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 |
|---|---|---|---|---|---|---|---|---|---|---|
InceptionA | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | Hiroaki-Ozaki/modelib-classification | InceptionA | false | 17,407 | [
"WTFPL"
] | 10 | 11077704cc0bc9a42fc4b94da60b57d31ff0f65c | https://github.com/Hiroaki-Ozaki/modelib-classification/tree/11077704cc0bc9a42fc4b94da60b57d31ff0f65c |
AT | # 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, math as tl_math
import torch.nn as nn
import torch._utils
from itertools impor... | Capetian/FaceX-Zoo | AT | false | 4,959 | [
"Apache-2.0"
] | 1 | 029786c40d8aba15d891d33973de25fcd7e5399a | https://github.com/Capetian/FaceX-Zoo/tree/029786c40d8aba15d891d33973de25fcd7e5399a |
TemporalPooling | import torch
import torch.nn as nn
import torch.distributions
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
class TemporalPooling(nn.Module):
def __init__(self, frames, kernel_size=3, stride=2, mode='avg'):
"""
Parameters
--------... | 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.distributions
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data... | IBM/AdaMML | TemporalPooling | false | 8,256 | [
"Apache-2.0"
] | 32 | be50c02188e6b31ca3a25f285b1b538c137d3d5c | https://github.com/IBM/AdaMML/tree/be50c02188e6b31ca3a25f285b1b538c137d3d5c |
Binarizer | # 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.autograd... | MeMihir/SuperResCompression | Binarizer | false | 5,586 | [
"MIT"
] | 1 | c76bcf6b12d56ce3ad81ebb1b204fc0425f0e633 | https://github.com/MeMihir/SuperResCompression/tree/c76bcf6b12d56ce3ad81ebb1b204fc0425f0e633 |
MyEntLoss | import torch
import torch.nn as nn
class MyEntLoss(nn.Module):
def __init__(self):
super().__init__()
def forward(self, x):
x = torch.nn.Softmax(dim=1)(x)
p = x / torch.repeat_interleave(x.sum(dim=1).unsqueeze(-1), repeats
=20, dim=1)
logp = torch.log2(p)
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | yuantn/MI-AOD | MyEntLoss | false | 16,776 | [
"Apache-2.0"
] | 188 | e57114d60f9ce5e43839cdf7068a90ee58092ec8 | https://github.com/yuantn/MI-AOD/tree/e57114d60f9ce5e43839cdf7068a90ee58092ec8 |
RangeNorm2D | import torch
import torch.nn as nn
import torch.autograd
class RangeNorm2D(nn.Module):
"""
This will normalize a saliency map to range from 0 to 1 via linear range function.
Input and output will be a 3D tensor of size [batch size x height x width].
Input can be any rea... | 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.autograd
assert_size_stride = torch._C._dynamo.guards.... | LLNL/fastcam | RangeNorm2D | false | 8,427 | [
"BSD-3-Clause"
] | 25 | 99cefe37528014247319468cf05f54fef259d3bf | https://github.com/LLNL/fastcam/tree/99cefe37528014247319468cf05f54fef259d3bf |
Model | # 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_... | positivevaib/semi-supervised-imagenet-classification | Model | false | 4,144 | [
"MIT"
] | 0 | 4fb6427f5a72951c1b866a1ddbc2599811bb5770 | https://github.com/positivevaib/semi-supervised-imagenet-classification/tree/4fb6427f5a72951c1b866a1ddbc2599811bb5770 |
LastBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | lelechen63/idinvert_pytorch | LastBlock | false | 10,450 | [
"MIT"
] | 0 | 0469e1e5460ee4dd626c05bd35a83d52f9dc2cac | https://github.com/lelechen63/idinvert_pytorch/tree/0469e1e5460ee4dd626c05bd35a83d52f9dc2cac |
NonLocal2d | # 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.... | shunya-toyokawa/qanet_human_parts_segmentatiom | NonLocal2d | false | 16,519 | [
"MIT"
] | 72 | 5527b247acd65534b455c26e3692a14b31669602 | https://github.com/shunya-toyokawa/qanet_human_parts_segmentatiom/tree/5527b247acd65534b455c26e3692a14b31669602 |
FFN | # 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.... | Anonymous1376/MOTR | FFN | false | 2,516 | [
"Apache-2.0"
] | 0 | 804cac1a22068af8a8ae127eead8399026d07419 | https://github.com/Anonymous1376/MOTR/tree/804cac1a22068af8a8ae127eead8399026d07419 |
BasicBlock | # 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 ... | Limingxing00/Retinal-Vessel-Segmentation-ISBI2022 | BasicBlock | false | 17,580 | [
"MIT"
] | 9 | 9480de5c17dc3665a5f6d6d0117596bc5ffc108e | https://github.com/Limingxing00/Retinal-Vessel-Segmentation-ISBI2022/tree/9480de5c17dc3665a5f6d6d0117596bc5ffc108e |
Critic | import torch
import torch.nn as nn
import torch.nn.functional as F
class Encoder(nn.Module):
"""Encodes the static & dynamic states using 1d Convolution."""
def __init__(self, input_size, hidden_size):
super(Encoder, self).__init__()
self.conv = nn.Conv1d(input_size, hidden_size, kernel_size=... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | dimichai/City-Metro-Network-Expansion-with-RL | Critic | false | 3,431 | [
"MIT"
] | 0 | 54cfec74d89b4e4fc912d480a3025e4c75e3b196 | https://github.com/dimichai/City-Metro-Network-Expansion-with-RL/tree/54cfec74d89b4e4fc912d480a3025e4c75e3b196 |
ResidualAttentionBlock | import torch
from typing import Callable
from torch import nn
from torch.nn import functional as F
import torch.distributed.nn
from collections import OrderedDict
from typing import Optional
class LayerNorm(nn.LayerNorm):
"""Subclass torch's LayerNorm to handle fp16."""
def forward(self, x: 'torch.Tensor'):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | NYU-DICE-Lab/open_clip | ResidualAttentionBlock | false | 897 | [
"MIT"
] | 0 | fd71804b503135fb1c7cc8de3a0d6599741c8ed9 | https://github.com/NYU-DICE-Lab/open_clip/tree/fd71804b503135fb1c7cc8de3a0d6599741c8ed9 |
TorchDiv | import torch
class TorchDiv(torch.nn.Module):
def __init__(self):
super(TorchDiv, self).__init__()
def forward(self, x, y):
return torch.div(x, y)
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | PogChamper/torch2trt | TorchDiv | false | 14,215 | [
"MIT"
] | 3,363 | 43b12627ec0de4d212efb6d02b07570205085ccc | https://github.com/PogChamper/torch2trt/tree/43b12627ec0de4d212efb6d02b07570205085ccc |
Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | bm2-lab/MDML | Net | false | 1,559 | [
"MIT"
] | 0 | 222fb22b2ee53dd3c1a6f2e99a88f71e9635e3a0 | https://github.com/bm2-lab/MDML/tree/222fb22b2ee53dd3c1a6f2e99a88f71e9635e3a0 |
EntropicRiskMeasure | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch.nn import Module
from torch import Tensor
from typing import C... | vishalbelsare/pfhedge | EntropicRiskMeasure | false | 16,686 | [
"MIT"
] | 81 | 4d7ff173995e0795942bc6ec55f3fdc5bfb7a5f1 | https://github.com/vishalbelsare/pfhedge/tree/4d7ff173995e0795942bc6ec55f3fdc5bfb7a5f1 |
CoAttention | # 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.... | srlee-ai/claf | CoAttention | false | 10,883 | [
"MIT"
] | 0 | 89b3e5c5ec0486886876ea3bac381508c6a6bf58 | https://github.com/srlee-ai/claf/tree/89b3e5c5ec0486886876ea3bac381508c6a6bf58 |
GPool | from torch.nn import Module
import torch
from torch.nn import Sequential
from torch.nn import Linear
class FullyConnected(torch.nn.Module):
def __init__(self, in_features, out_features, bias=True, activation=None):
super().__init__()
self.linear = torch.nn.Linear(in_features, out_features, bias=b... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | RRemixx/DMRDenoise | GPool | false | 14,278 | [
"MIT"
] | 79 | 026d25f9eaf98fdfd85a67caeb9b49cab71148e9 | https://github.com/RRemixx/DMRDenoise/tree/026d25f9eaf98fdfd85a67caeb9b49cab71148e9 |
SpaceToDepth | import torch
from torchvision import datasets as datasets
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data.distributed
class SpaceToDepth(nn.Module):
def __init__(self, block_size=4):
super().__init__()
assert block_size == 4
self.bs = block_size
... | 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 torchvision import datasets as datasets
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data.distr... | adam-dziedzic/ASL | SpaceToDepth | false | 12,101 | [
"MIT"
] | 0 | cc063f5e7eda1498544ad2c3b224985203b0774a | https://github.com/adam-dziedzic/ASL/tree/cc063f5e7eda1498544ad2c3b224985203b0774a |
EdgeCaseModel | import torch
from typing import Any
import torch.nn as nn
class LayerWithRidiculouslyLongNameAndDoesntDoAnything(nn.Module):
""" Model with a very long name. """
def __init__(self) ->None:
super().__init__()
self.identity = nn.Identity()
def forward(self, x: 'Any') ->Any:
return ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from typing import Any
import torch.nn as nn
assert_size_stride = torch._C._dyna... | e-dorigatti/torchinfo | EdgeCaseModel | false | 12,327 | [
"MIT"
] | 0 | 9fa0e677fb7002e89afd5b1bb372fe8c1dd813d6 | https://github.com/e-dorigatti/torchinfo/tree/9fa0e677fb7002e89afd5b1bb372fe8c1dd813d6 |
HighwayLayer | # 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 ... | Dhiraj100892/droidlet | HighwayLayer | false | 11,340 | [
"MIT"
] | 0 | e4ea578672531524552b6ff021165fc9371b0ec8 | https://github.com/Dhiraj100892/droidlet/tree/e4ea578672531524552b6ff021165fc9371b0ec8 |
Joiner | import torch
from torch import nn
from torch.nn import functional as F
class Joiner(nn.Module):
def __init__(self, x_latent_dim, y_latent_dim, hidden_dim):
super().__init__()
self.fc1 = nn.Linear(x_latent_dim + y_latent_dim, hidden_dim)
self.fc2 = nn.Linear(hidden_dim, 1)
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... | Andrewzh112/experiments | Joiner | false | 47 | [
"MIT"
] | 0 | a35fd9e6157cd9a746f82229c2487539f668716a | https://github.com/Andrewzh112/experiments/tree/a35fd9e6157cd9a746f82229c2487539f668716a |
ResidualBlock | import torch
import torch.nn as nn
from functools import partial
def ncsn_conv3x3(in_planes, out_planes, stride=1, bias=True, dilation=1,
init_scale=1.0, padding=1):
"""3x3 convolution with PyTorch initialization. Same as NCSNv1/NCSNv2."""
init_scale = 1e-10 if init_scale == 0 else init_scale
conv = 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 ... | samsartor/score_sde | ResidualBlock | false | 7,607 | [
"Apache-2.0"
] | 1 | d25c8d092a68d643c796d771c55f80075aa041d1 | https://github.com/samsartor/score_sde/tree/d25c8d092a68d643c796d771c55f80075aa041d1 |
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.... | ArrowLuo/GRACE | MultiHeadAttention | false | 8,786 | [
"Apache-2.0"
] | 17 | f27b500ba905685c03eee6d91d87adc9ef78b4d1 | https://github.com/ArrowLuo/GRACE/tree/f27b500ba905685c03eee6d91d87adc9ef78b4d1 |
Memory | import torch
import torch.nn as nn
import torch.nn.parallel
class Memory(nn.Module):
def __init__(self):
super(Memory, self).__init__()
self.sm = nn.Softmax()
self.mask = None
def applyMask(self, mask):
self.mask = mask
def forward(self, input, context_key, content_value... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | JoonHong-Kim/T2I_CL | Memory | false | 8,382 | [
"MIT"
] | 35 | c52aa73da903d6e4174eeef2663e5bc1163785b1 | https://github.com/JoonHong-Kim/T2I_CL/tree/c52aa73da903d6e4174eeef2663e5bc1163785b1 |
CharbonnierCompLoss | import functools
import torch
import torch.nn as nn
from torch.nn import functional as F
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Returns:
Tensor: Reduced lo... | 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 functools
import torc... | rivergold/mmediting | CharbonnierCompLoss | false | 7,563 | [
"Apache-2.0"
] | 1 | fd972635c48bb065db29d1b5090592a87c7263d2 | https://github.com/rivergold/mmediting/tree/fd972635c48bb065db29d1b5090592a87c7263d2 |
DilatedNet | # 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... | tilacyn/dsb2018_topcoders | DilatedNet | false | 16,589 | [
"MIT"
] | 413 | e0f95ef70bc062d4dea321d2aa73231a9538cd63 | https://github.com/tilacyn/dsb2018_topcoders/tree/e0f95ef70bc062d4dea321d2aa73231a9538cd63 |
TensorMin | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | Minyus/pipelinex | TensorMin | false | 14,045 | [
"Apache-2.0"
] | 188 | f35c524ec9c50751ee27d9a42d98317e16f1c544 | https://github.com/Minyus/pipelinex/tree/f35c524ec9c50751ee27d9a42d98317e16f1c544 |
ContrastiveDistanceLoss | # 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
from torch.nn.modules.loss import *
from torch.nn.modules import *
... | bbradt/catalyst | ContrastiveDistanceLoss | false | 3,182 | [
"Apache-2.0"
] | 0 | 38a503c8af040906e377b7485d7fe15a7bc1de19 | https://github.com/bbradt/catalyst/tree/38a503c8af040906e377b7485d7fe15a7bc1de19 |
ReOrgLayer | # 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.utils.data
import torch.utils.data.distributed
import torch._utils
assert_size_stride = torch._C._dynamo.... | DatatangAILAB/SuanFaShiXun04 | ReOrgLayer | false | 17,214 | [
"Apache-2.0"
] | 5 | f478e40dd84240ac71cbb54e6bacf9ff556fbb3e | https://github.com/DatatangAILAB/SuanFaShiXun04/tree/f478e40dd84240ac71cbb54e6bacf9ff556fbb3e |
M | # 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.parallel
import torch.utils.data
import torch.onnx
import torch.fx
import torch.optim
import torch.utils.data.distributed
as... | ShuaihuaLu/examples | M | false | 5,820 | [
"BSD-3-Clause"
] | 1 | 2639cf050493df9d3cbf065d45e6025733add0f4 | https://github.com/ShuaihuaLu/examples/tree/2639cf050493df9d3cbf065d45e6025733add0f4 |
APLoss_dist | # 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.... | ByungHeeCha/visual_localization | APLoss_dist | false | 17,040 | [
"BSD-3-Clause"
] | 3 | 787fb8f6ee5c6e69ece9e83a016d15596e5524bc | https://github.com/ByungHeeCha/visual_localization/tree/787fb8f6ee5c6e69ece9e83a016d15596e5524bc |
BasicBlock | # 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.... | Justin-Tan/ffjord | BasicBlock | false | 703 | [
"MIT"
] | 0 | 2caf8a4ff84933672fe0d94255d665b3dd7a6791 | https://github.com/Justin-Tan/ffjord/tree/2caf8a4ff84933672fe0d94255d665b3dd7a6791 |
CriticNetwork | import torch
import torch.nn as nn
import torch.nn.functional as F
class CriticNetwork(nn.Module):
def __init__(self, input_shape, output_shape, **kwargs):
super().__init__()
n_input = input_shape[-1]
n_output = output_shape[0]
self._h = nn.Linear(n_input, n_output)
nn.ini... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | TheCamusean/mushroom-rl | CriticNetwork | false | 2,893 | [
"MIT"
] | 0 | 48585f883e546ea57224b8d446ecb9b8ba90cf73 | https://github.com/TheCamusean/mushroom-rl/tree/48585f883e546ea57224b8d446ecb9b8ba90cf73 |
TorchTensorAttrNet | import torch
import torch.nn.functional
class TorchTensorAttrNet(torch.nn.Module):
def __init__(self):
super(TorchTensorAttrNet, self).__init__()
self.conv1 = torch.nn.Conv2d(3, 4, kernel_size=1, stride=1)
def forward(self, x):
x = self.conv1(x)
x = x * x.size(1)
retu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn.functional
assert_size_stride = torch._C._dynamo.guards.assert_s... | elad-c/model_optimization | TorchTensorAttrNet | false | 10,659 | [
"Apache-2.0"
] | 0 | b0ecf41c3f9434008d57d7fe724ff8585e19d4cc | https://github.com/elad-c/model_optimization/tree/b0ecf41c3f9434008d57d7fe724ff8585e19d4cc |
distLinear | import torch
import torch.nn as nn
from torch.nn.utils.weight_norm import WeightNorm
import torch.utils.data
class distLinear(nn.Module):
def __init__(self, indim, outdim):
super(distLinear, self).__init__()
self.L = nn.Linear(indim, outdim, bias=False)
self.class_wise_learnable_norm = Fa... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | VisionLearningGroup/CDS | distLinear | false | 18,054 | [
"MIT"
] | 7 | 5b3644c286f19f76acdc03c6f6021a6f6e4ec4fc | https://github.com/VisionLearningGroup/CDS/tree/5b3644c286f19f76acdc03c6f6021a6f6e4ec4fc |
Encoder | import torch
import torch.nn as nn
class Encoder(nn.Module):
def __init__(self, in_size, latent_size):
super().__init__()
self.linear1 = nn.Linear(in_size, int(in_size / 2))
self.linear2 = nn.Linear(int(in_size / 2), int(in_size / 4))
self.linear3 = nn.Linear(int(in_size / 4), lat... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | DuneeshaFernando/usad | Encoder | false | 11,396 | [
"BSD-3-Clause"
] | 0 | 22653a96deefe57013b1df57bb6dc316ef423c95 | https://github.com/DuneeshaFernando/usad/tree/22653a96deefe57013b1df57bb6dc316ef423c95 |
LinearScalerModel | # 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.utils.data
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | sergiolib/pytorch-CycleGAN-and-pix2pix | LinearScalerModel | false | 12,964 | [
"BSD-3-Clause"
] | 0 | cd3058a6a0522a0ed9178682b06cda538947e335 | https://github.com/sergiolib/pytorch-CycleGAN-and-pix2pix/tree/cd3058a6a0522a0ed9178682b06cda538947e335 |
L1DistanceLoss | # 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... | wanyao1992/structural-probes | L1DistanceLoss | false | 16,697 | [
"Apache-2.0"
] | 357 | 3071c93b23601d834628d79a74e46e8ab5e5a66b | https://github.com/wanyao1992/structural-probes/tree/3071c93b23601d834628d79a74e46e8ab5e5a66b |
_leaky_relu | import torch
from torch import nn
import torch.optim
import torch.utils.data
class _leaky_relu(nn.Module):
def __init__(self):
super(_leaky_relu, self).__init__()
def forward(self, x):
x_neg = 0.1 * x
return torch.max(x_neg, x)
def get_inputs():
return [torch.rand([4, 4, 4, 4])... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import torch.optim
import torch.utils.data
assert_size_stride = torc... | ap229997/cc | _leaky_relu | false | 9,828 | [
"MIT"
] | 0 | d6f272b8270a371c877f4315047610b33a6e9f2d | https://github.com/ap229997/cc/tree/d6f272b8270a371c877f4315047610b33a6e9f2d |
BertPredictionHeadTransform | # 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
from to... | Sy-Zhang/recurrent-transformer | BertPredictionHeadTransform | false | 11,136 | [
"MIT"
] | 0 | f66ba49a2c9ec42759d3d00d497b49ffe39e18de | https://github.com/Sy-Zhang/recurrent-transformer/tree/f66ba49a2c9ec42759d3d00d497b49ffe39e18de |
Decoder | import torch
import torch.nn as nn
class Decoder(nn.Module):
def __init__(self, latent_dim, hidden_dim, output_dim):
super(Decoder, self).__init__()
self.FC_hidden = nn.Linear(latent_dim, hidden_dim)
self.FC_output = nn.Linear(hidden_dim, output_dim)
def forward(self, x):
h =... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | CsekM8/dtu_mlops | Decoder | false | 11,318 | [
"Apache-2.0"
] | 0 | 5c96a9afac0298fab57b7d47e4c08497f4a5d8d9 | https://github.com/CsekM8/dtu_mlops/tree/5c96a9afac0298fab57b7d47e4c08497f4a5d8d9 |
Maxout | import torch
import torch.nn as nn
class Maxout(nn.Module):
def __init__(self, pool_size):
super().__init__()
self._pool_size = pool_size
def forward(self, x):
assert x.shape[-1
] % self._pool_size == 0, 'Wrong input last dim size ({}) for Maxout({})'.format(
... | 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... | hekaplex/FocusSeq2Seq | Maxout | false | 10,186 | [
"MIT"
] | 0 | 9bab5d3aa020b4d587add9d7a070335cf0feb2d6 | https://github.com/hekaplex/FocusSeq2Seq/tree/9bab5d3aa020b4d587add9d7a070335cf0feb2d6 |
Critic | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | ahgit2021/deep-reinforcement-learning | Critic | false | 3,046 | [
"MIT"
] | 0 | 081464ba45f803663e841e1635d829aa00cce870 | https://github.com/ahgit2021/deep-reinforcement-learning/tree/081464ba45f803663e841e1635d829aa00cce870 |
Rot180 | # 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... | ChristophReich1996/kornia | Rot180 | false | 273 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 35f955b46e8015da1cb9faa28c6943ec2b09cc2a | https://github.com/ChristophReich1996/kornia/tree/35f955b46e8015da1cb9faa28c6943ec2b09cc2a |
FM | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from sklearn.metrics import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = tor... | chenkkkk/DeepCTR-PyTorch | FM | false | 6,427 | [
"Apache-2.0"
] | 1 | a10a3ace4ad79171e7fb182407b3e4d22bf753e7 | https://github.com/chenkkkk/DeepCTR-PyTorch/tree/a10a3ace4ad79171e7fb182407b3e4d22bf753e7 |
TanhDeepLiftModel | # 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_... | YNNEKUW/captum | TanhDeepLiftModel | false | 11,994 | [
"BSD-3-Clause"
] | 0 | c8b5357b21f2ddf440e5f0ce25635977292aa5d1 | https://github.com/YNNEKUW/captum/tree/c8b5357b21f2ddf440e5f0ce25635977292aa5d1 |
Lookahead | # 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.data.distributed
import torch.nn as nn
assert_size_stride = t... | faboyds/deepspeech.pytorch | Lookahead | false | 3,486 | [
"MIT"
] | 0 | d20f3510a3c556a07f5d662a91a63acffc26633b | https://github.com/faboyds/deepspeech.pytorch/tree/d20f3510a3c556a07f5d662a91a63acffc26633b |
AttModel | import torch
import torch.nn as nn
import torch.nn.functional as F
class AttModel(nn.Module):
def __init__(self, n_node, din, hidden_dim, dout):
super(AttModel, self).__init__()
self.fcv = nn.Linear(din, hidden_dim)
self.fck = nn.Linear(din, hidden_dim)
self.fcq = nn.Linear(din, h... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | jungwoohan72/DGN_pytorch | AttModel | false | 10,357 | [
"MIT"
] | 0 | 65fe7ab4df661d97725f2a72a1fdb49df1b2ea44 | https://github.com/jungwoohan72/DGN_pytorch/tree/65fe7ab4df661d97725f2a72a1fdb49df1b2ea44 |
BertAttention | # 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.... | QuLiang132/nlp-notebook | BertAttention | false | 5,743 | [
"MIT"
] | 1 | b7659867b967d1e541bee5617cee017b3b67d9ba | https://github.com/QuLiang132/nlp-notebook/tree/b7659867b967d1e541bee5617cee017b3b67d9ba |
ScaledDotAttention | import torch
import torch.nn as nn
from torch.nn import LayerNorm
def scaled_dot_attention(q, k, v, mask=None, noise=0, dropout=lambda x: x):
"""
:param q: queries, (batch, time1, channels1)
:param k: keys, (batch, time2, channels1)
:param v: values, (batch, time2, channels2)
:param mask: boolean ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | yhgon/speedyspeech | ScaledDotAttention | false | 13,149 | [
"BSD-3-Clause"
] | 0 | 574c6a94091431f313e2aae8e154b8c80e6908ce | https://github.com/yhgon/speedyspeech/tree/574c6a94091431f313e2aae8e154b8c80e6908ce |
Decoder | # 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
from torch import nn
assert_size_stride = torch._C._dynamo.guards.as... | roger-tseng/demucs | Decoder | false | 12,947 | [
"MIT"
] | 0 | 4a54a3c523a86345df294798994b60c8194e0a43 | https://github.com/roger-tseng/demucs/tree/4a54a3c523a86345df294798994b60c8194e0a43 |
APL | import torch
from torch import nn
from torch.nn.parameter import Parameter
class APL(nn.Module):
"""
Implementation of APL (ADAPTIVE PIECEWISE LINEAR UNITS) unit:
.. math::
APL(x_i) = max(0,x) + \\sum_{s=1}^{S}{a_i^s * max(0, -x + b_i^s)}
with trainable parameters a and b, parameter... | 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
from torch.nn.parameter import Parameter
assert_size_stride = torch.... | THEFASHIONGEEK/Echo | APL | false | 11,905 | [
"MIT"
] | 0 | 8dcf279ca528f2bfd255f79de07c1a221512c6a0 | https://github.com/THEFASHIONGEEK/Echo/tree/8dcf279ca528f2bfd255f79de07c1a221512c6a0 |
Concat | import torch
from torch import nn
from typing import *
class Concat(nn.Module):
def __init__(self):
super(Concat, self).__init__()
def forward(self, modalities):
flattened = []
for modality in modalities:
flattened.append(torch.flatten(modality, start_dim=1))
retu... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
from typing import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dyn... | HughMun/MultiBench | Concat | false | 13,772 | [
"MIT"
] | 148 | d5712a0815a9486b0e0c76b54cd63c880188fc8e | https://github.com/HughMun/MultiBench/tree/d5712a0815a9486b0e0c76b54cd63c880188fc8e |
FinalTanh | import torch
class FinalTanh(torch.nn.Module):
def __init__(self, input_channels, hidden_channels,
hidden_hidden_channels, num_hidden_layers):
super(FinalTanh, self).__init__()
self.input_channels = input_channels
self.hidden_channels = hidden_channels
self.hidden_hidden_c... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | lysuk96/rl_representations | FinalTanh | false | 15,977 | [
"MIT"
] | 438 | 19de69305e40c9b3a1d746a7af26d232c9fb3f6f | https://github.com/lysuk96/rl_representations/tree/19de69305e40c9b3a1d746a7af26d232c9fb3f6f |
BoxOffsetIntersection | # 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... | HKUST-KnowComp/EFO-1-QA-benchmark | BoxOffsetIntersection | false | 17,369 | [
"MIT"
] | 9 | 600fb02c76ab631f93ee362ceb789216ec085790 | https://github.com/HKUST-KnowComp/EFO-1-QA-benchmark/tree/600fb02c76ab631f93ee362ceb789216ec085790 |
Actor | import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
def hidden_init(layer):
fan_in = layer.weight.data.size()[0]
lim = 1.0 / np.sqrt(fan_in)
return -lim, lim
class Actor(nn.Module):
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed, 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.... | AntoniaSophia/deep-reinforcement-learning | Actor | false | 8,849 | [
"MIT"
] | 0 | 1d1c77039eea22fcf6726c35c3dd2563adfcb519 | https://github.com/AntoniaSophia/deep-reinforcement-learning/tree/1d1c77039eea22fcf6726c35c3dd2563adfcb519 |
_BoundaryRefineModule | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from to... | Rocketbase-AI/rockets-mobilepose | _BoundaryRefineModule | false | 5,775 | [
"MIT"
] | 1 | be7273dff7fcf7d1023f431f4b63ac8d82978182 | https://github.com/Rocketbase-AI/rockets-mobilepose/tree/be7273dff7fcf7d1023f431f4b63ac8d82978182 |
ResolutionScalingLayer | import torch
import torch.utils.data
import torch
from torch import nn
import torch.nn.functional as F
class ResolutionScalingLayer(nn.Module):
"""Implements the resolution scaling layer.
Basically, this layer can be used to upsample feature maps from spatial domain
with nearest neighbor interpolation.
"""... | 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
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda... | IVRL/BIGPrior | ResolutionScalingLayer | false | 572 | [
"MIT"
] | 0 | 6bf3b18fcbbd3c58bad7a792a8d28b017abb2411 | https://github.com/IVRL/BIGPrior/tree/6bf3b18fcbbd3c58bad7a792a8d28b017abb2411 |
PatchSequential | # 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 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 |
BPRLoss | import torch
import torch.nn as nn
class BPRLoss(nn.Module):
""" BPRLoss, based on Bayesian Personalized Ranking
Args:
- gamma(float): Small value to avoid division by zero
Shape:
- Pos_score: (N)
- Neg_score: (N), same shape as the Pos_score
- Output: scalar.
Exampl... | 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
... | dreaming-qin/RecBole | BPRLoss | false | 12,308 | [
"MIT"
] | 0 | d6de39521484ded60c387ca604abaf86310acdbe | https://github.com/dreaming-qin/RecBole/tree/d6de39521484ded60c387ca604abaf86310acdbe |
ReinforcedReceiver | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
import torch.utils.data
from torch.distributions import Bernoulli
import torch.distributions
class ReinforcedReceiver(nn.Module):
def __init__(self, n_bits, n_hidden):
super(ReinforcedReceiver, self).__init__()
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
import to... | cjlovering/EGG | ReinforcedReceiver | false | 10,061 | [
"MIT"
] | 0 | cce146e035decbc410e981f8bc7ada32979f3b6d | https://github.com/cjlovering/EGG/tree/cce146e035decbc410e981f8bc7ada32979f3b6d |
LayerNormChannels | import torch
import torch.nn as nn
class LayerNormChannels(nn.Module):
def __init__(self, c_in):
"""
This module applies layer norm across channels in an image. Has been shown to work well with ResNet connections.
Inputs:
c_in - Number of channels of the input
"""
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | onlyrico/lightning-tutorials | LayerNormChannels | false | 12,856 | [
"Apache-2.0"
] | 0 | b5d5c4015422f8c70411e57734d73bb6c1472999 | https://github.com/onlyrico/lightning-tutorials/tree/b5d5c4015422f8c70411e57734d73bb6c1472999 |
Highway | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import t... | YuWVandy/chemicalx | Highway | false | 1,276 | [
"Apache-2.0"
] | 0 | c02f979a502409c26700e6d5a1b2e6c0aa77e64c | https://github.com/YuWVandy/chemicalx/tree/c02f979a502409c26700e6d5a1b2e6c0aa77e64c |
LinearPool | import torch
from torch import nn
class LinearPool(nn.Module):
def __init__(self):
super(LinearPool, self).__init__()
def forward(self, feat_map):
"""
Arguments:
feat_map(Tensor): tensor with shape (N, C, H, W)
return(Tensor): tensor with shape (N, C, 1, 1)
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | DavidChenL/Chexpert | LinearPool | false | 13,619 | [
"Apache-2.0"
] | 202 | 0300057d3a51301cff35a65f79729436678b4a79 | https://github.com/DavidChenL/Chexpert/tree/0300057d3a51301cff35a65f79729436678b4a79 |
GlobalAttentionGeneral | # 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.... | Huy2122k/Project3-AttnGANwCLIP | GlobalAttentionGeneral | false | 9,116 | [
"MIT"
] | 0 | 3fb8c643bf71599e1606ec468e86373ccde1ed20 | https://github.com/Huy2122k/Project3-AttnGANwCLIP/tree/3fb8c643bf71599e1606ec468e86373ccde1ed20 |
BatchMeanCrossEntropyWithLogSoftmax | # 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... | cadurosar/graph_kd_dense_cifar100 | BatchMeanCrossEntropyWithLogSoftmax | false | 1,622 | [
"MIT"
] | 0 | 84054ab4f8f61c9db3460993661ba7bf1d951b36 | https://github.com/cadurosar/graph_kd_dense_cifar100/tree/84054ab4f8f61c9db3460993661ba7bf1d951b36 |
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... | lshoek/creative-evo-controller | VAE | false | 10,533 | [
"MIT"
] | 0 | a5f1742c172255cca2338b76ae1c5b4db277bb0d | https://github.com/lshoek/creative-evo-controller/tree/a5f1742c172255cca2338b76ae1c5b4db277bb0d |
MaxPool2d | # 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... | tomking/PySNN | MaxPool2d | false | 16,598 | [
"MIT"
] | 175 | c99ba6cd28a518dc07cab765acac9b69ac6fe36b | https://github.com/tomking/PySNN/tree/c99ba6cd28a518dc07cab765acac9b69ac6fe36b |
FocalLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | wang-tf/RepNet-MDNet-VehicleReID | FocalLoss | false | 16,692 | [
"MIT"
] | 226 | d3d184331206ca4bdb5ea399e5b90a9ccc53b400 | https://github.com/wang-tf/RepNet-MDNet-VehicleReID/tree/d3d184331206ca4bdb5ea399e5b90a9ccc53b400 |
LabelPropagation | import torch
import torch.nn.functional as F
import torch.nn as nn
class LabelPropagation(nn.Module):
"""label propagation model adapted from https://github.com/CUAI/CorrectAndSmooth
`"Learning from Labeled and
Unlabeled Datawith Label Propagation"
<http://mlg.eng.cam.ac.uk/zoubin/papers/CMU-CALD-02-1... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | EdisonLeeeee/Graphgallery | LabelPropagation | false | 5,120 | [
"MIT"
] | 1 | 8ae9ef57d44f073d0ceaf3f33a3a998546f960a8 | https://github.com/EdisonLeeeee/Graphgallery/tree/8ae9ef57d44f073d0ceaf3f33a3a998546f960a8 |
Residual_D | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from to... | vandit15/Self-Supervised-Gans-Pytorch | Residual_D | false | 16,663 | [
"MIT"
] | 66 | 01408fcce3e6cf4795d90c0f9d27e6906d5b59f3 | https://github.com/vandit15/Self-Supervised-Gans-Pytorch/tree/01408fcce3e6cf4795d90c0f9d27e6906d5b59f3 |
SimplifiedScaledDotProductAttention | # 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.... | Nitin-Mane/External-Attention-pytorch | SimplifiedScaledDotProductAttention | false | 14,110 | [
"MIT"
] | 4,466 | 1ceda306c41063af11c956334747763444a4d83f | https://github.com/Nitin-Mane/External-Attention-pytorch/tree/1ceda306c41063af11c956334747763444a4d83f |
LocalDictionaryLoss | # 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
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
... | pbt17/manifold-learning-with-simplex-constraints | LocalDictionaryLoss | false | 7,452 | [
"MIT"
] | 1 | 36609e2d05600965ee1331823547a077ba7b5a51 | https://github.com/pbt17/manifold-learning-with-simplex-constraints/tree/36609e2d05600965ee1331823547a077ba7b5a51 |
DDPGCritic | # 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_... | ikamensh/machin | DDPGCritic | false | 6,857 | [
"MIT"
] | 1 | af7b423c47bc1412530cf6c96c11bd3af9b3e239 | https://github.com/ikamensh/machin/tree/af7b423c47bc1412530cf6c96c11bd3af9b3e239 |
Block_cls | import torch
from torch import nn
from functools import partial
import torch.utils.data
import torch.nn.parallel
from torch import optim as optim
def drop_path(x, drop_prob: 'float'=0.0, training: 'bool'=False):
"""Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).
This ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | TencentYoutuResearch/BaseArchitecture-EAT | Block_cls | false | 18,034 | [
"BSD-3-Clause"
] | 9 | b916738ef9b1314f5fdad780a0839cb4e010a208 | https://github.com/TencentYoutuResearch/BaseArchitecture-EAT/tree/b916738ef9b1314f5fdad780a0839cb4e010a208 |
TensorClampOptionMax | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | PogChamper/torch2trt | TensorClampOptionMax | false | 14,222 | [
"MIT"
] | 3,363 | 43b12627ec0de4d212efb6d02b07570205085ccc | https://github.com/PogChamper/torch2trt/tree/43b12627ec0de4d212efb6d02b07570205085ccc |
FunctionalRelu6 | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | NVIDIA-AI-IOT-private/torch2trt | FunctionalRelu6 | false | 10,504 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
IoULoss | # 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.parallel
import torch.optim
import torch.utils.data... | TransformersWsz/onestage_grounding | IoULoss | false | 2,916 | [
"MIT"
] | 0 | c939a7d5d7c7f9e1bfa8df2e6269397b8f840b5a | https://github.com/TransformersWsz/onestage_grounding/tree/c939a7d5d7c7f9e1bfa8df2e6269397b8f840b5a |
HSigmoid | import torch
import torch.nn as nn
import torch.quantization
class HSigmoid(nn.Module):
"""Hard Sigmoid."""
def __init__(self, inplace: 'bool'=True) ->None:
"""Initialize."""
super(HSigmoid, self).__init__()
self.relu6 = nn.ReLU6(inplace=inplace)
def forward(self, x: 'torch.Tenso... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.quantization
assert_size_stride = torch._C._dynamo.gua... | dhlee347/model_compression | HSigmoid | false | 6,568 | [
"MIT"
] | 1 | 274b85ff56d81f0b7cf6907cbc1bd10e16cdb956 | https://github.com/dhlee347/model_compression/tree/274b85ff56d81f0b7cf6907cbc1bd10e16cdb956 |
TAGConv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn.functional as F
import torch.nn as nn
assert_size_stride = torch... | sigeisler/grb | TAGConv | false | 16,457 | [
"MIT"
] | 51 | c89e21076dc05d1edb87dfe2eff20c29ba6bd0c1 | https://github.com/sigeisler/grb/tree/c89e21076dc05d1edb87dfe2eff20c29ba6bd0c1 |
Upsample_interpolate | # 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... | Mathiebhan/darknet_ros | Upsample_interpolate | false | 11,685 | [
"BSD-3-Clause"
] | 0 | 04a97b61b6b3b086da1a46331a747accd37d05f9 | https://github.com/Mathiebhan/darknet_ros/tree/04a97b61b6b3b086da1a46331a747accd37d05f9 |
ExgLayer | # 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... | Yottaxx/T-LSTM | ExgLayer | false | 18,152 | [
"MIT"
] | 9 | 92618d8c3ee2418b194a2e1592512548da955b77 | https://github.com/Yottaxx/T-LSTM/tree/92618d8c3ee2418b194a2e1592512548da955b77 |
GDeconv1DBlock | import torch
import torch.nn as nn
from torch.nn.utils.spectral_norm import spectral_norm
def build_norm_layer(norm_type, param=None, num_feats=None):
if norm_type == 'bnorm':
return nn.BatchNorm1d(num_feats)
elif norm_type == 'snorm':
spectral_norm(param)
return None
elif norm_typ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.nn.utils.spectral_norm import spectral_norm
ass... | silvadirceu/segan_pytorch | GDeconv1DBlock | false | 10,802 | [
"MIT"
] | 0 | 2215e711f7223b144e0c4d4fb4ed1d4842b18c5f | https://github.com/silvadirceu/segan_pytorch/tree/2215e711f7223b144e0c4d4fb4ed1d4842b18c5f |
ReduceDim | import torch
import torch.nn as nn
import torch.nn.functional as F
class ReduceDim(nn.Module):
def __init__(self, input_dimension, output_dimension):
super(ReduceDim, self).__init__()
self.fc = nn.Linear(input_dimension, output_dimension)
def forward(self, x):
x = self.fc(x)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | iamshant/mmt | ReduceDim | false | 15,580 | [
"Apache-2.0"
] | 201 | 2716e9037f2d59e9aadd92d607bcf753f0146946 | https://github.com/iamshant/mmt/tree/2716e9037f2d59e9aadd92d607bcf753f0146946 |
BinaryClassificationHead | from _paritybench_helpers import _mock_config
import torch
class BinaryClassificationHead(torch.nn.Module):
def __init__(self, config):
super().__init__()
self.config = config
self.dense = torch.nn.Linear(config.hidden_size, config.hidden_size)
self.dropout = torch.nn.Dropout(conf... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | techthiyanes/DeepPavlov | BinaryClassificationHead | false | 16,556 | [
"Apache-2.0"
] | 5,893 | 08555428388fed3c7b036c0a82a70a25efcabcff | https://github.com/techthiyanes/DeepPavlov/tree/08555428388fed3c7b036c0a82a70a25efcabcff |
ConstantODE | import torch
class ConstantODE(torch.nn.Module):
def __init__(self):
super(ConstantODE, self).__init__()
self.a = torch.nn.Parameter(torch.tensor(0.2))
self.b = torch.nn.Parameter(torch.tensor(3.0))
def forward(self, t, y):
return self.a + (y - (self.a * t + self.b)) ** 5
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | MaricelaM/torchdiffeq | ConstantODE | false | 14,005 | [
"MIT"
] | 4,088 | 4e070fb687167e53082a91f32e102af7f4521058 | https://github.com/MaricelaM/torchdiffeq/tree/4e070fb687167e53082a91f32e102af7f4521058 |
WSConv2d | import torch
import torch.nn as nn
import torch.utils.data
class WSConv2d(nn.Module):
"""
Weight scaled Conv2d (Equalized Learning Rate)
Note that input is multiplied rather than changing weights
this will have the same result.
Inspired by:
https://github.com/nvnbny/progressive_growing_of_gan... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | ZonePG/Machine-Learning-Collection | WSConv2d | false | 14,727 | [
"MIT"
] | 3,094 | 85f1e761fab85b61d4dbd44285d6483b75ba649c | https://github.com/ZonePG/Machine-Learning-Collection/tree/85f1e761fab85b61d4dbd44285d6483b75ba649c |
GatedLinearUnit | import torch
import torch.nn as nn
class GatedLinearUnit(nn.Module):
def __init__(self, input_size, hidden_layer_size, dropout_rate,
activation=None):
super(GatedLinearUnit, self).__init__()
self.input_size = input_size
self.hidden_layer_size = hidden_layer_size
self.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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | sherpahu/AutoX | GatedLinearUnit | false | 4,315 | [
"Apache-2.0"
] | 0 | 37aca6bb848ecfdde6868b9f8eb869563fece3eb | https://github.com/sherpahu/AutoX/tree/37aca6bb848ecfdde6868b9f8eb869563fece3eb |
Net | import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
def __init__(self, n_obs, n_mid, n_action):
super().__init__()
self.fc1 = nn.Linear(n_obs, n_mid)
self.fc2 = nn.Linear(n_mid, n_mid)
self.fc3 = nn.Linear(n_mid, n_action)
def forward(self... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | CUSP-NYU/autonomous-drone-swarm | Net | false | 192 | [
"MIT"
] | 0 | 3bad474fd9641521588af61ddc48b84ffc746a74 | https://github.com/CUSP-NYU/autonomous-drone-swarm/tree/3bad474fd9641521588af61ddc48b84ffc746a74 |
DiscriminatorLoss | # 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 ... | akanametov/CycleGAN | DiscriminatorLoss | false | 6,129 | [
"MIT"
] | 1 | a61e76134cfdda43306e326e3dbba38d8cb21163 | https://github.com/akanametov/CycleGAN/tree/a61e76134cfdda43306e326e3dbba38d8cb21163 |
DeeperAutoencoder | # 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_... | mariajmolina/ML-for-S2S | DeeperAutoencoder | false | 10,568 | [
"MIT"
] | 0 | 3de32e72042ba7e8b37a433579fa9c5630246d8c | https://github.com/mariajmolina/ML-for-S2S/tree/3de32e72042ba7e8b37a433579fa9c5630246d8c |
LatentLoss | import torch
from torch import Tensor
import torch.nn as nn
class LatentLoss(nn.Module):
def forward(self, mu: 'Tensor', logvar: 'Tensor') ->Tensor:
loss = -0.5 * torch.sum(1 + logvar - mu.pow(2) - logvar.exp())
return loss
def get_inputs():
return [torch.rand([4, 4, 4, 4]), 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
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | jinyeom/vae | LatentLoss | false | 3,734 | [
"MIT"
] | 0 | 861cb2edd5cebc9f56c2677d7b79f5ab0a05f874 | https://github.com/jinyeom/vae/tree/861cb2edd5cebc9f56c2677d7b79f5ab0a05f874 |
_Enc | # 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
empty_strided_cu... | SimonNick/metakbc | _Enc | false | 5,825 | [
"MIT"
] | 1 | b502104e00afcb274c673ecd3aaa0415933e745e | https://github.com/SimonNick/metakbc/tree/b502104e00afcb274c673ecd3aaa0415933e745e |
MaxPool | # 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
import torch.nn.parallel
import torch.optim
import torch.utils.data
... | Ramstein/Retinopathy2 | MaxPool | false | 974 | [
"MIT"
] | 0 | 669e74206c466e6351d4e3df6087c6aa39b5c6c2 | https://github.com/Ramstein/Retinopathy2/tree/669e74206c466e6351d4e3df6087c6aa39b5c6c2 |
NNMerge | # 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... | Justin-Yuan/learn-to-interact | NNMerge | false | 5,414 | [
"MIT"
] | 1 | eb013bb3bab269bda8a8075e64fe3bcd2964d8ae | https://github.com/Justin-Yuan/learn-to-interact/tree/eb013bb3bab269bda8a8075e64fe3bcd2964d8ae |
MyModel | import torch
import torch.nn as nn
import torch.nn.functional as F
class MyModel(nn.Module):
def __init__(self, state_size, action_size):
super(MyModel, self).__init__()
self.fc1 = nn.Linear(state_size, 64)
self.fc2 = nn.Linear(64, 64)
self.fc3 = nn.Linear(64, action_size)
de... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | Ghazalmg/slimevolleygym | MyModel | false | 2,295 | [
"Apache-2.0"
] | 0 | d880a35625c22bbe0bc10fa0352495f0aea06364 | https://github.com/Ghazalmg/slimevolleygym/tree/d880a35625c22bbe0bc10fa0352495f0aea06364 |
Net_mish_ranger | # 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... | kartheikiyer/dense_basis_toolbelt | Net_mish_ranger | false | 12,660 | [
"MIT"
] | 0 | 5cae6e8f4ea6983fba3625f47413d40d6b3bc6e4 | https://github.com/kartheikiyer/dense_basis_toolbelt/tree/5cae6e8f4ea6983fba3625f47413d40d6b3bc6e4 |
ResidualDenseBlock_5C | import torch
import torch.nn as nn
from torch.nn import Parameter
def l2normalize(v, eps=1e-12):
return v / (v.norm() + eps)
class LayerNorm(nn.Module):
def __init__(self, num_features, eps=1e-08, affine=True):
super(LayerNorm, self).__init__()
self.num_features = num_features
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
from torch.nn import Parameter
assert_size_stride = torch.... | LenKerr/Semantic-Colorization-GAN | ResidualDenseBlock_5C | false | 5,528 | [
"MIT"
] | 1 | 2ce52406ca6fc92e69692b451b1c9ae66ba3b76f | https://github.com/LenKerr/Semantic-Colorization-GAN/tree/2ce52406ca6fc92e69692b451b1c9ae66ba3b76f |
ScalarMix | import torch
import torch.nn as nn
class ScalarMix(nn.Module):
"""
Computes a parameterised scalar mixture of :math:`N` tensors, :math:`mixture = \\gamma * \\sum_{k}(s_k * tensor_k)`
where :math:`s = \\mathrm{softmax}(w)`, with :math:`w` and :math:`\\gamma` scalar parameters.
Args:
n_layers (... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | KoichiYasuoka/SuPar | ScalarMix | false | 11,617 | [
"MIT"
] | 0 | 9bcf10fb946cae75b6a311d4cd19bec5bb1a9487 | https://github.com/KoichiYasuoka/SuPar/tree/9bcf10fb946cae75b6a311d4cd19bec5bb1a9487 |
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