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 |
|---|---|---|---|---|---|---|---|---|---|---|
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 functools
import torch.nn.functional as F
import torch.nn as nn
assert_size_stride... | ChHanXiao/mmdetection | MSELoss | false | 9,154 | [
"Apache-2.0"
] | 0 | 324aa5a042857a9b57abe37385e1210709a20d02 | https://github.com/ChHanXiao/mmdetection/tree/324aa5a042857a9b57abe37385e1210709a20d02 |
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.... | D-hash-code/ffjord | BasicBlock | false | 11,367 | [
"MIT"
] | 0 | 3647ab35537a8bac3b4dc1e45a593819ac8e2c18 | https://github.com/D-hash-code/ffjord/tree/3647ab35537a8bac3b4dc1e45a593819ac8e2c18 |
PSNRLoss | import torch
def psnr(gt, pred, data_range=None, batch=True, reduce=True):
""" Compute the peak signal to noise ratio (psnr)
:param gt: gt image (torch.Tensor
:param pred: input image (torch.Tensor)
:param data_range: if None, estimated from gt
:return: (mean) psnr
"""
if batch:
ba... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
assert_size... | khammernik/sigmanet | PSNRLoss | false | 15,823 | [
"MIT"
] | 50 | 6eb8dbd1ee350bb9baee60eb254080f7d660bbc5 | https://github.com/khammernik/sigmanet/tree/6eb8dbd1ee350bb9baee60eb254080f7d660bbc5 |
Theta | # 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 torch.nn as nn
from typing import Tup... | Liuhong99/CST | Theta | false | 8,502 | [
"MIT"
] | 20 | f6653a4ee7968fa3ba875a182670636f648be783 | https://github.com/Liuhong99/CST/tree/f6653a4ee7968fa3ba875a182670636f648be783 |
TripletLoss | # 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.... | Luxios22/IDM | TripletLoss | false | 2,603 | [
"MIT"
] | 0 | 8d51103b7c252e6304e2a361976e16ed4b523944 | https://github.com/Luxios22/IDM/tree/8d51103b7c252e6304e2a361976e16ed4b523944 |
CCX_loss | import torch
import torch.utils.data
import torch.nn as nn
class CCX_loss(nn.Module):
def __init__(self, eps=1e-06, h=0.5):
super(CCX_loss, self).__init__()
self.eps = eps
self.h = h
def forward(self, x, y):
N, C, _H, _W = x.size()
y_mu = y.mean(3).mean(2).mean(0).res... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | qwopqwop200/Fast-Invertible-Rescaling-Net | CCX_loss | false | 7,538 | [
"MIT"
] | 1 | 871733f2eee7929d6b37c4d1d6a27347b39b67a9 | https://github.com/qwopqwop200/Fast-Invertible-Rescaling-Net/tree/871733f2eee7929d6b37c4d1d6a27347b39b67a9 |
Conv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | crazyofapple/bert | Conv | false | 3,362 | [
"Apache-2.0"
] | 0 | 09f6afffc064687f7ac85d847f082e1c8d1f3ffa | https://github.com/crazyofapple/bert/tree/09f6afffc064687f7ac85d847f082e1c8d1f3ffa |
MLP_model | import torch
import torch.nn as nn
import torch.nn.functional as F
class MLP_model(nn.Module):
"""Feedfoward neural network with 6 hidden layer"""
def __init__(self, in_size, out_size):
super().__init__()
self.linear1 = nn.Linear(in_size, 4096)
self.linear2 = nn.Linear(4096, 2048)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | WeihengXia0123/Machine_Learning_Service | MLP_model | false | 1,218 | [
"MIT"
] | 0 | 516d64ff780317ee96e18584001b77165ce6531c | https://github.com/WeihengXia0123/Machine_Learning_Service/tree/516d64ff780317ee96e18584001b77165ce6531c |
Self_Attn | import torch
import torch.utils.data
import torch.nn as nn
class Self_Attn(nn.Module):
""" Self attention Layer"""
def __init__(self, in_dim):
super(Self_Attn, self).__init__()
self.chanel_in = in_dim
self.query_conv = nn.Conv2d(in_channels=in_dim, out_channels=in_dim //
2... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | anonymous2022ijcai/RGSL | Self_Attn | false | 1,460 | [
"MIT"
] | 0 | 11c38ee50d50127c0f7c2a137bdb21ca5f7f3644 | https://github.com/anonymous2022ijcai/RGSL/tree/11c38ee50d50127c0f7c2a137bdb21ca5f7f3644 |
RNN | import torch
import torch.nn as nn
from torch.autograd import Variable
class RNN(nn.Module):
def __init__(self, input_size, hidden_size, output_size, all_categories,
n_categories, all_letters, n_letters):
super(RNN, self).__init__()
self.hidden_size = hidden_size
self.all_categori... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | tom-kuchler/vhive | RNN | false | 16,600 | [
"MIT"
] | 138 | ae1f2f5920e7607e9902ed1060bda62b56e332ac | https://github.com/tom-kuchler/vhive/tree/ae1f2f5920e7607e9902ed1060bda62b56e332ac |
LinearSQ | import math
import torch
from torch import Tensor
import torch.nn as nn
from torch.nn.parameter import Parameter
from torch.nn import functional as F
class LinearSQ(nn.Module):
__constants__ = ['in_features', 'out_features']
in_features: 'int'
out_features: 'int'
weight: 'Tensor'
def __init__(sel... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from torch import Tensor
import torch.nn as nn
from torch.nn.paramet... | June01/WFSAL-icmr21 | LinearSQ | false | 17,514 | [
"MIT"
] | 9 | 86fd6e9e34483ea17e088e4c1ee8f66edf3aecce | https://github.com/June01/WFSAL-icmr21/tree/86fd6e9e34483ea17e088e4c1ee8f66edf3aecce |
MultiLayeredConv1d | import torch
import torch.utils.data.distributed
import torch.utils.data
class MultiLayeredConv1d(torch.nn.Module):
"""Multi-layered conv1d for Transformer block.
This is a module of multi-leyered conv1d designed
to replace positionwise feed-forward network
in Transforner block, which is introduced 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
import torch.utils.data.distr... | MarkWuNLP/StreamingTransformer | MultiLayeredConv1d | false | 813 | [
"Apache-2.0"
] | 0 | df9bfe348608b7e55ef1ff70464070c0055ea799 | https://github.com/MarkWuNLP/StreamingTransformer/tree/df9bfe348608b7e55ef1ff70464070c0055ea799 |
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.... | ChantalMP/Graphormer | MultiHeadAttention | false | 8,934 | [
"MIT"
] | 0 | 5c384d0f2840afc88ee88aeb874f4b1f41d760bf | https://github.com/ChantalMP/Graphormer/tree/5c384d0f2840afc88ee88aeb874f4b1f41d760bf |
SmallMotionEncoder | import torch
import torch.nn as nn
import torch.nn.functional as F
class SmallMotionEncoder(nn.Module):
"""
Encodes motion features from the correlation levels of the pyramid
and the input flow estimate using convolution layers.
Parameters
----------
corr_radius : int
Correlation rad... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | NeelayS/ezflow | SmallMotionEncoder | false | 14,139 | [
"MIT"
] | 94 | b93a48c4adf5021f7eacbfc43220c7efa5ae55cd | https://github.com/NeelayS/ezflow/tree/b93a48c4adf5021f7eacbfc43220c7efa5ae55cd |
LayerNormGRUCell | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | faz1993/InnerEye-DeepLearning | LayerNormGRUCell | false | 15,339 | [
"MIT"
] | 402 | fb258d5c9a3ba18565b5a67e7ac1f00127d9ecb9 | https://github.com/faz1993/InnerEye-DeepLearning/tree/fb258d5c9a3ba18565b5a67e7ac1f00127d9ecb9 |
DynamicConv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn
assert_size_stride = torch._C._dynamo.guar... | naili-xing/singa-easy | DynamicConv2d | false | 12,812 | [
"Apache-2.0"
] | 0 | ed94cd8b6b77dc1e86c670000eae06d06f81926b | https://github.com/naili-xing/singa-easy/tree/ed94cd8b6b77dc1e86c670000eae06d06f81926b |
SimpleAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
class SimpleAttention(nn.Module):
def __init__(self, input_dim):
super(SimpleAttention, self).__init__()
self.input_dim = input_dim
self.scalar = nn.Linear(self.input_dim, 1, bias=False)
def forward(self, M, x=None):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | filkar/CASTLE | SimpleAttention | false | 3,499 | [
"MIT"
] | 0 | 128b316d24503875bcc298301c17b003e6d4599d | https://github.com/filkar/CASTLE/tree/128b316d24503875bcc298301c17b003e6d4599d |
ComplexConv2d | # 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... | jonashaag/PhoneFortifiedPerceptualLoss | ComplexConv2d | false | 3,768 | [
"MIT"
] | 0 | 1dabdd4203f59c2d1bfe22bffc4c63b204aa50bd | https://github.com/jonashaag/PhoneFortifiedPerceptualLoss/tree/1dabdd4203f59c2d1bfe22bffc4c63b204aa50bd |
SwaVLoss | import torch
import torch.nn.functional as F
from typing import List
import torch.nn as nn
@torch.no_grad()
def sinkhorn(out: 'torch.Tensor', iterations: 'int'=3, epsilon: 'float'=0.05):
"""Distributed sinkhorn algorithm.
As outlined in [0] and implemented in [1].
[0]: SwaV, 2020, https://arxiv.org/abs/... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn.functi... | jianzhnie/self_supervised | SwaVLoss | false | 7,051 | [
"Apache-2.0"
] | 1 | d1e0f31ab032150ab0ad007c1e19773135a5fb79 | https://github.com/jianzhnie/self_supervised/tree/d1e0f31ab032150ab0ad007c1e19773135a5fb79 |
MLP | # 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
assert_size_stride = torch._C... | linhthi/tgn | MLP | false | 12,713 | [
"Apache-2.0"
] | 0 | bb83f82d89aba07d07da3b173803fb0df32ebbbc | https://github.com/linhthi/tgn/tree/bb83f82d89aba07d07da3b173803fb0df32ebbbc |
DiceLoss | import torch
import torch.nn as nn
class DiceLoss(nn.Module):
def __init__(self):
super(DiceLoss, self).__init__()
def forward(self, input, target, logits=True):
if logits:
input = nn.Sigmoid()(input)
N = target.size(0)
smooth = 1
input_flat = input.view(N... | 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... | LanXiangExcavator/python-classifier-2021 | DiceLoss | false | 11,622 | [
"BSD-2-Clause"
] | 0 | 851079e76db8e5070132d1120dba941967e1245b | https://github.com/LanXiangExcavator/python-classifier-2021/tree/851079e76db8e5070132d1120dba941967e1245b |
GaussianLayer | import torch
import torch.nn as nn
class GaussianLayer(nn.Module):
def __init__(self, input_dim, output_dim):
super(GaussianLayer, self).__init__()
self.z_mu = torch.nn.Linear(input_dim, output_dim)
self.z_sigma = torch.nn.Linear(input_dim, output_dim)
def forward(self, x):
m... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | Junyoungpark/2021-lg-AI-camp | GaussianLayer | false | 17,527 | [
"MIT"
] | 4 | 3c0e5dd689e8e3dd61cc80243ad90cab951c06de | https://github.com/Junyoungpark/2021-lg-AI-camp/tree/3c0e5dd689e8e3dd61cc80243ad90cab951c06de |
MlpLite | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | likelyzhao/dino | MlpLite | false | 12,815 | [
"Apache-2.0"
] | 0 | ad019889b0e4c103f0471d085f79bba42c817d1b | https://github.com/likelyzhao/dino/tree/ad019889b0e4c103f0471d085f79bba42c817d1b |
JaccardLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | kevinkwshin/kaggle-pneumothorax | JaccardLoss | false | 15,820 | [
"MIT"
] | 74 | 24b91a9425097023f0cc7781a9380cb247babe22 | https://github.com/kevinkwshin/kaggle-pneumothorax/tree/24b91a9425097023f0cc7781a9380cb247babe22 |
RelativeMargin | import torch
import torch.nn as nn
class RelativeMargin(nn.Module):
def __init__(self):
super(RelativeMargin, self).__init__()
def forward(self, x1, x2, y1, y2, t, reduce=True):
if reduce:
loss = torch.mean(torch.clamp(torch.abs(y1 - y2) - t * (x1 - x2
), 0.0))
... | 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
... | UKPLab/ijcai2019-relis | RelativeMargin | false | 18,025 | [
"MIT"
] | 5 | 8a40762dcfa90c075a4f6591cbdceb468026ef17 | https://github.com/UKPLab/ijcai2019-relis/tree/8a40762dcfa90c075a4f6591cbdceb468026ef17 |
FactorizationMachine | from torch.nn import Module
import torch
from torch import FloatTensor
from torch.nn import Parameter
class SecondOrderInteraction(Module):
"""
Factorized parameters for the Second Order Interactions
Parameters
----------
n_features: int
Length of the input vector.
n_factors: int, opt... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import Module
from torch import FloatTensor
from torch.nn import P... | DanielMorales9/FactorizationPyTorch | FactorizationMachine | false | 17,198 | [
"MIT"
] | 4 | 50f0644fdb4a903550fb3f1ba78fb9fb8649ceb1 | https://github.com/DanielMorales9/FactorizationPyTorch/tree/50f0644fdb4a903550fb3f1ba78fb9fb8649ceb1 |
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.... | IanYHWu/tied-representation-learning | MultiHeadAttention | false | 5,331 | [
"MIT"
] | 1 | bda9814dc40cf552f7bdd2ade78f5e2958a7ea83 | https://github.com/IanYHWu/tied-representation-learning/tree/bda9814dc40cf552f7bdd2ade78f5e2958a7ea83 |
Router | # 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.... | techthiyanes/annotated_deep_learning_paper_implementations | Router | false | 16,649 | [
"MIT"
] | 3,714 | 8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 | https://github.com/techthiyanes/annotated_deep_learning_paper_implementations/tree/8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 |
GeM | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Parameter
from torch.nn.parameter import Parameter
def gem(x, p=3, eps=1e-06):
return F.avg_pool2d(x.clamp(min=eps).pow(p), (x.size(-2), x.size(-1))).pow(
1.0 / p)
class GeM(nn.Module):
def __init__(self, p=3.0,... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import... | beesk135/ReID-Survey | GeM | false | 1,532 | [
"MIT"
] | 0 | d1467c0ce5d3ca78640196360a05df9ff9f9f42a | https://github.com/beesk135/ReID-Survey/tree/d1467c0ce5d3ca78640196360a05df9ff9f9f42a |
Dunet_2levels | import torch
import torch.nn as nn
class Unet_2levels(nn.Module):
def __init__(self):
super().__init__()
self.relu = nn.ReLU()
self.sigmoid = nn.Sigmoid()
self.upsample = nn.Upsample(scale_factor=2, mode='bilinear',
align_corners=True)
self.maxpool = nn.MaxPool... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | AbdulMuqadim2001/dvae-refiner | Dunet_2levels | false | 7,700 | [
"MIT"
] | 27 | c1ff46f91b28e613a3b7b157f8fd97ddf43e6fb2 | https://github.com/AbdulMuqadim2001/dvae-refiner/tree/c1ff46f91b28e613a3b7b157f8fd97ddf43e6fb2 |
NLinear | import torch
from torch import Tensor
import torch.nn as nn
from torch.nn import Parameter
class NLinear(nn.Module):
def __init__(self, n: 'int', d_in: 'int', d_out: 'int', bias: 'bool'=True
) ->None:
super().__init__()
self.weight = Parameter(Tensor(n, d_in, d_out))
self.bias = 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 import Tensor
import torch.nn as nn
from torch.nn import Parameter
assert_size_stride = torch._C._dynamo.guards.assert_size_strid... | Yura52/tabular-dl-num-embeddings | NLinear | false | 14,713 | [
"MIT"
] | 57 | e49e95c52f829ad0ab7d653e0776c2a84c03e261 | https://github.com/Yura52/tabular-dl-num-embeddings/tree/e49e95c52f829ad0ab7d653e0776c2a84c03e261 |
LR_PAD | import torch
import torch.nn as nn
def lr_pad(x, padding=1):
""" Pad left/right-most to each other instead of zero padding """
return torch.cat([x[..., -padding:], x, x[..., :padding]], dim=3)
class LR_PAD(nn.Module):
""" Pad left/right-most to each other instead of zero padding """
def __init__(se... | 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... | ekbanasolutions/HorizonNet | LR_PAD | false | 15,286 | [
"MIT"
] | 254 | 4eff713f8d446c53c479d86b4d06af166b724a74 | https://github.com/ekbanasolutions/HorizonNet/tree/4eff713f8d446c53c479d86b4d06af166b724a74 |
DeepLiftRegressor | # 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_... | lzamparo/SeqDemote | DeepLiftRegressor | false | 7,155 | [
"MIT"
] | 1 | 3eaf18e88c9dc6a3d1a69444ecdba9f9b5d9682a | https://github.com/lzamparo/SeqDemote/tree/3eaf18e88c9dc6a3d1a69444ecdba9f9b5d9682a |
LeftSVDLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
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 |
VGGBase | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torchvision
from torch... | mosevg/ssd | VGGBase | false | 11,144 | [
"MIT"
] | 0 | 8fd9f6cc376c027427531bcf475188ae43c4b2d6 | https://github.com/mosevg/ssd/tree/8fd9f6cc376c027427531bcf475188ae43c4b2d6 |
Conv2dSame | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
from torch.nn import functional as F
import to... | Fanzhongjie/ARFE | Conv2dSame | false | 466 | [
"Apache-2.0"
] | 0 | 4b96b8c5bc0895d3d30acec2a490f81a860fe860 | https://github.com/Fanzhongjie/ARFE/tree/4b96b8c5bc0895d3d30acec2a490f81a860fe860 |
GridReduction2 | # 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 | GridReduction2 | false | 17,400 | [
"WTFPL"
] | 10 | 11077704cc0bc9a42fc4b94da60b57d31ff0f65c | https://github.com/Hiroaki-Ozaki/modelib-classification/tree/11077704cc0bc9a42fc4b94da60b57d31ff0f65c |
WeightedL1 | import torch
import torch.nn as nn
class WeightedL1(nn.Module):
def __init__(self):
super(WeightedL1, self).__init__()
def forward(self, x, target, w):
return (w * torch.abs(x - target)).mean()
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4]), torch.rand(
... | 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
... | acrosson/dl | WeightedL1 | false | 1,366 | [
"MIT"
] | 0 | 94e68533b38f53f09e9bef460ba96fa389fc8eb4 | https://github.com/acrosson/dl/tree/94e68533b38f53f09e9bef460ba96fa389fc8eb4 |
BERTIntermediate | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import ... | DAQuestionAnswering/Bert-n-Pals | BERTIntermediate | false | 6,896 | [
"MIT"
] | 1 | d5a288b9ac62259e70c249635108ba3906e19f00 | https://github.com/DAQuestionAnswering/Bert-n-Pals/tree/d5a288b9ac62259e70c249635108ba3906e19f00 |
BCEDiceLoss | import torch
from typing import *
import torch.nn as nn
def dice_coeff(input, target, smooth=1.0):
input_flat = input.view(-1)
target_flat = target.view(-1)
intersection = (input_flat * target_flat).sum()
return (2.0 * intersection + smooth) / (input_flat.sum() + target_flat.
sum() + smooth)
... | 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 typing... | abbiyanaila/torchwisdom | BCEDiceLoss | false | 6,050 | [
"MIT"
] | 1 | 56dc95ebca3f6861c7009cb4fa0c034e260236b1 | https://github.com/abbiyanaila/torchwisdom/tree/56dc95ebca3f6861c7009cb4fa0c034e260236b1 |
MarginCosineProduct | import torch
import torch.nn as nn
from torch.nn import Parameter
import torch.utils.data
import torch.optim
def cosine_sim(x1, x2, dim=1, eps=1e-08):
ip = torch.mm(x1, x2.t())
w1 = torch.norm(x1, 2, dim)
w2 = torch.norm(x2, 2, dim)
return ip / torch.ger(w1, w2).clamp(min=eps)
class MarginCosineProd... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | lindsey98/CosFace_pytorch | MarginCosineProduct | false | 10,397 | [
"MIT"
] | 0 | 39bddf763e06c7ccd21fbf45d0c7f1f4a9d8d24d | https://github.com/lindsey98/CosFace_pytorch/tree/39bddf763e06c7ccd21fbf45d0c7f1f4a9d8d24d |
Log_Loss | import torch
import torch.utils.data
import torch.nn as nn
import torch.nn.parallel
class Log_Loss(nn.Module):
def __init__(self):
super(Log_Loss, self).__init__()
def forward(self, ytrue, ypred):
delta = ypred - ytrue
return torch.mean(torch.log(torch.cosh(delta)))
def get_inputs(... | 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... | YanLu-nyu/transferlearning | Log_Loss | false | 14,618 | [
"MIT"
] | 9,657 | 037806c6eb8b0c12aefbfbf3e35cbf893093cff9 | https://github.com/YanLu-nyu/transferlearning/tree/037806c6eb8b0c12aefbfbf3e35cbf893093cff9 |
CharbonnierLoss | import functools
import torch
from torch.nn import functional as F
import torch.nn as nn
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
from torch.... | Jason-Khan/mmediting | CharbonnierLoss | false | 617 | [
"Apache-2.0"
] | 0 | d187f95a675dff3eb975a575bd9278d643b5b645 | https://github.com/Jason-Khan/mmediting/tree/d187f95a675dff3eb975a575bd9278d643b5b645 |
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... | Hsintien-Ng/idinvert_pytorch-reproduced | LastBlock | false | 8,257 | [
"MIT"
] | 20 | cf3302510573138cf16202add06feae7c93624ea | https://github.com/Hsintien-Ng/idinvert_pytorch-reproduced/tree/cf3302510573138cf16202add06feae7c93624ea |
GlobalAttention | # 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.... | NaomiatLibrary/OpenNMT-kpg-release | GlobalAttention | false | 884 | [
"MIT"
] | 0 | 1da3468d7dad22529a77f3526abf9b373bd3dc4c | https://github.com/NaomiatLibrary/OpenNMT-kpg-release/tree/1da3468d7dad22529a77f3526abf9b373bd3dc4c |
PositionwiseFeedForward | # 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... | ArrowLuo/GRACE | PositionwiseFeedForward | false | 7,748 | [
"Apache-2.0"
] | 17 | f27b500ba905685c03eee6d91d87adc9ef78b4d1 | https://github.com/ArrowLuo/GRACE/tree/f27b500ba905685c03eee6d91d87adc9ef78b4d1 |
SimpleCNNContainerConvBlocks | # 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_... | Propaler/FedMA | SimpleCNNContainerConvBlocks | false | 5,725 | [
"MIT"
] | 1 | e235d971e192fb0e93abd4ad37ac603552b6484c | https://github.com/Propaler/FedMA/tree/e235d971e192fb0e93abd4ad37ac603552b6484c |
GCNModelVAE | from torch.nn import Module
import torch
import torch.nn.functional as F
from torch.nn.modules.module import Module
from torch.nn.parameter import Parameter
import torch.nn as nn
import torch.nn.modules.loss
class GraphConvolution(Module):
"""
Simple GCN layer, similar to https://arxiv.org/abs/1609.02907
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | chundiliu/random_rewrite | GCNModelVAE | false | 1,713 | [
"MIT"
] | 0 | fd106642da82b0ad42b8b0fa405147b321d67cbb | https://github.com/chundiliu/random_rewrite/tree/fd106642da82b0ad42b8b0fa405147b321d67cbb |
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
import math
import torch.utils.data
import torch
import torch.nn as nn
import to... | a11isonliu/contrastive-unpaired-translation | ToRGB | false | 9,858 | [
"BSD-3-Clause"
] | 0 | 67651ed9877cae121d9398f46094ce8dbc678802 | https://github.com/a11isonliu/contrastive-unpaired-translation/tree/67651ed9877cae121d9398f46094ce8dbc678802 |
MLPNetwork | import torch
import torch.nn.functional as F
import torch.nn as nn
class MLPNetwork(nn.Module):
"""
MLP network (can be used as value or policy)
"""
def __init__(self, input_dim, out_dim, hidden_dim=64, nonlin=F.relu,
constrain_out=False, norm_in=False, discrete_action=True):
"""
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn.functional as... | Aks-Dmv/maddpg-pytorch | MLPNetwork | false | 4,815 | [
"MIT"
] | 1 | 8afe2448875824cf5aee69c5d0314a3e00777b6f | https://github.com/Aks-Dmv/maddpg-pytorch/tree/8afe2448875824cf5aee69c5d0314a3e00777b6f |
CombinedPooling | import torch
import torch.optim
import torch.utils.data
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data.distributed
class CombinedPooling(nn.Module):
def __init__(self):
super().__init__()
self.max_pooling = nn.AdaptiveMaxPool2d(1)
self.avg_pooling = nn.AdaptiveAvgP... | 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.optim
import torch.utils.data
import torch.nn as nn
import torch.nn.parallel... | VisualComputingInstitute/CROWDBOT_perception | CombinedPooling | false | 5,938 | [
"MIT"
] | 1 | df98f3f658c39fb3fa4ac0456f1214f7918009f6 | https://github.com/VisualComputingInstitute/CROWDBOT_perception/tree/df98f3f658c39fb3fa4ac0456f1214f7918009f6 |
UpsamplerModel | import torch
import numpy as np
from torch import nn
class UpsamplerModel(nn.Module):
def __init__(self, output_shape, factor):
assert output_shape[0] % factor == 0
assert output_shape[1] % factor == 0
super(UpsamplerModel, self).__init__()
self.output_shape = output_shape
... | 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 numpy as np
from torch import nn
assert_size_stride = torch._C._dynamo.guards.asse... | GuYuanjie/Deep-Retinex-fusion | UpsamplerModel | false | 17,355 | [
"MIT"
] | 5 | ffa2a1689fd512c8820fd87cbf665c09bcb142b4 | https://github.com/GuYuanjie/Deep-Retinex-fusion/tree/ffa2a1689fd512c8820fd87cbf665c09bcb142b4 |
IOU | import torch
class IOU(torch.nn.Module):
def __init__(self):
super(IOU, self).__init__()
def _iou(self, pred, target):
pred = torch.sigmoid(pred)
inter = (pred * target).sum(dim=(2, 3))
union = (pred + target).sum(dim=(2, 3)) - inter
iou = 1 - inter / union
re... | 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... | Mhaiyang/CVPR2021_PFNet | IOU | false | 8,559 | [
"BSD-3-Clause"
] | 24 | 2c4cab0730e6a0619fad79092f0b34f71c3b56c4 | https://github.com/Mhaiyang/CVPR2021_PFNet/tree/2c4cab0730e6a0619fad79092f0b34f71c3b56c4 |
h_swish | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guard... | Ghaust/SSD | h_swish | false | 9,125 | [
"MIT"
] | 0 | 2bf14a48795d20ad2177f622e84d62b3ff81183f | https://github.com/Ghaust/SSD/tree/2bf14a48795d20ad2177f622e84d62b3ff81183f |
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_... | BatFresh/Resoure_variation | Net | false | 8,872 | [
"MIT"
] | 0 | a55d182b7bdd2b65d7ad10c9f8cfcb45436ad291 | https://github.com/BatFresh/Resoure_variation/tree/a55d182b7bdd2b65d7ad10c9f8cfcb45436ad291 |
Sine | # 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... | brandstetter-johannes/ocp | Sine | false | 9,950 | [
"MIT",
"BSD-3-Clause"
] | 0 | 69cc90e6bed8aa09222cd77b926d7a34e96302ed | https://github.com/brandstetter-johannes/ocp/tree/69cc90e6bed8aa09222cd77b926d7a34e96302ed |
DownsampleA | # 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... | hamedomidvar/associativeconv | DownsampleA | false | 6,772 | [
"MIT"
] | 1 | 9930915abd3625871354df676865fc44eb92abf3 | https://github.com/hamedomidvar/associativeconv/tree/9930915abd3625871354df676865fc44eb92abf3 |
group | import torch
import torch.utils.data
import torch.nn as nn
import torch.nn.parallel
import torch.optim
class mfm(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size=3, stride=1,
padding=1, type=1):
super(mfm, self).__init__()
self.out_channels = out_channels
if 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.utils.data
impor... | ananiask8/FFWM | group | false | 3,134 | [
"MIT"
] | 0 | 117f593783da67da9dc910a751910760497ef37f | https://github.com/ananiask8/FFWM/tree/117f593783da67da9dc910a751910760497ef37f |
TransformerDecoderLayer | import torch
from torch import nn
import torch.nn.functional as F
def _get_activation_fn(activation):
if activation == 'relu':
return F.relu
raise RuntimeError('activation shud be relu, not {}'.format(activation))
class TransformerDecoderLayer(nn.Module):
def __init__(self, d_model, nhead, 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.... | salmon7ish/Video-Captioning | TransformerDecoderLayer | false | 4,393 | [
"MIT"
] | 0 | 08359b1824195a7f5eac5b58982efd19ebc6db01 | https://github.com/salmon7ish/Video-Captioning/tree/08359b1824195a7f5eac5b58982efd19ebc6db01 |
CEL | import torch
from torch import nn
class CEL(nn.Module):
def __init__(self):
super(CEL, self).__init__()
None
self.eps = 1e-06
def forward(self, pred, target):
pred = pred.sigmoid()
intersection = pred * target
numerator = (pred - intersection).sum() + (target ... | 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... | Farzanehkaji/MINet | CEL | false | 17,265 | [
"MIT"
] | 9 | cc2852cb2b3b20208f5edf38ec6952363a9b04a7 | https://github.com/Farzanehkaji/MINet/tree/cc2852cb2b3b20208f5edf38ec6952363a9b04a7 |
UpsamplingBilinear | import torch
import torch.nn as nn
from torch.quantization import QuantStub
from torch.quantization import DeQuantStub
class UpsamplingBilinear(nn.Module):
def __init__(self):
super().__init__()
self.quant = QuantStub()
self.dequant = DeQuantStub()
def forward(self, x):
x = s... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from torch.quantization import QuantStub
from torch.quantization im... | cli99/tvm | UpsamplingBilinear | false | 6,462 | [
"Apache-2.0"
] | 1 | 6c6e873a1325a32418108daad6e38f3df8c37660 | https://github.com/cli99/tvm/tree/6c6e873a1325a32418108daad6e38f3df8c37660 |
CharbonnierLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import functools
import torc... | cyysc1998/EDVRDarts | CharbonnierLoss | false | 6,513 | [
"MIT"
] | 1 | 201badbc8c6469b519647a8869c3782ebe1176cf | https://github.com/cyysc1998/EDVRDarts/tree/201badbc8c6469b519647a8869c3782ebe1176cf |
MultiHeadedAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | howardchenhd/Transformer-pytorch | MultiHeadedAttention | false | 6,824 | [
"MIT"
] | 1 | ae71ed5767272feb7e717be6d5bfce46f80ec57a | https://github.com/howardchenhd/Transformer-pytorch/tree/ae71ed5767272feb7e717be6d5bfce46f80ec57a |
GAT | import torch
import torch.nn as nn
import torch.nn.functional as F
class GraphAttentionLayer(nn.Module):
def __init__(self, in_features, out_features, dropout, alpha, concat=True):
super(GraphAttentionLayer, self).__init__()
self.dropout = dropout
self.in_features = in_features
se... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | a101269/Chinese_Semantic_Dependency_Parser_with_knowledge | GAT | false | 6,054 | [
"MIT"
] | 1 | ca9998045c7789bc3ea5ad6a8ce7fe0af8308669 | https://github.com/a101269/Chinese_Semantic_Dependency_Parser_with_knowledge/tree/ca9998045c7789bc3ea5ad6a8ce7fe0af8308669 |
Upsampler | import math
import torch
from torchvision.transforms import *
class ConvBlock(torch.nn.Module):
def __init__(self, input_size, output_size, kernel_size=3, stride=1,
padding=1, bias=True, activation='prelu', norm=None):
super(ConvBlock, self).__init__()
self.conv = torch.nn.Conv2d(input_si... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from torchvision.transforms import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch.... | Haabibi/RBPN-PyTorch | Upsampler | false | 5,257 | [
"MIT"
] | 1 | 0b04420b384fcc8f78a7b9afeca179fa6c0332c2 | https://github.com/Haabibi/RBPN-PyTorch/tree/0b04420b384fcc8f78a7b9afeca179fa6c0332c2 |
NoiseInjection | # 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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | ArashVahabpour/encoder4editing-contrastive | NoiseInjection | false | 13,271 | [
"MIT"
] | 1,051 | 1b91afe1693e01a41118e1ce2451b7d14bec51f4 | https://github.com/ArashVahabpour/encoder4editing-contrastive/tree/1b91afe1693e01a41118e1ce2451b7d14bec51f4 |
Perplexity | # 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... | cesarali/Tyche | Perplexity | false | 1,651 | [
"MIT"
] | 0 | d892df9e0b982f538ae38221ff5848f6d726a4fb | https://github.com/cesarali/Tyche/tree/d892df9e0b982f538ae38221ff5848f6d726a4fb |
Critic | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | sofya-pugach/spot_mini_mini | Critic | false | 16,485 | [
"MIT"
] | 323 | 42770145e91ed2625ccc7e4f4d7016ce14a61464 | https://github.com/sofya-pugach/spot_mini_mini/tree/42770145e91ed2625ccc7e4f4d7016ce14a61464 |
Prototypes | import torch
import torch.nn as nn
from torch.nn import functional as F
class Prototypes(nn.Module):
def __init__(self, fdim, num_classes, temp=0.05):
super().__init__()
self.prototypes = nn.Linear(fdim, num_classes, bias=False)
self.temp = temp
def forward(self, x):
x = F.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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | pmirallesr/Dassl.pytorch | Prototypes | false | 4,126 | [
"MIT"
] | 0 | ec41f816bb60a9af94c9b055c500f0e2e404cfc6 | https://github.com/pmirallesr/Dassl.pytorch/tree/ec41f816bb60a9af94c9b055c500f0e2e404cfc6 |
SPPModule | # 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... | ShuangXieIrene/ssds.pytorch | SPPModule | false | 14,421 | [
"MIT"
] | 661 | b5ec682a42c923afe964205b21448e9f141d55bc | https://github.com/ShuangXieIrene/ssds.pytorch/tree/b5ec682a42c923afe964205b21448e9f141d55bc |
HyperConv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
as... | D-hash-code/ffjord | HyperConv2d | false | 11,371 | [
"MIT"
] | 0 | 3647ab35537a8bac3b4dc1e45a593819ac8e2c18 | https://github.com/D-hash-code/ffjord/tree/3647ab35537a8bac3b4dc1e45a593819ac8e2c18 |
img_encoder | import torch
import torch.nn as nn
import torch.nn.functional as F
class resnet_block(nn.Module):
def __init__(self, dim_in, dim_out):
super(resnet_block, self).__init__()
self.dim_in = dim_in
self.dim_out = dim_out
if self.dim_in == self.dim_out:
self.conv_1 = nn.Conv... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.functional as F
assert_size_stride = torch... | luixiao1223/BSP-NET-pytorch | img_encoder | false | 3,976 | [
"MIT"
] | 0 | f871c8ce6a9d52ac922e110702c47cd1c89d0a73 | https://github.com/luixiao1223/BSP-NET-pytorch/tree/f871c8ce6a9d52ac922e110702c47cd1c89d0a73 |
ScaleExp | # 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
assert_size_stride = torch._C._dynamo.guards.assert... | Cogito2012/OpenTAL | ScaleExp | false | 7,892 | [
"BSD-3-Clause"
] | 16 | a7ab938a52b3fb82163eb1ba5403888359eb7e6a | https://github.com/Cogito2012/OpenTAL/tree/a7ab938a52b3fb82163eb1ba5403888359eb7e6a |
T5DenseReluDense | # 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 ... | Hzfinfdu/Black-Box-Tuning | T5DenseReluDense | false | 4,073 | [
"MIT"
] | 0 | 64eb5505875dc1b242c6f0a2a2f07e4000c24cb4 | https://github.com/Hzfinfdu/Black-Box-Tuning/tree/64eb5505875dc1b242c6f0a2a2f07e4000c24cb4 |
GrayscaleLoss | import torch
from torch import nn
class GrayscaleLayer(nn.Module):
def __init__(self):
super(GrayscaleLayer, self).__init__()
def forward(self, x):
return torch.mean(x, 1, keepdim=True)
class GrayscaleLoss(nn.Module):
def __init__(self):
super(GrayscaleLoss, self).__init__()
... | 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... | GuYuanjie/Deep-Retinex-fusion | GrayscaleLoss | false | 17,342 | [
"MIT"
] | 5 | ffa2a1689fd512c8820fd87cbf665c09bcb142b4 | https://github.com/GuYuanjie/Deep-Retinex-fusion/tree/ffa2a1689fd512c8820fd87cbf665c09bcb142b4 |
ISAB | # 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.... | OpenXAIProject/dac | ISAB | false | 8,704 | [
"MIT"
] | 17 | 652776e21b56dcb68839363bb077d5c5ea28d81e | https://github.com/OpenXAIProject/dac/tree/652776e21b56dcb68839363bb077d5c5ea28d81e |
GumbelSoftmaxLayer | import torch
import torch.nn as nn
from torch.distributions import RelaxedOneHotCategorical
import torch.nn.parallel
import torch.utils.data
import torch.distributions
def gumbel_softmax_sample(logits: 'torch.Tensor', temperature: 'float'=1.0,
training: 'bool'=True, straight_through: 'bool'=False):
size = log... | 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 torch.distributions import RelaxedOneHotCategorical
import torch.nn.parallel
import torch.utils.data
import torch... | Shawn-Guo-CN/EGG | GumbelSoftmaxLayer | false | 2,876 | [
"MIT"
] | 0 | 0a5b258108e2cd1c873d7f67e8c92551bb3d809c | https://github.com/Shawn-Guo-CN/EGG/tree/0a5b258108e2cd1c873d7f67e8c92551bb3d809c |
FiLMLayer | # 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.... | HexagonPrime/pixel-nerf | FiLMLayer | false | 2,419 | [
"BSD-2-Clause"
] | 0 | 298aa7a3451c01e6f19f73f0c756672d3de54bf9 | https://github.com/HexagonPrime/pixel-nerf/tree/298aa7a3451c01e6f19f73f0c756672d3de54bf9 |
DiffLoss | import torch
import torch.nn as nn
import torch.utils.checkpoint
class DiffLoss(nn.Module):
def __init__(self):
super(DiffLoss, self).__init__()
def forward(self, input1, input2):
batch_size = input1.size(0)
input1 = input1.view(batch_size, -1)
input2 = input2.view(batch_size... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | Wang-Chuanyu/MMSA | DiffLoss | false | 5,948 | [
"MIT"
] | 1 | 2a720530c369e68656102287edb651780e827135 | https://github.com/Wang-Chuanyu/MMSA/tree/2a720530c369e68656102287edb651780e827135 |
RealConv2d | # 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... | JamesLiao714/FullSubNet | RealConv2d | false | 607 | [
"MIT"
] | 0 | dad740bac35b5d7544c97740ae59101455acdc40 | https://github.com/JamesLiao714/FullSubNet/tree/dad740bac35b5d7544c97740ae59101455acdc40 |
AttentionUnit | # 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.... | ankur6ue/aster-ocr | AttentionUnit | false | 1,455 | [
"MIT"
] | 0 | c4503bb19c843d519a36f0e5b8bebd6809800e04 | https://github.com/ankur6ue/aster-ocr/tree/c4503bb19c843d519a36f0e5b8bebd6809800e04 |
HardtanhBoundToPOTNet | import torch
from torch.nn import Conv2d
from torch.nn import Hardtanh
from torch.nn.functional import relu
from torch.nn.functional import hardtanh
import torch.nn.functional
class HardtanhBoundToPOTNet(torch.nn.Module):
def __init__(self):
super(HardtanhBoundToPOTNet, self).__init__()
self.conv... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 Conv2d
f... | isabella232/model_optimization | HardtanhBoundToPOTNet | false | 10,221 | [
"Apache-2.0"
] | 0 | 074d1dfd8b4d18e57c6186c0ec5e49eb17a0fc7a | https://github.com/isabella232/model_optimization/tree/074d1dfd8b4d18e57c6186c0ec5e49eb17a0fc7a |
EDMLoss | import torch
import torch.nn as nn
import torch.optim
class EDMLoss(nn.Module):
def __init__(self):
super(EDMLoss, self).__init__()
def forward(self, p_target: 'torch.Tensor', p_estimate: 'torch.Tensor'):
assert p_target.shape == p_estimate.shape
cdf_target = torch.cumsum(p_target, d... | 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... | lishiyu0088/Neural_Bradley-Terry | EDMLoss | false | 7,100 | [
"MIT"
] | 1 | ea2108267cf24c1fcfdf432e70810283d90495af | https://github.com/lishiyu0088/Neural_Bradley-Terry/tree/ea2108267cf24c1fcfdf432e70810283d90495af |
LocalResponseNormLayer | # 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_... | nicofirst1/lucent | LocalResponseNormLayer | false | 12,911 | [
"Apache-2.0"
] | 0 | 1e249918e91cc04117368826cd7a192bd8cf2046 | https://github.com/nicofirst1/lucent/tree/1e249918e91cc04117368826cd7a192bd8cf2046 |
AttentionCollapse | import torch
import torch.nn as nn
class AttentionCollapse(nn.Module):
"""Collapsing over the channels with attention.
Parameters
----------
n_channels : int
Number of input channels.
Attributes
----------
affine : nn.Module
Fully connected layer performing linear mapping... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | vishalbelsare/deepdow | AttentionCollapse | false | 16,704 | [
"Apache-2.0"
] | 511 | cbb99347fba9a447d4fcae64fe5137c203643e44 | https://github.com/vishalbelsare/deepdow/tree/cbb99347fba9a447d4fcae64fe5137c203643e44 |
DiscretePolicyFunction | import torch
import torch.nn as nn
import torch.nn.functional as F
class DiscretePolicyFunction(nn.Module):
"""fully connected 200x200 hidden layers"""
def __init__(self, state_dim, action_dim):
super(DiscretePolicyFunction, self).__init__()
self.fc1 = nn.Linear(state_dim, 200)
self.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.... | himanshusahni/task-biased-url | DiscretePolicyFunction | false | 10,263 | [
"MIT"
] | 0 | 28e4ec318d46d84065b6e197fa9f4100bd4a4c34 | https://github.com/himanshusahni/task-biased-url/tree/28e4ec318d46d84065b6e197fa9f4100bd4a4c34 |
classifier | # 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.... | czq142857/DECOR-GAN | classifier | false | 15,118 | [
"MIT"
] | 55 | 79c80fc202b8af982989a3e3bb3afe85e606b71f | https://github.com/czq142857/DECOR-GAN/tree/79c80fc202b8af982989a3e3bb3afe85e606b71f |
HighWay | import torch
import torch.nn as nn
from torch.nn import Parameter
class HighWay(torch.nn.Module):
def __init__(self, f_in, f_out, bias=True):
super(HighWay, self).__init__()
self.w = Parameter(torch.Tensor(f_in, f_out))
nn.init.xavier_uniform_(self.w)
if bias:
self.bia... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.... | weihangzhang/EAkit | HighWay | false | 16,729 | [
"MIT"
] | 102 | dde8e914480cd1a3585271f70db11d567d9c2a04 | https://github.com/weihangzhang/EAkit/tree/dde8e914480cd1a3585271f70db11d567d9c2a04 |
MinElementwise | # 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... | bunderhi/torch2trt | MinElementwise | false | 1,598 | [
"MIT"
] | 0 | fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d | https://github.com/bunderhi/torch2trt/tree/fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d |
FCChain | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
impor... | IlyaBizyaev/ttools | FCChain | false | 8,308 | [
"MIT"
] | 11 | b1435b19f397ce1baff9daed3cb287e52a029fdb | https://github.com/IlyaBizyaev/ttools/tree/b1435b19f397ce1baff9daed3cb287e52a029fdb |
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.... | dataJSA/batch7_tomorrow_datascience | MultiheadAttention | false | 9,986 | [
"MIT"
] | 0 | e2dc6bc59c456fa927e0a1f6d12024ba410f520c | https://github.com/dataJSA/batch7_tomorrow_datascience/tree/e2dc6bc59c456fa927e0a1f6d12024ba410f520c |
AdaIN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | jwen307/pytorch_GAN_zoo | AdaIN | false | 10,371 | [
"BSD-3-Clause"
] | 0 | b1e538a2f03fda42bd7a12872238b770ea5e0f23 | https://github.com/jwen307/pytorch_GAN_zoo/tree/b1e538a2f03fda42bd7a12872238b770ea5e0f23 |
Distribution_Loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn.functi... | SHI-Labs/Semi-Supervised-Transfer-Learning | Distribution_Loss | false | 14,357 | [
"MIT"
] | 81 | f206750824ffe10f88a2b418b2b671da61b999f6 | https://github.com/SHI-Labs/Semi-Supervised-Transfer-Learning/tree/f206750824ffe10f88a2b418b2b671da61b999f6 |
SoftmaxDeepLiftModel | # 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.... | Europium248/captum | SoftmaxDeepLiftModel | false | 449 | [
"BSD-3-Clause"
] | 0 | ac02fae2651b8d68a44bcb9d03b91cbb3959f2fc | https://github.com/Europium248/captum/tree/ac02fae2651b8d68a44bcb9d03b91cbb3959f2fc |
GraphConvolution | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn import Module
f... | LucasAPayne/graph4nlp | GraphConvolution | false | 9,689 | [
"Apache-2.0"
] | 0 | 3b72308f6ed9ce04c535f78b4b21b6ae0a8f5421 | https://github.com/LucasAPayne/graph4nlp/tree/3b72308f6ed9ce04c535f78b4b21b6ae0a8f5421 |
LinearFeedforward | import torch
import torch.nn as nn
import torch.utils.data
class Linear(nn.Linear):
def forward(self, x):
size = x.size()
return super().forward(x.contiguous().view(-1, size[-1])).view(*
size[:-1], -1)
class Feedforward(nn.Module):
def __init__(self, d_in, d_out, activation=Non... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | Krish-sysadmin/genienlp | LinearFeedforward | false | 17,546 | [
"BSD-3-Clause"
] | 6 | 3586e4368eb0b0756a772294daedc043ce55454c | https://github.com/Krish-sysadmin/genienlp/tree/3586e4368eb0b0756a772294daedc043ce55454c |
BinaryLinear | import torch
import torch.nn as nn
import torch.nn.functional as F
class LearnableBias(nn.Module):
def __init__(self, out_chn):
super(LearnableBias, self).__init__()
self.bias = nn.Parameter(torch.zeros(out_chn), requires_grad=True)
def forward(self, x):
out = x + self.bias.expand_as... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | uzair789/pytorch-retinanet | BinaryLinear | false | 10,961 | [
"Apache-2.0"
] | 0 | cabac159a9877825ef04ab06d3b9a63bdfa4f306 | https://github.com/uzair789/pytorch-retinanet/tree/cabac159a9877825ef04ab06d3b9a63bdfa4f306 |
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 tnn
assert... | AbbasMZ/jittor | Net | false | 36 | [
"Apache-2.0"
] | 0 | fcec57f70422b52d6b8d0235e29f91fd2212f559 | https://github.com/AbbasMZ/jittor/tree/fcec57f70422b52d6b8d0235e29f91fd2212f559 |
SoftDiceLoss_binary | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | Nareshvrao/Understanding-Clouds-from-Satellite-Images | SoftDiceLoss_binary | false | 5,638 | [
"MIT"
] | 1 | 14c5e1f15e803e9638d7a3fa8b9e0d929a6015b6 | https://github.com/Nareshvrao/Understanding-Clouds-from-Satellite-Images/tree/14c5e1f15e803e9638d7a3fa8b9e0d929a6015b6 |
LocationLoss | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_str... | L-Net-1992/DI-drive | LocationLoss | false | 13,981 | [
"Apache-2.0"
] | 219 | cc7f47bedbf60922acbcf3a5f77fc8e274df62cf | https://github.com/L-Net-1992/DI-drive/tree/cc7f47bedbf60922acbcf3a5f77fc8e274df62cf |
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