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 |
|---|---|---|---|---|---|---|---|---|---|---|
VoxelFeatureExtractor | import torch
from torch import nn
class VoxelFeatureExtractor(nn.Module):
"""Computes mean of non-zero points within voxel."""
def forward(self, feature, occupancy):
"""
:feature FloatTensor of shape (N, K, C)
:return FloatTensor of shape (N, C)
"""
denominator = occup... | 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... | dd-iuonac/vision3d | VoxelFeatureExtractor | false | 15,154 | [
"MIT"
] | 131 | 9ea514c80eb99d265c3247321e59bfc1c2ccd94a | https://github.com/dd-iuonac/vision3d/tree/9ea514c80eb99d265c3247321e59bfc1c2ccd94a |
GenerationProbabilty | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class GenerationProbabilty(nn.Module):
def __init__(self, embedding_size, hidden_size, h_star_size):
"""Calculates `p_gen` as described in Pointer-Generator Networks paper."""
super(GenerationProbabilty, 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 math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.a... | abhishek0318/conll-sigmorphon-2018 | GenerationProbabilty | false | 18,208 | [
"MIT"
] | 6 | de4b8da7778947e03e7a35b56e0e53281f65e403 | https://github.com/abhishek0318/conll-sigmorphon-2018/tree/de4b8da7778947e03e7a35b56e0e53281f65e403 |
GatedConvTranspose | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | D-hash-code/ffjord-rnode-finalweek-mnist | GatedConvTranspose | false | 2,141 | [
"MIT"
] | 0 | 4cabcbadda79c68df53ec25f1f8fe03cfeee78f9 | https://github.com/D-hash-code/ffjord-rnode-finalweek-mnist/tree/4cabcbadda79c68df53ec25f1f8fe03cfeee78f9 |
MaxFeature | # 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_... | Serene99-09/mmediting | MaxFeature | false | 9,549 | [
"Apache-2.0"
] | 0 | be49e33650627ac26fdd065fbbaff66f726e3fde | https://github.com/Serene99-09/mmediting/tree/be49e33650627ac26fdd065fbbaff66f726e3fde |
WSDiceLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
import torch.nn as nn
import torch.nn.parallel
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty... | HarshSulakhe/pytorch_connectomics | WSDiceLoss | false | 9,859 | [
"MIT"
] | 0 | 73402e654afde69a43a5836cc90a32ef75c75dc2 | https://github.com/HarshSulakhe/pytorch_connectomics/tree/73402e654afde69a43a5836cc90a32ef75c75dc2 |
CRF | # 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.nn.init
assert_size_stride = torch._C._dynamo... | LiyuanLucasLiu/LightNER | CRF | false | 14,013 | [
"Apache-2.0"
] | 115 | 4abb61f473b8144a08ceaf74569cc6c1e9fdb53e | https://github.com/LiyuanLucasLiu/LightNER/tree/4abb61f473b8144a08ceaf74569cc6c1e9fdb53e |
CustomMSELoss | # 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
... | TAN-OpenLab/TCSE-net | CustomMSELoss | false | 9,537 | [
"Apache-2.0"
] | 0 | fc6ecf704a9c128a9b5b6853cffa8486ee0f54e8 | https://github.com/TAN-OpenLab/TCSE-net/tree/fc6ecf704a9c128a9b5b6853cffa8486ee0f54e8 |
JaccardLoss | import torch
from torch import nn
import torch.backends.cudnn
def jaccard(preds, trues, weight=None, is_average=True, eps=1e-06):
num = preds.size(0)
preds = preds.view(num, -1)
trues = trues.view(num, -1)
if weight is not None:
w = torch.autograd.Variable(weight).view(num, -1)
preds =... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import torch.backends.cudnn
assert_size_stride = torch._C._dynamo.gu... | cxz/tgs-salt-identification-challenge | JaccardLoss | false | 6,515 | [
"MIT"
] | 1 | 859f3d7f2d3184532c42c34444500eec3b03b1c8 | https://github.com/cxz/tgs-salt-identification-challenge/tree/859f3d7f2d3184532c42c34444500eec3b03b1c8 |
RegModel | from torch.nn import Module
import functools
import torch
import torch.nn as nn
from typing import *
class PrePostInitMeta(type):
"""A metaclass that calls optional `__pre_init__` and `__post_init__` methods"""
def __new__(cls, name, bases, dct):
x = super().__new__(cls, name, bases, dct)
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.nn import Module
import functools
import torch.nn as nn
from typing import *
assert_size_stride = torch._C._dynamo.guards.assert_... | davidpfahler/fastai_dev | RegModel | false | 10,054 | [
"Apache-2.0"
] | 0 | a86b15f86138a9902e8649e3f745e76a19139ab3 | https://github.com/davidpfahler/fastai_dev/tree/a86b15f86138a9902e8649e3f745e76a19139ab3 |
TransformerDecoderLayer | import math
import torch
from torch import nn
import torch.nn.functional as F
def _normalize(tensor, norm_layer):
"""
Broadcast layer norm
"""
size = tensor.size()
return norm_layer(tensor.view(-1, size[-1])).view(size)
class MultiHeadAttention(nn.Module):
def __init__(self, n_heads, dim, d... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | jinjiren/ParlAI | TransformerDecoderLayer | false | 12,635 | [
"MIT"
] | 0 | 40799aeee69f2a0bb25a1341bb8da0c44861268e | https://github.com/jinjiren/ParlAI/tree/40799aeee69f2a0bb25a1341bb8da0c44861268e |
SqueezeNet | import copy
import torch
import torch.nn as nn
import torch.utils.data
from torchvision.models.squeezenet import squeezenet1_0
from torchvision.models.squeezenet import squeezenet1_1
import torch.nn.modules.activation
class GramMatrix(nn.Module):
def forward(self, x):
b, c, h, w = x.size()
F = x.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import copy
import torch.nn a... | matherm/ummon3 | SqueezeNet | false | 7,339 | [
"BSD-3-Clause"
] | 1 | 08476d21ce17cc95180525d48202a1690dfc8a08 | https://github.com/matherm/ummon3/tree/08476d21ce17cc95180525d48202a1690dfc8a08 |
CSDN_Tem | # 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... | LOUEY233/CPS3320_python | CSDN_Tem | false | 747 | [
"MIT"
] | 0 | 3cc1733d91c3a8f680eeb984348e2a52ae3285ec | https://github.com/LOUEY233/CPS3320_python/tree/3cc1733d91c3a8f680eeb984348e2a52ae3285ec |
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
from torch import nn
a... | gabrielsluz/vince | FocalLoss | false | 15,384 | [
"Apache-2.0"
] | 61 | f4e17a2cf70c080a7e01e46d15537e33224c869b | https://github.com/gabrielsluz/vince/tree/f4e17a2cf70c080a7e01e46d15537e33224c869b |
SortNet | # 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 ... | bashish101/sort | SortNet | false | 3,191 | [
"MIT"
] | 0 | c8f3e4875c039e6eb935c34ed8403c5d439bf8ad | https://github.com/bashish101/sort/tree/c8f3e4875c039e6eb935c34ed8403c5d439bf8ad |
MaskedTemporalPooling | # 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.utils.data
import torch.nn
assert_size_stride = torch._C._dynamo.guards.asse... | zijian-hu/pytorchvideo | MaskedTemporalPooling | false | 4,703 | [
"Apache-2.0"
] | 0 | 51589b100437af2285c56ce2ccc7ccecb7f9b18b | https://github.com/zijian-hu/pytorchvideo/tree/51589b100437af2285c56ce2ccc7ccecb7f9b18b |
PKT | import torch
from torch import nn
class PKT(nn.Module):
"""Probabilistic Knowledge Transfer for deep representation learning
Code from author: https://github.com/passalis/probabilistic_kt"""
def __init__(self):
super(PKT, self).__init__()
def forward(self, f_s, f_t):
return self.cosi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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
fr... | bobo0810/RepDistiller | PKT | false | 10,166 | [
"BSD-2-Clause"
] | 0 | 0a4cea2142221b9b31c8e995920273f5619b37f8 | https://github.com/bobo0810/RepDistiller/tree/0a4cea2142221b9b31c8e995920273f5619b37f8 |
Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Antloup/Deep-large-picture-database-indexing | Net | false | 2,460 | [
"MIT"
] | 0 | ac5368805a29376f54eba0657550d73e4739a235 | https://github.com/Antloup/Deep-large-picture-database-indexing/tree/ac5368805a29376f54eba0657550d73e4739a235 |
KlCriterion | # 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.... | chunhuililili/mt_dnn | KlCriterion | false | 10,203 | [
"MIT"
] | 0 | 4c6efaf21724c7b8103a05e46b5b44d7b246225e | https://github.com/chunhuililili/mt_dnn/tree/4c6efaf21724c7b8103a05e46b5b44d7b246225e |
DummyLoss | # 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... | adriangrepo/segmentl | DummyLoss | false | 18,221 | [
"MIT"
] | 5 | 9b520bf6cfd005eef9bba3db36ee6b3bb373b085 | https://github.com/adriangrepo/segmentl/tree/9b520bf6cfd005eef9bba3db36ee6b3bb373b085 |
BPR_max | import torch
import torch.nn as nn
import torch.nn.functional as F
class BPR_max(nn.Module):
def __init__(self):
super(BPR_max, self).__init__()
def forward(self, logit):
logit_softmax = F.softmax(logit, dim=1)
diff = logit.diag().view(-1, 1).expand_as(logit) - logit
loss = -... | 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
... | hungthanhpham94/GRU4REC-pytorch | BPR_max | false | 15,547 | [
"Apache-2.0"
] | 184 | 666b84264c4afae757fe55c6997dcf0a4da1d44e | https://github.com/hungthanhpham94/GRU4REC-pytorch/tree/666b84264c4afae757fe55c6997dcf0a4da1d44e |
TransformerBlock | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.init as init
class TransformerBlock(nn.Module):
def __init__(self, input_size, d_k=16, d_v=16, n_heads=8, is_layer_norm
=False, attn_dropout=0.1):
super(TransformerBlock, self).__init__()
self.n_heads = n_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.... | bopopescu/covid-19-visualization | TransformerBlock | false | 12,193 | [
"MIT"
] | 0 | 8a9325b52f007dd5e3ee5bbd323b71bbf19b9640 | https://github.com/bopopescu/covid-19-visualization/tree/8a9325b52f007dd5e3ee5bbd323b71bbf19b9640 |
SimpleConv2dModule | import torch
import torch.nn.functional as F
import torch.jit
import torch.onnx
import torch.nn
class SimpleConv2dModule(torch.nn.Module):
def __init__(self, stride=1, padding=0, dilation=1, groups=1):
super(SimpleConv2dModule, self).__init__()
self.stride = stride
self.padding = 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
import torch.jit
import torch... | opti-mix/glow | SimpleConv2dModule | false | 7,398 | [
"Apache-2.0"
] | 1 | 4ba074df5da9822986a23a6679ab592c22660f6d | https://github.com/opti-mix/glow/tree/4ba074df5da9822986a23a6679ab592c22660f6d |
Atanh | # 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.onnx
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | mil-tokyo/webdnn | Atanh | false | 16,064 | [
"MIT"
] | 1,967 | 38a60fd3e1a4e72bc01108189a3aa51e0752aecd | https://github.com/mil-tokyo/webdnn/tree/38a60fd3e1a4e72bc01108189a3aa51e0752aecd |
ConcatSquashLinear | import torch
import torch.nn as nn
import torch.utils.data
class ConcatSquashLinear(nn.Module):
def __init__(self, dim_in, dim_out):
super(ConcatSquashLinear, self).__init__()
self._layer = nn.Linear(dim_in, dim_out)
self._hyper_bias = nn.Linear(1, dim_out, bias=False)
self._hyper... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | D-hash-code/ffjord | ConcatSquashLinear | false | 11,359 | [
"MIT"
] | 0 | 3647ab35537a8bac3b4dc1e45a593819ac8e2c18 | https://github.com/D-hash-code/ffjord/tree/3647ab35537a8bac3b4dc1e45a593819ac8e2c18 |
RBF | import torch
import torch.nn as nn
class RBF(nn.Module):
def __init__(self):
super(RBF, self).__init__()
self.mean = nn.Parameter(torch.Tensor([0.0]))
self.std = nn.Parameter(torch.Tensor([1.0]))
def forward(self, x):
gauss = torch.exp(-(x - self.mean) ** 2 / (2 * self.std **... | 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... | maet3608/torchy | RBF | false | 3,966 | [
"Apache-2.0"
] | 0 | 8c73732a1d4631bd97bfafdc18e52a22ff5410f7 | https://github.com/maet3608/torchy/tree/8c73732a1d4631bd97bfafdc18e52a22ff5410f7 |
AvgPoolShortCut | # 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... | Karthik-Ragunath/DDU | AvgPoolShortCut | false | 8,411 | [
"MIT"
] | 43 | b9daae9304bdeb222857884ef8cb3b6b3d004d33 | https://github.com/Karthik-Ragunath/DDU/tree/b9daae9304bdeb222857884ef8cb3b6b3d004d33 |
Projection | # 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.... | crystal-k7/chatspace | Projection | false | 6,493 | [
"Apache-2.0"
] | 1 | b63861eab74e1b85f0233f689cf97a13dff873e4 | https://github.com/crystal-k7/chatspace/tree/b63861eab74e1b85f0233f689cf97a13dff873e4 |
ConvWS2d | # 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 ... | Fanzhongjie/ARFE | ConvWS2d | false | 475 | [
"Apache-2.0"
] | 0 | 4b96b8c5bc0895d3d30acec2a490f81a860fe860 | https://github.com/Fanzhongjie/ARFE/tree/4b96b8c5bc0895d3d30acec2a490f81a860fe860 |
MaskedTemporalPooling | # 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.utils.data
import torch.nn
assert_size_stride = torch._C._dynamo.guards.asse... | kevinmtian/pytorchvideo | MaskedTemporalPooling | false | 15,822 | [
"Apache-2.0"
] | 2,391 | 168e16859a6029ef8ebeb476f9163bebb6c6b87d | https://github.com/kevinmtian/pytorchvideo/tree/168e16859a6029ef8ebeb476f9163bebb6c6b87d |
BiAttention | # 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.... | ChenZhongFu/KOBE | BiAttention | false | 13,473 | [
"MIT"
] | 176 | 710d7556516bdbd9ad971e6ff8b8f625a1a55e5a | https://github.com/ChenZhongFu/KOBE/tree/710d7556516bdbd9ad971e6ff8b8f625a1a55e5a |
MySmallModel | import torch
import torch.nn as nn
class MySmallModel(nn.Module):
def __init__(self, nodes):
super().__init__()
hidden_nodes = nodes * 2
self.fc1 = nn.Linear(nodes, hidden_nodes)
self.fc2 = nn.Linear(hidden_nodes, nodes)
self.fc3 = nn.Linear(nodes, 1)
def forward(self... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | minister19/RL_pytorch_get_started | MySmallModel | false | 4,007 | [
"MIT"
] | 0 | e444f524a14d329f9a25c53f102bc96c4ea36ad8 | https://github.com/minister19/RL_pytorch_get_started/tree/e444f524a14d329f9a25c53f102bc96c4ea36ad8 |
ReGLU | # 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_... | robburdon/pytorch_tabular | ReGLU | false | 16,324 | [
"MIT"
] | 560 | 9bf75f22c6e1b3033ad699713e77c283d55f3555 | https://github.com/robburdon/pytorch_tabular/tree/9bf75f22c6e1b3033ad699713e77c283d55f3555 |
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
from torch import nn
assert_s... | lilianluong/multitask-card-games | DQN | false | 7,093 | [
"MIT"
] | 1 | ae32e85583c61cc27a44946a6b5fa7c1e2c152ff | https://github.com/lilianluong/multitask-card-games/tree/ae32e85583c61cc27a44946a6b5fa7c1e2c152ff |
LogCoshLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | nizamphoenix/kaggle | LogCoshLoss | false | 4,093 | [
"MIT"
] | 0 | a9c993d0441a6d9260d605a630f95d938e6329db | https://github.com/nizamphoenix/kaggle/tree/a9c993d0441a6d9260d605a630f95d938e6329db |
ContinousRotReprDecoder | import torch
import torch.nn as nn
import torch.nn.functional as F
class ContinousRotReprDecoder(nn.Module):
def __init__(self):
super(ContinousRotReprDecoder, self).__init__()
def forward(self, module_input):
reshaped_input = module_input.view(-1, 3, 2)
b1 = F.normalize(reshaped_inp... | 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... | LuckyDC/human_body_prior | ContinousRotReprDecoder | false | 5,565 | [
"Xnet",
"X11"
] | 1 | 6a46613b4cbd9c62d888359f1435cec501643af3 | https://github.com/LuckyDC/human_body_prior/tree/6a46613b4cbd9c62d888359f1435cec501643af3 |
FCDiscriminatorCriterion | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | charlesCXK/PixelSSL | FCDiscriminatorCriterion | false | 1,664 | [
"Apache-2.0"
] | 0 | 2e85e12c1db5b24206bfbbf2d7f6348ae82b2105 | https://github.com/charlesCXK/PixelSSL/tree/2e85e12c1db5b24206bfbbf2d7f6348ae82b2105 |
LinearBlock | # 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.... | Brikwerk/learn2learn | LinearBlock | false | 13,722 | [
"MIT"
] | 1,774 | 7997c13c26ec627d13ce77ba98427260df78ada8 | https://github.com/Brikwerk/learn2learn/tree/7997c13c26ec627d13ce77ba98427260df78ada8 |
Decoder | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
import torch
class Decoder(nn.Module):
def __init__(self, num_question, k_3, k_4, dropout_rate):
super(Decoder, self).__init__()
self.layer_2 = nn.Linear(k_4, num_question)
self.dropout = nn.Dropout... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
import torch
assert_size_stride = ... | Zoe0123/Diagnostic-Question-Challenge | Decoder | false | 6,029 | [
"MIT"
] | 1 | 49094ba757ac5b6afcf3ebe4d721c637ea4912b1 | https://github.com/Zoe0123/Diagnostic-Question-Challenge/tree/49094ba757ac5b6afcf3ebe4d721c637ea4912b1 |
FeatureResizer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.... | ShoufaChen/mdetr-1 | FeatureResizer | false | 11,878 | [
"Apache-2.0"
] | 0 | 3d9e40891ffdd39d6a5bf56730d468ace142752f | https://github.com/ShoufaChen/mdetr-1/tree/3d9e40891ffdd39d6a5bf56730d468ace142752f |
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
import torch.utils.data
assert_size_stride = torch._C._dyn... | HLTCHKUST/emotion-dialogue | Conv | false | 8,178 | [
"MIT"
] | 40 | 0d58b339134dd9a2f386948ae474b270a77370f9 | https://github.com/HLTCHKUST/emotion-dialogue/tree/0d58b339134dd9a2f386948ae474b270a77370f9 |
Capsule_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
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | AahanSingh/Capsule-Networks | Capsule_conv | false | 16,875 | [
"MIT"
] | 5 | 798014b6ff5fe27abdc64d3af364fb7681f292fc | https://github.com/AahanSingh/Capsule-Networks/tree/798014b6ff5fe27abdc64d3af364fb7681f292fc |
PoolFormerBlock | import math
import torch
import warnings
import torch.nn as nn
def _no_grad_trunc_normal_(tensor, mean, std, a, b):
"""Copy & paste from PyTorch official master until it's in a few official releases - RW
Method based on https://people.sc.fsu.edu/~jburkardt/presentations/truncated_normal.pdf
"""
def n... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import ... | TranNhiem/solo-learn | PoolFormerBlock | false | 1,168 | [
"MIT"
] | 0 | 7539732b68d153087d09a26a23e1edfdc49bc086 | https://github.com/TranNhiem/solo-learn/tree/7539732b68d153087d09a26a23e1edfdc49bc086 |
DocumentTopicDecoder | # 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.... | WuDiDaBinGe/TAKG | DocumentTopicDecoder | false | 1,234 | [
"MIT"
] | 0 | 83e608e677a4ee74722d18cb5ef430f4f6c6ad31 | https://github.com/WuDiDaBinGe/TAKG/tree/83e608e677a4ee74722d18cb5ef430f4f6c6ad31 |
Norm | import torch
from torch import nn
class Norm(nn.Module):
def __init__(self, order=1, size_average=True):
super().__init__()
self.order = order
self.average = size_average
def forward(self, inp, target=None):
if target is not None:
inp = inp - target
inp = ... | 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... | vzinche/inferno | Norm | false | 4,509 | [
"Apache-2.0"
] | 0 | 91b22dfcd1b6a9ec415f0bbb6ae66caea42f4034 | https://github.com/vzinche/inferno/tree/91b22dfcd1b6a9ec415f0bbb6ae66caea42f4034 |
Vflip | # 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... | IEM-Computer-Vision/kornia | Vflip | false | 9,264 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | f98bd9a2158a6e59cda076d55d476acf13f4e0af | https://github.com/IEM-Computer-Vision/kornia/tree/f98bd9a2158a6e59cda076d55d476acf13f4e0af |
GlobalMaxPooling | # 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... | zake7749/Sequence-to-Sequence-101 | GlobalMaxPooling | false | 16,786 | [
"MIT"
] | 64 | f9e9a8e836dc1cb3b35d6e148f6378fcd2736951 | https://github.com/zake7749/Sequence-to-Sequence-101/tree/f9e9a8e836dc1cb3b35d6e148f6378fcd2736951 |
TAGConv | # 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... | EdisonLeeeee/GraphGallery | TAGConv | false | 13,646 | [
"MIT"
] | 300 | 4eec9c5136bda14809bd22584b26cc346cdb633b | https://github.com/EdisonLeeeee/GraphGallery/tree/4eec9c5136bda14809bd22584b26cc346cdb633b |
BCE_disc_sm_v7 | # AOT ID: ['2_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | Sampson-Lee/SIB-Net | BCE_disc_sm_v7 | false | 2,829 | [
"MIT"
] | 0 | 650399082e9237327fa38168ccfc7d48153a1db5 | https://github.com/Sampson-Lee/SIB-Net/tree/650399082e9237327fa38168ccfc7d48153a1db5 |
CNN_DropOut | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import t... | MichaelLee-ceo/FedSAUC | CNN_DropOut | false | 5,597 | [
"Apache-2.0"
] | 1 | 8c00008772213562ff6a07bf9fa92c3831713118 | https://github.com/MichaelLee-ceo/FedSAUC/tree/8c00008772213562ff6a07bf9fa92c3831713118 |
BahdanauAttention | # 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.... | Ventu012/P2_Image_Captioning | BahdanauAttention | false | 2,935 | [
"MIT"
] | 0 | 320e620145205efbc9222ad0f840469c0ec8d091 | https://github.com/Ventu012/P2_Image_Captioning/tree/320e620145205efbc9222ad0f840469c0ec8d091 |
OutConv | import torch
import numpy as np
import torch.nn as nn
from abc import abstractmethod
class BaseModel(nn.Module):
"""
Base class for all models
"""
@abstractmethod
def forward(self, *inputs):
"""
Forward pass logic
:return: Model output
"""
raise NotImpleme... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
import torch.nn as nn
from abc import abstractmethod
assert_s... | ActonMartin/Unet_pytorch | OutConv | false | 8,885 | [
"MIT"
] | 0 | 561c596d65fd5976426366283a527d341e09d1e7 | https://github.com/ActonMartin/Unet_pytorch/tree/561c596d65fd5976426366283a527d341e09d1e7 |
AgentNN | import torch
class AgentNN(torch.nn.Module):
""" Simple network. """
def __init__(self, D_in, D_out):
super(AgentNN, self).__init__()
self.linear1 = torch.nn.Linear(D_in, 20)
self.h1 = torch.nn.Linear(20, 15)
self.linear2 = torch.nn.Linear(15, D_out)
self.activation = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride ... | gimait/DaDSbot | AgentNN | false | 12,423 | [
"MIT"
] | 0 | 6ee6fea2339faa9a9a2fce29c3b00def378d88d3 | https://github.com/gimait/DaDSbot/tree/6ee6fea2339faa9a9a2fce29c3b00def378d88d3 |
BahdanauAttn | # 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.... | Eurus-Holmes/VAG-NMT | BahdanauAttn | false | 8,082 | [
"Apache-2.0"
] | 12 | 38095c4a5477a0e7e2fa1592e8401aa9cddf2beb | https://github.com/Eurus-Holmes/VAG-NMT/tree/38095c4a5477a0e7e2fa1592e8401aa9cddf2beb |
GraphResConvolution | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn import Module
i... | SowmyaAitha/Palmira | GraphResConvolution | false | 17,943 | [
"MIT"
] | 6 | c3ae884e35b8b3703a5e4ba52d7b0bdae6da1bad | https://github.com/SowmyaAitha/Palmira/tree/c3ae884e35b8b3703a5e4ba52d7b0bdae6da1bad |
GeometricLoss | # 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 numpy as np
import torch.nn as nn
assert_size_stride = torch._C._d... | sanfengliao/DeepNavi | GeometricLoss | false | 10,732 | [
"Apache-2.0"
] | 0 | dc405ac0010075c2eea63083528db7cb765ad161 | https://github.com/sanfengliao/DeepNavi/tree/dc405ac0010075c2eea63083528db7cb765ad161 |
ITN2D | import torch
import torch.nn.functional as F
import torch.nn as nn
class ITN2D(nn.Module):
def __init__(self, input_channels):
super(ITN2D, self).__init__()
use_bias = True
self.conv11 = nn.Conv2d(input_channels, 2, kernel_size=3, padding=1,
bias=use_bias)
self.conv12 ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | swaroopkml96/istn | ITN2D | false | 16,533 | [
"Apache-2.0"
] | 91 | 600543e071aa56907509aa090697295cdc69a6b1 | https://github.com/swaroopkml96/istn/tree/600543e071aa56907509aa090697295cdc69a6b1 |
rSoftMax | import torch
from torch import nn
from torch.nn import functional as F
class rSoftMax(nn.Module):
def __init__(self, radix, cardinality):
super().__init__()
self.radix = radix
self.cardinality = cardinality
def forward(self, x):
batch = x.size(0)
if self.radix > 1:
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
a... | Kwongy/Pretrained-backbone-Pytorch | rSoftMax | false | 2,484 | [
"MIT"
] | 0 | 1b24bb677e0fd420cce32715c1ead8f0c804d707 | https://github.com/Kwongy/Pretrained-backbone-Pytorch/tree/1b24bb677e0fd420cce32715c1ead8f0c804d707 |
RAddFloat | import torch
class RAddFloat(torch.nn.Module):
def __init__(self):
super(RAddFloat, self).__init__()
def forward(self, x):
return 1.0 + 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... | NVIDIA-AI-IOT-private/torch2trt | RAddFloat | false | 10,525 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
DPFP | from torch.nn import Module
import torch
from torch import nn
import torch.utils.data
import torch.nn.functional
import torch.autograd
class DPFP(Module):
"""
## Deterministic Parameter Free Project (DPFP)
This is the new projection function $ extcolor{lightgreen}{\\phi}$ introduced in the paper.
DPF... | 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 import Module
from torch import nn
import torch.utils.data
import torch.nn.... | mcx/annotated_deep_learning_paper_implementations | DPFP | false | 7,198 | [
"MIT"
] | 1 | f169f3a71dd2d36eb28ad31062d3475efa367b88 | https://github.com/mcx/annotated_deep_learning_paper_implementations/tree/f169f3a71dd2d36eb28ad31062d3475efa367b88 |
ELU_1 | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_... | bantiitnab/kaggle-TGS-salt-identification | ELU_1 | false | 1,513 | [
"MIT"
] | 0 | 8b3350278b2ee8f01ba2a0734af9514d369f3228 | https://github.com/bantiitnab/kaggle-TGS-salt-identification/tree/8b3350278b2ee8f01ba2a0734af9514d369f3228 |
Sum | import torch
import numpy as np
import torch.nn.functional as F
from torch import nn
from torch.autograd import Variable as Variable
class Sum(nn.Module):
def __init__(self, in_channels, in_features, out_channels, dropout=0.0):
"""
Create a Sum layer.
Args:
in_channels (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 import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
f... | AmurG/SPFlow | Sum | false | 4,857 | [
"Apache-2.0"
] | 1 | ab28dd4af9ed722ace69c6b290cf0a279bbda39e | https://github.com/AmurG/SPFlow/tree/ab28dd4af9ed722ace69c6b290cf0a279bbda39e |
PairwiseLoss | import torch
import torch.nn as nn
class PairwiseLoss(nn.Module):
def __init__(self):
super().__init__()
self.m = 0
def forward(self, pos_out, neg_out):
distance = 1 - pos_out + neg_out
loss = torch.mean(torch.max(torch.tensor(0), distance))
return loss
def get_inpu... | 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... | GrantXie/wikidata-wikifier | PairwiseLoss | false | 17,305 | [
"MIT"
] | 3 | a65c9b71596e390999af9de7638eb8c8c13c1581 | https://github.com/GrantXie/wikidata-wikifier/tree/a65c9b71596e390999af9de7638eb8c8c13c1581 |
BCELoss | import torch
from torch import nn
import torch.nn.functional as F
import torchvision.transforms.functional as F
from torch.nn import functional as F
import torch.cuda
def binary_cross_entropy(inputs, target, weight=None, reduction='mean',
smooth_eps=None, from_logits=False):
"""cross entropy loss, with suppor... | 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 ... | RichardScottOZ/sota-data-augmentation-and-optimizers | BCELoss | false | 8,749 | [
"MIT"
] | 31 | 60128ca762ac2864a3b54c43c36d1d5aa2033e5a | https://github.com/RichardScottOZ/sota-data-augmentation-and-optimizers/tree/60128ca762ac2864a3b54c43c36d1d5aa2033e5a |
LxmertAttentionOutput | from _paritybench_helpers import _mock_config
import torch
from torch import nn
class LxmertAttentionOutput(nn.Module):
def __init__(self, config):
super().__init__()
self.dense = nn.Linear(config.hidden_size, config.hidden_size)
self.LayerNorm = nn.LayerNorm(config.hidden_size, eps=1e-12... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | rsgit95/med_kg_txt_multimodal | LxmertAttentionOutput | false | 4,205 | [
"Apache-2.0"
] | 0 | 80355b0cf58e0571531ad6f9728c533110ca996d | https://github.com/rsgit95/med_kg_txt_multimodal/tree/80355b0cf58e0571531ad6f9728c533110ca996d |
EqualLinearWithLeakyRelu | import math
import torch
from torch import nn
from torch.nn import functional as F
class EqualLinearWithLeakyRelu(nn.Module):
"""Add this class for onnx -- data driven flow is difficult tracing."""
def __init__(self, in_dim, out_dim, lr_mul=0.01):
super().__init__()
self.weight = nn.Parameter... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.as... | delldu/StyleGAN2 | EqualLinearWithLeakyRelu | false | 6,550 | [
"MIT",
"BSD-2-Clause",
"Apache-2.0"
] | 1 | 4bcba4673d3dc32ac3a67f6b5d5e24b490cdfbb3 | https://github.com/delldu/StyleGAN2/tree/4bcba4673d3dc32ac3a67f6b5d5e24b490cdfbb3 |
PreActBlockNoBN | # 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_... | arhik/LoCo | PreActBlockNoBN | false | 12,114 | [
"MIT"
] | 0 | de3792a8c5650ee1efa0682ad494a3b1b1be3dd0 | https://github.com/arhik/LoCo/tree/de3792a8c5650ee1efa0682ad494a3b1b1be3dd0 |
WeightNormConv2d | import torch
import torch.nn as nn
from torch.nn.utils.weight_norm import weight_norm
import torch.onnx
class WeightNormConv2d(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, stride=1,
padding=0, dilation=1, groups=1, bias=True, padding_mode='zeros'):
super(WeightNormConv2d... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | AntixK/Neural-Blocks | WeightNormConv2d | false | 17,016 | [
"MIT"
] | 3 | 018a44bbb703fc848234b95a3e604576bd9df88f | https://github.com/AntixK/Neural-Blocks/tree/018a44bbb703fc848234b95a3e604576bd9df88f |
EuclideanDistance | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data.dataloader
from torch import nn
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | chen-yuxuan/flair | EuclideanDistance | false | 12,206 | [
"MIT"
] | 0 | 480d2c9afd66ab8d3bf40a676917e84dba3c4cee | https://github.com/chen-yuxuan/flair/tree/480d2c9afd66ab8d3bf40a676917e84dba3c4cee |
ResidualBlock | import torch
import torch.nn as nn
import torch.nn.functional as F
class ResidualBlock(nn.Module):
def __init__(self, input_channel, output_channel, upsample=True):
super(ResidualBlock, self).__init__()
self.conv1 = nn.Conv2d(input_channel, output_channel, kernel_size=3,
padding=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.... | Holmes-Alan/TxST | ResidualBlock | false | 9,250 | [
"MIT"
] | 0 | c5b59a12bbb9e62244c3b608581d5cb9606525e0 | https://github.com/Holmes-Alan/TxST/tree/c5b59a12bbb9e62244c3b608581d5cb9606525e0 |
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 math as tl_math
import functools
impor... | SeHwanJoo/mmsegmentation_body | BCEDiceLoss | false | 1,049 | [
"Apache-2.0"
] | 0 | 31c4bf27c3dc0a84bfbb06a0c017c5908c17f0ac | https://github.com/SeHwanJoo/mmsegmentation_body/tree/31c4bf27c3dc0a84bfbb06a0c017c5908c17f0ac |
SinActivation | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_... | PeterouZh/CIPS-3D | SinActivation | false | 14,168 | [
"MIT"
] | 308 | 9b8bfa0fb23f642af042e150ccd70408f9d137c6 | https://github.com/PeterouZh/CIPS-3D/tree/9b8bfa0fb23f642af042e150ccd70408f9d137c6 |
PositionAttentionModule | import torch
import numpy as np
from torch import nn
from torch.nn import init
class ScaledDotProductAttention(nn.Module):
"""
Scaled dot-product attention
"""
def __init__(self, d_model, d_k, d_v, h, dropout=0.1):
"""
:param d_model: Output dimensionality of the model
:param ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | rushirajsherlocked/External-Attention-pytorch | PositionAttentionModule | false | 4,344 | [
"MIT"
] | 0 | 7d6814b2d90909adf81c62f3f8a89e30a59d6481 | https://github.com/rushirajsherlocked/External-Attention-pytorch/tree/7d6814b2d90909adf81c62f3f8a89e30a59d6481 |
MS_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
import torch.nn as nn
import torch.multiprocessing
import torch.onnx
assert_size... | cvmlarun/RANet | MS_Block | false | 6,511 | [
"Apache-2.0"
] | 1 | 3f67a3f36aaacd9cc7fb98ec79f77db8f1ebdc60 | https://github.com/cvmlarun/RANet/tree/3f67a3f36aaacd9cc7fb98ec79f77db8f1ebdc60 |
MultiHeadedAttention | # 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.... | haophancs/TREQS | MultiHeadedAttention | false | 15,501 | [
"MIT"
] | 149 | 49e354ce2a08cf963ec139d99936020e0f80ced8 | https://github.com/haophancs/TREQS/tree/49e354ce2a08cf963ec139d99936020e0f80ced8 |
ResizeConv2d | import torch
import torch.nn.functional as F
import torch.nn as nn
import torch.cuda
import torch.optim
import torch.utils.data
class ResizeConv2d(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, scale_factor,
mode='nearest'):
super().__init__()
self.scale_factor = 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
import torch.cuda
import torch.optim
import torch.utils.da... | AhmadQasim/MedAL | ResizeConv2d | false | 7,635 | [
"MIT"
] | 13 | 0ad6064d0d07f23722034b866ba86d93b62517f4 | https://github.com/AhmadQasim/MedAL/tree/0ad6064d0d07f23722034b866ba86d93b62517f4 |
SimpleConvTranspose2dModule | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.jit
import torch... | YaronBenAtar/glow | SimpleConvTranspose2dModule | false | 14,644 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
eca_layer | import torch
import torch.nn as nn
import torch.optim
class eca_layer(nn.Module):
"""Constructs a ECA module.
Args:
channel: Number of channels of the input feature map
k_size: Adaptive selection of kernel size
"""
def __init__(self, channel, k_size=3):
super(eca_layer, 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
import torch.optim
assert_size_stride = torch._C._dynamo.g... | purbayankar/PyTorch-Zero-Shot-Super-Resolution | eca_layer | false | 12,941 | [
"MIT"
] | 0 | 434fe5e84e166eef1f8c03880fc83c7e8749c49c | https://github.com/purbayankar/PyTorch-Zero-Shot-Super-Resolution/tree/434fe5e84e166eef1f8c03880fc83c7e8749c49c |
HardGRUCellNUAPT | import math
import torch
from torch import Tensor
import torch.nn as nn
import torch.nn.functional as F
from typing import Optional
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
def truncated_normal(t, mean=0.0, std=0.01):
torch.nn.init.normal_(t, mean=mea... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | pan185/UnarySim | HardGRUCellNUAPT | false | 7,449 | [
"MIT"
] | 1 | c03386efdbb8151f3c33f34b44d1d6a6fc960434 | https://github.com/pan185/UnarySim/tree/c03386efdbb8151f3c33f34b44d1d6a6fc960434 |
BatchHardTripletLoss | import torch
import torch.nn as nn
class BatchHardTripletLoss(nn.Module):
def __init__(self, margin=0):
super(BatchHardTripletLoss, self).__init__()
self.margin = margin
self.ranking_loss = nn.MarginRankingLoss(margin=margin)
def forward(self, inputs, targets):
batch_size = 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
from torch._inductor.runtime.... | chenyanghungry/person-reid-lib | BatchHardTripletLoss | false | 15,023 | [
"MIT"
] | 81 | 783e66c9bfedf582e2cf935b9f5be960b543ac3c | https://github.com/chenyanghungry/person-reid-lib/tree/783e66c9bfedf582e2cf935b9f5be960b543ac3c |
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.... | devjwsong/dialogue-error-correction-pytorch | Attention | false | 6,573 | [
"MIT"
] | 1 | ee0fa1f27eb995893a5943181a1fd0099a9e9202 | https://github.com/devjwsong/dialogue-error-correction-pytorch/tree/ee0fa1f27eb995893a5943181a1fd0099a9e9202 |
CrossEntropyLoss | import torch
import torch.utils.data
import torch
import torch.nn as nn
class CrossEntropyLoss(nn.Module):
def __init__(self, label_nc):
super(CrossEntropyLoss, self).__init__()
self.softmax = nn.LogSoftmax(dim=1)
self.criterion = nn.NLLLoss2d()
def forward(self, output, 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 math as tl_math
import torch.utils.dat... | WeisiX/ITAS3D | CrossEntropyLoss | false | 18,085 | [
"MIT"
] | 4 | fc861e0cb2d4516905bfadab5e5e880c2b021832 | https://github.com/WeisiX/ITAS3D/tree/fc861e0cb2d4516905bfadab5e5e880c2b021832 |
ESA | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import autograd as autograd
import torch.fft
from itertools import product as product
class ESA(nn.Module):
def __init__(self, channel=64, reduction=4, bias=True):
super(ESA, self).__init__()
self.r_nc = channel // redu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | hduba/KAIR | ESA | false | 3,600 | [
"MIT"
] | 0 | dbd7596c7e4a4667b9b7baac369fc6c02571fa58 | https://github.com/hduba/KAIR/tree/dbd7596c7e4a4667b9b7baac369fc6c02571fa58 |
L1Norm | import torch
import torch.nn as nn
class L1Norm(nn.Module):
def __init__(self):
super(L1Norm, self).__init__()
self.eps = 1e-10
def forward(self, x):
norm = torch.sum(torch.abs(x), dim=1) + self.eps
x = x / norm.expand_as(x)
return x
def get_inputs():
return [to... | 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... | bankbiz/Key.Net | L1Norm | false | 12,149 | [
"BSD-3-Clause-Clear"
] | 0 | 5ba46614821e94be1b36d97721bd6c2e5fff9e20 | https://github.com/bankbiz/Key.Net/tree/5ba46614821e94be1b36d97721bd6c2e5fff9e20 |
GammaScaleMap | import torch
import torch.nn as nn
import torch.autograd
class GammaScaleMap(nn.Module):
"""
Compute Gamma Scale on a 4D tensor (The hard way). This acts as a standard PyTorch layer.
Gamma Scale is computed independantly for each batch item at each location x,y
Input should ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torch.nn as nn
import torch.autograd
assert_size_stride... | LLNL/fastcam | GammaScaleMap | false | 8,434 | [
"BSD-3-Clause"
] | 25 | 99cefe37528014247319468cf05f54fef259d3bf | https://github.com/LLNL/fastcam/tree/99cefe37528014247319468cf05f54fef259d3bf |
LossFunc | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | xenbaloch/efficientderain | LossFunc | false | 16,743 | [
"MIT"
] | 109 | d5646815fd14a5a03c859102ecd2f298db7e53be | https://github.com/xenbaloch/efficientderain/tree/d5646815fd14a5a03c859102ecd2f298db7e53be |
SymEncoder | import torch
from torch import nn
import torch.utils.data
class SymEncoder(nn.Module):
def __init__(self, feature_size, symmetry_size, hidden_size):
super(SymEncoder, self).__init__()
self.left = nn.Linear(feature_size, hidden_size)
self.right = nn.Linear(symmetry_size, hidden_size)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | kevin-kaixu/grass_pytorch | SymEncoder | false | 15,814 | [
"Apache-2.0"
] | 85 | 1d8dc6dcc0ab3ca029e449f57c37ba3910a4f90a | https://github.com/kevin-kaixu/grass_pytorch/tree/1d8dc6dcc0ab3ca029e449f57c37ba3910a4f90a |
AvgPoolPad | # 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... | Danish-VSL/deep-person-reid | AvgPoolPad | false | 13,547 | [
"MIT"
] | 244 | 2e3a4b6706b84c77203f9905683b917ab0871b93 | https://github.com/Danish-VSL/deep-person-reid/tree/2e3a4b6706b84c77203f9905683b917ab0871b93 |
_CNN | # 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... | Lnna/OpenNRE-PyTorch | _CNN | false | 5,692 | [
"MIT"
] | 1 | 907026a8bece7a867558087131cd1e97d41eb3f2 | https://github.com/Lnna/OpenNRE-PyTorch/tree/907026a8bece7a867558087131cd1e97d41eb3f2 |
Critic | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | DougTrajano/ds_drl_continuous_control | Critic | false | 11,379 | [
"MIT"
] | 0 | a160b53f68f9fc30c917038af406367dcaa44dc7 | https://github.com/DougTrajano/ds_drl_continuous_control/tree/a160b53f68f9fc30c917038af406367dcaa44dc7 |
ContrastiveLoss | import torch
import torch.nn.functional as F
class ContrastiveLoss(torch.nn.Module):
"""
Contrastive loss function.
Based on: http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf
"""
def __init__(self, margin=2.0):
super(ContrastiveLoss, self).__init__()
self.margin =... | 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
assert_size_stride = torch._... | Rajat-Mehta/Vehicle-Re-identification-UI | ContrastiveLoss | false | 5,756 | [
"MIT"
] | 1 | 9769ae9dac8bd43a3b66f705cb2830fa498649d2 | https://github.com/Rajat-Mehta/Vehicle-Re-identification-UI/tree/9769ae9dac8bd43a3b66f705cb2830fa498649d2 |
DiagonalwiseRefactorization | import torch
import numpy as np
import torch.nn.parallel
import torch.optim
import torch
import torch.nn as nn
import torch.utils.data
import torch.utils.data.distributed
def get_mask(in_channels, channels, ks):
in_channels = int(in_channels)
channels = int(channels)
if len(ks) == 1:
mask = np.zer... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
import torch.nn.parallel
import torch.optim
import torch
impo... | LaputaDream/region-based-non-local-network | DiagonalwiseRefactorization | false | 8,432 | [
"MIT"
] | 18 | 98e5fb3d8010e8c5360ac3066fdc06c37106d7dc | https://github.com/LaputaDream/region-based-non-local-network/tree/98e5fb3d8010e8c5360ac3066fdc06c37106d7dc |
Envelope | import torch
import torch.fx
import torch.utils.data
class Envelope(torch.nn.Module):
def __init__(self, exponent):
super(Envelope, self).__init__()
self.p = exponent + 1
self.a = -(self.p + 1) * (self.p + 2) / 2
self.b = self.p * (self.p + 2)
self.c = -self.p * (self.p + ... | 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.fx
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynam... | JinheonBaek/pytorch_geometric | Envelope | false | 17,513 | [
"MIT"
] | 4 | dfd32d08a3d8191d6290e53458d4eda515d04fd6 | https://github.com/JinheonBaek/pytorch_geometric/tree/dfd32d08a3d8191d6290e53458d4eda515d04fd6 |
SoftArgmax2D | # 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
... | Mykko/Human-Path-Prediction | SoftArgmax2D | false | 2,682 | [
"MIT"
] | 0 | 956fcf16b98c81cf8e23133f9a766192e17e63e0 | https://github.com/Mykko/Human-Path-Prediction/tree/956fcf16b98c81cf8e23133f9a766192e17e63e0 |
MultiHead | # 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.... | matatabinoneko/densecap | MultiHead | false | 12,787 | [
"BSD-3-Clause"
] | 0 | 723d9c2cfd3f16b2eb7584cc7cb0aaef973854dd | https://github.com/matatabinoneko/densecap/tree/723d9c2cfd3f16b2eb7584cc7cb0aaef973854dd |
TorchAdd | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | Akababa/torch2trt | TorchAdd | false | 18,426 | [
"MIT"
] | 2 | 03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 | https://github.com/Akababa/torch2trt/tree/03063b74a7eb40f5aac88d49be6b8b5e4e4e92d7 |
DepthwiseSeparableConv | import torch
import torch.nn.functional as F
import torch.nn as nn
class DepthwiseSeparableConv(nn.Module):
def __init__(self, in_ch, out_ch, k, bias=True):
super().__init__()
self.depthwise_conv = nn.Conv1d(in_channels=in_ch, out_channels=
in_ch, kernel_size=k, groups=in_ch, 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
import torch.nn as nn
assert_... | MobtgZhang/MWMLNet | DepthwiseSeparableConv | false | 5,607 | [
"MIT"
] | 1 | 125bb39935916b6b4be505c51cb6a04eb49b96d0 | https://github.com/MobtgZhang/MWMLNet/tree/125bb39935916b6b4be505c51cb6a04eb49b96d0 |
GCN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn import Module
i... | DAIZHENWEI/FastGCN_pytorch | GCN | false | 336 | [
"MIT"
] | 0 | 87efe350d5acbe517a0642e9862ac9676b55c053 | https://github.com/DAIZHENWEI/FastGCN_pytorch/tree/87efe350d5acbe517a0642e9862ac9676b55c053 |
Downsample | import torch
import numpy as np
class BaseModule(torch.nn.Module):
def __init__(self):
super(BaseModule, self).__init__()
@property
def nparams(self):
"""
Returns number of trainable parameters of the module.
"""
num_params = 0
for name, param in self.name... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stri... | Sobsz/uberduck-ml-dev | Downsample | false | 1,068 | [
"Apache-2.0"
] | 0 | f099238f6f2e3f600d72d89dea3c883c59d91387 | https://github.com/Sobsz/uberduck-ml-dev/tree/f099238f6f2e3f600d72d89dea3c883c59d91387 |
GateGRUSelectionLayer | import torch
import torch.nn as nn
class GateGRUSelectionLayer(nn.Module):
def __init__(self, dim_model, dim_ff, prob_dropout):
super(GateGRUSelectionLayer, self).__init__()
self.reset = nn.Linear(dim_model * 2, dim_model)
self.update = nn.Linear(dim_model * 2, dim_model)
self.pro... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | KirkGuo/HCN | GateGRUSelectionLayer | false | 5,450 | [
"MIT"
] | 1 | 7d8020c8d76413b6ca3a359fb2e9b34652949e17 | https://github.com/KirkGuo/HCN/tree/7d8020c8d76413b6ca3a359fb2e9b34652949e17 |
ModulatedToRGB | # 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
from functools import partial
from torch.nn import functio... | Sardhendu/mmediting | ModulatedToRGB | false | 9,901 | [
"Apache-2.0"
] | 0 | 623b59ac758d856abc9fab7e845beeab61074d8f | https://github.com/Sardhendu/mmediting/tree/623b59ac758d856abc9fab7e845beeab61074d8f |
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