0786868 | https://github.com/joeization/CycleGAN/tree/9635c8e3a7b1634b2e2eb5b5299f03a4e0786868 |
LayerNorm | import torch
import torch.utils.data
import torch.nn as nn
class LayerNorm(nn.Module):
"""
Construct a layernorm module (See citation for details).
"""
def __init__(self, features, eps=1e-06):
super(LayerNorm, self).__init__()
self.a_2 = nn.Parameter(torch.ones(features))
self... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.data
import torch.nn as nn
assert_size_stride = torch._C._dy... | Akhil-Raj/Trajectory-Transformer | LayerNorm | false | 4 | [
"MIT"
] | 0 | dd09fda99443f6afb59d962026573162219ea6a9 | https://github.com/Akhil-Raj/Trajectory-Transformer/tree/dd09fda99443f6afb59d962026573162219ea6a9 |
ShiftedSoftplus | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.tensorboard
class ShiftedSoftplus(nn.Module):
def __init__(self):
super().__init__()
self.shift = torch.log(torch.tensor(2.0)).item()
def forward(self, x):
return F.softplus(x) - self.shift
def ge... | 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.utils.tensorboard
assert_si... | Dieg0Alejandr0/3D-Generative-SBDD | ShiftedSoftplus | false | 1,220 | [
"MIT"
] | 0 | 51ffd36a6cf5048eeff6e68186a4608048feea4c | https://github.com/Dieg0Alejandr0/3D-Generative-SBDD/tree/51ffd36a6cf5048eeff6e68186a4608048feea4c |
MaxRotationPoolP4 | # 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... | claudio-unipv/groupcnn | MaxRotationPoolP4 | false | 12,229 | [
"MIT"
] | 0 | 2b1514f5a0fb9a78c6f646e1c075e5c3d5af9c0c | https://github.com/claudio-unipv/groupcnn/tree/2b1514f5a0fb9a78c6f646e1c075e5c3d5af9c0c |
SoftDetectionModule | import torch
import torch.nn.functional as F
import torch.nn as nn
class SoftDetectionModule(nn.Module):
def __init__(self, soft_local_max_size=3):
super(SoftDetectionModule, self).__init__()
self.soft_local_max_size = soft_local_max_size
self.pad = self.soft_local_max_size // 2
def ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | liuyuzhenn/d2-net | SoftDetectionModule | false | 15,925 | [
"BSD-3-Clause-Clear"
] | 603 | bc3394934c87cba232144756b1fece4c8ed3aba1 | https://github.com/liuyuzhenn/d2-net/tree/bc3394934c87cba232144756b1fece4c8ed3aba1 |
VdConv1D | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
def calculate_kl(log_alpha):
return 0.5 * torch.sum(torch.log1p(torch.exp(-log_alpha)))
class VdConv1D(nn.Module):
"""
Conv1D Layer variational dropout
"""
def __init__(self, in_channels, out_channels, 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.triton_helpers import libdevice, math as tl_math
im... | Neronjust2017/pytorch-classification-project | VdConv1D | false | 886 | [
"MIT"
] | 0 | fc5f4d7c46d071765f682ce20e6580646d4e5c76 | https://github.com/Neronjust2017/pytorch-classification-project/tree/fc5f4d7c46d071765f682ce20e6580646d4e5c76 |
Block | import torch
import torch.nn as nn
from functools import partial
class Mlp(nn.Module):
def __init__(self, in_features, hidden_features=None, out_features=None,
act_layer=nn.GELU, drop=0.0):
super().__init__()
out_features = out_features or in_features
hidden_features = hidden_feat... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | xuewengeophysics/Conformer | Block | false | 13,141 | [
"Apache-2.0"
] | 0 | e769a1ac9ab110dae2a356a4de1e06ccd0e95041 | https://github.com/xuewengeophysics/Conformer/tree/e769a1ac9ab110dae2a356a4de1e06ccd0e95041 |
QNetwork | import torch
import torch.nn as nn
import torch.nn.functional as F
class QNetwork(nn.Module):
"""Actor (Policy) Model. Deep Net function approximator for q(s,a)"""
def __init__(self, state_size, action_size, seed):
"""Initialize parameters and build model.
Parameters:
==========
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | andreaspts/DRL_LUNAR_LANDER | QNetwork | false | 3,111 | [
"MIT"
] | 0 | 61f19b294ba7ed069795c70a3ceca4d9f7ff8a66 | https://github.com/andreaspts/DRL_LUNAR_LANDER/tree/61f19b294ba7ed069795c70a3ceca4d9f7ff8a66 |
AttNet | # 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.... | SionHu/LP-MOT | AttNet | false | 1,080 | [
"MIT"
] | 0 | 90e6a1d51ebe1a948ac5c018a5ee560654e824f1 | https://github.com/SionHu/LP-MOT/tree/90e6a1d51ebe1a948ac5c018a5ee560654e824f1 |
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