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 |
|---|---|---|---|---|---|---|---|---|---|---|
Conv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | DQiaole/ZITS | Conv | false | 7,946 | [
"Apache-2.0"
] | 40 | 5f7a060167790789d5e29a3d14d3c2ef8a34e765 | https://github.com/DQiaole/ZITS/tree/5f7a060167790789d5e29a3d14d3c2ef8a34e765 |
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... | PogChamper/torch2trt | TensorClampMax | false | 14,214 | [
"MIT"
] | 3,363 | 43b12627ec0de4d212efb6d02b07570205085ccc | https://github.com/PogChamper/torch2trt/tree/43b12627ec0de4d212efb6d02b07570205085ccc |
UNetModule | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import t... | cxz/tgs-salt-identification-challenge | UNetModule | false | 6,518 | [
"MIT"
] | 1 | 859f3d7f2d3184532c42c34444500eec3b03b1c8 | https://github.com/cxz/tgs-salt-identification-challenge/tree/859f3d7f2d3184532c42c34444500eec3b03b1c8 |
MLP | import torch
from torch import nn
from torch.nn import functional as F
class MLP(nn.Module):
"""
Multi-Layer Perceptron
:param in_dim: int, size of input feature
:param n_classes: int, number of output classes
:param hidden_dim: int, size of hidden vector
:param dropout: fl... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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... | bigdata-ustc/DisenQNet | MLP | false | 6,338 | [
"MIT"
] | 1 | 908fadeb9b8d278450213deff70205703bd91da6 | https://github.com/bigdata-ustc/DisenQNet/tree/908fadeb9b8d278450213deff70205703bd91da6 |
Policy | # 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 math as tl_math
from copy import deepc... | Mirofil/AutoDL-Projects | Policy | false | 2,654 | [
"MIT"
] | 0 | e7ee9fe27e5c5561a4b9fd1c1ee185677ef30893 | https://github.com/Mirofil/AutoDL-Projects/tree/e7ee9fe27e5c5561a4b9fd1c1ee185677ef30893 |
wTransitionLinearUnit | # 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.... | TTomatoZhang/GHGCN | wTransitionLinearUnit | false | 3,090 | [
"Apache-2.0"
] | 0 | 09a07ff9e29e5889b912ca5feff74bb9308eda55 | https://github.com/TTomatoZhang/GHGCN/tree/09a07ff9e29e5889b912ca5feff74bb9308eda55 |
MultiHeadAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Oreoluwa1234/NeMo | MultiHeadAttention | false | 9,717 | [
"Apache-2.0"
] | 0 | b01e3ceed34efe31fd43866685dbdd19a6b30928 | https://github.com/Oreoluwa1234/NeMo/tree/b01e3ceed34efe31fd43866685dbdd19a6b30928 |
SimpleCosModule | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = t... | andreas-hommel/glow | SimpleCosModule | false | 3,330 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
Mish | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.gua... | Cris-zj/mmdetection | Mish | false | 8,919 | [
"Apache-2.0"
] | 0 | ede648b93e7ba2562f835f338b778f3e705f7119 | https://github.com/Cris-zj/mmdetection/tree/ede648b93e7ba2562f835f338b778f3e705f7119 |
ContinuousLoss_L2 | # 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
... | Emilien-mipt/emotic | ContinuousLoss_L2 | false | 11,397 | [
"MIT"
] | 0 | c27c0a4f4c8e7ef81edcd527f9f4aa4747ab72af | https://github.com/Emilien-mipt/emotic/tree/c27c0a4f4c8e7ef81edcd527f9f4aa4747ab72af |
GELU_ | import math
import torch
import torch.nn as nn
class GELU_(nn.Module):
def forward(self, x):
return 0.5 * x * (1 + torch.tanh(math.sqrt(2 / math.pi) * (x +
0.044715 * torch.pow(x, 3))))
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.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | CherokeeLanguage/Comprehensive-Transformer-TTS | GELU_ | false | 4,985 | [
"MIT"
] | 1 | 2d97e7125d4e7b4e02950687dfbb6f14e7a1d531 | https://github.com/CherokeeLanguage/Comprehensive-Transformer-TTS/tree/2d97e7125d4e7b4e02950687dfbb6f14e7a1d531 |
MultiHeadAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | MIracleyin/RecBole-notebook | MultiHeadAttention | false | 9,614 | [
"MIT"
] | 0 | ef32b3e57a297ff4889dec1f63c7984f8f901a23 | https://github.com/MIracleyin/RecBole-notebook/tree/ef32b3e57a297ff4889dec1f63c7984f8f901a23 |
ContrastiveLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | vzinche/inferno | ContrastiveLoss | false | 4,510 | [
"Apache-2.0"
] | 0 | 91b22dfcd1b6a9ec415f0bbb6ae66caea42f4034 | https://github.com/vzinche/inferno/tree/91b22dfcd1b6a9ec415f0bbb6ae66caea42f4034 |
EnchanceReLU | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class EnchanceReLU(nn.ReLU):
def __init__(self, args):
super(EnchanceReLU, self).__init__(inplace=True)
self.shift = getattr(args, 'fm_boundary', 0.25)
def forward(self, x):
x = x + self.shift
x ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | XiaotaoChen/model-quantization | EnchanceReLU | false | 14,605 | [
"BSD-2-Clause"
] | 66 | a745ef691e9329b9c973a2dd795761cd3da8b6ae | https://github.com/XiaotaoChen/model-quantization/tree/a745ef691e9329b9c973a2dd795761cd3da8b6ae |
ConvMlp | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import t... | LoveEachDay/towhee | ConvMlp | false | 11,659 | [
"Apache-2.0"
] | 0 | 513c9c2626676cadaaf0a16ac3c828d96bec91a1 | https://github.com/LoveEachDay/towhee/tree/513c9c2626676cadaaf0a16ac3c828d96bec91a1 |
Wav2Vec2ClassificationHead | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class Wav2Vec2ClassificationHead(nn.Module):
"""Head for classification tasks
Layers:
- dropout
- dense layer (default xlsr hidden size = 1024)
- relu
- dropout
- classificiation layer ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | HLasse/wav2vec_finetune | Wav2Vec2ClassificationHead | false | 18,359 | [
"MIT"
] | 6 | 084ab432ba4acbf5ce81267e2791fb36a0b70daa | https://github.com/HLasse/wav2vec_finetune/tree/084ab432ba4acbf5ce81267e2791fb36a0b70daa |
CriterionCWD | # 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... | yubin1219/Semantic-Seg | CriterionCWD | false | 4,642 | [
"BSD-2-Clause"
] | 0 | c40bd43d3d7e44bc995b8d041736580dec084251 | https://github.com/yubin1219/Semantic-Seg/tree/c40bd43d3d7e44bc995b8d041736580dec084251 |
ACLoss | import torch
import torch.utils.data
class ACLoss(torch.nn.Module):
"""Active Contour loss
http://openaccess.thecvf.com/content_CVPR_2019/papers/Chen_Learning_Active_Contour_Models_for_Medical_Image_Segmentation_CVPR_2019_paper.pdf
Supports 2D and 3D data, as long as all spatial dimensions have the same
... | 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... | ELEKTRONN/elektronn3 | ACLoss | false | 13,593 | [
"MIT"
] | 124 | 19c751855dffc67b744cd43e757aa4a5bd577d9b | https://github.com/ELEKTRONN/elektronn3/tree/19c751855dffc67b744cd43e757aa4a5bd577d9b |
TemperatureHolder | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_... | KtechB/pfrl | TemperatureHolder | false | 2,464 | [
"MIT"
] | 0 | 9be4726d327b7ce32d9008c40119c98c93febad5 | https://github.com/KtechB/pfrl/tree/9be4726d327b7ce32d9008c40119c98c93febad5 |
SLMLexicon | # 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.... | cmdowney88/XLSLM | SLMLexicon | false | 3,309 | [
"MIT"
] | 0 | 7fe266bd0f0ad8a79a30052a18104b974d1c32e8 | https://github.com/cmdowney88/XLSLM/tree/7fe266bd0f0ad8a79a30052a18104b974d1c32e8 |
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... | apoorv2904/Self-Supervised-Speech-Pretraining-and-Representation-Learning | VectorQuantizeLayer_GB | false | 9,818 | [
"MIT"
] | 0 | 6bdf02836ed31fdf7f185eddcd004770526c57c3 | https://github.com/apoorv2904/Self-Supervised-Speech-Pretraining-and-Representation-Learning/tree/6bdf02836ed31fdf7f185eddcd004770526c57c3 |
LogitCosineDistance | import torch
import torch.utils.data.dataloader
import torch.nn
def dot_product(a: 'torch.Tensor', b: 'torch.Tensor', normalize=False):
"""
Computes dot product for pairs of vectors.
:param normalize: Vectors are normalized (leads to cosine similarity)
:return: Matrix with res[i][j] = dot_product(a[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.... | chen-yuxuan/flair | LogitCosineDistance | false | 12,205 | [
"MIT"
] | 0 | 480d2c9afd66ab8d3bf40a676917e84dba3c4cee | https://github.com/chen-yuxuan/flair/tree/480d2c9afd66ab8d3bf40a676917e84dba3c4cee |
MSELoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import functools
import torch.nn as nn
import torch.nn.functional as F
assert_size_stride... | Andrew-Zhu/DyFPN | MSELoss | false | 7,716 | [
"Apache-2.0"
] | 32 | a74463b59c4ce28253c2449a07c0f6692a0147a1 | https://github.com/Andrew-Zhu/DyFPN/tree/a74463b59c4ce28253c2449a07c0f6692a0147a1 |
GlobalPoolingBlock | import torch
import torch.nn as nn
class Block(nn.Module):
def __init__(self):
"""Initialisation for a lower-level DeepLPF conv block
:returns: N/A
:rtype: N/A
"""
super(Block, self).__init__()
def conv3x3(self, in_channels, out_channels, stride=1):
"""Repre... | 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... | DevilMayNotCry/My_curl | GlobalPoolingBlock | false | 9,123 | [
"BSD-3-Clause"
] | 0 | a8f65a3e58cbdeefb4679aa2f0c3d9d800b67381 | https://github.com/DevilMayNotCry/My_curl/tree/a8f65a3e58cbdeefb4679aa2f0c3d9d800b67381 |
Linear | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn import Module
i... | goodman1204/CAN-pytorch | Linear | false | 12,462 | [
"MIT"
] | 0 | 73d9486c93dd069101c750f94a0750fff0500abb | https://github.com/goodman1204/CAN-pytorch/tree/73d9486c93dd069101c750f94a0750fff0500abb |
FF | # 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... | noxsine/WTSDNet | FF | false | 7,355 | [
"MIT"
] | 1 | 7f25fb62c705c730c4d2fab6c86f9cf3535e6d80 | https://github.com/noxsine/WTSDNet/tree/7f25fb62c705c730c4d2fab6c86f9cf3535e6d80 |
Abs | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | AlliedToasters/elko_den | Abs | false | 7,647 | [
"Apache-2.0"
] | 38 | 4e69f7f5c0dc7ffad54c7e190a2b75aba2eab7d2 | https://github.com/AlliedToasters/elko_den/tree/4e69f7f5c0dc7ffad54c7e190a2b75aba2eab7d2 |
InResBlock | # 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... | ishine/GANsNRoses | InResBlock | false | 15,638 | [
"MIT"
] | 969 | 414e9e77c3df47d4ecf7941b5dcfdffec67403ee | https://github.com/ishine/GANsNRoses/tree/414e9e77c3df47d4ecf7941b5dcfdffec67403ee |
ShakeResNeXt | # 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 math
from torch import... | aierh/autoML | ShakeResNeXt | false | 14,761 | [
"MIT"
] | 185 | 8e31966edf6de2c223d5eeb6cd4b4dbd6ddbbf77 | https://github.com/aierh/autoML/tree/8e31966edf6de2c223d5eeb6cd4b4dbd6ddbbf77 |
SamePadConv2d | # 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... | jjeamin/obJDetection | SamePadConv2d | false | 6,951 | [
"MIT"
] | 1 | eb7fbc410beb00fad1a6477e827e9ce2d8efbac5 | https://github.com/jjeamin/obJDetection/tree/eb7fbc410beb00fad1a6477e827e9ce2d8efbac5 |
MulticlassSegmentationLoss | # 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.nn import Module
from torch import Tensor
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = to... | PiePline/PieToolbelt | MulticlassSegmentationLoss | false | 5,714 | [
"MIT"
] | 1 | bcf9cab16bf3dbb19015c074a305f9ea8a8dc48e | https://github.com/PiePline/PieToolbelt/tree/bcf9cab16bf3dbb19015c074a305f9ea8a8dc48e |
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
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | djz233/GraphMask | Gate | false | 12,296 | [
"MIT"
] | 0 | 4b699a1685f0d26973bb90cd75b09d74726cdc2f | https://github.com/djz233/GraphMask/tree/4b699a1685f0d26973bb90cd75b09d74726cdc2f |
CauchyLoss | import torch
from typing import *
import torch.nn as nn
class CauchyLoss(nn.Module):
def __init__(self):
super().__init__()
def forward(self, x, y):
err = torch.sum(torch.pow(x - y, 2), dim=-1)
return torch.mean(torch.log(1 + err), dim=-1)
def get_inputs():
return [torch.rand([... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from typing import *
import torch.nn as nn
assert_size_stride = torch._C.... | ciwanceylan/gated-gradient-flow | CauchyLoss | false | 6,442 | [
"Apache-2.0"
] | 1 | c4f6c0c987f428697336e4514099aa7ef2351388 | https://github.com/ciwanceylan/gated-gradient-flow/tree/c4f6c0c987f428697336e4514099aa7ef2351388 |
ContrastiveLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._... | Rajat-Mehta/Vehicle-Re-identification-UI | ContrastiveLoss | false | 5,756 | [
"MIT"
] | 1 | 9769ae9dac8bd43a3b66f705cb2830fa498649d2 | https://github.com/Rajat-Mehta/Vehicle-Re-identification-UI/tree/9769ae9dac8bd43a3b66f705cb2830fa498649d2 |
ContractingBlock | import torch
from torch import nn
from torch.nn import functional as F
class ContractingBlock(nn.Module):
"""
ContractingBlock Class
Performs two convolutions followed by a max pool operation.
Values:
input_channels: the number of channels to expect from a given input
"""
def __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 import nn
assert_s... | akanametov/unet-pytorch | ContractingBlock | false | 3,054 | [
"MIT"
] | 0 | 6cf0f70674958356ea4ac36fe61b0415921f72ae | https://github.com/akanametov/unet-pytorch/tree/6cf0f70674958356ea4ac36fe61b0415921f72ae |
LinearModel | import torch
from torch import nn
class LinearModel(nn.Module):
def __init__(self, context_points: 'int'):
super().__init__()
self.window = context_points
self.linear = nn.Linear(context_points, 1)
def forward(self, y_c):
_bs, _length, d_y = y_c.shape
inp = y_c[:, -se... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | Azerrroth/spacetimeformer | LinearModel | false | 101 | [
"MIT"
] | 0 | e822444a6d696a1edb9e446d6f3482a70681be3c | https://github.com/Azerrroth/spacetimeformer/tree/e822444a6d696a1edb9e446d6f3482a70681be3c |
ActorNetwork | import torch
import torch as T
import torch.nn as nn
import torch.optim as optim
class ActorNetwork(nn.Module):
def __init__(self, alpha, state_dim, action_dim, fc1_dim, fc2_dim):
super(ActorNetwork, self).__init__()
self.fc1 = nn.Linear(state_dim, fc1_dim)
self.ln1 = nn.LayerNorm(fc1_dim... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | indigoLovee/TD3 | ActorNetwork | false | 6,889 | [
"MIT"
] | 1 | 0e86a40c27ec376b52e9f8e0e70db28e7411276b | https://github.com/indigoLovee/TD3/tree/0e86a40c27ec376b52e9f8e0e70db28e7411276b |
GaussActivation | import torch
from torch import nn
from torch.nn.parameter import Parameter
class GaussActivation(nn.Module):
def __init__(self, a, mu, sigma1, sigma2):
super(GaussActivation, self).__init__()
self.a = Parameter(torch.tensor(a, dtype=torch.float32))
self.mu = Parameter(torch.tensor(mu, dty... | 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
f... | delldu/ImagePatch | GaussActivation | false | 6,544 | [
"MIT"
] | 1 | aaeadba9fe9f40e9bf900468f100a06bafc8231f | https://github.com/delldu/ImagePatch/tree/aaeadba9fe9f40e9bf900468f100a06bafc8231f |
PadSameConv2d | # 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... | fish258/MonoRec | PadSameConv2d | false | 15,354 | [
"MIT"
] | 388 | c0612d2710802004cdd83205e63d0582de543c41 | https://github.com/fish258/MonoRec/tree/c0612d2710802004cdd83205e63d0582de543c41 |
DoubleResolutionLayer | import torch
import torch.nn as nn
class DoubleResolutionLayer(nn.Module):
def forward(self, x):
x = nn.functional.interpolate(x, scale_factor=2, mode='nearest')
return x
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | NunoEdgarGFlowHub/gandissect | DoubleResolutionLayer | false | 5,661 | [
"MIT"
] | 1 | 1a162a6bd3d4842139feb9f191aa1fad565dee4e | https://github.com/NunoEdgarGFlowHub/gandissect/tree/1a162a6bd3d4842139feb9f191aa1fad565dee4e |
SpatialCGNL | import torch
import torch.nn as nn
class SpatialCGNL(nn.Module):
"""Spatial CGNL block with dot production kernel for image classfication.
"""
def __init__(self, inplanes, planes, use_scale=False, groups=8):
self.use_scale = use_scale
self.groups = groups
super(SpatialCGNL, self).... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | zj1008/GALD-DGCNet | SpatialCGNL | false | 16,853 | [
"MIT"
] | 127 | be7ebfe2b3d28ea28a2b4714852999d4af2a785e | https://github.com/zj1008/GALD-DGCNet/tree/be7ebfe2b3d28ea28a2b4714852999d4af2a785e |
ExpNormalBasis | import torch
import numpy as np
import torch.nn as nn
class ExpNormalBasis(nn.Module):
def __init__(self, n_rbf, cutoff, learnable_mu, learnable_beta):
super().__init__()
self.mu = torch.linspace(np.exp(-cutoff), 1, n_rbf)
init_beta = (2 / n_rbf * (1 - np.exp(-cutoff))) ** -2
self... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import numpy as np
import torch.nn as nn
assert_size_stride = torch._C._d... | ClintvanHoesel/MXMNet_adapted | ExpNormalBasis | false | 304 | [
"MIT"
] | 0 | 091aae4a664b5b0944dfe95dbd2f5da441541437 | https://github.com/ClintvanHoesel/MXMNet_adapted/tree/091aae4a664b5b0944dfe95dbd2f5da441541437 |
LogCoshLoss | # 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
assert_size... | mfredriksz/semanticGAN_code | LogCoshLoss | false | 16,033 | [
"BSD-2-Clause",
"MIT"
] | 107 | c6e7b490086afd8a7593e2892452295555910494 | https://github.com/mfredriksz/semanticGAN_code/tree/c6e7b490086afd8a7593e2892452295555910494 |
WordPredictor | import torch
import torch.nn.functional as F
import torch.nn as nn
import torch.jit
import torch.jit.quantized
import torch.onnx.operators
class WordPredictor(nn.Module):
def __init__(self, encoder_output_dim, hidden_dim, output_dim,
topk_labels_per_source_token=None, use_self_attention=False):
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
import torch.nn.functional as... | Ayansam1152/translate | WordPredictor | false | 13,400 | [
"BSD-3-Clause"
] | 748 | 33d397fc25fb1072abd2975c77c602a2d031c6c4 | https://github.com/Ayansam1152/translate/tree/33d397fc25fb1072abd2975c77c602a2d031c6c4 |
MultiHeadAttention | import math
import torch
import numpy as np
from torch import nn
class MultiHeadAttention(nn.Module):
def __init__(self, n_heads, input_dim, embed_dim, val_dim=None, key_dim
=None):
super(MultiHeadAttention, self).__init__()
if val_dim is None:
val_dim = embed_dim // n_heads
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | lin-bo/RL_back2depot_VRP | MultiHeadAttention | false | 7,099 | [
"MIT"
] | 1 | 2a159d1df221ff314d98d79b8fde2b739a454ff7 | https://github.com/lin-bo/RL_back2depot_VRP/tree/2a159d1df221ff314d98d79b8fde2b739a454ff7 |
UniformNoiseGenerator | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch import device
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.distributions
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
... | AlexMeinke/Provable-OOD-Detection | UniformNoiseGenerator | false | 7,699 | [
"MIT"
] | 21 | 9a132aec994ff718c96b81885736ab866df60d87 | https://github.com/AlexMeinke/Provable-OOD-Detection/tree/9a132aec994ff718c96b81885736ab866df60d87 |
BertSelfOutput | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.utils.checkpoint
class BertSelfOutput(nn.Module):
def __init__(self, config):
super().__init__()
self.dense = nn.Linear(config.hidden_size, config.hidden_size)
self.LayerNorm = nn.LayerNorm(confi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | Hzfinfdu/Black-Box-Tuning | BertSelfOutput | false | 3,749 | [
"MIT"
] | 0 | 64eb5505875dc1b242c6f0a2a2f07e4000c24cb4 | https://github.com/Hzfinfdu/Black-Box-Tuning/tree/64eb5505875dc1b242c6f0a2a2f07e4000c24cb4 |
dream_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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | mkelcb/knet | dream_loss | false | 7,244 | [
"MIT"
] | 1 | f0e75f526c8bcdc6969052328b2b1b9cd6767cd8 | https://github.com/mkelcb/knet/tree/f0e75f526c8bcdc6969052328b2b1b9cd6767cd8 |
ScaledDotProductAttention | import torch
import numpy as np
import torch.utils.data
import torch.nn as nn
class ScaledDotProductAttention(nn.Module):
"""
Scaled dot-product attention
"""
def __init__(self, *, d_model: int, d_k: int, d_v: int, h: int):
"""
:param d_model: Output dimensionality of the model
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 |
FeedForward | # 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.... | sakrnference/data-to-text-hierarchical | FeedForward | false | 16,366 | [
"Apache-2.0"
] | 82 | 09b8fa8bf85385f25348378a30e830d425c93db3 | https://github.com/sakrnference/data-to-text-hierarchical/tree/09b8fa8bf85385f25348378a30e830d425c93db3 |
DenseSynthesizer | # 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_... | llucid-97/dfa-scales-to-modern-deep-learning | DenseSynthesizer | false | 15,945 | [
"MIT"
] | 63 | 66efb4b4ef8a378bf01ea0e5e6794d6bb4380c97 | https://github.com/llucid-97/dfa-scales-to-modern-deep-learning/tree/66efb4b4ef8a378bf01ea0e5e6794d6bb4380c97 |
Conv2dBlock | import torch
import torch.nn.functional as F
import torch.nn as 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 = mom... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn.functional as... | ricklentz/Seg-Uncertainty | Conv2dBlock | false | 16,322 | [
"MIT"
] | 298 | 82fd7056cccb265b3fc3e8a90338866661cab230 | https://github.com/ricklentz/Seg-Uncertainty/tree/82fd7056cccb265b3fc3e8a90338866661cab230 |
AttentionVasvani | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.gua... | a1247418/MT18_LH_human-sleep-classification | AttentionVasvani | false | 1,333 | [
"MIT"
] | 0 | c4a40571390aaa14b1cc8a458100e21252fe05d2 | https://github.com/a1247418/MT18_LH_human-sleep-classification/tree/c4a40571390aaa14b1cc8a458100e21252fe05d2 |
HessianResp | import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.init
import torch.nn
class HessianResp(nn.Module):
def __init__(self):
super(HessianResp, self).__init__()
self.gx = nn.Conv2d(1, 1, kernel_size=(1, 3), bias=False)
self.gx.weight.data = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import numpy ... | rdguez-mariano/affnet | HessianResp | false | 16,321 | [
"MIT"
] | 211 | a3f0bb32d9001d1daf024f38d29867f37816ea78 | https://github.com/rdguez-mariano/affnet/tree/a3f0bb32d9001d1daf024f38d29867f37816ea78 |
InvDepth | import torch
import torch.nn as nn
class InvDepth(nn.Module):
"""Inverse depth layer"""
def __init__(self, in_channels, out_channels=1, min_depth=0.5):
"""
Initializes an InvDepth object.
Parameters
----------
in_channels : int
Number of input 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | aliasghar53/packnet-sfm | InvDepth | false | 9,782 | [
"MIT"
] | 0 | d07dcbf026194b618a2bd9fc05b599563611f9a3 | https://github.com/aliasghar53/packnet-sfm/tree/d07dcbf026194b618a2bd9fc05b599563611f9a3 |
Net | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
class Net(nn.Module):
def __init__(self, device):
super(Net, self).__init__()
self.conv1 = nn.Conv2d(in_channels=1, out_channels=24, kernel_size=
5, padding=0)
self.conv2 = 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
import torch.nn as nn
import ... | IW276/IW276SS21P16 | Net | false | 9,338 | [
"MIT"
] | 0 | b798a2747c2b25a5e33fd8bcda91d9c52b9c01fc | https://github.com/IW276/IW276SS21P16/tree/b798a2747c2b25a5e33fd8bcda91d9c52b9c01fc |
AttentionPool2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | HIT-SCIR-xuanxuan/OpenKS | AttentionPool2d | false | 13,771 | [
"Apache-2.0"
] | 88 | a7f2ce0890822113322aad22e98d6c961e63caef | https://github.com/HIT-SCIR-xuanxuan/OpenKS/tree/a7f2ce0890822113322aad22e98d6c961e63caef |
CovarianceLayer | import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
class CovarianceLayer(nn.Module):
def __init__(self, patch_size=5, channels=1):
self.patch_size = patch_size
super(CovarianceLayer, self).__init__()
mean_mask = np.ones((channels, channels, patch_size, p... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | GuYuanjie/DeepFusionPrior | CovarianceLayer | false | 5,238 | [
"MIT"
] | 1 | a7126e073ed8c49b6a9a662492b64aaeee56cc01 | https://github.com/GuYuanjie/DeepFusionPrior/tree/a7126e073ed8c49b6a9a662492b64aaeee56cc01 |
conv_head_pooling | import torch
import torch.nn as nn
import torch.utils.data
class conv_head_pooling(nn.Module):
def __init__(self, in_feature, out_feature, stride, conv_type,
padding_mode='zeros', dilation=1):
super(conv_head_pooling, self).__init__()
if conv_type == 'depthwise':
_groups = in_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | sstsai-adl/d2go | conv_head_pooling | false | 16,489 | [
"Apache-2.0"
] | 687 | 6cff773797b14698043589afe57ea67cd76286f9 | https://github.com/sstsai-adl/d2go/tree/6cff773797b14698043589afe57ea67cd76286f9 |
PyramidPoolingModule | import torch
import torch.nn as nn
import torch.nn.functional as F
class PyramidPoolingModule(nn.Module):
def __init__(self, pyramids=[1, 2, 3, 6]):
super(PyramidPoolingModule, self).__init__()
self.pyramids = pyramids
def forward(self, input):
feat = input
height, width = in... | 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... | nassir90/ICNet-pytorch | PyramidPoolingModule | false | 16,140 | [
"MIT"
] | 83 | af6eec01a4419ce43c52d295bc502c366478fbd7 | https://github.com/nassir90/ICNet-pytorch/tree/af6eec01a4419ce43c52d295bc502c366478fbd7 |
ConvGLU | import torch
from torch import nn
import torch.utils.data
import torch.optim
def str2act(txt):
"""Translates text to neural network activation"""
return {'sigmoid': nn.Sigmoid(), 'relu': nn.ReLU(), 'none': nn.
Sequential(), 'lrelu': nn.LeakyReLU(0.2), 'selu': nn.SELU()}[txt.
lower()]
class 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
from torch import nn
import torch.utils.data
import torch.optim
assert_size_stri... | Oktai15/NeMo | ConvGLU | false | 5,670 | [
"Apache-2.0"
] | 1 | 5b6dd3850129898be47cf0d65587897ec45a5b59 | https://github.com/Oktai15/NeMo/tree/5b6dd3850129898be47cf0d65587897ec45a5b59 |
MlpMixer | # 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 ... | amayuelas/NNKGReasoning | MlpMixer | false | 6,221 | [
"MIT"
] | 1 | 0e3623b344fd4e3088ece897f898ddbb1f80888d | https://github.com/amayuelas/NNKGReasoning/tree/0e3623b344fd4e3088ece897f898ddbb1f80888d |
OneLayerFCBodyWithAction | import torch
import torch.nn as nn
import torch.nn.functional as F
def layer_init(layer, w_scale=1.0):
nn.init.orthogonal_(layer.weight.data)
layer.weight.data.mul_(w_scale)
nn.init.constant_(layer.bias.data, 0)
return layer
class OneLayerFCBodyWithAction(nn.Module):
def __init__(self, state_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
import torch.nn as nn
import ... | Sohojoe/UdacityDeepRL-Project2 | OneLayerFCBodyWithAction | false | 5,844 | [
"MIT"
] | 1 | 7137eea0b606ea32d00424d23130ff213f03ecf1 | https://github.com/Sohojoe/UdacityDeepRL-Project2/tree/7137eea0b606ea32d00424d23130ff213f03ecf1 |
Keypoint2DLoss | import torch
import torch.nn as nn
class Keypoint2DLoss(nn.Module):
def __init__(self, loss_type: 'str'='l1'):
"""
2D keypoint loss module.
Args:
loss_type (str): Choose between l1 and l2 losses.
"""
super(Keypoint2DLoss, self).__init__()
if loss_type =... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | michael-p-sachen/ProHMR | Keypoint2DLoss | false | 10,571 | [
"BSD-3-Clause"
] | 0 | 0167d05a9a45939a217d02b4ef8fd67977c15f82 | https://github.com/michael-p-sachen/ProHMR/tree/0167d05a9a45939a217d02b4ef8fd67977c15f82 |
VarianceNorm2d | # 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_... | samsartor/score_sde | VarianceNorm2d | false | 7,601 | [
"Apache-2.0"
] | 1 | d25c8d092a68d643c796d771c55f80075aa041d1 | https://github.com/samsartor/score_sde/tree/d25c8d092a68d643c796d771c55f80075aa041d1 |
PositionwiseFeedForward | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | SivilTaram/dialogue-utterance-rewriter-pytorch | PositionwiseFeedForward | false | 2,927 | [
"MIT"
] | 0 | 92c2254958b7a1ee9199836f7f2236575270983f | https://github.com/SivilTaram/dialogue-utterance-rewriter-pytorch/tree/92c2254958b7a1ee9199836f7f2236575270983f |
SmoothPinballLoss | import torch
from torch import nn
from torch.nn import functional
class SmoothPinballLoss(nn.Module):
"""
Smoth version of the pinball loss function.
Parameters
----------
quantiles : torch.tensor
alpha : int
Smoothing rate.
Attributes
----------
self.pred : torch.tensor
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.gua... | Javicadserres/wind-production-forecast | SmoothPinballLoss | false | 630 | [
"MIT"
] | 0 | 903fbf53d2ea34dc1a63e89cee252e76d6c25876 | https://github.com/Javicadserres/wind-production-forecast/tree/903fbf53d2ea34dc1a63e89cee252e76d6c25876 |
BoundSqrt | # 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 math
import numpy as np
import torch.nn as nn
import torch.nn.functional... | Mahoumaru/auto_LiRPA | BoundSqrt | false | 13,224 | [
"BSD-3-Clause"
] | 0 | b03a6c36eb1b921726778359d6d2b94e0cd7e480 | https://github.com/Mahoumaru/auto_LiRPA/tree/b03a6c36eb1b921726778359d6d2b94e0cd7e480 |
ResidualUnit | import torch
import torch.nn as nn
import torch.utils.model_zoo
def default_conv(in_channels, out_channels, kernel_size, bias=True):
return nn.Conv2d(in_channels, out_channels, kernel_size, padding=
kernel_size // 2, bias=bias)
class ResidualUnit(nn.Module):
def __init__(self, inChannel, outChannel... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.model_zoo
assert_size_stride = torch._C... | NawaNae/ESRT-Huawei | ResidualUnit | false | 2,664 | [
"MIT"
] | 0 | edea1c0bafec940dc7ea8e5110c355a83188665c | https://github.com/NawaNae/ESRT-Huawei/tree/edea1c0bafec940dc7ea8e5110c355a83188665c |
KeypointRCNNPredictor | import torch
import torch.utils.data
from torch import nn
class KeypointRCNNPredictor(nn.Module):
def __init__(self, in_channels, num_keypoints):
super(KeypointRCNNPredictor, self).__init__()
input_features = in_channels
deconv_kernel = 4
self.kps_score_lowres = nn.ConvTranspose2d... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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
from ... | Jack-XHP/LabPicV2-MaskRCNN | KeypointRCNNPredictor | false | 9,163 | [
"MIT"
] | 0 | b0586b2827000c7b7337d5110b2b1fd6185053a8 | https://github.com/Jack-XHP/LabPicV2-MaskRCNN/tree/b0586b2827000c7b7337d5110b2b1fd6185053a8 |
LinearCombine | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
import torch.optim
import torch.utils.data
class LinearCombine(nn.Module):
def __init__(self, layers_num, trainable=True, input_aware=False,
word_level=False):
super(LinearCombine, self).__init__()
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import ... | HarshCasper/nni | LinearCombine | false | 5,284 | [
"MIT"
] | 1 | 291bbbba9f296382015a77b2c88eb5db5b44bf94 | https://github.com/HarshCasper/nni/tree/291bbbba9f296382015a77b2c88eb5db5b44bf94 |
BertAttention | from _paritybench_helpers import _mock_config
import math
import torch
import torch.utils.data
import torch.nn as nn
import torch.nn
import torch as torch
import torch.sparse
class BertSelfAttention(nn.Module):
def __init__(self, config):
super(BertSelfAttention, self).__init__()
if config.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 import triton_helpers
from torch._inductor.runtime.... | Sengxian/cogdl | BertAttention | false | 4,734 | [
"MIT"
] | 0 | b0a855feef6a883bcc0f7df421fc6092ec18abde | https://github.com/Sengxian/cogdl/tree/b0a855feef6a883bcc0f7df421fc6092ec18abde |
GumbelQuantizer | # 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.... | TobiasNorlund/vq-vae | GumbelQuantizer | false | 5,920 | [
"Apache-2.0"
] | 1 | bdfc35f35491e8d4877a13f7f84d6cbdcc69daa0 | https://github.com/TobiasNorlund/vq-vae/tree/bdfc35f35491e8d4877a13f7f84d6cbdcc69daa0 |
CenteredL1Loss | import torch
from torch.nn.functional import l1_loss
class CenteredL1Loss(torch.nn.Module):
def __init__(self, margin):
super(CenteredL1Loss, self).__init__()
self.m = margin
def forward(self, true, preds):
return l1_loss(preds[:, :, self.m:-self.m, self.m:-self.m], true[:,
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | wsdea/EfficientSR | CenteredL1Loss | false | 4,541 | [
"MIT"
] | 0 | 077dea18c90e0d5bed722c609a776033c09f80e6 | https://github.com/wsdea/EfficientSR/tree/077dea18c90e0d5bed722c609a776033c09f80e6 |
Swish | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | CW-Huang/sdeflow-light | Swish | false | 7,830 | [
"MIT"
] | 35 | 524650bc5ad69522b3e0905672deef0650374512 | https://github.com/CW-Huang/sdeflow-light/tree/524650bc5ad69522b3e0905672deef0650374512 |
FCNet | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
class FCNet(nn.Module):
def __init__(self, input_size, output_size):
super().__init__()
self.l1 = nn.Linear(input_size, 5)
self.relu = nn.ReLU()
self.l2 = nn.Linear(5, output_siz... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | savan77/nni | FCNet | false | 4,277 | [
"MIT"
] | 0 | 510213393d9cae58c5a8cccd21f322f7bba4e0cf | https://github.com/savan77/nni/tree/510213393d9cae58c5a8cccd21f322f7bba4e0cf |
ContextGate | import torch
import torch.nn as nn
import torch.cuda
import torch.distributed
class ContextGate(nn.Module):
"""
Context gate is a decoder module that takes as input the previous word
embedding, the current decoder state and the attention state, and
produces a gate.
The gate can be used to select t... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.cuda
import torch.distributed
assert_size_str... | ChenRocks/Distill-BERT-Textgen-ONMT | ContextGate | false | 17,100 | [
"MIT"
] | 7 | d83dd1a95af7513cbfae4a2768f6effc2f3a589f | https://github.com/ChenRocks/Distill-BERT-Textgen-ONMT/tree/d83dd1a95af7513cbfae4a2768f6effc2f3a589f |
FirstStage | # 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 ... | YibinXie/Pose_Estimation | FirstStage | false | 2,987 | [
"MIT"
] | 0 | 5849140bf842bf3aeaad75827f5e7b7f2999c9ee | https://github.com/YibinXie/Pose_Estimation/tree/5849140bf842bf3aeaad75827f5e7b7f2999c9ee |
PatchEmbed | import torch
from itertools import chain as chain
import torch.utils.data
import torch.nn as nn
class PatchEmbed(nn.Module):
"""
PatchEmbed.
"""
def __init__(self, dim_in=3, dim_out=768, kernel=(1, 16, 16), stride=(1,
4, 4), padding=(1, 7, 7), conv_2d=False):
super().__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 itertools import chain as chain
import torch.utils.data
import torch.nn as ... | makarandtapaswi/SlowFast | PatchEmbed | false | 16,000 | [
"Apache-2.0"
] | 4,914 | 39ef35c9a086443209b458cceaec86a02e27b369 | https://github.com/makarandtapaswi/SlowFast/tree/39ef35c9a086443209b458cceaec86a02e27b369 |
ContrastiveLoss | import torch
import torchvision.transforms.functional as F
import torch.nn.functional as F
import torch.nn as nn
class ContrastiveLoss(nn.Module):
"""
Contrastive loss function.
Based on: http://yann.lecun.com/exdb/publis/pdf/hadsell-chopra-lecun-06.pdf
"""
def __init__(self, margin=2.0):
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | chenyanghungry/person-reid-lib | ContrastiveLoss | false | 15,019 | [
"MIT"
] | 81 | 783e66c9bfedf582e2cf935b9f5be960b543ac3c | https://github.com/chenyanghungry/person-reid-lib/tree/783e66c9bfedf582e2cf935b9f5be960b543ac3c |
MeanMaxPooling | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | HLTCHKUST/MulQG | MeanMaxPooling | false | 8,189 | [
"MIT"
] | 19 | 8e257f2d6c0f03c07ea8a0bf0e8f55b0cde60605 | https://github.com/HLTCHKUST/MulQG/tree/8e257f2d6c0f03c07ea8a0bf0e8f55b0cde60605 |
T5DenseReluDense | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | Elvisambition/bert_seq2seq | T5DenseReluDense | false | 7,619 | [
"Apache-2.0"
] | 1 | 643ac537c16872f0d13200de06001d8201a54fbb | https://github.com/Elvisambition/bert_seq2seq/tree/643ac537c16872f0d13200de06001d8201a54fbb |
Flip | # 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.nn.init
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dy... | Johnson-yue/TensorMONK | Flip | false | 5,406 | [
"MIT"
] | 1 | 1785132b82c685c3b3fc05b00dec46b1fccfc948 | https://github.com/Johnson-yue/TensorMONK/tree/1785132b82c685c3b3fc05b00dec46b1fccfc948 |
MultiheadAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
def fill_with_neg_inf(t):
"""FP16-compatible function that fills a tensor with -inf."""
return t.float().fill_(float('-inf')).type_as(t)
def _get_full_incremental_state_key(module_instance, key):
module_name = module_instance.__class__._... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Blind-Aid/sentiment-discovery | MultiheadAttention | false | 13,422 | [
"BSD-3-Clause"
] | 1,093 | 081c7c855e00864b52e97cac0b0e097cc86d9731 | https://github.com/Blind-Aid/sentiment-discovery/tree/081c7c855e00864b52e97cac0b0e097cc86d9731 |
ElectronicAsymptotic | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | MikeEntwistle/deepqmc | ElectronicAsymptotic | false | 17,730 | [
"MIT"
] | 4 | b5c20bf1768f04227becd5079c6b40aefc97d26c | https://github.com/MikeEntwistle/deepqmc/tree/b5c20bf1768f04227becd5079c6b40aefc97d26c |
SpatialDepthWisePerHeadConvolution | from torch.nn import Module
import torch
from torch import nn
import torch.utils.data
import torch.nn.functional
import torch.autograd
class SpatialDepthWisePerHeadConvolution(Module):
"""
## Spatial Depth Wise Per Head Convolution
"""
def __init__(self, heads: 'int', d_k: 'int', kernel_size: 'int'=3... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import Module
from torch import nn
import torch.utils.data
import ... | techthiyanes/annotated_deep_learning_paper_implementations | SpatialDepthWisePerHeadConvolution | false | 16,569 | [
"MIT"
] | 3,714 | 8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 | https://github.com/techthiyanes/annotated_deep_learning_paper_implementations/tree/8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 |
SimpleNet | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | haakonrob/AI-Feynman | SimpleNet | false | 10,146 | [
"MIT"
] | 0 | 445b68e9a260dcea67a94eed6e0aeb267f25d2ef | https://github.com/haakonrob/AI-Feynman/tree/445b68e9a260dcea67a94eed6e0aeb267f25d2ef |
BentIdentity | # 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_... | awlange/pysurvival | BentIdentity | false | 14,923 | [
"Apache-2.0"
] | 242 | 841b9bc6ce700ba8898d2a1488aa9cd25ee7a8e6 | https://github.com/awlange/pysurvival/tree/841b9bc6ce700ba8898d2a1488aa9cd25ee7a8e6 |
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.... | sridas123/TD3 | Actor | false | 12,996 | [
"MIT"
] | 0 | 2556c952ef7623c8201fdfdd9102e23d98101f5c | https://github.com/sridas123/TD3/tree/2556c952ef7623c8201fdfdd9102e23d98101f5c |
HardSigmoid | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
import torch.utils.data.distributed
from torch import nn
import t... | Adlik/zen_nas | HardSigmoid | false | 16,863 | [
"Apache-2.0"
] | 7 | d820d5c7d5bbb6fd66a76d5f16513647d6ea7a57 | https://github.com/Adlik/zen_nas/tree/d820d5c7d5bbb6fd66a76d5f16513647d6ea7a57 |
ChannelSpatialSELayer3D | # 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 ... | HiLab-git/PyMIC | ChannelSpatialSELayer3D | false | 13,785 | [
"Apache-2.0"
] | 147 | abf5c43de43668b85f4c049c95a8f1b7cf1d9f16 | https://github.com/HiLab-git/PyMIC/tree/abf5c43de43668b85f4c049c95a8f1b7cf1d9f16 |
ActorCriticNetwork | import torch
import torch.nn as nn
import torch.nn.functional as F
class ActorCriticNetwork(nn.Module):
def __init__(self, num_inputs, num_actions, hidden_size=256):
super(ActorCriticNetwork, self).__init__()
self.num_actions = num_actions
self.critic_linear1 = nn.Linear(num_inputs, hidde... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | linklab/link_rl_book_codes | ActorCriticNetwork | false | 10,421 | [
"MIT"
] | 0 | b272b46d5ecd2802f34648440ff53641c68cbbf0 | https://github.com/linklab/link_rl_book_codes/tree/b272b46d5ecd2802f34648440ff53641c68cbbf0 |
DiceLoss4BraTS | import torch
from torch import nn
import torch.jit
import torch.nn.functional
class BinaryDiceLoss(nn.Module):
def __init__(self, smooth=1, p=2, reduction='mean'):
super(BinaryDiceLoss, self).__init__()
self.smooth = smooth
self.p = p
self.reduction = reduction
def forward(se... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.jit
import torch.nn.functional
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strid... | MargeryLab/nnConRes | DiceLoss4BraTS | false | 9,332 | [
"Apache-2.0"
] | 0 | a5aba912d0f0f30490ae820fb6d3dbb8cf1556d4 | https://github.com/MargeryLab/nnConRes/tree/a5aba912d0f0f30490ae820fb6d3dbb8cf1556d4 |
ConcatCell | import torch
import torch as th
import torch.nn as nn
class ConcatCell(nn.Module):
def __init__(self, input_dim):
super(ConcatCell, self).__init__()
self.input_dim = input_dim
def forward(self, x1, x2):
return th.cat([x1, x2], dim=-1)
def get_output_dim(self):
return sel... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | HKUST-KnowComp/DisCOC | ConcatCell | false | 17,331 | [
"MIT"
] | 4 | d9e10d4938ef485254551fdb6c1a36eb31a26cfd | https://github.com/HKUST-KnowComp/DisCOC/tree/d9e10d4938ef485254551fdb6c1a36eb31a26cfd |
LinearModel | import torch
import torch.nn as nn
class LinearModel(nn.Module):
"""Linear model applying on the logits alpha * x + beta.
By default, this model is initialized as an identity operation.
See https://arxiv.org/abs/1905.13260 for an example usage.
:param alpha: A learned scalar.
:param beta: A lea... | 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... | billpsomas/incremental_learning.pytorch | LinearModel | false | 14,961 | [
"MIT"
] | 277 | a401a6609fc61c74698739cf937c0ece1c10913f | https://github.com/billpsomas/incremental_learning.pytorch/tree/a401a6609fc61c74698739cf937c0ece1c10913f |
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 ... | taomo/pytorch-A3C-1 | Net | false | 4,413 | [
"MIT"
] | 0 | 8e26720c75ca8b7e987b267e5e0e652d0c5d23cf | https://github.com/taomo/pytorch-A3C-1/tree/8e26720c75ca8b7e987b267e5e0e652d0c5d23cf |
Mean | import torch
from torchvision.datasets import *
import torch.nn as nn
from torchvision.transforms import *
class Mean(nn.Module):
def __init__(self, dim, keep_dim=False):
super(Mean, self).__init__()
self.dim = dim
self.keep_dim = keep_dim
def forward(self, input):
return inp... | 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 torchvision.datasets import *
import torch.nn as nn
from torchvision.transforms import *
assert_size_stride = torch._C._dynamo.guards.a... | tousifulhaque/DANet | Mean | false | 4,484 | [
"MIT"
] | 0 | 1a0c91f0e551a071b5e335b4157313780a8a1b1a | https://github.com/tousifulhaque/DANet/tree/1a0c91f0e551a071b5e335b4157313780a8a1b1a |
UpsampleConvLayer | # 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.... | MKFMIKU/PFFNet | UpsampleConvLayer | false | 8,498 | [
"MIT"
] | 41 | e506010a7cf00a32e77681845bdaf78ba88b027d | https://github.com/MKFMIKU/PFFNet/tree/e506010a7cf00a32e77681845bdaf78ba88b027d |
ScalarMix | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | TheSecret3003/crf_parser | ScalarMix | false | 2,900 | [
"MIT"
] | 0 | 34682ca8729d376b5582a3117e650b524fbcb355 | https://github.com/TheSecret3003/crf_parser/tree/34682ca8729d376b5582a3117e650b524fbcb355 |
CatConv | import torch
import torch.nn as nn
class CatConv(nn.Module):
def __init__(self, in_kernels_1, in_kernels_2, kernels):
super(CatConv, self).__init__()
self.conv = nn.Conv2d(in_kernels_1 + in_kernels_2, kernels,
kernel_size=1, bias=True)
def forward(self, x1, x2):
x1 = torc... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | ColinKohler/ActionDyanmicsNetwork | CatConv | false | 313 | [
"MIT"
] | 0 | 9cb6ffca111bfb1e1efb31cbac9201a98739a6ed | https://github.com/ColinKohler/ActionDyanmicsNetwork/tree/9cb6ffca111bfb1e1efb31cbac9201a98739a6ed |
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