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 |
|---|---|---|---|---|---|---|---|---|---|---|
LocallyConnected | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.as... | atong01/Graphical-modelling-continuous-time | LocallyConnected | false | 3,142 | [
"MIT"
] | 0 | f1c8d9bc30a44c38fd504e4cce2f7886fc352f92 | https://github.com/atong01/Graphical-modelling-continuous-time/tree/f1c8d9bc30a44c38fd504e4cce2f7886fc352f92 |
ConvNet | import torch
import torch.nn as nn
import torch.nn.functional as F
class ConvNet(nn.Module):
"""Small ConvNet for CONIC."""
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(3, 6, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(6, 16, 5)
self.fc1 =... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | citelab/fastsync | ConvNet | false | 1,721 | [
"Apache-2.0"
] | 0 | 8e2166f87fc53479b57fef536a971c3a2e6e4309 | https://github.com/citelab/fastsync/tree/8e2166f87fc53479b57fef536a971c3a2e6e4309 |
TrueDynamics | # 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
... | Alfo5123/ConcreteDropout | TrueDynamics | false | 16,868 | [
"MIT"
] | 7 | c442871553e20a2de078c0fbac7fa52302d50abf | https://github.com/Alfo5123/ConcreteDropout/tree/c442871553e20a2de078c0fbac7fa52302d50abf |
TransformerLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | HarryPham0123/FPT_data_centric_competition | TransformerLayer | false | 5,278 | [
"Apache-2.0"
] | 1 | 3fa1e0ac48fdae2649b639229d9a74f75e461878 | https://github.com/HarryPham0123/FPT_data_centric_competition/tree/3fa1e0ac48fdae2649b639229d9a74f75e461878 |
ReLU | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from abc import abstractmethod
import torch.utils.data
import torch... | zijian-hu/pytorchvideo | ReLU | false | 4,697 | [
"Apache-2.0"
] | 0 | 51589b100437af2285c56ce2ccc7ccecb7f9b18b | https://github.com/zijian-hu/pytorchvideo/tree/51589b100437af2285c56ce2ccc7ccecb7f9b18b |
Gate | # 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... | hansd410/mnemonic | Gate | false | 3,567 | [
"BSD-3-Clause"
] | 0 | 409508d08da7f5d5940ffb56fd9715e6ef1e68a3 | https://github.com/hansd410/mnemonic/tree/409508d08da7f5d5940ffb56fd9715e6ef1e68a3 |
QNetwork | import torch
import torch.nn as nn
import torch.nn.functional as F
def weights_init_(m):
if isinstance(m, nn.Linear):
torch.nn.init.xavier_uniform_(m.weight, gain=1)
torch.nn.init.constant_(m.bias, 0)
class QNetwork(nn.Module):
def __init__(self, num_inputs, num_actions, hidden_dim):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | QwQ2000/E2GAN | QNetwork | false | 8,668 | [
"MIT"
] | 34 | f27b715362de4459129206217d100ae5b6cf82c8 | https://github.com/QwQ2000/E2GAN/tree/f27b715362de4459129206217d100ae5b6cf82c8 |
Net | import torch
import torch.nn as nn
import torch.nn.functional as F
class DeepMind(nn.Module):
def __init__(self):
super(DeepMind, self).__init__()
self.conv1 = nn.Conv2d(4, 32, 8, stride=4)
self.conv2 = nn.Conv2d(32, 64, 4, stride=2)
self.conv3 = nn.Conv2d(64, 32, 3, stride=1)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | TianhongDai/Self_Imitation_Learning | Net | false | 15,270 | [
"MIT"
] | 61 | e49003582fa3d875495d84682f2a3332d4922dbc | https://github.com/TianhongDai/Self_Imitation_Learning/tree/e49003582fa3d875495d84682f2a3332d4922dbc |
CrossAttention | # 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.... | LoveEachDay/towhee | CrossAttention | false | 11,661 | [
"Apache-2.0"
] | 0 | 513c9c2626676cadaaf0a16ac3c828d96bec91a1 | https://github.com/LoveEachDay/towhee/tree/513c9c2626676cadaaf0a16ac3c828d96bec91a1 |
SourceContextGate | # 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 ... | ESCM-summarization/ESCM-summary-evaluation | SourceContextGate | false | 9,118 | [
"MIT"
] | 0 | 3780b51f0ed44cbbea3f163a871d875f1e5e9393 | https://github.com/ESCM-summarization/ESCM-summary-evaluation/tree/3780b51f0ed44cbbea3f163a871d875f1e5e9393 |
MulScalarNegative | import torch
import torch.nn as nn
from torch.quantization import QuantStub
from torch.quantization import DeQuantStub
class MulScalarNegative(nn.Module):
def __init__(self):
super().__init__()
self.float_op = nn.quantized.FloatFunctional()
self.quant = QuantStub()
self.dequant = ... | 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.quantization import QuantStub
from torch.quantization import DeQuantStub
assert_size_stride = torch._C._dyn... | Leslie-Fang/incubator-tvm | MulScalarNegative | false | 9,290 | [
"Apache-2.0"
] | 0 | aa035f4650926f5e714b02cbab6d974f0a17352f | https://github.com/Leslie-Fang/incubator-tvm/tree/aa035f4650926f5e714b02cbab6d974f0a17352f |
NormedConv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | Bo396543018/mmdetection | NormedConv2d | false | 7,794 | [
"Apache-2.0"
] | 16 | eb337336d3c239dc1d20534496f69df41ae9a300 | https://github.com/Bo396543018/mmdetection/tree/eb337336d3c239dc1d20534496f69df41ae9a300 |
NeuralModel | import torch
import torch.nn as nn
class NeuralModel(nn.Module):
def __init__(self, input):
super(NeuralModel, self).__init__()
self.dense1 = nn.Linear(in_features=input, out_features=128)
self.dense2 = nn.Linear(in_features=128, out_features=16)
self.dense3 = nn.Linear(in_feature... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | sumitsharmamanit/Facial-emotion-recognition | NeuralModel | false | 10,806 | [
"Apache-2.0"
] | 0 | f95770c0cfabd46a8f9589eb415ce69eaeaea4c6 | https://github.com/sumitsharmamanit/Facial-emotion-recognition/tree/f95770c0cfabd46a8f9589eb415ce69eaeaea4c6 |
SigmaL1SmoothLoss | import torch
import torch.nn as nn
from typing import *
class SigmaL1SmoothLoss(nn.Module):
def forward(self, output, target):
reg_diff = torch.abs(target - output)
reg_loss = torch.where(torch.le(reg_diff, 1 / 9), 4.5 * torch.pow(
reg_diff, 2), reg_diff - 1 / 18)
return reg_l... | 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
... | LaurenSpiegel/fastai_docs | SigmaL1SmoothLoss | false | 753 | [
"Apache-2.0"
] | 0 | 4fe6b62116d88dea9610548133e6cadb6b260a73 | https://github.com/LaurenSpiegel/fastai_docs/tree/4fe6b62116d88dea9610548133e6cadb6b260a73 |
TripletLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from 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... | awesome-archive/CAIL2019 | TripletLoss | false | 14,912 | [
"MIT"
] | 300 | 31e917752676ad77d247a47e04f17a8f9ea68721 | https://github.com/awesome-archive/CAIL2019/tree/31e917752676ad77d247a47e04f17a8f9ea68721 |
JS_Divergence | # 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... | loveorchids/omni_torch | JS_Divergence | false | 7,126 | [
"Apache-2.0"
] | 1 | 9bd654387619c0cbc6aee9e91482ecc9200138ef | https://github.com/loveorchids/omni_torch/tree/9bd654387619c0cbc6aee9e91482ecc9200138ef |
Linear | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
def keep_variance_fn(x):
return x + 0.001
class Linear(nn.Module):
def __init__(self, in_features, out_features, bias=True,
keep_variance_fn=None):
super(Linear, self).__init__()
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.nn.parameter import Parameter
assert_size_strid... | THAKAORI/SalsaNext | Linear | false | 11,916 | [
"MIT"
] | 0 | 855cd7e9ebb83ee62538ba4753a011ada7bbfb6c | https://github.com/THAKAORI/SalsaNext/tree/855cd7e9ebb83ee62538ba4753a011ada7bbfb6c |
predicates1 | import torch
import torch.nn as nn
import torch.nn.functional as func
class predicates1(nn.Module):
def __init__(self, num_predicates, body_len):
super().__init__()
self.weights = nn.Parameter(torch.zeros(body_len, num_predicates).
uniform_(0.0, 0.1))
self.beta = nn.Parameter(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | IBM/LOA | predicates1 | false | 8,277 | [
"MIT"
] | 12 | 9cd402c814f1d9c8b4de52ee18a3cb7ec2c6d07a | https://github.com/IBM/LOA/tree/9cd402c814f1d9c8b4de52ee18a3cb7ec2c6d07a |
CNN | # 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_... | ai-antena/cifar10 | CNN | false | 9,681 | [
"MIT"
] | 0 | a3c72693cffae4a5150f1ca5f19472098163ed1a | https://github.com/ai-antena/cifar10/tree/a3c72693cffae4a5150f1ca5f19472098163ed1a |
GeneralizedMeanPooling | import torch
import torch.nn as nn
class GeneralizedMeanPooling(nn.Module):
"""Applies a 2D power-average adaptive pooling over an input signal composed of several input planes.
The function computed is: :math:`f(X) = pow(sum(pow(X, p)), 1/p)`
- At p = infinity, one gets Max Pooling
- At p = 1... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | AsyaPes/light-reid-master | GeneralizedMeanPooling | false | 8,961 | [
"MIT"
] | 0 | acb4bdd973cdf3832294d8e42442305ab52014f5 | https://github.com/AsyaPes/light-reid-master/tree/acb4bdd973cdf3832294d8e42442305ab52014f5 |
ComplexDropout | import torch
from torch import nn
import torch.utils
class ComplexDropout(nn.Module):
def __init__(self, p=0.5, inplace=False):
super(ComplexDropout, self).__init__()
self.p = p
self.inplace = inplace
self.dropout_r = nn.Dropout(p, inplace)
self.dropout_i = nn.Dropout(p, i... | 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynam... | muqiaoy/dl_signal | ComplexDropout | false | 16,115 | [
"MIT"
] | 54 | 3a30d14982016644bfc96a7d1ca0109b441f17fd | https://github.com/muqiaoy/dl_signal/tree/3a30d14982016644bfc96a7d1ca0109b441f17fd |
EQ | import torch
class EQ(torch.nn.Module):
def __init__(self):
super(EQ, self).__init__()
def forward(self, x, y):
return x == y
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | NVIDIA-AI-IOT-private/torch2trt | EQ | false | 10,502 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
HS | import torch
import torch.nn as nn
class HS(nn.Module):
def __init__(self):
super(HS, self).__init__()
def forward(self, inputs):
clip = torch.clamp(inputs + 3, 0, 6) / 6
return inputs * clip
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
retur... | 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... | BXuan694/basemodel-pytorch | HS | false | 4,878 | [
"MIT"
] | 1 | a36c96904580be902e323db17eebbe2ea1f54176 | https://github.com/BXuan694/basemodel-pytorch/tree/a36c96904580be902e323db17eebbe2ea1f54176 |
Actor | # 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.... | LeonLester/Machin-title-in-progress- | Actor | false | 11,647 | [
"MIT"
] | 0 | 777479d47b520dcdc6b09c247591b5fe1d6cbe8c | https://github.com/LeonLester/Machin-title-in-progress-/tree/777479d47b520dcdc6b09c247591b5fe1d6cbe8c |
ScaledDotProductAttention | # 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.... | YehLi/xmodaler | ScaledDotProductAttention | false | 14,695 | [
"Apache-2.0"
] | 830 | 5340054398c076cfa717317d151ca595c5e37198 | https://github.com/YehLi/xmodaler/tree/5340054398c076cfa717317d151ca595c5e37198 |
GroupedChannelNorm | import torch
import torch.utils.data
import torch
from torch import nn
class GroupedChannelNorm(nn.Module):
def __init__(self, num_groups):
super().__init__()
self.num_groups = num_groups
def forward(self, x):
shape = list(x.shape)
new_shape = [shape[0], self.num_groups, shap... | 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
import torch
from torch import nn
assert_size_stride = ... | guyii54/Contrastive-I2I | GroupedChannelNorm | false | 6,766 | [
"BSD-3-Clause"
] | 1 | e73daa0f9d3770c2280a304c39678d5b22440647 | https://github.com/guyii54/Contrastive-I2I/tree/e73daa0f9d3770c2280a304c39678d5b22440647 |
EncoderLayer | import math
import torch
import torch.nn.functional as F
import torch.nn as nn
def attention(q, k, v, d_k, mask=None, dropout=None):
scores = torch.matmul(q, k.transpose(-2, -1)) / math.sqrt(d_k)
if mask is not None:
mask = mask.unsqueeze(1)
scores = scores.masked_fill(mask == 0, -1000000000.0... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | macg0406/Transformer | EncoderLayer | false | 12,762 | [
"Apache-2.0"
] | 0 | 8c747a6e9f108c63ecc600bf14cde6827b438172 | https://github.com/macg0406/Transformer/tree/8c747a6e9f108c63ecc600bf14cde6827b438172 |
Norm | import torch
import torch.nn as nn
class Norm(nn.Module):
def __init__(self, n_state, axis=-1, epsilon=1e-05):
super().__init__()
self.n_state = n_state
self.g = nn.Parameter(torch.ones([self.n_state]))
self.b = nn.Parameter(torch.zeros([self.n_state]))
self.axis = axis
... | 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_... | Aalanli/MusicGeneration | Norm | false | 5 | [
"MIT"
] | 0 | 7d268322d692013d8ac6e70be31741cea519fa28 | https://github.com/Aalanli/MusicGeneration/tree/7d268322d692013d8ac6e70be31741cea519fa28 |
ResidualBlock_noBN | # 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 ... | YingqiLiulll/scrips_for_SR | ResidualBlock_noBN | false | 1,306 | [
"MIT"
] | 0 | 04fa6fdaf157e913d3e2521cd80315a10a2ccedc | https://github.com/YingqiLiulll/scrips_for_SR/tree/04fa6fdaf157e913d3e2521cd80315a10a2ccedc |
CAM_Module | # 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.... | ayushmankumar7/pytorch-lanenet | CAM_Module | false | 14,940 | [
"MIT"
] | 160 | db9f116ba3f42dbfabf064e4a89ec068e9da4ee4 | https://github.com/ayushmankumar7/pytorch-lanenet/tree/db9f116ba3f42dbfabf064e4a89ec068e9da4ee4 |
SimpleTypeasModel | # 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... | andreas-hommel/glow | SimpleTypeasModel | false | 3,366 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | wfondrie/wefpy | MLP | false | 13,094 | [
"Apache-2.0"
] | 0 | 00691d453048203e1e3b1daea53879067ee4a395 | https://github.com/wfondrie/wefpy/tree/00691d453048203e1e3b1daea53879067ee4a395 |
CMVN | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | hhhaaahhhaa/s3prl | CMVN | false | 15,506 | [
"Apache-2.0"
] | 856 | a469787f05c42196c4d989555082f5fd9dcbe8a6 | https://github.com/hhhaaahhhaa/s3prl/tree/a469787f05c42196c4d989555082f5fd9dcbe8a6 |
Project3D | import torch
import torch.nn as nn
class Project3D(nn.Module):
"""Layer which projects 3D points into a camera with intrinsics K and at position T
"""
def __init__(self, batch_size, height, width, eps=1e-07):
super(Project3D, self).__init__()
self.batch_size = batch_size
self.heig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | Sid1057/sid1057.github.io | Project3D | false | 17,935 | [
"MIT"
] | 4 | 623d1731e308b42b6f86304dcfd671a061b414bf | https://github.com/Sid1057/sid1057.github.io/tree/623d1731e308b42b6f86304dcfd671a061b414bf |
MarginLoss | from torch.nn import Module
import torch
import torch.nn.functional as F
import torch.utils.data
import torch.nn.functional
import torch.autograd
class MarginLoss(Module):
'\n ## Margin loss for class existence\n\n A separate margin loss is used for each output capsule and the total loss is the sum of them.... | 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.nn import Module
... | techthiyanes/annotated_deep_learning_paper_implementations | MarginLoss | false | 16,551 | [
"MIT"
] | 3,714 | 8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 | https://github.com/techthiyanes/annotated_deep_learning_paper_implementations/tree/8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 |
VertexConv | import torch
from torch import nn
class Transform(nn.Module):
"""
A Vertex Transformation module
Permutation invariant transformation: (N, k, d) -> (N, k, d)
"""
def __init__(self, dim_in, k):
"""
:param dim_in: input feature dimension
:param k: k neighbors
"""
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | weiyx15/DHGNN | VertexConv | false | 16,710 | [
"MIT"
] | 124 | 870a1763c34af6ee9a7a3207fed4a5e6bdb95d23 | https://github.com/weiyx15/DHGNN/tree/870a1763c34af6ee9a7a3207fed4a5e6bdb95d23 |
DecoderLayer | import torch
import torch.nn.functional as F
import torch.nn as nn
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.... | AlbertiPot/attention-is-all-you-need-pytorch | DecoderLayer | false | 46 | [
"MIT"
] | 0 | c5ec40907db281b85b3bd7a5dd8016940291add0 | https://github.com/AlbertiPot/attention-is-all-you-need-pytorch/tree/c5ec40907db281b85b3bd7a5dd8016940291add0 |
SSIM | # 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
... | Sid1057/sid1057.github.io | SSIM | false | 17,939 | [
"MIT"
] | 4 | 623d1731e308b42b6f86304dcfd671a061b414bf | https://github.com/Sid1057/sid1057.github.io/tree/623d1731e308b42b6f86304dcfd671a061b414bf |
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
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | Justin-Tan/ffjord | GatedConv2d | false | 693 | [
"MIT"
] | 0 | 2caf8a4ff84933672fe0d94255d665b3dd7a6791 | https://github.com/Justin-Tan/ffjord/tree/2caf8a4ff84933672fe0d94255d665b3dd7a6791 |
MyConv1dPadSame | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
from itertools import product as product
from math import sqrt as sqrt
class MyConv1dPadSame(nn.Module):
"""
extend nn.Conv1d to support SAME padding
"""
def __init__(self, in_channels, out_channels, 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
import torch.nn as nn
import torch.utils.data
from itertools import product as p... | WFDetector/WFDetection | MyConv1dPadSame | false | 2,949 | [
"Apache-2.0"
] | 0 | b16d35b3a3a5de62de9e0bac83eccd21b6358b53 | https://github.com/WFDetector/WFDetection/tree/b16d35b3a3a5de62de9e0bac83eccd21b6358b53 |
ln_mod | import torch
import torch.nn as nn
from torch.nn.parameter import Parameter
class ln_mod(nn.Module):
def __init__(self, nx, eps=1e-05):
super().__init__()
self.eps = eps
self.weight = Parameter(torch.Tensor(nx))
def forward(self, x):
return x / torch.sqrt(torch.std(x, axis=-1... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
from torch.nn.parameter import Parameter
assert_size_stri... | lienghongky/image-gpt2 | ln_mod | false | 12,707 | [
"MIT"
] | 0 | ef9f3c61d4a09cbb75114dd067d0014948e82d7b | https://github.com/lienghongky/image-gpt2/tree/ef9f3c61d4a09cbb75114dd067d0014948e82d7b |
GT | import torch
class GT(torch.nn.Module):
def __init__(self):
super(GT, self).__init__()
def forward(self, x, y):
return x > y
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | NVIDIA-AI-IOT-private/torch2trt | GT | false | 10,511 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
InvConv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
from torch.nn import functional as F
assert_size_stride = t... | HugoSenetaire/glow-pytorch | InvConv2d | false | 577 | [
"MIT"
] | 0 | 7f11be87cac9770df63867910c34738dedee6f56 | https://github.com/HugoSenetaire/glow-pytorch/tree/7f11be87cac9770df63867910c34738dedee6f56 |
Generative_Model | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | frhrdr/MMD-GAN | Generative_Model | false | 10,069 | [
"Apache-2.0"
] | 0 | 7522093498b658026344541ddd5c248095763fb6 | https://github.com/frhrdr/MMD-GAN/tree/7522093498b658026344541ddd5c248095763fb6 |
Actor | import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
def hidden_init(layer):
fan_in = layer.weight.data.size()[0]
lim = 1.0 / np.sqrt(fan_in)
return -lim, lim
class Actor(nn.Module):
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed, f... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | ShirelJosef/deep-reinforcement-learning | Actor | false | 11,884 | [
"MIT"
] | 0 | 63979b975c71e730c9d4c66e39efac210260dd18 | https://github.com/ShirelJosef/deep-reinforcement-learning/tree/63979b975c71e730c9d4c66e39efac210260dd18 |
FocalLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
class FocalLoss(nn.Module):
def __init__(self, gamma=2):
super().__init__()
self.gamma = gamma
def forward(self, input, target):
if not target.size() == input.size():
raise ValueError(
'Tar... | 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... | OctThe16th/COMP-652-FinalProject | FocalLoss | false | 2,712 | [
"MIT"
] | 0 | 00b8a2328516d8ca76d365004c753a91cc426b30 | https://github.com/OctThe16th/COMP-652-FinalProject/tree/00b8a2328516d8ca76d365004c753a91cc426b30 |
ActFirstResBlock | import torch
import torch.nn.functional as F
from torch import nn
class AdaptiveInstanceNorm2d(nn.Module):
def __init__(self, num_features, eps=1e-05, momentum=0.1):
super(AdaptiveInstanceNorm2d, self).__init__()
self.num_features = num_features
self.eps = eps
self.momentum = mome... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | cplusx/SIGN | ActFirstResBlock | false | 1,754 | [
"Apache-2.0"
] | 0 | 9777fc3ddd4c6f799caeefe1e72482d5b1ecd8ae | https://github.com/cplusx/SIGN/tree/9777fc3ddd4c6f799caeefe1e72482d5b1ecd8ae |
BatchNormNode | # 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_... | BrandonKates/graph-convnet-tsp | BatchNormNode | false | 11,259 | [
"MIT"
] | 0 | f6e17e84311c23fd5cab041b7a27b4e0636c44f8 | https://github.com/BrandonKates/graph-convnet-tsp/tree/f6e17e84311c23fd5cab041b7a27b4e0636c44f8 |
MOTION_Channel_ReplaceBlock | # 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.parallel
import torch.optim
import torch
import torch.nn as nn
a... | RongchangLi/DEN | MOTION_Channel_ReplaceBlock | false | 17,866 | [
"MIT"
] | 4 | f8b744f96a3a68cf0784080ffd561a5279715727 | https://github.com/RongchangLi/DEN/tree/f8b744f96a3a68cf0784080ffd561a5279715727 |
MatchRNNAttention | # 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.... | jamaalhay/Final_Proj | MatchRNNAttention | false | 15,673 | [
"MIT"
] | 104 | 3f524a90fee5a3cb21466ab76f630d060792045d | https://github.com/jamaalhay/Final_Proj/tree/3f524a90fee5a3cb21466ab76f630d060792045d |
AdaptiveCatAvgMaxPool2d | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
import torchvision... | Hhhhhhao/pytorch-image-models | AdaptiveCatAvgMaxPool2d | false | 5,302 | [
"Apache-2.0"
] | 1 | 9cc7dda6e5fcbbc7ac5ba5d2d44050d2a8e3e38d | https://github.com/Hhhhhhao/pytorch-image-models/tree/9cc7dda6e5fcbbc7ac5ba5d2d44050d2a8e3e38d |
SoftDiceLossSquared | # 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._C
import torch.serialization
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strid... | dkswxd/Swin-Transformer-Semantic-Segmentation | SoftDiceLossSquared | false | 1,851 | [
"Apache-2.0"
] | 0 | 6af19736e5492a01d8952d4ee86a6d59b21c2ae1 | https://github.com/dkswxd/Swin-Transformer-Semantic-Segmentation/tree/6af19736e5492a01d8952d4ee86a6d59b21c2ae1 |
Attention | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.nn.functional as F
class Attention(nn.Module):
EPS = 1e-08
def __init__(self, options, weights=None):
super(Attention, self).__init__()
self.n_encoder = options['n_encoder']
self.n_decoder = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | KaiQiangSong/joint_parse_summ | Attention | false | 8,799 | [
"BSD-3-Clause"
] | 29 | 5d4a40d9a681bc8b06c847643d810846f3867216 | https://github.com/KaiQiangSong/joint_parse_summ/tree/5d4a40d9a681bc8b06c847643d810846f3867216 |
ConvBlock | import torch
from torch import nn
class ConvBlock(torch.nn.Module):
def __init__(self, input_size, output_size, kernel_size, stride,
padding, bias=True):
super(ConvBlock, self).__init__()
self.conv = torch.nn.Conv2d(input_size, output_size, kernel_size,
stride, padding, bias=b... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | Holmes-Alan/RefVAE | ConvBlock | false | 8,262 | [
"MIT"
] | 13 | 836b8f1168f1b0f923b609a48e202ace7806f79c | https://github.com/Holmes-Alan/RefVAE/tree/836b8f1168f1b0f923b609a48e202ace7806f79c |
PolicyNet | # 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_... | johntiger1/vaal_querying | PolicyNet | false | 6,981 | [
"BSD-2-Clause"
] | 1 | c20da3b0b5ca9f25334523f831d0ba8a11f710ca | https://github.com/johntiger1/vaal_querying/tree/c20da3b0b5ca9f25334523f831d0ba8a11f710ca |
wide_basic | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils
import torch.utils.data
assert_size_str... | Silent-Zebra/JEM | wide_basic | false | 17,933 | [
"Apache-2.0"
] | 6 | 33440aff8429d9a24a8ba858d0209f4b48be8e05 | https://github.com/Silent-Zebra/JEM/tree/33440aff8429d9a24a8ba858d0209f4b48be8e05 |
ShuffleCatChunk | import torch
import torch.nn as nn
class ShuffleCatChunk(nn.Module):
def forward(self, a, b):
assert a.size() == b.size()
_n, c, _h, _w = a.size()
a = torch.chunk(a, chunks=c, dim=1)
b = torch.chunk(b, chunks=c, dim=1)
x = [None] * (c * 2)
x[::2] = a
x[1::2... | 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 | ShuffleCatChunk | false | 10,916 | [
"MIT"
] | 0 | 11840512ab46f22dce6aea37a7823110175adffa | https://github.com/tony23545/yolact_edge/tree/11840512ab46f22dce6aea37a7823110175adffa |
TreeCRF | # 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
from torch.nn.parameter import Parameter
assert_size_strid... | krishnamrith12/DCST | TreeCRF | false | 12,779 | [
"MIT"
] | 0 | 7ba956d7e648aaeb25816ccfc709106db9293270 | https://github.com/krishnamrith12/DCST/tree/7ba956d7e648aaeb25816ccfc709106db9293270 |
Net | import torch
import torch.nn.functional as F
class Net(torch.nn.Module):
def __init__(self):
super(Net, self).__init__()
self.l1 = torch.nn.Linear(784, 512)
self.l2 = torch.nn.Linear(512, 256)
self.l3 = torch.nn.Linear(256, 128)
self.l4 = torch.nn.Linear(128, 64)
s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C... | jobsfan/pytorch | Net | false | 6,972 | [
"Apache-2.0"
] | 1 | 221ae8e3673f8d2fbf0a58f40a30553c76084831 | https://github.com/jobsfan/pytorch/tree/221ae8e3673f8d2fbf0a58f40a30553c76084831 |
BahdanauAttn | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class BahdanauAttn(nn.Module):
def __init__(self, context_size, hidden_size):
super(BahdanauAttn, self).__init__()
self.hidden_size = hidden_size
self.context_size = context_size
self.attn_h = nn.Linear... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Eurus-Holmes/VAG-NMT | BahdanauAttn | false | 8,082 | [
"Apache-2.0"
] | 12 | 38095c4a5477a0e7e2fa1592e8401aa9cddf2beb | https://github.com/Eurus-Holmes/VAG-NMT/tree/38095c4a5477a0e7e2fa1592e8401aa9cddf2beb |
Conv3BN | # 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 ... | jayden-chua/image-mask | Conv3BN | false | 3,698 | [
"MIT"
] | 0 | ce2c6a32bf13df582e7b57e506d58518258be292 | https://github.com/jayden-chua/image-mask/tree/ce2c6a32bf13df582e7b57e506d58518258be292 |
EntropicLoss | from torch.nn import Module
import torch
from torch import Tensor
from typing import Callable
from typing import Union
from abc import ABC
def _format_float(value: 'float') ->str:
"""
>>> _format_float(1)
'1'
>>> _format_float(1.0)
'1.'
>>> _format_float(1e-4)
'1.0000e-04'
"""
tens... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch.nn import Module
from torch import Tensor
from typing import C... | vishalbelsare/pfhedge | EntropicLoss | false | 16,681 | [
"MIT"
] | 81 | 4d7ff173995e0795942bc6ec55f3fdc5bfb7a5f1 | https://github.com/vishalbelsare/pfhedge/tree/4d7ff173995e0795942bc6ec55f3fdc5bfb7a5f1 |
ASPP | # 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... | DoggyLiu0116/MamboNet | ASPP | false | 5,113 | [
"MIT"
] | 1 | 3b708091422491f660c4bd5eb12b06ce3b8a5f79 | https://github.com/DoggyLiu0116/MamboNet/tree/3b708091422491f660c4bd5eb12b06ce3b8a5f79 |
PVABlock | # 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.... | YacobBY/vedastr | PVABlock | false | 1,268 | [
"Apache-2.0"
] | 0 | 2353780489b58d2398b9af49d238ef0df3f45f2a | https://github.com/YacobBY/vedastr/tree/2353780489b58d2398b9af49d238ef0df3f45f2a |
ResidualAttentionBlock | import torch
from collections import OrderedDict
from torch import nn
class LayerNorm(nn.Module):
def __init__(self, hidden_size, eps=1e-12):
"""Construct a layernorm module in the TF style (epsilon inside the square root).
"""
super(LayerNorm, self).__init__()
self.weight = nn.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
from torch._inductor.runtime.... | abhisheklalwani/ActionCLIP | ResidualAttentionBlock | false | 14,760 | [
"MIT"
] | 141 | dd2ab27db4bf3d5be3a51cd011cb49aa8b679de0 | https://github.com/abhisheklalwani/ActionCLIP/tree/dd2ab27db4bf3d5be3a51cd011cb49aa8b679de0 |
PRelu | import torch
from torch import nn
import torch.onnx
class PRelu(nn.Module):
def forward(self, X: 'torch.Tensor', slope: 'torch.Tensor'):
return torch.clamp(X, min=0) + torch.clamp(X, max=0) * slope
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 import nn
import torch.onnx
assert_size_stride = torch._C._dynamo.guards.asser... | Piteryo/onnx2pytorch | PRelu | false | 9,448 | [
"Apache-2.0"
] | 0 | c25b3a5289ee7073d644d280a112c15382b7f690 | https://github.com/Piteryo/onnx2pytorch/tree/c25b3a5289ee7073d644d280a112c15382b7f690 |
netmodel | # 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 numpy as np
from torch.nn import Parameter
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch... | uber-common/safemutations | netmodel | false | 16,634 | [
"MIT"
] | 91 | 40e5fd03a244f89bf157d4bedf79201e706aedc1 | https://github.com/uber-common/safemutations/tree/40e5fd03a244f89bf157d4bedf79201e706aedc1 |
SIMPA | # 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
from torch.nn.parameter import Parameter
assert_size_strid... | SherylHYX/SSSNET_Signed_Clustering | SIMPA | false | 17,918 | [
"MIT"
] | 5 | 85736c18e86b396d64177d22b8c7f9859dfd794c | https://github.com/SherylHYX/SSSNET_Signed_Clustering/tree/85736c18e86b396d64177d22b8c7f9859dfd794c |
FC_Q | import torch
import torch.nn as nn
import torch.nn.functional as F
class FC_Q(nn.Module):
def __init__(self, state_dim, num_actions):
super(FC_Q, self).__init__()
self.q1 = nn.Linear(state_dim, 256)
self.q2 = nn.Linear(256, 256)
self.q3 = nn.Linear(256, num_actions)
self.i... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | hotaekjoo/SQV | FC_Q | false | 12,510 | [
"MIT"
] | 0 | d725342e7fd8548ee5fa018e5ccac4542969deed | https://github.com/hotaekjoo/SQV/tree/d725342e7fd8548ee5fa018e5ccac4542969deed |
ChanLayerNorm | import torch
import torch.nn as nn
class ChanLayerNorm(nn.Module):
"""Channelwise LayerNorm"""
def __init__(self, d: 'int', **kwargs):
super().__init__()
self.ln = nn.LayerNorm(d, **kwargs)
def forward(self, x):
x = self.ln(x.permute(0, 2, 3, 1))
return x.permute(0, 3, 1,... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | arampacha/generative_models | ChanLayerNorm | false | 1,470 | [
"Apache-2.0"
] | 0 | 34f5a2fc760bbd7f9f9a956d8d8670c9746e5152 | https://github.com/arampacha/generative_models/tree/34f5a2fc760bbd7f9f9a956d8d8670c9746e5152 |
C3D | import torch
import torch.nn as nn
import torch.nn
class C3D(nn.Module):
"""
The C3D network as described in [1].
"""
def __init__(self):
super(C3D, self).__init__()
self.conv1 = nn.Conv3d(3, 64, kernel_size=(3, 3, 3), padding=(1, 1, 1))
self.pool1 = nn.MaxPool3d(kernel_size=(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | kar98kbang/c3d-pytorch | C3D | false | 4,143 | [
"MIT"
] | 0 | 22b3564798cb9249ad6fdb6c9d929bff3fdfa567 | https://github.com/kar98kbang/c3d-pytorch/tree/22b3564798cb9249ad6fdb6c9d929bff3fdfa567 |
PoolingF | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.data
impo... | bomtorazek/contrastive-unpaired-translation | PoolingF | false | 12,186 | [
"BSD-3-Clause"
] | 0 | 07c048038375e1b9a4e464154b8dbc49f5e16ede | https://github.com/bomtorazek/contrastive-unpaired-translation/tree/07c048038375e1b9a4e464154b8dbc49f5e16ede |
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.... | sabernn/vit-pytorch | AttentionHead | false | 4,227 | [
"MIT"
] | 0 | 21a2671aa92adb941a56ae629f6089f550949fb2 | https://github.com/sabernn/vit-pytorch/tree/21a2671aa92adb941a56ae629f6089f550949fb2 |
ConvNCFBPRLoss | # 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
... | BELIEVEfxy/LightSANs | ConvNCFBPRLoss | false | 7,769 | [
"MIT"
] | 17 | 94ce7e59d144dbc787153b8c486cad334790ec6e | https://github.com/BELIEVEfxy/LightSANs/tree/94ce7e59d144dbc787153b8c486cad334790ec6e |
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
from torch._inductor.runtime.... | aishikawa/drl-impl | ActorNetwork | false | 9,694 | [
"MIT"
] | 0 | 1afe7426494cd94990cb4dae247486a25dfe37bf | https://github.com/aishikawa/drl-impl/tree/1afe7426494cd94990cb4dae247486a25dfe37bf |
BertPreTrainingHeads | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
from to... | kimihitosugiyama/text_analysis | BertPreTrainingHeads | false | 3,841 | [
"Apache-2.0"
] | 0 | 8f51022957928c31e52af1e0fd407daca3addb40 | https://github.com/kimihitosugiyama/text_analysis/tree/8f51022957928c31e52af1e0fd407daca3addb40 |
SimmatModule | import torch
class SimmatModule(torch.nn.Module):
def __init__(self, padding=-1):
super().__init__()
self.padding = padding
self._hamming_index_loaded = None
self._hamming_index = None
def forward(self, query_embed, doc_embed, query_tok, doc_tok):
simmat = []
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | gitter-badger/FlexNeuART | SimmatModule | false | 15,447 | [
"Apache-2.0"
] | 101 | f69e5421bdebe9db0d993b5470dace61872f90df | https://github.com/gitter-badger/FlexNeuART/tree/f69e5421bdebe9db0d993b5470dace61872f90df |
Value | # 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 ... | dragen1860/TRPO-Pytorch | Value | false | 6,597 | [
"MIT"
] | 1 | c5a8e5ac890ec50e331db12fd5885dd4fb753a3b | https://github.com/dragen1860/TRPO-Pytorch/tree/c5a8e5ac890ec50e331db12fd5885dd4fb753a3b |
LayerNorm | import torch
import torch.nn as nn
class LayerNorm(nn.Module):
"""Norm to 0-mean 1-std , then do a learned diagonal affine transform."""
def __init__(self, features, eps=1e-05):
super(LayerNorm, self).__init__()
self.scale = nn.Parameter(torch.ones(features))
self.shift = nn.Parameter... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | mzz235711/IAM | LayerNorm | false | 12,884 | [
"Apache-2.0"
] | 0 | e42c2b766442b666224b107b671eeab65f9b8efd | https://github.com/mzz235711/IAM/tree/e42c2b766442b666224b107b671eeab65f9b8efd |
ConvModule | # 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.... | Five-Hundred-Years-Ago/StreamingTransformer | ConvModule | false | 9,091 | [
"Apache-2.0"
] | 0 | fdaace64ed786bbdaeea2b9f44e96f9403ef98fe | https://github.com/Five-Hundred-Years-Ago/StreamingTransformer/tree/fdaace64ed786bbdaeea2b9f44e96f9403ef98fe |
SEModule | import torch
from torchvision import datasets as datasets
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data.distributed
class FastAvgPool2d(nn.Module):
def __init__(self, flatten=False):
super(FastAvgPool2d, self).__init__()
self.flatten = flatten
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._inductor.runtime import triton_helpers
from torchvision import datas... | adam-dziedzic/ASL | SEModule | false | 12,113 | [
"MIT"
] | 0 | cc063f5e7eda1498544ad2c3b224985203b0774a | https://github.com/adam-dziedzic/ASL/tree/cc063f5e7eda1498544ad2c3b224985203b0774a |
GroupNorm2D | import torch
import torch.nn as nn
class GroupNorm2D(nn.Module):
def __init__(self, num_channels, num_groups=4, epsilon=1e-05):
super(GroupNorm2D, self).__init__()
self.num_channels = num_channels
self.num_groups = num_channels // 4
self.epsilon = epsilon
self.gamma = nn.P... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | HarmanDotpy/Normalizations-in-Deep-Learning | GroupNorm2D | false | 528 | [
"MIT"
] | 0 | 3e1899837fb3ba625f515ef1a995f3573b65456d | https://github.com/HarmanDotpy/Normalizations-in-Deep-Learning/tree/3e1899837fb3ba625f515ef1a995f3573b65456d |
ClassHead | # 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.nn
assert_size_stride = torch._C._dynamo.guard... | ZongqingHou/Pytorch_Retinaface | ClassHead | false | 3,074 | [
"MIT"
] | 0 | 6284b7158a0d9d3d4a2cc267a393c21863a1b938 | https://github.com/ZongqingHou/Pytorch_Retinaface/tree/6284b7158a0d9d3d4a2cc267a393c21863a1b938 |
h_sigmoid | import torch
import torch.nn as nn
class h_sigmoid(nn.Module):
def __init__(self, inplace=True):
super(h_sigmoid, self).__init__()
self.relu = nn.ReLU6(inplace=inplace)
def forward(self, x):
return self.relu(x + 3) / 6
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def g... | 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... | EileenWang90/mmpose | h_sigmoid | false | 2,173 | [
"Apache-2.0"
] | 0 | 3fa1328a3b6351bf9b35df60d4d959973a6f8a71 | https://github.com/EileenWang90/mmpose/tree/3fa1328a3b6351bf9b35df60d4d959973a6f8a71 |
HSigmoid | import torch
import torch.utils.data
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.functional
import torch.optim
import torch.nn.parallel
import torch.utils.data.distributed
class HSigmoid(nn.Module):
""" Applies the Hard-Sigmoid function element-wise.
`"Searching for Mob... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
import torch
import torch.nn as nn
import torch.nn.functional
imp... | PhelaPoscam/SRGAN-PyTorch | HSigmoid | false | 942 | [
"Apache-2.0"
] | 0 | c1c68707dbddd1130b2ea71023df748080bcbd52 | https://github.com/PhelaPoscam/SRGAN-PyTorch/tree/c1c68707dbddd1130b2ea71023df748080bcbd52 |
RMSPool | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
assert_s... | cleverhans-lab/model-extraction-iclr | RMSPool | false | 1,724 | [
"MIT"
] | 0 | 805205287876423621baca9d5e990edfe68ea803 | https://github.com/cleverhans-lab/model-extraction-iclr/tree/805205287876423621baca9d5e990edfe68ea803 |
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.... | AnoushkaVyas/TextOutlierDetection | SelfAttention | false | 52 | [
"MIT"
] | 0 | 290a6800262090998d32c8bbd311e3d53737e2cd | https://github.com/AnoushkaVyas/TextOutlierDetection/tree/290a6800262090998d32c8bbd311e3d53737e2cd |
ImageTransformationNet | # 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.... | rileypsmith/Fast-Style-Transfer | ImageTransformationNet | false | 4,244 | [
"MIT"
] | 0 | 8b2164f8bc6d63530f914610b6c5c5c1b0f4ffd5 | https://github.com/rileypsmith/Fast-Style-Transfer/tree/8b2164f8bc6d63530f914610b6c5c5c1b0f4ffd5 |
Conv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | tuxedcat/A2C | Conv | false | 10,890 | [
"Apache-2.0"
] | 0 | 4a6686af05667f8760f2731f184e1845a2d11c6f | https://github.com/tuxedcat/A2C/tree/4a6686af05667f8760f2731f184e1845a2d11c6f |
CosAttention | import torch
import torch.nn as nn
class CosAttention(nn.Module):
def __init__(self):
super(CosAttention, self).__init__()
def forward(self, q, k, v):
"""
q: (batchsize, hidden_dim)
k: (batchsize, seqlen, hidden_dim)
v: (batchsize, seqlen, hidden_dim)
"""
... | 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... | lonePatient/TorchBlocks | CosAttention | false | 15,956 | [
"MIT"
] | 82 | 4a65d746cc8a396cb7df73ed4644d97ddf843e29 | https://github.com/lonePatient/TorchBlocks/tree/4a65d746cc8a396cb7df73ed4644d97ddf843e29 |
AUXModule | import torch
import torch.nn.functional as F
import torch.nn as nn
class AUXModule(nn.Module):
def __init__(self, in_features, out_features):
super().__init__()
self.linear = nn.Linear(in_features, out_features)
def forward(self, x):
x = F.adaptive_max_pool2d(x, output_size=(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
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | KeremTurgutlu/fast-kaggle | AUXModule | false | 17,535 | [
"Apache-2.0"
] | 8 | 0ea341b44a58da2dfb606a0ae32bac166985b49e | https://github.com/KeremTurgutlu/fast-kaggle/tree/0ea341b44a58da2dfb606a0ae32bac166985b49e |
FunctionalConv3d | import torch
class FunctionalConv3d(torch.nn.Module):
def __init__(self, *args, **kwargs):
super().__init__()
self.conv = torch.nn.Conv3d(*args, **kwargs)
def forward(self, x):
x = torch.nn.functional.conv3d(x, self.conv.weight, self.conv.bias,
self.conv.stride, self.conv... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
reinterpret_tens... | NVIDIA-AI-IOT-private/torch2trt | FunctionalConv3d | false | 10,519 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
poly | import torch
import numpy as np
import torch.nn as nn
import torch.utils.data
class poly(nn.Module):
"""Polynomial activation function.
degreelist: list of powers of the polynomial.
"""
def __init__(self, degreelist):
super(poly, self).__init__()
self.degreelist = degreelist
... | 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
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strid... | cjbumgardner/HE_for_Medical_Data | poly | false | 6,458 | [
"MIT"
] | 1 | 248dcd8b48924fe1f6edbeee4e16282d4a31069a | https://github.com/cjbumgardner/HE_for_Medical_Data/tree/248dcd8b48924fe1f6edbeee4e16282d4a31069a |
Loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | Airpooyan/FaceRecognition | Loss | false | 4,800 | [
"Apache-2.0"
] | 1 | 5bd5b14d46635ee5972fd556c103533193469d86 | https://github.com/Airpooyan/FaceRecognition/tree/5bd5b14d46635ee5972fd556c103533193469d86 |
LatentPredModel | # 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_... | BoyuanChen/neural-state-variables | LatentPredModel | false | 7,827 | [
"MIT"
] | 17 | 10483d93ac8c006f3786c434fb57d70d9ab465ec | https://github.com/BoyuanChen/neural-state-variables/tree/10483d93ac8c006f3786c434fb57d70d9ab465ec |
SpatialGroupEnhance | # 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
from torch.nn import init
assert_size_stride = torch._C._d... | LeftAttention/Attention-Codebase | SpatialGroupEnhance | false | 17,598 | [
"Apache-2.0"
] | 6 | 348ec66233a7c0f95a3cb5f0f11641e2a7a9b9c3 | https://github.com/LeftAttention/Attention-Codebase/tree/348ec66233a7c0f95a3cb5f0f11641e2a7a9b9c3 |
DuelingNet | # 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... | moriaki3193/Torch26 | DuelingNet | false | 7,271 | [
"MIT"
] | 1 | fb75f6b6bb07c63fedb03fad7b647837eb40db2e | https://github.com/moriaki3193/Torch26/tree/fb75f6b6bb07c63fedb03fad7b647837eb40db2e |
SIMSE | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.utils.checkpoint
assert_size_stride = torch._C._dynamo... | Wang-Chuanyu/MMSA | SIMSE | false | 5,955 | [
"MIT"
] | 1 | 2a720530c369e68656102287edb651780e827135 | https://github.com/Wang-Chuanyu/MMSA/tree/2a720530c369e68656102287edb651780e827135 |
FCN_Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import numpy as np
from torch... | ilcessadecalcular/segmentation | FCN_Net | false | 10,767 | [
"MIT"
] | 0 | 24ba499a399efdba212ec5e2235b72ed8270cc24 | https://github.com/ilcessadecalcular/segmentation/tree/24ba499a399efdba212ec5e2235b72ed8270cc24 |
TransformerDecoderLayer | # 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 | TransformerDecoderLayer | false | 12,635 | [
"MIT"
] | 0 | 40799aeee69f2a0bb25a1341bb8da0c44861268e | https://github.com/jinjiren/ParlAI/tree/40799aeee69f2a0bb25a1341bb8da0c44861268e |
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