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 |
|---|---|---|---|---|---|---|---|---|---|---|
SplAtConv2d | from torch.autograd import Function
from torch.nn import Module
import logging
import torch
import torch.utils.data
import torch.distributed as dist
from torch import nn
import torch.nn.functional as F
from torch.autograd.function import Function
from torch.autograd import Function
from torch.nn.modules.utils import _p... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | JHMeusener/detectron2-ResNeSt | SplAtConv2d | false | 604 | [
"Apache-2.0"
] | 0 | 6abab6fb9496a528f6aa2d4e1e27f3e7ceb42685 | https://github.com/JHMeusener/detectron2-ResNeSt/tree/6abab6fb9496a528f6aa2d4e1e27f3e7ceb42685 |
BertAttention | from _paritybench_helpers import _mock_config
import math
import torch
import torch.nn as nn
class BertSelfAttention(nn.Module):
"""
self attention层
原理可看这篇博客: http://jalammar.github.io/illustrated-transformer/
"""
def __init__(self, config):
super(BertSelfAttention, 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.... | QuLiang132/nlp-notebook | BertAttention | false | 5,743 | [
"MIT"
] | 1 | b7659867b967d1e541bee5617cee017b3b67d9ba | https://github.com/QuLiang132/nlp-notebook/tree/b7659867b967d1e541bee5617cee017b3b67d9ba |
VisTransformerDecoderLayer | # 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.... | Kamino666/Video-Captioning-Transformer | VisTransformerDecoderLayer | false | 8,409 | [
"Apache-2.0"
] | 14 | 06e6c95d9bf11d61f5825be3c640e489521f9934 | https://github.com/Kamino666/Video-Captioning-Transformer/tree/06e6c95d9bf11d61f5825be3c640e489521f9934 |
BeitPooler | # 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
from torch import nn
import torch.utils.checkpoint
assert_size_stride = torch._... | Clemens123/transformers | BeitPooler | false | 13,203 | [
"Apache-2.0"
] | 0 | 22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 | https://github.com/Clemens123/transformers/tree/22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 |
Unit1D | import torch
import torch.nn as nn
import torch.nn.functional as F
class Unit1D(nn.Module):
def __init__(self, in_channels, output_channels, kernel_shape=1, stride
=1, padding='same', activation_fn=F.relu, use_bias=True):
super(Unit1D, self).__init__()
self.conv1d = nn.Conv1d(in_channels,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | Cogito2012/OpenTAL | Unit1D | false | 7,900 | [
"BSD-3-Clause"
] | 16 | a7ab938a52b3fb82163eb1ba5403888359eb7e6a | https://github.com/Cogito2012/OpenTAL/tree/a7ab938a52b3fb82163eb1ba5403888359eb7e6a |
LayerNorm | import torch
from torch import nn
class LayerNorm(nn.Module):
def __init__(self, dim, eps=1e-05):
super().__init__()
self.eps = eps
self.g = nn.Parameter(torch.ones(1, dim, 1, 1, 1))
self.b = nn.Parameter(torch.zeros(1, dim, 1, 1, 1))
def forward(self, x):
std = torch... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | dumpmemory/uniformer-pytorch | LayerNorm | false | 15,278 | [
"MIT"
] | 71 | 756c4edb7ab0947dc202c145f7c95571848e0594 | https://github.com/dumpmemory/uniformer-pytorch/tree/756c4edb7ab0947dc202c145f7c95571848e0594 |
GlobalpoolFC | import torch
from torch import nn
class GlobalpoolFC(nn.Module):
def __init__(self, num_in, num_class):
super(GlobalpoolFC, self).__init__()
self.pool = nn.AdaptiveAvgPool2d(output_size=1)
self.fc = nn.Linear(num_in, num_class)
def forward(self, x):
rep = self.pool(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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | blackcow/Fair-AT | GlobalpoolFC | false | 1,550 | [
"Apache-2.0"
] | 0 | 62fc269fedd4b63c4b48ae390d494b3832e65fa8 | https://github.com/blackcow/Fair-AT/tree/62fc269fedd4b63c4b48ae390d494b3832e65fa8 |
ScaledDotProductAttention | import torch
import torch.nn as nn
class ScaledDotProductAttention(nn.Module):
"""Scaled dot-product attention mechanism."""
def __init__(self, temperature, attention_dropout=0.1):
super().__init__()
self.temperature = temperature
self.dropout = nn.Dropout(attention_dropout)
s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | AutuanLiu/PyTorch-ML | ScaledDotProductAttention | false | 16,966 | [
"MIT"
] | 9 | 884c7723843d9ffb4da09d95eb97886b2cc38f28 | https://github.com/AutuanLiu/PyTorch-ML/tree/884c7723843d9ffb4da09d95eb97886b2cc38f28 |
DilatedCircularConv | import torch
import torch.nn as nn
class DilatedCircularConv(nn.Module):
def __init__(self, state_dim, out_state_dim=None, n_adj=4, dilation=1):
super(DilatedCircularConv, self).__init__()
self.n_adj = n_adj
self.dilation = dilation
out_state_dim = state_dim if out_state_dim is No... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | LiWentomng/boxlevelset | DilatedCircularConv | false | 8,468 | [
"Apache-2.0"
] | 25 | 8cc40bf6ae4a343c482c676c72259cc12c29d31c | https://github.com/LiWentomng/boxlevelset/tree/8cc40bf6ae4a343c482c676c72259cc12c29d31c |
WeightedMCEloss | # 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
... | CarlosPena00/pytorch-unet | WeightedMCEloss | false | 210 | [
"MIT"
] | 0 | 8365bace23e4b04b9c5b75cd6720807ea8cac5ab | https://github.com/CarlosPena00/pytorch-unet/tree/8365bace23e4b04b9c5b75cd6720807ea8cac5ab |
NaiveGroupNorm | from torch.nn import Module
import torch
from torch.nn import Parameter
from torch.nn import init
import torch.nn.parallel
import torch.utils.data
class NaiveGroupNorm(Module):
"""NaiveGroupNorm implements Group Normalization with the high-level matrix operations in PyTorch.
It is a temporary solution to expo... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch.nn import Module
from torch.nn import Parameter
from torch.nn import... | UrwLee/AdelaiDet | NaiveGroupNorm | false | 9,633 | [
"BSD-2-Clause"
] | 0 | 4cd88a80355d21261e94400767f44701ebc4b402 | https://github.com/UrwLee/AdelaiDet/tree/4cd88a80355d21261e94400767f44701ebc4b402 |
TensorClamp | # 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... | ahangchen/torch2trt | TensorClamp | false | 6,112 | [
"MIT"
] | 1 | 53c663f0e0570ef7ffd6771354ae3478f63bd328 | https://github.com/ahangchen/torch2trt/tree/53c663f0e0570ef7ffd6771354ae3478f63bd328 |
Transformer | # 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.... | LucWeber/2048-RLenv | Transformer | false | 1,014 | [
"MIT"
] | 0 | 6beff54691f0436f0fbca6bdbb9430fd37eab37d | https://github.com/LucWeber/2048-RLenv/tree/6beff54691f0436f0fbca6bdbb9430fd37eab37d |
ScaleLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
import torch._utils
assert_size_stride = torch._C._... | aagaard/ritm_interactive_segmentation | ScaleLayer | false | 12,033 | [
"MIT"
] | 0 | c68b45a54e99eb5401f50e62f7e43a11e34964ee | https://github.com/aagaard/ritm_interactive_segmentation/tree/c68b45a54e99eb5401f50e62f7e43a11e34964ee |
GrayLoss | # 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
... | GuYuanjie/DeepFusionPrior | GrayLoss | false | 5,219 | [
"MIT"
] | 1 | a7126e073ed8c49b6a9a662492b64aaeee56cc01 | https://github.com/GuYuanjie/DeepFusionPrior/tree/a7126e073ed8c49b6a9a662492b64aaeee56cc01 |
SimpleConvTranspose2dModule | import torch
import torch.nn.functional as F
import torch.jit
import torch.onnx
import torch.nn
class SimpleConvTranspose2dModule(torch.nn.Module):
def __init__(self, stride=1, padding=0, output_padding=0, dilation=1,
groups=1):
super(SimpleConvTranspose2dModule, self).__init__()
self.str... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | briancoutinho/glow | SimpleConvTranspose2dModule | false | 12,558 | [
"Apache-2.0"
] | 0 | 4c919d60b3c33296c4109aec8020a1733c98f5b5 | https://github.com/briancoutinho/glow/tree/4c919d60b3c33296c4109aec8020a1733c98f5b5 |
BasicModel4_MultiArgs | # 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... | aravipati12/captum | BasicModel4_MultiArgs | false | 10,113 | [
"BSD-3-Clause"
] | 0 | ef3e81d89c8c4404a49c384cf0727f2e7d393f5f | https://github.com/aravipati12/captum/tree/ef3e81d89c8c4404a49c384cf0727f2e7d393f5f |
FilterNorm | import torch
import torch.nn as nn
from torch.nn.init import calculate_gain
class FilterNorm(nn.Module):
def __init__(self, in_channels, kernel_size, filter_type, nonlinearity=
'linear', running_std=False, running_mean=False):
assert filter_type in ('spatial', 'channel')
assert in_channel... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
from torch.nn.init import calculate_gain
assert_size_stri... | danyayay/ynet_adaptive | FilterNorm | false | 1,793 | [
"MIT"
] | 0 | f1daea6f3d5ec8a7349c2ee72bf742df83786103 | https://github.com/danyayay/ynet_adaptive/tree/f1daea6f3d5ec8a7349c2ee72bf742df83786103 |
AsymmetricLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Return:
Tensor: Reduced loss tensor.
"""
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | HexaFarms/MMClassification | AsymmetricLoss | false | 11,479 | [
"Apache-2.0"
] | 0 | d61d0448b6bcd2fd4c0a408688f603a53ab16ca2 | https://github.com/HexaFarms/MMClassification/tree/d61d0448b6bcd2fd4c0a408688f603a53ab16ca2 |
MSELoss | import functools
import torch
import torch.nn as nn
import torch.nn.functional as F
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Return:
Tensor: Reduced loss ten... | 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 functools
import torch.nn as nn
import torch.nn.functional as F
assert_size_stride... | AtticusJohnson/mmdetection | MSELoss | false | 11,231 | [
"Apache-2.0"
] | 0 | d8d89bafcce13d3b32b1fb3366be3bb9830546c2 | https://github.com/AtticusJohnson/mmdetection/tree/d8d89bafcce13d3b32b1fb3366be3bb9830546c2 |
deepQ | # 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_... | ExilesAI/RLAgents | deepQ | false | 9,005 | [
"MIT"
] | 0 | b8159a933c4674c7a62bfe9555870336616a59f3 | https://github.com/ExilesAI/RLAgents/tree/b8159a933c4674c7a62bfe9555870336616a59f3 |
TVLoss | import torch
import torch.utils.data
import torch
import torch.nn as nn
class TVLoss(nn.Module):
def __init__(self, TVLoss_weight=1.0):
super(TVLoss, self).__init__()
self.TVLoss_weight = TVLoss_weight
def forward(self, x):
batch_size = x.size()[0]
h_x = x.size()[2]
w... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
import torch
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cud... | xyp8023/pytorch-CycleGAN-and-pix2pix | TVLoss | false | 13,125 | [
"BSD-3-Clause"
] | 0 | dce720d985a951a3cfed470ef4c2ef206c0e0817 | https://github.com/xyp8023/pytorch-CycleGAN-and-pix2pix/tree/dce720d985a951a3cfed470ef4c2ef206c0e0817 |
MaxOut | import torch
import torch.nn as nn
class MaxOut(nn.Module):
def __init__(self, input_size: 'int', hidden_size: 'int') ->None:
super(MaxOut, self).__init__()
self._ops_1 = nn.Linear(input_size, hidden_size)
self._ops_2 = nn.Linear(input_size, hidden_size)
def forward(self, x: 'torch.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 import triton_helpers
import torch.nn as nn
assert_... | aisolab/nlp_implementation | MaxOut | false | 14,773 | [
"MIT"
] | 181 | 21ea6e3f5737e7074bdd8dd190e5f5172f86f6bf | https://github.com/aisolab/nlp_implementation/tree/21ea6e3f5737e7074bdd8dd190e5f5172f86f6bf |
SReLU | import torch
from torch import nn
from torch.nn.parameter import Parameter
class SReLU(nn.Module):
"""
SReLU (S-shaped Rectified Linear Activation Unit): a combination of three linear functions, which perform mapping R → R with the following formulation:
.. math::
h(x_i) = \\left\\{\\begin{matri... | 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 torch.nn.parameter import Parameter
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_... | Venkateshwar2506/Echo | SReLU | false | 1,189 | [
"MIT"
] | 0 | 5d236b25ee4900754f48e0a865e1bf1ae9183875 | https://github.com/Venkateshwar2506/Echo/tree/5d236b25ee4900754f48e0a865e1bf1ae9183875 |
LeftSVDLayer | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
class LeftSVDLayer(nn.Module):
def __init__(self, ih, oh, dropout=None, bias=True):
super().__init__()
self.weight = Parameter(torch.Tensor(oh, ih))
self.dropout = 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 math
import torch.nn as nn
from torch.nn.parameter import Parameter
asser... | collodi/ml_svd | LeftSVDLayer | false | 1,737 | [
"MIT"
] | 0 | 67a608ca10d3d37bf861e4e7490e62d298fa83b9 | https://github.com/collodi/ml_svd/tree/67a608ca10d3d37bf861e4e7490e62d298fa83b9 |
GateAddNorm | import torch
from torch import nn
from torchvision import models as models
import torch.onnx
import torch.nn
class GatedLinearUnit(nn.Module):
def __init__(self, input_size, output_size, dropout=0):
super().__init__()
self.dropout = nn.Dropout(dropout)
self.w4 = nn.Linear(input_size, outp... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | krodyush/training_extensions | GateAddNorm | false | 10,984 | [
"Apache-2.0"
] | 0 | 542f4004dfbc6fc62a622065367ba4f85a703dd3 | https://github.com/krodyush/training_extensions/tree/542f4004dfbc6fc62a622065367ba4f85a703dd3 |
StateCritic | # 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_... | dimichai/City-Metro-Network-Expansion-with-RL | StateCritic | false | 3,444 | [
"MIT"
] | 0 | 54cfec74d89b4e4fc912d480a3025e4c75e3b196 | https://github.com/dimichai/City-Metro-Network-Expansion-with-RL/tree/54cfec74d89b4e4fc912d480a3025e4c75e3b196 |
FusedUpsample | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
from math import sqrt
assert_size_stride = torch._C._dynamo... | KUMartin77/AAA738_StyleGAN_pytorch | FusedUpsample | false | 11,603 | [
"BSD-2-Clause"
] | 0 | ed0689102c922d336f53e374e8be2ab532a84ccd | https://github.com/KUMartin77/AAA738_StyleGAN_pytorch/tree/ed0689102c922d336f53e374e8be2ab532a84ccd |
BertSelfAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | noble6emc2/MoCo-SSPT | BertSelfAttention | false | 12,852 | [
"MIT"
] | 0 | e6d7cf3f0a3b5a467318dfc32096e4929adbe646 | https://github.com/noble6emc2/MoCo-SSPT/tree/e6d7cf3f0a3b5a467318dfc32096e4929adbe646 |
TKipfGCN | # 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.... | zxhhh97/cogdl | TKipfGCN | false | 4,682 | [
"MIT"
] | 0 | de21c78d9bbbf0c6cafbc72ff241cda35693ec37 | https://github.com/zxhhh97/cogdl/tree/de21c78d9bbbf0c6cafbc72ff241cda35693ec37 |
Attention | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import *
class Attention(nn.Module):
def __init__(self, opt):
super(Attention, self).__init__()
self.rnn_size = opt.rnn_size
self.att_hid_size = opt.att_hid... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | VISLANG-Lab/MGCL | Attention | false | 1,893 | [
"MIT"
] | 0 | 22da06ffa7410d9632bfda8eefb1b79e4f660de0 | https://github.com/VISLANG-Lab/MGCL/tree/22da06ffa7410d9632bfda8eefb1b79e4f660de0 |
CpuEmbedding | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | SUSTechBruce/RL_CTR | CpuEmbedding | false | 2,801 | [
"Apache-2.0"
] | 0 | 817398dc1c117e22f41281830ae3c33bba8062d3 | https://github.com/SUSTechBruce/RL_CTR/tree/817398dc1c117e22f41281830ae3c33bba8062d3 |
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.... | HuXiao-THU/Crane-Group-Control | Actor | false | 558 | [
"MIT"
] | 0 | ea71bc9b1e3957fd755312ceb52bda1be8244f5a | https://github.com/HuXiao-THU/Crane-Group-Control/tree/ea71bc9b1e3957fd755312ceb52bda1be8244f5a |
PositionwiseFeedForward | import torch
import torch.nn as nn
import torch.optim
class LayerNorm(nn.Module):
def __init__(self, features, eps=1e-06):
super(LayerNorm, self).__init__()
self.a_2 = nn.Parameter(torch.ones(features))
self.b_2 = nn.Parameter(torch.zeros(features))
self.eps = eps
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._inductor.runtime.... | howardchenhd/Transformer-pytorch | PositionwiseFeedForward | false | 6,823 | [
"MIT"
] | 1 | ae71ed5767272feb7e717be6d5bfce46f80ec57a | https://github.com/howardchenhd/Transformer-pytorch/tree/ae71ed5767272feb7e717be6d5bfce46f80ec57a |
SirenLayer | import torch
import numpy as np
from torch import nn
class SirenLayer(nn.Module):
def __init__(self, in_f, out_f, w0=30, is_first=False, is_last=False):
super().__init__()
self.in_f = in_f
self.w0 = w0
self.linear = nn.Linear(in_f, out_f)
self.is_first = is_first
s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import numpy ... | abrilcf/pixel-nerf | SirenLayer | false | 1,356 | [
"BSD-2-Clause"
] | 0 | 9a6a8ab6c39ec01d52df3bf4c03830f7162cc679 | https://github.com/abrilcf/pixel-nerf/tree/9a6a8ab6c39ec01d52df3bf4c03830f7162cc679 |
CRF | # 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... | ay94/CrossNER | CRF | false | 14,945 | [
"MIT"
] | 77 | 2e7ba2a7798c961e3f29fbc51252c5a8d40224bf | https://github.com/ay94/CrossNER/tree/2e7ba2a7798c961e3f29fbc51252c5a8d40224bf |
CapsuleConvLayer | # 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_... | juingzhou/Base-on-PyTorch-implementation-CapsuleNet | CapsuleConvLayer | false | 10,318 | [
"MIT"
] | 0 | 6b030bf93b258d9d6496379bcbe4b94542366817 | https://github.com/juingzhou/Base-on-PyTorch-implementation-CapsuleNet/tree/6b030bf93b258d9d6496379bcbe4b94542366817 |
GTConv_2 | # 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... | verashira/TSPNet | GTConv_2 | false | 16,670 | [
"MIT"
] | 83 | ee454165dcc61cdbbff19565364e2221727ed2b8 | https://github.com/verashira/TSPNet/tree/ee454165dcc61cdbbff19565364e2221727ed2b8 |
ConvLayer | # 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... | DA4EVENT/home | ConvLayer | false | 17,186 | [
"MIT"
] | 5 | 18cc93a795ce132e05b886aa34565a102915b1c6 | https://github.com/DA4EVENT/home/tree/18cc93a795ce132e05b886aa34565a102915b1c6 |
NIN | # 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 string
import numpy as np
import torch.utils.data
import torch
import tor... | mrjavoman/Image-Super-Resolution-via-Iterative-Refinement | NIN | false | 7,285 | [
"Apache-2.0"
] | 1 | 2eb11d972e8e024c3b1d7a84f90895e329b5b408 | https://github.com/mrjavoman/Image-Super-Resolution-via-Iterative-Refinement/tree/2eb11d972e8e024c3b1d7a84f90895e329b5b408 |
PaddedInstanceNorm1d | # 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_... | shaun95/cotatron | PaddedInstanceNorm1d | false | 16,414 | [
"BSD-3-Clause"
] | 202 | 2d0254399a3063ba1d2f77bef535cc148041236e | https://github.com/shaun95/cotatron/tree/2d0254399a3063ba1d2f77bef535cc148041236e |
TVLoss | import torch
from torch import nn
from torch.nn import functional as F
class TVLoss(nn.Module):
"""L2 total variation loss, as in Mahendran et al."""
def forward(self, input):
input = F.pad(input, (0, 1, 0, 1), 'replicate')
x_diff = input[..., :-1, 1:] - input[..., :-1, :-1]
y_diff = ... | 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... | MED-YAHYAOUI/style-transfer-pytorch | TVLoss | false | 11,662 | [
"MIT"
] | 0 | 867a6a45d964c151d6b94f50153cf535385c9078 | https://github.com/MED-YAHYAOUI/style-transfer-pytorch/tree/867a6a45d964c151d6b94f50153cf535385c9078 |
MaskNet | import torch
import torch.nn as nn
class MaskNet(nn.Module):
def __init__(self):
super(MaskNet, self).__init__()
self.conv1 = nn.Conv2d(in_channels=1, out_channels=16, kernel_size=
5, stride=1, padding=2)
self.relu1 = nn.ReLU()
self.Pool1 = nn.MaxPool2d(kernel_size=(2,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | DongChengdongHangZhou/adversarial-attack-iris | MaskNet | false | 11,415 | [
"Apache-2.0"
] | 0 | ae7e408c47c332fc876d572acd4701e4b8970487 | https://github.com/DongChengdongHangZhou/adversarial-attack-iris/tree/ae7e408c47c332fc876d572acd4701e4b8970487 |
TVLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | JaledMC/neural-style-pt | TVLoss | false | 11,539 | [
"MIT"
] | 0 | ce205c867761e251e86c89722df81c74dad7a221 | https://github.com/JaledMC/neural-style-pt/tree/ce205c867761e251e86c89722df81c74dad7a221 |
NN1 | # 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_... | kirtanp/MAMO-fair | NN1 | false | 7,039 | [
"Apache-2.0"
] | 1 | fd0fc39383f11a9e1ec401233b89c2399860fb94 | https://github.com/kirtanp/MAMO-fair/tree/fd0fc39383f11a9e1ec401233b89c2399860fb94 |
Dummy | import torch
from torch import nn
class Dummy(nn.Module):
def forward(self, input):
x = input
return x + 1
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | Tomaz-Vieira/tiktorch | Dummy | false | 18,020 | [
"MIT"
] | 8 | 2d6803c4ba5e26e4b27bf8af6638040fa4fc5628 | https://github.com/Tomaz-Vieira/tiktorch/tree/2d6803c4ba5e26e4b27bf8af6638040fa4fc5628 |
SelfAttention | import torch
from torch import nn
import torch.utils.data
class SelfAttention(nn.Module):
def __init__(self, embed_size, heads):
super(SelfAttention, self).__init__()
self.embed_size = embed_size
self.heads = heads
self.head_dim = embed_size // heads
assert self.head_dim *... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | jiazhi412/Machine-Learning-Collection | SelfAttention | false | 3,747 | [
"MIT"
] | 0 | 1c30faf1e27a79eeca966c017e956df8f7f6ef17 | https://github.com/jiazhi412/Machine-Learning-Collection/tree/1c30faf1e27a79eeca966c017e956df8f7f6ef17 |
SigmaL1SmoothLoss | # 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
... | davidpfahler/fastai_dev | SigmaL1SmoothLoss | false | 10,050 | [
"Apache-2.0"
] | 0 | a86b15f86138a9902e8649e3f745e76a19139ab3 | https://github.com/davidpfahler/fastai_dev/tree/a86b15f86138a9902e8649e3f745e76a19139ab3 |
FocalLoss | import torch
import torch.nn as nn
class FocalLoss(nn.Module):
def __init__(self, gamma=1.5, alpha=0.25, reduction=torch.mean):
super(FocalLoss, self).__init__()
self.loss_fcn = nn.BCEWithLogitsLoss(reduction='none')
self.gamma = gamma
self.alpha = alpha
self.reduction = r... | 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... | PatrickChoDev/LiDAR-ObjDetect | FocalLoss | false | 2,730 | [
"MIT"
] | 0 | a839220d28a1fda045278ded0992e46f408a5442 | https://github.com/PatrickChoDev/LiDAR-ObjDetect/tree/a839220d28a1fda045278ded0992e46f408a5442 |
MinibatchDiscrimination1d | # 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.... | torchgan/torchgan | MinibatchDiscrimination1d | false | 16,612 | [
"MIT"
] | 1,300 | f4139537ac2d3d8609d5aecc859a6fb797b107a1 | https://github.com/torchgan/torchgan/tree/f4139537ac2d3d8609d5aecc859a6fb797b107a1 |
BLogDiceLoss | import torch
import torch.nn.functional
import torch.nn as nn
def centercrop(image, w, h):
_nt, _ct, ht, wt = image.size()
padw, padh = (wt - w) // 2, (ht - h) // 2
if padw > 0 and padh > 0:
image = image[:, :, padh:-padh, padw:-padw]
return image
class BLogDiceLoss(nn.Module):
def __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.triton_helpers import math as tl_math
import torch.nn.functional
import torch.nn as nn
assert_size_stride = tor... | HelenGuohx/cv-ferattn-code | BLogDiceLoss | false | 5,285 | [
"MIT"
] | 1 | faa9b7850fe2a0f8c08193bb129b5fec4639d616 | https://github.com/HelenGuohx/cv-ferattn-code/tree/faa9b7850fe2a0f8c08193bb129b5fec4639d616 |
Normalize | import torch
from torchvision.datasets import *
import torch.nn.functional as F
import torch.nn as nn
from torchvision.transforms import *
class Normalize(nn.Module):
"""Performs :math:`L_p` normalization of inputs over specified dimension.
Does:
.. math::
v = \\frac{v}{\\max(\\lVert v \\rVert_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
from torchvision.datasets im... | ruijieren98/DANet | Normalize | false | 16,355 | [
"MIT"
] | 2,190 | e38d61e371179833c08888fd5a1ee444cf5bd875 | https://github.com/ruijieren98/DANet/tree/e38d61e371179833c08888fd5a1ee444cf5bd875 |
ValueFunction | import torch
import torch.nn as nn
import torch.nn.functional as F
class ValueFunction(nn.Module):
"""fully connected 200x200 hidden layers"""
def __init__(self, state_dim):
super(ValueFunction, self).__init__()
self.fc1 = nn.Linear(state_dim, 200)
self.fc2 = nn.Linear(200, 200)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | himanshusahni/task-biased-url | ValueFunction | false | 10,252 | [
"MIT"
] | 0 | 28e4ec318d46d84065b6e197fa9f4100bd4a4c34 | https://github.com/himanshusahni/task-biased-url/tree/28e4ec318d46d84065b6e197fa9f4100bd4a4c34 |
L0Loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
a... | sailfish009/torch-toolbox | L0Loss | false | 7,588 | [
"BSD-3-Clause"
] | 1 | 80dfc22c697b9f323e097de72af04f0e5435d7b4 | https://github.com/sailfish009/torch-toolbox/tree/80dfc22c697b9f323e097de72af04f0e5435d7b4 |
Context2AnswerAttention | import torch
import torch.nn as nn
import torch.multiprocessing
import torch.utils.data
import torch.nn.modules.loss
class Context2AnswerAttention(nn.Module):
def __init__(self, dim, hidden_size):
super(Context2AnswerAttention, self).__init__()
self.linear_sim = nn.Linear(dim, hidden_size, bias=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.... | cminusQAQ/graph4nlp | Context2AnswerAttention | false | 15,073 | [
"Apache-2.0"
] | 1,269 | d980e897131f1b9d3766750c06316d94749904fa | https://github.com/cminusQAQ/graph4nlp/tree/d980e897131f1b9d3766750c06316d94749904fa |
LT | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | Ilyabasharov/torch2trt | LT | false | 2,515 | [
"MIT"
] | 0 | 76bf298b3da408509665e23e2494922b131afb10 | https://github.com/Ilyabasharov/torch2trt/tree/76bf298b3da408509665e23e2494922b131afb10 |
ToRGB | # 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
import math
import torch.utils.data
from tor... | achrefjarray/ESRGANplus-master | ToRGB | false | 1,375 | [
"Apache-2.0"
] | 0 | ba470ec5c565a6dc8b48575b1e185ef6b796aec6 | https://github.com/achrefjarray/ESRGANplus-master/tree/ba470ec5c565a6dc8b48575b1e185ef6b796aec6 |
FSoftmaxTest | # 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 numpy as np
imp... | goldbattle/onnx2keras | FSoftmaxTest | false | 12,456 | [
"MIT"
] | 0 | dcf52041299ce4216552d1132ec86eb4debd5303 | https://github.com/goldbattle/onnx2keras/tree/dcf52041299ce4216552d1132ec86eb4debd5303 |
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.... | jinwoo1225/MichiGAN-HAiR | BasicBlock | false | 6,958 | [
"MIT"
] | 1 | dece2ad2e93de3a7c52b4a657ecc0f1a667ccc7e | https://github.com/jinwoo1225/MichiGAN-HAiR/tree/dece2ad2e93de3a7c52b4a657ecc0f1a667ccc7e |
TransformerLayer | # 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.... | William-Zhanng/Protein_affinity | TransformerLayer | false | 6,018 | [
"MIT"
] | 1 | 8abd12073b182274bf464ff23fd3be406c4e39ac | https://github.com/William-Zhanng/Protein_affinity/tree/8abd12073b182274bf464ff23fd3be406c4e39ac |
ExpandingBlock | import torch
from torch import nn
class ExpandingBlock(nn.Module):
def __init__(self, input_channels, use_bn=True):
super(ExpandingBlock, self).__init__()
self.conv1 = nn.ConvTranspose2d(input_channels, input_channels // 2,
kernel_size=3, stride=2, padding=1, output_padding=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
from torch._inductor.runtime.... | diegushko/CycleGAN | ExpandingBlock | false | 12,283 | [
"MIT"
] | 0 | 630d1cd00cef3f09f036d3c734d31c772cc0a786 | https://github.com/diegushko/CycleGAN/tree/630d1cd00cef3f09f036d3c734d31c772cc0a786 |
NextMinMinusLambdaBlock | import torch
import warnings
import torch.nn as nn
import torch.nn.functional as F
from torch import optim as optim
class LayerNorm(nn.Module):
""" LayerNorm that supports two data formats: channels_last (default) or channels_first.
The ordering of the dimensions in the inputs. channels_last corresponds to i... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | pgruening/ConvNeXt | NextMinMinusLambdaBlock | false | 12,928 | [
"MIT"
] | 0 | e9a1beaf312f3a724f0c21d098efbe7db872b049 | https://github.com/pgruening/ConvNeXt/tree/e9a1beaf312f3a724f0c21d098efbe7db872b049 |
GCN | from torch.nn import Module
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
from torch.nn.modules.module import Module
class GraphConvolution(Module):
"""
Simple GCN layer, similar to https://arxiv.org/abs/1609.02907
"""
def __in... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn import Module
i... | DAIZHENWEI/FastGCN_pytorch | GCN | false | 336 | [
"MIT"
] | 0 | 87efe350d5acbe517a0642e9862ac9676b55c053 | https://github.com/DAIZHENWEI/FastGCN_pytorch/tree/87efe350d5acbe517a0642e9862ac9676b55c053 |
AlexOutputBlock | # 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 ... | earhian/imgclsmob | AlexOutputBlock | false | 6,650 | [
"MIT"
] | 1 | c87c0942420876941868c016211073dec4392e4d | https://github.com/earhian/imgclsmob/tree/c87c0942420876941868c016211073dec4392e4d |
KeypointRCNNPredictorNoUpscale | import torch
import torch.nn as nn
import torch.quantization.quantize_fx
import torch.utils.data
class KeypointRCNNPredictorNoUpscale(nn.Module):
def __init__(self, in_channels, num_keypoints):
super(KeypointRCNNPredictorNoUpscale, self).__init__()
input_features = in_channels
deconv_kern... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.quantize_fx
import torch.utils.d... | JacobSzwejbka/d2go | KeypointRCNNPredictorNoUpscale | false | 628 | [
"Apache-2.0"
] | 0 | d86ecc92eb97f14fcd97d626185f61c6817351e4 | https://github.com/JacobSzwejbka/d2go/tree/d86ecc92eb97f14fcd97d626185f61c6817351e4 |
ClassAttention | # 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.... | alhamami/Object-Detection-And-Tracking | ClassAttention | false | 18,270 | [
"MIT"
] | 5 | a211a1dc103e812c539cd0ee16a2da4251943bed | https://github.com/alhamami/Object-Detection-And-Tracking/tree/a211a1dc103e812c539cd0ee16a2da4251943bed |
TransformerDecoderLayer | import math
import torch
import torch.nn as nn
class MultiHeadAttention(nn.Module):
"""
A model layer which implements a simplified version of masked attention, as
introduced by "Attention Is All You Need" (https://arxiv.org/abs/1706.03762).
Usage:
attn = MultiHeadAttention(embed_dim, num_heads... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Michellemingxuan/stanford_cs231n | TransformerDecoderLayer | false | 11,819 | [
"MIT"
] | 0 | b1d0a5a4a3b2fe5d685e34a4ebd810cbc56ec143 | https://github.com/Michellemingxuan/stanford_cs231n/tree/b1d0a5a4a3b2fe5d685e34a4ebd810cbc56ec143 |
DotProductSimilarity | # 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... | michiyasunaga/GreaseLM | DotProductSimilarity | false | 16,041 | [
"MIT"
] | 76 | 596aa5047841e3e97730f621a2e4576772733df2 | https://github.com/michiyasunaga/GreaseLM/tree/596aa5047841e3e97730f621a2e4576772733df2 |
GCN_encoder | import torch
import torch.nn as nn
import torch.nn.init as init
class GraphConv(nn.Module):
def __init__(self, input_dim, output_dim):
super(GraphConv, self).__init__()
self.input_dim = input_dim
self.output_dim = output_dim
self.weight = nn.Parameter(torch.FloatTensor(input_dim, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | Qin-Folks/graph-generation | GCN_encoder | false | 2,890 | [
"MIT"
] | 0 | afe1b697272b0e683b4551918de36f57f714e70b | https://github.com/Qin-Folks/graph-generation/tree/afe1b697272b0e683b4551918de36f57f714e70b |
SimpleAddMmModule | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleAddMmModule(torch.nn.Module):
def __init__(self, alpha=1, beta=1):
super(SimpleAddMmModule, self).__init__()
self.alpha = alpha
self.beta = beta
def forward(self, a, b, c):
return (a + a).addmm(b, 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
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C... | opti-mix/glow | SimpleAddMmModule | false | 7,383 | [
"Apache-2.0"
] | 1 | 4ba074df5da9822986a23a6679ab592c22660f6d | https://github.com/opti-mix/glow/tree/4ba074df5da9822986a23a6679ab592c22660f6d |
ConvReLUNorm | # 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.... | admariner/NeMo | ConvReLUNorm | false | 1,379 | [
"Apache-2.0"
] | 0 | e542d7f9063a40afa4119a3b94de4c2c636a37bb | https://github.com/admariner/NeMo/tree/e542d7f9063a40afa4119a3b94de4c2c636a37bb |
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
from torch import nn
assert_s... | akapoorx00/machinelearning-stuff | Model | false | 3,060 | [
"Apache-2.0"
] | 0 | 53184019b77d3387fd15b13d3bfa75529b8ed003 | https://github.com/akapoorx00/machinelearning-stuff/tree/53184019b77d3387fd15b13d3bfa75529b8ed003 |
SimpleConv | import torch
import torch.nn as nn
class SimpleConv(nn.Module):
def __init__(self, in_size):
super(SimpleConv, self).__init__()
self.conv = nn.Conv2d(in_size, 6, 3, padding='same')
self.relu = nn.ReLU()
def forward(self, x):
x = self.conv(x)
x = self.relu(x)
r... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | msc5/ml-tools | SimpleConv | false | 4,033 | [
"Apache-2.0"
] | 0 | 75ca504bdc0495e8a929ad73501b7de692b3089a | https://github.com/msc5/ml-tools/tree/75ca504bdc0495e8a929ad73501b7de692b3089a |
SelfAttention | from _paritybench_helpers import _mock_config
import math
import torch
import torch.nn as nn
from torch.nn import functional as F
class SelfAttention(nn.Module):
def __init__(self, config):
super().__init__()
assert config.n_embd % config.n_head == 0
self.qkv = nn.Linear(config.n_embd, co... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | evelynmitchell/rasp | SelfAttention | false | 6,665 | [
"MIT"
] | 1 | 9b33bbf911e6c4ff018c9883c39eb698c0abe803 | https://github.com/evelynmitchell/rasp/tree/9b33bbf911e6c4ff018c9883c39eb698c0abe803 |
MSELoss | # 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... | ahmad4633/mmfashion | MSELoss | false | 6,115 | [
"Apache-2.0"
] | 1 | ad2c911bf71bb95dce340a963e7f83c477a84824 | https://github.com/ahmad4633/mmfashion/tree/ad2c911bf71bb95dce340a963e7f83c477a84824 |
ProdAttention | # 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
... | AminJun/speech | ProdAttention | false | 13,260 | [
"Apache-2.0"
] | 642 | 95149ca3780d8590a36d8f1adeb8d6508a0ff1cc | https://github.com/AminJun/speech/tree/95149ca3780d8590a36d8f1adeb8d6508a0ff1cc |
SafeLog | # 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
... | Mrswolf/brainda | SafeLog | false | 8,565 | [
"MIT"
] | 24 | cbd2fa6334d9e6243324dbaf086be4eb4047e801 | https://github.com/Mrswolf/brainda/tree/cbd2fa6334d9e6243324dbaf086be4eb4047e801 |
GT | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | PogChamper/torch2trt | GT | false | 14,189 | [
"MIT"
] | 3,363 | 43b12627ec0de4d212efb6d02b07570205085ccc | https://github.com/PogChamper/torch2trt/tree/43b12627ec0de4d212efb6d02b07570205085ccc |
ScaledDotProductAttention | import torch
import numpy as np
from torch import nn
class ScaledDotProductAttention(nn.Module):
"""
Scaled dot-product attention
"""
def __init__(self, d_model, d_k, d_v, h):
"""
:param d_model: Output dimensionality of the model
:param d_k: Dimensionality of queries and keys... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | jmhessel/meshed-memory-transformer | ScaledDotProductAttention | false | 10,330 | [
"BSD-3-Clause"
] | 0 | b502da2522f2e25d602fba547ed6ebf7968857a9 | https://github.com/jmhessel/meshed-memory-transformer/tree/b502da2522f2e25d602fba547ed6ebf7968857a9 |
A2CActorDisc | # 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.... | iffiX/machin | A2CActorDisc | false | 15,589 | [
"MIT"
] | 287 | 7fa986b1bafdefff117d6ff73d14644a5488de9d | https://github.com/iffiX/machin/tree/7fa986b1bafdefff117d6ff73d14644a5488de9d |
JointsMSELoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
import torch.n... | Gerrystev/efficientnet-simple-baseline | JointsMSELoss | false | 11,444 | [
"MIT"
] | 0 | 03ae4da4e91825f73d5185d0d195dd141bd7c4f1 | https://github.com/Gerrystev/efficientnet-simple-baseline/tree/03ae4da4e91825f73d5185d0d195dd141bd7c4f1 |
xTanH | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride... | nayyarv/bayesnets | xTanH | false | 7,315 | [
"MIT"
] | 1 | 090abd1a0a91c2b9d6d57a182ee5be1f65a22e11 | https://github.com/nayyarv/bayesnets/tree/090abd1a0a91c2b9d6d57a182ee5be1f65a22e11 |
MinibatchStd | import torch
import torch.nn as nn
import torch.utils.tensorboard
class MinibatchStd(nn.Module):
"""
Adds the aveage std of each data point over a
slice of the minibatch to that slice as a new
feature map. This gives an output with one extra
channel.
Arguments:
group_size (int): Number... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.utils.tensorboard
assert_size_stride = torch... | andoleg/stylegan2_pytorch | MinibatchStd | false | 15,327 | [
"MIT"
] | 121 | 27a367d00d35742cf66587f1bd1b1263469a8101 | https://github.com/andoleg/stylegan2_pytorch/tree/27a367d00d35742cf66587f1bd1b1263469a8101 |
Attention | import torch
import torch.utils.data
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.utils import weight_norm
class FCNet(nn.Module):
def __init__(self, in_size, out_size, activate=None, drop=0.0):
super(FCNet, self).__init__()
self.lin = weight_norm(nn.Linear(in_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | zaynmi/semantic-equivalent-da-for-vqa | Attention | false | 16,802 | [
"MIT"
] | 298 | f121fb3e8fee8af5f1935a7526f19e0d884bd95b | https://github.com/zaynmi/semantic-equivalent-da-for-vqa/tree/f121fb3e8fee8af5f1935a7526f19e0d884bd95b |
TLU | import torch
from torch import nn
from torch.nn import Parameter
from torch.nn.parameter import Parameter
class TLU(nn.Module):
def __init__(self, num_features):
"""max(y, tau) = max(y - tau, 0) + tau = ReLU(y - tau) + tau"""
super(TLU, self).__init__()
self.num_features = num_features
... | 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 import Parameter
from torch.nn.parameter import Parame... | hfyer/NAIC2020_ReID_R1 | TLU | false | 6,808 | [
"Apache-2.0"
] | 1 | 240f0c9f65e482e6b0090f01d9f9e3373a337033 | https://github.com/hfyer/NAIC2020_ReID_R1/tree/240f0c9f65e482e6b0090f01d9f9e3373a337033 |
SmoothSoftmax | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | zsl24/voice-activity-detection | SmoothSoftmax | false | 16,823 | [
"MIT"
] | 74 | a034be23c6283121c6b72e778c6ff6711045cbe3 | https://github.com/zsl24/voice-activity-detection/tree/a034be23c6283121c6b72e778c6ff6711045cbe3 |
translatedSigmoid | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.gua... | MachineLearningLifeScience/What-is-a-meaningful-representation-of-protein-sequences | translatedSigmoid | false | 17,664 | [
"BSD-3-Clause"
] | 4 | 2c24db6ee8763b0b6098d7509cf3325647931c11 | https://github.com/MachineLearningLifeScience/What-is-a-meaningful-representation-of-protein-sequences/tree/2c24db6ee8763b0b6098d7509cf3325647931c11 |
Modified | # 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... | Karin-S/USYD-ELEC5307 | Modified | false | 9,222 | [
"Apache-2.0"
] | 0 | 83cb40adf0c15ee703a880fc7aba5c69b82a5434 | https://github.com/Karin-S/USYD-ELEC5307/tree/83cb40adf0c15ee703a880fc7aba5c69b82a5434 |
LinearConvExpansion | import torch
import numpy as np
import torch.nn as nn
class LinearConvExpansion(nn.Module):
"""expansion 1D -> 2D"""
def __init__(self, d_features, n_channel, n_depth):
super().__init__()
self.d_features = d_features
self.n_channel = n_channel
self.n_depth = n_depth
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
import numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | Jincheng-Sun/Kylearn-pytorch | LinearConvExpansion | false | 645 | [
"MIT"
] | 0 | e72f2ab45a3f4724e843a27bec37664d3612fdca | https://github.com/Jincheng-Sun/Kylearn-pytorch/tree/e72f2ab45a3f4724e843a27bec37664d3612fdca |
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.... | RPrenger/NeMo | MultiHeadAttention | false | 5,746 | [
"Apache-2.0"
] | 1 | e8912ca6e3321347272a6a7da18e052812fb2062 | https://github.com/RPrenger/NeMo/tree/e8912ca6e3321347272a6a7da18e052812fb2062 |
ConvertTCHWtoCTHW | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_... | XianyuanLiu/Transfer-Learning-Library | ConvertTCHWtoCTHW | false | 10,126 | [
"MIT"
] | 0 | 25f83f32437032df88ca6101ecd1f63ec7a0aa2c | https://github.com/XianyuanLiu/Transfer-Learning-Library/tree/25f83f32437032df88ca6101ecd1f63ec7a0aa2c |
SAGEAggregator | import torch
import torch.nn as nn
class SAGEAggregator(nn.Module):
def __init__(self, in_features, out_features, agg_method='mean', concat
=False, bias=False):
super().__init__()
self.in_features = in_features
self.out_features = out_features
self.concat = concat
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | EdisonLeeeee/Graphgallery | SAGEAggregator | false | 5,109 | [
"MIT"
] | 1 | 8ae9ef57d44f073d0ceaf3f33a3a998546f960a8 | https://github.com/EdisonLeeeee/Graphgallery/tree/8ae9ef57d44f073d0ceaf3f33a3a998546f960a8 |
Net | import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(1, 32, 5)
self.conv2 = nn.Conv2d(32, 64, 5)
self.conv3 = nn.Conv2d(64, 128, 5)
self.fc1 = nn.Linear(512, 512)
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
from torch._inductor.runtime.... | mmayers88/learn_pytorch | Net | false | 4,043 | [
"MIT"
] | 0 | 0dbc1aed24d869109feb23bfa6e970686cf485e3 | https://github.com/mmayers88/learn_pytorch/tree/0dbc1aed24d869109feb23bfa6e970686cf485e3 |
HingeMarginLoss | import torch
import torch.nn as nn
class HingeMarginLoss(nn.Module):
"""
计算hinge loss 接口
"""
def __init__(self):
super(HingeMarginLoss, self).__init__()
def forward(self, t, tr, delt=None, size_average=False):
"""
计算hingle loss
"""
if delt is None:
... | 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... | Aurelius84/SPWE | HingeMarginLoss | false | 16,936 | [
"MIT"
] | 9 | 5f9fc5495e879b5272c118271a69c5adad4ba260 | https://github.com/Aurelius84/SPWE/tree/5f9fc5495e879b5272c118271a69c5adad4ba260 |
ChannelPool | # 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... | Linus4world/mrs-gan | ChannelPool | false | 5,535 | [
"BSD-2-Clause"
] | 1 | 64669251584a7421cce3a5173983a2275dcb438a | https://github.com/Linus4world/mrs-gan/tree/64669251584a7421cce3a5173983a2275dcb438a |
Conv2d | # 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... | RQuispeC/pytorch-ACSCP | Conv2d | false | 8,698 | [
"MIT"
] | 25 | c83f08632012c2245250ff9c5140814461db575c | https://github.com/RQuispeC/pytorch-ACSCP/tree/c83f08632012c2245250ff9c5140814461db575c |
Upconv | # 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.functional as F
from torch.nn import Conv2d
from tor... | pc2005/MonoRec | Upconv | false | 12,863 | [
"MIT"
] | 0 | 6e1628eeef9987b1acce3e5e8bb6a6a324fc8d2c | https://github.com/pc2005/MonoRec/tree/6e1628eeef9987b1acce3e5e8bb6a6a324fc8d2c |
MinibatchStdDev | # 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 as th
assert_size_stride = torch._C._dynamo.guards.assert_size_str... | alexeyhorkin/ProGAN-PyTorch | MinibatchStdDev | false | 9,908 | [
"MIT"
] | 0 | 731ba596e9366c602a771a40b81957cd12386836 | https://github.com/alexeyhorkin/ProGAN-PyTorch/tree/731ba596e9366c602a771a40b81957cd12386836 |
SimpleReluModel | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.... | briancoutinho/glow | SimpleReluModel | false | 12,579 | [
"Apache-2.0"
] | 0 | 4c919d60b3c33296c4109aec8020a1733c98f5b5 | https://github.com/briancoutinho/glow/tree/4c919d60b3c33296c4109aec8020a1733c98f5b5 |
FusedLeakyReLU | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
def fused_leaky_relu(input, bias, negative_slope=0.2, scale=2 ** 0.5):
rest_dim = [1] * (input.ndim - bias.ndim - 1)
return F.leaky_relu(input + bias.view(1, bias.shape[0], *rest_dim),
negative_slope=negative_sl... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_strid... | HappyBelief/ContraD | FusedLeakyReLU | false | 13,747 | [
"MIT"
] | 168 | abb72562ddac8d8ab37fe9af6ac4c44c61e8ea0f | https://github.com/HappyBelief/ContraD/tree/abb72562ddac8d8ab37fe9af6ac4c44c61e8ea0f |
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