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 |
|---|---|---|---|---|---|---|---|---|---|---|
mfm | # 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_... | JunhongH/CP-GAN | mfm | false | 17,525 | [
"Apache-2.0"
] | 9 | 5ac129da8cf6d010dc0da03bb4637d20c822d50b | https://github.com/JunhongH/CP-GAN/tree/5ac129da8cf6d010dc0da03bb4637d20c822d50b |
DetNet2 | # 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... | liangzhao123/topic_ws | DetNet2 | false | 3,913 | [
"Apache-2.0"
] | 0 | ef7aba11b975eab5f657101ed696b49ec94b5f86 | https://github.com/liangzhao123/topic_ws/tree/ef7aba11b975eab5f657101ed696b49ec94b5f86 |
SeparableConv | # 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... | lixinsu/RCZoo | SeparableConv | false | 15,938 | [
"MIT"
] | 166 | 37fcb7962fbd4c751c561d4a0c84173881ea8339 | https://github.com/lixinsu/RCZoo/tree/37fcb7962fbd4c751c561d4a0c84173881ea8339 |
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.... | NouamaneTazi/conv-emotion | Attention | false | 14,123 | [
"MIT"
] | 488 | 0c9dcb9cc5234a7ca8cf6af81aabe28ef3814d0e | https://github.com/NouamaneTazi/conv-emotion/tree/0c9dcb9cc5234a7ca8cf6af81aabe28ef3814d0e |
DiceBCELoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class DiceLoss(nn.Module):
def __init__(self, smooth: 'float'=1.0, apply_sigmoid: 'bool'=False):
super().__init__()
self.smooth = smooth
self.apply_sigmoid = apply_sigmoid
def forward(self, y_pred: 'torch.Tensor', y_t... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | tfmoraes/deep_heart_torch | DiceBCELoss | false | 10,853 | [
"MIT"
] | 0 | 4168ce01d600e69baf82c752a3e57af86861b6ea | https://github.com/tfmoraes/deep_heart_torch/tree/4168ce01d600e69baf82c752a3e57af86861b6ea |
custom_embedding | # 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 ... | EpiSci/SoCRATES | custom_embedding | false | 17,245 | [
"MIT"
] | 6 | 901a896c5a765e3cb56f290188cde71c8707192d | https://github.com/EpiSci/SoCRATES/tree/901a896c5a765e3cb56f290188cde71c8707192d |
LayerNorm | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class LayerNorm(nn.Module):
""" layer normalization """
def __init__(self, cfg, eps=1e-12):
super().__init__()
self.gamma = nn.Parameter(torch.ones(cfg.hidden_dim))
self.beta = nn.Parameter(torch.zeros(cf... | 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_... | Kyumin-Park/Protein-Chemical-Releativity-BERT | LayerNorm | false | 1,897 | [
"MIT"
] | 0 | 6a339f4e640d99199f38a00769f5872c2a53ac55 | https://github.com/Kyumin-Park/Protein-Chemical-Releativity-BERT/tree/6a339f4e640d99199f38a00769f5872c2a53ac55 |
Attention | import math
import torch
from torch import nn
import torch.nn.functional as F
class Attention(nn.Module):
"""
score_i = f(Q, K_i), i = 1, 2, ..., t
dot: f(Q, K_i) = Q.transpose · K_i
scaled_dot: f(Q, K_i) = Q.transpose · K_i / √(key_dim)
general: f(Q, K_i) = Q.transpose · W ·... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | WangDaYeeeeee/BERT-With-KnowledgeBase | Attention | false | 2,959 | [
"Apache-2.0"
] | 0 | 5f205295ce9b69ab0f813ef34409fdf2de3a14ca | https://github.com/WangDaYeeeeee/BERT-With-KnowledgeBase/tree/5f205295ce9b69ab0f813ef34409fdf2de3a14ca |
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 torch.nn as nn
... | ljrprocc/Motif-Removal | DiceLoss | false | 3,941 | [
"MIT"
] | 0 | 8979ca91398212248a2be61345c99bdec53ae37e | https://github.com/ljrprocc/Motif-Removal/tree/8979ca91398212248a2be61345c99bdec53ae37e |
GatedConv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
im... | piggy2303/DeepFillv2_Pytorch | GatedConv2d | false | 7,473 | [
"MIT"
] | 1 | dd35299f11704f878ed7a33e14ccd51a9d64baaf | https://github.com/piggy2303/DeepFillv2_Pytorch/tree/dd35299f11704f878ed7a33e14ccd51a9d64baaf |
Conv | # 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... | Ravikiran2402/_MOEL | Conv | false | 11,805 | [
"MIT"
] | 0 | 57e311712c67e1e554a3a9187709f8e2728d19be | https://github.com/Ravikiran2402/_MOEL/tree/57e311712c67e1e554a3a9187709f8e2728d19be |
Lookahead | import torch
import torch.utils.data.distributed
import torch.nn as nn
import torch.nn.functional as F
class Lookahead(nn.Module):
def __init__(self, n_features, context):
super(Lookahead, self).__init__()
assert context > 0
self.context = context
self.n_features = n_features
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data.distributed
import torch.nn as nn
assert_size_stride = t... | chaiyujin/deepspeech.pytorch | Lookahead | false | 9,896 | [
"MIT"
] | 0 | b4edbafb955f35316869ce3fda2dc9cd47968038 | https://github.com/chaiyujin/deepspeech.pytorch/tree/b4edbafb955f35316869ce3fda2dc9cd47968038 |
GrayLoss | import torch
import torch.nn as nn
class GrayLoss(nn.Module):
def __init__(self):
super(GrayLoss, self).__init__()
self.l1 = nn.L1Loss()
def forward(self, x):
y = torch.ones_like(x) / 2.0
return 1 / self.l1(x, y)
def get_inputs():
return [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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | GuYuanjie/DeepFusionPrior | GrayLoss | false | 5,219 | [
"MIT"
] | 1 | a7126e073ed8c49b6a9a662492b64aaeee56cc01 | https://github.com/GuYuanjie/DeepFusionPrior/tree/a7126e073ed8c49b6a9a662492b64aaeee56cc01 |
ScaledDotAttention | import torch
import torch.nn as nn
from torch.nn import LayerNorm
def scaled_dot_attention(q, k, v, mask=None, noise=0, dropout=lambda x: x):
"""
:param q: queries, (batch, time1, channels1)
:param k: keys, (batch, time2, channels1)
:param v: values, (batch, time2, channels2)
:param mask: boolean ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | iclementine/speedyspeech | ScaledDotAttention | false | 10,418 | [
"BSD-3-Clause"
] | 0 | db527587a3699b71082d61c9e9fad7ed795d1980 | https://github.com/iclementine/speedyspeech/tree/db527587a3699b71082d61c9e9fad7ed795d1980 |
MultiHeadedAttention | import math
import torch
from typing import Tuple
from torch import nn
class MultiHeadedAttention(nn.Module):
"""Multi-Head Attention layer.
Args:
n_head (int): The number of heads.
n_feat (int): The number of features.
dropout_rate (float): Dropout rate.
"""
def __init__(se... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | eschmidbauer/wenet | MultiHeadedAttention | false | 12,365 | [
"Apache-2.0"
] | 0 | f0bbf6af16fa92d26a7f68ac21e0354a7500a025 | https://github.com/eschmidbauer/wenet/tree/f0bbf6af16fa92d26a7f68ac21e0354a7500a025 |
LT | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | ahangchen/torch2trt | LT | false | 6,090 | [
"MIT"
] | 1 | 53c663f0e0570ef7ffd6771354ae3478f63bd328 | https://github.com/ahangchen/torch2trt/tree/53c663f0e0570ef7ffd6771354ae3478f63bd328 |
RelPositionMultiHeadedAttention | # 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.... | Masao-Someki/Conformer | RelPositionMultiHeadedAttention | false | 8,543 | [
"MIT"
] | 18 | 866da9ae05a6d07304775c592caac8d516f67c92 | https://github.com/Masao-Someki/Conformer/tree/866da9ae05a6d07304775c592caac8d516f67c92 |
wide_basic | import torch
import torch.nn as nn
def get_norm(n_filters, norm):
if norm is None:
return Identity()
elif norm == 'batch':
return nn.BatchNorm2d(n_filters, momentum=0.9)
elif norm == 'instance':
return nn.InstanceNorm2d(n_filters, affine=True)
elif norm == 'layer':
retu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | jliu/HDGE | wide_basic | false | 15,716 | [
"Apache-2.0"
] | 69 | 1615d04d55ec038590fc7f18810344a8257edaa0 | https://github.com/jliu/HDGE/tree/1615d04d55ec038590fc7f18810344a8257edaa0 |
SqueezeEmbedding | # 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... | XuMayi/PyABSA | SqueezeEmbedding | false | 1,260 | [
"MIT"
] | 0 | 3d71c0cdaea7ea1eff600d9091c3c63f61c111e5 | https://github.com/XuMayi/PyABSA/tree/3d71c0cdaea7ea1eff600d9091c3c63f61c111e5 |
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
assert_... | JohnJim0816/rl-tutorials | Critic | false | 8,367 | [
"MIT"
] | 16 | e99daea815da85f9f25dff2d01b030249a203d22 | https://github.com/JohnJim0816/rl-tutorials/tree/e99daea815da85f9f25dff2d01b030249a203d22 |
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.... | byamao1/MMSA | MultiheadAttention | false | 14,992 | [
"MIT"
] | 198 | 1a894d042144c9ac75b3465d38871ce8c2987251 | https://github.com/byamao1/MMSA/tree/1a894d042144c9ac75b3465d38871ce8c2987251 |
ConcatConv2d | # 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... | gaozhihan/torchdiffeq | ConcatConv2d | false | 6,718 | [
"MIT"
] | 1 | 414781617d595ba01cc3f23382e25ab890f4ca66 | https://github.com/gaozhihan/torchdiffeq/tree/414781617d595ba01cc3f23382e25ab890f4ca66 |
PatchEmbeddings | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import Module
from torch import nn
import torch.utils.data
import ... | ppvalluri09/annotated_deep_learning_paper_implementations | PatchEmbeddings | false | 11,068 | [
"MIT"
] | 0 | 387b6dfd1ef1f6d295e9394c24b5798071d9a3e4 | https://github.com/ppvalluri09/annotated_deep_learning_paper_implementations/tree/387b6dfd1ef1f6d295e9394c24b5798071d9a3e4 |
Transformer | import torch
import torch.nn as nn
import torch.nn.parallel
class Mlp(nn.Module):
"""Implementation of MLP"""
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
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.... | QLSong/cv-classify | Transformer | false | 2,766 | [
"Apache-2.0"
] | 0 | 02f53d03868f299a08b5c97a266b50a7fdcd3f2b | https://github.com/QLSong/cv-classify/tree/02f53d03868f299a08b5c97a266b50a7fdcd3f2b |
ExtractTensorPatches | # 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 as F
from typing import Tuple
from typing import Union
from typing import Optional
from tor... | NickleDave/kornia | ExtractTensorPatches | false | 2,681 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 5392651d0bc268da577fa0a49aa50f957289c7dd | https://github.com/NickleDave/kornia/tree/5392651d0bc268da577fa0a49aa50f957289c7dd |
ScalarMix | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.utils.data.dataloader
import torch.nn as nn
import torch.nn
... | Dadmatech/DadmaTools | ScalarMix | false | 7,971 | [
"Apache-2.0"
] | 25 | c1b7add5c33544f69c1ba1c5250a5ea07caf9aa2 | https://github.com/Dadmatech/DadmaTools/tree/c1b7add5c33544f69c1ba1c5250a5ea07caf9aa2 |
PositionGenerator | # 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 ... | Jh-SYSU/MolRep | PositionGenerator | false | 13,878 | [
"MIT"
] | 57 | b2c802d18d41d7db26c19c6dd644098f945e48a1 | https://github.com/Jh-SYSU/MolRep/tree/b2c802d18d41d7db26c19c6dd644098f945e48a1 |
ShakeResNet | # 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 math
from torch.nn imp... | ang421/dda | ShakeResNet | false | 9,912 | [
"MIT"
] | 0 | 391ad696ec8479ce41a0d7d6bfbfae06edaddf67 | https://github.com/ang421/dda/tree/391ad696ec8479ce41a0d7d6bfbfae06edaddf67 |
SimpleClampModel | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleClampModel(torch.nn.Module):
def __init__(self, min, max):
super(SimpleClampModel, self).__init__()
self.min = min
self.max = max
def forward(self, input):
return torch.clamp(input, self.min, self.max... | 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.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.... | briancoutinho/glow | SimpleClampModel | false | 12,556 | [
"Apache-2.0"
] | 0 | 4c919d60b3c33296c4109aec8020a1733c98f5b5 | https://github.com/briancoutinho/glow/tree/4c919d60b3c33296c4109aec8020a1733c98f5b5 |
MILLR | import torch
import numpy as np
from torch import nn
import torch as tc
from sklearn.metrics import *
from torch.utils.data import DataLoader
from torch.utils.data import WeightedRandomSampler
class myDataset(torch.utils.data.Dataset):
def __init__(self, x, y):
self.x = x
self.y = y
def __le... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import numpy as np
from torch... | mhbl3/PrecursorAnalysis | MILLR | false | 7,370 | [
"MIT"
] | 1 | aaa2fe0219ad579b9126fef9cc8594a59ae66815 | https://github.com/mhbl3/PrecursorAnalysis/tree/aaa2fe0219ad579b9126fef9cc8594a59ae66815 |
TwoLayerFCBodyWithAction | # 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 ... | Fieps1/p3-tennis | TwoLayerFCBodyWithAction | false | 585 | [
"MIT"
] | 0 | 29f3dab5810d7cd7f84120416a615956d266c256 | https://github.com/Fieps1/p3-tennis/tree/29f3dab5810d7cd7f84120416a615956d266c256 |
GlobalAvgPool | # 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... | XudongLinthu/video_feature_extractor | GlobalAvgPool | false | 14,602 | [
"Apache-2.0"
] | 250 | 54bdbeef2e9f4db8d7697b26edef124979625f58 | https://github.com/XudongLinthu/video_feature_extractor/tree/54bdbeef2e9f4db8d7697b26edef124979625f58 |
CDAE | import torch
from torch import nn
from torch.autograd import Variable
def add_gaussian_noise(x, std):
return x + Variable(x.data.new(x.size()).normal_(0, std))
class CDAE(nn.Module):
"""
Convolutional denoising autoencoder layer for stacked autoencoders.
Args:
in_channels: the number of cha... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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
from tor... | mmcenta/eye-disease-recognition | CDAE | false | 4,025 | [
"MIT"
] | 0 | 52e1dedbce27514b605b9f8ad976d6042b7e2f14 | https://github.com/mmcenta/eye-disease-recognition/tree/52e1dedbce27514b605b9f8ad976d6042b7e2f14 |
TransposeConv2dLayer | import torch
import torch.nn as nn
from torch.nn import functional as F
from torch.nn import Parameter
def l2normalize(v, eps=1e-12):
return v / (v.norm() + eps)
class LayerNorm(nn.Module):
def __init__(self, num_features, eps=1e-08, affine=True):
super(LayerNorm, self).__init__()
self.num_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.nn import Parameter
assert_size_stride = torch.... | kangzhiq/DeepFillv2_Pytorch | TransposeConv2dLayer | false | 10,433 | [
"MIT"
] | 0 | 9c7ed61b25bb995713f89108b712490737abe1b1 | https://github.com/kangzhiq/DeepFillv2_Pytorch/tree/9c7ed61b25bb995713f89108b712490737abe1b1 |
L1 | import torch
import numpy as np
import torch.nn as nn
class L1(nn.Module):
def __init__(self):
nn.Module.__init__(self)
def forward(self, s, t):
if isinstance(s, np.ndarray):
s = torch.from_numpy(s).float()
if isinstance(t, np.ndarray):
t = torch.from_numpy(t)... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | mrernst/rl_robotics_research | L1 | false | 10,613 | [
"MIT"
] | 0 | 0bc446cfb69591cb4ee3ce8d39815c463090a5f6 | https://github.com/mrernst/rl_robotics_research/tree/0bc446cfb69591cb4ee3ce8d39815c463090a5f6 |
DiceLoss | import torch
import torch.nn as nn
class DiceLoss(nn.Module):
def __init__(self, loss_weight=1.0):
super(DiceLoss, self).__init__()
self.loss_weight = loss_weight
def forward(self, input, target, mask, reduce=True):
batch_size = input.size(0)
input = torch.sigmoid(input)
... | 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... | bhuyle/PAN_ocr | DiceLoss | false | 9,855 | [
"Apache-2.0"
] | 0 | bcd03892d4eb08a779a0a7ae63d526d8ea38cb01 | https://github.com/bhuyle/PAN_ocr/tree/bcd03892d4eb08a779a0a7ae63d526d8ea38cb01 |
GridReduction1 | # 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_... | Hiroaki-Ozaki/modelib-classification | GridReduction1 | false | 17,395 | [
"WTFPL"
] | 10 | 11077704cc0bc9a42fc4b94da60b57d31ff0f65c | https://github.com/Hiroaki-Ozaki/modelib-classification/tree/11077704cc0bc9a42fc4b94da60b57d31ff0f65c |
CMul | # 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
import torch.nn as nn
import torch.nn.parallel
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided... | nhonth/DeLF-pytorch | CMul | false | 16,162 | [
"MIT"
] | 315 | 5577a447a0330b9e976cff56a10fc91669216b8c | https://github.com/nhonth/DeLF-pytorch/tree/5577a447a0330b9e976cff56a10fc91669216b8c |
SymKlCriterion | import torch
import torch.nn.functional as F
from torch.nn.modules.loss import _Loss
from torch.optim.lr_scheduler import *
class Criterion(_Loss):
def __init__(self, alpha=1.0, name='criterion'):
super().__init__()
"""Alpha is used to weight each loss term
"""
self.alpha = alpha
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch.... | mahartmann/mt-dnn | SymKlCriterion | false | 10,479 | [
"MIT"
] | 0 | c9aa3379dc255fd8fc40f24b6cd508f6a645b32f | https://github.com/mahartmann/mt-dnn/tree/c9aa3379dc255fd8fc40f24b6cd508f6a645b32f |
Upsampler | import math
import torch
import torch.utils.data
from torchvision.transforms import *
class ConvBlock(torch.nn.Module):
def __init__(self, input_size, output_size, kernel_size=3, stride=1,
padding=1, bias=True, activation='prelu', norm=None):
super(ConvBlock, self).__init__()
self.conv = ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.utils.data
from torchvision.transforms import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | HamsterBiz/iSeeBetter | Upsampler | false | 11,656 | [
"MIT"
] | 0 | a71cee61583bdedab1f3b368e2cb7dc5ad969aed | https://github.com/HamsterBiz/iSeeBetter/tree/a71cee61583bdedab1f3b368e2cb7dc5ad969aed |
Flatten | import torch
from torch import nn
class Flatten(nn.Module):
def __init__(self):
super(Flatten, self).__init__()
def forward(self, x):
"""
Arguments:
x: a float tensor with shape [batch_size, c, h, w].
Returns:
a float tensor with shape [batch_size, c*h... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | DebugVBZ/pixel2style2pixel | Flatten | false | 8,943 | [
"MIT"
] | 0 | e884c0cf471ad9ee09b8743d7ffd532283a638e5 | https://github.com/DebugVBZ/pixel2style2pixel/tree/e884c0cf471ad9ee09b8743d7ffd532283a638e5 |
_GateAddNorm | # 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 ... | Gian-Wiher/darts | _GateAddNorm | false | 5,215 | [
"Apache-2.0"
] | 1 | 0d267e08643e2e3f88163a5d955b8be75840c2f6 | https://github.com/Gian-Wiher/darts/tree/0d267e08643e2e3f88163a5d955b8be75840c2f6 |
complex_relu_layer | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import 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... | XitongZhang1994/SimpleMagNet | complex_relu_layer | false | 5,995 | [
"MIT"
] | 1 | d3df7a2f528474214b7d396ea9831db3aa280090 | https://github.com/XitongZhang1994/SimpleMagNet/tree/d3df7a2f528474214b7d396ea9831db3aa280090 |
ConvertPointsToHomogeneous | import torch
import torch.nn as nn
def convert_points_to_homogeneous(points):
"""Function that converts points from Euclidean to homogeneous space.
See :class:`~torchgeometry.ConvertPointsToHomogeneous` for details.
Examples::
>>> input = torch.rand(2, 4, 3) # BxNx3
>>> output = tgm.co... | 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... | aravinho/frankmocap | ConvertPointsToHomogeneous | false | 3,121 | [
"BSD-3-Clause"
] | 0 | 6a150a9cb96e9b32a60d8047eaa84d0c37e471f5 | https://github.com/aravinho/frankmocap/tree/6a150a9cb96e9b32a60d8047eaa84d0c37e471f5 |
SplAtConv2d | from torch.nn import Module
import torch
from torch import nn
import torch.nn.functional as F
from torch.nn import Conv2d
from torch.nn import ReLU
from torch.nn.modules.utils import _pair
class DropBlock2D(object):
def __init__(self, *args, **kwargs):
raise NotImplementedError
class rSoftMax(nn.Module... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | DYF-AI/openvino-x | SplAtConv2d | false | 5,054 | [
"Apache-2.0"
] | 1 | 0f18ebb240ea3394f7e461aca34fac158e686d95 | https://github.com/DYF-AI/openvino-x/tree/0f18ebb240ea3394f7e461aca34fac158e686d95 |
PolicyNet | # 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... | JohnJim0816/rl-tutorials | PolicyNet | false | 8,370 | [
"MIT"
] | 16 | e99daea815da85f9f25dff2d01b030249a203d22 | https://github.com/JohnJim0816/rl-tutorials/tree/e99daea815da85f9f25dff2d01b030249a203d22 |
Decoder | import torch
import torch.nn as nn
class Decoder(nn.Module):
def __init__(self):
super(Decoder, self).__init__()
self.layers = nn.Sequential()
self.layers.add_module('Conv3', nn.Conv2d(64, 32, 3, 1, 1))
self.layers.add_module('Act3', nn.ReLU(inplace=True))
self.layers.add_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | VarunBabbar/Image_Compressor | Decoder | false | 1,192 | [
"MIT"
] | 0 | 254d8d411f7cd16f3ce242275532c9fca537269c | https://github.com/VarunBabbar/Image_Compressor/tree/254d8d411f7cd16f3ce242275532c9fca537269c |
TokenLearnedEncoding | # 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
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 |
Decoder5 | import torch
import torch.nn as nn
class Decoder5(nn.Module):
def __init__(self, model=None, fixed=False):
super(Decoder5, self).__init__()
self.fixed = fixed
self.conv51 = nn.Conv2d(512, 512, 3, 1, 0)
self.conv44 = nn.Conv2d(512, 512, 3, 1, 0)
self.conv43 = nn.Conv2d(512,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | EndyWon/Texture-Reformer | Decoder5 | false | 8,226 | [
"MIT"
] | 11 | f84f95accb3574c7b759a7f03c0b0b4e150314b5 | https://github.com/EndyWon/Texture-Reformer/tree/f84f95accb3574c7b759a7f03c0b0b4e150314b5 |
Neumann | import math
import torch
import torch.nn as nn
class Neumann(nn.Module):
def __init__(self, n_features, depth, residual_connection, mlp_depth,
init_type):
super().__init__()
self.depth = depth
self.n_features = n_features
self.residual_connection = residual_connection
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import math
import torch.nn a... | alexprz/NeuMiss | Neumann | false | 18,272 | [
"BSD-3-Clause"
] | 9 | bf4f68ba4dd29b51ec3de9d6eef85deecebfa68d | https://github.com/alexprz/NeuMiss/tree/bf4f68ba4dd29b51ec3de9d6eef85deecebfa68d |
GeneralizedDiceLoss | import collections
import torch
import warnings
from typing import Optional
from typing import Union
from typing import Any
from typing import Callable
from typing import Tuple
import torch.nn
from torch.nn.modules.loss import _Loss
from enum import Enum
import collections.abc
def issequenceiterable(obj: 'Any') ->boo... | 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 collections
from typi... | Alxaline/MONAI | GeneralizedDiceLoss | false | 4,894 | [
"Apache-2.0"
] | 1 | 6b8fdf9db7f13ed7d88d605155a0463840abcbf2 | https://github.com/Alxaline/MONAI/tree/6b8fdf9db7f13ed7d88d605155a0463840abcbf2 |
encoder | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | bblinn2017/IM-NET-pytorch | encoder | false | 3,195 | [
"MIT"
] | 0 | 82ff646aaf2f93ae1560debb40fe05f1420ff655 | https://github.com/bblinn2017/IM-NET-pytorch/tree/82ff646aaf2f93ae1560debb40fe05f1420ff655 |
FocalLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Return:
Tensor: Reduced loss tensor.
"""
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | JiYuanFeng/mmclassification | FocalLoss | false | 13,893 | [
"Apache-2.0"
] | 1,190 | b337ef1f11b85148cca4b6fb0c4da3f8cc2eede6 | https://github.com/JiYuanFeng/mmclassification/tree/b337ef1f11b85148cca4b6fb0c4da3f8cc2eede6 |
Squash | import torch
import torch.nn as nn
class Squash(nn.Module):
def forward(self, x, dim=-1):
squared_norm = (x ** 2).sum(dim=dim, keepdim=True)
scale = squared_norm / (1 + squared_norm)
return scale * x / (squared_norm.sqrt() + 1e-08)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | MobtgZhang/MWMLNet | Squash | false | 5,602 | [
"MIT"
] | 1 | 125bb39935916b6b4be505c51cb6a04eb49b96d0 | https://github.com/MobtgZhang/MWMLNet/tree/125bb39935916b6b4be505c51cb6a04eb49b96d0 |
MaxPool2dLayer | # 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... | fuzhanrahmanian/lucent | MaxPool2dLayer | false | 15,380 | [
"Apache-2.0"
] | 449 | 13b24c3c37784185275da73c7a11095b2ae809c5 | https://github.com/fuzhanrahmanian/lucent/tree/13b24c3c37784185275da73c7a11095b2ae809c5 |
SimpleModel | # 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.optim
import torch.utils.data
import torch.utils.data... | ZVK/jukebox | SimpleModel | false | 18,192 | [
"MIT"
] | 5 | 23fd6753f2892214ad3d97f6f2b59f8cc8d0c57a | https://github.com/ZVK/jukebox/tree/23fd6753f2892214ad3d97f6f2b59f8cc8d0c57a |
ScaledDotProductAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
class ScaledDotProductAttention(nn.Module):
""" Scaled Dot-Product Attention """
def __init__(self, temperature, attn_dropout=0.1):
super().__init__()
self.temperature = temperature
self.dropout = nn.Dropout(attn_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 import triton_helpers
from torch._inductor.runtime.... | MinkiJ/SnaTCHer | ScaledDotProductAttention | false | 8,564 | [
"MIT"
] | 12 | 335c42469f0a7ad72c5c3480c8effc8c293823e0 | https://github.com/MinkiJ/SnaTCHer/tree/335c42469f0a7ad72c5c3480c8effc8c293823e0 |
AttentionPool2d | # 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.... | Liujingxiu23/guided-diffusion | AttentionPool2d | false | 5,573 | [
"MIT"
] | 1 | 0ba878e517b276c45d1195eb29f6f5f72659a05b | https://github.com/Liujingxiu23/guided-diffusion/tree/0ba878e517b276c45d1195eb29f6f5f72659a05b |
LeakyReLU | import torch
class Activation(torch.nn.Module):
def __init__(self) ->None:
super().__init__()
def forward(self, inputs: 'torch.Tensor') ->torch.Tensor:
raise NotImplementedError
class LeakyReLU(Activation):
def forward(self, inputs: 'torch.Tensor') ->torch.Tensor:
return torch... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | altescy/xtorch | LeakyReLU | false | 9,708 | [
"MIT"
] | 0 | bcbbbe645f4d62c211af5b3555c526cc60792c32 | https://github.com/altescy/xtorch/tree/bcbbbe645f4d62c211af5b3555c526cc60792c32 |
LinearAttentionLayer | # 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.... | HuyTu7/dl_optimizers | LinearAttentionLayer | false | 9,136 | [
"MIT"
] | 0 | 245242718324cebcabe657bdbc704aa54ad0b8d2 | https://github.com/HuyTu7/dl_optimizers/tree/245242718324cebcabe657bdbc704aa54ad0b8d2 |
TorchClampOptionMaxMin | import torch
class TorchClampOptionMaxMin(torch.nn.Module):
def forward(self, x):
return torch.clamp(x, min=-0.1, max=0.1)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | PogChamper/torch2trt | TorchClampOptionMaxMin | false | 14,283 | [
"MIT"
] | 3,363 | 43b12627ec0de4d212efb6d02b07570205085ccc | https://github.com/PogChamper/torch2trt/tree/43b12627ec0de4d212efb6d02b07570205085ccc |
DiracInitBlock | import torch
import torch.nn as nn
import torch.utils.data
class DiracInitBlock(nn.Module):
"""
DiracNetV2 specific initial block.
Parameters:
----------
in_channels : int
Number of input channels.
out_channels : int
Number of output channels.
"""
def __init__(self, i... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | earhian/imgclsmob | DiracInitBlock | false | 6,624 | [
"MIT"
] | 1 | c87c0942420876941868c016211073dec4392e4d | https://github.com/earhian/imgclsmob/tree/c87c0942420876941868c016211073dec4392e4d |
GeneralizedMeanPoolingFpn | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
from abc import ABC
from tor... | catcodee/cluster-contrast-reid | GeneralizedMeanPoolingFpn | false | 3,279 | [
"MIT"
] | 0 | f6359990a4326375f23c3fd654df3fc6dcc9c579 | https://github.com/catcodee/cluster-contrast-reid/tree/f6359990a4326375f23c3fd654df3fc6dcc9c579 |
LearnedPositionalEncoding | import torch
from torch import nn
class LayerNorm(nn.Module):
"""A layernorm module in the TF style (epsilon inside the square root)."""
def __init__(self, d_model, variance_epsilon=1e-12):
super().__init__()
self.gamma = nn.Parameter(torch.ones(d_model))
self.beta = nn.Parameter(torc... | 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... | JamesNgo3781/vietocr | LearnedPositionalEncoding | false | 5,377 | [
"Apache-2.0"
] | 1 | 9d311bbeb18c51c8ff90022f07c0463b204407dc | https://github.com/JamesNgo3781/vietocr/tree/9d311bbeb18c51c8ff90022f07c0463b204407dc |
UpBlock | import torch
import torch.nn as nn
class UpBlock(nn.Module):
def __init__(self, in_f, out_f, stride=2, add_blur=False):
super(UpBlock, self).__init__()
self.shuffle = nn.ConvTranspose2d(in_f, out_f, kernel_size=3,
stride=stride, padding=0)
self.has_blur = add_blur
if 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | parth-shettiwar/Image-Toonification | UpBlock | false | 12,859 | [
"MIT"
] | 0 | a24d76fa9737558ac38a2fdf23469376f25c0abd | https://github.com/parth-shettiwar/Image-Toonification/tree/a24d76fa9737558ac38a2fdf23469376f25c0abd |
ShallowCombination | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class ShallowCombination(nn.Module):
"""This Module can be used to generate a shallow combination from two embeddings using a gate."""
def __init__(self, bertram_config: 'BertramConfig'):
super(ShallowCombination, self).... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | stefan-it/bertram | ShallowCombination | false | 16,497 | [
"Apache-2.0"
] | 50 | 2e449cdc677577d1ca8b9daf852f324be4074940 | https://github.com/stefan-it/bertram/tree/2e449cdc677577d1ca8b9daf852f324be4074940 |
Attention | import math
import torch
import torch.nn as nn
import torch.optim
import torch.nn.functional as F
class Attention(nn.Module):
"""Attention layer - Custom layer to perform weighted average over the second axis (axis=1)
Transforming a tensor of size [N, W, H] to [N, 1, H].
N: batch size
W: n... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | ovechkinVT/SkipRNN | Attention | false | 7,436 | [
"MIT"
] | 1 | 7c1f37349d464b1b6bf8835520abad22b199f1ad | https://github.com/ovechkinVT/SkipRNN/tree/7c1f37349d464b1b6bf8835520abad22b199f1ad |
TinyCnn | import torch
import torch.nn as nn
class TinyCnn(nn.Module):
def __init__(self, feature_extraction=False) ->None:
super().__init__()
self.feature_extraction = feature_extraction
self.conv1 = nn.Conv2d(3, 3, 5)
self.relu1 = nn.ReLU()
self.pool1 = nn.MaxPool2d(2, 2)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | aravipati12/captum | TinyCnn | false | 10,098 | [
"BSD-3-Clause"
] | 0 | ef3e81d89c8c4404a49c384cf0727f2e7d393f5f | https://github.com/aravipati12/captum/tree/ef3e81d89c8c4404a49c384cf0727f2e7d393f5f |
AdaIN | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.optim
import torch.utils.data
assert_size_st... | VITA-Group/Sandwich-Batch-Normalization | AdaIN | false | 14,537 | [
"MIT"
] | 46 | 25e7df6e64a67cebd7e70b911f874cfc1bd19df0 | https://github.com/VITA-Group/Sandwich-Batch-Normalization/tree/25e7df6e64a67cebd7e70b911f874cfc1bd19df0 |
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.... | Yingting-dev/ReChorus | MultiHeadAttention | false | 2,985 | [
"MIT"
] | 0 | a16bc1e42f3e90e889133d7476c52ada44db573b | https://github.com/Yingting-dev/ReChorus/tree/a16bc1e42f3e90e889133d7476c52ada44db573b |
SquaredErrorBayesRisk | # 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.nn import Module
import torch.utils.data
import torch.nn.functional
import torch.autograd
assert_size_stride = torch._C._dynamo.g... | mcx/annotated_deep_learning_paper_implementations | SquaredErrorBayesRisk | false | 7,214 | [
"MIT"
] | 1 | f169f3a71dd2d36eb28ad31062d3475efa367b88 | https://github.com/mcx/annotated_deep_learning_paper_implementations/tree/f169f3a71dd2d36eb28ad31062d3475efa367b88 |
QNetwork | # 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_... | QwQ2000/E2GAN | QNetwork | false | 8,668 | [
"MIT"
] | 34 | f27b715362de4459129206217d100ae5b6cf82c8 | https://github.com/QwQ2000/E2GAN/tree/f27b715362de4459129206217d100ae5b6cf82c8 |
DHead | import torch
import torch.nn as nn
from math import *
class DHead(nn.Module):
def __init__(self):
super().__init__()
self.conv = nn.Conv2d(256, 1, 4)
def forward(self, x):
output = torch.sigmoid(self.conv(x))
return output
def get_inputs():
return [torch.rand([4, 256, 6... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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 math import *
assert_size_stride = torch._C._dynamo.g... | pengyuzhang97/NIID-Bench | DHead | false | 16,234 | [
"MIT"
] | 124 | 235b6f5c2bf218a587f9effae346a2f616de1855 | https://github.com/pengyuzhang97/NIID-Bench/tree/235b6f5c2bf218a587f9effae346a2f616de1855 |
templateModel | # 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 logging
import numpy a... | awoloshuk/NephNet | templateModel | false | 6,308 | [
"MIT"
] | 1 | 562431364874fef1680069c7a5235c67b96504b8 | https://github.com/awoloshuk/NephNet/tree/562431364874fef1680069c7a5235c67b96504b8 |
RMulInt | import torch
class RMulInt(torch.nn.Module):
def __init__(self):
super(RMulInt, self).__init__()
def forward(self, x):
return 10 * x
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | bunderhi/torch2trt | RMulInt | false | 1,605 | [
"MIT"
] | 0 | fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d | https://github.com/bunderhi/torch2trt/tree/fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d |
SimpleReluModel | # 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.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.... | YaronBenAtar/glow | SimpleReluModel | false | 14,674 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
HardSigmoid | # 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... | DetectionBLWX/WSDDN.pytorch | HardSigmoid | false | 17,216 | [
"MIT"
] | 7 | 05020d9d0445af90ba0af3f095aa12b18e3da7d2 | https://github.com/DetectionBLWX/WSDDN.pytorch/tree/05020d9d0445af90ba0af3f095aa12b18e3da7d2 |
AdaptiveBilinear | import torch
import torch.nn.functional as F
import torch.nn as nn
class AdaptiveBilinear(nn.Module):
def __init__(self):
super(AdaptiveBilinear, self).__init__()
def forward(self, x1, x2):
"""
:param x1: (b, l1, dim1)
:param x2: (b, l2, dim2)
:return:
"""
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | LindgeW/BiaffineNER | AdaptiveBilinear | false | 8,459 | [
"Apache-2.0"
] | 13 | 0ae179e9ff731362f6c8ba6d0b24485ad45e8bbf | https://github.com/LindgeW/BiaffineNER/tree/0ae179e9ff731362f6c8ba6d0b24485ad45e8bbf |
Scale | import torch
import torch.nn as nn
class Scale(nn.Module):
def __init__(self, nchannels, bias=True, init_scale=1.0):
super().__init__()
self.nchannels = nchannels
self.weight = nn.Parameter(torch.Tensor(1, nchannels, 1, 1))
if bias:
self.bias = nn.Parameter(torch.Tenso... | 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... | CuongNguyen218/ObjectDetection-OneStageDet | Scale | false | 359 | [
"MIT"
] | 0 | 60efe8b0ee6782b2aea20a32264b2ce1fc21901f | https://github.com/CuongNguyen218/ObjectDetection-OneStageDet/tree/60efe8b0ee6782b2aea20a32264b2ce1fc21901f |
TransformDecoder4 | import torch
import torch.nn as nn
class TransformDecoder4(nn.Module):
def __init__(self):
super(TransformDecoder4, self).__init__()
self.conv41 = nn.Conv2d(1024, 256, 3, 1, 0)
self.conv34 = nn.Conv2d(256, 256, 3, 1, 0)
self.conv33 = nn.Conv2d(256, 256, 3, 1, 0)
self.conv3... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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/pytorch-AdaIN | TransformDecoder4 | false | 2,694 | [
"MIT"
] | 0 | 02ae320345232983c754ea233613aedc21e4d348 | https://github.com/MingSun-Tse/pytorch-AdaIN/tree/02ae320345232983c754ea233613aedc21e4d348 |
GEGLU | # 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 ... | samedii/latent-diffusion | GEGLU | false | 16,362 | [
"MIT"
] | 563 | f13bf9bf463d95b5a16aeadd2b02abde31f769f8 | https://github.com/samedii/latent-diffusion/tree/f13bf9bf463d95b5a16aeadd2b02abde31f769f8 |
VisErrorLoss | # 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... | gathierry/FashionAI-KeyPointsDetectionOfApparel | VisErrorLoss | false | 15,426 | [
"Apache-2.0"
] | 174 | 2e0942b42b4a9cd974cdddc151675738dc8a8cb4 | https://github.com/gathierry/FashionAI-KeyPointsDetectionOfApparel/tree/2e0942b42b4a9cd974cdddc151675738dc8a8cb4 |
NormedLinear | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Parameter
class NormedLinear(nn.Module):
def __init__(self, in_features, out_features):
super(NormedLinear, self).__init__()
self.weight = Parameter(torch.Tensor(in_features, out_features))
self.weight... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ZonghaiZhu/EZBM | NormedLinear | false | 1,321 | [
"MIT"
] | 0 | b4f6fbd10598c79f144b778ef848554ac62a173a | https://github.com/ZonghaiZhu/EZBM/tree/b4f6fbd10598c79f144b778ef848554ac62a173a |
Discriminator | # 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.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | Shen-Lab/GraphCL | Discriminator | false | 14,408 | [
"MIT"
] | 275 | 1d43f79d7f33f8133f9d4b4b8254d8aaeb09a615 | https://github.com/Shen-Lab/GraphCL/tree/1d43f79d7f33f8133f9d4b4b8254d8aaeb09a615 |
SeqAttendImgAttOnlyFusion | import torch
from torch import nn
class SeqAttendImgFusion(nn.Module):
def __init__(self, seq_dim, img_dim, hidden_dim, att_dropout,
att_scale_factor=1, **kwargs):
super(SeqAttendImgFusion, self).__init__()
self.SeqTrans = nn.Linear(seq_dim, hidden_dim, bias=False)
self.ImgTrans =... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Asichurter/MalFusionFSL | SeqAttendImgAttOnlyFusion | false | 16,993 | [
"MIT"
] | 4 | 713bf64cc07a3489f42941fd2299837075575ac0 | https://github.com/Asichurter/MalFusionFSL/tree/713bf64cc07a3489f42941fd2299837075575ac0 |
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.... | SofiaValdiviesov/LinearStyleTransfer | decoder3 | false | 9,660 | [
"BSD-2-Clause"
] | 0 | 6837c6a9be16bb5981fa0744e5d23f61d08e6940 | https://github.com/SofiaValdiviesov/LinearStyleTransfer/tree/6837c6a9be16bb5981fa0744e5d23f61d08e6940 |
SquaredErrorBayesRisk | from torch.nn import Module
import torch
import torch.utils.data
import torch.nn.functional
import torch.autograd
class SquaredErrorBayesRisk(Module):
"""
<a id="SquaredErrorBayesRisk"></a>
## Bayes Risk with Squared Error Loss
Here the cost function is squared error,
$$\\sum_{k=1}^K (y_k - p_k)... | 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.nn import Module
import torch.utils.data
import torch.nn.functional
import torch.autograd
assert_size_stride = torch._C._dynamo.g... | techthiyanes/annotated_deep_learning_paper_implementations | SquaredErrorBayesRisk | false | 16,587 | [
"MIT"
] | 3,714 | 8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 | https://github.com/techthiyanes/annotated_deep_learning_paper_implementations/tree/8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 |
BasicNN | # AOT ID: ['1_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.... | DNCoelho/clipper | BasicNN | false | 13,541 | [
"Apache-2.0"
] | 1,403 | 0144078c9da757ee319d60b362d9f51538657ca8 | https://github.com/DNCoelho/clipper/tree/0144078c9da757ee319d60b362d9f51538657ca8 |
GroupGRUCell | # 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 ... | Hritikbansal/RNNs_SVA_OOD | GroupGRUCell | false | 17,397 | [
"MIT"
] | 4 | a1c73955342d9d35c49da5fcb7b315e37b0f75d1 | https://github.com/Hritikbansal/RNNs_SVA_OOD/tree/a1c73955342d9d35c49da5fcb7b315e37b0f75d1 |
Mnist_CNN | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.quantization
import torch.onnx
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
class Mnist_CNN(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | harrydrippin/tutorials | Mnist_CNN | false | 12,491 | [
"BSD-3-Clause"
] | 0 | a8def2dfd44b4b8e22c36a3e4470f37b59ebedfb | https://github.com/harrydrippin/tutorials/tree/a8def2dfd44b4b8e22c36a3e4470f37b59ebedfb |
LayerNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.optim
assert_size_stride = torch._C._dynamo.... | Arsenaut/comet-commonsense | LayerNorm | false | 13,311 | [
"Apache-2.0"
] | 521 | ffa4691ba6bfcb46ea2ed4ce91de5c6815f66e52 | https://github.com/Arsenaut/comet-commonsense/tree/ffa4691ba6bfcb46ea2ed4ce91de5c6815f66e52 |
DistillLoss | import torch
import torch.nn as nn
class DistillLoss(nn.Module):
def __init__(self):
super(DistillLoss, self).__init__()
def forward(self, t_feat, feat, cams):
assert len(cams) == feat.shape[0] and feat.shape[0] == t_feat.shape[0]
t_feat = t_feat / t_feat.norm(p=2, dim=1, keepdim=Tru... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | Terminator8758/Precise-ICS-master | DistillLoss | false | 18,009 | [
"MIT"
] | 4 | 9f4591fee6ab64d9dd91f551355d29562bf663cb | https://github.com/Terminator8758/Precise-ICS-master/tree/9f4591fee6ab64d9dd91f551355d29562bf663cb |
h_sigmoid | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
class h_sigmoid(nn.Module):
def __init__(self, inplace=True, h_max=1):
super(h_sigmoid, self).__init__()
self.relu = nn.ReLU6(inplace=inplace)
self.h_... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data... | SpectrePrediction/micronet | h_sigmoid | false | 2,838 | [
"MIT"
] | 0 | f56269c7a8744f750e9870f0baa9fb6e68f27b9c | https://github.com/SpectrePrediction/micronet/tree/f56269c7a8744f750e9870f0baa9fb6e68f27b9c |
Highway | # 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 ... | thophan92/cs224n-winter2019 | Highway | false | 4,426 | [
"MIT"
] | 0 | f3f8041b35e949e73167135d662a2bd93e7406de | https://github.com/thophan92/cs224n-winter2019/tree/f3f8041b35e949e73167135d662a2bd93e7406de |
Fp32GroupNorm | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
import torch.onnx.operators
import torch.optim
import torch.optim.lr_scheduler
class Fp32GroupNorm(nn.GroupNorm):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
def forward(self, input)... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.utils.data
import torch.onnx.operators
impor... | AbhilashMathews/adahessian | Fp32GroupNorm | false | 4,836 | [
"MIT"
] | 1 | bacccecc7a078c3e9e72aa55b17d8e46d21dc9c9 | https://github.com/AbhilashMathews/adahessian/tree/bacccecc7a078c3e9e72aa55b17d8e46d21dc9c9 |
SRCNN | # 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.... | akimotty877/mmediting | SRCNN | false | 3,080 | [
"Apache-2.0"
] | 0 | cae872d6f3e867ba144c7c0dbc29a0ee1a29e5a6 | https://github.com/akimotty877/mmediting/tree/cae872d6f3e867ba144c7c0dbc29a0ee1a29e5a6 |
MultiLayeredConv1d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C... | carankt/FastSpeech2-1 | MultiLayeredConv1d | false | 6,383 | [
"Apache-2.0"
] | 1 | 42c06e4fbdf741a0719154d1cb4617b7d3f15a5c | https://github.com/carankt/FastSpeech2-1/tree/42c06e4fbdf741a0719154d1cb4617b7d3f15a5c |
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 numpy as np
import tor... | BenKang34/deep-reinforcement-learning-nanodegree | Critic | false | 151 | [
"MIT"
] | 0 | 17c9007f757dfb1217c869fdee51798c4a21ba92 | https://github.com/BenKang34/deep-reinforcement-learning-nanodegree/tree/17c9007f757dfb1217c869fdee51798c4a21ba92 |
MagnitudeTestModel | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
from torchvision import models as models
import torch.nn.pa... | aalborov/openvino_training_extensions | MagnitudeTestModel | false | 6,038 | [
"Apache-2.0"
] | 1 | a0bb39424151a98e1ca80c4aa5c865636d401785 | https://github.com/aalborov/openvino_training_extensions/tree/a0bb39424151a98e1ca80c4aa5c865636d401785 |
ClassHead | import torch
import torch.nn as nn
import torch._utils
from itertools import product as product
import torch.utils.data.distributed
class ClassHead(nn.Module):
def __init__(self, inchannels=512, num_anchors=3):
super(ClassHead, self).__init__()
self.num_anchors = num_anchors
self.conv1x1 ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
from itertools import product as produ... | Capetian/FaceX-Zoo | ClassHead | false | 5,028 | [
"Apache-2.0"
] | 1 | 029786c40d8aba15d891d33973de25fcd7e5399a | https://github.com/Capetian/FaceX-Zoo/tree/029786c40d8aba15d891d33973de25fcd7e5399a |
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