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 |
|---|---|---|---|---|---|---|---|---|---|---|
layer_normalization | # 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_... | Woodytse/transformer | layer_normalization | false | 11,968 | [
"MIT"
] | 0 | 56f7c3051765e8cb3c34d2e9a41d483cec162256 | https://github.com/Woodytse/transformer/tree/56f7c3051765e8cb3c34d2e9a41d483cec162256 |
SimpleGeluModule | import torch
import torch.jit
import torch.nn.functional as F
import torch.onnx
import torch.nn
class SimpleGeluModule(torch.nn.Module):
def forward(self, tensor):
return F.gelu(tensor + tensor)
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.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._... | YaronBenAtar/glow | SimpleGeluModule | false | 14,665 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
Conv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | sakshi-06/pystiche | Conv | false | 7,595 | [
"BSD-3-Clause"
] | 1 | 21a67364b332a34a2308a929f200900c76be5b73 | https://github.com/sakshi-06/pystiche/tree/21a67364b332a34a2308a929f200900c76be5b73 |
ResizeTransform | # 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... | Zer0-00/voxelmorph | ResizeTransform | false | 12,028 | [
"Apache-2.0"
] | 0 | ed2e0384cf22d19f7e57bea5887fc197d55f60bc | https://github.com/Zer0-00/voxelmorph/tree/ed2e0384cf22d19f7e57bea5887fc197d55f60bc |
FFN | # 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_... | baburamShapure/federatedGraphConv | FFN | false | 3,157 | [
"MIT"
] | 0 | 015e502fcf1b911ab23572b00c547591a4bdf378 | https://github.com/baburamShapure/federatedGraphConv/tree/015e502fcf1b911ab23572b00c547591a4bdf378 |
ConvModule | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import warnings
import torch.... | Complicateddd/Complicateddd-ROITransformer | ConvModule | false | 11,309 | [
"Apache-2.0"
] | 0 | 2adfbf98892d569c460d100c6e2169c5fa3a9b82 | https://github.com/Complicateddd/Complicateddd-ROITransformer/tree/2adfbf98892d569c460d100c6e2169c5fa3a9b82 |
SchedulerTestNet | # 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... | bzrry/lightning-bolts | SchedulerTestNet | false | 14,994 | [
"Apache-2.0"
] | 822 | bd392ad858039290c72c20cc3f10df39384e90b9 | https://github.com/bzrry/lightning-bolts/tree/bd392ad858039290c72c20cc3f10df39384e90b9 |
TargetContextGate | # 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 ... | AndrewM1998/MultimodalNMT | TargetContextGate | false | 7,710 | [
"MIT"
] | 40 | b66d3a40ac9bc5c11ae124f51d1a9abf7cd6a04b | https://github.com/AndrewM1998/MultimodalNMT/tree/b66d3a40ac9bc5c11ae124f51d1a9abf7cd6a04b |
softCE | # 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
... | s-tatsu/AutoNER | softCE | false | 16,351 | [
"Apache-2.0"
] | 446 | 75f8d092a5bf83fabf4ac4e879fab9120bbcd083 | https://github.com/s-tatsu/AutoNER/tree/75f8d092a5bf83fabf4ac4e879fab9120bbcd083 |
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
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Bartolo1024/ignite | Policy | false | 4,900 | [
"BSD-3-Clause"
] | 1 | b087fef0bc5f97cda415c1c56f1cd589383c54be | https://github.com/Bartolo1024/ignite/tree/b087fef0bc5f97cda415c1c56f1cd589383c54be |
EqualConvTranspose2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from math import sqrt
import torch.utils.data
assert_size_... | GuiCamargoX/gans_pytorch | EqualConvTranspose2d | false | 9,139 | [
"MIT"
] | 0 | 3103184e54ea0d2922fc664a994a912bf61db426 | https://github.com/GuiCamargoX/gans_pytorch/tree/3103184e54ea0d2922fc664a994a912bf61db426 |
PositionWiseFeedForward | import torch
from torch import nn
class PositionWiseFeedForward(nn.Module):
"""
Position-Wise Feed-Forward Network
Parameters
----------
d_model : int
Size of word embeddings
hidden_size : int
Size of position-wise feed forward network
dropout : float
Dropout
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Renovamen/Text-Classification | PositionWiseFeedForward | false | 14,281 | [
"MIT"
] | 72 | 4a4aa4001c402ed4371ebaabe1393b27794e5992 | https://github.com/Renovamen/Text-Classification/tree/4a4aa4001c402ed4371ebaabe1393b27794e5992 |
MinusOne | # 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.optim
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strid... | ai-in-motion/moai | MinusOne | false | 18,315 | [
"Apache-2.0"
] | 10 | e38cac046c059d2e2331ef4883bbabc5a500a5cf | https://github.com/ai-in-motion/moai/tree/e38cac046c059d2e2331ef4883bbabc5a500a5cf |
SimpleTypeasModel | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleTypeasModel(torch.nn.Module):
def __init__(self):
super(SimpleTypeasModel, self).__init__()
def forward(self, tensor, other=None):
other = tensor if other is None else other
if tensor.dtype != torch.bool:
... | 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 | SimpleTypeasModel | false | 12,595 | [
"Apache-2.0"
] | 0 | 4c919d60b3c33296c4109aec8020a1733c98f5b5 | https://github.com/briancoutinho/glow/tree/4c919d60b3c33296c4109aec8020a1733c98f5b5 |
GlobalAttention | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Roc-Ng/HANet | GlobalAttention | false | 8,702 | [
"MIT"
] | 34 | e679703e9e725205424d87f750358fb4f62ceec5 | https://github.com/Roc-Ng/HANet/tree/e679703e9e725205424d87f750358fb4f62ceec5 |
Project3D | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | mattpoggi/depthstillation | Project3D | false | 16,018 | [
"MIT"
] | 122 | b74ea4343d8d9f082c82e9f72d9294200aea8bb7 | https://github.com/mattpoggi/depthstillation/tree/b74ea4343d8d9f082c82e9f72d9294200aea8bb7 |
MultiLabelCircleLoss | import torch
from torch import nn
class MultiLabelCircleLoss(nn.Module):
def __init__(self, reduction='mean', inf=1000000000000.0):
"""CircleLoss of MultiLabel, 多个目标类的多标签分类场景，希望“每个目标类得分都不小于每个非目标类的得分”
多标签分类的交叉熵(softmax+crossentropy推广, N选K问题), LSE函数的梯度恰好是softmax函数
让同类相似度与非同类相似度之间拉开一定的margin... | 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... | dumpmemory/Pytorch-NLU | MultiLabelCircleLoss | false | 15,281 | [
"Apache-2.0"
] | 115 | 864fb9acc7751fc51abd3d05d24b5a9a7eab7110 | https://github.com/dumpmemory/Pytorch-NLU/tree/864fb9acc7751fc51abd3d05d24b5a9a7eab7110 |
GAT | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | jk96491/SMAC | GAT | false | 15,726 | [
"Apache-2.0"
] | 64 | 7aaf4673b0eecafc4ab25f381eea20fc762af56a | https://github.com/jk96491/SMAC/tree/7aaf4673b0eecafc4ab25f381eea20fc762af56a |
UNet | # 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.... | jabae/detectEM | UNet | false | 7,052 | [
"MIT"
] | 1 | 2d1a5116164d0bed0a8ea767a227d05a8970a448 | https://github.com/jabae/detectEM/tree/2d1a5116164d0bed0a8ea767a227d05a8970a448 |
SmallAdversarialNetwork | # 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_... | caozhangjie/kinetics_i3d_pytorch | SmallAdversarialNetwork | false | 9,923 | [
"MIT"
] | 0 | 237713bb76cf71b6d60d1a4df98f00df3a489cc3 | https://github.com/caozhangjie/kinetics_i3d_pytorch/tree/237713bb76cf71b6d60d1a4df98f00df3a489cc3 |
ContourDTConsistency | import torch
from typing import Optional
import torch.utils.data
import torch.nn as nn
import torch.nn.parallel
class ContourDTConsistency(nn.Module):
"""Consistency regularization between the instance contour map and
signed distance transform.
Args:
pred1 (torch.Tensor): contour logits.
... | 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... | Atharva-Peshkar/pytorch_connectomics | ContourDTConsistency | false | 13,308 | [
"MIT"
] | 99 | 8eccd9640a9a454d4df095a3529a030e58f882f5 | https://github.com/Atharva-Peshkar/pytorch_connectomics/tree/8eccd9640a9a454d4df095a3529a030e58f882f5 |
Classifier | import torch
import torch.nn as nn
class Classifier(nn.Module):
def __init__(self, n_hid, n_out):
super(Classifier, self).__init__()
self.n_hid = n_hid
self.n_out = n_out
self.linear = nn.Linear(n_hid, n_out)
def forward(self, x):
tx = self.linear(x)
return to... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | KathleenQ/context-aware-doc-analysis | Classifier | false | 11,610 | [
"MIT"
] | 0 | 93af994b2dee09f5fe6bfcc2e76e47e74708d3fe | https://github.com/KathleenQ/context-aware-doc-analysis/tree/93af994b2dee09f5fe6bfcc2e76e47e74708d3fe |
ISub | # 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_sub_0(in_ptr0, in_ptr1, out_ptr1, xnumel,... | NVIDIA-AI-IOT-private/torch2trt | ISub | false | 10,516 | [
"MIT"
] | 0 | 953d60039e0c81e90eea467c3df2e6e3f7040242 | https://github.com/NVIDIA-AI-IOT-private/torch2trt/tree/953d60039e0c81e90eea467c3df2e6e3f7040242 |
AutoregressiveShift | import torch
import torch.nn as nn
class AutoregressiveShift(nn.Module):
"""Shifts input right to make model autoregressive."""
def __init__(self, embed_dim):
super(AutoregressiveShift, self).__init__()
self.embed_dim = embed_dim
self.first_token = nn.Parameter(torch.Tensor(1, 1, embe... | 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... | Nintorac/survae_experiments | AutoregressiveShift | false | 902 | [
"MIT"
] | 0 | d68cc25e2604aab08b53617c1f3ffe4716f166c4 | https://github.com/Nintorac/survae_experiments/tree/d68cc25e2604aab08b53617c1f3ffe4716f166c4 |
MultiheadAttention | import torch
import torch.nn as nn
from torch.nn import Parameter
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_nam... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ArkanDH/Team5-Inverse-Cooking-Stuff | MultiheadAttention | false | 2,003 | [
"MIT"
] | 0 | ec224918b25fb7a04aa09995e4d11804448df7dd | https://github.com/ArkanDH/Team5-Inverse-Cooking-Stuff/tree/ec224918b25fb7a04aa09995e4d11804448df7dd |
AvgPoolPad | # 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.utils.data
import torch.nn as nn
from torch import optim as optim
import torch.nn.parallel
assert_size_stride = torch._C._dynam... | Exir-lxr/crldr-prune-pytorch | AvgPoolPad | false | 2,297 | [
"Apache-2.0"
] | 0 | adeb5e0b24ce66ff9531d4d947f72412c1b5c033 | https://github.com/Exir-lxr/crldr-prune-pytorch/tree/adeb5e0b24ce66ff9531d4d947f72412c1b5c033 |
VGG16 | # 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
import tor... | SharhadBashar/1-stage-wseg | VGG16 | false | 5,913 | [
"Apache-2.0"
] | 1 | 83bf13444f5039ffed2de1605f09b3f90b525586 | https://github.com/SharhadBashar/1-stage-wseg/tree/83bf13444f5039ffed2de1605f09b3f90b525586 |
MAB | import math
import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
def qkv_attention(queries, keys, values, presence=None):
"""
Transformer-like self-attention.
Args:
queries: Tensor of shape [B, N, d_k].
keys: Tensor of shape [B, M, d_k].
values: : Tensor... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | karayanni/torch-scae | MAB | false | 10,431 | [
"Apache-2.0"
] | 0 | e044662d8942d8d1923d13d071f375144cf4a1e8 | https://github.com/karayanni/torch-scae/tree/e044662d8942d8d1923d13d071f375144cf4a1e8 |
PlainRefiner | # 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_... | Juggernaut93/mmediting | PlainRefiner | false | 13,910 | [
"Apache-2.0"
] | 1,884 | 8ef46ace29756dd2df1d92f2f73a33646e33e007 | https://github.com/Juggernaut93/mmediting/tree/8ef46ace29756dd2df1d92f2f73a33646e33e007 |
SoftTargetCrossEntropy | import torch
from typing import *
import torch.nn.functional as F
from torch.nn.modules.loss import _WeightedLoss
class SoftTargetCrossEntropy(_WeightedLoss):
def __init__(self, weight=None, reduction='mean'):
super().__init__(weight=weight, reduction=reduction)
self.weight = weight
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 import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from typing import *
f... | SuHuynh/leaf-disease-classification-kaggle | SoftTargetCrossEntropy | false | 9,484 | [
"MIT"
] | 0 | b1c15881de5a20e590a69f6b2fbb476b003bc077 | https://github.com/SuHuynh/leaf-disease-classification-kaggle/tree/b1c15881de5a20e590a69f6b2fbb476b003bc077 |
JointsMSELoss | import torch
import torch.nn as nn
import torch.utils.data
class JointsMSELoss(nn.Module):
def __init__(self, use_target_weight):
super(JointsMSELoss, self).__init__()
self.criterion = nn.MSELoss(size_average=True)
self.use_target_weight = use_target_weight
def forward(self, 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
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | AlongRide/Py3torch_HigherHRNet | JointsMSELoss | false | 4,829 | [
"MIT"
] | 1 | 62c455b62c0ac6d1de482fd3740dc947033e9e9a | https://github.com/AlongRide/Py3torch_HigherHRNet/tree/62c455b62c0ac6d1de482fd3740dc947033e9e9a |
idct_8x8 | import itertools
import torch
import numpy as np
from torch import nn
class idct_8x8(nn.Module):
""" Inverse discrete Cosine Transformation
Input:
dcp(tensor): batch x height x width
Output:
image(tensor): batch x height x width
"""
def __init__(self):
super(idct_8x8, 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
import itertools
import numpy as np
from torch import nn
assert_size_stride = to... | Liamkuo/SAIR | idct_8x8 | false | 17,576 | [
"MIT"
] | 6 | 0fb289cd975b5a196b58e7d16bac00e31fd41d39 | https://github.com/Liamkuo/SAIR/tree/0fb289cd975b5a196b58e7d16bac00e31fd41d39 |
PixelNorm | import torch
import torch.nn as nn
def pixel_norm(x, eps=1e-06):
"""Pixel Normalization.
This normalization is proposed in:
Progressive Growing of GANs for Improved Quality, Stability, and Variation
Args:
x (torch.Tensor): Tensor to be normalized.
eps (float, optional): Epsilon to av... | 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_... | matrixgame2018/mmediting | PixelNorm | false | 16,021 | [
"Apache-2.0"
] | 1,884 | 5170a64a586cc876a5cb459fbfa0cf9b55bfa5fd | https://github.com/matrixgame2018/mmediting/tree/5170a64a586cc876a5cb459fbfa0cf9b55bfa5fd |
PGNet | # 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.... | Lovestarni/Reinforcement-learning-with-tensorflow | PGNet | false | 9,289 | [
"MIT"
] | 0 | 822a4ae812b044687c11138ef9c9db1e1190f98c | https://github.com/Lovestarni/Reinforcement-learning-with-tensorflow/tree/822a4ae812b044687c11138ef9c9db1e1190f98c |
SCRM | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | DemoAuguste/ZAQ-code | SCRM | false | 9,078 | [
"MIT"
] | 0 | 9986a2d217ab5cb284e08c062f8726cabacb311e | https://github.com/DemoAuguste/ZAQ-code/tree/9986a2d217ab5cb284e08c062f8726cabacb311e |
ScaledDotProduction | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Jincheng-Sun/Kylearn-pytorch | ScaledDotProduction | false | 639 | [
"MIT"
] | 0 | e72f2ab45a3f4724e843a27bec37664d3612fdca | https://github.com/Jincheng-Sun/Kylearn-pytorch/tree/e72f2ab45a3f4724e843a27bec37664d3612fdca |
layer_1_to_1 | # 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 numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | HyTruongSon/InvariantGraphNetworks-PyTorch | layer_1_to_1 | false | 17,411 | [
"Apache-2.0"
] | 7 | da9fdaa4f858d6fcae14b08a59d4b172a2aabaf8 | https://github.com/HyTruongSon/InvariantGraphNetworks-PyTorch/tree/da9fdaa4f858d6fcae14b08a59d4b172a2aabaf8 |
ExtResNetBlock | import torch
from torch.nn import functional as F
import torch.nn as nn
def padding(im, patch_size, fill_value=0):
H, W = im.size(2), im.size(3)
pad_h, pad_w = 0, 0
if H % patch_size > 0:
pad_h = patch_size - H % patch_size
if W % patch_size > 0:
pad_w = patch_size - W % patch_size
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch.nn impor... | Curli-quan/fewshot-select | ExtResNetBlock | false | 17,211 | [
"Apache-2.0"
] | 7 | 34f8ce5069ed1fbd01c1fa73a3ef264c98dadafe | https://github.com/Curli-quan/fewshot-select/tree/34f8ce5069ed1fbd01c1fa73a3ef264c98dadafe |
WeightedCrossEntropyLoss | # 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
... | CSL-KU/OpenPCDet | WeightedCrossEntropyLoss | false | 2,093 | [
"Apache-2.0"
] | 0 | 2c5fca0da1521add4b40e6cdfe75d02d4285b83f | https://github.com/CSL-KU/OpenPCDet/tree/2c5fca0da1521add4b40e6cdfe75d02d4285b83f |
SingleHead | # 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 ... | StevenGrove/DynamicHead | SingleHead | false | 14,441 | [
"Apache-2.0"
] | 69 | d62aa84e1d1c6a0c74d46258ad77b11413c10bef | https://github.com/StevenGrove/DynamicHead/tree/d62aa84e1d1c6a0c74d46258ad77b11413c10bef |
Discriminator | # 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 numpy as np
from torch import nn
assert_size_stride = torch._C._dynamo.gu... | Benjamin-Etheredge/lightning-bolts | Discriminator | false | 169 | [
"Apache-2.0"
] | 0 | 1971d6a924729940b98793aa7751bdf769350aca | https://github.com/Benjamin-Etheredge/lightning-bolts/tree/1971d6a924729940b98793aa7751bdf769350aca |
GaussianKernel | # 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
... | neka-nat/Transfer-Learning-Library | GaussianKernel | false | 16,150 | [
"MIT"
] | 1,474 | a3b27b0d7562fa90a02e914140b37ab438469e6c | https://github.com/neka-nat/Transfer-Learning-Library/tree/a3b27b0d7562fa90a02e914140b37ab438469e6c |
SamePad2dStrong | import math
import torch
import torch.nn.functional as F
import torch.nn as nn
class SamePad2dStrong(nn.Module):
"""Mimics tensorflow's 'SAME' padding.
"""
def __init__(self, kernel_size, stride):
super(SamePad2dStrong, self).__init__()
self.kernel_size = torch.nn.modules.utils._pair(kern... | 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... | IssamLaradji/wisenet | SamePad2dStrong | false | 17,436 | [
"Apache-2.0"
] | 7 | 881457f5168815f5e9d03f110244842d539747a0 | https://github.com/IssamLaradji/wisenet/tree/881457f5168815f5e9d03f110244842d539747a0 |
SimpleCumSumModule | # 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 | SimpleCumSumModule | false | 3,319 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
Block | import torch
from torch import nn
from torch.nn import functional as F
def get_conv(in_dim, out_dim, kernel_size, stride, padding, zero_bias=True,
zero_weights=False, groups=1, scaled=False):
c = nn.Conv2d(in_dim, out_dim, kernel_size, stride, padding, groups=groups)
if zero_bias:
c.bias.data *= 0... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | seunghyukcho/vdvae | Block | false | 12,966 | [
"MIT"
] | 0 | 3a552d80351d670fdbde8302c556a6e668d33762 | https://github.com/seunghyukcho/vdvae/tree/3a552d80351d670fdbde8302c556a6e668d33762 |
depthwise_block | import torch
import torch.nn as nn
import torch.utils.data
class depthwise_conv(nn.Module):
def __init__(self, kernel_size=3, stride=1, padding=1):
super(depthwise_conv, self).__init__()
self.depthwise = nn.Conv2d(1, 1, kernel_size=kernel_size, stride=
stride, padding=padding)
de... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | Zacchaeus14/lang-seg | depthwise_block | false | 9,767 | [
"MIT"
] | 0 | ad1196a4d33830f3219dbe2260a69364a745f094 | https://github.com/Zacchaeus14/lang-seg/tree/ad1196a4d33830f3219dbe2260a69364a745f094 |
RegressionModel | import torch
import torch.nn as nn
class RegressionModel(nn.Module):
def __init__(self, num_features_in, num_anchors=9, feature_size=256):
super(RegressionModel, self).__init__()
self.conv1 = nn.Conv2d(num_features_in, feature_size, kernel_size=3,
padding=1)
self.act1 = nn.ReL... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | DvdNss/FaceMaskDetection | RegressionModel | false | 407 | [
"Apache-2.0"
] | 0 | 3a4efe2bf8fb224d72636c853684a563b4e7a2e4 | https://github.com/DvdNss/FaceMaskDetection/tree/3a4efe2bf8fb224d72636c853684a563b4e7a2e4 |
KernelMatcher | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | fengtaoo/opmft | KernelMatcher | false | 6,700 | [
"MIT"
] | 1 | 64f2a12c724295cd913eda02502f2e2a20f2dd55 | https://github.com/fengtaoo/opmft/tree/64f2a12c724295cd913eda02502f2e2a20f2dd55 |
Affine | # 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
import torch.nn.parallel
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty... | akarshkumar0101/timm-mlp-shaker | Affine | false | 1,386 | [
"Apache-2.0"
] | 0 | ab211dd137b790ac57f5ed924c2ada148d54a194 | https://github.com/akarshkumar0101/timm-mlp-shaker/tree/ab211dd137b790ac57f5ed924c2ada148d54a194 |
CDCM | import torch
import torch.nn as nn
class CDCM(nn.Module):
"""
Compact Dilation Convolution based Module
"""
def __init__(self, in_channels, out_channels):
super(CDCM, self).__init__()
self.relu1 = nn.ReLU()
self.conv1 = nn.Conv2d(in_channels, out_channels, kernel_size=1,
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | ZitongYu/pidinet | CDCM | false | 18,205 | [
"MIT"
] | 5 | 15cdf9fb056549934877675bf7571b427f86db55 | https://github.com/ZitongYu/pidinet/tree/15cdf9fb056549934877675bf7571b427f86db55 |
BaseModel | import torch
from torchvision.transforms import *
import torch.nn as nn
import torch.nn.functional as F
class BaseModel(nn.Module):
def __init__(self, num_classes):
super().__init__()
self.conv1 = nn.Conv2d(3, 32, kernel_size=7, stride=1)
self.conv2 = nn.Conv2d(32, 64, kernel_size=3, stri... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torchvision.transforms i... | bsm8734/BC_stage1_Image_Classification | BaseModel | false | 1,674 | [
"MIT"
] | 0 | f915a6fb6748bd9041b1dc2e917d732e202e9cc3 | https://github.com/bsm8734/BC_stage1_Image_Classification/tree/f915a6fb6748bd9041b1dc2e917d732e202e9cc3 |
Sinc | import torch
import torch.nn as nn
class Sinc(nn.Module):
def forward(self, x, epsilon=1e-09):
return torch.sin(x + epsilon) / (x + epsilon)
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 math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | fmhoward/pysurvival | Sinc | false | 12,379 | [
"Apache-2.0"
] | 0 | 3fea55f09477e9f0844845e09d6ea60434436e2e | https://github.com/fmhoward/pysurvival/tree/3fea55f09477e9f0844845e09d6ea60434436e2e |
UpsamplingPixelShuffle | # 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 torchvision import models as models
import torch.nn.pa... | aalborov/openvino_training_extensions | UpsamplingPixelShuffle | false | 6,046 | [
"Apache-2.0"
] | 1 | a0bb39424151a98e1ca80c4aa5c865636d401785 | https://github.com/aalborov/openvino_training_extensions/tree/a0bb39424151a98e1ca80c4aa5c865636d401785 |
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
import triton
import 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.parameter import Parameter
from torch.nn.modules import Module
import t... | Cubbee/apex | Model | false | 16,397 | [
"BSD-3-Clause"
] | 268 | 0a991543846966d5f586540dc2441e512139e9fc | https://github.com/Cubbee/apex/tree/0a991543846966d5f586540dc2441e512139e9fc |
CausalConv2d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | eric11220/vq-vae-2-pytorch | CausalConv2d | false | 12,368 | [
"MIT"
] | 0 | ac455ec8873428e16a361d49bf1dda30472ece13 | https://github.com/eric11220/vq-vae-2-pytorch/tree/ac455ec8873428e16a361d49bf1dda30472ece13 |
Block | # 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.... | KKallidromitis/vissl | Block | false | 5,454 | [
"MIT"
] | 1 | c553e7f6b13c5fa951e3f989beb129899eb8cc80 | https://github.com/KKallidromitis/vissl/tree/c553e7f6b13c5fa951e3f989beb129899eb8cc80 |
QNetworkSmall | # 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_... | Yigit-Arisoy/deep-rts | QNetworkSmall | false | 14,690 | [
"MIT"
] | 144 | a5ed2c29b76789830df9f7075480c7229ccf0f4d | https://github.com/Yigit-Arisoy/deep-rts/tree/a5ed2c29b76789830df9f7075480c7229ccf0f4d |
TensorNearestPad | import torch
class TensorNearestPad(torch.nn.Module):
def __init__(self, lower=1, upper=1):
super().__init__()
assert isinstance(lower, int) and lower >= 0
assert isinstance(upper, int) and upper >= 0
self.lower = lower
self.upper = upper
def forward(self, input):
... | 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... | Minyus/kedex | TensorNearestPad | false | 9,684 | [
"Apache-2.0"
] | 0 | 92f952eed3cb6109bc783f449051f2bd13579d2a | https://github.com/Minyus/kedex/tree/92f952eed3cb6109bc783f449051f2bd13579d2a |
DiceLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | apyskir/steppy-toolkit | DiceLoss | false | 3,118 | [
"MIT"
] | 0 | 3190054954aeab043ced1c079d87bdd3582bb232 | https://github.com/apyskir/steppy-toolkit/tree/3190054954aeab043ced1c079d87bdd3582bb232 |
Decoder5 | import torch
import torch.nn as nn
class Decoder5(nn.Module):
def __init__(self, model=None, fixed=False):
super(Decoder5, self).__init__()
self.fixed = fixed
self.conv51 = nn.Conv2d(512, 512, 3, 1, 0)
self.conv44 = nn.Conv2d(512, 512, 3, 1, 0)
self.conv43 = nn.Conv2d(512,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | MingSun-Tse/Collaborative-Distillation | Decoder5 | false | 14,093 | [
"MIT"
] | 172 | 915712674af82ff91d926d922c14988cce0430f3 | https://github.com/MingSun-Tse/Collaborative-Distillation/tree/915712674af82ff91d926d922c14988cce0430f3 |
MinMaxNorm | import torch
import torch.nn as nn
class MinMaxNorm(nn.Module):
def __init__(self, min, max, a=0, b=1):
super(MinMaxNorm, self).__init__()
self.min, self.max = min, max
self.a, self.b = a, b
def forward(self, x):
return self.a + (x - self.min) * (self.b - self.a) / (self.max ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | iclementine/speedyspeech | MinMaxNorm | false | 10,402 | [
"BSD-3-Clause"
] | 0 | db527587a3699b71082d61c9e9fad7ed795d1980 | https://github.com/iclementine/speedyspeech/tree/db527587a3699b71082d61c9e9fad7ed795d1980 |
DenseBlock | import torch
import torch.nn as nn
import torch.nn.functional as F
class ConvLeakyRelu2d(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size=3, padding=1,
stride=1, dilation=1, groups=1):
super(ConvLeakyRelu2d, self).__init__()
self.conv = nn.Conv2d(in_channels, out_chan... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
assert_size_stride = torch... | Linfeng-Tang/SeAFusion | DenseBlock | false | 8,506 | [
"MIT"
] | 18 | 54cf7ee116da3f726941560279bf12fedd0d434d | https://github.com/Linfeng-Tang/SeAFusion/tree/54cf7ee116da3f726941560279bf12fedd0d434d |
ExpanderConv2d | import torch
import torch.nn as nn
class ExpanderConv2d(nn.Module):
def __init__(self, indim, outdim, kernel_size, expandSize, stride=1,
padding=0, inDil=1, groups=1, mode='random'):
super(ExpanderConv2d, self).__init__()
self.conStride = stride
self.conPad = padding
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | noonespecial009/resnet-variations | ExpanderConv2d | false | 12,837 | [
"MIT"
] | 0 | 11ee33d1855c292b15930a2a2c1d757d1ac85699 | https://github.com/noonespecial009/resnet-variations/tree/11ee33d1855c292b15930a2a2c1d757d1ac85699 |
Dense_block | # 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... | Mohanned-Elkholy/ResNet-GAN | Dense_block | false | 5,612 | [
"MIT"
] | 1 | 81b01294d8b5035131aee24d486e2cb879030832 | https://github.com/Mohanned-Elkholy/ResNet-GAN/tree/81b01294d8b5035131aee24d486e2cb879030832 |
ACNet | # 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
import tor... | RocksonZeta/ac | ACNet | false | 996 | [
"MIT"
] | 0 | 050a5cd176864cc2e1f7c376045c3342a7f93221 | https://github.com/RocksonZeta/ac/tree/050a5cd176864cc2e1f7c376045c3342a7f93221 |
IdentityPadding | # 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... | citelab/fastsync | IdentityPadding | false | 1,710 | [
"Apache-2.0"
] | 0 | 8e2166f87fc53479b57fef536a971c3a2e6e4309 | https://github.com/citelab/fastsync/tree/8e2166f87fc53479b57fef536a971c3a2e6e4309 |
LocationNetwork | # 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.... | bennzo/DT-RAM-PyTorch | LocationNetwork | false | 1,540 | [
"MIT"
] | 0 | b364662ab7650ffd26cf129673752521e004b13a | https://github.com/bennzo/DT-RAM-PyTorch/tree/b364662ab7650ffd26cf129673752521e004b13a |
S2S2Mean | import torch
from torch import nn as nn
def s2s2_gram_schmidt(v1, v2):
"""Normalise 2 3-vectors. Project second to orthogonal component.
Take cross product for third. Stack to form SO matrix."""
u1 = v1
e1 = u1 / u1.norm(p=2, dim=-1, keepdim=True).clamp(min=1e-05)
u2 = v2 - (e1 * v2).sum(-1, keepd... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | pimdh/lie-vae | S2S2Mean | false | 16,272 | [
"MIT"
] | 83 | 0e0cc4d533c064fcfc405e8a75449f8b2f6cf8cf | https://github.com/pimdh/lie-vae/tree/0e0cc4d533c064fcfc405e8a75449f8b2f6cf8cf |
SppPooling | # 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... | Asichurter/Few-Shot-Project | SppPooling | false | 75 | [
"MIT"
] | 0 | 865cd6aa7b996c518dfa48dcc9ffad90445f9efe | https://github.com/Asichurter/Few-Shot-Project/tree/865cd6aa7b996c518dfa48dcc9ffad90445f9efe |
HSwish | import torch
from torch import nn
import torch.utils.data
class HSwish(nn.Module):
"""Hard Swish activation function.
See: https://arxiv.org/abs/1905.02244
"""
def forward(self, x):
return x * nn.functional.relu6(x + 3).div_(6)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def g... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards... | shiyuann/determined | HSwish | false | 16,421 | [
"Apache-2.0"
] | 1,729 | 856123ae112759de7bded9bc7bd0e07055f2174b | https://github.com/shiyuann/determined/tree/856123ae112759de7bded9bc7bd0e07055f2174b |
EdgeClassifLoss | import torch
import torch.optim
class EdgeClassifLoss(torch.nn.Module):
def __init__(self, normalize=torch.nn.Sigmoid(), loss=torch.nn.BCELoss(
reduction='mean')):
super(EdgeClassifLoss, self).__init__()
if isinstance(loss, torch.nn.BCELoss):
self.loss = lambda preds, target: ... | 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... | MauTrib/gnn-en-folie | EdgeClassifLoss | false | 818 | [
"Apache-2.0"
] | 0 | 3ca639919a2b285a41641717f4131107c015b510 | https://github.com/MauTrib/gnn-en-folie/tree/3ca639919a2b285a41641717f4131107c015b510 |
CORblock_Z | import torch
import torch.utils.model_zoo
from torch import nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
class Identity(nn.Module):
"""
Helper module that stores the current tensor. Useful for accessing by name
"""
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.utils.model_zoo
... | AnnaTruzzi/cornet_analysis | CORblock_Z | false | 1,965 | [
"MIT"
] | 0 | 0a2fd0c5a6b09a80d3c8a47441b08fd6129f7a2d | https://github.com/AnnaTruzzi/cornet_analysis/tree/0a2fd0c5a6b09a80d3c8a47441b08fd6129f7a2d |
RefineFireModel | # 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 numpy ... | BoyuanChen/neural-state-variables | RefineFireModel | false | 7,859 | [
"MIT"
] | 17 | 10483d93ac8c006f3786c434fb57d70d9ab465ec | https://github.com/BoyuanChen/neural-state-variables/tree/10483d93ac8c006f3786c434fb57d70d9ab465ec |
GatedConv | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
def concat_elu(x):
"""Concatenated ReLU (http://arxiv.org/abs/1603.05201), but with ELU."""
return F.elu(torch.cat((x, -x), dim=1))
class WNConv2d(nn.Module):
"""Weight-normalized 2d convolution.
Args:
in_chann... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | Catherine0505/mar-scf-flow | GatedConv | false | 17,109 | [
"Apache-2.0"
] | 10 | aa7c3564cb9f2967c5e580a633516dba1b597f98 | https://github.com/Catherine0505/mar-scf-flow/tree/aa7c3564cb9f2967c5e580a633516dba1b597f98 |
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.... | jaehyek/attention-is-all-you-need | MultiHeadAttention | false | 12,604 | [
"MIT"
] | 0 | 9b421f7c98414aeb9f397c5195e3a6a9080a4669 | https://github.com/jaehyek/attention-is-all-you-need/tree/9b421f7c98414aeb9f397c5195e3a6a9080a4669 |
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
assert_size_stride = torch._C... | SunHaozhe/modular-metalearning | Net | false | 14,446 | [
"MIT"
] | 70 | c94dd18c6d105f18667d4de7bb4c81fa538a541c | https://github.com/SunHaozhe/modular-metalearning/tree/c94dd18c6d105f18667d4de7bb4c81fa538a541c |
GeneralizedMeanPooling | import torch
import torch.nn as nn
import torch.utils.data
class GeneralizedMeanPooling(nn.Module):
"""Applies a 2D power-average adaptive pooling over an input signal composed of several input planes.
The function computed is: :math:`f(X) = pow(sum(pow(X, p)), 1/p)`
- At p = infinity, one gets Max Po... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import... | RichardDominik/AIC21-MTMC | GeneralizedMeanPooling | false | 14,309 | [
"MIT"
] | 63 | f69f63f9c40e2dc98e98c7af1cebe3d5605307ee | https://github.com/RichardDominik/AIC21-MTMC/tree/f69f63f9c40e2dc98e98c7af1cebe3d5605307ee |
FAdd | # 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... | dawnclaude/onnx2keras | FAdd | false | 15,225 | [
"MIT"
] | 115 | 3d2a47c0a228b91fd434232274e216e491da36e3 | https://github.com/dawnclaude/onnx2keras/tree/3d2a47c0a228b91fd434232274e216e491da36e3 |
Critic | import torch
import torch.nn as nn
import torch.nn.functional as F
class Critic(nn.Module):
def __init__(self, state_dim, action_dim):
super(Critic, self).__init__()
self.l1 = nn.Linear(state_dim + action_dim, 6)
self.l2 = nn.Linear(6, 4)
self.l3 = nn.Linear(4, 1)
self.l4 ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | pkj415/CityLearn-2 | Critic | false | 10,668 | [
"MIT"
] | 0 | 003012ddeb52868d42d85b835a9a5f2c28008927 | https://github.com/pkj415/CityLearn-2/tree/003012ddeb52868d42d85b835a9a5f2c28008927 |
L1Loss | # 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 functools
impor... | ChHanXiao/mmdetection | L1Loss | false | 9,145 | [
"Apache-2.0"
] | 0 | 324aa5a042857a9b57abe37385e1210709a20d02 | https://github.com/ChHanXiao/mmdetection/tree/324aa5a042857a9b57abe37385e1210709a20d02 |
SpaceToDepth | # 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... | Dauriel/weather4cast2021 | SpaceToDepth | false | 357 | [
"Apache-2.0"
] | 0 | 29e818c4bcd488ec84b51558bf5392e4a887db70 | https://github.com/Dauriel/weather4cast2021/tree/29e818c4bcd488ec84b51558bf5392e4a887db70 |
NetVLAD | # 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.... | lulor/project_vg | NetVLAD | false | 7,269 | [
"MIT"
] | 1 | 27b0c3b3038c5a666dde516a0a265ae8ddf2059f | https://github.com/lulor/project_vg/tree/27b0c3b3038c5a666dde516a0a265ae8ddf2059f |
_BoundaryRefineModule | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | CuthbertCai/pytorch-semantic-segmentation | _BoundaryRefineModule | false | 13,526 | [
"MIT"
] | 1,328 | aa2a47b73c1aa14555e1421e2366275254ea5376 | https://github.com/CuthbertCai/pytorch-semantic-segmentation/tree/aa2a47b73c1aa14555e1421e2366275254ea5376 |
SpatialGate | # 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 ... | JoohyungLee0106/rectal_MR_volume_classification | SpatialGate | false | 694 | [
"MIT"
] | 0 | d2a7d13dae9fe7255b983cbc210567dd452a936f | https://github.com/JoohyungLee0106/rectal_MR_volume_classification/tree/d2a7d13dae9fe7255b983cbc210567dd452a936f |
Down2d | # 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 ... | Shimamura-Lab-SU/SGV | Down2d | false | 2,830 | [
"MIT"
] | 0 | 8df3c314532528b8597c5dbb28bdfb23155bee82 | https://github.com/Shimamura-Lab-SU/SGV/tree/8df3c314532528b8597c5dbb28bdfb23155bee82 |
LayerNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
from torch import Tensor
import torch.nn as nn
from torch.nn import... | alex-kj-chin/universal-computation | LayerNorm | false | 12,076 | [
"MIT"
] | 0 | a41cc7d685a3e0c56c11bc346c25394464da2e06 | https://github.com/alex-kj-chin/universal-computation/tree/a41cc7d685a3e0c56c11bc346c25394464da2e06 |
GeneralizedDiceLoss | import collections
import torch
import warnings
from typing import Optional
from typing import Union
from typing import Callable
from typing import Any
from typing import Tuple
import torch.nn
from torch.nn.modules.loss import _Loss
from enum import Enum
import collections.abc
def issequenceiterable(obj: 'Any') ->boo... | 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 collections
from typi... | Irme/MONAI | GeneralizedDiceLoss | false | 17,472 | [
"Apache-2.0"
] | 3 | dc4bf661831b14f4231cb325cc1b15d38c1e406c | https://github.com/Irme/MONAI/tree/dc4bf661831b14f4231cb325cc1b15d38c1e406c |
CrossEntropyLossTF | # 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.nn import M... | ClashLuke/memcnn | CrossEntropyLossTF | false | 302 | [
"MIT"
] | 0 | 1d48132282c02506ca3d35540f819c4c9130eab4 | https://github.com/ClashLuke/memcnn/tree/1d48132282c02506ca3d35540f819c4c9130eab4 |
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
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 |
BertSelfAttention | from _paritybench_helpers import _mock_config
import math
import torch
from torch import nn
class BertSelfAttention(nn.Module):
def __init__(self, config):
super(BertSelfAttention, self).__init__()
if config.hidden_size % config.num_attention_heads != 0:
raise ValueError(
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | noble6emc2/MoCo-SSPT | BertSelfAttention | false | 12,852 | [
"MIT"
] | 0 | e6d7cf3f0a3b5a467318dfc32096e4929adbe646 | https://github.com/noble6emc2/MoCo-SSPT/tree/e6d7cf3f0a3b5a467318dfc32096e4929adbe646 |
layer_1_to_2 | # 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 numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | HyTruongSon/InvariantGraphNetworks-PyTorch | layer_1_to_2 | false | 17,421 | [
"Apache-2.0"
] | 7 | da9fdaa4f858d6fcae14b08a59d4b172a2aabaf8 | https://github.com/HyTruongSon/InvariantGraphNetworks-PyTorch/tree/da9fdaa4f858d6fcae14b08a59d4b172a2aabaf8 |
PositionalEncoding2D | # 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
import torch.nn as nn
import torch.utils.checkpoint
assert_size_stride = torch._C._dynamo... | RosettaCommons/RFDesign | PositionalEncoding2D | false | 14,338 | [
"MIT"
] | 45 | b404b8b2c57f89c047529c30259aeeb8f6012b61 | https://github.com/RosettaCommons/RFDesign/tree/b404b8b2c57f89c047529c30259aeeb8f6012b61 |
Linear | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.model_zoo
class Linear(nn.Module):
def __init__(self, stride):
super(Linear, self).__init__()
self.scale = stride
def forward(self, x):
return F.interpolate(x, scale_factor=self.scale, mode='linear'... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.utils.model_zoo
assert_size_stride = torch._C._dynamo.... | guoyongcs/HNAS | Linear | false | 15,478 | [
"MIT"
] | 60 | 2b34e1b637bb03d23ca6559c1b5d1245d9744348 | https://github.com/guoyongcs/HNAS/tree/2b34e1b637bb03d23ca6559c1b5d1245d9744348 |
LNN | # 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.... | lipmedusea/pytorch | LNN | false | 12,716 | [
"MIT"
] | 0 | 5d94694b9e1193a93dd7f75ea2042b5a1cf178bc | https://github.com/lipmedusea/pytorch/tree/5d94694b9e1193a93dd7f75ea2042b5a1cf178bc |
TorchGloVeModel | import torch
import torch.nn as nn
import torch.utils.data
from torch.nn.init import xavier_uniform_
class TorchGloVeModel(nn.Module):
def __init__(self, n_words, embed_dim):
super().__init__()
self.n_words = n_words
self.embed_dim = embed_dim
self.W = self._init_weights(self.n_wo... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
from torch.nn.init import xavier_u... | atticusg/cs224u | TorchGloVeModel | false | 1,492 | [
"Apache-2.0"
] | 0 | 66e0f2714e246dcb8836f706ae9ff5613c51ed34 | https://github.com/atticusg/cs224u/tree/66e0f2714e246dcb8836f706ae9ff5613c51ed34 |
PARALossSoftmax | import torch
import torch.nn as nn
import torch.nn.functional as F
class PARALossSoftmax(nn.Module):
"""
Softmax classifier for sentence-level relation extraction.
"""
def __init__(self):
"""
Args:
sentence_encoder: encoder for sentences
num_class: number of cl... | 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 |
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.... | thilinicooray/pyGAT | GAT | false | 13,051 | [
"MIT"
] | 0 | 0c8fd0fdae20e42a41116cc9691e1223fd9d0a93 | https://github.com/thilinicooray/pyGAT/tree/0c8fd0fdae20e42a41116cc9691e1223fd9d0a93 |
SpatialAttention2d | # 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... | khodwe56/kaggle-birdsong-recognition | SpatialAttention2d | false | 12,673 | [
"MIT"
] | 0 | 95a902c37355619cf02558968f000038e487db47 | https://github.com/khodwe56/kaggle-birdsong-recognition/tree/95a902c37355619cf02558968f000038e487db47 |
LayerNorm | import torch
import torch.nn as nn
import torch.nn
import torch.onnx
import torch.utils.checkpoint
class LayerNorm(nn.Module):
def __init__(self, hidden_size, epsilon, cast_fp16=True, formula=0):
super().__init__()
self.layer_norm = nn.LayerNorm(hidden_size, eps=epsilon)
self.layer_norm.b... | 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
import torch.onnx
import torch.utils.chec... | TingGong1/onnxruntime | LayerNorm | false | 5,900 | [
"MIT"
] | 1 | 435010ab6873974803591fa22262ed8b3e36e44d | https://github.com/TingGong1/onnxruntime/tree/435010ab6873974803591fa22262ed8b3e36e44d |
GCN_classifier | from torch.nn import Module
import math
import torch
import torch.nn.functional as F
from torch.nn.modules.module import Module
from torch.nn.parameter import Parameter
from scipy.sparse import *
class GraphConvolution(Module):
"""
Simple GCN layer, similar to https://arxiv.org/abs/1609.02907
"""
def... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | TTomatoZhang/GHGCN | GCN_classifier | false | 3,132 | [
"Apache-2.0"
] | 0 | 09a07ff9e29e5889b912ca5feff74bb9308eda55 | https://github.com/TTomatoZhang/GHGCN/tree/09a07ff9e29e5889b912ca5feff74bb9308eda55 |
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