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 |
|---|---|---|---|---|---|---|---|---|---|---|
SelfAttentive | # 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.... | OLUWAMUYIWA/sent_analysis | SelfAttentive | false | 9,402 | [
"MIT"
] | 0 | 16334d9f5f2bad1135763c6e8cbe3d7272237d73 | https://github.com/OLUWAMUYIWA/sent_analysis/tree/16334d9f5f2bad1135763c6e8cbe3d7272237d73 |
CustomNet | import torch
import torch.nn as nn
class CustomNet(nn.Module):
"""
A network with a fully connected layer followed by a sigmoid layer. This is
used for testing customized operation handles.
"""
def __init__(self, input_dim: 'int', output_dim: 'int') ->None:
super(CustomNet, 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | DenXX/fvcore | CustomNet | false | 2,206 | [
"Apache-2.0"
] | 0 | 4b91cf092f4f5d379b2c93398780a3b5755e7179 | https://github.com/DenXX/fvcore/tree/4b91cf092f4f5d379b2c93398780a3b5755e7179 |
FCNet | import torch
import torch.nn as nn
from torch.nn.utils import weight_norm
import torch.utils.data
class FCNet(nn.Module):
def __init__(self, in_size, out_size, activate=None, drop=0.0):
super(FCNet, self).__init__()
self.lin = weight_norm(nn.Linear(in_size, out_size), dim=None)
self.drop_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | KaihuaTang/VQA2.0-Recent-Approachs-2018.pytorch | FCNet | false | 13,937 | [
"MIT"
] | 298 | 52e1ba5a7f3b88c617115ccc755e2e7868e8de2b | https://github.com/KaihuaTang/VQA2.0-Recent-Approachs-2018.pytorch/tree/52e1ba5a7f3b88c617115ccc755e2e7868e8de2b |
ResidualBlockNoBN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from to... | cyysc1998/EDVRDarts | ResidualBlockNoBN | false | 6,548 | [
"MIT"
] | 1 | 201badbc8c6469b519647a8869c3782ebe1176cf | https://github.com/cyysc1998/EDVRDarts/tree/201badbc8c6469b519647a8869c3782ebe1176cf |
C3D | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | gramuah/gui4lola | C3D | false | 12,839 | [
"MIT"
] | 0 | 6924d681db3b14f9b10a53b115640a749a33e774 | https://github.com/gramuah/gui4lola/tree/6924d681db3b14f9b10a53b115640a749a33e774 |
Encoding | import torch
import torch.nn.functional as F
import torch.nn as nn
import torch._C
import torch.serialization
class Encoding(nn.Module):
"""Encoding Layer: a learnable residual encoder.
Input is of shape (batch_size, channels, height, width).
Output is of shape (batch_size, num_codes, channels).
Ar... | 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
... | HusterRC/mmsegmentation | Encoding | false | 5,325 | [
"Apache-2.0"
] | 1 | c3e4dbc2e06de3f47f75098f76772b4ee7e91e35 | https://github.com/HusterRC/mmsegmentation/tree/c3e4dbc2e06de3f47f75098f76772b4ee7e91e35 |
CnptAttention | # 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... | adonis704/ucas_2021_hc_15 | CnptAttention | false | 18,225 | [
"MIT"
] | 6 | 7308c3b32962ef5430d85ccfcb199ebe40bf4a7f | https://github.com/adonis704/ucas_2021_hc_15/tree/7308c3b32962ef5430d85ccfcb199ebe40bf4a7f |
Encoder | import torch
import torch.nn as nn
import torch.nn.functional as F
class Lambda(nn.Module):
"""An easy way to create a pytorch layer for a simple `func`."""
def __init__(self, func):
"""create a layer that simply calls `func` with `x`"""
super().__init__()
self.func = func
def fo... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | BHD233/PaddleOCR2Pytorch | Encoder | false | 13,377 | [
"Apache-2.0"
] | 364 | f114069b3e2669c6adf0adf9596756205f184c9c | https://github.com/BHD233/PaddleOCR2Pytorch/tree/f114069b3e2669c6adf0adf9596756205f184c9c |
AddNorm | import torch
import torch.nn.functional as F
import torch.nn as nn
class TimeDistributedInterpolation(nn.Module):
def __init__(self, output_size: 'int', batch_first: 'bool'=False,
trainable: 'bool'=False):
super().__init__()
self.output_size = output_size
self.batch_first = batch_... | 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.functional as F
import torch.nn as nn
assert_size_stride = torc... | JustinNeumann/pytorch-forecasting | AddNorm | false | 705 | [
"MIT"
] | 0 | 4f6e449cb3788b856e66c4283398a5db201aa6ff | https://github.com/JustinNeumann/pytorch-forecasting/tree/4f6e449cb3788b856e66c4283398a5db201aa6ff |
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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import functools
impor... | AnonSubmission6150/submission6150 | DiceLoss | false | 8,993 | [
"Apache-2.0"
] | 0 | 571633d9a12b4fd7a9546947787fc068966dab04 | https://github.com/AnonSubmission6150/submission6150/tree/571633d9a12b4fd7a9546947787fc068966dab04 |
EdgeGCN | from torch.nn import Module
import torch
from torch.nn.modules.module import Module
import torch.nn as nn
class EdgeGCN(Module):
"""
Simple GCN layer, similar to https://arxiv.org/abs/1609.02907
"""
def __init__(self, in_features, out_features, include_adj=True, bias=True):
super(EdgeGCN, sel... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch.nn... | hou-yz/pygcn | EdgeGCN | false | 3,629 | [
"MIT"
] | 0 | 26195954035c5eaae2d6e086cfec24cad2642f2e | https://github.com/hou-yz/pygcn/tree/26195954035c5eaae2d6e086cfec24cad2642f2e |
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.triton_helpers import libdevice
import numpy as np
... | rbak/deep-rl-udacity-project-3 | Actor | false | 12,930 | [
"MIT"
] | 0 | 4bf2aec6b0ef27636ebd11dfd4b442554208cffb | https://github.com/rbak/deep-rl-udacity-project-3/tree/4bf2aec6b0ef27636ebd11dfd4b442554208cffb |
PositionwiseFeedForward | import torch
import torch.nn as nn
class PositionwiseFeedForward(nn.Module):
"""Implements FFN equation."""
def __init__(self, d_model, d_ff, dropout=0.1):
super(PositionwiseFeedForward, self).__init__()
self.w_1 = nn.Linear(d_model, d_ff)
self.w_2 = nn.Linear(d_ff, d_model)
s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | Aminah92/saint | PositionwiseFeedForward | false | 16,886 | [
"MIT"
] | 7 | e18f5d5d093dce458c7d427eed4a375021c05bb9 | https://github.com/Aminah92/saint/tree/e18f5d5d093dce458c7d427eed4a375021c05bb9 |
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 ... | cjlovering/EGG | Critic | false | 10,055 | [
"MIT"
] | 0 | cce146e035decbc410e981f8bc7ada32979f3b6d | https://github.com/cjlovering/EGG/tree/cce146e035decbc410e981f8bc7ada32979f3b6d |
Conv2dSame | # 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.... | ChenFengYe/relightable-nr | Conv2dSame | false | 13,465 | [
"MIT"
] | 105 | 239a97406f4df01cf5786dcdde58e464395a682d | https://github.com/ChenFengYe/relightable-nr/tree/239a97406f4df01cf5786dcdde58e464395a682d |
BinaryParamAdd | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import abc
import inspect
import warnings
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
from typ... | Johnsonms/NNI_master | BinaryParamAdd | false | 11,573 | [
"MIT"
] | 0 | e5e5c7aed89cf3189cffe1056464833c15eb54ff | https://github.com/Johnsonms/NNI_master/tree/e5e5c7aed89cf3189cffe1056464833c15eb54ff |
AFTSimple | import torch
from torch import nn
class AFTSimple(nn.Module):
def __init__(self, max_seqlen, dim, hidden_dim=64):
super().__init__()
"""
max_seqlen: the maximum number of timesteps (sequence length) to be fed in
dim: the embedding dimension of the tokens
hidden_dim: the hi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Datta0/aft-pytorch | AFTSimple | false | 2,134 | [
"MIT"
] | 0 | a0ebad01ea6616b00bde319b0c5e63bea467c400 | https://github.com/Datta0/aft-pytorch/tree/a0ebad01ea6616b00bde319b0c5e63bea467c400 |
CoordConvSinAct | # 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
from torch im... | PeterouZh/CIPS-3D | CoordConvSinAct | false | 14,162 | [
"MIT"
] | 308 | 9b8bfa0fb23f642af042e150ccd70408f9d137c6 | https://github.com/PeterouZh/CIPS-3D/tree/9b8bfa0fb23f642af042e150ccd70408f9d137c6 |
MseCriterion | import torch
import torch.nn.functional as F
from torch.nn.modules.loss import _Loss
from torch.optim.lr_scheduler import *
class Criterion(_Loss):
def __init__(self, alpha=1.0, name='criterion'):
super().__init__()
"""Alpha is used to weight each loss term
"""
self.alpha = alpha
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn.modules.loss import _Loss
from torch.optim.lr_scheduler import *
assert_siz... | chunhuililili/mt_dnn | MseCriterion | false | 10,208 | [
"MIT"
] | 0 | 4c6efaf21724c7b8103a05e46b5b44d7b246225e | https://github.com/chunhuililili/mt_dnn/tree/4c6efaf21724c7b8103a05e46b5b44d7b246225e |
VectorQuantizer | import torch
from torch import nn
from torch.nn import functional as F
class VectorQuantizer(nn.Module):
"""
Reference:
[1] https://github.com/deepmind/sonnet/blob/v2/sonnet/src/nets/vqvae.py
"""
def __init__(self, num_embeddings: 'int', embedding_dim: 'int', beta:
'float'=0.25):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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... | threewisemonkeys-as/PyTorch-VAE | VectorQuantizer | false | 4,433 | [
"Apache-2.0"
] | 0 | 4ed0fc7581d4792b435134aa9e06d5e35a5db118 | https://github.com/threewisemonkeys-as/PyTorch-VAE/tree/4ed0fc7581d4792b435134aa9e06d5e35a5db118 |
encoder3 | # 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.... | SofiaValdiviesov/LinearStyleTransfer | encoder3 | false | 9,678 | [
"BSD-2-Clause"
] | 0 | 6837c6a9be16bb5981fa0744e5d23f61d08e6940 | https://github.com/SofiaValdiviesov/LinearStyleTransfer/tree/6837c6a9be16bb5981fa0744e5d23f61d08e6940 |
NoNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.utils.checkpoint
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | jxhe/unify-parameter-efficient-tuning | NoNorm | false | 15,770 | [
"Apache-2.0"
] | 101 | 3222ce2c0079566a28043e22380eb4ab6ad14389 | https://github.com/jxhe/unify-parameter-efficient-tuning/tree/3222ce2c0079566a28043e22380eb4ab6ad14389 |
ResidualBlock | import torch
import torch.nn as nn
class ResidualBlock(nn.Module):
def __init__(self, channels):
super(ResidualBlock, self).__init__()
self.conv1 = nn.Conv2d(channels, channels, kernel_size=3, padding=1)
self.in1 = nn.InstanceNorm2d(channels)
self.prelu = nn.PReLU()
self.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.triton_helpers import libdevice
import torch.nn as ... | generall/Torchlite | ResidualBlock | false | 6,743 | [
"MIT"
] | 1 | 2eb3e2a20b7619bd58b0b0fca120e2aefca0e79a | https://github.com/generall/Torchlite/tree/2eb3e2a20b7619bd58b0b0fca120e2aefca0e79a |
tofp16 | # 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.functional
import torch.nn.parallel
import torch.utils.data
import torch.optim
import torch.utils.data... | DeanChan/apex | tofp16 | false | 9,016 | [
"BSD-3-Clause"
] | 0 | a03267e5e1209f559a6671da56c479a216f418d1 | https://github.com/DeanChan/apex/tree/a03267e5e1209f559a6671da56c479a216f418d1 |
Attention | import torch
import torch.nn as nn
class Attention(nn.Module):
def __init__(self, feature_dim, maxlen=70):
super().__init__()
self.attention_fc = nn.Linear(feature_dim, 1)
self.bias = nn.Parameter(torch.zeros(1, maxlen, 1, requires_grad=True))
def forward(self, rnn_output):
"... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | deepframwork/TorchBlocks | Attention | false | 6,542 | [
"MIT"
] | 1 | 35f6e1bb83d2b9b05ba914a21fd365cb26ac4a32 | https://github.com/deepframwork/TorchBlocks/tree/35f6e1bb83d2b9b05ba914a21fd365cb26ac4a32 |
ResidualBlock | # 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 ... | jonasvj/protein-generation | ResidualBlock | false | 3,776 | [
"MIT"
] | 0 | ad716f2dba6f6642a6d54571571e6f539cee3644 | https://github.com/jonasvj/protein-generation/tree/ad716f2dba6f6642a6d54571571e6f539cee3644 |
BertLayer | from _paritybench_helpers import _mock_config
import inspect
import math
import torch
from torch import nn
from typing import Callable
from typing import List
from typing import Set
from typing import Tuple
def find_pruneable_heads_and_indices(heads: 'List[int]', n_heads: 'int',
head_size: 'int', already_pruned_h... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | RyanWangZf/SurvTRACE | BertLayer | false | 18,392 | [
"MIT"
] | 8 | d55299a28629d233f49ad1feaea7ed00835f0dd0 | https://github.com/RyanWangZf/SurvTRACE/tree/d55299a28629d233f49ad1feaea7ed00835f0dd0 |
SA_block | # 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.... | reinforcementdriving/SA-Det3D | SA_block | false | 16,327 | [
"MIT"
] | 134 | 682cbf5a3023bd580632435d1e4e0acb0ae08ab8 | https://github.com/reinforcementdriving/SA-Det3D/tree/682cbf5a3023bd580632435d1e4e0acb0ae08ab8 |
HR2O_NL | import torch
import torch.nn as nn
class HR2O_NL(nn.Module):
def __init__(self, hidden_dim=512, kernel_size=3, mlp_1x1=False):
super(HR2O_NL, self).__init__()
self.hidden_dim = hidden_dim
padding = kernel_size // 2
self.conv_q = nn.Conv2d(hidden_dim, hidden_dim, 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.... | AlexandreDh/ACAR-Net | HR2O_NL | false | 13,472 | [
"Apache-2.0"
] | 162 | db28009388512e31cb6ff8e86725dc9b026886b6 | https://github.com/AlexandreDh/ACAR-Net/tree/db28009388512e31cb6ff8e86725dc9b026886b6 |
LinearAdditiveUpsample | import torch
import torch.utils.data
import torch
import torch.nn as nn
class LinearAdditiveUpsample(nn.Module):
"""Bi/Trilinear Additive Upsample
Upsampling strategy described in Wojna et al (https://doi.org/10.1007/s11263-019-01170-8) to avoid checkerboard
patterns while keeping a better performance fo... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
import torch
import torch.nn as nn
assert_size_stride = torch._C.... | giuliabaldini/Pix2PixNIfTI | LinearAdditiveUpsample | false | 3,544 | [
"BSD-3-Clause"
] | 0 | 59ff825760f682d2734bd5e95503a03f80d32414 | https://github.com/giuliabaldini/Pix2PixNIfTI/tree/59ff825760f682d2734bd5e95503a03f80d32414 |
MHA | from _paritybench_helpers import _mock_config
import math
import torch
import torch.nn as nn
class MHA(nn.Module):
def __init__(self, config):
super().__init__()
self.num_attention_heads = config.num_attention_heads
self.hidden_size = config.hidden_size
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.... | qinyiwei/MuTual | MHA | false | 4,168 | [
"MIT"
] | 0 | 3bdd13c1388d6136b8944666dfd434870760cc93 | https://github.com/qinyiwei/MuTual/tree/3bdd13c1388d6136b8944666dfd434870760cc93 |
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
import ... | jcolekaplan/computer_vision | Net | false | 12,603 | [
"MIT"
] | 0 | 48d39b081a7b6b699019052eeae36ab703bb34eb | https://github.com/jcolekaplan/computer_vision/tree/48d39b081a7b6b699019052eeae36ab703bb34eb |
BCEDiceLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch ... | ha55anali/pytorch-nested-unet | BCEDiceLoss | false | 10,189 | [
"MIT"
] | 0 | 444dbd0ff7764478de662723b211c23bd65d99f9 | https://github.com/ha55anali/pytorch-nested-unet/tree/444dbd0ff7764478de662723b211c23bd65d99f9 |
Actor | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | JiangengDong/ECE276C | Actor | false | 5,395 | [
"MIT"
] | 1 | 2338b5226d6fed8858402e8d67db7f2eead98221 | https://github.com/JiangengDong/ECE276C/tree/2338b5226d6fed8858402e8d67db7f2eead98221 |
TwoHiddenLayerFc | # 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_... | jasonyanglu/fedavgpy | TwoHiddenLayerFc | false | 6,927 | [
"MIT"
] | 1 | cefbe5854f02d3df1197d849872286439c86e949 | https://github.com/jasonyanglu/fedavgpy/tree/cefbe5854f02d3df1197d849872286439c86e949 |
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 ... | bage79/transformer-evolution-bage | PoswiseFeedForwardNet | false | 6,315 | [
"Apache-2.0"
] | 1 | 715bdf61421dc19e21fb0f66bfa4b564305987f8 | https://github.com/bage79/transformer-evolution-bage/tree/715bdf61421dc19e21fb0f66bfa4b564305987f8 |
TensorMax | import torch
def tensor_max(input, dim, keepdim=False):
if isinstance(dim, int):
return torch.max(input, dim=dim, keepdim=keepdim)[0]
else:
if isinstance(dim, tuple):
dim = list(dim)
for d in dim:
input = torch.max(input, dim=d, keepdim=keepdim)[0]
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 import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | Minyus/kedex | TensorMax | false | 9,692 | [
"Apache-2.0"
] | 0 | 92f952eed3cb6109bc783f449051f2bd13579d2a | https://github.com/Minyus/kedex/tree/92f952eed3cb6109bc783f449051f2bd13579d2a |
orientation_neuron | # 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... | AgamChopra/simulation-in-a-box | orientation_neuron | false | 11,173 | [
"MIT"
] | 0 | 2a346a2fc83d79e542b64f1bd45c338d27a1934d | https://github.com/AgamChopra/simulation-in-a-box/tree/2a346a2fc83d79e542b64f1bd45c338d27a1934d |
moving_avg | # 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... | MAZiqing/FEDformer | moving_avg | false | 17,649 | [
"MIT"
] | 7 | 7914d39df829494a8172afb9676982c3789d491d | https://github.com/MAZiqing/FEDformer/tree/7914d39df829494a8172afb9676982c3789d491d |
FeedForwardNeuralNetModel | # 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... | Hedingber/demos | FeedForwardNeuralNetModel | false | 13,776 | [
"Apache-2.0"
] | 64 | 6d1433ada6d44166cfcd11646276f2fffeff2fc0 | https://github.com/Hedingber/demos/tree/6d1433ada6d44166cfcd11646276f2fffeff2fc0 |
DPLSTMCell | import math
import torch
import torch.nn as nn
import torch.utils.data
import torch.utils.data.distributed
import torch.nn.parallel
from typing import Tuple
class LSTMLinear(nn.Linear):
"""
This function is the same as a nn.Linear layer, except that in the backward pass
the grad_samples get accumulated (i... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import ... | madhavajay/opacus | DPLSTMCell | false | 10,482 | [
"Apache-2.0"
] | 0 | 7ae098764b4cf2388c66e263dd8d56bca0a290d0 | https://github.com/madhavajay/opacus/tree/7ae098764b4cf2388c66e263dd8d56bca0a290d0 |
TestModel | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.fx
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.... | NVIDIA/Torch-TensorRT | TestModel | false | 14,086 | [
"BSD-3-Clause"
] | 430 | 1a22204fecec690bc3c2a318dab4f57b98c57f05 | https://github.com/NVIDIA/Torch-TensorRT/tree/1a22204fecec690bc3c2a318dab4f57b98c57f05 |
DistanceWiseRKD | import torch
from torch import nn
import torch.nn.functional as F
def euclidean_distance(pred, squared=False, eps=1e-12):
"""Calculate the Euclidean distance between the two examples in the output
representation space.
Args:
pred (torch.Tensor): The prediction of the teacher or student with
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
import ... | HIT-cwh/mmrazor | DistanceWiseRKD | false | 13,742 | [
"Apache-2.0"
] | 553 | 2dad24044d7f1dad88f20221f8fc071dd40fdd4f | https://github.com/HIT-cwh/mmrazor/tree/2dad24044d7f1dad88f20221f8fc071dd40fdd4f |
MultiHeadAttention | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
def attention(q, k, v, d_k, mask=None, dropout=None):
scores = torch.matmul(q, k.transpose(-2, -1)) / math.sqrt(d_k)
if mask is not None:
mask = mask.unsqueeze(1)
scores = scores.masked_fill(mask == 0, -1000000000.0... | 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.... | AviVarma/torchASN-Transformer | MultiHeadAttention | false | 107 | [
"MIT"
] | 0 | 55bccf4cdb099cd8e9ac99f5f87f989ce2add983 | https://github.com/AviVarma/torchASN-Transformer/tree/55bccf4cdb099cd8e9ac99f5f87f989ce2add983 |
EuclideanDistance | import torch
import torch as th
import torch.nn as nn
class EuclideanDistance(nn.Module):
def __init__(self):
super(EuclideanDistance, self).__init__()
self.m = nn.Sigmoid()
def forward(self, i, j):
i_norm = self.m(i)
j_norm = self.m(j)
return th.sqrt(th.sum((i_norm -... | 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_... | IBM/aihn-ucsd | EuclideanDistance | false | 8,281 | [
"Apache-2.0"
] | 20 | 6c6a56d11c704b529a31868418e350e9760ff9d9 | https://github.com/IBM/aihn-ucsd/tree/6c6a56d11c704b529a31868418e350e9760ff9d9 |
Decoder3 | # 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.... | MingSun-Tse/Collaborative-Distillation | Decoder3 | false | 14,030 | [
"MIT"
] | 172 | 915712674af82ff91d926d922c14988cce0430f3 | https://github.com/MingSun-Tse/Collaborative-Distillation/tree/915712674af82ff91d926d922c14988cce0430f3 |
PLU | import torch
import torch.nn as nn
class PLU(nn.Module):
def __init__(self):
super(PLU, self).__init__()
self.w1 = torch.nn.Parameter(torch.ones(1))
self.w2 = torch.nn.Parameter(torch.ones(1))
def forward(self, x):
return self.w1 * torch.max(x, torch.zeros_like(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
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | craigxchen/Reinforcement-Learning-Function-Approximation | PLU | false | 6,486 | [
"MIT"
] | 1 | 09c4df1dd44c6a76a3f574bebc959a19b141f3fe | https://github.com/craigxchen/Reinforcement-Learning-Function-Approximation/tree/09c4df1dd44c6a76a3f574bebc959a19b141f3fe |
StableBCELoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = t... | GenoM87/hubmap | StableBCELoss | false | 2,273 | [
"MIT"
] | 0 | 4acd11c373c6bb136ea9c6627a174ff02afa5986 | https://github.com/GenoM87/hubmap/tree/4acd11c373c6bb136ea9c6627a174ff02afa5986 |
par_start_encoder | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import numpy as np
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynam... | GerbenBeintema/deepSI | par_start_encoder | false | 8,205 | [
"BSD-3-Clause"
] | 12 | 580711210398064bb7f01e41d08b7a248a88b35b | https://github.com/GerbenBeintema/deepSI/tree/580711210398064bb7f01e41d08b7a248a88b35b |
GaussionConvD | import torch
import torch.nn.functional as F
import torch.nn as nn
class GaussionConvD(nn.Module):
"""The subsequent layer in `RobustGCN` that takes node distribution (mean, var) as input"""
def __init__(self, in_features, out_features, bias=False, gamma=1.0):
super().__init__()
self.in_featu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 | GaussionConvD | false | 5,105 | [
"MIT"
] | 1 | 8ae9ef57d44f073d0ceaf3f33a3a998546f960a8 | https://github.com/EdisonLeeeee/Graphgallery/tree/8ae9ef57d44f073d0ceaf3f33a3a998546f960a8 |
KeyValueAttention | import torch
import torch.nn as nn
from torch.autograd import Variable
import torch.nn.functional as F
import torch.utils.data
import torch.nn.init
class KeyValueAttention(nn.Module):
def __init__(self, query_size, key_size, value_size, hid_size, init_range):
super(KeyValueAttention, 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.... | msft-shahins/ConvLab-2 | KeyValueAttention | false | 12,818 | [
"Apache-2.0"
] | 0 | ad74c0e9e021916f9330af11e046ed72914b7740 | https://github.com/msft-shahins/ConvLab-2/tree/ad74c0e9e021916f9330af11e046ed72914b7740 |
MyLinear | import torch
from torch import nn
from torch.nn import functional as F
import torchvision.transforms.functional as F
import torch.nn.functional as F
class MyLinear(nn.Module):
"""Linear layer with equalized learning rate and custom learning rate multiplier."""
def __init__(self, input_size, output_size, gain... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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... | AnimeshKoratana/blurryface | MyLinear | false | 601 | [
"Apache-2.0"
] | 0 | c6cb5feec02f6d5af3acb1678336800390715d65 | https://github.com/AnimeshKoratana/blurryface/tree/c6cb5feec02f6d5af3acb1678336800390715d65 |
CopyChannels | import torch
class CopyChannels(torch.nn.Module):
def __init__(self, multiple=3, dim=1):
super(CopyChannels, self).__init__()
self.multiple = multiple
self.dim = dim
def forward(self, x):
return torch.cat([x for _ in range(self.multiple)], dim=self.dim)
def get_inputs():
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
reinterpret... | NehzUx/autodl | CopyChannels | false | 8,578 | [
"Apache-2.0"
] | 25 | c80fdc4b297ed1ec2b9e6911d313f1fe31d83cb9 | https://github.com/NehzUx/autodl/tree/c80fdc4b297ed1ec2b9e6911d313f1fe31d83cb9 |
BertAttention | from _paritybench_helpers import _mock_config
import math
import torch
from torch import nn
class BertLayerNorm(nn.Module):
"""
LayerNorm层
"""
def __init__(self, hidden_size, eps=1e-12):
super(BertLayerNorm, self).__init__()
self.gamma = nn.Parameter(torch.ones(hidden_size))
s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | kalanile/JDQA | BertAttention | false | 7,017 | [
"MIT"
] | 1 | 68e1d0259d316b3577a1f2fafa773b50f1885762 | https://github.com/kalanile/JDQA/tree/68e1d0259d316b3577a1f2fafa773b50f1885762 |
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... | zyzisyz/torch-practice | VAE | false | 4,684 | [
"Apache-2.0"
] | 0 | 92f2b7f1a01bbabd1a2cf2a4dd9099a0eeb9cf00 | https://github.com/zyzisyz/torch-practice/tree/92f2b7f1a01bbabd1a2cf2a4dd9099a0eeb9cf00 |
ResBlock1D | import torch
import torch.nn as nn
import torch.nn.functional as F
class ResBlock1D(nn.Module):
def __init__(self, inplanes, planes, seq_len, stride=1, downsample=None):
super(ResBlock1D, self).__init__()
self.conv1 = nn.Conv1d(inplanes, planes, kernel_size=3, stride=
stride, padding=... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | liuruoze/mini-AlphaStar | ResBlock1D | false | 15,933 | [
"Apache-2.0"
] | 108 | cf9de2507d526a5fb8ef67676aab2ffb92738640 | https://github.com/liuruoze/mini-AlphaStar/tree/cf9de2507d526a5fb8ef67676aab2ffb92738640 |
DRS | import torch
import torch.nn as nn
class DRS(nn.Module):
"""
DRS non-learnable setting
hyperparameter O , additional training paramters X
"""
def __init__(self, delta):
super(DRS, self).__init__()
self.relu = nn.ReLU()
self.delta = delta
self.global_max_pool = nn.... | 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... | manideep1108/DRS | DRS | false | 15,991 | [
"MIT"
] | 62 | 0858c3ffea310e9d504b7c2b06db5f281273df56 | https://github.com/manideep1108/DRS/tree/0858c3ffea310e9d504b7c2b06db5f281273df56 |
Actor | import torch
import torch.nn as nn
import torch.nn.functional as F
class Actor(nn.Module):
def __init__(self, obs_dim, action_dim):
super(Actor, self).__init__()
self.obs_dim = obs_dim
self.action_dim = action_dim
self.linear1 = nn.Linear(self.obs_dim, 512)
self.linear2 = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | AYUSHKABIRVERMA/Multi-agent-reinforcement-learning | Actor | false | 13,247 | [
"MIT"
] | 62 | cd7c13d723cd74dc278939d81d5dd1b0906cee7c | https://github.com/AYUSHKABIRVERMA/Multi-agent-reinforcement-learning/tree/cd7c13d723cd74dc278939d81d5dd1b0906cee7c |
IdentityPadding | import torch
import torch.nn as nn
import torch.utils.data.distributed
import torch.nn.functional as F
class IdentityPadding(nn.Module):
def __init__(self, in_channels, out_channels, stride=1):
super(IdentityPadding, self).__init__()
if stride == 2:
self.pooling = nn.AvgPool2d(kernel_... | 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... | Crisescode/Distributed-DL-Example | IdentityPadding | false | 7,908 | [
"Apache-2.0"
] | 19 | a7ff2b4a6c07a126c30eaa886cc6e8cd02a83949 | https://github.com/Crisescode/Distributed-DL-Example/tree/a7ff2b4a6c07a126c30eaa886cc6e8cd02a83949 |
FixedSubnetConv | import math
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.nn.functional as F
class FixedSubnetConv(nn.Conv2d):
def __init__(self, *args, **kwargs):
super().__init__(*args... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.multiprocessing
import torch.nn as nn
import torch.nn.p... | adityakusupati/LLC-2.0 | FixedSubnetConv | false | 18,218 | [
"MIT"
] | 10 | 38608bbaa425b15dcf5c971000b7a1b08120fb5c | https://github.com/adityakusupati/LLC-2.0/tree/38608bbaa425b15dcf5c971000b7a1b08120fb5c |
Route | import torch
import torch.nn as nn
class Route(nn.Module):
def __init__(self):
super(Route, self).__init__()
def forward(self, x1, x2):
"""
x1 means previous output; x2 means current output
"""
out = torch.cat((x2, x1), dim=1)
return out
def get_inputs():
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | CV-YYDS/YOLOv3 | Route | false | 11,275 | [
"MIT"
] | 0 | a433064721dfc932509aaed6cb44a785b24bc768 | https://github.com/CV-YYDS/YOLOv3/tree/a433064721dfc932509aaed6cb44a785b24bc768 |
Ceil | import torch
import torch.onnx
import torch.nn as nn
class Ceil(nn.Module):
def forward(self, x):
return torch.ceil(x)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.onnx
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | mil-tokyo/webdnn | Ceil | false | 16,060 | [
"MIT"
] | 1,967 | 38a60fd3e1a4e72bc01108189a3aa51e0752aecd | https://github.com/mil-tokyo/webdnn/tree/38a60fd3e1a4e72bc01108189a3aa51e0752aecd |
IndexedSegmentationMap | import torch
import torch.nn as nn
class IndexedSegmentationMap(nn.Module):
"""
Takes the raw logits from the n-channel output convolution and uses argmax to convert to an indexed output map.
"""
def __init__(self):
super().__init__()
def forward(self, x: 'torch.Tensor') ->torch.Tensor:
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | HalestormAI/efficientnet-unet | IndexedSegmentationMap | false | 2,336 | [
"MIT"
] | 0 | b6d5ec86d667ce7ac1f689bc16269dca83a079f0 | https://github.com/HalestormAI/efficientnet-unet/tree/b6d5ec86d667ce7ac1f689bc16269dca83a079f0 |
BinaryDiceLoss | # 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... | cnuzh/CSNet | BinaryDiceLoss | false | 6,463 | [
"MIT"
] | 1 | a6c3163624f55dc294ec2e5a6de020d77bd4ff91 | https://github.com/cnuzh/CSNet/tree/a6c3163624f55dc294ec2e5a6de020d77bd4ff91 |
FocalLoss | import torch
import torch.nn as nn
class FocalLoss(nn.Module):
"""
Softmax and sigmoid focal loss.
copy from https://github.com/lonePatient/TorchBlocks
"""
def __init__(self, num_labels, activation_type='softmax', gamma=2.0,
alpha=0.25, epsilon=1e-09):
super(FocalLoss, self).__ini... | 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
... | gitabtion/BertBasedCscModels | FocalLoss | false | 15,449 | [
"Apache-2.0"
] | 158 | 1daf505d109c5922eeedb6674edbb1b73db21e45 | https://github.com/gitabtion/BertBasedCscModels/tree/1daf505d109c5922eeedb6674edbb1b73db21e45 |
rec_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.... | gzerveas/TransformChrome | rec_attention | false | 6,784 | [
"MIT"
] | 1 | ab1046009aff2ec863aa65223dcfcd750d41ab86 | https://github.com/gzerveas/TransformChrome/tree/ab1046009aff2ec863aa65223dcfcd750d41ab86 |
ConvRelu | # 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
impor... | jmargutt/automated-building-detection | ConvRelu | false | 15,714 | [
"MIT"
] | 48 | e1668a470b94252040f27d26098826c293fbb46d | https://github.com/jmargutt/automated-building-detection/tree/e1668a470b94252040f27d26098826c293fbb46d |
TransformerDecoderLayer | import torch
import torch.nn as nn
import torch.nn.functional as F
def _get_activation_fn(activation):
if activation == 'relu':
return F.relu
elif activation == 'gelu':
return F.gelu
raise RuntimeError('activation should be relu/gelu, not {}'.format(
activation))
class DotProduct... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | amazon-research/long-short-term-transformer | TransformerDecoderLayer | false | 14,847 | [
"Apache-2.0"
] | 52 | a425be4b52ab68fddd85c91d26571e4cdfe8379a | https://github.com/amazon-research/long-short-term-transformer/tree/a425be4b52ab68fddd85c91d26571e4cdfe8379a |
Actor | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Lttcc/Olympics | Actor | false | 791 | [
"MIT"
] | 0 | 97411244073d127e83e84bf61b1b0a1d6718c31c | https://github.com/Lttcc/Olympics/tree/97411244073d127e83e84bf61b1b0a1d6718c31c |
FocalLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | AnassBenBouazza/Project-calibration-temperature_scaling | FocalLoss | false | 13,263 | [
"MIT"
] | 724 | cf96350f5e4349404fa092a97a71baf2bb7686ec | https://github.com/AnassBenBouazza/Project-calibration-temperature_scaling/tree/cf96350f5e4349404fa092a97a71baf2bb7686ec |
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.triton_helpers import libdevice
import math
import ... | EddieMG/LateTemporalModeling3DCNN | PositionwiseFeedForward | false | 2,285 | [
"MIT"
] | 0 | 94c87dc1d31d09bc310d0e735a2e55453976cb0d | https://github.com/EddieMG/LateTemporalModeling3DCNN/tree/94c87dc1d31d09bc310d0e735a2e55453976cb0d |
StoppingNetwork | # 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
impo... | bennzo/DT-RAM-PyTorch | StoppingNetwork | false | 1,535 | [
"MIT"
] | 0 | b364662ab7650ffd26cf129673752521e004b13a | https://github.com/bennzo/DT-RAM-PyTorch/tree/b364662ab7650ffd26cf129673752521e004b13a |
MultiheadAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | dashstander/glide-text2im | MultiheadAttention | false | 1,806 | [
"MIT"
] | 0 | 58f03a871ee0567e27fccc40df98203e675a9b8e | https://github.com/dashstander/glide-text2im/tree/58f03a871ee0567e27fccc40df98203e675a9b8e |
interaction | import torch
import torch.nn as nn
class interaction(nn.Module):
def __init__(self, conf):
super().__init__()
def forward(self, p, h):
p = p.unsqueeze(2)
h = h.unsqueeze(1)
return p * h
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | aditya140/NoveltyDetectionResearch | interaction | false | 6,078 | [
"MIT"
] | 1 | f9b27e6e8d9c23f85d4d91241ee5d050ecd6b6ef | https://github.com/aditya140/NoveltyDetectionResearch/tree/f9b27e6e8d9c23f85d4d91241ee5d050ecd6b6ef |
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
import torch.nn as nn
assert_... | AviVarma/torchASN-Transformer | FeedForward | false | 88 | [
"MIT"
] | 0 | 55bccf4cdb099cd8e9ac99f5f87f989ce2add983 | https://github.com/AviVarma/torchASN-Transformer/tree/55bccf4cdb099cd8e9ac99f5f87f989ce2add983 |
TensorLog | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_str... | Minyus/pipelinex | TensorLog | false | 14,038 | [
"Apache-2.0"
] | 188 | f35c524ec9c50751ee27d9a42d98317e16f1c544 | https://github.com/Minyus/pipelinex/tree/f35c524ec9c50751ee27d9a42d98317e16f1c544 |
classifier | import torch
import torch.nn as nn
import torch.nn.functional as F
class classifier(nn.Module):
def __init__(self, ef_dim, z_dim, class_num, voxel_size):
super(classifier, self).__init__()
self.ef_dim = ef_dim
self.z_dim = z_dim
self.class_num = class_num
self.voxel_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.... | czq142857/DECOR-GAN | classifier | false | 15,118 | [
"MIT"
] | 55 | 79c80fc202b8af982989a3e3bb3afe85e606b71f | https://github.com/czq142857/DECOR-GAN/tree/79c80fc202b8af982989a3e3bb3afe85e606b71f |
LanguageModelCriterion | # 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
from torch.autograd import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | anonymous2021hello/transformer-cil | LanguageModelCriterion | false | 3,117 | [
"MIT"
] | 0 | aed4017b61afaf4d9d21d40a078eefb4c7031cd1 | https://github.com/anonymous2021hello/transformer-cil/tree/aed4017b61afaf4d9d21d40a078eefb4c7031cd1 |
PositionWiseFeedForward | import torch
import torch.nn as nn
import torch.nn.init as init
class LayerNorm(nn.Module):
def __init__(self, d_hid, eps=1e-06):
super(LayerNorm, self).__init__()
self.gamma = nn.Parameter(torch.ones(d_hid))
self.beta = nn.Parameter(torch.zeros(d_hid))
self.eps = eps
def for... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Lhx94As/PHO-LID | PositionWiseFeedForward | false | 5,540 | [
"MIT"
] | 1 | 44843b25b977dd6e0b77b520dbe3f2ff1ea633cd | https://github.com/Lhx94As/PHO-LID/tree/44843b25b977dd6e0b77b520dbe3f2ff1ea633cd |
MedianPool2d | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.utils import _pair
from torch.nn.modules.utils import _quadruple
class MedianPool2d(nn.Module):
""" Median pool (usable as median filter when stride=1) module.
Args:
kernel_size: size of pooling kernel, int ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
from torch.nn.modules.utils import _pair
from torch... | Zhang-Jack/adversarial_yolo2 | MedianPool2d | false | 18,193 | [
"MIT"
] | 8 | 91c2a4793047f656482cebf0309984db823e8030 | https://github.com/Zhang-Jack/adversarial_yolo2/tree/91c2a4793047f656482cebf0309984db823e8030 |
SageLayer | # 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_... | HKUST-KnowComp/CSKB-Population | SageLayer | false | 8,164 | [
"MIT"
] | 13 | 7b1b2d25fbd0095b0cf009b933cfd5a62feadd58 | https://github.com/HKUST-KnowComp/CSKB-Population/tree/7b1b2d25fbd0095b0cf009b933cfd5a62feadd58 |
WasLoss | import torch
import torch.nn as nn
class WasLoss(nn.Module):
def __init__(self):
super(WasLoss, self).__init__()
self.MSEls = torch.nn.BCEWithLogitsLoss()
def forward(self, true_data, fake_data):
SLX, _ = torch.sort(true_data, 0)
SLG, _ = torch.sort(fake_data, 0)
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
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | Johnson-yue/RS-GAN | WasLoss | false | 8,372 | [
"MIT"
] | 26 | 8e8723045d63d8f9a4b510800cd909e7a6e3d195 | https://github.com/Johnson-yue/RS-GAN/tree/8e8723045d63d8f9a4b510800cd909e7a6e3d195 |
LinearWithConstraint | # 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 ... | jiuney/XAI606-EEGNet | LinearWithConstraint | false | 6,967 | [
"MIT"
] | 1 | 45ff28630ed1b09d0853f2cfb148a5dd2693e5ab | https://github.com/jiuney/XAI606-EEGNet/tree/45ff28630ed1b09d0853f2cfb148a5dd2693e5ab |
CReLU_IN | import torch
import torch.nn as nn
import torch.nn.functional as F
class CReLU_IN(nn.Module):
def __init__(self, channels):
super(CReLU_IN, self).__init__()
self.bn = nn.InstanceNorm2d(channels * 2, eps=1e-05, momentum=0.1,
affine=True)
def forward(self, x):
cat = torch.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
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 |
ContextGate | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.cuda
assert_size_stride = torch._C._dynamo.gu... | AndrewM1998/MultimodalNMT | ContextGate | false | 7,718 | [
"MIT"
] | 40 | b66d3a40ac9bc5c11ae124f51d1a9abf7cd6a04b | https://github.com/AndrewM1998/MultimodalNMT/tree/b66d3a40ac9bc5c11ae124f51d1a9abf7cd6a04b |
Expand | # 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... | Aditya239233/MDP | Expand | false | 16,906 | [
"MIT"
] | 4 | 87491e1d67e547c11f4bdd5d784d120473429eae | https://github.com/Aditya239233/MDP/tree/87491e1d67e547c11f4bdd5d784d120473429eae |
NetVLAD | # 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.... | ByungHeeCha/visual_localization | NetVLAD | false | 17,431 | [
"BSD-3-Clause"
] | 3 | 787fb8f6ee5c6e69ece9e83a016d15596e5524bc | https://github.com/ByungHeeCha/visual_localization/tree/787fb8f6ee5c6e69ece9e83a016d15596e5524bc |
RSoftmax | import torch
import torch.nn as nn
import torch.nn.functional as F
class RSoftmax(nn.Module):
"""Radix Softmax module in ``SplitAttentionConv2d``.
Args:
radix (int): Radix of input.
groups (int): Groups of input.
"""
def __init__(self, radix, groups):
super().__init__()
... | 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
... | David-19940718/mmclassification | RSoftmax | false | 5,050 | [
"Apache-2.0"
] | 1 | 987dd45457e38c4787237ea468799849dce11ada | https://github.com/David-19940718/mmclassification/tree/987dd45457e38c4787237ea468799849dce11ada |
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_... | arifmujib/MIT-Machine-Learning-Projects | DQN | false | 9,728 | [
"MIT"
] | 0 | 445f2dddf4441bf8248166e6eb15a0716444ab21 | https://github.com/arifmujib/MIT-Machine-Learning-Projects/tree/445f2dddf4441bf8248166e6eb15a0716444ab21 |
CrossEntropyLoss | import torch
import torch.utils.cpp_extension
class CrossEntropyLoss(torch.nn.Module):
def __init__(self):
super(CrossEntropyLoss, self).__init__()
self.ce_loss = torch.nn.CrossEntropyLoss()
def forward(self, cls_output, label, **_):
return self.ce_loss(cls_output, label).mean()
de... | 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.utils.cpp... | hugobloem/PyTorch-StudioGAN | CrossEntropyLoss | false | 12,668 | [
"MIT"
] | 0 | 3deab27c0774adba5a94c7f452d32d4cbc3b117c | https://github.com/hugobloem/PyTorch-StudioGAN/tree/3deab27c0774adba5a94c7f452d32d4cbc3b117c |
MLPAttention | # 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.... | Nickeilf/pysimt | MLPAttention | false | 9,503 | [
"MIT"
] | 0 | 05c8de92d0e2b930e40939ad3695d8d2c2954dda | https://github.com/Nickeilf/pysimt/tree/05c8de92d0e2b930e40939ad3695d8d2c2954dda |
ChannelReplicate | import torch
import torch.nn as nn
class ChannelReplicate(nn.Module):
def __init__(self, factor=3):
super(ChannelReplicate, self).__init__()
self.factor = factor
def forward(self, input):
template = input
for i in range(0, self.factor - 1):
input = torch.cat((temp... | 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... | YingqiLiulll/scrips_for_SR | ChannelReplicate | false | 1,250 | [
"MIT"
] | 0 | 04fa6fdaf157e913d3e2521cd80315a10a2ccedc | https://github.com/YingqiLiulll/scrips_for_SR/tree/04fa6fdaf157e913d3e2521cd80315a10a2ccedc |
LayerNorm | import math
import torch
from torch import Tensor
import torch.nn as nn
from torch.nn import Parameter
from torch.autograd import Variable
class LayerNorm(nn.Module):
"""
Layer Normalization based on Ba & al.:
'Layer Normalization'
https://arxiv.org/pdf/1607.06450.pdf
"""
def __init__(self, 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.triton_helpers import libdevice
import math
from torch import Tensor
import torch.nn as nn
from torch.nn import... | alex-kj-chin/universal-computation | LayerNorm | false | 12,076 | [
"MIT"
] | 0 | a41cc7d685a3e0c56c11bc346c25394464da2e06 | https://github.com/alex-kj-chin/universal-computation/tree/a41cc7d685a3e0c56c11bc346c25394464da2e06 |
MyNeural | # 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
assert_size_s... | med-boubekri/Covid-Fact-Checker | MyNeural | false | 12,774 | [
"MIT"
] | 0 | 7869bcd830f33aefe4afeb5b75808f479e8094f2 | https://github.com/med-boubekri/Covid-Fact-Checker/tree/7869bcd830f33aefe4afeb5b75808f479e8094f2 |
GatedFusion | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | qinyan-li/DocEE | GatedFusion | false | 7,516 | [
"MIT"
] | 1 | e8d2202a44907df5f12f9a67180d849a54421ab7 | https://github.com/qinyan-li/DocEE/tree/e8d2202a44907df5f12f9a67180d849a54421ab7 |
SAC | # 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.... | Luoxd1996/SCPM-Net | SAC | false | 8,487 | [
"MIT"
] | 26 | 2039ea5253ec831dcae79c2f0caa6e5d2641a1f9 | https://github.com/Luoxd1996/SCPM-Net/tree/2039ea5253ec831dcae79c2f0caa6e5d2641a1f9 |
BartClassificationHead | import torch
from torch import nn
import torch.utils.checkpoint
class BartClassificationHead(nn.Module):
"""Head for sentence-level classification tasks."""
def __init__(self, input_dim: 'int', inner_dim: 'int', num_classes:
'int', pooler_dropout: 'float'):
super().__init__()
self.den... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | Clemens123/transformers | BartClassificationHead | false | 11,488 | [
"Apache-2.0"
] | 0 | 22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 | https://github.com/Clemens123/transformers/tree/22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 |
PredictionConvolutions | # 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 itertools import product as product
import torch.optim... | aarashfeizi/a-PyTorch-Tutorial-to-Object-Detection | PredictionConvolutions | false | 1,444 | [
"MIT"
] | 0 | a9e1f3092d4b8c094bff5cd0897e0e3c1e0bc9c2 | https://github.com/aarashfeizi/a-PyTorch-Tutorial-to-Object-Detection/tree/a9e1f3092d4b8c094bff5cd0897e0e3c1e0bc9c2 |
ContrastiveLoss | import torch
import torch.nn.functional as F
import torch.utils.data
import torch.nn.parallel
import torch.optim
class ContrastiveLoss(torch.nn.Module):
def __init__(self, margin=2.0):
super(ContrastiveLoss, self).__init__()
self.margin = margin
def forward(self, output1, output2, label):
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.data
impo... | wenqingchu/Semantic-CariGANs | ContrastiveLoss | false | 16,731 | [
"BSD-3-Clause"
] | 50 | d6c2fc2046ee62b42dd70fa8892775e33337bbdf | https://github.com/wenqingchu/Semantic-CariGANs/tree/d6c2fc2046ee62b42dd70fa8892775e33337bbdf |
TokenLearnedEncoding | import torch
from torch import nn
class TokenLearnedEncoding(nn.Module):
"""
Learned additive img/word/action token encoding implemented on top of nn.Embedding
"""
def __init__(self, d_model, vocab_size=3, init_range=0.1):
super().__init__()
self.emb = nn.Embedding(vocab_size, d_model... | 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... | ishikasingh/teach | TokenLearnedEncoding | false | 15,618 | [
"MIT"
] | 54 | 5554f02f55c22abfe5c2a749dbb24c13377726c8 | https://github.com/ishikasingh/teach/tree/5554f02f55c22abfe5c2a749dbb24c13377726c8 |
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