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 |
|---|---|---|---|---|---|---|---|---|---|---|
MAPE | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | RosarioAndolina/psychXRF | MAPE | false | 990 | [
"MIT"
] | 0 | e2adadbd17664d7f74c10304f84b3751c571226e | https://github.com/RosarioAndolina/psychXRF/tree/e2adadbd17664d7f74c10304f84b3751c571226e |
InstanceNorm | import torch
import torch.utils.data
from torch import nn
class InstanceNorm(nn.Module):
def __init__(self, epsilon=1e-08):
super(InstanceNorm, self).__init__()
self.epsilon = epsilon
def forward(self, x):
x = x - torch.mean(x, (2, 3), True)
tmp = torch.mul(x, x)
tmp ... | 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
from torch import nn
assert_size_stride = torch._C._dyn... | Archjbald/PoseStylizer | InstanceNorm | false | 1,966 | [
"BSD-3-Clause"
] | 0 | 95aae02d1f4ac83536d91b8db5f78d12e7830f97 | https://github.com/Archjbald/PoseStylizer/tree/95aae02d1f4ac83536d91b8db5f78d12e7830f97 |
GatedLinear | import torch
import torch.nn as nn
class GatedLinear(nn.Module):
def __init__(self, in_features, out_features):
super(GatedLinear, self).__init__()
self.layer_f = nn.Linear(in_features, out_features)
self.layer_g = nn.Linear(in_features, out_features)
def forward(self, x):
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | D-hash-code/ffjord-rnode-finalweek-mnist | GatedLinear | false | 2,151 | [
"MIT"
] | 0 | 4cabcbadda79c68df53ec25f1f8fe03cfeee78f9 | https://github.com/D-hash-code/ffjord-rnode-finalweek-mnist/tree/4cabcbadda79c68df53ec25f1f8fe03cfeee78f9 |
OELossLogConf | import torch
import torch.nn as nn
import torch.distributions
import torch.utils.data
class OELossLogConf(nn.Module):
def __init__(self):
super().__init__()
def forward(self, confs):
return -confs.mean(1)
def get_inputs():
return [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
import torch.nn as nn
import torch.distributions
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | AlexMeinke/Provable-OOD-Detection | OELossLogConf | false | 7,689 | [
"MIT"
] | 21 | 9a132aec994ff718c96b81885736ab866df60d87 | https://github.com/AlexMeinke/Provable-OOD-Detection/tree/9a132aec994ff718c96b81885736ab866df60d87 |
SelfAttention | import torch
import torch.nn as nn
import torch.utils.data
class SelfAttention(nn.Module):
def __init__(self, embed_size, heads):
super(SelfAttention, self).__init__()
self.embed_size = embed_size
self.heads = heads
self.head_dim = embed_size // heads
assert self.head_dim ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | ZonePG/Machine-Learning-Collection | SelfAttention | false | 14,734 | [
"MIT"
] | 3,094 | 85f1e761fab85b61d4dbd44285d6483b75ba649c | https://github.com/ZonePG/Machine-Learning-Collection/tree/85f1e761fab85b61d4dbd44285d6483b75ba649c |
NCutLossOptimized | import torch
from torch import Tensor
import torch.nn as nn
class NCutLossOptimized(nn.Module):
"""Implementation of the continuous N-Cut loss, as in:
'W-Net: A Deep Model for Fully Unsupervised Image Segmentation', by Xia, Kulis (2017)"""
def __init__(self, radius: 'int'=5):
"""
:param r... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | Christer-L/wnet_pytorch | NCutLossOptimized | false | 279 | [
"MIT"
] | 0 | c7a7d3db0c07d5e2d83fe152ce5fdae31472748b | https://github.com/Christer-L/wnet_pytorch/tree/c7a7d3db0c07d5e2d83fe152ce5fdae31472748b |
BhattacharyyaDistance | import torch
import torch.nn as nn
class BhattacharyyaDistance(nn.Module):
def __init__(self):
super(BhattacharyyaDistance, self).__init__()
def forward(self, hist1, hist2):
bh_dist = torch.sqrt(hist1 * hist2).sum()
return bh_dist
def get_inputs():
return [torch.rand([4, 4, 4, ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | tommy90191/Find_Tiny_but_Important_Image_Changes | BhattacharyyaDistance | false | 4,438 | [
"MIT"
] | 0 | 429d679606f96f32db4cddf167a9cfb963d3df26 | https://github.com/tommy90191/Find_Tiny_but_Important_Image_Changes/tree/429d679606f96f32db4cddf167a9cfb963d3df26 |
MaskDiscriminator | import torch
import torch.nn as nn
class MaskDiscriminator(nn.Module):
def __init__(self):
super(MaskDiscriminator, self).__init__()
filter_num_list = [64, 128, 256, 512, 2]
self.conv1 = nn.Conv2d(2, filter_num_list[0], kernel_size=4, stride
=2, padding=2, bias=False)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | JACKYLUO1991/DCBNet | MaskDiscriminator | false | 17,469 | [
"MIT"
] | 6 | b797584b66ad99fe984f58268befb12ec60ccfae | https://github.com/JACKYLUO1991/DCBNet/tree/b797584b66ad99fe984f58268befb12ec60ccfae |
_Residual_Block_SR | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn.functional
import torch.nn as nn
assert_size_stride = torch._C._... | HelenGuohx/cv-ferattn-code | _Residual_Block_SR | false | 5,291 | [
"MIT"
] | 1 | faa9b7850fe2a0f8c08193bb129b5fec4639d616 | https://github.com/HelenGuohx/cv-ferattn-code/tree/faa9b7850fe2a0f8c08193bb129b5fec4639d616 |
Linear_2L_KFRA | # 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 ... | kw-lee/Bayesian-Neural-Networks | Linear_2L_KFRA | false | 7,063 | [
"MIT"
] | 1 | 3327fcf85e47c15d86c872211427bff133880c34 | https://github.com/kw-lee/Bayesian-Neural-Networks/tree/3327fcf85e47c15d86c872211427bff133880c34 |
MultiHeadAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
class ScaledDotProductAttention(nn.Module):
""" Scaled Dot-Product Attention """
def __init__(self, temperature, attn_dropout=0.1):
super().__init__()
self.temperature = temperature
self.dropout = nn.Dropout(attn_dropo... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | BlackNoodle/TUCORE-GCN | MultiHeadAttention | false | 7,808 | [
"MIT"
] | 27 | 16fb37d81c5b1182a31fcf7da08a9c0013b20cd6 | https://github.com/BlackNoodle/TUCORE-GCN/tree/16fb37d81c5b1182a31fcf7da08a9c0013b20cd6 |
Fcn8s | import torch
import numpy as np
import torch.nn as nn
def _upsampling_weights(in_channels, out_channels, kernel_size):
factor = (kernel_size + 1) // 2
if kernel_size % 2 == 1:
center = factor - 1
else:
center = factor - 0.5
og = np.ogrid[:kernel_size, :kernel_size]
filt = (1 - abs(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import numpy as np
import tor... | jgibson2/crfasrnn_pytorch | Fcn8s | false | 4,661 | [
"MIT"
] | 0 | 04c8477343bc1a186b3712f876b497f00e43ae72 | https://github.com/jgibson2/crfasrnn_pytorch/tree/04c8477343bc1a186b3712f876b497f00e43ae72 |
FCN8VGG16 | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import numpy as np
from torch... | DoranLyong/DeepFish | FCN8VGG16 | false | 5,416 | [
"MIT"
] | 1 | 3ea3e13653f708d4a8dcb54b990dcc2997edf4e9 | https://github.com/DoranLyong/DeepFish/tree/3ea3e13653f708d4a8dcb54b990dcc2997edf4e9 |
Image2Patch | import torch
import torch.nn as nn
import torch.nn.functional as F
class Image2Patch(nn.Module):
"""Some Information about Image2Patch"""
def __init__(self, channels, image_size, patch_size):
super(Image2Patch, self).__init__()
if type(patch_size) == int:
patch_size = [patch_size,... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | uthree/ReMixer | Image2Patch | false | 13,059 | [
"MIT"
] | 0 | 587e1b6a01850df649eccf043689f84a7dd5e2dc | https://github.com/uthree/ReMixer/tree/587e1b6a01850df649eccf043689f84a7dd5e2dc |
BWCEWLoss | import torch
from torch import Tensor
from typing import Optional
from torch import nn
class BWCEWLoss(nn.Module):
""" Binary weighted cross entropy loss. """
def __init__(self, positive_class_weight: 'Optional[Tensor]'=None,
robust_lambda: 'int'=0, confidence_penalty: 'int'=0, **kwargs):
sup... | 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 ... | Connormcc3/ludwig | BWCEWLoss | false | 9,003 | [
"Apache-2.0"
] | 0 | 5d562cbc0c4fed3e607969e18611f34240eef177 | https://github.com/Connormcc3/ludwig/tree/5d562cbc0c4fed3e607969e18611f34240eef177 |
Decoder | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | NREL/ml-combustion-pdf-models | Decoder | false | 17,735 | [
"Apache-2.0"
] | 6 | 0505b9c54ab4c1e2b7ef8ca9f59f76bfb2e3732d | https://github.com/NREL/ml-combustion-pdf-models/tree/0505b9c54ab4c1e2b7ef8ca9f59f76bfb2e3732d |
AlphaVectorMultiplication | import torch
import numpy as np
from torch import nn
from typing import *
class AlphaVectorMultiplication(nn.Module):
def __init__(self, size_alpha):
super(AlphaVectorMultiplication, self).__init__()
self.size_alpha = size_alpha
self.alpha = nn.Parameter(torch.from_numpy(np.zeros((1, size... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import numpy as np
from torch import nn
from typing import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | HughMun/MultiBench | AlphaVectorMultiplication | false | 13,791 | [
"MIT"
] | 148 | d5712a0815a9486b0e0c76b54cd63c880188fc8e | https://github.com/HughMun/MultiBench/tree/d5712a0815a9486b0e0c76b54cd63c880188fc8e |
NeuralNetNonDifferentiableOutput | # 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
import torch.... | almiliMSFT/onnxruntime | NeuralNetNonDifferentiableOutput | false | 14,806 | [
"MIT"
] | 6,036 | c002dc86a364852859ca9642698fcfc5edf22c9d | https://github.com/almiliMSFT/onnxruntime/tree/c002dc86a364852859ca9642698fcfc5edf22c9d |
Net | from _paritybench_helpers import _mock_config
import torch
class Net(torch.nn.Module):
def __init__(self, configs):
super(Net, self).__init__()
self.fc1 = torch.nn.Linear(configs['input_size'], configs[
'hidden_size'])
self.fc1_activate = torch.nn.ReLU()
self.fc2 = 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.... | Lovestarni/Reinforcement-learning-with-tensorflow | Net | false | 11,126 | [
"MIT"
] | 0 | 822a4ae812b044687c11138ef9c9db1e1190f98c | https://github.com/Lovestarni/Reinforcement-learning-with-tensorflow/tree/822a4ae812b044687c11138ef9c9db1e1190f98c |
BahdanauAttention | # 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 ... | vigilancetrent/chatbot-advanced | BahdanauAttention | false | 16,667 | [
"Apache-2.0"
] | 52 | 2e0c72c4df2e1434da995b7105f8f0414aba6248 | https://github.com/vigilancetrent/chatbot-advanced/tree/2e0c72c4df2e1434da995b7105f8f0414aba6248 |
Bottleneck | # 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.... | Jincheng-Sun/Kylearn-pytorch | Bottleneck | false | 653 | [
"MIT"
] | 0 | e72f2ab45a3f4724e843a27bec37664d3612fdca | https://github.com/Jincheng-Sun/Kylearn-pytorch/tree/e72f2ab45a3f4724e843a27bec37664d3612fdca |
BCEBlurWithLogitsLoss | import torch
import torch.nn as nn
import torch.utils.data
class BCEBlurWithLogitsLoss(nn.Module):
def __init__(self, alpha=0.05):
super(BCEBlurWithLogitsLoss, self).__init__()
self.loss_fcn = nn.BCEWithLogitsLoss(reduction='none')
self.alpha = alpha
def forward(self, pred, true):
... | 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... | ChaokunChang/SVAS | BCEBlurWithLogitsLoss | false | 256 | [
"Apache-2.0"
] | 0 | 61af6eb39269edff8ea5147311628b3200c3a3d2 | https://github.com/ChaokunChang/SVAS/tree/61af6eb39269edff8ea5147311628b3200c3a3d2 |
StdConv2d | # 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 ... | GUOSHU-COOL/TransUNet | StdConv2d | false | 2,263 | [
"Apache-2.0"
] | 0 | 6cb2c2f35eb6a571b12edbd095de5dda16c25015 | https://github.com/GUOSHU-COOL/TransUNet/tree/6cb2c2f35eb6a571b12edbd095de5dda16c25015 |
LosslessYCbCr | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn.parallel
import torch.utils.data
from torch import nn
import torch.fft
assert_size_stride = torch._C._dynamo.guards.assert_s... | KazutakaYamanouchi/bachelor-study | LosslessYCbCr | false | 2,616 | [
"Apache-2.0"
] | 0 | a5b8392459e7649cb8a35d09e65bd269d13b5297 | https://github.com/KazutakaYamanouchi/bachelor-study/tree/a5b8392459e7649cb8a35d09e65bd269d13b5297 |
CrossAttention | import torch
import torch.nn as nn
class MultiHeadAttention(nn.Module):
def __init__(self, num_q_channels: 'int', num_kv_channels: 'int',
num_heads: 'int', dropout: 'float'):
super().__init__()
self.attention = nn.MultiheadAttention(embed_dim=num_q_channels,
num_heads=num_head... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | DartingMelody/perceiver-io | CrossAttention | false | 358 | [
"Apache-2.0"
] | 0 | fb818b1763f61e259b23b8b014df2ac01c303a54 | https://github.com/DartingMelody/perceiver-io/tree/fb818b1763f61e259b23b8b014df2ac01c303a54 |
NoNorm | import torch
import torch.nn as nn
class NoNorm(nn.Module):
def __init__(self, feat_size):
super(NoNorm, self).__init__()
self.bias = nn.Parameter(torch.zeros(feat_size))
self.weight = nn.Parameter(torch.ones(feat_size))
def forward(self, input_tensor):
return input_tensor * ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | deepframwork/TorchBlocks | NoNorm | false | 6,535 | [
"MIT"
] | 1 | 35f6e1bb83d2b9b05ba914a21fd365cb26ac4a32 | https://github.com/deepframwork/TorchBlocks/tree/35f6e1bb83d2b9b05ba914a21fd365cb26ac4a32 |
ConvMeanPool | import torch
from torch import nn
class MyConvo2d(nn.Module):
def __init__(self, input_dim, output_dim, kernel_size, he_init=True,
stride=1, bias=True):
super(MyConvo2d, self).__init__()
self.he_init = he_init
self.padding = int((kernel_size - 1) / 2)
self.conv = nn.Conv2d... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | justaboutlola/improved-wgan-pytorch | ConvMeanPool | false | 15,754 | [
"MIT"
] | 412 | 5bb0b729809152d9129ef72a9dd28b3ff83021a2 | https://github.com/justaboutlola/improved-wgan-pytorch/tree/5bb0b729809152d9129ef72a9dd28b3ff83021a2 |
SinkhornDistance | import torch
import torch.utils.data
class SinkhornDistance(torch.nn.Module):
"""
Given two empirical measures each with :math:`P_1` locations
:math:`x\\in\\mathbb{R}^{D_1}` and :math:`P_2` locations :math:`y\\in\\mathbb{R}^{D_2}`,
outputs an approximation of the regularized OT cost for po... | 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... | yjh0410/actionformer_release | SinkhornDistance | false | 16,855 | [
"MIT"
] | 61 | 7a97422111d3e29c8d2e14088c850c6975855ea7 | https://github.com/yjh0410/actionformer_release/tree/7a97422111d3e29c8d2e14088c850c6975855ea7 |
AutoEncoder | import torch
import torch.nn as nn
import torch.utils.data
class AutoEncoder(nn.Module):
def __init__(self, num_question, k):
""" Initialize a class AutoEncoder.
:param num_question: int
:param k: int
"""
super(AutoEncoder, self).__init__()
self.g = nn.Linear(num_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | harryye930/ML-Performance-Prediction | AutoEncoder | false | 3,580 | [
"MIT"
] | 0 | 82fac16da3c2dde6054cf5b579aa6864e9d37b30 | https://github.com/harryye930/ML-Performance-Prediction/tree/82fac16da3c2dde6054cf5b579aa6864e9d37b30 |
AddReadout | # 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... | DazhiZhong/MiDaS | AddReadout | false | 11,378 | [
"MIT"
] | 0 | e8bafa9c0cf6d2a9d940d2dc36f0ea28a75e5809 | https://github.com/DazhiZhong/MiDaS/tree/e8bafa9c0cf6d2a9d940d2dc36f0ea28a75e5809 |
GetMask | # 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... | NoteXYX/ACL2017 | GetMask | false | 14,118 | [
"Apache-2.0"
] | 119 | 436f59f2aa0044a9d57c95a2a58b2158cb99738d | https://github.com/NoteXYX/ACL2017/tree/436f59f2aa0044a9d57c95a2a58b2158cb99738d |
MHAttention | import math
import torch
from torch import nn
import torch.nn.functional as F
class MHAttention(nn.Module):
def __init__(self, ninp, nhead, dropout):
super(MHAttention, self).__init__()
if ninp % nhead != 0:
raise ValueError(
'The hidden size is not a multiple of the n... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | microsoft/Protein-Folding | MHAttention | false | 7,226 | [
"MIT"
] | 1 | f534b2dd1e3f192fbcdadf234f25828c7f458a58 | https://github.com/microsoft/Protein-Folding/tree/f534b2dd1e3f192fbcdadf234f25828c7f458a58 |
LinearMaxPoolLinearModel | import torch
import torch.nn as nn
class LinearMaxPoolLinearModel(nn.Module):
def __init__(self) ->None:
super().__init__()
self.lin1 = nn.Linear(4, 4, bias=False)
self.lin1.weight = nn.Parameter(torch.eye(4, 4))
self.pool1 = nn.MaxPool1d(4)
self.lin2 = nn.Linear(1, 1, 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
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | sagnik/captum | LinearMaxPoolLinearModel | false | 4,351 | [
"BSD-3-Clause"
] | 0 | d6b663745ee6c01f072a4358233dec381324c283 | https://github.com/sagnik/captum/tree/d6b663745ee6c01f072a4358233dec381324c283 |
ActorCritic | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
from torch.distributions import Categorical
class ActorCritic(nn.Module):
def __init__(self):
super().__init__()
self.affine1 = nn.Linear(4, 128)
self.action_head = nn.Linear(128, 2)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | shinoyuki222/torch-light | ActorCritic | false | 16,425 | [
"MIT"
] | 310 | 4799805d9bcae82a9f12a574dcf9fdd838c92ee9 | https://github.com/shinoyuki222/torch-light/tree/4799805d9bcae82a9f12a574dcf9fdd838c92ee9 |
ResnetBlockGroupNormConv1d | import torch
import torch.nn as nn
class GroupNorm1d(nn.Module):
""" Group normalization that does per-point group normalization.
Args:
groups (int): number of groups
f_dim (int): feature dimension, mush be divisible by groups
"""
def __init__(self, groups, f_dim, eps=1e-05, affine=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
from torch._inductor.runtime.... | taconite/MetaAvatar-release | ResnetBlockGroupNormConv1d | false | 16,526 | [
"MIT"
] | 60 | c9403a478ee82232633d25f65f108befd21d04e9 | https://github.com/taconite/MetaAvatar-release/tree/c9403a478ee82232633d25f65f108befd21d04e9 |
PermEqui1_max | import torch
import torch.nn as nn
class PermEqui1_max(nn.Module):
def __init__(self, in_dim, out_dim):
super(PermEqui1_max, self).__init__()
self.Gamma = nn.Linear(in_dim, out_dim)
def forward(self, x):
xm, _ = x.max(1, keepdim=True)
x = self.Gamma(x - xm)
return x
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | haoruilee/DeepSets | PermEqui1_max | false | 15,497 | [
"Apache-2.0"
] | 213 | b405dd6b51a34fb1ef622e25e6685b417b7b7cbb | https://github.com/haoruilee/DeepSets/tree/b405dd6b51a34fb1ef622e25e6685b417b7b7cbb |
AtteMatchLay | import torch
import torch.nn as nn
from torch.nn.functional import cosine_similarity
def multi_perspective_expand_for_2D(in_tensor, decompose_params):
"""
Return: [batch_size, decompse_dim, dim]
"""
in_tensor = in_tensor.unsqueeze(1)
decompose_params = decompose_params.unsqueeze(0)
return torc... | 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... | Gromy1211/torch-light | AtteMatchLay | false | 11,459 | [
"MIT"
] | 0 | c7d7a9bc5ab1eab03d800a27d9325859516f01e6 | https://github.com/Gromy1211/torch-light/tree/c7d7a9bc5ab1eab03d800a27d9325859516f01e6 |
ConvMeanPool | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | justaboutlola/improved-wgan-pytorch | ConvMeanPool | false | 15,754 | [
"MIT"
] | 412 | 5bb0b729809152d9129ef72a9dd28b3ff83021a2 | https://github.com/justaboutlola/improved-wgan-pytorch/tree/5bb0b729809152d9129ef72a9dd28b3ff83021a2 |
CustomConv2d | import torch
import torch.nn as nn
class CustomConv2d(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, stride=1,
padding=None, bias=True, residual_init=True):
super(CustomConv2d, self).__init__()
self.residual_init = residual_init
if padding is 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | ChiragCD/NR-GAN | CustomConv2d | false | 13,480 | [
"MIT"
] | 54 | fc455c6219b09bc8bf605715504b78b2bb801e48 | https://github.com/ChiragCD/NR-GAN/tree/fc455c6219b09bc8bf605715504b78b2bb801e48 |
StandardNorm | import torch
import torch.nn as nn
class StandardNorm(nn.Module):
def __init__(self, mean, std):
super(StandardNorm, self).__init__()
self.mean = mean
self.std = std
def forward(self, x):
return (x - self.mean) / self.std
def inverse(self, x):
return x * self.std... | 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... | iclementine/speedyspeech | StandardNorm | false | 10,406 | [
"BSD-3-Clause"
] | 0 | db527587a3699b71082d61c9e9fad7ed795d1980 | https://github.com/iclementine/speedyspeech/tree/db527587a3699b71082d61c9e9fad7ed795d1980 |
DenseGCNConv | import math
import torch
from torch.nn import Parameter
import torch.utils.data
def glorot(tensor):
if tensor is not None:
stdv = math.sqrt(6.0 / (tensor.size(-2) + tensor.size(-1)))
tensor.data.uniform_(-stdv, stdv)
def zeros(tensor):
if tensor is not None:
tensor.data.fill_(0)
cl... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | pwycl/pytorch_geometric | DenseGCNConv | false | 10,782 | [
"MIT"
] | 0 | ef7b1add2bb5a36a3a68cae7639c42000f629cac | https://github.com/pwycl/pytorch_geometric/tree/ef7b1add2bb5a36a3a68cae7639c42000f629cac |
CosineEnvelope | import torch
import numpy as np
import torch.nn as nn
class CosineEnvelope(nn.Module):
def __init__(self, cutoff):
super().__init__()
self.cutoff = cutoff
def forward(self, d):
output = 0.5 * (torch.cos(np.pi * d / self.cutoff) + 1)
exclude = d >= self.cutoff
output[e... | 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... | ClintvanHoesel/MXMNet_adapted | CosineEnvelope | false | 305 | [
"MIT"
] | 0 | 091aae4a664b5b0944dfe95dbd2f5da441541437 | https://github.com/ClintvanHoesel/MXMNet_adapted/tree/091aae4a664b5b0944dfe95dbd2f5da441541437 |
ThreeLayerCNN | # 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
asser... | Bhaskers-Blu-Org1/Trusted-ML-Pipelines | ThreeLayerCNN | false | 7,783 | [
"Apache-2.0"
] | 13 | 3805a2e72f73cef318e1992eee70aeb319b06d1a | https://github.com/Bhaskers-Blu-Org1/Trusted-ML-Pipelines/tree/3805a2e72f73cef318e1992eee70aeb319b06d1a |
QRLoss | # 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.triton_helpers import math as tl_math
from torch.nn... | LaudateCorpus1/torchgeo | QRLoss | false | 2,498 | [
"MIT"
] | 0 | 747a9352b9663e7d0e0c90a8b53533f0bb06c9b3 | https://github.com/LaudateCorpus1/torchgeo/tree/747a9352b9663e7d0e0c90a8b53533f0bb06c9b3 |
h_sigmoid | import torch
import torch.nn as nn
class h_sigmoid(nn.Module):
def __init__(self, inplace=True, h_max=1):
super(h_sigmoid, self).__init__()
self.relu = nn.ReLU6(inplace=inplace)
self.h_max = h_max
def forward(self, x):
return self.relu(x + 3) * self.h_max / 6
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | rahulmangalampalli/esvit | h_sigmoid | false | 12,917 | [
"MIT"
] | 0 | 5caf6e36b088ae2e7aaa4100b307eec991078e3e | https://github.com/rahulmangalampalli/esvit/tree/5caf6e36b088ae2e7aaa4100b307eec991078e3e |
LayerNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | UT-Austin-RPL/maple | LayerNorm | false | 18,042 | [
"MIT"
] | 9 | aef9fe9869945df5bbd1b02fd40813aac135cf5a | https://github.com/UT-Austin-RPL/maple/tree/aef9fe9869945df5bbd1b02fd40813aac135cf5a |
SpatialPyramidPooling | # 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... | SekiroRong/YOLOP | SpatialPyramidPooling | false | 5,819 | [
"MIT"
] | 1 | e59628925dfaadfa549790cd0cf1c8a7e1139a2c | https://github.com/SekiroRong/YOLOP/tree/e59628925dfaadfa549790cd0cf1c8a7e1139a2c |
SelfAttentionGPT2 | # 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.... | jplasser/former | SelfAttentionGPT2 | false | 15,749 | [
"MIT"
] | 674 | 7dabf7b355e94f2f0af966bd0daead539a30675a | https://github.com/jplasser/former/tree/7dabf7b355e94f2f0af966bd0daead539a30675a |
GatedConv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.utils
import torch.distributions
assert_size_s... | Butters-cloud/denoising-normalizing-flow | GatedConv2d | false | 7,828 | [
"MIT"
] | 12 | 12d56a0d069e10a744acabf5e78fdbfba8df54ee | https://github.com/Butters-cloud/denoising-normalizing-flow/tree/12d56a0d069e10a744acabf5e78fdbfba8df54ee |
Network | # 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_... | ExileExodus/Deep-Reinforcement-Learning | Network | false | 9,014 | [
"MIT"
] | 0 | 0007e5c4b74e920c250a15c18762966e1b55c17d | https://github.com/ExileExodus/Deep-Reinforcement-Learning/tree/0007e5c4b74e920c250a15c18762966e1b55c17d |
ShuffleCat | # 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... | tony23545/yolact_edge | ShuffleCat | false | 10,921 | [
"MIT"
] | 0 | 11840512ab46f22dce6aea37a7823110175adffa | https://github.com/tony23545/yolact_edge/tree/11840512ab46f22dce6aea37a7823110175adffa |
ConvRelu | import torch
import torch.utils.data
import torch.nn as nn
import torch.backends.cudnn
class ConvRelu(nn.Module):
"""3x3 convolution followed by ReLU activation building block."""
def __init__(self, num_in, num_out):
super().__init__()
self.block = nn.Conv2d(num_in, num_out, kernel_size=3, pa... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | HugoPopo/robosat.pink | ConvRelu | false | 2,349 | [
"MIT"
] | 0 | daa6a0cd6dff68103b9bcc78a8c9a15d8912c42d | https://github.com/HugoPopo/robosat.pink/tree/daa6a0cd6dff68103b9bcc78a8c9a15d8912c42d |
PatchEmbed | # 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 itertools import chain as chain
import torch.utils.data
import torch.nn as ... | billcai/SlowFast | PatchEmbed | false | 1,562 | [
"Apache-2.0"
] | 0 | 778888e63351e55861801996b37c7ff9a3746587 | https://github.com/billcai/SlowFast/tree/778888e63351e55861801996b37c7ff9a3746587 |
MuLawDecoding | import torch
from torch import Tensor
import torchaudio.functional as F
class MuLawDecoding(torch.nn.Module):
"""Decode mu-law encoded signal. For more info see the
`Wikipedia Entry <https://en.wikipedia.org/wiki/%CE%9C-law_algorithm>`_
This expects an input with values between 0 and quantization_channe... | 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... | Nayef211/audio | MuLawDecoding | false | 11,745 | [
"BSD-2-Clause"
] | 0 | 241ab1e8284e589262f510ee9411baf2bc374ded | https://github.com/Nayef211/audio/tree/241ab1e8284e589262f510ee9411baf2bc374ded |
ResidualBlock_noBN | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.init as init
def initialize_weights(net_l, scale=1):
if not isinstance(net_l, list):
net_l = [net_l]
for net in net_l:
for m in net.modules():
if isinstance(m, nn.Conv2d):
init.kaimin... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | YingqiLiulll/scrips_for_SR | ResidualBlock_noBN | false | 1,306 | [
"MIT"
] | 0 | 04fa6fdaf157e913d3e2521cd80315a10a2ccedc | https://github.com/YingqiLiulll/scrips_for_SR/tree/04fa6fdaf157e913d3e2521cd80315a10a2ccedc |
SimpleEncoder | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from torch import Tensor
import torch.nn as nn
assert_size_stride = ... | doiken23/mccformers.pytorch | SimpleEncoder | false | 6,590 | [
"MIT"
] | 1 | 678bd9448e3a2f35bd408e8c8e510e0ea1f9a19f | https://github.com/doiken23/mccformers.pytorch/tree/678bd9448e3a2f35bd408e8c8e510e0ea1f9a19f |
ScaledDotProductAttentionMemory | # 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.... | CurryYuan/X-Trans2Cap | ScaledDotProductAttentionMemory | false | 7,951 | [
"Apache-2.0"
] | 11 | c78a27209f14fcbbec74fe8b5edc06faea2e7d44 | https://github.com/CurryYuan/X-Trans2Cap/tree/c78a27209f14fcbbec74fe8b5edc06faea2e7d44 |
SqueezeExcite | import torch
import torch.nn as nn
from torch.nn import functional as F
import torch.utils.data.distributed
def _make_divisible(v, divisor, min_value=None):
"""
This function is taken from the original tf repo.
It ensures that all layers have a channel number that is divisible by 8
It can be seen here... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | Erfun76/insightface | SqueezeExcite | false | 9,279 | [
"MIT"
] | 0 | 148cef36a43a055f68d2b6a475f4aa38625ad8b4 | https://github.com/Erfun76/insightface/tree/148cef36a43a055f68d2b6a475f4aa38625ad8b4 |
AE | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn
class AE(nn.Module):
def __init__(self, num_channels):
super(AE, self).__init__()
self.enc1 = nn.Conv2d(num_channels, 64, kernel_size=3, padding=1)
self.enc2 = nn.Conv2d(64, 32, kernel_size=3, padding=1)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | ahanagemini/Phd_final_year_old_sr | AE | false | 3,045 | [
"BSD-2-Clause"
] | 0 | 62be9d1294acdb724a2fe424789b657a44e2cd7d | https://github.com/ahanagemini/Phd_final_year_old_sr/tree/62be9d1294acdb724a2fe424789b657a44e2cd7d |
InstanceNorm2dPlus | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | henryaddison/score_sde_pytorch | InstanceNorm2dPlus | false | 12,500 | [
"Apache-2.0"
] | 0 | be07c3a3346bf8ceadabf6a3b436db5d5c3d0252 | https://github.com/henryaddison/score_sde_pytorch/tree/be07c3a3346bf8ceadabf6a3b436db5d5c3d0252 |
CriticDownAction | import torch
import torch.nn as nn
import torch.nn.functional as F
class MLPBase(nn.Module):
def __init__(self, num_inputs, num_outputs):
super(MLPBase, self).__init__()
self.l1 = nn.Linear(num_inputs, 400)
self.l2 = nn.Linear(400, 300)
self.l3 = nn.Linear(300, num_outputs)
d... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | yangfanthu/modular-rl | CriticDownAction | false | 13,145 | [
"BSD-2-Clause"
] | 0 | 25c599bab641a7e732dbaf116cd240fa2358f113 | https://github.com/yangfanthu/modular-rl/tree/25c599bab641a7e732dbaf116cd240fa2358f113 |
Simplenet | # 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.optim.lr_scheduler... | Chih-Ling-Hsu/distiller | Simplenet | false | 13,543 | [
"Apache-2.0"
] | 94 | 33d1697298c6e3a7f7bfa615741fd0cda61d2794 | https://github.com/Chih-Ling-Hsu/distiller/tree/33d1697298c6e3a7f7bfa615741fd0cda61d2794 |
ToRGB | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.autograd import Function
import math
import torch.nn as nn
import tor... | cyysc1998/EDVRDarts | ToRGB | false | 6,523 | [
"MIT"
] | 1 | 201badbc8c6469b519647a8869c3782ebe1176cf | https://github.com/cyysc1998/EDVRDarts/tree/201badbc8c6469b519647a8869c3782ebe1176cf |
BCELoss2d | # 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... | ForrestPi/SegDL | BCELoss2d | false | 5,166 | [
"MIT"
] | 1 | 56f2ff229dfa7540704d6de50292c724693aac75 | https://github.com/ForrestPi/SegDL/tree/56f2ff229dfa7540704d6de50292c724693aac75 |
CoxPHLossSorted | # 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 Tens... | gabrielasuchopar/pycox | CoxPHLossSorted | false | 3,511 | [
"BSD-2-Clause"
] | 0 | e4ea5f0ee26c6d3e3a468f164de2b7c426376e99 | https://github.com/gabrielasuchopar/pycox/tree/e4ea5f0ee26c6d3e3a468f164de2b7c426376e99 |
AsymmetricLoss | # 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... | JiYuanFeng/mmclassification | AsymmetricLoss | false | 13,883 | [
"Apache-2.0"
] | 1,190 | b337ef1f11b85148cca4b6fb0c4da3f8cc2eede6 | https://github.com/JiYuanFeng/mmclassification/tree/b337ef1f11b85148cca4b6fb0c4da3f8cc2eede6 |
torch_uint8_to_float | import torch
class torch_uint8_to_float(torch.nn.Module):
def __init__(self):
super(torch_uint8_to_float, self).__init__()
def forward(self, x):
return x.permute(2, 0, 1).unsqueeze(0).contiguous()
def get_inputs():
return [torch.rand([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... | ozendelait/pytorch-semseg | torch_uint8_to_float | false | 7,440 | [
"MIT"
] | 1 | 200491febd653bd26befcd5b3d52c614aa832b7e | https://github.com/ozendelait/pytorch-semseg/tree/200491febd653bd26befcd5b3d52c614aa832b7e |
DQfDNetwork | # 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.... | DPS0340/DQNDemo | DQfDNetwork | false | 17,459 | [
"MIT"
] | 8 | 5b57159ea8ff8a6b127cb18ff28da6696b40665b | https://github.com/DPS0340/DQNDemo/tree/5b57159ea8ff8a6b127cb18ff28da6696b40665b |
ScoringFunction | # 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... | sunwhawhang/headpose-fsanet-pytorch | ScoringFunction | false | 4,473 | [
"MIT"
] | 0 | d37d39dbff649b2f607367f35d9eadba2fea18f7 | https://github.com/sunwhawhang/headpose-fsanet-pytorch/tree/d37d39dbff649b2f607367f35d9eadba2fea18f7 |
SplitAndConcat | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | sstsai-adl/d2go | SplitAndConcat | false | 16,488 | [
"Apache-2.0"
] | 687 | 6cff773797b14698043589afe57ea67cd76286f9 | https://github.com/sstsai-adl/d2go/tree/6cff773797b14698043589afe57ea67cd76286f9 |
ShuffleBlock | # 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... | ORNL/AADL | ShuffleBlock | false | 17,757 | [
"BSD-3-Clause"
] | 6 | 8a509676d0a0a78f1f334a3dc93e92721cfcfe90 | https://github.com/ORNL/AADL/tree/8a509676d0a0a78f1f334a3dc93e92721cfcfe90 |
CNNHead | # 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_... | baseballChatbot7/KBO_MRC | CNNHead | false | 6,316 | [
"MIT"
] | 1 | ad11318d785bacdf29a12adfd25afe90d7ff2779 | https://github.com/baseballChatbot7/KBO_MRC/tree/ad11318d785bacdf29a12adfd25afe90d7ff2779 |
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.... | jinjiren/ParlAI | TransformerEncoderLayer | false | 12,626 | [
"MIT"
] | 0 | 40799aeee69f2a0bb25a1341bb8da0c44861268e | https://github.com/jinjiren/ParlAI/tree/40799aeee69f2a0bb25a1341bb8da0c44861268e |
Hidden2DiscreteDeal | # 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.... | justinchiu/NeuralDialog | Hidden2DiscreteDeal | false | 3,790 | [
"Apache-2.0"
] | 0 | f272cc2e12ffdd44c94263ee373208a22c057129 | https://github.com/justinchiu/NeuralDialog/tree/f272cc2e12ffdd44c94263ee373208a22c057129 |
LearnedKernel | # 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... | AayushGrover/ViscaNet | LearnedKernel | false | 7,541 | [
"MIT"
] | 1 | 41786e10b84f2264b638567bdce1c189c1b66b00 | https://github.com/AayushGrover/ViscaNet/tree/41786e10b84f2264b638567bdce1c189c1b66b00 |
ClassAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | sithu31296/image_classification | ClassAttention | false | 16,462 | [
"MIT"
] | 57 | 6b8cbce96100225621cee3166a73e852ba216cc3 | https://github.com/sithu31296/image_classification/tree/6b8cbce96100225621cee3166a73e852ba216cc3 |
BasicBlock | import torch
import torch.nn as nn
def conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=dilation, groups=groups, bias=True, dilation=dilation)
class BasicBlock(nn.Module):
expansion = 1
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 torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | columbia-robovision/SSCNav | BasicBlock | false | 6,469 | [
"MIT"
] | 1 | 0e781a350cddb68c499402d6468ad1adcfb1759d | https://github.com/columbia-robovision/SSCNav/tree/0e781a350cddb68c499402d6468ad1adcfb1759d |
Norm | import torch
import torch.nn as nn
class Norm(nn.Module):
def __init__(self, dim_seq, input_size, eps=1e-06):
super().__init__()
self.size = input_size
self.seq = dim_seq
self.alpha = nn.Parameter(torch.ones((self.size, self.seq)))
self.bias = nn.Parameter(torch.zeros((sel... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | mingweima/hintplaygame | Norm | false | 4,003 | [
"MIT"
] | 0 | 31f35a22111a2e5e7e5d8e90f92326bc784c5fe7 | https://github.com/mingweima/hintplaygame/tree/31f35a22111a2e5e7e5d8e90f92326bc784c5fe7 |
TracedModule | # 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.quantization
import torch.onnx
import torch.nn.parallel
import tor... | Nayef211/tutorials | TracedModule | false | 9,536 | [
"BSD-3-Clause"
] | 0 | faf2c476fc3be855051fbea3cce77eaf7b2a2175 | https://github.com/Nayef211/tutorials/tree/faf2c476fc3be855051fbea3cce77eaf7b2a2175 |
MarginDisparityDiscrepancy | import torch
from typing import Optional
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
def shift_log(x: 'torch.Tensor', offset: 'Optional[float]'=1e-06
) ->torch.Tensor:
"""
First shift, then ca... | 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 typing import Opt... | NiteshBharadwaj/ignoringhumanpose | MarginDisparityDiscrepancy | false | 916 | [
"MIT"
] | 0 | 1fb7a063fded9cff18f7de4e1d71845983077256 | https://github.com/NiteshBharadwaj/ignoringhumanpose/tree/1fb7a063fded9cff18f7de4e1d71845983077256 |
Upsampler | import math
import torch
import torch.utils.data
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 = ... | 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.utils.data
from torchvision.transforms import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | RyanMoussouni/iSeeBetter | Upsampler | false | 14,345 | [
"MIT"
] | 327 | af193ae0852f8e477fcd6875dce874eb5092a24a | https://github.com/RyanMoussouni/iSeeBetter/tree/af193ae0852f8e477fcd6875dce874eb5092a24a |
Aggregator | # 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.... | FANTASTPATR/STST | Aggregator | false | 465 | [
"Apache-2.0"
] | 0 | 8f969fcfe31f9555b19e783fb14eecf72def4122 | https://github.com/FANTASTPATR/STST/tree/8f969fcfe31f9555b19e783fb14eecf72def4122 |
ScaledDotProductAttention | # 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.... | Prasath2001/commonsense-rl | ScaledDotProductAttention | false | 2,731 | [
"Apache-2.0"
] | 0 | ef3e83270d34cf211b2d2086120cccae0621477b | https://github.com/Prasath2001/commonsense-rl/tree/ef3e83270d34cf211b2d2086120cccae0621477b |
SKL | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | Raiselimit/TorchBlocks | SKL | false | 5,749 | [
"MIT"
] | 1 | a5baecb9a2470ff175087475630f2b7db3f7ef51 | https://github.com/Raiselimit/TorchBlocks/tree/a5baecb9a2470ff175087475630f2b7db3f7ef51 |
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.... | TaoRuijie/TalkNet_ASD | attentionLayer | false | 14,460 | [
"MIT"
] | 79 | 4a2bc4859ee192ab450eaf63937a799212f2b021 | https://github.com/TaoRuijie/TalkNet_ASD/tree/4a2bc4859ee192ab450eaf63937a799212f2b021 |
MultiscaleRecLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | eezkni/UEGAN | MultiscaleRecLoss | false | 15,288 | [
"MIT"
] | 73 | a6616ac559819d487cae0f301d98cf2922a11a09 | https://github.com/eezkni/UEGAN/tree/a6616ac559819d487cae0f301d98cf2922a11a09 |
AttentionPool2d | # 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.... | Jinsu-L/KELIP | AttentionPool2d | false | 5,418 | [
"Apache-2.0"
] | 1 | d3261cbb9ba3c3ad474dd560a5add8b69ed78477 | https://github.com/Jinsu-L/KELIP/tree/d3261cbb9ba3c3ad474dd560a5add8b69ed78477 |
Encoder | # 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... | benedictquartey/modified-wm | Encoder | false | 3,212 | [
"MIT"
] | 0 | bc6cab1aadff24f4be8bb7b9c183b6ef266cf8ba | https://github.com/benedictquartey/modified-wm/tree/bc6cab1aadff24f4be8bb7b9c183b6ef266cf8ba |
TorchClampOptionMaxMin | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | PogChamper/torch2trt | TorchClampOptionMaxMin | false | 14,283 | [
"MIT"
] | 3,363 | 43b12627ec0de4d212efb6d02b07570205085ccc | https://github.com/PogChamper/torch2trt/tree/43b12627ec0de4d212efb6d02b07570205085ccc |
Critic | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.autograd
class Critic(nn.Module):
def __init__(self, input_size, hidden_size, output_size):
super(Critic, self).__init__()
self.linear1 = nn.Linear(input_size, hidden_size)
self.linear2 = nn.Linear(hidden_size... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | vivekagra/Biplane-Quadrotor | Critic | false | 10,896 | [
"BSD-3-Clause"
] | 0 | afe69216494842f5bfe16cbcc0cdcc6ef0de7769 | https://github.com/vivekagra/Biplane-Quadrotor/tree/afe69216494842f5bfe16cbcc0cdcc6ef0de7769 |
ChannelRate | import torch
import torch.nn as nn
class ChannelRate(nn.Module):
rates: 'torch.Tensor'
def __init__(self, num_channels: 'int', device=None, dtype=None):
super().__init__()
kw = {'device': device, 'dtype': dtype}
self.rates = nn.Parameter(torch.ones(num_channels, **kw))
def forwar... | 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... | YodaEmbedding/deep-compression | ChannelRate | false | 1,271 | [
"MIT"
] | 0 | cc1ea691921fbe2e5cffeb30a02b777dadd08700 | https://github.com/YodaEmbedding/deep-compression/tree/cc1ea691921fbe2e5cffeb30a02b777dadd08700 |
GDL | # 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 numpy as np
from torch import nn
import torch.nn.functional
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_str... | BRAIN-Lab-UNC/BrainExtraction-TissueSegmentation-Macaque | GDL | false | 13,370 | [
"MIT"
] | 770 | b5329035d9e32c8a27151cf2396eaf209396a334 | https://github.com/BRAIN-Lab-UNC/BrainExtraction-TissueSegmentation-Macaque/tree/b5329035d9e32c8a27151cf2396eaf209396a334 |
ResidualNetworkSegment | import torch
import torch.nn as nn
import torch.nn.functional as F
class ResidualNetworkSegment(nn.Module):
"""Modified ResidualNetworkSegment model class"""
def __init__(self, block, num_blocks, width, depth):
super(ResidualNetworkSegment, self).__init__()
assert (depth - 4
) % 4... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | Arjung27/DeepThinking | ResidualNetworkSegment | false | 16,967 | [
"MIT"
] | 6 | 13a2ce534bcb0b9379a22fffef52d975d650adb2 | https://github.com/Arjung27/DeepThinking/tree/13a2ce534bcb0b9379a22fffef52d975d650adb2 |
RegModel | import torch
import torch.nn as nn
class RegModel(nn.Module):
def __init__(self, input_size):
super(RegModel, self).__init__()
self.fc1 = nn.Linear(input_size, 50)
self.relu1 = nn.ReLU()
self.dout = nn.Dropout(0.2)
self.fc2 = nn.Linear(50, 100)
self.prelu = nn.PReL... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | amperie/user-models | RegModel | false | 3,092 | [
"Apache-2.0"
] | 0 | 5236c50d0f20a7bac81acc5d1936a3502de2f5f3 | https://github.com/amperie/user-models/tree/5236c50d0f20a7bac81acc5d1936a3502de2f5f3 |
RefModel2d | import torch
import torch.nn.functional as F
class RefModel2d(torch.nn.Module):
"""The 2D reference model."""
def __init__(self):
super().__init__()
self.l1 = torch.nn.Conv2d(2, 2, 3, stride=2, bias=False, padding=1,
padding_mode='reflect')
self.l2 = torch.nn.BatchNorm2d(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.... | shuohan/pytorch-layers | RefModel2d | false | 4,341 | [
"MIT"
] | 0 | 020846fd02d501cf477552179c19ba4b5e9a0695 | https://github.com/shuohan/pytorch-layers/tree/020846fd02d501cf477552179c19ba4b5e9a0695 |
DiceLoss | # 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 collections
from typing import Optional
from typing import Union
from typing import Any
from typing import Callable
from typing impor... | Alxaline/MONAI | DiceLoss | false | 4,856 | [
"Apache-2.0"
] | 1 | 6b8fdf9db7f13ed7d88d605155a0463840abcbf2 | https://github.com/Alxaline/MONAI/tree/6b8fdf9db7f13ed7d88d605155a0463840abcbf2 |
RepeatModule | # 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.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | opti-mix/glow | RepeatModule | false | 7,376 | [
"Apache-2.0"
] | 1 | 4ba074df5da9822986a23a6679ab592c22660f6d | https://github.com/opti-mix/glow/tree/4ba074df5da9822986a23a6679ab592c22660f6d |
GatedConnection | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim
class GatedConnection(nn.Module):
def __init__(self, d_model):
super().__init__()
self.w = nn.Linear(d_model * 2, d_model, True)
def forward(self, t1, t2):
g = F.sigmoid(self.w(torch.cat([t1, t2], -... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.optim
assert_size_stride = torch._C._dynamo.g... | Blickwinkel1107/NJUNMT-pytorch | GatedConnection | false | 17,022 | [
"MIT"
] | 9 | 82f684fe768b137ca0649b7b79a1820077917385 | https://github.com/Blickwinkel1107/NJUNMT-pytorch/tree/82f684fe768b137ca0649b7b79a1820077917385 |
RNN | # 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.... | chauhankartik/DeepLearning-EarlySteps | RNN | false | 6,420 | [
"MIT"
] | 1 | 44b0189cf6e81f8032a6a80cc33ff80496ebd462 | https://github.com/chauhankartik/DeepLearning-EarlySteps/tree/44b0189cf6e81f8032a6a80cc33ff80496ebd462 |
KaggleAccuracy | import torch
from torch import Tensor
from torch import nn
class KaggleAccuracy(nn.Module):
def __init__(self, threshold: 'float'=0.25, num_patches: 'int'=38, size:
'int'=418) ->None:
super().__init__()
self.threshold = threshold
self.num_patches = num_patches
self.patch_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 import Tensor
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | AlessandroRuzzi/Computational-Intelligence-Lab-2021 | KaggleAccuracy | false | 14 | [
"MIT"
] | 0 | ed9dae37618e0ca2f01c4e336df4354e77e00c1f | https://github.com/AlessandroRuzzi/Computational-Intelligence-Lab-2021/tree/ed9dae37618e0ca2f01c4e336df4354e77e00c1f |
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