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 |
|---|---|---|---|---|---|---|---|---|---|---|
InformedSender | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
import torch.utils.data
import torch.distributions
class InformedSender(nn.Module):
def __init__(self, game_size, feat_size, embedding_size, hidden_size,
vocab_size=100, temp=1.0):
super(InformedSender, 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.... | ptigas/EGG | InformedSender | false | 7,507 | [
"MIT"
] | 1 | 5319cc9de2c17bc72de717737cfbb5be2285c59b | https://github.com/ptigas/EGG/tree/5319cc9de2c17bc72de717737cfbb5be2285c59b |
RobertaLMHead | # 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 ... | BlackNoodle/TUCORE-GCN | RobertaLMHead | false | 8,784 | [
"MIT"
] | 27 | 16fb37d81c5b1182a31fcf7da08a9c0013b20cd6 | https://github.com/BlackNoodle/TUCORE-GCN/tree/16fb37d81c5b1182a31fcf7da08a9c0013b20cd6 |
CMVN | # 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_... | Ethan07902050/s3prl | CMVN | false | 2,271 | [
"MIT"
] | 0 | 854aff0b3062fc2cff531401923b8745f64701e7 | https://github.com/Ethan07902050/s3prl/tree/854aff0b3062fc2cff531401923b8745f64701e7 |
conv_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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | naver-ai/PfLayer | conv_embedding | false | 16,138 | [
"Apache-2.0"
] | 59 | da8f80b2ea3b6bd7fbee3beee8b1516c89bc0441 | https://github.com/naver-ai/PfLayer/tree/da8f80b2ea3b6bd7fbee3beee8b1516c89bc0441 |
NgramCombined | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.cuda
import torch.distributed
class NgramCombined(nn.Module):
def __init__(self, n_gram):
super(NgramCombined, self).__init__()
self.n_gram = n_gram
def forward(self, x):
out = x
if self.n_gram > ... | 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.cuda
import torch.distributed
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strid... | phuongnm-bkhn/OpenNMT-py | NgramCombined | false | 10,630 | [
"MIT"
] | 0 | 554a826139f1bfc55f4ea6a3e7491858c2afec4c | https://github.com/phuongnm-bkhn/OpenNMT-py/tree/554a826139f1bfc55f4ea6a3e7491858c2afec4c |
ResidualBlock | import torch
import torch.nn as nn
class ConvLayer(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, stride, norm
=None, bias=True):
super(ConvLayer, self).__init__()
reflection_padding = kernel_size // 2
self.reflection_pad = nn.ReflectionPad2d(reflection_pad... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | alhsu713/fast_blind_video_consistency | ResidualBlock | false | 12,078 | [
"MIT"
] | 0 | 2037ec5f68a361b926c31b3a12c1cd04e2331797 | https://github.com/alhsu713/fast_blind_video_consistency/tree/2037ec5f68a361b926c31b3a12c1cd04e2331797 |
ELUPlus | import torch
from torch import nn
import torch.nn
class ELUPlus(nn.Module):
def __init__(self):
super().__init__()
self.elu = nn.ELU()
def forward(self, x):
return self.elu(x) + 1.0
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
import torch.nn
assert_size_stride = torch._C._dynamo.guar... | KailinLi/nflows | ELUPlus | false | 8,381 | [
"MIT"
] | 13 | 7c07a1d5e510beb681d1b11d6ffda95a086a8153 | https://github.com/KailinLi/nflows/tree/7c07a1d5e510beb681d1b11d6ffda95a086a8153 |
ContourDTConsistency | import torch
from typing import Optional
import torch.utils.data
import torch.nn as nn
import torch.nn.parallel
class ContourDTConsistency(nn.Module):
"""Consistency regularization between the instance contour map and
signed distance transform.
Args:
pred1 (torch.Tensor): contour logits.
... | 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... | devaansh100/pytorch_connectomics | ContourDTConsistency | false | 6,553 | [
"MIT"
] | 1 | b1e4b16b0480546ea806d14876208080815ed964 | https://github.com/devaansh100/pytorch_connectomics/tree/b1e4b16b0480546ea806d14876208080815ed964 |
LinearActivation | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch.nn impor... | axiserr/Hetu | LinearActivation | false | 14,936 | [
"Apache-2.0"
] | 82 | 0052f727488db0570d6b37f63549b43b0920bc29 | https://github.com/axiserr/Hetu/tree/0052f727488db0570d6b37f63549b43b0920bc29 |
TimeVarFIRFilter | import torch
import torch.utils.data
import torch.nn as torch_nn
import torch.nn.functional as torch_nn_func
class TimeVarFIRFilter(torch_nn.Module):
""" TimeVarFIRFilter
Given sequences of filter coefficients and a signal, do filtering
Filter coefs: (batchsize=1, signal_length, filter_order = 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
import torch.utils.data
import torch.nn as torch_nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = tor... | Ninushkat/Impact-Synth-Hardware | TimeVarFIRFilter | false | 14,091 | [
"MIT"
] | 55 | 37a2ecfec51b052b39d1ad0d4676f09d5f00e3c2 | https://github.com/Ninushkat/Impact-Synth-Hardware/tree/37a2ecfec51b052b39d1ad0d4676f09d5f00e3c2 |
FocusLayer | import torch
import torch.nn as nn
class FocusLayer(nn.Module):
def __init__(self, c1, c2, k=1):
super().__init__()
def forward(self, x):
return torch.cat([x[..., ::2], x[..., 1::2]], dim=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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | gdevos010/Informer2020 | FocusLayer | false | 3,526 | [
"Apache-2.0"
] | 0 | 607a1981ff8b8009eda3570a1ea4c9617289c9f2 | https://github.com/gdevos010/Informer2020/tree/607a1981ff8b8009eda3570a1ea4c9617289c9f2 |
OffsetNet | import torch
import torch.nn as nn
class OffsetNet(nn.Module):
"""OffsetNet in Temporal interlace module.
The OffsetNet consists of one convolution layer and two fc layers
with a relu activation following with a sigmoid function. Following
the convolution layer, two fc layers and relu are applied to ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | Viditagarwal7479/Video-Swin-Transformer | OffsetNet | false | 18,087 | [
"Apache-2.0"
] | 9 | 37910ef3141c7b2eef76544f9ec8bdf26ec94c7d | https://github.com/Viditagarwal7479/Video-Swin-Transformer/tree/37910ef3141c7b2eef76544f9ec8bdf26ec94c7d |
BCELoss | # 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... | schokoro/torchutils | BCELoss | false | 10,743 | [
"MIT"
] | 0 | bcab35e8c943a1fcd4550fbb023188fa5d688663 | https://github.com/schokoro/torchutils/tree/bcab35e8c943a1fcd4550fbb023188fa5d688663 |
DenoisingDownsample | import torch
import torch.nn as nn
class DenoisingDownsample(nn.Module):
"""Downsampling operation used in the denoising network. Support average
pooling and convolution for downsample operation.
Args:
in_channels (int): Number of channels of the input feature map to be
downsampled.
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | arkel23/mmgeneration | DenoisingDownsample | false | 9,944 | [
"Apache-2.0"
] | 0 | 41a30e2972f2037f6aac60ed761bed3fe47bfe4d | https://github.com/arkel23/mmgeneration/tree/41a30e2972f2037f6aac60ed761bed3fe47bfe4d |
DepthwiseSeparableConv | # 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_... | raghavjajodia/squad | DepthwiseSeparableConv | false | 13,018 | [
"MIT"
] | 0 | 4eb6ccdfaa904aa97215c8bc65cd77b54ff54601 | https://github.com/raghavjajodia/squad/tree/4eb6ccdfaa904aa97215c8bc65cd77b54ff54601 |
BiAffine | # 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
import torch.utils.data
from torch.nn import Parameter
asse... | FengZiYjun/fastNLP | BiAffine | false | 5,163 | [
"Apache-2.0"
] | 1 | 3ae73ab0a05d1ceef4a5181516891a8057d7f719 | https://github.com/FengZiYjun/fastNLP/tree/3ae73ab0a05d1ceef4a5181516891a8057d7f719 |
DeepCritic | # 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... | drib861204/Soft-Actor-Critic-and-Extensions | DeepCritic | false | 15,236 | [
"MIT"
] | 143 | 3075df7430c1c49177b3798d753a9e3f6226672e | https://github.com/drib861204/Soft-Actor-Critic-and-Extensions/tree/3075df7430c1c49177b3798d753a9e3f6226672e |
SeqToSeqAtten | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | xdong73S/Match_LSTM_v2.0 | SeqToSeqAtten | false | 4,572 | [
"MIT"
] | 0 | dfb8cfbc2a5dafc6655eecf151a7dbcf808cd729 | https://github.com/xdong73S/Match_LSTM_v2.0/tree/dfb8cfbc2a5dafc6655eecf151a7dbcf808cd729 |
StridedStyle | # 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... | PeterouZh/GAN2Shape | StridedStyle | false | 14,172 | [
"MIT"
] | 421 | ea077e543a3fb824ce06385e8a837dcbae8e9aaa | https://github.com/PeterouZh/GAN2Shape/tree/ea077e543a3fb824ce06385e8a837dcbae8e9aaa |
RgbaToBgr | # 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 | RgbaToBgr | false | 9,259 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | f98bd9a2158a6e59cda076d55d476acf13f4e0af | https://github.com/IEM-Computer-Vision/kornia/tree/f98bd9a2158a6e59cda076d55d476acf13f4e0af |
SegmentationLosses | import torch
import torch.nn as nn
class SegmentationLosses(nn.CrossEntropyLoss):
"""2D Cross Entropy Loss with Auxilary Loss"""
def __init__(self, weight=None, ignore_index=-1):
super(SegmentationLosses, self).__init__(weight, None, ignore_index)
def forward(self, pred, target):
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
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | MarcosPampuch/TDNet_CARLA | SegmentationLosses | false | 803 | [
"MIT"
] | 0 | efc1c872966f1cef49b82723170586a6abcfb524 | https://github.com/MarcosPampuch/TDNet_CARLA/tree/efc1c872966f1cef49b82723170586a6abcfb524 |
ValueNetwork | # 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_... | DensoITLab/spinningup_in_pytorch | ValueNetwork | false | 7,962 | [
"MIT"
] | 11 | 612d8c4c6593c8c5ecb5a939bf43085daac9e552 | https://github.com/DensoITLab/spinningup_in_pytorch/tree/612d8c4c6593c8c5ecb5a939bf43085daac9e552 |
UpSampleLayer | import torch
import torch.utils.data
import torch.nn as torch_nn
import torch.nn.functional as torch_nn_func
class Conv1dKeepLength(torch_nn.Conv1d):
""" Wrapper for causal convolution
Input tensor: (batchsize=1, length, dim_in)
Output tensor: (batchsize=1, length, dim_out)
https://github.com/pytorch... | 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 torch_nn
import torch.nn.functional as torch_nn_func
assert_size_stride = torch._C._dynamo.guards... | Ninushkat/Impact-Synth-Hardware | UpSampleLayer | false | 14,090 | [
"MIT"
] | 55 | 37a2ecfec51b052b39d1ad0d4676f09d5f00e3c2 | https://github.com/Ninushkat/Impact-Synth-Hardware/tree/37a2ecfec51b052b39d1ad0d4676f09d5f00e3c2 |
MNISTClassifier | # 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 torchvision
import tor... | developer0hye/PyTorch-Deformable-Convolution-v2 | MNISTClassifier | false | 15,194 | [
"MIT"
] | 70 | 3ed601fa70ee111278b95b134caf29e085642bc2 | https://github.com/developer0hye/PyTorch-Deformable-Convolution-v2/tree/3ed601fa70ee111278b95b134caf29e085642bc2 |
DuelingQNetwork | # 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_... | czarrar/udacity_rl | DuelingQNetwork | false | 9,970 | [
"MIT"
] | 0 | d5e9a878b24e6234ab4ac9f612be103bb7f933c4 | https://github.com/czarrar/udacity_rl/tree/d5e9a878b24e6234ab4ac9f612be103bb7f933c4 |
Conv2dSamePadding | # 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
import torch.nn.functional as F
assert_size_stride = torch.... | hulaba/pycrop-yield-prediction | Conv2dSamePadding | false | 6,830 | [
"MIT"
] | 1 | b4790dc2f87a73e8a0604e8c22466314090c5abf | https://github.com/hulaba/pycrop-yield-prediction/tree/b4790dc2f87a73e8a0604e8c22466314090c5abf |
FDiv | import torch
import torch.nn as nn
class FDiv(nn.Module):
def __init__(self):
super(FDiv, self).__init__()
def forward(self, x, y):
x = x / 2
y = y / 2
x = x / y
return x
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_ini... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | dawnclaude/onnx2keras | FDiv | false | 15,132 | [
"MIT"
] | 115 | 3d2a47c0a228b91fd434232274e216e491da36e3 | https://github.com/dawnclaude/onnx2keras/tree/3d2a47c0a228b91fd434232274e216e491da36e3 |
GLU | # 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... | MichaelHopwood/GLRM | GLU | false | 5,588 | [
"MIT"
] | 1 | 80930762e6964afb8ef0db9e5ae3a10cfcc975b2 | https://github.com/MichaelHopwood/GLRM/tree/80930762e6964afb8ef0db9e5ae3a10cfcc975b2 |
Generator | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.a... | nigelnnk/MATCh-sensitivity | Generator | false | 7,338 | [
"MIT"
] | 1 | aaf2b924ac98c8c5925bbf431481724d11a102f8 | https://github.com/nigelnnk/MATCh-sensitivity/tree/aaf2b924ac98c8c5925bbf431481724d11a102f8 |
ResidualBlock | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guard... | L-Net-1992/DI-engine | ResidualBlock | false | 5,490 | [
"Apache-2.0"
] | 1 | 06803b4e18fa64bbed0fd1d44952242c0c063b0f | https://github.com/L-Net-1992/DI-engine/tree/06803b4e18fa64bbed0fd1d44952242c0c063b0f |
MnistMlp | # 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.... | shyam196/exptune | MnistMlp | false | 12,986 | [
"MIT"
] | 0 | be9bb23355ecd1a464dbc93dc35050b7f9d40227 | https://github.com/shyam196/exptune/tree/be9bb23355ecd1a464dbc93dc35050b7f9d40227 |
Sentence_Maxpool | # 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_... | Tiamat-Tech/just-ask | Sentence_Maxpool | false | 14,501 | [
"Apache-2.0"
] | 59 | 80725161e12ad0682b4c2091f61a5889a335ba21 | https://github.com/Tiamat-Tech/just-ask/tree/80725161e12ad0682b4c2091f61a5889a335ba21 |
NormalizationLayer | # 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.init
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Harshdeep1996/jina-hub | NormalizationLayer | false | 2,330 | [
"Apache-2.0"
] | 0 | 880ff719715b89969860c70219d26a931a031d10 | https://github.com/Harshdeep1996/jina-hub/tree/880ff719715b89969860c70219d26a931a031d10 |
NegativeLearningLoss | # 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
... | BIT-DA/RIPU | NegativeLearningLoss | false | 16,953 | [
"MIT"
] | 9 | 125edf112c9ded1e7497aedb2a092331824df100 | https://github.com/BIT-DA/RIPU/tree/125edf112c9ded1e7497aedb2a092331824df100 |
CharbonnierLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import... | Blatts01/VckImageRestoration | CharbonnierLoss | false | 2,026 | [
"MIT"
] | 0 | ae4e2221d9d4e236a08722cb92ac5cc88947e311 | https://github.com/Blatts01/VckImageRestoration/tree/ae4e2221d9d4e236a08722cb92ac5cc88947e311 |
TracedModule | # 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.parallel
import torch.optim
import torch.util... | ScorpioDoctor/antares02 | TracedModule | false | 1,024 | [
"BSD-3-Clause"
] | 0 | 631b817d2e98f351d1173b620d15c4a5efed11da | https://github.com/ScorpioDoctor/antares02/tree/631b817d2e98f351d1173b620d15c4a5efed11da |
MatrixAttention | # 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 math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guar... | Aunsiels/qagnn | MatrixAttention | false | 11,303 | [
"MIT"
] | 0 | d89a3dd650ac4b8b8aae34e0cce7cfc698892d80 | https://github.com/Aunsiels/qagnn/tree/d89a3dd650ac4b8b8aae34e0cce7cfc698892d80 |
SequentialPolarizedSelfAttention | # 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.... | LeftAttention/Attention-Codebase | SequentialPolarizedSelfAttention | false | 17,665 | [
"Apache-2.0"
] | 6 | 348ec66233a7c0f95a3cb5f0f11641e2a7a9b9c3 | https://github.com/LeftAttention/Attention-Codebase/tree/348ec66233a7c0f95a3cb5f0f11641e2a7a9b9c3 |
SimpleModule | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleModule(torch.nn.Module):
def __init__(self):
super(SimpleModule, self).__init__()
def forward(self, x):
y = x + x
y = y + 2
return y
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get... | 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.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | YaronBenAtar/glow | SimpleModule | false | 14,669 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
AdaIN | # 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
assert_size_stride ... | pigunther/Self-Correction-Human-Parsing-Updated | AdaIN | false | 7,467 | [
"MIT"
] | 1 | 17331eaa5d6586a1ebb633eb61ed810d00d30a2f | https://github.com/pigunther/Self-Correction-Human-Parsing-Updated/tree/17331eaa5d6586a1ebb633eb61ed810d00d30a2f |
DiagLinear | # 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 math
from torch import Tensor
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda... | nihaarshah/behavenet | DiagLinear | false | 12,829 | [
"MIT"
] | 0 | 35bf5360e136075ca5ec30b3f98a2112a53e992c | https://github.com/nihaarshah/behavenet/tree/35bf5360e136075ca5ec30b3f98a2112a53e992c |
MultiHeadAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data.distributed
class ScaledDotProductAttention(nn.Module):
""" Scaled Dot-Product Attention """
def __init__(self, temperature, attn_dropout=0.1):
super().__init__()
self.temperature = temperature
def... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | QiuhongAnnaWei/IBRNet | MultiHeadAttention | false | 14,276 | [
"Apache-2.0"
] | 254 | 6c8b68e6d95eae04535ff0906387ec7899f5d5ce | https://github.com/QiuhongAnnaWei/IBRNet/tree/6c8b68e6d95eae04535ff0906387ec7899f5d5ce |
MetapathAggrLayer | import torch
from torch.nn import functional as F
from torch import nn
class MetapathAggrLayer(nn.Module):
"""
metapath attention layer.
"""
def __init__(self, in_features, nmeta, dropout, alpha):
super(MetapathAggrLayer, self).__init__()
self.dropout = dropout
self.in_feature... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | dingdanhao110/HINGCN | MetapathAggrLayer | false | 1,850 | [
"MIT"
] | 0 | 281b73c03bd3b00e35bce4c5e1c27076233555e4 | https://github.com/dingdanhao110/HINGCN/tree/281b73c03bd3b00e35bce4c5e1c27076233555e4 |
DPLSTMCell | # 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 ... | anibadde/opacus | DPLSTMCell | false | 14,872 | [
"Apache-2.0"
] | 958 | be221231e1b579bdae4ad34c8ae0c7c4928cee25 | https://github.com/anibadde/opacus/tree/be221231e1b579bdae4ad34c8ae0c7c4928cee25 |
ResidualBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | JEF1056/Reconstruction-Style | ResidualBlock | false | 17,467 | [
"MIT"
] | 6 | 3430d9e9f05c6980ae251cf15b619148a2c899d6 | https://github.com/JEF1056/Reconstruction-Style/tree/3430d9e9f05c6980ae251cf15b619148a2c899d6 |
L2Norm | import torch
import torch.nn as nn
from random import *
class L2Norm(nn.Module):
def __init__(self, n_channels, scale=1.0):
super(L2Norm, self).__init__()
self.n_channels = n_channels
self.scale = scale
self.eps = 1e-10
self.weight = nn.Parameter(torch.Tensor(self.n_channe... | 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
from random import *
assert_size_stride = torch._C._dynam... | Hoclor/CoSADUV-Contextual-Saliency-for-Detecting-Anomalies-in-UAV-Video | L2Norm | false | 17,381 | [
"MIT"
] | 4 | 674b72af15ba8833317b8daa9d1e614ea63151c1 | https://github.com/Hoclor/CoSADUV-Contextual-Saliency-for-Detecting-Anomalies-in-UAV-Video/tree/674b72af15ba8833317b8daa9d1e614ea63151c1 |
BertSelfAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | IsaacChanghau/ReLoCLNet | BertSelfAttention | false | 8,805 | [
"MIT"
] | 31 | 56cb666ce516cce9acbcfce78fb4e95d81e11e54 | https://github.com/IsaacChanghau/ReLoCLNet/tree/56cb666ce516cce9acbcfce78fb4e95d81e11e54 |
MaskNet | import torch
import torch.nn as nn
from itertools import product as product
class MaskNet(nn.Module):
def __init__(self):
super(MaskNet, self).__init__()
self.conv1 = nn.Conv2d(in_channels=1, out_channels=16, kernel_size=
5, stride=1, padding=2)
self.relu1 = nn.ReLU()
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 it... | DongChengdongHangZhou/caffe-to-pytorch | MaskNet | false | 2,280 | [
"Apache-2.0"
] | 0 | 5e3104f3aa77d35bad5d2de235b067460c136fd5 | https://github.com/DongChengdongHangZhou/caffe-to-pytorch/tree/5e3104f3aa77d35bad5d2de235b067460c136fd5 |
MatrixAttention | import math
import torch
import torch.nn as nn
class SimilarityFunction(nn.Module):
"""
A ``SimilarityFunction`` takes a pair of tensors with the same shape, and computes a similarity
function on the vectors in the last dimension. For example, the tensors might both have shape
`(batch_size, sentence_... | 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.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guar... | michiyasunaga/GreaseLM | MatrixAttention | false | 16,046 | [
"MIT"
] | 76 | 596aa5047841e3e97730f621a2e4576772733df2 | https://github.com/michiyasunaga/GreaseLM/tree/596aa5047841e3e97730f621a2e4576772733df2 |
GramLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | NejcHirci/material-addon | GramLoss | false | 17,779 | [
"MIT"
] | 4 | c08e2081413c3319b712c2f7193ac8013f601382 | https://github.com/NejcHirci/material-addon/tree/c08e2081413c3319b712c2f7193ac8013f601382 |
Cutout | import random
import torch
def _gen_cutout_coord(height, width, size):
height_loc = random.randint(0, height - 1)
width_loc = random.randint(0, width - 1)
upper_coord = max(0, height_loc - size // 2), max(0, width_loc - size // 2)
lower_coord = min(height, height_loc + size // 2), min(width, width_loc... | 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 random
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cu... | DensoITLab/TeachAugment | Cutout | false | 7,966 | [
"BSD-2-Clause"
] | 20 | 66ec099a0afab99e18531c5437182cfe17dc30c8 | https://github.com/DensoITLab/TeachAugment/tree/66ec099a0afab99e18531c5437182cfe17dc30c8 |
LayerScale_Block_CA | # 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.... | WangFeng18/deit | LayerScale_Block_CA | false | 11,970 | [
"Apache-2.0"
] | 0 | 62a2c54faf683af8316fbec2e99f666879949cb4 | https://github.com/WangFeng18/deit/tree/62a2c54faf683af8316fbec2e99f666879949cb4 |
sobel_net | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | phonhay103/DocTr | sobel_net | false | 7,470 | [
"MIT"
] | 1 | f052703976e2558633027907af48ecb1dc7718ff | https://github.com/phonhay103/DocTr/tree/f052703976e2558633027907af48ecb1dc7718ff |
Actor | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
from torch.optim.lr_scheduler import *
import torch.optim.lr_scheduler
import torch.quantization
import torch.onnx
import torch.testing
class Actor(nn.Module):
def __init__(self, nb_states, nb_actions, hidden1=... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | Donfa1con/distiller | Actor | false | 11,524 | [
"Apache-2.0"
] | 0 | 645ee41bfebc463523b228ff087e41619607d8b2 | https://github.com/Donfa1con/distiller/tree/645ee41bfebc463523b228ff087e41619607d8b2 |
SmoothSoftmax | import torch
from torch import Tensor
from torch import nn
class SmoothSoftmax(nn.Module):
def forward(self, x: 'Tensor'):
logistic_value = torch.sigmoid(x)
return logistic_value / logistic_value.sum(dim=-1, keepdim=True)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_in... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | zsl24/voice-activity-detection | SmoothSoftmax | false | 16,823 | [
"MIT"
] | 74 | a034be23c6283121c6b72e778c6ff6711045cbe3 | https://github.com/zsl24/voice-activity-detection/tree/a034be23c6283121c6b72e778c6ff6711045cbe3 |
make_binary | import torch
from torch import Tensor
class make_binary(torch.nn.Module):
def __init__(self, inplace=False):
super().__init__()
self.inplace = inplace
def forward(self, tensor: 'Tensor') ->Tensor:
return tensor % 2
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_i... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | fcaretti/mitosis_MNIST | make_binary | false | 3,487 | [
"MIT"
] | 0 | 3dce002ff41a09ddd65eb220dc6e5f5c0013a0ea | https://github.com/fcaretti/mitosis_MNIST/tree/3dce002ff41a09ddd65eb220dc6e5f5c0013a0ea |
Hardswish | # 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... | Alex-Beh/hand_tracking | Hardswish | false | 11,162 | [
"Apache-2.0"
] | 0 | 40ac39e10ed5815d9400d6a87149015ad6ab9686 | https://github.com/Alex-Beh/hand_tracking/tree/40ac39e10ed5815d9400d6a87149015ad6ab9686 |
TiledConv2d | import torch
import torch.nn as nn
import torch.nn.functional as F
class TiledConv2d(nn.Module):
def __init__(self, in_features, out_features):
super().__init__()
self.conv = nn.Conv2d(in_features, out_features, kernel_size=3,
bias=False)
def forward(self, x):
return 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... | mkarmann/conway-reversed | TiledConv2d | false | 10,678 | [
"MIT"
] | 0 | a3ae10dd5768affb9caf193a246395ee0fb2bc6f | https://github.com/mkarmann/conway-reversed/tree/a3ae10dd5768affb9caf193a246395ee0fb2bc6f |
SimpleSinModule | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = t... | briancoutinho/glow | SimpleSinModule | false | 12,589 | [
"Apache-2.0"
] | 0 | 4c919d60b3c33296c4109aec8020a1733c98f5b5 | https://github.com/briancoutinho/glow/tree/4c919d60b3c33296c4109aec8020a1733c98f5b5 |
BertSelfOutput | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | BIT-ENGD/eeqa | BertSelfOutput | false | 14,919 | [
"MIT"
] | 142 | 2995abbaff1fb47131246a247ee7ed62aa94f4c3 | https://github.com/BIT-ENGD/eeqa/tree/2995abbaff1fb47131246a247ee7ed62aa94f4c3 |
AddCoords | # 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... | SeunghwanByun/Real-Time-Road-Detection-Network | AddCoords | false | 1,048 | [
"MIT"
] | 0 | bc46615adef0e2b1a9a03dd4951559ca5849e6e1 | https://github.com/SeunghwanByun/Real-Time-Road-Detection-Network/tree/bc46615adef0e2b1a9a03dd4951559ca5849e6e1 |
ResidualBlock_noBN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
impor... | GuoShi28/GCP-Net | ResidualBlock_noBN | false | 8,191 | [
"Apache-2.0"
] | 24 | cef7513fa242343055af64e612429e4384d3c1d7 | https://github.com/GuoShi28/GCP-Net/tree/cef7513fa242343055af64e612429e4384d3c1d7 |
Net | import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
def __init__(self, c1=32, c2=64, c3=128, c4=256, l1=512, d1=0.0):
super().__init__()
self.conv1 = nn.Conv2d(9, c1, (5, 5))
self.conv2 = nn.Conv2d(c1, c2, (5, 5))
self.conv3 = nn.Conv2d(c2, c3,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | vtomi97/LHYP | Net | false | 11,088 | [
"MIT"
] | 0 | 3db91f889c0f6b866b9537975f664f072e021ea9 | https://github.com/vtomi97/LHYP/tree/3db91f889c0f6b866b9537975f664f072e021ea9 |
SwishV2 | # 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... | chizhu/pytorch-loss | SwishV2 | false | 6,437 | [
"MIT"
] | 1 | c8fbd78771f11a910b0b51ae3697c09761dd9696 | https://github.com/chizhu/pytorch-loss/tree/c8fbd78771f11a910b0b51ae3697c09761dd9696 |
Rot180 | import torch
import torch.nn as nn
def rot180(input: 'torch.Tensor') ->torch.Tensor:
return torch.flip(input, [-2, -1])
class Rot180(nn.Module):
"""Rotate a tensor image or a batch of tensor images
180 degrees. Input must be a tensor of shape (C, H, W)
or a batch of tensors :math:`(*, C, H, W)`.
... | 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... | NickleDave/kornia | Rot180 | false | 2,674 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 5392651d0bc268da577fa0a49aa50f957289c7dd | https://github.com/NickleDave/kornia/tree/5392651d0bc268da577fa0a49aa50f957289c7dd |
MLPFunc | import torch
from torch import nn
from torch.nn import functional as F
from torch.autograd import Variable
def seq_dropout(x, p=0, training=False):
"""
x: batch * len * input_size
"""
if training is False or p == 0:
return x
dropout_mask = Variable(1.0 / (1 - p) * torch.bernoulli((1 - p) *... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | lixinsu/RCZoo | MLPFunc | false | 15,926 | [
"MIT"
] | 166 | 37fcb7962fbd4c751c561d4a0c84173881ea8339 | https://github.com/lixinsu/RCZoo/tree/37fcb7962fbd4c751c561d4a0c84173881ea8339 |
LinearFeedforward | import torch
from torch import nn
import torch.utils.data
class Linear(nn.Linear):
def forward(self, x):
size = x.size()
return super().forward(x.contiguous().view(-1, size[-1])).view(*
size[:-1], -1)
class Feedforward(nn.Module):
def __init__(self, d_in, d_out, activation=None... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | FGDBTKD/decaNLP | LinearFeedforward | false | 13,678 | [
"BSD-3-Clause"
] | 2,361 | ff2d7e18cc226197bb8fe5fe796c4b8bc0395e86 | https://github.com/FGDBTKD/decaNLP/tree/ff2d7e18cc226197bb8fe5fe796c4b8bc0395e86 |
Module_CharbonnierLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | Pumpkin123709/LBEC | Module_CharbonnierLoss | false | 944 | [
"MIT"
] | 0 | 18661faa35769f731847e0226ff601754e134668 | https://github.com/Pumpkin123709/LBEC/tree/18661faa35769f731847e0226ff601754e134668 |
NormalDivLoss | # 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, math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.gu... | JWHan717/CS492I-Project | NormalDivLoss | false | 8,315 | [
"MIT"
] | 23 | 5da80bc41425ee90711a3de89c5501b5f7acd4b7 | https://github.com/JWHan717/CS492I-Project/tree/5da80bc41425ee90711a3de89c5501b5f7acd4b7 |
HighwayLayer | import torch
from torch import nn
import torch.utils.data
import torch.utils.data.distributed
import torch.utils.checkpoint
def my_xavier_init(m, gain=1):
"""Xavier initialization: weights initialization that tries to make variance of outputs
of a layer equal to variance of its inputs.
"""
for p in m.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | CowherdChris/droidlet | HighwayLayer | false | 8,017 | [
"MIT"
] | 26 | 8d965c1ebc38eceb6f8083c52b1146c1bc17d5e1 | https://github.com/CowherdChris/droidlet/tree/8d965c1ebc38eceb6f8083c52b1146c1bc17d5e1 |
TV_L1Loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch.... | JaguAroo/SRResCGAN | TV_L1Loss | false | 610 | [
"MIT"
] | 0 | 9aac612aff631f7fb9142e0a36de9559cfc1a62d | https://github.com/JaguAroo/SRResCGAN/tree/9aac612aff631f7fb9142e0a36de9559cfc1a62d |
ConcatClassifierHead | from _paritybench_helpers import _mock_config
from torch.nn import Module
import torch
import torch.nn as nn
import torch.nn
class ConcatClassifierHead(Module):
def __init__(self, config: 'dict'):
super(ConcatClassifierHead, self).__init__()
self.linear_layer_1 = nn.Linear(config['max_objects_per... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | SpyrosMouselinos/DeltaFormers | ConcatClassifierHead | false | 5,857 | [
"Apache-2.0"
] | 1 | 38508fa9b85f2c50aa0031b67e7e8feff1a75b27 | https://github.com/SpyrosMouselinos/DeltaFormers/tree/38508fa9b85f2c50aa0031b67e7e8feff1a75b27 |
EncoderLayer | # 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 | EncoderLayer | false | 12,776 | [
"BSD-3-Clause"
] | 0 | 723d9c2cfd3f16b2eb7584cc7cb0aaef973854dd | https://github.com/matatabinoneko/densecap/tree/723d9c2cfd3f16b2eb7584cc7cb0aaef973854dd |
ActorMARL | # 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.... | BIT-UAV-JJJ/ElegantRL | ActorMARL | false | 4,889 | [
"Apache-2.0"
] | 1 | 5ce5c1030949bb862d0d56b0e78a9a1f47efe63a | https://github.com/BIT-UAV-JJJ/ElegantRL/tree/5ce5c1030949bb862d0d56b0e78a9a1f47efe63a |
QNetwork | import torch
import torch.nn.functional as F
import torch.nn as nn
class QNetwork(nn.Module):
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed, fc1_units=64,
fc2_units=64):
"""Initialize parameters and build model.
Params
======
state_si... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | AlexS28/SABER | QNetwork | false | 16,874 | [
"BSD-3-Clause"
] | 4 | 91f74319a41f473b8e8f9eff6b7d9b604b94c7da | https://github.com/AlexS28/SABER/tree/91f74319a41f473b8e8f9eff6b7d9b604b94c7da |
Encoder | import torch
from torch import nn
import torch.hub
import torch.nn.functional as F
class Encoder(nn.Module):
"""Estimation of the nonnegative mixture weight by a 1-D conv layer.
"""
def __init__(self, L, N, audio_channels):
super(Encoder, self).__init__()
self.L, self.N = L, N
sel... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import t... | FindingBen/demucs-copy | Encoder | false | 9,066 | [
"MIT"
] | 0 | b607e9c91b776eb03bf95a2aa9c4900c92fc7c3f | https://github.com/FindingBen/demucs-copy/tree/b607e9c91b776eb03bf95a2aa9c4900c92fc7c3f |
MLPDecoder | import torch
import torch.nn as nn
import torch.nn.functional as F
class MLPDecoder(nn.Module):
def __init__(self, input_channels, output_channels, set_size, dim,
particle_types):
super().__init__()
self.output_channels = output_channels
self.set_size = set_size
self.parti... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | bostdiek/DarkMachinesAutoEncoder | MLPDecoder | false | 3,245 | [
"MIT"
] | 0 | f05f482b1bbd79cd777221bfe0d37e75b72c3e2b | https://github.com/bostdiek/DarkMachinesAutoEncoder/tree/f05f482b1bbd79cd777221bfe0d37e75b72c3e2b |
NLgate | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | HughMun/MultiBench | NLgate | false | 13,812 | [
"MIT"
] | 148 | d5712a0815a9486b0e0c76b54cd63c880188fc8e | https://github.com/HughMun/MultiBench/tree/d5712a0815a9486b0e0c76b54cd63c880188fc8e |
NonSaturatingLoss | # 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... | DensoITLab/TeachAugment | NonSaturatingLoss | false | 7,983 | [
"BSD-2-Clause"
] | 20 | 66ec099a0afab99e18531c5437182cfe17dc30c8 | https://github.com/DensoITLab/TeachAugment/tree/66ec099a0afab99e18531c5437182cfe17dc30c8 |
PFLDLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import ... | Markus92/nni | PFLDLoss | false | 5,582 | [
"MIT"
] | 1 | 2641c7343f4b411b002bea4f5648941268194ed7 | https://github.com/Markus92/nni/tree/2641c7343f4b411b002bea4f5648941268194ed7 |
SmallMaskNet | # 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... | saikatdutta/NME-VFI | SmallMaskNet | false | 7,591 | [
"Apache-2.0"
] | 1 | 5915e2336ea3ed7113a9c6a91bbc7f6b5deaac17 | https://github.com/saikatdutta/NME-VFI/tree/5915e2336ea3ed7113a9c6a91bbc7f6b5deaac17 |
DiscShiftLoss | import torch
import torch.nn as nn
class DiscShiftLoss(nn.Module):
"""Disc shift loss.
Args:
loss_weight (float, optional): Loss weight. Defaults to 1.0.
"""
def __init__(self, loss_weight=0.1):
super().__init__()
self.loss_weight = loss_weight
def forward(self, ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | Sardhendu/mmediting | DiscShiftLoss | false | 9,878 | [
"Apache-2.0"
] | 0 | 623b59ac758d856abc9fab7e845beeab61074d8f | https://github.com/Sardhendu/mmediting/tree/623b59ac758d856abc9fab7e845beeab61074d8f |
BertLayerNormNoVar | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | vtu81/auto_LiRPA | BertLayerNormNoVar | false | 16,689 | [
"BSD-3-Clause"
] | 161 | 294152077c0abfafb5d62fee39335e60eff087b4 | https://github.com/vtu81/auto_LiRPA/tree/294152077c0abfafb5d62fee39335e60eff087b4 |
EncoderLayer | import math
import torch
from torch import nn
from torch.nn import functional as F
class LayerNorm(nn.Module):
def __init__(self, d_model, eps=1e-06):
super(LayerNorm, self).__init__()
self.gamma = nn.Parameter(torch.ones(d_model))
self.beta = nn.Parameter(torch.zeros(d_model))
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.... | Adelashl6/mask_transformers | EncoderLayer | false | 4,842 | [
"MIT"
] | 1 | 2a2e4d1b40ae3ed546cb850d041af246806b63e7 | https://github.com/Adelashl6/mask_transformers/tree/2a2e4d1b40ae3ed546cb850d041af246806b63e7 |
MsgNorm | import torch
import torch.nn.functional as F
class MsgNorm(torch.nn.Module):
def __init__(self, learn_msg_scale=False):
super(MsgNorm, self).__init__()
self.msg_scale = torch.nn.Parameter(torch.Tensor([1.0]),
requires_grad=learn_msg_scale)
def forward(self, x, msg, p=2):
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._... | Basvanstein/nasbench301 | MsgNorm | false | 13,390 | [
"Apache-2.0"
] | 55 | 2984dec45c760d47762f50efe39b71e9d1ac22e0 | https://github.com/Basvanstein/nasbench301/tree/2984dec45c760d47762f50efe39b71e9d1ac22e0 |
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Jianxun-Wang/Physics-constrained-Bayesian-deep-learning | Net | false | 8,378 | [
"MIT"
] | 24 | cde0287f848f83c6def1fe409c67d7d4e14174da | https://github.com/Jianxun-Wang/Physics-constrained-Bayesian-deep-learning/tree/cde0287f848f83c6def1fe409c67d7d4e14174da |
CanineSelfAttention | from _paritybench_helpers import _mock_config
import math
import torch
from torch import nn
import torch.utils.checkpoint
class CanineSelfAttention(nn.Module):
def __init__(self, config):
super().__init__()
if (config.hidden_size % config.num_attention_heads != 0 and not
hasattr(confi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ncoop57/transformers | CanineSelfAttention | false | 4,061 | [
"Apache-2.0"
] | 0 | d7e156bd1ae2467e9ea1dbc44f31da0ed2296aee | https://github.com/ncoop57/transformers/tree/d7e156bd1ae2467e9ea1dbc44f31da0ed2296aee |
MultiHeadAttention | 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.... | csyhhu/attention-is-all-you-need-pytorch | MultiHeadAttention | false | 6,510 | [
"MIT"
] | 1 | 5792c9714295b1a33d1ca074206ec223f436b954 | https://github.com/csyhhu/attention-is-all-you-need-pytorch/tree/5792c9714295b1a33d1ca074206ec223f436b954 |
SoftBinaryCrossEntropyLoss | import torch
class SoftBinaryCrossEntropyLoss(torch.nn.Module):
def __init__(self, tau=1.0):
super().__init__()
self.tau = tau
self.bce_logit = torch.nn.BCEWithLogitsLoss()
def forward(self, pred, true):
logits = pred / self.tau
l = self.bce_logit(logits, true)
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
assert_size... | mfredriksz/semanticGAN_code | SoftBinaryCrossEntropyLoss | false | 16,026 | [
"BSD-2-Clause",
"MIT"
] | 107 | c6e7b490086afd8a7593e2892452295555910494 | https://github.com/mfredriksz/semanticGAN_code/tree/c6e7b490086afd8a7593e2892452295555910494 |
AugCNN | # 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.functional as F
assert_size_stride = torch... | minqi/auto-drac | AugCNN | false | 16,093 | [
"MIT"
] | 84 | 59a25bbabd51946d7a645db9c5d59071b73b006d | https://github.com/minqi/auto-drac/tree/59a25bbabd51946d7a645db9c5d59071b73b006d |
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.utils.data
assert_size_stride = torch._C._dy... | yjh0410/actionformer_release | LayerNorm | false | 16,764 | [
"MIT"
] | 61 | 7a97422111d3e29c8d2e14088c850c6975855ea7 | https://github.com/yjh0410/actionformer_release/tree/7a97422111d3e29c8d2e14088c850c6975855ea7 |
L1GradLoss | # 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
... | alsgkals2/SRResCGAN | L1GradLoss | false | 14,814 | [
"MIT"
] | 81 | a71201a93e1819045f9c7711743812546d3a1f31 | https://github.com/alsgkals2/SRResCGAN/tree/a71201a93e1819045f9c7711743812546d3a1f31 |
FBANKNormalizer | from _paritybench_helpers import _mock_config
import torch
import torch.utils.data
class FBANKNormalizer(torch.nn.Module):
def __init__(self, config):
super(FBANKNormalizer, self).__init__()
self.num_mel_bins = config.num_mel_bins
self.weight = torch.nn.Parameter(torch.tensor([1 / 10] * s... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_... | lorenlugosch/autoregressive-models | FBANKNormalizer | false | 7,115 | [
"Apache-2.0"
] | 1 | 2c50bc331d3b68cc7144f7456591bbc2321cc658 | https://github.com/lorenlugosch/autoregressive-models/tree/2c50bc331d3b68cc7144f7456591bbc2321cc658 |
BDiceLoss | # 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... | CarlosPena00/pytorch-unet | BDiceLoss | false | 197 | [
"MIT"
] | 0 | 8365bace23e4b04b9c5b75cd6720807ea8cac5ab | https://github.com/CarlosPena00/pytorch-unet/tree/8365bace23e4b04b9c5b75cd6720807ea8cac5ab |
DDPGConvBody | import torch
import torch.nn as nn
import torch.nn.functional as F
def layer_init(layer, w_scale=1.0):
nn.init.orthogonal_(layer.weight.data)
layer.weight.data.mul_(w_scale)
nn.init.constant_(layer.bias.data, 0)
return layer
class DDPGConvBody(nn.Module):
def __init__(self, in_channels=4):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | GoingMyWay/DeepRL | DDPGConvBody | false | 13,805 | [
"MIT"
] | 2,857 | 78df98a8eeccc41dacd952932435a5ecc42e1c67 | https://github.com/GoingMyWay/DeepRL/tree/78df98a8eeccc41dacd952932435a5ecc42e1c67 |
HardSigmoid | import torch
from torch import nn
import torch.nn.functional as F
class HardSigmoid(nn.Module):
def __init__(self, slope=0.2, offset=0.5):
super().__init__()
self.slope = slope
self.offset = offset
def forward(self, x):
x = self.slope * x + self.offset
x = F.threshold... | 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... | gentlebreeze1/dbnet | HardSigmoid | false | 3,530 | [
"Apache-2.0"
] | 0 | be28a7ae835af7d6f8b7c2b636b875adc9fc187c | https://github.com/gentlebreeze1/dbnet/tree/be28a7ae835af7d6f8b7c2b636b875adc9fc187c |
IntervalObservationEncoder | # 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... | IusztinPaul/yacht | IntervalObservationEncoder | false | 17,451 | [
"Apache-2.0"
] | 5 | c68ab7c66bde860bb91534c29e97772ba328adb5 | https://github.com/IusztinPaul/yacht/tree/c68ab7c66bde860bb91534c29e97772ba328adb5 |
RewardModelNetwork | import torch
import torch.nn as nn
import torch.utils.data
class RewardModelNetwork(nn.Module):
def __init__(self, input_size: 'int', hidden_size: 'int', output_size:
'int') ->None:
super(RewardModelNetwork, self).__init__()
self.l1 = nn.Linear(input_size, hidden_size)
self.l2 = 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 torch.nn as ... | L-Net-1992/DI-engine | RewardModelNetwork | false | 5,495 | [
"Apache-2.0"
] | 1 | 06803b4e18fa64bbed0fd1d44952242c0c063b0f | https://github.com/L-Net-1992/DI-engine/tree/06803b4e18fa64bbed0fd1d44952242c0c063b0f |
SmallBlock | import torch
from torch import nn
from torchvision import models as models
import torch.onnx
import torch.nn
class SmallBlock(nn.Module):
def __init__(self, channels):
super(SmallBlock, self).__init__()
self.conv1 = nn.Conv2d(in_channels=channels, out_channels=channels,
kernel_size=3,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | dqawami/openvino_training_extensions | SmallBlock | false | 15,220 | [
"Apache-2.0"
] | 256 | dddda1dfd651eaae2d59cecda84275b1b03bd0ad | https://github.com/dqawami/openvino_training_extensions/tree/dddda1dfd651eaae2d59cecda84275b1b03bd0ad |
CPUForgetMult | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from typing import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | WittmannF/fastai_docs | CPUForgetMult | false | 5,976 | [
"Apache-2.0"
] | 1 | 03ecae01557a5e4a196dd858b10a57b224df52cd | https://github.com/WittmannF/fastai_docs/tree/03ecae01557a5e4a196dd858b10a57b224df52cd |
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