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 |
|---|---|---|---|---|---|---|---|---|---|---|
ActNormFlow | import torch
from typing import Dict
from typing import Tuple
import torch.nn as nn
from torch.nn import Parameter
class Flow(nn.Module):
"""
Normalizing Flow base class
"""
_registry = dict()
def __init__(self, inverse):
super(Flow, self).__init__()
self.inverse = inverse
de... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from typing import Dict
from typing import Tuple
import torch.nn as nn
fr... | juheeuu/flowseq | ActNormFlow | false | 12,650 | [
"Apache-2.0"
] | 0 | e6e50406656335ff7a2f9ed4bd81d7cc7d1195fb | https://github.com/juheeuu/flowseq/tree/e6e50406656335ff7a2f9ed4bd81d7cc7d1195fb |
AsymmetricalFocalLoss | # 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
... | venisehannoyer/Hear-me-GirlsInAI-team1 | AsymmetricalFocalLoss | false | 10,949 | [
"Apache-2.0"
] | 0 | 664b3af4befe9b73c28d4362969699bc2254bdf9 | https://github.com/venisehannoyer/Hear-me-GirlsInAI-team1/tree/664b3af4befe9b73c28d4362969699bc2254bdf9 |
HGCN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
im... | cugbbaiyun/HGCN-MIX | HGCN | false | 6,507 | [
"Apache-2.0"
] | 1 | 82b5c22a3cb2dabc2b86c54f23fa314477d92b63 | https://github.com/cugbbaiyun/HGCN-MIX/tree/82b5c22a3cb2dabc2b86c54f23fa314477d92b63 |
Discriminate_Loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.nn.functional
import torch.nn
assert_size_stride = tor... | ChmarsLuo/Hero_anomaly_prediction | Discriminate_Loss | false | 4,992 | [
"Apache-2.0"
] | 1 | dba2322dabb3476466e296db6c316fc08e0cb11d | https://github.com/ChmarsLuo/Hero_anomaly_prediction/tree/dba2322dabb3476466e296db6c316fc08e0cb11d |
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 numbers
import torch.nn as nn
import torch.utils.data
import torch.nn.in... | AbhilashMathews/adahessian | LayerNorm | false | 4,835 | [
"MIT"
] | 1 | bacccecc7a078c3e9e72aa55b17d8e46d21dc9c9 | https://github.com/AbhilashMathews/adahessian/tree/bacccecc7a078c3e9e72aa55b17d8e46d21dc9c9 |
NN | import torch
import torch.nn as nn
class NN(nn.Module):
def __init__(self, input_size, h1, h2, h3, num_output):
super(NN, self).__init__()
self.fc1 = nn.Linear(input_size, h1)
self.fc2 = nn.Linear(h1, h2)
self.fc3 = nn.Linear(h2, h3)
self.fc4 = nn.Linear(h3, num_output)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | kgarg8/hypertune | NN | false | 12,677 | [
"MIT"
] | 0 | fbc4b87c9aefcd8449f6068232d7105975ff9dc9 | https://github.com/kgarg8/hypertune/tree/fbc4b87c9aefcd8449f6068232d7105975ff9dc9 |
BCEWithLogitsLossWeighted | import torch
import torch.nn as nn
class WeightedLoss(nn.Module):
def __init__(self):
super(WeightedLoss, self).__init__()
self.weighted = False
def generate_weight_mask(self, mask, to_ignore=None):
""" Generates a weight mask where pixel weights are inversely proportional 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 import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | Guangyun-Xu/uois | BCEWithLogitsLossWeighted | false | 13,726 | [
"MIT"
] | 106 | 00069af841dd3ea9a86e6e3a89c3b7222240e6e5 | https://github.com/Guangyun-Xu/uois/tree/00069af841dd3ea9a86e6e3a89c3b7222240e6e5 |
decoder5 | # 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.... | Holmes-Alan/RefVAE | decoder5 | false | 8,334 | [
"MIT"
] | 13 | 836b8f1168f1b0f923b609a48e202ace7806f79c | https://github.com/Holmes-Alan/RefVAE/tree/836b8f1168f1b0f923b609a48e202ace7806f79c |
MaskLoss | import torch
import torch.nn as nn
import torch.hub
class MaskLoss(nn.Module):
def __init__(self, size_average=None, reduce=None, reduction='mean'):
super(MaskLoss, self).__init__()
self.reduction = reduction
def forward(self, input, target):
N, _W = input.size()
torch.min(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._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | lisadunlap/explainable-nbdt | MaskLoss | false | 7,110 | [
"MIT"
] | 1 | e045bfd0b55b21fd87c9a233b73a0ca77672efff | https://github.com/lisadunlap/explainable-nbdt/tree/e045bfd0b55b21fd87c9a233b73a0ca77672efff |
SoftDiceLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.backends.cudnn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
em... | ArmenGhambaryan/kaggle_carvana_segmentation | SoftDiceLoss | false | 13,299 | [
"MIT"
] | 447 | 648a6b5c807cb69011316fe6501241dacc027db2 | https://github.com/ArmenGhambaryan/kaggle_carvana_segmentation/tree/648a6b5c807cb69011316fe6501241dacc027db2 |
Upsample | # 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... | AIplayblocks/littlecarroute | Upsample | false | 4,765 | [
"MIT"
] | 1 | e20b4a318746637dd1e2170b175201bd8ba1e7d5 | https://github.com/AIplayblocks/littlecarroute/tree/e20b4a318746637dd1e2170b175201bd8ba1e7d5 |
Fadein | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.utils.data
class Fadein(nn.Module):
def __init__(self, cfg):
super(Fadein, self).__init__()
self.alpha = 0.0
def update_alpha(self, delta):
self.alpha = self.alpha + delta
self.alpha... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | hyunobae/SRGAN | Fadein | false | 3,634 | [
"MIT"
] | 0 | 9a967312c08e608833d2037398948617e1200c35 | https://github.com/hyunobae/SRGAN/tree/9a967312c08e608833d2037398948617e1200c35 |
PatchSequential | import math
import torch
import warnings
from typing import Dict
from typing import Optional
from typing import Tuple
import torch.nn as nn
import torch.nn.functional as F
from typing import cast
from typing import List
from typing import Union
from torch.distributions import Bernoulli
from itertools import zip_longest... | 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 warnings
from typing import Dict
from typing import Optional
from typing import Tuple
import torch.nn as nn
import torch.... | rozumden/kornia | PatchSequential | false | 4,247 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | f62f324b201eea50e1e50db3fbf3e968e0a337c5 | https://github.com/rozumden/kornia/tree/f62f324b201eea50e1e50db3fbf3e968e0a337c5 |
AttentiveNorm2d | # 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 ... | ppomelo/Attentive-Transformation-Based-Normalization | AttentiveNorm2d | false | 4,131 | [
"Apache-2.0"
] | 0 | 62ad02eb025613e90f4fe0e0a9f0f85839e53092 | https://github.com/ppomelo/Attentive-Transformation-Based-Normalization/tree/62ad02eb025613e90f4fe0e0a9f0f85839e53092 |
PrimaryCapsules | import torch
import torch.nn as nn
def squash(s, dim=-1):
"""
"Squashing" non-linearity that shrunks short vectors to almost zero length and long vectors to a length slightly below 1
Eq. (1): v_j = ||s_j||^2 / (1 + ||s_j||^2) * s_j / ||s_j||
Args:
s: Vector before activation
dim: Dimension along which t... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | jjcao/capsule-network | PrimaryCapsules | false | 15,708 | [
"MIT"
] | 171 | 0c2d9976b25d64720a90d3db71e5869d2592ab71 | https://github.com/jjcao/capsule-network/tree/0c2d9976b25d64720a90d3db71e5869d2592ab71 |
DeepHeadModule | import torch
import torch.nn as nn
import torch.nn.functional as F
from math import sqrt as sqrt
class DeepHeadModule(nn.Module):
def __init__(self, input_channels, output_channels):
super(DeepHeadModule, self).__init__()
self._input_channels = input_channels
self._output_channels = outpu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from ma... | NTech-Lab/deepfake-detection-challenge | DeepHeadModule | false | 14,075 | [
"Apache-2.0"
] | 98 | 52095ce4a49f298faf075a5eb28391722b9e4103 | https://github.com/NTech-Lab/deepfake-detection-challenge/tree/52095ce4a49f298faf075a5eb28391722b9e4103 |
InvertibleChannelMixing2D | # 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.autograd import Function
from torch import nn
from warnings import wa... | cetmann/iunets | InvertibleChannelMixing2D | false | 15,017 | [
"MIT"
] | 86 | 80ed7cce0e505a0396c42359eaf27819222d71f6 | https://github.com/cetmann/iunets/tree/80ed7cce0e505a0396c42359eaf27819222d71f6 |
Net | import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
self.conv1 = nn.Conv2d(3, 16, 3, padding=1)
self.conv2 = nn.Conv2d(16, 16, 3, padding=1)
self.conv3 = nn.Conv2d(16, 20, 3, padding=1)
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.... | Hunkzer/DLplayground | Net | false | 11,499 | [
"Apache-2.0"
] | 0 | c85238e00052a80e6a59e5d1c705014c45eeb6aa | https://github.com/Hunkzer/DLplayground/tree/c85238e00052a80e6a59e5d1c705014c45eeb6aa |
BertSelfOutput | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.utils.checkpoint
class BertSelfOutput(nn.Module):
def __init__(self, config, twin=False, merge=False):
super().__init__()
self.LayerNorm = nn.LayerNorm(config.hidden_size, eps=config.
layer_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 ... | MikeWangWZHL/BLIP | BertSelfOutput | false | 1,888 | [
"BSD-3-Clause"
] | 0 | b82134f1892a54c8f63b0f4b51bdcb8684e1dc6d | https://github.com/MikeWangWZHL/BLIP/tree/b82134f1892a54c8f63b0f4b51bdcb8684e1dc6d |
CELossWeighted | # 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
... | Guangyun-Xu/uois | CELossWeighted | false | 13,729 | [
"MIT"
] | 106 | 00069af841dd3ea9a86e6e3a89c3b7222240e6e5 | https://github.com/Guangyun-Xu/uois/tree/00069af841dd3ea9a86e6e3a89c3b7222240e6e5 |
GlobalAveragePooling | # 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... | HexaFarms/MMClassification | GlobalAveragePooling | false | 11,481 | [
"Apache-2.0"
] | 0 | d61d0448b6bcd2fd4c0a408688f603a53ab16ca2 | https://github.com/HexaFarms/MMClassification/tree/d61d0448b6bcd2fd4c0a408688f603a53ab16ca2 |
SelfAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
class SelfAttention(nn.Module):
def __init__(self, hidden_size, attention_size=100, n_attention_heads=1):
super().__init__()
self.hidden_size = hidden_size
self.attention_size = attention_size
self.n_attention_head... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | AnoushkaVyas/TextOutlierDetection | SelfAttention | false | 52 | [
"MIT"
] | 0 | 290a6800262090998d32c8bbd311e3d53737e2cd | https://github.com/AnoushkaVyas/TextOutlierDetection/tree/290a6800262090998d32c8bbd311e3d53737e2cd |
Conv3x3 | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | Fatmangh/VIDEO-ACTION-CLASSIFICATION-USING-PRETAINED-SELF-SUPERVISED-DEPTH-AWARE-DENSE-PREDICTIVE-CODING- | Conv3x3 | false | 2,245 | [
"MIT"
] | 0 | 13fac05601efed16ae8b29989aad487e04cd90a7 | https://github.com/Fatmangh/VIDEO-ACTION-CLASSIFICATION-USING-PRETAINED-SELF-SUPERVISED-DEPTH-AWARE-DENSE-PREDICTIVE-CODING-/tree/13fac05601efed16ae8b29989aad487e04cd90a7 |
Hardswish | import torch
import torch.nn as nn
import torch.nn.functional as F
class Hardswish(nn.Module):
@staticmethod
def forward(x):
return x * F.hardtanh(x + 3, 0.0, 6.0) / 6.0
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 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 |
TransformerNet | # 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.... | Chandan-h-509/ignite | TransformerNet | false | 9,057 | [
"BSD-3-Clause"
] | 0 | f8c39828cb1dac49b6ef358cdf77865bf2430106 | https://github.com/Chandan-h-509/ignite/tree/f8c39828cb1dac49b6ef358cdf77865bf2430106 |
Critic | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import numpy as np
import tor... | YufengJin/deep-reinforcement-learning | Critic | false | 2,996 | [
"MIT"
] | 0 | 141cf00f169b46aa492c9e7520429bfdaab0117d | https://github.com/YufengJin/deep-reinforcement-learning/tree/141cf00f169b46aa492c9e7520429bfdaab0117d |
SeparableConv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
@triton.jit
de... | Pumpkin123709/LBEC | SeparableConv2d | false | 950 | [
"MIT"
] | 0 | 18661faa35769f731847e0226ff601754e134668 | https://github.com/Pumpkin123709/LBEC/tree/18661faa35769f731847e0226ff601754e134668 |
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.... | Daetheys/Lazimpa | InformedSender | false | 7,956 | [
"MIT"
] | 15 | 21f4f4ebcdfa8b6a775b64673dd3001763c91cf1 | https://github.com/Daetheys/Lazimpa/tree/21f4f4ebcdfa8b6a775b64673dd3001763c91cf1 |
MCFullyConnected | import collections
import torch
import torch.utils.data
from torch import nn
def get_redistribution(kind: 'str', num_states: 'int', num_features: 'int'=
None, num_out: 'int'=None, normaliser: 'nn.Module'=None, **kwargs):
if kind == 'linear':
return LinearRedistribution(num_states, num_features, num_ou... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | hoedt/stable-nalu | MCFullyConnected | false | 3,619 | [
"MIT"
] | 0 | 64b3d240db8bff4da857d955f213ef3c7e38e035 | https://github.com/hoedt/stable-nalu/tree/64b3d240db8bff4da857d955f213ef3c7e38e035 |
MultiHeadAttention | import torch
import torch.nn as nn
class MultiHeadAttention(nn.Module):
def __init__(self, num_q_channels: 'int', num_kv_channels: 'int',
num_heads: 'int', dropout: 'float'):
super().__init__()
self.attention = nn.MultiheadAttention(embed_dim=num_q_channels,
num_heads=num_head... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | felixyu7/perceiver-io-1 | MultiHeadAttention | false | 3,536 | [
"Apache-2.0"
] | 0 | 895f09e75e5a4b5e90dfef5d3a86ea26c2f48f4e | https://github.com/felixyu7/perceiver-io-1/tree/895f09e75e5a4b5e90dfef5d3a86ea26c2f48f4e |
Gaussian | import torch
from torch import nn
from torch.nn import functional as F
import torch.utils.data
class Gaussian(nn.Module):
def __init__(self, in_dim, z_dim):
super(Gaussian, self).__init__()
self.mu = nn.Linear(in_dim, z_dim)
self.var = nn.Linear(in_dim, z_dim)
def reparameterize(self... | import torch
from torch import device
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libd... | Fischer19/GMVAE | Gaussian | false | 9,025 | [
"MIT"
] | 0 | b960e24df8a10e9e07b2111ccb8939dd2556a6c2 | https://github.com/Fischer19/GMVAE/tree/b960e24df8a10e9e07b2111ccb8939dd2556a6c2 |
ConvStem2 | import torch
import torch.nn as nn
class ConvStem2(nn.Module):
def __init__(self, in_chans=3, out_chans=64, kernel_size=7, stride=2):
super(ConvStem2, self).__init__()
self.conv = nn.Conv2d(in_chans, out_chans, kernel_size=kernel_size,
stride=stride, padding=kernel_size // 2, bias=Fal... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | yoookoo/cnn-transformer | ConvStem2 | false | 13,199 | [
"Apache-2.0"
] | 0 | 8ee54ea944ed752162e3098db7f8f689ec150efe | https://github.com/yoookoo/cnn-transformer/tree/8ee54ea944ed752162e3098db7f8f689ec150efe |
ContrastiveLoss | import torch
import torch.nn as nn
import torch.nn.modules
import torch.nn
import torch.nn.init
import torch.optim.lr_scheduler
class ContrastiveLoss(nn.Module):
"""
Contrastive loss function.
References:
https://github.com/delijati/pytorch-siamese/blob/master/contrastive.py
LaTeX:
L... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.nn.modules
import torch.nn
import torch.nn.init
import... | JoshuaBeard/netharn | ContrastiveLoss | false | 676 | [
"Apache-2.0"
] | 0 | 90773542c47363e663ee58f20fd151eb89bc313b | https://github.com/JoshuaBeard/netharn/tree/90773542c47363e663ee58f20fd151eb89bc313b |
AttentivePoolingModule | import torch
import torch.nn as nn
class AttentivePoolingModule(nn.Module):
"""
Implementation of Attentive Pooling
"""
def __init__(self, input_dim, activation='ReLU', **kwargs):
super(AttentivePoolingModule, self).__init__()
self.W_a = nn.Linear(input_dim, input_dim)
self.W... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | B06901052/s3prl | AttentivePoolingModule | false | 117 | [
"MIT"
] | 0 | 5f63d2df043d2d7c81580cd042fa2cea34746f48 | https://github.com/B06901052/s3prl/tree/5f63d2df043d2d7c81580cd042fa2cea34746f48 |
L1_Charbonnier_loss | import torch
import torch.nn as nn
class L1_Charbonnier_loss(nn.Module):
"""L1 Charbonnierloss."""
def __init__(self):
super(L1_Charbonnier_loss, self).__init__()
self.eps = 1e-06
def forward(self, X, Y):
diff = torch.add(X, -Y)
error = torch.sqrt(diff * diff + self.eps)
... | 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... | Tiger1994/LapSRN | L1_Charbonnier_loss | false | 5,887 | [
"MIT"
] | 1 | 4f2222ebad97ad6730fe352f5a3c8a06f0f61e7a | https://github.com/Tiger1994/LapSRN/tree/4f2222ebad97ad6730fe352f5a3c8a06f0f61e7a |
MultiHeadAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.a... | LindgeW/DomainAdaption4DependencyParsing | MultiHeadAttention | false | 5,532 | [
"Apache-2.0"
] | 1 | 5de136a37d8fe730e4235ed95bf923763fe21ea6 | https://github.com/LindgeW/DomainAdaption4DependencyParsing/tree/5de136a37d8fe730e4235ed95bf923763fe21ea6 |
SDRLoss | import torch
import torch.nn as nn
class SDRLoss(nn.Module):
def __init__(self):
super().__init__()
def forward(self, deg, clean):
loss_sdr = -1.0 * torch.mean(deg * clean) ** 2 / (torch.mean(deg **
2) + 2e-07)
return loss_sdr
def get_inputs():
return [torch.rand([4... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | PandoraLS/SpeechEnhancement | SDRLoss | false | 17,787 | [
"MIT"
] | 6 | f548eaafbe524a40c8cfd2221f7adf3a444b7a7d | https://github.com/PandoraLS/SpeechEnhancement/tree/f548eaafbe524a40c8cfd2221f7adf3a444b7a7d |
Linear_tanh | # 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 ... | Armand-Morin/AutoML | Linear_tanh | false | 64 | [
"MIT"
] | 0 | 189867e2c7734d9afb87a9f51fd42bd6cc527a64 | https://github.com/Armand-Morin/AutoML/tree/189867e2c7734d9afb87a9f51fd42bd6cc527a64 |
Padding2 | # 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._utils
assert_size_stride = torch._C._dynamo.guards.assert_size_str... | ijinjay/torch2mindspore | Padding2 | false | 3,654 | [
"MIT"
] | 0 | e4c06bd5e8a3b25b72bf158393a66c5cd1b572d2 | https://github.com/ijinjay/torch2mindspore/tree/e4c06bd5e8a3b25b72bf158393a66c5cd1b572d2 |
GeneralizedMeanPooling | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
from to... | Challyfilio/NAIC2021 | GeneralizedMeanPooling | false | 232 | [
"MIT"
] | 0 | 11b38a920dcc902f9b798dc43ae360062862e6e4 | https://github.com/Challyfilio/NAIC2021/tree/11b38a920dcc902f9b798dc43ae360062862e6e4 |
FeedForward | import torch
from torch import nn
from torch.nn import functional as F
class AffineTransform(nn.Module):
def __init__(self, num_features):
super().__init__()
self.alpha = nn.Parameter(torch.ones(1, 1, num_features))
self.beta = nn.Parameter(torch.zeros(1, 1, num_features))
def forwar... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | jaketae/res-mlp | FeedForward | false | 12,600 | [
"MIT"
] | 0 | 6c957e4fe67a2f13d9b4fd3fa36b7eddcf5323fd | https://github.com/jaketae/res-mlp/tree/6c957e4fe67a2f13d9b4fd3fa36b7eddcf5323fd |
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
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | EE559DeepLearningEPFL/Project1 | CNN | false | 406 | [
"MIT"
] | 0 | cbafdfee26771ae0ba3cd36375e68d92e9f108b2 | https://github.com/EE559DeepLearningEPFL/Project1/tree/cbafdfee26771ae0ba3cd36375e68d92e9f108b2 |
AdaptiveInstanceNorm | import torch
from torch import nn
from math import sqrt
def equal_lr(module, name='weight'):
"""Rescale weights after every updates.
"""
EqualLR.apply(module, name)
return module
class EqualLR:
def __init__(self, name):
self.name = name
def compute_weight(self, module):
wei... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | hologerry/style-based-gan-pytorch | AdaptiveInstanceNorm | false | 3,620 | [
"MIT"
] | 0 | 1a694fb3ea0288f1aaaa43aa67a570d908d9dc27 | https://github.com/hologerry/style-based-gan-pytorch/tree/1a694fb3ea0288f1aaaa43aa67a570d908d9dc27 |
MyLinear | # 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... | mahkons/orthogonal | MyLinear | false | 3,960 | [
"MIT"
] | 0 | 19a69134ca9a01ef564eab624b8c1526291770aa | https://github.com/mahkons/orthogonal/tree/19a69134ca9a01ef564eab624b8c1526291770aa |
Prenet | import torch
import torch.nn.functional as F
import torch.nn as nn
class Linear(nn.Module):
def __init__(self, in_dim, out_dim, bias=True, w_init='linear'):
super(Linear, self).__init__()
self.linear = nn.Linear(in_dim, out_dim, bias=bias)
nn.init.xavier_uniform_(self.linear.weight, gain=... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | poria-cat/Transformer-TTS-Pytorch | Prenet | false | 10,751 | [
"MIT"
] | 0 | 1e9e2dccc16c17372bf86ca73001f76645f53338 | https://github.com/poria-cat/Transformer-TTS-Pytorch/tree/1e9e2dccc16c17372bf86ca73001f76645f53338 |
FCNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | Markus92/nni | FCNet | false | 5,581 | [
"MIT"
] | 1 | 2641c7343f4b411b002bea4f5648941268194ed7 | https://github.com/Markus92/nni/tree/2641c7343f4b411b002bea4f5648941268194ed7 |
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.nn
import torch.onnx
import torch.utils.chec... | TingGong1/onnxruntime | LayerNorm | false | 5,900 | [
"MIT"
] | 1 | 435010ab6873974803591fa22262ed8b3e36e44d | https://github.com/TingGong1/onnxruntime/tree/435010ab6873974803591fa22262ed8b3e36e44d |
PatchEmbedding | # 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... | Curli-quan/fewshot-select | PatchEmbedding | false | 17,205 | [
"Apache-2.0"
] | 7 | 34f8ce5069ed1fbd01c1fa73a3ef264c98dadafe | https://github.com/Curli-quan/fewshot-select/tree/34f8ce5069ed1fbd01c1fa73a3ef264c98dadafe |
MLPNet | # 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_... | ngtrunghuan/50.021-ArtificialIntelligence | MLPNet | false | 4,085 | [
"MIT"
] | 0 | b0c3d9f8cc70312ea1298818482a4b25d4ddbded | https://github.com/ngtrunghuan/50.021-ArtificialIntelligence/tree/b0c3d9f8cc70312ea1298818482a4b25d4ddbded |
CLSHead | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.utils
import torch.nn.functional as F
class CLSHead(nn.Module):
def __init__(self, config, init_weights=None):
super(CLSHead, self).__init__()
self.layer_1 = nn.Linear(config.d_model, config.d_model)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | MSU-MLSys-Lab/CATE | CLSHead | false | 8,770 | [
"Apache-2.0"
] | 15 | 654c393d7df888d2c3f3b90f9e6752faa061157e | https://github.com/MSU-MLSys-Lab/CATE/tree/654c393d7df888d2c3f3b90f9e6752faa061157e |
ActorCriticMLP | # 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.... | kfirgedal/lightning-bolts | ActorCriticMLP | false | 12,665 | [
"Apache-2.0"
] | 0 | cbb8b6c21ca1de757d0f289fb840d59a3b6a10f5 | https://github.com/kfirgedal/lightning-bolts/tree/cbb8b6c21ca1de757d0f289fb840d59a3b6a10f5 |
Symmetric | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.quantization
import torch.onnx
import torch.nn.parallel
import torch.utils.data
import torch.fx
import to... | LeeSHa00/PyTorch-tutorials-kr | Symmetric | false | 11,903 | [
"BSD-3-Clause"
] | 0 | 6a25b48b1a6cc96ea4edebeede2e419ef73b96fc | https://github.com/LeeSHa00/PyTorch-tutorials-kr/tree/6a25b48b1a6cc96ea4edebeede2e419ef73b96fc |
ActorCritic | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
from torch.distributions import Categorical
class ActorCritic(nn.Module):
def __init__(self):
super().__init__()
self.affine1 = nn.Linear(4, 128)
self.action_head = nn.Linear(128, 2)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Gromy1211/torch-light | ActorCritic | false | 11,463 | [
"MIT"
] | 0 | c7d7a9bc5ab1eab03d800a27d9325859516f01e6 | https://github.com/Gromy1211/torch-light/tree/c7d7a9bc5ab1eab03d800a27d9325859516f01e6 |
LayerNorm2D | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_... | ishine/neural_sp | LayerNorm2D | false | 15,655 | [
"Apache-2.0"
] | 577 | 7995613541d994976b00d80dcc12e2835163acfb | https://github.com/ishine/neural_sp/tree/7995613541d994976b00d80dcc12e2835163acfb |
AvgPoolPad | import torch
import torch.nn.functional
import torch.nn as nn
class AvgPoolPad(nn.Module):
def __init__(self, stride=2, padding=1):
super(AvgPoolPad, self).__init__()
self.pad = nn.ZeroPad2d((1, 0, 1, 0))
self.pool = nn.AvgPool2d(3, stride=stride, padding=padding,
count_includ... | 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.functional
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch.... | CarlosPena00/pytorchvision | AvgPoolPad | false | 212 | [
"MIT"
] | 0 | 824b3a5a8940f3ee6b4da5de7a391a88e5aa36a2 | https://github.com/CarlosPena00/pytorchvision/tree/824b3a5a8940f3ee6b4da5de7a391a88e5aa36a2 |
LocalSubGraphLayer | # 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.... | cdicle-motional/l5kit | LocalSubGraphLayer | false | 6,414 | [
"Apache-2.0"
] | 1 | 4dc4ee5391479bb71f0b373f39c316f9eef5a961 | https://github.com/cdicle-motional/l5kit/tree/4dc4ee5391479bb71f0b373f39c316f9eef5a961 |
PixelwiseNorm | import torch
class PixelwiseNorm(torch.nn.Module):
"""
------------------------------------------------------------------------------------
Pixelwise feature vector normalization.
reference:
https://github.com/tkarras/progressive_growing_of_gans/blob/master/networks.py#L120
-------------------... | 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... | SashaMatsun/torch-GAN | PixelwiseNorm | false | 1,016 | [
"MIT"
] | 0 | 534a634530548d3f8b3a102c3e43e1cc64d8506d | https://github.com/SashaMatsun/torch-GAN/tree/534a634530548d3f8b3a102c3e43e1cc64d8506d |
Fp32GroupNorm | import torch
import torch.nn as nn
import torch.nn.functional as F
class Fp32GroupNorm(nn.GroupNorm):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
def forward(self, input):
output = F.group_norm(input.float(), self.num_groups, self.weight.
float() if sel... | 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 | Fp32GroupNorm | false | 2,282 | [
"MIT"
] | 0 | 854aff0b3062fc2cff531401923b8745f64701e7 | https://github.com/Ethan07902050/s3prl/tree/854aff0b3062fc2cff531401923b8745f64701e7 |
ModuleFallbackSub | import torch
import torch.nn as nn
import torch.fx
class ModuleFallbackSub(nn.Module):
def __init__(self):
super(ModuleFallbackSub, self).__init__()
self.conv = nn.Conv2d(1, 3, 3)
self.relu = nn.ReLU()
def forward(self, x):
return self.relu(self.conv(x))
def get_inputs():
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | NVIDIA/Torch-TensorRT | ModuleFallbackSub | false | 14,084 | [
"BSD-3-Clause"
] | 430 | 1a22204fecec690bc3c2a318dab4f57b98c57f05 | https://github.com/NVIDIA/Torch-TensorRT/tree/1a22204fecec690bc3c2a318dab4f57b98c57f05 |
SmallTransformerNet | # 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.... | CorentinChauvin/style-transfer-KD | SmallTransformerNet | false | 5,119 | [
"MIT"
] | 1 | 87bcb2963dbb8d09faf94c74a744f358cafe5427 | https://github.com/CorentinChauvin/style-transfer-KD/tree/87bcb2963dbb8d09faf94c74a744f358cafe5427 |
RegressionModel | # 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_... | DvdNss/FaceMaskDetection | RegressionModel | false | 407 | [
"Apache-2.0"
] | 0 | 3a4efe2bf8fb224d72636c853684a563b4e7a2e4 | https://github.com/DvdNss/FaceMaskDetection/tree/3a4efe2bf8fb224d72636c853684a563b4e7a2e4 |
resBlock | import torch
import torch.nn as nn
import torch.nn.functional as F
class resBlock(nn.Module):
def __init__(self, channelDepth, windowSize=3):
super(resBlock, self).__init__()
self.pad = nn.ReflectionPad2d(1)
self.IN_conv1 = nn.InstanceNorm2d(channelDepth)
self.conv1 = nn.Conv2d(ch... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | SeokjaeLIM/DSSN_release-Pytorch | resBlock | false | 17,897 | [
"Apache-2.0"
] | 7 | fef1dac120d7b83367b4c69f239b089ab5f004d7 | https://github.com/SeokjaeLIM/DSSN_release-Pytorch/tree/fef1dac120d7b83367b4c69f239b089ab5f004d7 |
AverageAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.cuda
import torch.distributed
assert_size_str... | MaxatTezekbayev/OpenNMT-py-lexical | AverageAttention | false | 5,589 | [
"MIT"
] | 1 | 44182999b863fc4074d67e0281c5bdab19abddfe | https://github.com/MaxatTezekbayev/OpenNMT-py-lexical/tree/44182999b863fc4074d67e0281c5bdab19abddfe |
FBLoss | # 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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | lRomul/argus-tgs-salt | FBLoss | false | 15,866 | [
"MIT"
] | 74 | 2ba7db4d09256bc025c49860cd79560ced6b8a1b | https://github.com/lRomul/argus-tgs-salt/tree/2ba7db4d09256bc025c49860cd79560ced6b8a1b |
MultiHeadAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | connoisseures/vedastr | MultiHeadAttention | false | 10,049 | [
"Apache-2.0"
] | 0 | 5dc64f3f6f810f615414aec3508e5dfba1239216 | https://github.com/connoisseures/vedastr/tree/5dc64f3f6f810f615414aec3508e5dfba1239216 |
Residual_Covolution | # 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_... | Dayan-Guan/SVMin | Residual_Covolution | false | 17,227 | [
"MIT"
] | 6 | d72b21f65958b1fda0abdbb60bd78d01e9d9cc8f | https://github.com/Dayan-Guan/SVMin/tree/d72b21f65958b1fda0abdbb60bd78d01e9d9cc8f |
PositioningCost | # 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_... | Juju-botu/diffeqml-research | PositioningCost | false | 13,918 | [
"Apache-2.0"
] | 49 | aa796c87447e5299ec4f25a07fc4d032afb1f63e | https://github.com/Juju-botu/diffeqml-research/tree/aa796c87447e5299ec4f25a07fc4d032afb1f63e |
AttCeMeanLoss | # 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
... | lonePatient/TorchBlocks | AttCeMeanLoss | false | 15,967 | [
"MIT"
] | 82 | 4a65d746cc8a396cb7df73ed4644d97ddf843e29 | https://github.com/lonePatient/TorchBlocks/tree/4a65d746cc8a396cb7df73ed4644d97ddf843e29 |
group | # 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_... | aryachiranjeev/Dependable-AI | group | false | 9,772 | [
"MIT"
] | 0 | 750570572c1baaa2590a89c0982e2f71b15b48b9 | https://github.com/aryachiranjeev/Dependable-AI/tree/750570572c1baaa2590a89c0982e2f71b15b48b9 |
SorensenDiceLoss | # 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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | krayyalasomayajula/inferno | SorensenDiceLoss | false | 3,951 | [
"Apache-2.0"
] | 0 | 1c56f34ff19c69dec3d3cb6287b659345bce3492 | https://github.com/krayyalasomayajula/inferno/tree/1c56f34ff19c69dec3d3cb6287b659345bce3492 |
PLU | # 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... | CuongNguyen218/ObjectDetection-OneStageDet | PLU | false | 331 | [
"MIT"
] | 0 | 60efe8b0ee6782b2aea20a32264b2ce1fc21901f | https://github.com/CuongNguyen218/ObjectDetection-OneStageDet/tree/60efe8b0ee6782b2aea20a32264b2ce1fc21901f |
VeryFlatNet | # 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
from ite... | royerloic/aydin | VeryFlatNet | false | 16,361 | [
"BSD-3-Clause"
] | 78 | f9c61a24030891d008c318b250da5faec69fcd7d | https://github.com/royerloic/aydin/tree/f9c61a24030891d008c318b250da5faec69fcd7d |
Accuracy | from torch.nn import Module
import torch
from torch import Tensor
class Accuracy(Module):
"""
Class for calculating the accuracy for a given prediction and the labels
for comparison.
Expects the inputs to be from a range of 0 to 1 and sets a crossing threshold at 0.5
the labels are similarly round... | 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 Tensor
assert_size_stride = torch._C._dynam... | eldarkurtic/sparseml | Accuracy | false | 10,051 | [
"Apache-2.0"
] | 0 | 9535ce1a576cd672fead58826376eef22baaebf7 | https://github.com/eldarkurtic/sparseml/tree/9535ce1a576cd672fead58826376eef22baaebf7 |
KDLoss_source_code | # 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 ... | PangJian123/ISM-ReID | KDLoss_source_code | false | 17,817 | [
"Apache-2.0"
] | 8 | 4c8e4b4ae591add83e1e6ba0b4b7d2750eeb9ee9 | https://github.com/PangJian123/ISM-ReID/tree/4c8e4b4ae591add83e1e6ba0b4b7d2750eeb9ee9 |
MaxPool | import torch
import torch.nn as nn
class MaxPool(nn.Module):
"""Module for MaxPool conversion testing
"""
def __init__(self, inp=10, out=16, kernel_size=3, bias=True):
super(MaxPool, self).__init__()
self.conv2d = nn.Conv2d(inp, out, kernel_size=kernel_size, bias=bias)
self.pool =... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | AliaksandrSiarohin/pytorch2keras | MaxPool | false | 8,902 | [
"MIT"
] | 0 | 9c8ee213cff43ade152b1de78fa76fd05ec8b40a | https://github.com/AliaksandrSiarohin/pytorch2keras/tree/9c8ee213cff43ade152b1de78fa76fd05ec8b40a |
MLP_VAE | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch import device
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from... | manuelladron/artistic_style_robotic_painting | MLP_VAE | false | 7,158 | [
"MIT"
] | 1 | 3769fc470bb4f69d2ea77d2713e4eb9bf0eaa4e9 | https://github.com/manuelladron/artistic_style_robotic_painting/tree/3769fc470bb4f69d2ea77d2713e4eb9bf0eaa4e9 |
MNIST_CNN | import torch
import torch.nn.functional as F
import torch.nn as nn
import torch.utils.data
class SqueezeLastTwo(nn.Module):
"""A module which squeezes the last two dimensions, ordinary squeeze can be a problem for batch size 1"""
def __init__(self):
super(SqueezeLastTwo, self).__init__()
def for... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | SirRob1997/DomainBed | MNIST_CNN | false | 5,859 | [
"MIT"
] | 1 | 7399a2b0a63df48f4b67755a3f33901223d5c8fb | https://github.com/SirRob1997/DomainBed/tree/7399a2b0a63df48f4b67755a3f33901223d5c8fb |
GAT | # 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.... | thilinicooray/pyGAT | GAT | false | 13,051 | [
"MIT"
] | 0 | 0c8fd0fdae20e42a41116cc9691e1223fd9d0a93 | https://github.com/thilinicooray/pyGAT/tree/0c8fd0fdae20e42a41116cc9691e1223fd9d0a93 |
Round | # 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.utils.data
impo... | felixcheng97/IICNet | Round | false | 15,353 | [
"MIT"
] | 50 | 2648d7148c01a03226128c24a285c4a52e2b5aa0 | https://github.com/felixcheng97/IICNet/tree/2648d7148c01a03226128c24a285c4a52e2b5aa0 |
PADB | import torch
import torch.utils.data
import torch.nn as nn
class PA(nn.Module):
def __init__(self, nf):
super(PA, self).__init__()
self.conv = nn.Conv2d(nf, nf, 1)
self.sigmoid = nn.Sigmoid()
def forward(self, x):
y = self.conv(x)
y = self.sigmoid(y)
out = tor... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
assert_size_stride = torch._C._dyn... | qwopqwop200/Fast-Invertible-Rescaling-Net | PADB | false | 7,545 | [
"MIT"
] | 1 | 871733f2eee7929d6b37c4d1d6a27347b39b67a9 | https://github.com/qwopqwop200/Fast-Invertible-Rescaling-Net/tree/871733f2eee7929d6b37c4d1d6a27347b39b67a9 |
MSELossWithIgnore | import torch
import torch.nn.functional
from torch import nn
class MSELossWithIgnore(nn.Module):
def __init__(self, ignore_value: 'int', fraction: 'float'=1.0):
super().__init__()
self.ignore_value = ignore_value
self.fraction = fraction
def forward(self, output, target):
los... | 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.functional
from torch import nn
assert_size_stride = torch._C._dynamo.gua... | drivendataorg/DrivenData-2021-Geopose-Solution | MSELossWithIgnore | false | 6,600 | [
"MIT"
] | 1 | fc1dead0aeb1ade9e9d87b55f56e631c57e966a6 | https://github.com/drivendataorg/DrivenData-2021-Geopose-Solution/tree/fc1dead0aeb1ade9e9d87b55f56e631c57e966a6 |
Generator | import torch
import torch.nn as nn
import torch.nn.functional as F
class Generator(nn.Module):
"""Define standard linear + softmax generation step."""
def __init__(self, emb_size, vocab_size):
super(Generator, self).__init__()
self.proj = nn.Linear(emb_size, vocab_size, bias=False)
def f... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | msobrevillac/Multilingual-RDF-Verbalizer | Generator | false | 10,561 | [
"MIT"
] | 0 | ba396693f65eaf74d1f60eb9aed3e78ab9593b22 | https://github.com/msobrevillac/Multilingual-RDF-Verbalizer/tree/ba396693f65eaf74d1f60eb9aed3e78ab9593b22 |
EncoderNet | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
class EncoderNet(nn.Module):
def __init__(self, pedestrian_num, input_size, hidden_size):
super(EncoderNet, self).__init__()
self.pedestrian_num = pedestrian_num
self.input_size = input_size
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | hk19960522/2018-DL-Final | EncoderNet | false | 3,605 | [
"MIT"
] | 0 | cbc70260aa22d7df366a1d28bee472f1fc5b82c7 | https://github.com/hk19960522/2018-DL-Final/tree/cbc70260aa22d7df366a1d28bee472f1fc5b82c7 |
MaskedMSELoss | # 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.optim
assert_size_stride = torch._C._dynamo.guards.ass... | NouamaneTazi/conv-emotion | MaskedMSELoss | false | 14,125 | [
"MIT"
] | 488 | 0c9dcb9cc5234a7ca8cf6af81aabe28ef3814d0e | https://github.com/NouamaneTazi/conv-emotion/tree/0c9dcb9cc5234a7ca8cf6af81aabe28ef3814d0e |
Feedforward | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | LavanayaBajaj/CREATE-CLASSIFIER | Feedforward | false | 774 | [
"MIT"
] | 0 | f00c7ec686f532a22e62d55aad169c831988be1b | https://github.com/LavanayaBajaj/CREATE-CLASSIFIER/tree/f00c7ec686f532a22e62d55aad169c831988be1b |
ConditionalRandomField | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
i... | FengZiYjun/fastNLP | ConditionalRandomField | false | 5,180 | [
"Apache-2.0"
] | 1 | 3ae73ab0a05d1ceef4a5181516891a8057d7f719 | https://github.com/FengZiYjun/fastNLP/tree/3ae73ab0a05d1ceef4a5181516891a8057d7f719 |
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 import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import functools
impor... | CK-er/mmdet | L1Loss | false | 2,063 | [
"Apache-2.0"
] | 0 | 9bea4068efbcf7bf739dbe41917a68d525c29868 | https://github.com/CK-er/mmdet/tree/9bea4068efbcf7bf739dbe41917a68d525c29868 |
ResBlock | # 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_... | NeilDG/SGID-PFF | ResBlock | false | 17,746 | [
"MIT"
] | 8 | e027ac65e63f3c052665290cd0438bb7bdeabf9f | https://github.com/NeilDG/SGID-PFF/tree/e027ac65e63f3c052665290cd0438bb7bdeabf9f |
SimpleClampModel | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleClampModel(torch.nn.Module):
def __init__(self, min, max):
super(SimpleClampModel, self).__init__()
self.min = min
self.max = max
def forward(self, input):
return torch.clamp(input, self.min, self.max... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.... | andreas-hommel/glow | SimpleClampModel | false | 3,329 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
FixupBasicBlock | import torch
import torch as th
import torch.utils.data
import torch.nn as nn
def _get_activation(activation):
valid = ['relu', 'leaky_relu', 'lrelu', 'tanh', 'sigmoid']
assert activation in valid, 'activation should be one of {}'.format(valid)
if activation == 'relu':
return nn.ReLU(inplace=True)... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch as th
import tor... | IlyaBizyaev/ttools | FixupBasicBlock | false | 8,358 | [
"MIT"
] | 11 | b1435b19f397ce1baff9daed3cb287e52a029fdb | https://github.com/IlyaBizyaev/ttools/tree/b1435b19f397ce1baff9daed3cb287e52a029fdb |
MlpBlock | # 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... | rushirajsherlocked/External-Attention-pytorch | MlpBlock | false | 4,218 | [
"MIT"
] | 0 | 7d6814b2d90909adf81c62f3f8a89e30a59d6481 | https://github.com/rushirajsherlocked/External-Attention-pytorch/tree/7d6814b2d90909adf81c62f3f8a89e30a59d6481 |
MaskBCELoss | import torch
import torch.nn.functional as F
from torch.nn.modules.loss import _Loss
class MaskBCELoss(_Loss):
def __init__(self, reduction='mean'):
super(MaskBCELoss, self).__init__()
assert reduction in ['none', 'sum', 'mean']
self.reduction = reduction
def forward(self, input, tar... | 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.... | imguozhen/proactive-chat | MaskBCELoss | false | 10,291 | [
"Apache-2.0"
] | 0 | 80d13e28cb93c26a65ace0a028c53fd0bafcdbf9 | https://github.com/imguozhen/proactive-chat/tree/80d13e28cb93c26a65ace0a028c53fd0bafcdbf9 |
DyIntraModalityUpdate | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
class DyIntraModalityUpdate(nn.Module):
"""
Dynamic Intra-modality Attention Flow
"""
def __init__(self, v_size, q_size, output_size, num_head, drop=0.0):
super(DyIntraModalityUpdate, self).__init__()
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | TranTony/DFAF-for-VQA.pytorch | DyIntraModalityUpdate | false | 11,964 | [
"MIT"
] | 0 | eba1a893e8e5d3d8bf85078611b0bcf4d56eea86 | https://github.com/TranTony/DFAF-for-VQA.pytorch/tree/eba1a893e8e5d3d8bf85078611b0bcf4d56eea86 |
Discriminator | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class Discriminator(nn.Module):
def __init__(self, num_inputs, args):
super(Discriminator, self).__init__()
self.fc1 = nn.Linear(num_inputs, args.hidden_size)
self.fc2 = nn.Linear(args.hidden_size, args.hidde... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | sgrimbly/lets-do-irl | Discriminator | false | 4,308 | [
"MIT"
] | 0 | 4233e238342394feef6a7bd495cc6b700d435b00 | https://github.com/sgrimbly/lets-do-irl/tree/4233e238342394feef6a7bd495cc6b700d435b00 |
Conv2dZeroInit | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | david-klindt/invertible-resnet | Conv2dZeroInit | false | 3,386 | [
"MIT"
] | 0 | ac6756a7ba5d0dbcb6b4cec43f8b86079318fd89 | https://github.com/david-klindt/invertible-resnet/tree/ac6756a7ba5d0dbcb6b4cec43f8b86079318fd89 |
GLU | import torch
from torch import nn
class GLU(nn.Module):
def __init__(self, input_num):
super(GLU, self).__init__()
self.sigmoid = nn.Sigmoid()
self.linear = nn.Linear(input_num, input_num)
def forward(self, x):
lin = self.linear(x.permute(0, 2, 3, 1))
lin = lin.permut... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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... | aagnone3/dc19t2 | GLU | false | 1,348 | [
"Apache-2.0"
] | 0 | cc7baf2a8fe73d28c224f0bf68b5355efd96c24f | https://github.com/aagnone3/dc19t2/tree/cc7baf2a8fe73d28c224f0bf68b5355efd96c24f |
ConcatBlock | # 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
assert_size_stride = torch._C._... | Luoxd1996/awesome-semi-supervised-learning-for-medical-image-segmentation | ConcatBlock | false | 17,706 | [
"MIT"
] | 6 | 34d78f41e4fa5927b03cb9f9b2fd473cd16f5e57 | https://github.com/Luoxd1996/awesome-semi-supervised-learning-for-medical-image-segmentation/tree/34d78f41e4fa5927b03cb9f9b2fd473cd16f5e57 |
ResidualAttention | import torch
from torch import nn
class ResidualAttention(nn.Module):
def __init__(self, channel=512, num_class=1000, la=0.2):
super().__init__()
self.la = la
self.fc = nn.Conv2d(in_channels=channel, out_channels=num_class,
kernel_size=1, stride=1, bias=False)
def forward... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | rushirajsherlocked/External-Attention-pytorch | ResidualAttention | false | 4,303 | [
"MIT"
] | 0 | 7d6814b2d90909adf81c62f3f8a89e30a59d6481 | https://github.com/rushirajsherlocked/External-Attention-pytorch/tree/7d6814b2d90909adf81c62f3f8a89e30a59d6481 |
iCaRL_loss | import torch
import torch.nn as nn
class iCaRL_loss(nn.Module):
def __init__(self):
super(iCaRL_loss, self).__init__()
def forward(self, logist, target):
eps = 1e-06
logist = logist.double()
target = target.double()
p0 = torch.mul(target, torch.log(logist + eps))
... | 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... | mao-example/End-to-End-Incremental-Learning | iCaRL_loss | false | 16,003 | [
"MIT"
] | 53 | 39d6f4e594e805a713aa7a1deedbcb03d1f2c9cc | https://github.com/mao-example/End-to-End-Incremental-Learning/tree/39d6f4e594e805a713aa7a1deedbcb03d1f2c9cc |
LinearAttention | # 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.... | DavidRuhe/simple-variational-diffusion-models | LinearAttention | false | 17,251 | [
"MIT"
] | 4 | a32355bf052a8f08e9c1919080588d0b22c8de4e | https://github.com/DavidRuhe/simple-variational-diffusion-models/tree/a32355bf052a8f08e9c1919080588d0b22c8de4e |
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