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 |
|---|---|---|---|---|---|---|---|---|---|---|
SimpleMaxModule | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleMaxModule(torch.nn.Module):
def __init__(self):
super(SimpleMaxModule, self).__init__()
def forward(self, a, b):
return torch.max(a + a, b + b)
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([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
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.... | YaronBenAtar/glow | SimpleMaxModule | false | 14,677 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
MeanAggregator | # 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... | angpo/VKD | MeanAggregator | false | 14,850 | [
"MIT"
] | 68 | 2a136e00dad4c73612d6efe087675604ac2416eb | https://github.com/angpo/VKD/tree/2a136e00dad4c73612d6efe087675604ac2416eb |
VAE | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
import torch.onnx
import torch.optim
import torch.utils.data.distributed
import torch.nn.functional as F
import torch.autograd
class VAE(nn.Module):
def __init__(self):
super(VAE, self).__init__()
self.fc1 = nn.Li... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | angelajiang/examples | VAE | false | 9,732 | [
"BSD-3-Clause"
] | 0 | 9964d6bd97a93420f101ebcdc40f8bd540930956 | https://github.com/angelajiang/examples/tree/9964d6bd97a93420f101ebcdc40f8bd540930956 |
FC1 | # 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_... | Po-Chun-Chien/LUT-Net | FC1 | false | 11,787 | [
"MIT"
] | 0 | 413559027980db2585d939cd4a514a172b62f57d | https://github.com/Po-Chun-Chien/LUT-Net/tree/413559027980db2585d939cd4a514a172b62f57d |
BertPSIHead | from _paritybench_helpers import _mock_config
import torch
from torch import nn
class BertPSIHead(nn.Module):
def __init__(self, config):
super().__init__()
self.transform = nn.Linear(config.hidden_size, config.hidden_size)
self.activation = nn.Tanh()
self.decoder = nn.Linear(conf... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | gitlost-murali/awesome-align | BertPSIHead | false | 3,548 | [
"BSD-3-Clause"
] | 0 | 39fb45ca85a98e005447bddb52c48e65ce7d399b | https://github.com/gitlost-murali/awesome-align/tree/39fb45ca85a98e005447bddb52c48e65ce7d399b |
TensorSigmoid | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | Ilyabasharov/torch2trt | TensorSigmoid | false | 2,540 | [
"MIT"
] | 0 | 76bf298b3da408509665e23e2494922b131afb10 | https://github.com/Ilyabasharov/torch2trt/tree/76bf298b3da408509665e23e2494922b131afb10 |
HyperDecoder | import torch
import torch.nn as nn
import torch.nn.functional as F
class HyperDecoder(nn.Module):
def __init__(self, input_dim, outputdim=None):
super(HyperDecoder, self).__init__()
self.input_dim = input_dim
self.fc1 = nn.Linear(input_dim, input_dim)
self.fc2 = nn.Linear(input_di... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | LXie502/point_based_pcgc | HyperDecoder | false | 2,488 | [
"MIT"
] | 0 | 9c4b577d35276c8674b568efc0b9d2473bb00a70 | https://github.com/LXie502/point_based_pcgc/tree/9c4b577d35276c8674b568efc0b9d2473bb00a70 |
GaussianKernel | import torch
from typing import Optional
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
import torch.utils.data.distributed
import torch.optim
class GaussianKernel(nn.Module):
"""Gaussian Kernel Matrix
Gaussian Kernel k is defined by
.. math::
k(x_1, x_2) = \\exp \\left( ... | 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... | mstoelzle/Transfer-Learning-Library | GaussianKernel | false | 12,876 | [
"MIT"
] | 0 | 7d5022668cbe6d1bedbc7c386d44b9d89c272d6b | https://github.com/mstoelzle/Transfer-Learning-Library/tree/7d5022668cbe6d1bedbc7c386d44b9d89c272d6b |
KL_Loss | import torch
from torch import nn
import torch.nn.functional as F
import torch.utils
class KL_Loss(nn.Module):
def __init__(self, temperature=1):
super(KL_Loss, self).__init__()
self.T = temperature
def forward(self, output_batch, teacher_outputs):
output_batch = F.log_softmax(output... | 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 ... | Little0o0/FedML | KL_Loss | false | 5,551 | [
"Apache-2.0"
] | 1 | 720015c90fcfec88d465a81b1e8fb45676dce9fb | https://github.com/Little0o0/FedML/tree/720015c90fcfec88d465a81b1e8fb45676dce9fb |
CriticNet | # 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_... | cugzj/Adaptive-B | CriticNet | false | 6,492 | [
"Apache-2.0"
] | 1 | cebc965b1dbad93332ae371bfef8640259d940c4 | https://github.com/cugzj/Adaptive-B/tree/cebc965b1dbad93332ae371bfef8640259d940c4 |
VectorQuantizeLayer_GB | # 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... | jefflai108/Self-Supervised-Speech-Pretraining-and-Representation-Learning | VectorQuantizeLayer_GB | false | 6,934 | [
"MIT"
] | 1 | bb8df008397d5a0360ab7d4b68e91588ed648270 | https://github.com/jefflai108/Self-Supervised-Speech-Pretraining-and-Representation-Learning/tree/bb8df008397d5a0360ab7d4b68e91588ed648270 |
BertPooler | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class BertPooler(nn.Module):
def __init__(self, config):
super(BertPooler, self).__init__()
self.dense = nn.Linear(config.hidden_size, config.hidden_size)
self.activation = nn.Tanh()
def forward(self, hi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | Ago3/VLP | BertPooler | false | 9,952 | [
"Apache-2.0"
] | 0 | 4dec0e04b8592f4a74fe66c253dbb92574e7e2ba | https://github.com/Ago3/VLP/tree/4dec0e04b8592f4a74fe66c253dbb92574e7e2ba |
ChannelPool | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch._C
import torch.serialization
assert_size_stride = tor... | pprp/mmsegmentation | ChannelPool | false | 12,902 | [
"Apache-2.0"
] | 0 | 5d615401358dea2d6527a033bef505a9c7e0f034 | https://github.com/pprp/mmsegmentation/tree/5d615401358dea2d6527a033bef505a9c7e0f034 |
Sin | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_... | HJReachability/safety_rl | Sin | false | 17,329 | [
"BSD-3-Clause"
] | 5 | 00b441b41cea2a5062ffdc4ac30903b51364c2f9 | https://github.com/HJReachability/safety_rl/tree/00b441b41cea2a5062ffdc4ac30903b51364c2f9 |
MultipleRegression | # 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... | jiruifu-jerry0219/UpperLimbEstimator | MultipleRegression | false | 10,277 | [
"Apache-2.0"
] | 0 | d62deef93419934dcb33e43707dd0634a235fb9a | https://github.com/jiruifu-jerry0219/UpperLimbEstimator/tree/d62deef93419934dcb33e43707dd0634a235fb9a |
TV_L2Loss | # 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.... | JaguAroo/SRResCGAN | TV_L2Loss | false | 629 | [
"MIT"
] | 0 | 9aac612aff631f7fb9142e0a36de9559cfc1a62d | https://github.com/JaguAroo/SRResCGAN/tree/9aac612aff631f7fb9142e0a36de9559cfc1a62d |
GraphConv | # 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
import torch.autograd
assert_size_stride = ... | CompileException/kaolin | GraphConv | false | 5,033 | [
"ECL-2.0",
"Apache-2.0"
] | 1 | 8b14752453956a57a4bf6295d49889518835f7a9 | https://github.com/CompileException/kaolin/tree/8b14752453956a57a4bf6295d49889518835f7a9 |
ExtractTensorPatches | # 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 typing import Optional
from typing import Tuple
import torch.nn as nn
import torch.nn.functional as F
from typing import Union
from tor... | JoanFM/kornia | ExtractTensorPatches | false | 11,550 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 808898887cde69074ca3e3df9b24dea9682aad90 | https://github.com/JoanFM/kornia/tree/808898887cde69074ca3e3df9b24dea9682aad90 |
SoftCrossEntropyLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.utils.dat... | i-murray/pycls | SoftCrossEntropyLoss | false | 3,648 | [
"MIT"
] | 0 | 858dac527eb11732ba08b94162d18b53454b9018 | https://github.com/i-murray/pycls/tree/858dac527eb11732ba08b94162d18b53454b9018 |
model | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | vishal-keshav/pytorch-project-template | model | false | 10,898 | [
"MIT"
] | 0 | 526dd5b1036ed9cf592172301a2c85e8425cd154 | https://github.com/vishal-keshav/pytorch-project-template/tree/526dd5b1036ed9cf592172301a2c85e8425cd154 |
Pooler | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.optim.lr_scheduler import *
def linear(x):
return x
def activation(func_a):
"""Activation function wrapper
"""
try:
f = eval(func_a)
except:
f = linear
return f
class DropoutWrapper(nn.Module):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.functional as F
from torch.optim.lr_schedu... | praj000/DeepPavlov | Pooler | false | 7,487 | [
"Apache-2.0"
] | 1 | 3c9e4c989c6f6b89cd187f0ec2e2b7c71d1e3bf3 | https://github.com/praj000/DeepPavlov/tree/3c9e4c989c6f6b89cd187f0ec2e2b7c71d1e3bf3 |
ReferenceActivationBinarizationModule | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
from torchvision import models as models
import torch.nn.parallel
import torch.optim
import torch.utils.data
import tor... | JinYAnGHe/openvino_training_extensions | ReferenceActivationBinarizationModule | false | 2,715 | [
"Apache-2.0"
] | 0 | a0b4456a3c9fe6c1b7eabc9d5eb4e74d01453dee | https://github.com/JinYAnGHe/openvino_training_extensions/tree/a0b4456a3c9fe6c1b7eabc9d5eb4e74d01453dee |
AddLayerNorm_v1 | import torch
import torch.cuda
import torch.backends.cudnn
import torch.backends.mkl
class AddLayerNorm_v1(torch.nn.Module):
def __init__(self, dim=32):
super(AddLayerNorm_v1, self).__init__()
self.layernorm = torch.nn.LayerNorm(dim)
def forward(self, x, y, z):
x = x + y + z
... | 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.cuda
import torch.backends.cudnn
import torch.backends.mkl
assert_... | JudeDavis1/intel-extension-for-pytorch | AddLayerNorm_v1 | false | 2,578 | [
"Apache-2.0"
] | 0 | 364e34cb4917a709f5108c07d4005bf82f3d5067 | https://github.com/JudeDavis1/intel-extension-for-pytorch/tree/364e34cb4917a709f5108c07d4005bf82f3d5067 |
DIAYNActionModel | # 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.... | Purple-PI/rlstructures | DIAYNActionModel | false | 14,260 | [
"MIT"
] | 281 | 9b201b083715bbda2f3534b010c84e11dfc0a1c7 | https://github.com/Purple-PI/rlstructures/tree/9b201b083715bbda2f3534b010c84e11dfc0a1c7 |
FCLateActionSAQFunction | # 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... | g-votte/pfrl | FCLateActionSAQFunction | false | 15,382 | [
"MIT"
] | 824 | 4c30c1d73f0941a2b649b62937eec346bb55a95e | https://github.com/g-votte/pfrl/tree/4c30c1d73f0941a2b649b62937eec346bb55a95e |
CoAttentionTransformerEncoderLayer | # 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.... | doiken23/mccformers.pytorch | CoAttentionTransformerEncoderLayer | false | 6,615 | [
"MIT"
] | 1 | 678bd9448e3a2f35bd408e8c8e510e0ea1f9a19f | https://github.com/doiken23/mccformers.pytorch/tree/678bd9448e3a2f35bd408e8c8e510e0ea1f9a19f |
LocalNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | DevilMayNotCry/My_curl | LocalNet | false | 9,133 | [
"BSD-3-Clause"
] | 0 | a8f65a3e58cbdeefb4679aa2f0c3d9d800b67381 | https://github.com/DevilMayNotCry/My_curl/tree/a8f65a3e58cbdeefb4679aa2f0c3d9d800b67381 |
CNormalized_Linear | import math
import torch
import torch as th
class CNormalized_Linear(th.nn.Module):
"""Linear layer with column-wise normalized input matrix."""
def __init__(self, in_features, out_features, bias=False):
"""Initialize the layer."""
super(CNormalized_Linear, self).__init__()
self.in_fe... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
import ... | TheSignPainter/CausalDiscoveryToolbox | CNormalized_Linear | false | 14,481 | [
"MIT"
] | 528 | 33eae18184905e505be978b08003b9477bf38e0c | https://github.com/TheSignPainter/CausalDiscoveryToolbox/tree/33eae18184905e505be978b08003b9477bf38e0c |
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... | XeniaLLL/glow-pytorch | InvConv2d | false | 11,974 | [
"MIT"
] | 0 | 66d434e57853de1aaafaa5a5533d21705dc92e10 | https://github.com/XeniaLLL/glow-pytorch/tree/66d434e57853de1aaafaa5a5533d21705dc92e10 |
SimpleSumModule | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.... | opti-mix/glow | SimpleSumModule | false | 7,415 | [
"Apache-2.0"
] | 1 | 4ba074df5da9822986a23a6679ab592c22660f6d | https://github.com/opti-mix/glow/tree/4ba074df5da9822986a23a6679ab592c22660f6d |
Critic | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.nn.functional as F
class Critic(nn.Module):
def __init__(self, opts):
super(Critic, self).__init__()
self.l1 = nn.Linear(opts.state_dim + opts.action_dim, 256)
self.l2 = nn.Linear(256, 256)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | Jiang-HB/AC_CDQ | Critic | false | 18,375 | [
"MIT"
] | 7 | 4b4ec2d611c4481ad0b99cf7ea79eb23014a0325 | https://github.com/Jiang-HB/AC_CDQ/tree/4b4ec2d611c4481ad0b99cf7ea79eb23014a0325 |
ReduceBranch | import torch
import torch.nn as nn
import torch.nn.functional as F
class ReduceBranch(nn.Module):
def __init__(self, planes, stride=2):
super(ReduceBranch, self).__init__()
self.conv1 = nn.Conv2d(planes, planes, kernel_size=1, stride=1,
padding=0, bias=False)
self.conv2 = nn.C... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | dnddnjs/pytorch-vision | ReduceBranch | false | 15,196 | [
"MIT"
] | 48 | d432b467774f838bef37372d6cff3576c6559803 | https://github.com/dnddnjs/pytorch-vision/tree/d432b467774f838bef37372d6cff3576c6559803 |
EmbeddingModel | # 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.... | Deepest-Project/agent57_from_ngu | EmbeddingModel | false | 5,200 | [
"MIT"
] | 1 | 2f596024c7538cfaa5cf63cde1b77f8a1c22d208 | https://github.com/Deepest-Project/agent57_from_ngu/tree/2f596024c7538cfaa5cf63cde1b77f8a1c22d208 |
Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | NlGG/Rejection | Net | false | 929 | [
"MIT"
] | 0 | 5f7cc64b71dacc2eb794b3f7c48390457e363cc5 | https://github.com/NlGG/Rejection/tree/5f7cc64b71dacc2eb794b3f7c48390457e363cc5 |
GroupNorm | # 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_... | EKami/EzeeML | GroupNorm | false | 8,034 | [
"MIT"
] | 35 | 21753a0ede7cc1dc675a2dcd09b6306cea2cad56 | https://github.com/EKami/EzeeML/tree/21753a0ede7cc1dc675a2dcd09b6306cea2cad56 |
SmallConvNet | import torch
import torch.nn as nn
from numpy import prod
class SmallConvNet(nn.Module):
"""
A network with three conv layers. This is used for testing convolution
layers for activation count.
"""
def __init__(self, input_dim: 'int') ->None:
super(SmallConvNet, self).__init__()
co... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from numpy import prod
assert_size_stride = torch._C._dyna... | DenXX/fvcore | SmallConvNet | false | 2,212 | [
"Apache-2.0"
] | 0 | 4b91cf092f4f5d379b2c93398780a3b5755e7179 | https://github.com/DenXX/fvcore/tree/4b91cf092f4f5d379b2c93398780a3b5755e7179 |
SimpleLSTM | # 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.utils.... | GuoShi28/GCP-Net | SimpleLSTM | false | 8,173 | [
"Apache-2.0"
] | 24 | cef7513fa242343055af64e612429e4384d3c1d7 | https://github.com/GuoShi28/GCP-Net/tree/cef7513fa242343055af64e612429e4384d3c1d7 |
OuterProductLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | Ahren09/RecBole | OuterProductLayer | false | 1,919 | [
"MIT"
] | 0 | b3921818dfbc1b81f9eda8d5e9f05bc9d9114089 | https://github.com/Ahren09/RecBole/tree/b3921818dfbc1b81f9eda8d5e9f05bc9d9114089 |
IMul | # 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
@triton.jit
def triton_poi_fused_mul_0(in_ptr0, in_ptr1, out_ptr1, xnumel,... | ahangchen/torch2trt | IMul | false | 6,099 | [
"MIT"
] | 1 | 53c663f0e0570ef7ffd6771354ae3478f63bd328 | https://github.com/ahangchen/torch2trt/tree/53c663f0e0570ef7ffd6771354ae3478f63bd328 |
DNN | import math
import torch
import torch.nn.functional as F
import torch.nn as nn
class DNN(nn.Module):
def __init__(self, n_concat, freq_bins, *, dropout=0.2):
super().__init__()
hidden_units = 2048
self.dropout = dropout
self.fc1 = nn.Linear(n_concat * freq_bins, hidden_units)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 math
import torch.nn a... | cHemingway/sednn_pytorch_ignite | DNN | false | 9,898 | [
"MIT"
] | 0 | 5b82dcc92829513acc382f0b189003cca206468b | https://github.com/cHemingway/sednn_pytorch_ignite/tree/5b82dcc92829513acc382f0b189003cca206468b |
LipschitzCube | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.utils.data.distributed
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda ... | rh-ia/color-information | LipschitzCube | false | 4,281 | [
"MIT"
] | 0 | e912a1667e4fffb339dbc574c85020ec6cf78b02 | https://github.com/rh-ia/color-information/tree/e912a1667e4fffb339dbc574c85020ec6cf78b02 |
PositionalWiseFeedForward | # 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.... | JiaweiSheng/FAAN | PositionalWiseFeedForward | false | 8,354 | [
"MIT"
] | 41 | b439b829506c4e2e9044a6b2ab7f3d844f445a95 | https://github.com/JiaweiSheng/FAAN/tree/b439b829506c4e2e9044a6b2ab7f3d844f445a95 |
ConditionTime | import torch
from torch import nn as nn
def condition_time(x, i=0, size=(12, 16), seq_len=15):
"""create one hot encoded time image-layers, i in [1, seq_len]"""
assert i < seq_len
times = torch.eye(seq_len, dtype=x.dtype, device=x.device)[i].unsqueeze(-1
).unsqueeze(-1)
ones = torch.ones(1, *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 nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._emp... | openclimatefix/MetNet | ConditionTime | false | 7,368 | [
"MIT"
] | 1 | 06eed550e93da6325641958b0d36c15adde1d928 | https://github.com/openclimatefix/MetNet/tree/06eed550e93da6325641958b0d36c15adde1d928 |
GAT | import torch
import torch.nn as nn
import torch.nn.functional as F
class GraphAttentionLayer(nn.Module):
"""
Simple GAT layer, similar to https://arxiv.org/abs/1710.10903
"""
def __init__(self, in_features, out_features, dropout, alpha, concat=True):
super(GraphAttentionLayer, self).__init__(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | OkYongChoi/smac | GAT | false | 17,815 | [
"Apache-2.0"
] | 8 | 5b2b59e42d17a124e97feeecf9154a3a0aa9d260 | https://github.com/OkYongChoi/smac/tree/5b2b59e42d17a124e97feeecf9154a3a0aa9d260 |
BasicModel3 | import torch
import torch.nn as nn
import torch.nn.functional as F
class BasicModel3(nn.Module):
"""
Example model two from the paper
https://arxiv.org/pdf/1703.01365.pdf
f(x1, x2) = RELU(ReLU(x1 - 1) - ReLU(x2))
"""
def __init__(self):
super().__init__()
def forward... | 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... | ngduduong/captum | BasicModel3 | false | 4,070 | [
"BSD-3-Clause"
] | 0 | 6fe5f0f23ea975e73e0c0dee79bdc01b4223d283 | https://github.com/ngduduong/captum/tree/6fe5f0f23ea975e73e0c0dee79bdc01b4223d283 |
ContrastiveEmbeddingLoss | import torch
from torch import nn
from torch.nn.modules.loss import *
from torch.nn.modules import *
from torch.optim import *
from torch.optim.lr_scheduler import *
import torch.distributed
import torch.multiprocessing
import torch.backends
class ContrastiveEmbeddingLoss(nn.Module):
"""The Contrastive embedding ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
from to... | Casyfill/catalyst | ContrastiveEmbeddingLoss | false | 9,000 | [
"Apache-2.0"
] | 0 | 7f63545dbc53902c3dd959463def28a67a16a989 | https://github.com/Casyfill/catalyst/tree/7f63545dbc53902c3dd959463def28a67a16a989 |
KL_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 libdevice, math as tl_math
from torch ... | NeutrinoLiu/FedML | KL_Loss | false | 2,669 | [
"Apache-2.0"
] | 0 | 1670b2a3f0b2d63c374a9a4a19449090c694bc78 | https://github.com/NeutrinoLiu/FedML/tree/1670b2a3f0b2d63c374a9a4a19449090c694bc78 |
ResidualBlock | # 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.... | Aftaab99/pytorch-multiple-style-transfer | ResidualBlock | false | 18,450 | [
"BSD-3-Clause"
] | 3 | 172d384d8ef06d005a49715a9c75fc8f26a4e4f9 | https://github.com/Aftaab99/pytorch-multiple-style-transfer/tree/172d384d8ef06d005a49715a9c75fc8f26a4e4f9 |
KLDivergence | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_... | akanametov/pathgan | KLDivergence | false | 18,293 | [
"MIT"
] | 8 | d93464a9c2490532afdf7bbc0f60decdf2d0767d | https://github.com/akanametov/pathgan/tree/d93464a9c2490532afdf7bbc0f60decdf2d0767d |
ResBlock | # 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.... | gaozhihan/torchdiffeq | ResBlock | false | 6,717 | [
"MIT"
] | 1 | 414781617d595ba01cc3f23382e25ab890f4ca66 | https://github.com/gaozhihan/torchdiffeq/tree/414781617d595ba01cc3f23382e25ab890f4ca66 |
Model | from torch.nn import Module
import torch
import torch.nn.functional
from torch.nn import Parameter
from torch.nn.parameter import Parameter
from torch.nn.modules import Module
import torch.nn.parallel
import torch.utils.data
import torch.optim
import torch.utils.data.distributed
from torch.nn import Module
class Mode... | 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.nn import Module
import torch.nn.functional
from torch.nn import Parameter
from torch.nn.parameter import Parameter
from torch.nn... | DominickZhang/Distillation-Swin-Transformer | Model | false | 13,236 | [
"MIT"
] | 0 | 6fc7b25bd558edb14e6f15715f53612c37e5166f | https://github.com/DominickZhang/Distillation-Swin-Transformer/tree/6fc7b25bd558edb14e6f15715f53612c37e5166f |
Offset | import torch
from torch import nn
class Offset(nn.Module):
def __init__(self, init_value=0.0):
super(Offset, self).__init__()
self.bias = nn.Parameter(torch.FloatTensor([init_value]))
def forward(self, input):
return input + self.bias
def get_inputs():
return [torch.rand([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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | flipson/dd3d | Offset | false | 15,356 | [
"MIT"
] | 227 | 86d8660c29612b79836dad9b6c39972ac2ca1557 | https://github.com/flipson/dd3d/tree/86d8660c29612b79836dad9b6c39972ac2ca1557 |
FastAttention | import torch
import torch.nn as nn
class FastAttention(nn.Module):
""" wuch15's Fastformer Attention module (Official) """
def __init__(self, dim, dim_head, heads, dropout=0.1, initializer_range
=0.02):
super(FastAttention, self).__init__()
self.initializer_range = initializer_range
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ishine/Comprehensive-Transformer-TTS | FastAttention | false | 15,627 | [
"MIT"
] | 147 | dca252cae50a18464ce2410aa85a21c557c72d7a | https://github.com/ishine/Comprehensive-Transformer-TTS/tree/dca252cae50a18464ce2410aa85a21c557c72d7a |
SeparableConvBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.utils.data
import torch.nn.functional as F
from itertoo... | lingtengqiu/LearnableTreeFilterV2 | SeparableConvBlock | false | 7,098 | [
"Apache-2.0"
] | 1 | 3814a5a84c0a5c33d6538749eaf5aed4827366de | https://github.com/lingtengqiu/LearnableTreeFilterV2/tree/3814a5a84c0a5c33d6538749eaf5aed4827366de |
MLPDecoder | # 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_... | cheng-xie/motionEncode | MLPDecoder | false | 1,677 | [
"MIT"
] | 0 | fa2152b3eaf2e09ad9477d054566db0a7bc4c7b4 | https://github.com/cheng-xie/motionEncode/tree/fa2152b3eaf2e09ad9477d054566db0a7bc4c7b4 |
BoxOffsetIntersection | import torch
import torch.nn as nn
import torch.nn.functional as F
class BoxOffsetIntersection(nn.Module):
def __init__(self, dim):
super(BoxOffsetIntersection, self).__init__()
self.dim = dim
self.layer1 = nn.Linear(self.dim, self.dim)
self.layer2 = nn.Linear(self.dim, self.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_... | amayuelas/NNKGReasoning | BoxOffsetIntersection | false | 6,181 | [
"MIT"
] | 1 | 0e3623b344fd4e3088ece897f898ddbb1f80888d | https://github.com/amayuelas/NNKGReasoning/tree/0e3623b344fd4e3088ece897f898ddbb1f80888d |
DAFAttention | # 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.... | NicholasPaulBrazeauSanchez/squad | DAFAttention | false | 11,755 | [
"MIT"
] | 0 | 7343f41b186f1647e474824e5035c8dd639028b2 | https://github.com/NicholasPaulBrazeauSanchez/squad/tree/7343f41b186f1647e474824e5035c8dd639028b2 |
_ImpalaBlock | import torch
from torch import nn
class _ImpalaResBlock(nn.Module):
def __init__(self, n_channels: 'int'):
super().__init__()
self.n_channels = n_channels
kernel_size = 3
padding = 1
self.relu = nn.ReLU()
self.relu_inplace = nn.ReLU()
self.conv1 = 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._inductor.runtime import triton_helpers
from torch import nn
assert_s... | IBM/vsrl-framework | _ImpalaBlock | false | 8,285 | [
"MIT"
] | 44 | 42e0853bffb5efbb66cd97178aff9e10ad18c5a9 | https://github.com/IBM/vsrl-framework/tree/42e0853bffb5efbb66cd97178aff9e10ad18c5a9 |
GroupNorm | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
import torch._utils
import torch.optim
def num_groups(group_size, channels):
if not group_size:
return 1
else:
assert channels % group_size == 0
return channels // group_size
class GroupNorm(n... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.nn.parallel
import torch._utils
import torch... | Alicegaz/torchok | GroupNorm | false | 16,935 | [
"Apache-2.0"
] | 8 | 7b8f95df466a25b1ad8ee93bed1a3c7516440cf4 | https://github.com/Alicegaz/torchok/tree/7b8f95df466a25b1ad8ee93bed1a3c7516440cf4 |
SimplePowModule | # 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... | briancoutinho/glow | SimplePowModule | false | 12,585 | [
"Apache-2.0"
] | 0 | 4c919d60b3c33296c4109aec8020a1733c98f5b5 | https://github.com/briancoutinho/glow/tree/4c919d60b3c33296c4109aec8020a1733c98f5b5 |
MaxMarginRankingLoss | # 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... | minjoong507/TVRetrieval | MaxMarginRankingLoss | false | 10,745 | [
"MIT"
] | 0 | 919e1766ab8aa1ef267bd3b80d4f87b06cde09a9 | https://github.com/minjoong507/TVRetrieval/tree/919e1766ab8aa1ef267bd3b80d4f87b06cde09a9 |
GRU221 | import torch
import torch.nn as nn
class GRU221(nn.Module):
def __init__(self, input_size, hidden_size):
super(GRU221, self).__init__()
self.wir = nn.Linear(in_features=input_size, out_features=hidden_size)
self.whr = nn.Linear(in_features=2 * hidden_size, out_features=
hidden... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | smeznar/ProGED | GRU221 | false | 10,808 | [
"BSD-3-Clause"
] | 0 | 191cfd2b7b1fece819109a4b61e3f7533332fd74 | https://github.com/smeznar/ProGED/tree/191cfd2b7b1fece819109a4b61e3f7533332fd74 |
CosineLoss | # 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.functional a... | ackness/eth-xgaze-estimator | CosineLoss | false | 9,644 | [
"MIT"
] | 0 | b617cda6505885942c81b7f2d41399b62985b9a7 | https://github.com/ackness/eth-xgaze-estimator/tree/b617cda6505885942c81b7f2d41399b62985b9a7 |
ScaleNorm | import torch
import torch.nn as nn
import torch.jit
import torch.nn
class ScaleNorm(nn.Module):
def __init__(self, *args):
super().__init__()
self.scale = nn.Parameter(torch.tensor(1.0, dtype=torch.float))
def forward(self, inputs):
out = inputs.view(inputs.size(0), -1)
norm ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.jit
import torch.nn
assert_size_stride = tor... | ankmathur96/torchsupport | ScaleNorm | false | 3,171 | [
"MIT"
] | 0 | 77bf4a90b8770a408665e2604428808c3ed2f979 | https://github.com/ankmathur96/torchsupport/tree/77bf4a90b8770a408665e2604428808c3ed2f979 |
PairwiseBCELoss | import torch
from abc import abstractmethod
import torch.utils.data.dataloader
import torch.nn.functional as F
from torch import nn
import torch.nn
class SimilarityLoss(nn.Module):
def __init__(self):
super(SimilarityLoss, self).__init__()
@abstractmethod
def forward(self, inputs, targets):
... | 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 abc im... | MaxDall/flair | PairwiseBCELoss | false | 9,312 | [
"MIT"
] | 0 | fe33be4a63134595c21891edbe00ef9bd6014641 | https://github.com/MaxDall/flair/tree/fe33be4a63134595c21891edbe00ef9bd6014641 |
depthwise_conv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | Zacchaeus14/lang-seg | depthwise_conv | false | 9,786 | [
"MIT"
] | 0 | ad1196a4d33830f3219dbe2260a69364a745f094 | https://github.com/Zacchaeus14/lang-seg/tree/ad1196a4d33830f3219dbe2260a69364a745f094 |
Decoder | import torch
from torch import nn
class Decoder(nn.Module):
def __init__(self, latent_dim=4, obs_dim=2, nhidden=20):
super(Decoder, self).__init__()
self.relu = nn.ReLU(inplace=True)
self.fc1 = nn.Linear(latent_dim, nhidden)
self.fc2 = nn.Linear(nhidden, obs_dim)
def forward(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | BoyanJIANG/4D-Compositional-Representation | Decoder | false | 7,868 | [
"Apache-2.0"
] | 12 | 64d5f4bbd6b8e6bc3bfd8f76736f6d468c71a73c | https://github.com/BoyanJIANG/4D-Compositional-Representation/tree/64d5f4bbd6b8e6bc3bfd8f76736f6d468c71a73c |
ResnetBlockConv1D | # 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_... | DveloperY0115/texture_fields | ResnetBlockConv1D | false | 13,612 | [
"MIT"
] | 78 | 28c277696e0a658ffff3496892810d5a0ef03f65 | https://github.com/DveloperY0115/texture_fields/tree/28c277696e0a658ffff3496892810d5a0ef03f65 |
InteractionLayer | # 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.... | yoyomimi/AS-Net | InteractionLayer | false | 16,782 | [
"MIT"
] | 49 | 85ce753707c6d1838c3983111ccbba4b1861f438 | https://github.com/yoyomimi/AS-Net/tree/85ce753707c6d1838c3983111ccbba4b1861f438 |
CriterionKD | import torch
import torch.nn as nn
from torch.nn import functional as F
import torch._utils
import torch.optim
class CriterionKD(nn.Module):
"""
knowledge distillation loss
"""
def __init__(self, upsample=False, temperature=4):
super(CriterionKD, self).__init__()
self.upsample = upsam... | 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... | yubin1219/Semantic-Seg | CriterionKD | false | 4,677 | [
"BSD-2-Clause"
] | 0 | c40bd43d3d7e44bc995b8d041736580dec084251 | https://github.com/yubin1219/Semantic-Seg/tree/c40bd43d3d7e44bc995b8d041736580dec084251 |
UpSample | import torch
import torch.nn as nn
import torch._C
import torch.serialization
class UpSample(nn.Module):
def __init__(self, n_chan, factor=2):
super(UpSample, self).__init__()
out_chan = n_chan * factor * factor
self.proj = nn.Conv2d(n_chan, out_chan, 1, 1, 0)
self.up = nn.PixelSh... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch._C
import torch.serialization
assert_size_str... | AlexanderDokuchaev/mmsegmentation | UpSample | false | 11,185 | [
"Apache-2.0"
] | 0 | 0c443ee370cce6227661b802184072174c4e3f64 | https://github.com/AlexanderDokuchaev/mmsegmentation/tree/0c443ee370cce6227661b802184072174c4e3f64 |
ResidualBlock_noBN | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import autograd as autograd
import torch.nn.init as init
import torch.fft
from itertools import product as product
def initialize_weights(net_l, scale=1):
if not isinstance(net_l, list):
net_l = [net_l]
for net in net_l:
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | hduba/KAIR | ResidualBlock_noBN | false | 3,613 | [
"MIT"
] | 0 | dbd7596c7e4a4667b9b7baac369fc6c02571fa58 | https://github.com/hduba/KAIR/tree/dbd7596c7e4a4667b9b7baac369fc6c02571fa58 |
TensorClampMax | import torch
class TensorClampMax(torch.nn.Module):
def forward(self, x):
return x.clamp_max(0.1)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | Ilyabasharov/torch2trt | TensorClampMax | false | 2,547 | [
"MIT"
] | 0 | 76bf298b3da408509665e23e2494922b131afb10 | https://github.com/Ilyabasharov/torch2trt/tree/76bf298b3da408509665e23e2494922b131afb10 |
Quantinizer | import torch
class Quantinizer(torch.nn.Module):
def __init__(self, size):
super(Quantinizer, self).__init__()
self.size = size
def forward(self, x):
x = (x * self.size * 0.999).long()
return torch.nn.functional.one_hot(x, num_classes=self.size).float()
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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | CODEJIN/SPEECHSPLIT | Quantinizer | false | 7,812 | [
"MIT"
] | 13 | b4201ca9822b2e73f98f60c160c00db3b49a0050 | https://github.com/CODEJIN/SPEECHSPLIT/tree/b4201ca9822b2e73f98f60c160c00db3b49a0050 |
EntMaxSelectLayer | # 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.... | YotamElor/ae-smote | EntMaxSelectLayer | false | 9,639 | [
"MIT"
] | 0 | 730ccc414c3b832a72a48087e709d283e27e273b | https://github.com/YotamElor/ae-smote/tree/730ccc414c3b832a72a48087e709d283e27e273b |
Sign | # 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.autograd import Function
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda... | MeMihir/SuperResCompression | Sign | false | 5,587 | [
"MIT"
] | 1 | c76bcf6b12d56ce3ad81ebb1b204fc0425f0e633 | https://github.com/MeMihir/SuperResCompression/tree/c76bcf6b12d56ce3ad81ebb1b204fc0425f0e633 |
LeNet_300_100 | import torch
from typing import *
import torch.nn as nn
import torch.nn.functional as F
class LeNet_300_100(nn.Module):
def __init__(self):
super().__init__()
self.fc1 = nn.Linear(784, 300)
self.fc2 = nn.Linear(300, 100)
self.fc3 = nn.Linear(100, 10)
def forward(self, x):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | chomd90/snip | LeNet_300_100 | false | 1,706 | [
"MIT"
] | 0 | 04aa8ca76364c61c3f6013832827fa292402652b | https://github.com/chomd90/snip/tree/04aa8ca76364c61c3f6013832827fa292402652b |
PARALossSoftmax | # 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
... | igorvlnascimento/redn | PARALossSoftmax | false | 15,614 | [
"MIT"
] | 100 | f40f19a0fdfbb11a7987996d520716a05bafd77b | https://github.com/igorvlnascimento/redn/tree/f40f19a0fdfbb11a7987996d520716a05bafd77b |
GeneralizedMeanPooling | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch ... | HumberMe/mmclassification | GeneralizedMeanPooling | false | 562 | [
"Apache-2.0"
] | 0 | 68f1542068d3af4db932c97e6a728181432fff0c | https://github.com/HumberMe/mmclassification/tree/68f1542068d3af4db932c97e6a728181432fff0c |
duelingdqnNet | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim
import torch.autograd
class duelingdqnNet(nn.Module):
def __init__(self, STATE_NUM, ACTION_NUM):
super(duelingdqnNet, self).__init__()
self.ACTION_NUM = ACTION_NUM
self.fc1_a = nn.Linear(in_features=STAT... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | ChangQingAAS/Deep-Reinforcement-Learning | duelingdqnNet | false | 251 | [
"MIT"
] | 0 | 3bc1381c632b1730a48e63e972aea62086c4287c | https://github.com/ChangQingAAS/Deep-Reinforcement-Learning/tree/3bc1381c632b1730a48e63e972aea62086c4287c |
EncoderImageWeightNormPrecomp | import torch
from collections import OrderedDict
import torch.nn as nn
import torch.nn.init
from torch.nn.utils.weight_norm import weight_norm
def l2norm(X, dim, eps=1e-08):
"""L2-normalize columns of X
"""
norm = torch.pow(X, 2).sum(dim=dim, keepdim=True).sqrt() + eps
X = torch.div(X, norm)
retur... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 collections im... | ChopinSharp/SCAN | EncoderImageWeightNormPrecomp | false | 4,996 | [
"Apache-2.0"
] | 1 | 4a165b2aeb3007685054d0c550540893b2006b17 | https://github.com/ChopinSharp/SCAN/tree/4a165b2aeb3007685054d0c550540893b2006b17 |
TotalVariationLoss | # 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... | TropComplique/CNNMRF | TotalVariationLoss | false | 18,011 | [
"MIT"
] | 3 | 602f861b14ed240acac89e6502e69f797d4f4a49 | https://github.com/TropComplique/CNNMRF/tree/602f861b14ed240acac89e6502e69f797d4f4a49 |
ValueNetwork | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
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 ValueNetwork(nn.Module):
def __init__(self, num_inputs, hidd... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | Yunaik/drl_env | ValueNetwork | false | 1,291 | [
"MIT"
] | 0 | d284e79847c59daa6ccb222f30fc7e2a86375546 | https://github.com/Yunaik/drl_env/tree/d284e79847c59daa6ccb222f30fc7e2a86375546 |
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
... | davidpfahler/fastai_dev | SigmaL1SmoothLoss | false | 10,050 | [
"Apache-2.0"
] | 0 | a86b15f86138a9902e8649e3f745e76a19139ab3 | https://github.com/davidpfahler/fastai_dev/tree/a86b15f86138a9902e8649e3f745e76a19139ab3 |
ClassicUpConv | import torch
from torch import nn
class ClassicUpConv(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, padding=
'same', upscale_factor=2, padding_mode='zeros'):
super(ClassicUpConv, self).__init__()
self.upscale_factor = upscale_factor
self.conv = nn.Conv2d(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.... | GerbenBeintema/deepSI | ClassicUpConv | false | 8,179 | [
"BSD-3-Clause"
] | 12 | 580711210398064bb7f01e41d08b7a248a88b35b | https://github.com/GerbenBeintema/deepSI/tree/580711210398064bb7f01e41d08b7a248a88b35b |
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.... | CCThompson82/deep-reinforcement-learning | Actor | false | 8,922 | [
"MIT"
] | 0 | f93faf0fb2b2dd8cfafeb8a4480e5520cefe6cb2 | https://github.com/CCThompson82/deep-reinforcement-learning/tree/f93faf0fb2b2dd8cfafeb8a4480e5520cefe6cb2 |
SparsemaxBisect | from torch.autograd import Function
import torch
import torch.nn as nn
def sparsemax_bisect(X, dim=-1, n_iter=50, ensure_sum_one=True):
"""sparsemax: normalizing sparse transform (a la softmax), via bisection.
Solves the projection:
min_p ||x - p||_2 s.t. p >= 0, sum(p) == 1.
Parameters
... | 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.autograd import Function
import torch.nn as nn
assert_size_stride = torch._C._... | cifkao/entmax | SparsemaxBisect | false | 15,042 | [
"MIT"
] | 298 | f18bab9318f9d2471a36545ee0b4c97be6d48a87 | https://github.com/cifkao/entmax/tree/f18bab9318f9d2471a36545ee0b4c97be6d48a87 |
PolicyNetwork | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from to... | sofya-pugach/spot_mini_mini | PolicyNetwork | false | 16,487 | [
"MIT"
] | 323 | 42770145e91ed2625ccc7e4f4d7016ce14a61464 | https://github.com/sofya-pugach/spot_mini_mini/tree/42770145e91ed2625ccc7e4f4d7016ce14a61464 |
SpatialConv3D | # 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... | Tencent/DVQA | SpatialConv3D | false | 14,473 | [
"BSD-3-Clause"
] | 408 | 21727333a6b41d54ad1a8beca1fcbe00a69ed347 | https://github.com/Tencent/DVQA/tree/21727333a6b41d54ad1a8beca1fcbe00a69ed347 |
TabularNetD | import torch
import numpy as np
import matplotlib.pyplot as plt
import torch.nn as nn
import torch.optim as optim
class GaussianNoise(nn.Module):
"""Gaussian noise regularizer"""
def __init__(self, device, sigma=0.1):
super().__init__()
self.device = device
self.sigma = sigma
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
import numpy as np
import matplotlib.pyplot as plt
import torch.nn as nn
import ... | Atrus619/CSDGAN | TabularNetD | false | 5,223 | [
"MIT"
] | 1 | 712be213e59b32a79a4970684d726af63616edaf | https://github.com/Atrus619/CSDGAN/tree/712be213e59b32a79a4970684d726af63616edaf |
ComboLoss | # 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... | jchen42703/reproducing-cloud-3rd-place | ComboLoss | false | 6,945 | [
"Apache-2.0"
] | 1 | 25571f53efd48f68735d7fe2991e3ad783cbd4b1 | https://github.com/jchen42703/reproducing-cloud-3rd-place/tree/25571f53efd48f68735d7fe2991e3ad783cbd4b1 |
StandardizedConv2d | import torch
import torch.nn as nn
import torch.nn.functional as F
class StandardizedConv2d(nn.Conv2d):
def __init__(self, in_channels, out_channels, kernel_size, stride=1,
padding=0, dilation=1, groups=1, bias=True):
super(StandardizedConv2d, self).__init__(in_channels, out_channels,
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | KKallidromitis/vissl | StandardizedConv2d | false | 5,429 | [
"MIT"
] | 1 | c553e7f6b13c5fa951e3f989beb129899eb8cc80 | https://github.com/KKallidromitis/vissl/tree/c553e7f6b13c5fa951e3f989beb129899eb8cc80 |
MaskedSoftmax | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
a... | Artisan-Lab/SMTimer | MaskedSoftmax | false | 16,952 | [
"MIT"
] | 5 | 8e0bbb854afd360dcc61d6b098c4ae8931bae14c | https://github.com/Artisan-Lab/SMTimer/tree/8e0bbb854afd360dcc61d6b098c4ae8931bae14c |
ActorCritic | # 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.... | Gromy1211/torch-light | ActorCritic | false | 11,463 | [
"MIT"
] | 0 | c7d7a9bc5ab1eab03d800a27d9325859516f01e6 | https://github.com/Gromy1211/torch-light/tree/c7d7a9bc5ab1eab03d800a27d9325859516f01e6 |
autoencoder | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C... | charlesmackin/tiny | autoencoder | false | 1,676 | [
"Apache-2.0"
] | 0 | bf8afc5cfc15e12efdd3bca0d559adfdfc435981 | https://github.com/charlesmackin/tiny/tree/bf8afc5cfc15e12efdd3bca0d559adfdfc435981 |
ConvolModel | import torch
import torch.nn as nn
import torch.nn.functional as F
class ConvolModel(nn.Module):
def __init__(self):
super(ConvolModel, self).__init__()
self.conv1 = nn.Conv2d(1, 5, 2)
self.conv2 = nn.Conv2d(5, 10, 2)
self.conv3 = nn.Conv2d(10, 10, 2)
def forward(self, x):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | VVKot/mlinseconds-find-me | ConvolModel | false | 11,961 | [
"MIT"
] | 0 | f50ec09ef5cef23b694970a9a975f7a0f8c59b76 | https://github.com/VVKot/mlinseconds-find-me/tree/f50ec09ef5cef23b694970a9a975f7a0f8c59b76 |
SimpleAvgPool2dModule | # 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 | SimpleAvgPool2dModule | false | 3,320 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
NormalizeImages | # 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_... | matteo-ronchetti/IKA | NormalizeImages | false | 7,178 | [
"MIT"
] | 1 | 29d1752a059c3ab7659b332b72bf8c1506e7dd20 | https://github.com/matteo-ronchetti/IKA/tree/29d1752a059c3ab7659b332b72bf8c1506e7dd20 |
ModelWithDuplicates | # 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.... | saman-aghazadeh/distiller | ModelWithDuplicates | false | 4,258 | [
"Apache-2.0"
] | 0 | 7e8d3e6193c807f7c55d8453f64e1bc3c02eee30 | https://github.com/saman-aghazadeh/distiller/tree/7e8d3e6193c807f7c55d8453f64e1bc3c02eee30 |
Conv | import torch
import torch.nn as nn
import torch.utils.data
class Conv(nn.Module):
"""
Convenience class that does padding and convolution for inputs in the format
[batch_size, sequence length, hidden size]
"""
def __init__(self, input_size, output_size, kernel_size, pad_type):
"""
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | HLTCHKUST/emotion-dialogue | Conv | false | 8,178 | [
"MIT"
] | 40 | 0d58b339134dd9a2f386948ae474b270a77370f9 | https://github.com/HLTCHKUST/emotion-dialogue/tree/0d58b339134dd9a2f386948ae474b270a77370f9 |
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