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 |
|---|---|---|---|---|---|---|---|---|---|---|
SMAPELoss | import torch
import torch.nn as nn
class SMAPELoss(nn.Module):
def forward(self, input, target):
return (torch.abs(input - target) / (torch.abs(input) + torch.abs(
target) + 0.01)).mean()
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_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 math as tl_math
import torch.nn as nn
... | arpan-dhatt/oidn | SMAPELoss | false | 14,897 | [
"Apache-2.0"
] | 1,206 | 9419411ba4b343b475b53587cadd44c83d68dc2a | https://github.com/arpan-dhatt/oidn/tree/9419411ba4b343b475b53587cadd44c83d68dc2a |
EltwiseSubEmbed | import torch
from torch import nn
class EltwiseSubEmbed(nn.Module):
def __init__(self, nonlinearity='square', use_batch_norm=False,
use_classifier=False, num_features=0, num_classes=0):
super(EltwiseSubEmbed, self).__init__()
self.nonlinearity = nonlinearity
if nonlinearity is not... | 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... | YantaoShen/kpm_rw_person_reid | EltwiseSubEmbed | false | 14,637 | [
"MIT"
] | 112 | 01393e024aa1139c9e7e934954cc35826f438a54 | https://github.com/YantaoShen/kpm_rw_person_reid/tree/01393e024aa1139c9e7e934954cc35826f438a54 |
down_right_shifted_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
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | ajayjain/lmconv | down_right_shifted_conv2d | false | 14,778 | [
"MIT"
] | 69 | e00576de5118702c90493e88c6e459b0e45d1290 | https://github.com/ajayjain/lmconv/tree/e00576de5118702c90493e88c6e459b0e45d1290 |
Pow | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | Ilyabasharov/torch2trt | Pow | false | 2,534 | [
"MIT"
] | 0 | 76bf298b3da408509665e23e2494922b131afb10 | https://github.com/Ilyabasharov/torch2trt/tree/76bf298b3da408509665e23e2494922b131afb10 |
DGCNLayer | # 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
i... | cjx96/CDRIB | DGCNLayer | false | 6,467 | [
"MIT"
] | 1 | e0d2d2b70ec195a76b479b94fb7758d286350c39 | https://github.com/cjx96/CDRIB/tree/e0d2d2b70ec195a76b479b94fb7758d286350c39 |
relu | import torch
import torch.nn as nn
class relu(nn.Module):
def __init__(self, layer=10, channels=32):
super(relu, self).__init__()
layers = []
for i in range(layer):
layers.append(nn.ReLU(inplace=True))
self.layers = nn.Sequential(*layers)
def forward(self, x):
... | 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
@... | yifanpu001/PytorchToCaffe | relu | false | 4,722 | [
"MIT"
] | 0 | 37c1ebfc3547e93b1c174721036d03c831c60e48 | https://github.com/yifanpu001/PytorchToCaffe/tree/37c1ebfc3547e93b1c174721036d03c831c60e48 |
GlobalAveragePooling | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | Jackqu/mmpose | GlobalAveragePooling | false | 8,368 | [
"Apache-2.0"
] | 38 | ad8acc5ff5da7993c6befdc4b1ced2c2ecb64533 | https://github.com/Jackqu/mmpose/tree/ad8acc5ff5da7993c6befdc4b1ced2c2ecb64533 |
FusedLeakyReLU | # 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
import torch.utils.checkpoint
from torch.nn import functional as F
assert_size_stride = torch._C._dynamo.guards.assert_... | Dokhyam/StyleCLIP | FusedLeakyReLU | false | 9,172 | [
"MIT"
] | 0 | 3953c6fda14672762897d3ee16c0458dc848c21d | https://github.com/Dokhyam/StyleCLIP/tree/3953c6fda14672762897d3ee16c0458dc848c21d |
SEModule | # 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_... | amajidsinar/seer | SEModule | false | 1,426 | [
"Apache-2.0"
] | 0 | 35f25b3fbf22968f0b09c266b8fd66a44fcc4d9c | https://github.com/amajidsinar/seer/tree/35f25b3fbf22968f0b09c266b8fd66a44fcc4d9c |
AnyHead | import torch
import torch.nn as nn
class AnyHead(nn.Module):
"""AnyNet Head part"""
def __init__(self, w_in, nc):
super(AnyHead, self).__init__()
self.avg_pool = nn.AdaptiveAvgPool2d((1, 1))
self.fc = nn.Linear(w_in, nc, bias=True)
def forward(self, x):
x = self.avg_pool(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Alessiacosmos/Basic-RegNet-pytorch | AnyHead | false | 18,398 | [
"MIT"
] | 2 | fd6b9a67599dcea6c90ba247f532a7624252b33c | https://github.com/Alessiacosmos/Basic-RegNet-pytorch/tree/fd6b9a67599dcea6c90ba247f532a7624252b33c |
ResBlock2 | import torch
import torch.nn as nn
import torch.multiprocessing
import torch.onnx
class ResBlock2(nn.Module):
def __init__(self, input_feature, planes, dilated=1, group=1):
super(ResBlock2, self).__init__()
self.conv1 = nn.Conv2d(input_feature, planes, kernel_size=1, bias=
False, grou... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | cvmlarun/RANet | ResBlock2 | false | 6,514 | [
"Apache-2.0"
] | 1 | 3f67a3f36aaacd9cc7fb98ec79f77db8f1ebdc60 | https://github.com/cvmlarun/RANet/tree/3f67a3f36aaacd9cc7fb98ec79f77db8f1ebdc60 |
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 import triton_helpers
from torch import nn
assert_s... | AbeJLazaro/TraductorEspanolOtomi | PositionwiseFeedForward | false | 1,915 | [
"MIT"
] | 0 | 75e1558d3b1a7efe9beb3c7d992c3bf1d3d88d0b | https://github.com/AbeJLazaro/TraductorEspanolOtomi/tree/75e1558d3b1a7efe9beb3c7d992c3bf1d3d88d0b |
VGGNet | # 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_... | miyosuda/oculomotor | VGGNet | false | 7,295 | [
"Apache-2.0"
] | 1 | 78e7ec61a808d058116c69bff1ea71ecf117c126 | https://github.com/miyosuda/oculomotor/tree/78e7ec61a808d058116c69bff1ea71ecf117c126 |
GDL | import torch
import numpy as np
from torch import nn
import torch.jit
import torch.nn.functional
def sum_tensor(inp, axes, keepdim=False):
axes = np.unique(axes).astype(int)
if keepdim:
for ax in axes:
inp = inp.sum(int(ax), keepdim=True)
else:
for ax in sorted(axes, reverse=Tr... | 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 numpy as np
from torch import nn
import torch.jit
import torch.nn.functional
assert_size_stride = torch._C._dynamo.guards.assert_size... | ShishuaiHu/DCAC | GDL | false | 5,827 | [
"MIT"
] | 1 | de04d00edde1b38385a8e5aade7541e2c22807e7 | https://github.com/ShishuaiHu/DCAC/tree/de04d00edde1b38385a8e5aade7541e2c22807e7 |
LearnableTimeDepWeightedCost | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_... | bechtle/LearningToLearn | LearnableTimeDepWeightedCost | false | 3,270 | [
"MIT"
] | 0 | 52eed5359e8a42bd99abe1df554a3b035dd3e2d2 | https://github.com/bechtle/LearningToLearn/tree/52eed5359e8a42bd99abe1df554a3b035dd3e2d2 |
DQN | import torch
import torch.nn as nn
import torch.nn.functional as F
class DQN(nn.Module):
def __init__(self, obs_size, action_size, seed):
super(DQN, self).__init__()
self.fc1 = nn.Linear(obs_size, 128)
self.fc2 = nn.Linear(128, 128)
self.fc3 = nn.Linear(128, sum(action_size))
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | ulyssesdotcodes/ReaL-Crowds | DQN | false | 4,466 | [
"BSD-3-Clause"
] | 0 | 9da01fe4d1858c3c26d6387e34f4e76db5385d51 | https://github.com/ulyssesdotcodes/ReaL-Crowds/tree/9da01fe4d1858c3c26d6387e34f4e76db5385d51 |
ResNetV2 | # 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.... | HelenR6/imagenet-r | ResNetV2 | false | 14,853 | [
"MIT"
] | 155 | 0bf04f2bf5d60d1098fc9a78f4e8c042e434eb69 | https://github.com/HelenR6/imagenet-r/tree/0bf04f2bf5d60d1098fc9a78f4e8c042e434eb69 |
SAM | import torch
import torch.nn as nn
class SAM(nn.Module):
def __init__(self, channels_in):
super(SAM, self).__init__()
self.channels_in = channels_in
self.avg_pool = nn.AvgPool3d(kernel_size=(self.channels_in, 1, 1))
self.max_pool = nn.MaxPool3d(kernel_size=(self.channels_in, 1, 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | rinkwitz/Thesis_Semantic_Image_Segmentation_on_Satellite_Imagery_using_UNets | SAM | false | 7,557 | [
"MIT"
] | 1 | 75d3a4a536f6ef81fe0efd4f5fbba32b627a7472 | https://github.com/rinkwitz/Thesis_Semantic_Image_Segmentation_on_Satellite_Imagery_using_UNets/tree/75d3a4a536f6ef81fe0efd4f5fbba32b627a7472 |
AttentionLayer | # 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.... | vietbt/ViTextnormASR | AttentionLayer | false | 10,955 | [
"Apache-2.0"
] | 0 | 57444aa7247c67b2628d1802e9ed53dae4857ee4 | https://github.com/vietbt/ViTextnormASR/tree/57444aa7247c67b2628d1802e9ed53dae4857ee4 |
XNOR_BinarizeConv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch.autograd... | RuiLin0212/BATMANN | XNOR_BinarizeConv2d | false | 17,864 | [
"MIT"
] | 6 | 5c5cc3334090fc0442bfd2ffdd41bdcab88cbea2 | https://github.com/RuiLin0212/BATMANN/tree/5c5cc3334090fc0442bfd2ffdd41bdcab88cbea2 |
Select | # 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
from torch.nn import Parameter
from torch.nn.parameter import Parameter
assert_size_stride = torch._C._dynamo.guards.a... | Nuctech-AI/LBS_pruning | Select | false | 17,748 | [
"MIT"
] | 6 | d2f67b287b69968b54a55fc3d25e26eef64d29a7 | https://github.com/Nuctech-AI/LBS_pruning/tree/d2f67b287b69968b54a55fc3d25e26eef64d29a7 |
GAT | import torch
import torch.nn as nn
import torch.nn.functional as F
class GraphAttentionLayer(nn.Module):
"""
Simple GAT layer, similar to https://arxiv.org/abs/1710.10903
"""
def __init__(self, in_features, out_features, dropout, alpha, concat=True):
super(GraphAttentionLayer, 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.... | jk96491/SMAC | GAT | false | 15,726 | [
"Apache-2.0"
] | 64 | 7aaf4673b0eecafc4ab25f381eea20fc762af56a | https://github.com/jk96491/SMAC/tree/7aaf4673b0eecafc4ab25f381eea20fc762af56a |
lovasz_hinge | import torch
import torch.nn.parallel
import torch.utils.data
from torchvision.transforms import functional as F
import torch.nn.functional as F
from torch.autograd import Variable
def flatten_binary_scores(scores, labels, ignore=255):
"""
Flattens predictions in the batch (binary case)
Remove labels equa... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn.parallel
import torch.utils.data
from torchvision.transforms import functional as F
import torch.nn.functional as F
from tor... | PhillipHuang2017/ext_portrait_segmentation | lovasz_hinge | false | 1,111 | [
"MIT"
] | 0 | 6d0cec0a953dacbc94a01ea8b719feb687b7c029 | https://github.com/PhillipHuang2017/ext_portrait_segmentation/tree/6d0cec0a953dacbc94a01ea8b719feb687b7c029 |
SobLoss | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | Filco306/TopologyLayer | SobLoss | false | 13,669 | [
"MIT"
] | 250 | 1d6261017a80cff0ee06bb896ded40777b0989b4 | https://github.com/Filco306/TopologyLayer/tree/1d6261017a80cff0ee06bb896ded40777b0989b4 |
CELossWeighted | import torch
import torch.nn as nn
class WeightedLoss(nn.Module):
def __init__(self):
super(WeightedLoss, self).__init__()
self.weighted = False
def generate_weight_mask(self, mask, to_ignore=None):
""" Generates a weight mask where pixel weights are inversely proportional to
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | Guangyun-Xu/uois | CELossWeighted | false | 13,729 | [
"MIT"
] | 106 | 00069af841dd3ea9a86e6e3a89c3b7222240e6e5 | https://github.com/Guangyun-Xu/uois/tree/00069af841dd3ea9a86e6e3a89c3b7222240e6e5 |
CosineSimilarity | import torch
import torch.nn as nn
import torch.nn.functional as F
class CosineSimilarity(nn.Module):
def __init__(self, dim=-1):
super(CosineSimilarity, self).__init__()
self.m = nn.CosineSimilarity(dim=dim)
def forward(self, i, j):
i = F.normalize(i, p=2, dim=-1)
j = F.norm... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | IBM/aihn-ucsd | CosineSimilarity | false | 8,255 | [
"Apache-2.0"
] | 20 | 6c6a56d11c704b529a31868418e350e9760ff9d9 | https://github.com/IBM/aihn-ucsd/tree/6c6a56d11c704b529a31868418e350e9760ff9d9 |
BlurPool2d | import torch
from torch.nn import *
import torch.nn as nn
class BlurPool2d(nn.Sequential):
"""Blur Pooling Layer (MaxPool2d replacement)
See: https://richzhang.github.io/antialiased-cnns/
Paper: https://arxiv.org/abs/1904.11486
"""
__constants__ = ['in_features']
_blur_kernel = torch.tensor([[... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn import *
import... | aktgpt/brevis | BlurPool2d | false | 18,278 | [
"MIT"
] | 8 | 0c3dcabd241ea50cafbc2012250804e1ecb7555e | https://github.com/aktgpt/brevis/tree/0c3dcabd241ea50cafbc2012250804e1ecb7555e |
Conv2d | import torch
import torch.utils.data
import torch.nn.functional as F
class Conv2d(torch.nn.Conv2d):
"""
A wrapper around :class:`torch.nn.Conv2d` to support empty inputs and more features.
"""
def __init__(self, *args, **kwargs):
"""
Extra keyword arguments supported in addition to th... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | AbirKhan96/facebook-detectron2 | Conv2d | false | 16,865 | [
"Apache-2.0"
] | 5 | 6a3bf813353d74bbeb8674e3566e7bbb33eb5c87 | https://github.com/AbirKhan96/facebook-detectron2/tree/6a3bf813353d74bbeb8674e3566e7bbb33eb5c87 |
MyEntLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | yuantn/MI-AOD | MyEntLoss | false | 16,776 | [
"Apache-2.0"
] | 188 | e57114d60f9ce5e43839cdf7068a90ee58092ec8 | https://github.com/yuantn/MI-AOD/tree/e57114d60f9ce5e43839cdf7068a90ee58092ec8 |
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._inductor.runtime.... | codeislife99/pytorch-meta-optimizer | Model | false | 9,938 | [
"MIT"
] | 0 | 24f00be05e6e173efa67fe953e466bdf1dcb50e9 | https://github.com/codeislife99/pytorch-meta-optimizer/tree/24f00be05e6e173efa67fe953e466bdf1dcb50e9 |
InnerProductLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.gu... | BELIEVEfxy/LightSANs | InnerProductLoss | false | 7,760 | [
"MIT"
] | 17 | 94ce7e59d144dbc787153b8c486cad334790ec6e | https://github.com/BELIEVEfxy/LightSANs/tree/94ce7e59d144dbc787153b8c486cad334790ec6e |
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
from torch._inductor.runtime.... | Hiroshiba/pytorch-trainer | MLP | false | 13,775 | [
"MIT"
] | 45 | b4b3d648868e4cec33c69e18fc3877c103a8d438 | https://github.com/Hiroshiba/pytorch-trainer/tree/b4b3d648868e4cec33c69e18fc3877c103a8d438 |
NgramCombined | # 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.cuda
import torch.distributed
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strid... | phuongnm-bkhn/OpenNMT-py | NgramCombined | false | 10,630 | [
"MIT"
] | 0 | 554a826139f1bfc55f4ea6a3e7491858c2afec4c | https://github.com/phuongnm-bkhn/OpenNMT-py/tree/554a826139f1bfc55f4ea6a3e7491858c2afec4c |
SimpleCeilModule | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleCeilModule(torch.nn.Module):
def forward(self, a, b):
c = a + b
return torch.ceil(c)
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._... | andreas-hommel/glow | SimpleCeilModule | false | 3,321 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
SEBlock | # 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... | DYF-AI/openvino-x | SEBlock | false | 5,047 | [
"Apache-2.0"
] | 1 | 0f18ebb240ea3394f7e461aca34fac158e686d95 | https://github.com/DYF-AI/openvino-x/tree/0f18ebb240ea3394f7e461aca34fac158e686d95 |
TransformerEncoderLayer | # 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.... | Hirni-Meshram3/text | TransformerEncoderLayer | false | 5,330 | [
"BSD-3-Clause"
] | 1 | 84e6c7bd99c7fb3c229ff289aa722149e3136094 | https://github.com/Hirni-Meshram3/text/tree/84e6c7bd99c7fb3c229ff289aa722149e3136094 |
Encoder3 | import torch
import torch.nn as nn
class Encoder3(nn.Module):
def __init__(self, D, H, M):
super().__init__()
self.D = D
self.M = M
self.H = H
self.enc1 = nn.Linear(in_features=self.D, out_features=self.H * 2)
self.enc2 = nn.Linear(in_features=self.H * 2, out_featu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | le0x99/deep-generative-modeling | Encoder3 | false | 7,081 | [
"MIT"
] | 1 | 40ffd1640dc3e5a6a2b4ba16a1d767034f081475 | https://github.com/le0x99/deep-generative-modeling/tree/40ffd1640dc3e5a6a2b4ba16a1d767034f081475 |
AUGRUCell | import torch
import torch.nn as nn
import torch.nn.functional as F
class AUGRUCell(nn.Module):
' Effect of GRU with attentional update gate (AUGRU). AUGRU combines attention mechanism and GRU seamlessly.\n\n Formally:\n ..math: \tilde{{u}}_{t}^{\\prime}=a_{t} * {u}_{t}^{\\prime} \\\n {h}_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | dreaming-qin/RecBole | AUGRUCell | false | 12,320 | [
"MIT"
] | 0 | d6de39521484ded60c387ca604abaf86310acdbe | https://github.com/dreaming-qin/RecBole/tree/d6de39521484ded60c387ca604abaf86310acdbe |
GAT | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Ononoki-Yotsugi/IDGL | GAT | false | 9,502 | [
"Apache-2.0"
] | 0 | a99f840681a4ae26c2740ed9e9302d4e15a68c7f | https://github.com/Ononoki-Yotsugi/IDGL/tree/a99f840681a4ae26c2740ed9e9302d4e15a68c7f |
ResolutionScalingLayer | import torch
import torch.nn as nn
import torch.nn.functional as F
class ResolutionScalingLayer(nn.Module):
"""Implements the resolution scaling layer.
Basically, this layer can be used to upsample or downsample feature maps from
spatial domain with nearest neighbor interpolation.
"""
def __init__(sel... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | AsianZeus/Diverse-Facial-Edit | ResolutionScalingLayer | false | 9,404 | [
"Apache-2.0"
] | 0 | 3d4b1b41546a08a1fa3cb164ade33e319806b12b | https://github.com/AsianZeus/Diverse-Facial-Edit/tree/3d4b1b41546a08a1fa3cb164ade33e319806b12b |
NeuralNet | # 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_... | Chris01e/Minh-V- | NeuralNet | false | 11,304 | [
"MIT"
] | 0 | 87e080f8583c0658f683e5a82cfa9ba2d116901e | https://github.com/Chris01e/Minh-V-/tree/87e080f8583c0658f683e5a82cfa9ba2d116901e |
MaskedSoftmax | # 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.utils.dat... | Nullius-2020/TAKG-Paddle | MaskedSoftmax | false | 14,127 | [
"MIT"
] | 130 | 7ebb5c4cdd1d2c68b1ca4a518b73c5e815fc5812 | https://github.com/Nullius-2020/TAKG-Paddle/tree/7ebb5c4cdd1d2c68b1ca4a518b73c5e815fc5812 |
WeightedBCEDiceLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | LovreAB17/Eff-UNet | WeightedBCEDiceLoss | false | 17,599 | [
"MIT"
] | 5 | b1e76a68d96e55324b6859c64ad2367653143e5e | https://github.com/LovreAB17/Eff-UNet/tree/b1e76a68d96e55324b6859c64ad2367653143e5e |
TorchAdd | # 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... | ahangchen/torch2trt | TorchAdd | false | 6,113 | [
"MIT"
] | 1 | 53c663f0e0570ef7ffd6771354ae3478f63bd328 | https://github.com/ahangchen/torch2trt/tree/53c663f0e0570ef7ffd6771354ae3478f63bd328 |
MLP | import torch
import torch as th
import torch.nn as nn
class MLP(nn.Module):
def __init__(self, input_size, output_size, hidden=128):
super(MLP, self).__init__()
self.linear1 = nn.Linear(input_size, hidden, bias=False)
self.linear2 = nn.Linear(hidden, output_size, bias=False)
def forw... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | bwubrian/cherry | MLP | false | 6,370 | [
"Apache-2.0"
] | 1 | de0cd2d833336144bce2a0b97e4dad40cbd78d7c | https://github.com/bwubrian/cherry/tree/de0cd2d833336144bce2a0b97e4dad40cbd78d7c |
ValueNetwork | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import t... | AmmarFayad/Influence-based-Reinforcement-Learning-in-Intrinsically-motivated-Agents | ValueNetwork | false | 4,846 | [
"MIT"
] | 1 | e7cfa4121542312de641792288f7487f86971c1e | https://github.com/AmmarFayad/Influence-based-Reinforcement-Learning-in-Intrinsically-motivated-Agents/tree/e7cfa4121542312de641792288f7487f86971c1e |
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 ... | pkj415/CityLearn-2 | Critic | false | 10,668 | [
"MIT"
] | 0 | 003012ddeb52868d42d85b835a9a5f2c28008927 | https://github.com/pkj415/CityLearn-2/tree/003012ddeb52868d42d85b835a9a5f2c28008927 |
ANet | import torch
import torch.nn as nn
import torch.utils.data
class ANet(nn.Module):
def __init__(self, in_feature):
super(ANet, self).__init__()
self.layer = nn.Linear(in_feature, 1)
self.sigmoid = nn.Sigmoid()
def forward(self, x):
x = self.layer(x)
x = self.sigmoid(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
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | Neronjust2017/TransferBed | ANet | false | 5,648 | [
"MIT"
] | 1 | eaa703a4bc10eaf6216fe1394cd272f6e75489e2 | https://github.com/Neronjust2017/TransferBed/tree/eaa703a4bc10eaf6216fe1394cd272f6e75489e2 |
Intensity | import torch
import torch.nn as nn
class Intensity(nn.Module):
def __init__(self, scale):
super().__init__()
self.scale = scale
def forward(self, x):
r = torch.randn((x.size(0), 1, 1, 1), device=x.device)
noise = 1.0 + self.scale * r.clamp(-2.0, 2.0)
return x * noise
... | import torch
from torch import device
import triton
import triton.language as tl
from 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.guar... | alcinos/SPR | Intensity | false | 3,075 | [
"MIT"
] | 0 | dec8df83eeaa25a1d75ecff0cf4ce4bfae9cab4c | https://github.com/alcinos/SPR/tree/dec8df83eeaa25a1d75ecff0cf4ce4bfae9cab4c |
ContrastiveLoss | # 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.nn import Module
import torch.nn as nn
from torch.nn.modules import Module
ass... | Brain03Yao/M2TGCN | ContrastiveLoss | false | 17,013 | [
"MIT"
] | 6 | 72c65687fa52c618740cd6d1db7366116f68398c | https://github.com/Brain03Yao/M2TGCN/tree/72c65687fa52c618740cd6d1db7366116f68398c |
ExampleBackbone | import torch
import torch.nn as nn
import torch._C
import torch.serialization
class ExampleBackbone(nn.Module):
def __init__(self):
super(ExampleBackbone, self).__init__()
self.conv = nn.Conv2d(3, 3, 3)
def init_weights(self, pretrained=None):
pass
def forward(self, 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
import torch.nn as nn
import torch._C
import torch.serialization
assert_size_str... | AlexanderDokuchaev/mmsegmentation | ExampleBackbone | false | 11,183 | [
"Apache-2.0"
] | 0 | 0c443ee370cce6227661b802184072174c4e3f64 | https://github.com/AlexanderDokuchaev/mmsegmentation/tree/0c443ee370cce6227661b802184072174c4e3f64 |
Conv3x3 | import torch
import torch.nn as nn
class Conv3x3(nn.Module):
"""Layer to pad and convolve input
"""
def __init__(self, in_channels, out_channels, use_refl=True):
super(Conv3x3, self).__init__()
if use_refl:
self.pad = nn.ReflectionPad2d(1)
else:
self.pad = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | Sid1057/sid1057.github.io | Conv3x3 | false | 17,964 | [
"MIT"
] | 4 | 623d1731e308b42b6f86304dcfd671a061b414bf | https://github.com/Sid1057/sid1057.github.io/tree/623d1731e308b42b6f86304dcfd671a061b414bf |
BasicBlock | import torch
import torch.nn as nn
import torch.utils.data
class BasicBlock(nn.Module):
expansion = 1
def __init__(self, dim):
super(BasicBlock, self).__init__()
self.conv1 = nn.Conv2d(dim, dim, kernel_size=3, padding=1, bias=False)
self.bn1 = nn.GroupNorm(2, dim, eps=0.0001)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | musyoku/ffjord | BasicBlock | false | 7,306 | [
"MIT"
] | 1 | 9e431e122e59fa9a71f3f301dec8fdd3db51e0ce | https://github.com/musyoku/ffjord/tree/9e431e122e59fa9a71f3f301dec8fdd3db51e0ce |
ModulatedConv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch.autograd... | SavvaI/stylegan2-pytorch | ModulatedConv2d | false | 9,497 | [
"MIT",
"BSD-2-Clause",
"Apache-2.0"
] | 0 | b8e4b605bd951283ef2c9a784e7afa0a486975bb | https://github.com/SavvaI/stylegan2-pytorch/tree/b8e4b605bd951283ef2c9a784e7afa0a486975bb |
DQN_hot1 | # 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 ... | CoAxLab/azad | DQN_hot1 | false | 17,174 | [
"MIT"
] | 6 | d1498069dd8856e93ae077b34dd7c9f1c7ce80e6 | https://github.com/CoAxLab/azad/tree/d1498069dd8856e93ae077b34dd7c9f1c7ce80e6 |
Block | import math
import torch
from typing import Optional
import torch.nn.functional as F
from torch import nn
def attention(query, key, value, mask=None, dropout=None):
"""Compute 'Scaled Dot Product Attention'
"""
d_k = query.size(-1)
scores = torch.matmul(query, key.transpose(-2, -1)) / math.sqrt(d_k)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | malhotraa/transformer-experiments | Block | false | 10,472 | [
"MIT"
] | 0 | 82931b89b14d26dbd6e4ffef8d6f2fd8b7279c0f | https://github.com/malhotraa/transformer-experiments/tree/82931b89b14d26dbd6e4ffef8d6f2fd8b7279c0f |
ChannelAttentionModule | # 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.... | YuSuen/ACCycleGAN | ChannelAttentionModule | false | 9,651 | [
"MIT"
] | 0 | e407f2e6e7148181109d6d49b5e1006ae26493e4 | https://github.com/YuSuen/ACCycleGAN/tree/e407f2e6e7148181109d6d49b5e1006ae26493e4 |
MergeLayer | # 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... | TraianVidrascu/DGAT | MergeLayer | false | 2,910 | [
"Apache-2.0"
] | 0 | 8855634d6262dec867512880442429918a9ee4b4 | https://github.com/TraianVidrascu/DGAT/tree/8855634d6262dec867512880442429918a9ee4b4 |
BBoxTransform | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_... | awesome-amy/efficientmask | BBoxTransform | false | 12,139 | [
"MIT"
] | 0 | 2456d52af92f765de771fbb6bd27fe2b9f19533b | https://github.com/awesome-amy/efficientmask/tree/2456d52af92f765de771fbb6bd27fe2b9f19533b |
Feature_extraction | import torch
from torchvision import transforms as transforms
import torch.nn as nn
class Feature_extraction(nn.Module):
def __init__(self, k, p):
super(Feature_extraction, self).__init__()
self.conv_1 = nn.Conv2d(3, 64, kernel_size=5, padding=2)
self.conv_2 = nn.Conv2d(64, 64, kernel_siz... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 torchvision import trans... | justinluyao/phd_thesis | Feature_extraction | false | 3,803 | [
"MIT"
] | 0 | 0a61f5deaac86dd34839ce24c2ad89e1411a8540 | https://github.com/justinluyao/phd_thesis/tree/0a61f5deaac86dd34839ce24c2ad89e1411a8540 |
TorchFloorDiv | import torch
class TorchFloorDiv(torch.nn.Module):
def __init__(self):
super(TorchFloorDiv, self).__init__()
def forward(self, x, y):
return torch.floor_divide(x, y)
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | NVIDIA-AI-IOT-private/torch2trt | TorchFloorDiv | false | 10,542 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
DoubleAttention | import torch
from torch import nn
from torch.nn import functional as F
from torch.nn import init
class DoubleAttention(nn.Module):
def __init__(self, in_channels, c_m, c_n, reconstruct=True):
super().__init__()
self.in_channels = in_channels
self.reconstruct = reconstruct
self.c_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 import triton_helpers
from torch._inductor.runtime.... | Nitin-Mane/External-Attention-pytorch | DoubleAttention | false | 14,107 | [
"MIT"
] | 4,466 | 1ceda306c41063af11c956334747763444a4d83f | https://github.com/Nitin-Mane/External-Attention-pytorch/tree/1ceda306c41063af11c956334747763444a4d83f |
GeM | # 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 libdevice
from torch import nn
from to... | h8c2/kaggle-landmark-recognition-2020-1st-place | GeM | false | 10,167 | [
"MIT"
] | 0 | 3285b6c9548d100b14800ea3927f5974b25facd9 | https://github.com/h8c2/kaggle-landmark-recognition-2020-1st-place/tree/3285b6c9548d100b14800ea3927f5974b25facd9 |
GlobalAveragePool | # 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... | ElisevanderPol/symmetrizer | GlobalAveragePool | false | 8,039 | [
"MIT"
] | 16 | 8dae02bee2ba7132ae4fb07e07020767d280842c | https://github.com/ElisevanderPol/symmetrizer/tree/8dae02bee2ba7132ae4fb07e07020767d280842c |
Conv1dWeightNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | juheeuu/flowseq | Conv1dWeightNorm | false | 12,657 | [
"Apache-2.0"
] | 0 | e6e50406656335ff7a2f9ed4bd81d7cc7d1195fb | https://github.com/juheeuu/flowseq/tree/e6e50406656335ff7a2f9ed4bd81d7cc7d1195fb |
InvConv2d | import torch
from torch import nn
from torch.nn import functional as F
class InvConv2d(nn.Module):
def __init__(self, in_channel):
super().__init__()
weight = torch.randn(in_channel, in_channel)
q, _ = torch.qr(weight)
weight = q.unsqueeze(2).unsqueeze(3)
self.weight = nn.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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 import functional as F
assert_size_stride = t... | AvivNavon/glow-pytorch | InvConv2d | false | 8,877 | [
"MIT"
] | 0 | de0fb2c1d8a4000337b2fbd1215df68530070431 | https://github.com/AvivNavon/glow-pytorch/tree/de0fb2c1d8a4000337b2fbd1215df68530070431 |
VanillaRNNCell | # 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 ... | YuXie96/time | VanillaRNNCell | false | 1,282 | [
"MIT"
] | 0 | 8539d55d2449c712f54331b06720ab7faf3593df | https://github.com/YuXie96/time/tree/8539d55d2449c712f54331b06720ab7faf3593df |
MaxPool2dStaticSamePadding | # 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... | ChrisLiuxp/efficientdet | MaxPool2dStaticSamePadding | false | 269 | [
"MIT"
] | 0 | 5d52ac491e1dd2a29ee6650bb746f1e840c24fcc | https://github.com/ChrisLiuxp/efficientdet/tree/5d52ac491e1dd2a29ee6650bb746f1e840c24fcc |
KDETH | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch ... | Alibaba-MIIL/HeadSharingKD | KDETH | false | 7,696 | [
"BSD-2-Clause"
] | 15 | 8e2738bf069c7d12ec933f9b9107f267f7b6603a | https://github.com/Alibaba-MIIL/HeadSharingKD/tree/8e2738bf069c7d12ec933f9b9107f267f7b6603a |
My_loss | import torch
from torch import nn as nn
import torch.nn.parallel
import torch.optim
from torch.autograd import Variable as Variable
import torch.utils.data
import torch._utils
class My_loss(torch.nn.Module):
def __init__(self):
super().__init__()
def forward(self, x, y):
vx = x - torch.mean(... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn as nn
i... | wtomin/MIMA-Net | My_loss | false | 16,732 | [
"MIT"
] | 58 | c0330777313ac04b25e53b137dbecd78b5c8dde6 | https://github.com/wtomin/MIMA-Net/tree/c0330777313ac04b25e53b137dbecd78b5c8dde6 |
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.triton_helpers import libdevice
from typing import ... | Flash-Of-Thunder/testing | Model | false | 8,147 | [
"Apache-2.0"
] | 18 | 36366e2cd32756fb07abc533ecbb7672a4738bc6 | https://github.com/Flash-Of-Thunder/testing/tree/36366e2cd32756fb07abc533ecbb7672a4738bc6 |
RDivFloat | import torch
class RDivFloat(torch.nn.Module):
def __init__(self):
super(RDivFloat, self).__init__()
def forward(self, x):
return 100.0 / x
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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | bunderhi/torch2trt | RDivFloat | false | 1,602 | [
"MIT"
] | 0 | fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d | https://github.com/bunderhi/torch2trt/tree/fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d |
NormalizationLayer | import torch
import torch.utils.data
class NormalizationLayer(torch.nn.Module):
"""Class for normalization layer."""
def __init__(self, normalize_scale=1.0, learn_scale=True):
super(NormalizationLayer, self).__init__()
self.norm_s = float(normalize_scale)
if learn_scale:
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.triton_helpers import libdevice
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_siz... | hmtrii/tirg | NormalizationLayer | false | 10,161 | [
"Apache-2.0"
] | 0 | e404020795bb46fb01b6bd82a2618f9370174012 | https://github.com/hmtrii/tirg/tree/e404020795bb46fb01b6bd82a2618f9370174012 |
AverageAttention | import torch
import torch.nn as nn
import torch.cuda
import torch.distributed
class PositionwiseFeedForward(nn.Module):
""" A two-layer Feed-Forward-Network with residual layer norm.
Args:
d_model (int): the size of input for the first-layer of the FFN.
d_ff (int): the hidden layer size of th... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.cuda
import torch.distributed
assert_size_str... | KaijuML/PARENTing-rl | AverageAttention | false | 17,532 | [
"Apache-2.0"
] | 8 | 98d20e1899e0ff3a9a7a6bb3e50ec28ff0b3b700 | https://github.com/KaijuML/PARENTing-rl/tree/98d20e1899e0ff3a9a7a6bb3e50ec28ff0b3b700 |
TwoLayerCNN | # 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_... | LFhase/string-embed | TwoLayerCNN | false | 9,211 | [
"MIT"
] | 0 | da8eb60186fcd26a94734f265f79fa5fc5096f76 | https://github.com/LFhase/string-embed/tree/da8eb60186fcd26a94734f265f79fa5fc5096f76 |
TorchAdd | # 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... | Yakings/AIPerf | TorchAdd | false | 14,616 | [
"MIT"
] | 52 | 6e5c50a3b769ab4b1075aaab9841b5554f40bceb | https://github.com/Yakings/AIPerf/tree/6e5c50a3b769ab4b1075aaab9841b5554f40bceb |
LinearNet | import torch
import torch.nn
import torch.optim
class LinearNet(torch.nn.Module):
def __init__(self, D_in, H, D_out):
super().__init__()
self.linear1 = torch.nn.Linear(D_in, H)
self.nonlinear = torch.nn.ReLU()
self.linear2 = torch.nn.Linear(H, D_out)
def forward(self, x: 'tor... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | DavidV17/ReAgent | LinearNet | false | 364 | [
"BSD-3-Clause"
] | 0 | 9b55696849cf133bc8494a5bce57df420ffe7517 | https://github.com/DavidV17/ReAgent/tree/9b55696849cf133bc8494a5bce57df420ffe7517 |
SelfAttention | # 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.... | MatthewMasters/grover | SelfAttention | false | 836 | [
"MIT"
] | 0 | 737a340754bc4c63134ef84019a0a84023fd69a3 | https://github.com/MatthewMasters/grover/tree/737a340754bc4c63134ef84019a0a84023fd69a3 |
CenterLoss | # 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 libdevice
from torch import nn
from to... | vadimadr/openvino_training_extensions | CenterLoss | false | 11,044 | [
"Apache-2.0"
] | 0 | 5d64b8423c8eb7b374ed629fad938359d34a07d2 | https://github.com/vadimadr/openvino_training_extensions/tree/5d64b8423c8eb7b374ed629fad938359d34a07d2 |
Block | import torch
import torch.nn as nn
from torch.nn import functional as F
def get_conv(in_dim, out_dim, kernel_size, stride, padding, zero_bias=True,
zero_weights=False, groups=1, scaled=False):
c = nn.Conv2d(in_dim, out_dim, kernel_size, stride, padding, groups=groups)
if zero_bias:
c.bias.data *= ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | ashesh-0/vdvae | Block | false | 9,740 | [
"MIT"
] | 0 | a1ed5dfaf01a88af750413f5fcb907a5b73833a5 | https://github.com/ashesh-0/vdvae/tree/a1ed5dfaf01a88af750413f5fcb907a5b73833a5 |
UpSampling | # 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... | PatrickChoDev/LiDAR-ObjDetect | UpSampling | false | 2,729 | [
"MIT"
] | 0 | a839220d28a1fda045278ded0992e46f408a5442 | https://github.com/PatrickChoDev/LiDAR-ObjDetect/tree/a839220d28a1fda045278ded0992e46f408a5442 |
SineODE | # 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 math
assert_size_stride = torch._C._dynamo.guards.assert_size_stri... | arnabgho/torchdiffeq | SineODE | false | 3,193 | [
"MIT"
] | 0 | d4f73440d0e714b87ea133610e61eefbd673e5f5 | https://github.com/arnabgho/torchdiffeq/tree/d4f73440d0e714b87ea133610e61eefbd673e5f5 |
Attention | # 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.... | SunZongdi/self-critical.pytorch | Attention | false | 5,864 | [
"MIT"
] | 1 | 6cecbeb949e68007b72e84198cf74f9fb288aeda | https://github.com/SunZongdi/self-critical.pytorch/tree/6cecbeb949e68007b72e84198cf74f9fb288aeda |
AttentionHead | # 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.... | ErikHumphrey/sustain-seq2seq | AttentionHead | false | 17,273 | [
"Apache-2.0"
] | 4 | c4787f0ca1047d01385e4fa4ffde59c6a8ab4cc4 | https://github.com/ErikHumphrey/sustain-seq2seq/tree/c4787f0ca1047d01385e4fa4ffde59c6a8ab4cc4 |
TemporalEmbedding | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guar... | Linan2018/Informer2020 | TemporalEmbedding | false | 2,514 | [
"Apache-2.0"
] | 0 | 30e63a7d3ed9310b917b05c4d60b340d2dd0517a | https://github.com/Linan2018/Informer2020/tree/30e63a7d3ed9310b917b05c4d60b340d2dd0517a |
NavigatorBranch | # 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... | HyperGAN/imgclsmob | NavigatorBranch | false | 17,696 | [
"MIT"
] | 9 | 88b9776a5a927dc9a54e85e31978c4a9ec5ecbf3 | https://github.com/HyperGAN/imgclsmob/tree/88b9776a5a927dc9a54e85e31978c4a9ec5ecbf3 |
AFMLayer | import itertools
import torch
import torch.nn as nn
import torch.nn.functional as F
from sklearn.metrics import *
import torch.onnx
import torch as torch
class AFMLayer(nn.Module):
"""Attentonal Factorization Machine models pairwise (order-2) feature
interactions without linear term and bias.
Input shap... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | dulvqingyunLT/DeepCTR-Torch | AFMLayer | false | 10,424 | [
"Apache-2.0"
] | 0 | f40cf08f3469aa471f9ca69e44c5de51180341cc | https://github.com/dulvqingyunLT/DeepCTR-Torch/tree/f40cf08f3469aa471f9ca69e44c5de51180341cc |
VNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from to... | AswinRetnakumar/Machina | VNet | false | 13,326 | [
"MIT"
] | 302 | 6519935ca4553192ac99fc1c7c1e7cab9dd72693 | https://github.com/AswinRetnakumar/Machina/tree/6519935ca4553192ac99fc1c7c1e7cab9dd72693 |
SAGEConv | import torch
import torch.nn.functional as F
import torch.nn as nn
class SAGEConv(nn.Module):
"""
Description
-----------
SAGE convolutional layer.
Parameters
----------
in_features : int
Dimension of input features.
pool_features : int
Dimension of pooling features.
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | sigeisler/grb | SAGEConv | false | 16,451 | [
"MIT"
] | 51 | c89e21076dc05d1edb87dfe2eff20c29ba6bd0c1 | https://github.com/sigeisler/grb/tree/c89e21076dc05d1edb87dfe2eff20c29ba6bd0c1 |
ConcatPool2d | import torch
import torch.nn as nn
class ConcatPool2d(nn.Module):
"""Layer that concats `AvgPool2d` and `MaxPool2d`"""
def __init__(self, ks, stride=None, padding=0):
super().__init__()
self.ap = nn.AvgPool2d(ks, stride, padding)
self.mp = nn.MaxPool2d(ks, stride, padding)
def fo... | 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... | davidleonfdez/face2anime | ConcatPool2d | false | 1,801 | [
"MIT"
] | 0 | 896bf85a7aa28322cc9e9e586685db8cbbf39d89 | https://github.com/davidleonfdez/face2anime/tree/896bf85a7aa28322cc9e9e586685db8cbbf39d89 |
PartialViewPredictionModule | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | Impavidity/relogic | PartialViewPredictionModule | false | 8,803 | [
"MIT"
] | 24 | f647106e143cd603b95b63e06ea530cdd516aefe | https://github.com/Impavidity/relogic/tree/f647106e143cd603b95b63e06ea530cdd516aefe |
ActorNetwork | # 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... | yutiansut/Personae | ActorNetwork | false | 16,777 | [
"MIT"
] | 1,046 | e5e89cbaaf2c4708952d25fdb25e99837aecdb4e | https://github.com/yutiansut/Personae/tree/e5e89cbaaf2c4708952d25fdb25e99837aecdb4e |
GAT | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | gitubee/pyGAT | GAT | false | 10,164 | [
"MIT"
] | 0 | bc4cc2b6565b7f2ad99daf88013207f64991c273 | https://github.com/gitubee/pyGAT/tree/bc4cc2b6565b7f2ad99daf88013207f64991c273 |
BatchNormNode | import torch
import torch.nn as nn
class BatchNormNode(nn.Module):
"""Batch normalization for node features.
"""
def __init__(self, hidden_dim):
super(BatchNormNode, self).__init__()
self.batch_norm = nn.BatchNorm1d(hidden_dim, track_running_stats=False)
def forward(self, x):
... | 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_... | BrandonKates/graph-convnet-tsp | BatchNormNode | false | 11,259 | [
"MIT"
] | 0 | f6e17e84311c23fd5cab041b7a27b4e0636c44f8 | https://github.com/BrandonKates/graph-convnet-tsp/tree/f6e17e84311c23fd5cab041b7a27b4e0636c44f8 |
EmbeddingsInteraction | import torch
import torch.nn as nn
class EmbeddingsInteraction(nn.Module):
def __init__(self):
super(EmbeddingsInteraction, self).__init__()
def forward(self, x):
"""
:param x: shape (batch_size, num_fields, embedding_dim)
:return: shape (batch_size, num_fields*(num_fields)//... | 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 | EmbeddingsInteraction | false | 2,789 | [
"Apache-2.0"
] | 0 | 817398dc1c117e22f41281830ae3c33bba8062d3 | https://github.com/SUSTechBruce/RL_CTR/tree/817398dc1c117e22f41281830ae3c33bba8062d3 |
Theta | from torch.autograd import Function
import torch
from typing import Optional
from typing import Tuple
import torch.nn as nn
from typing import Any
import torch.nn.parallel
import torch.utils.data
import torch.utils.data.distributed
import torch.optim
class GradientReverseFunction(Function):
@staticmethod
def... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.autograd import Function
from typing import Optional
from typing impo... | mstoelzle/Transfer-Learning-Library | Theta | false | 12,877 | [
"MIT"
] | 0 | 7d5022668cbe6d1bedbc7c386d44b9d89c272d6b | https://github.com/mstoelzle/Transfer-Learning-Library/tree/7d5022668cbe6d1bedbc7c386d44b9d89c272d6b |
LossPredLoss | # 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... | KMU-AELAB/Active_Learning | LossPredLoss | false | 2,449 | [
"MIT"
] | 0 | bc569c16b5f12b58989a8f3db59b7eb4e35cce1b | https://github.com/KMU-AELAB/Active_Learning/tree/bc569c16b5f12b58989a8f3db59b7eb4e35cce1b |
PixelNorm | # 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
from torch import nn
import torch.nn.parallel
import torch.utils.data
import to... | IdanAzuri/MixMatch-pytorch | PixelNorm | false | 579 | [
"MIT"
] | 0 | b8de2bc30c09e1256b92e0394403487fc4f90135 | https://github.com/IdanAzuri/MixMatch-pytorch/tree/b8de2bc30c09e1256b92e0394403487fc4f90135 |
CNN_small | # 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 ... | JiarunLiu/Co-correcting | CNN_small | false | 8,361 | [
"Apache-2.0"
] | 19 | 4e3ca4951de5d73ca812bbbcfe666273082ff2fd | https://github.com/JiarunLiu/Co-correcting/tree/4e3ca4951de5d73ca812bbbcfe666273082ff2fd |
BilinearRanking | # 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.... | IgnatovFedor/DeepPavlov | BilinearRanking | false | 9,177 | [
"Apache-2.0"
] | 0 | 02ba9c4b2919384c142c170c7f89c65cf05dd426 | https://github.com/IgnatovFedor/DeepPavlov/tree/02ba9c4b2919384c142c170c7f89c65cf05dd426 |
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