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 |
|---|---|---|---|---|---|---|---|---|---|---|
SumAggregator | # 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... | GraphNAS/GraphNAS | SumAggregator | false | 13,723 | [
"Apache-2.0"
] | 94 | b4f05bb10b8b96bb9e82344bfae36a23db2431a6 | https://github.com/GraphNAS/GraphNAS/tree/b4f05bb10b8b96bb9e82344bfae36a23db2431a6 |
Sigmoid | # 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... | ElliotHYLee/MyPyTorchAPI | Sigmoid | false | 11,395 | [
"MIT"
] | 0 | edb25b724372367e96e3bd2f420c023c4efbfcd7 | https://github.com/ElliotHYLee/MyPyTorchAPI/tree/edb25b724372367e96e3bd2f420c023c4efbfcd7 |
Encoder_attention | # 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.... | CrowdDynamicsLab/InfoMotif | Encoder_attention | false | 17,177 | [
"BSD-3-Clause"
] | 7 | cca1ffa14cc94408a5c4c50b7b1707c608e3bc9b | https://github.com/CrowdDynamicsLab/InfoMotif/tree/cca1ffa14cc94408a5c4c50b7b1707c608e3bc9b |
MockAccuracy | import torch
class _Metric(torch.nn.Module):
def __init__(self):
super().__init__()
def forward(self, input: 'torch.Tensor', target: 'torch.Tensor'):
raise NotImplementedError()
class Accuracy(_Metric):
def __init__(self):
super().__init__()
def forward(self, input: 'torc... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | Stillerman/MusicTransformer-pytorch | MockAccuracy | false | 14,449 | [
"MIT"
] | 170 | 73abb7cab271beba042b7b6fc06a6a9aaee82e8c | https://github.com/Stillerman/MusicTransformer-pytorch/tree/73abb7cab271beba042b7b6fc06a6a9aaee82e8c |
CTLSTMCell | # 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, math as tl_math
im... | LitteleStar/TDPP | CTLSTMCell | false | 797 | [
"Apache-2.0"
] | 0 | 7b85016bea01c4c018337152599043dc2efbaba8 | https://github.com/LitteleStar/TDPP/tree/7b85016bea01c4c018337152599043dc2efbaba8 |
GatedConnection | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.optim
assert_size_stride = torch._C._dynamo.g... | Blickwinkel1107/NJUNMT-pytorch | GatedConnection | false | 17,022 | [
"MIT"
] | 9 | 82f684fe768b137ca0649b7b79a1820077917385 | https://github.com/Blickwinkel1107/NJUNMT-pytorch/tree/82f684fe768b137ca0649b7b79a1820077917385 |
DownConv | # 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_... | loftiskg/unet-pytorch | DownConv | false | 12,727 | [
"MIT"
] | 0 | 38ddc3ddc3b00bfd575212484e05df1745504e5c | https://github.com/loftiskg/unet-pytorch/tree/38ddc3ddc3b00bfd575212484e05df1745504e5c |
GateLayer | import torch
from torch import nn
class GateLayer(nn.Module):
def __init__(self, input_dim):
super(GateLayer, self).__init__()
self._norm_layer1 = nn.Linear(input_dim * 2, input_dim)
self._norm_layer2 = nn.Linear(input_dim, 1)
def forward(self, input1, input2):
norm_input = 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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | Zilize/CRSLab | GateLayer | false | 1,320 | [
"MIT"
] | 0 | fb357d0dfb7d2cf7b67b892d98e52032a31ca564 | https://github.com/Zilize/CRSLab/tree/fb357d0dfb7d2cf7b67b892d98e52032a31ca564 |
Attention_SEblock | # 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.... | Andrew-Zhu/DyFPN | Attention_SEblock | false | 7,752 | [
"Apache-2.0"
] | 32 | a74463b59c4ce28253c2449a07c0f6692a0147a1 | https://github.com/Andrew-Zhu/DyFPN/tree/a74463b59c4ce28253c2449a07c0f6692a0147a1 |
Foo | # 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.functional
import torch.nn.parallel
import torch.utils.data
import torch.optim
import torch.utils.data.distributed
assert_si... | DonnieKim411/apex | Foo | false | 13,602 | [
"BSD-3-Clause"
] | 6,523 | fb00a5a1d569c7b118aa672b3dacac3663ca3911 | https://github.com/DonnieKim411/apex/tree/fb00a5a1d569c7b118aa672b3dacac3663ca3911 |
NeuralNetPartialNoGradModel | import torch
import torch.nn
import torch.onnx
class NeuralNetPartialNoGradModel(torch.nn.Module):
def __init__(self, input_size, hidden_size, num_classes):
super(NeuralNetPartialNoGradModel, self).__init__()
self.fc1 = torch.nn.Linear(input_size, hidden_size).requires_grad_(
False)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn
import torch.... | RyanUnderhill/onnxruntime | NeuralNetPartialNoGradModel | false | 11,833 | [
"MIT"
] | 0 | 6df4e293ffbb47d739d2dedfbb87fa6234b8c37c | https://github.com/RyanUnderhill/onnxruntime/tree/6df4e293ffbb47d739d2dedfbb87fa6234b8c37c |
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
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | Altair-inc/behaviour-seq-transformer | FF | false | 16,887 | [
"MIT"
] | 10 | 74185eb5588b1e57a936de9901313dddcc10acf4 | https://github.com/Altair-inc/behaviour-seq-transformer/tree/74185eb5588b1e57a936de9901313dddcc10acf4 |
RankingLoss | # 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... | andrejmiscic/simcls-pytorch | RankingLoss | false | 18,305 | [
"MIT"
] | 5 | 516315c4b35955e4201677fc838f5f38a6e8fd54 | https://github.com/andrejmiscic/simcls-pytorch/tree/516315c4b35955e4201677fc838f5f38a6e8fd54 |
SqueezeExcitate | # 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... | Dogy06/COVID-Efficientnet-Pytorch-1 | SqueezeExcitate | false | 17,223 | [
"MIT"
] | 4 | 3c1f7d9513abe59783152efca28dc886bf4afc2f | https://github.com/Dogy06/COVID-Efficientnet-Pytorch-1/tree/3c1f7d9513abe59783152efca28dc886bf4afc2f |
BigRamDuel | # 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_... | ayjabri/DeepRL | BigRamDuel | false | 1,527 | [
"MIT"
] | 0 | 0be095e3a3d04f60b4cdc97ed330dffc17b3024a | https://github.com/ayjabri/DeepRL/tree/0be095e3a3d04f60b4cdc97ed330dffc17b3024a |
backWarp | import torch
import numpy as np
import torch.nn as nn
class backWarp(nn.Module):
"""
A class for creating a backwarping object.
This is used for backwarping to an image:
Given optical flow from frame I0 to I1 --> F_0_1 and frame I1,
it generates I0 <-- backwarp(F_0_1, I1).
...
Methods
... | 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 numpy as np
import to... | CM-BF/FeatureFlow | backWarp | false | 13,450 | [
"MIT"
] | 161 | 06642697922f17211e5faa353e24b1a0946885b1 | https://github.com/CM-BF/FeatureFlow/tree/06642697922f17211e5faa353e24b1a0946885b1 |
ScaledL2Norm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.onnx
import tor... | AndySer37/pytorch-ssd-mobile | ScaledL2Norm | false | 1,988 | [
"MIT"
] | 0 | ec4935940ffa374edc1e9a7009c279e727e548d7 | https://github.com/AndySer37/pytorch-ssd-mobile/tree/ec4935940ffa374edc1e9a7009c279e727e548d7 |
sAG | # 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... | rinkwitz/Thesis_Semantic_Image_Segmentation_on_Satellite_Imagery_using_UNets | sAG | false | 7,564 | [
"MIT"
] | 1 | 75d3a4a536f6ef81fe0efd4f5fbba32b627a7472 | https://github.com/rinkwitz/Thesis_Semantic_Image_Segmentation_on_Satellite_Imagery_using_UNets/tree/75d3a4a536f6ef81fe0efd4f5fbba32b627a7472 |
BasicAcM | # 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 numpy
from t... | MIMUW-RL/spp-rl | BasicAcM | false | 17,640 | [
"MIT"
] | 7 | 86b96cdd220cc4eae86f7cfd26924c69b498dcc6 | https://github.com/MIMUW-RL/spp-rl/tree/86b96cdd220cc4eae86f7cfd26924c69b498dcc6 |
myCustomModel | # 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.... | awoloshuk/NephNet | myCustomModel | false | 6,302 | [
"MIT"
] | 1 | 562431364874fef1680069c7a5235c67b96504b8 | https://github.com/awoloshuk/NephNet/tree/562431364874fef1680069c7a5235c67b96504b8 |
LayerNorm | import torch
import torch.nn as nn
class LayerNorm(nn.Module):
def __init__(self, features, eps=1e-06):
super(LayerNorm, self).__init__()
self.gamma = nn.Parameter(torch.ones(features))
self.beta = nn.Parameter(torch.zeros(features))
self.eps = eps
def forward(self, 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.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | Dodger23/SincNet | LayerNorm | false | 13,585 | [
"MIT"
] | 951 | bf848e88dc8d6cbeb4484e89486ec0a4ab237cb1 | https://github.com/Dodger23/SincNet/tree/bf848e88dc8d6cbeb4484e89486ec0a4ab237cb1 |
CNN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | WinterSoHot/OpenNRE | CNN | false | 14,587 | [
"MIT"
] | 3,284 | bc58d8fff2a2f42a5349c184f16ab7a8c50ae32b | https://github.com/WinterSoHot/OpenNRE/tree/bc58d8fff2a2f42a5349c184f16ab7a8c50ae32b |
Cat | import torch
import torch.nn as nn
class Cat(nn.Module):
def forward(self, a, b):
x = torch.cat((a, b), dim=1)
return x
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | AbhinandanVellanki/yolact_edge | Cat | false | 1,955 | [
"MIT"
] | 0 | 06d6318cf70ef511b19aa1c14f0476e4ffac2722 | https://github.com/AbhinandanVellanki/yolact_edge/tree/06d6318cf70ef511b19aa1c14f0476e4ffac2722 |
FeedForward | import torch
from torch import nn
import torch.nn.functional as F
class FeedForward(nn.Module):
def __init__(self, dim, d_ff=128, dropout=0.1):
super().__init__()
self.linear_1 = nn.Linear(dim, d_ff)
self.dropout = nn.Dropout(dropout)
self.linear_2 = nn.Linear(d_ff, dim)
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.triton_helpers import libdevice
from torch import n... | abcdefg-dev-dd/asxdcvfg | FeedForward | false | 6,055 | [
"Apache-2.0"
] | 1 | 83421d4a133810968d6e04b256a9312895452941 | https://github.com/abcdefg-dev-dd/asxdcvfg/tree/83421d4a133810968d6e04b256a9312895452941 |
SpatialDepthWiseConvolution | # 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 math
from torch import nn
import torch.utils.data
import torch.nn.functional
import torch.autograd
assert... | mcx/annotated_deep_learning_paper_implementations | SpatialDepthWiseConvolution | false | 7,210 | [
"MIT"
] | 1 | f169f3a71dd2d36eb28ad31062d3475efa367b88 | https://github.com/mcx/annotated_deep_learning_paper_implementations/tree/f169f3a71dd2d36eb28ad31062d3475efa367b88 |
GlobalAvgPool2d | # 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... | Abdul-Mukit/ssp_with_hand_tracking | GlobalAvgPool2d | false | 11,148 | [
"MIT"
] | 0 | 04429ac9789283694a9176b94f70ab4e5a8c0727 | https://github.com/Abdul-Mukit/ssp_with_hand_tracking/tree/04429ac9789283694a9176b94f70ab4e5a8c0727 |
AdaptiveCatAvgMaxPool2d | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import torch.onnx
import torch.utils.data
import torchvision.transfo... | cagery/pytorch-image-models | AdaptiveCatAvgMaxPool2d | false | 9,903 | [
"Apache-2.0"
] | 0 | 9211b0bd368cecf970165cfad81770dc14e25d45 | https://github.com/cagery/pytorch-image-models/tree/9211b0bd368cecf970165cfad81770dc14e25d45 |
DCGANGenerator_mnist | # 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 functools
im... | Gabriele91/EvolutionaryGAN-pytorch | DCGANGenerator_mnist | false | 9,135 | [
"MIT"
] | 0 | 993cb13551908727e52aef738f8954072b5b398a | https://github.com/Gabriele91/EvolutionaryGAN-pytorch/tree/993cb13551908727e52aef738f8954072b5b398a |
My_loss | import torch
import torch.nn as nn
class My_loss(nn.Module):
def __init__(self):
super().__init__()
def forward(self, x, y, batch_size):
return torch.sum(torch.pow(x - y, 2)) / batch_size / 2
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4, 4, 4]), 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 import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | H-Liu1997/Pytorch_Pose_Estimation_Framework | My_loss | false | 5,250 | [
"MIT"
] | 1 | 06616b3459ff639f8486e6ea4f93922597788b2a | https://github.com/H-Liu1997/Pytorch_Pose_Estimation_Framework/tree/06616b3459ff639f8486e6ea4f93922597788b2a |
ClassBlock | # 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.... | QLSong/cv-classify | ClassBlock | false | 2,751 | [
"Apache-2.0"
] | 0 | 02f53d03868f299a08b5c97a266b50a7fdcd3f2b | https://github.com/QLSong/cv-classify/tree/02f53d03868f299a08b5c97a266b50a7fdcd3f2b |
DCT | import torch
import torch.nn as nn
class DCT(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, out_pad=0):
super(DCT, self).__init__()
self.dcnn = nn.ConvTranspose2d(in_channels, out_channels,
kernel_size=2, stride=2, output_padding=out_pad)
self.tanh = nn... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | adamkrekorian/CI-UNet | DCT | false | 1,372 | [
"MIT"
] | 0 | fab0f8806540f5d79911bd81ba54dff135f9814f | https://github.com/adamkrekorian/CI-UNet/tree/fab0f8806540f5d79911bd81ba54dff135f9814f |
LogitCond | # 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
... | Lee-Gihun/Micronet_GSJ | LogitCond | false | 8,451 | [
"MIT"
] | 12 | 72289bb66507b6c3b4d14f2e5916dec718a1b198 | https://github.com/Lee-Gihun/Micronet_GSJ/tree/72289bb66507b6c3b4d14f2e5916dec718a1b198 |
ComboLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | johnugeorge/medperf | ComboLoss | false | 6,974 | [
"Apache-2.0"
] | 1 | 5bc3f643064df14e9476bd4d4c1a4c0cce5337d5 | https://github.com/johnugeorge/medperf/tree/5bc3f643064df14e9476bd4d4c1a4c0cce5337d5 |
Permute | # 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.onnx
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynam... | mil-tokyo/webdnn | Permute | false | 16,081 | [
"MIT"
] | 1,967 | 38a60fd3e1a4e72bc01108189a3aa51e0752aecd | https://github.com/mil-tokyo/webdnn/tree/38a60fd3e1a4e72bc01108189a3aa51e0752aecd |
DummyAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
class DummyAttention(nn.Module):
def __init__(self, in_channels):
super().__init__()
self.linear1 = nn.Linear(in_channels, 32)
self.linear2 = nn.Linear(32, 1)
pass
def forward(self, net):
value = net
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | aaalgo/health_outcome_challenge | DummyAttention | false | 3,022 | [
"BSD-3-Clause"
] | 0 | 6d0cb660123ac6fb4939c1d50a8f1914e8e3e165 | https://github.com/aaalgo/health_outcome_challenge/tree/6d0cb660123ac6fb4939c1d50a8f1914e8e3e165 |
ExpPool | import torch
from torch import nn
class ExpPool(nn.Module):
def __init__(self):
super(ExpPool, self).__init__()
def forward(self, feat_map):
"""
Numerically stable implementation of the operation
Arguments:
feat_map(Tensor): tensor with shape (N, C, H, W)
... | 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... | iampartho/EEE426 | ExpPool | false | 3,640 | [
"Apache-2.0"
] | 0 | a706660c0efcd4adea44d54c57a34bcaa4439ec1 | https://github.com/iampartho/EEE426/tree/a706660c0efcd4adea44d54c57a34bcaa4439ec1 |
StddevLayer | # 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
from torch import nn
import torch.nn
assert_size_stride = torch._C._dynamo.guar... | Qingyang-Xu/GANInversion_with_ConsecutiveImgs | StddevLayer | false | 8,676 | [
"MIT"
] | 23 | 9078a48ec3474dacdd02693b051e3addef1c5697 | https://github.com/Qingyang-Xu/GANInversion_with_ConsecutiveImgs/tree/9078a48ec3474dacdd02693b051e3addef1c5697 |
UpsampleConv2d | # 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.... | TrueMatthewKirkham/face-preserving-style-transfer | UpsampleConv2d | false | 5,917 | [
"MIT"
] | 1 | ae8a9509570227ea52776fba85658022124c886c | https://github.com/TrueMatthewKirkham/face-preserving-style-transfer/tree/ae8a9509570227ea52776fba85658022124c886c |
Attention | import torch
import torch.nn as nn
class Attention(nn.Module):
def __init__(self, hidden):
super(Attention, self).__init__()
self.linear = nn.Linear(hidden, 1, bias=False)
def forward(self, x, mask=None):
weights = self.linear(x)
if mask is not None:
weights = wei... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | IAMZn1018/ccks2021-entity-linking | Attention | false | 9,110 | [
"Apache-2.0"
] | 0 | 6596b0b16d8c1fc4400c736b30ff46158d1575e4 | https://github.com/IAMZn1018/ccks2021-entity-linking/tree/6596b0b16d8c1fc4400c736b30ff46158d1575e4 |
SymDecoder | # 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... | kevin-kaixu/grass_pytorch | SymDecoder | false | 15,817 | [
"Apache-2.0"
] | 85 | 1d8dc6dcc0ab3ca029e449f57c37ba3910a4f90a | https://github.com/kevin-kaixu/grass_pytorch/tree/1d8dc6dcc0ab3ca029e449f57c37ba3910a4f90a |
BasicModel6_MultiTensor | import torch
import torch.nn as nn
import torch.nn.functional as F
class BasicModel6_MultiTensor(nn.Module):
def __init__(self):
super().__init__()
def forward(self, input1, input2):
input = input1 + input2
return 1 - F.relu(1 - input)[:, 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 import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | ngduduong/captum | BasicModel6_MultiTensor | false | 4,072 | [
"BSD-3-Clause"
] | 0 | 6fe5f0f23ea975e73e0c0dee79bdc01b4223d283 | https://github.com/ngduduong/captum/tree/6fe5f0f23ea975e73e0c0dee79bdc01b4223d283 |
PixelShuffle | import torch
import torch.nn as nn
import torch.nn.parallel
class PixelShuffle(nn.Module):
def __init__(self, ry=2, rx=2):
super().__init__()
self.ry = ry
self.rx = rx
def forward(self, x):
ry = self.ry
rx = self.rx
[B, C, H, W] = list(x.shape)
x = x.r... | 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C... | LonglifeHyun/GANda_text-to-image | PixelShuffle | false | 2,567 | [
"MIT"
] | 0 | 095ded617e4df7d7ff7f4954381dde77db6d6883 | https://github.com/LonglifeHyun/GANda_text-to-image/tree/095ded617e4df7d7ff7f4954381dde77db6d6883 |
CustomGruCell | import torch
import numpy as np
import torch.nn as nn
class CustomGruCell(nn.Module):
"""
A forward only GRU cell.
Input should be: (sequence length x batch size x input_size).
The output is the output of the final forward call.
It's not clear if it would be possible to use the output from each ce... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 numpy as np
... | abogaziah/PySyft | CustomGruCell | false | 1,361 | [
"Apache-2.0"
] | 0 | 812dc6f350261793c67a928786fc081158f22a76 | https://github.com/abogaziah/PySyft/tree/812dc6f350261793c67a928786fc081158f22a76 |
UsBlock_nounpool | import torch
import torch.nn as nn
def conv3x3(in_channels, out_channels, stride=1, padding=1, bias=True):
return nn.Conv3d(in_channels, out_channels, kernel_size=3, stride=
stride, padding=padding, bias=bias)
class UsBlock_nounpool(nn.Module):
def __init__(self, in_channels, out_channels, up_mode=... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | MATHplus-Young-Academy/P2-Cardiac-Motion | UsBlock_nounpool | false | 5,560 | [
"Apache-2.0"
] | 1 | 844995e8e5760f981c425d13c0bd7f2f3bb8baec | https://github.com/MATHplus-Young-Academy/P2-Cardiac-Motion/tree/844995e8e5760f981c425d13c0bd7f2f3bb8baec |
MNIST_Encoder | import torch
import torch.nn as nn
from torch.nn import functional as F
class MNIST_Encoder(nn.Module):
def __init__(self, in_channels, latent_size):
super(MNIST_Encoder, self).__init__()
self.in_channels = in_channels
self.latent_size = latent_size
self.linear1 = nn.Linear(self.i... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | mdiephuis/adversarial-autoencoders | MNIST_Encoder | false | 7,216 | [
"MIT"
] | 1 | a722239564362796774de21a64fd92e81dce4089 | https://github.com/mdiephuis/adversarial-autoencoders/tree/a722239564362796774de21a64fd92e81dce4089 |
ConvertPointsToHomogeneous | # 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... | DoJing/frankmocap | ConvertPointsToHomogeneous | false | 11,368 | [
"BSD-3-Clause"
] | 0 | ac2ddc5a75a885ede5068a25049ca2bfe9330576 | https://github.com/DoJing/frankmocap/tree/ac2ddc5a75a885ede5068a25049ca2bfe9330576 |
GaussianSmearing | import torch
import torch.nn as nn
class GaussianSmearing(nn.Module):
def __init__(self, in_features, start=0, end=1, num_freqs=50):
super(GaussianSmearing, self).__init__()
self.num_freqs = num_freqs
offset = torch.linspace(start, end, num_freqs)
self.coeff = -0.5 / (offset[1] - ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | Irlirion/ocp | GaussianSmearing | false | 13,845 | [
"MIT",
"BSD-3-Clause"
] | 242 | 6fb3e794eef31559db990300198eca20f41d8f37 | https://github.com/Irlirion/ocp/tree/6fb3e794eef31559db990300198eca20f41d8f37 |
QNetwork | import torch
import torch.nn as nn
import torch.nn.functional as F
def weights_init_(m):
if isinstance(m, nn.Linear):
torch.nn.init.xavier_uniform_(m.weight, gain=1)
torch.nn.init.constant_(m.bias, 0)
class QNetwork(nn.Module):
def __init__(self, num_inputs, num_actions, hidden_dim):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | NagisaZj/pytorch-soft-actor-critic | QNetwork | false | 9,319 | [
"MIT"
] | 0 | 7f219269356b11273e873a9f4d3ac7b86fe317cb | https://github.com/NagisaZj/pytorch-soft-actor-critic/tree/7f219269356b11273e873a9f4d3ac7b86fe317cb |
TimeIntervalTransformerLayer | # 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.... | Yingting-dev/ReChorus | TimeIntervalTransformerLayer | false | 2,997 | [
"MIT"
] | 0 | a16bc1e42f3e90e889133d7476c52ada44db573b | https://github.com/Yingting-dev/ReChorus/tree/a16bc1e42f3e90e889133d7476c52ada44db573b |
Attention | # 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.... | aaronbae/acl2020-dialogue-coherence-assessment | Attention | false | 1,343 | [
"MIT"
] | 0 | 98142558b2f80ace390d6b583a3242a373803a85 | https://github.com/aaronbae/acl2020-dialogue-coherence-assessment/tree/98142558b2f80ace390d6b583a3242a373803a85 |
Conv2dSamePadding | import torch
from torch import nn
import torch.nn.functional as F
def conv2d_same_padding(input, weight, bias=None, stride=1, dilation=1,
groups=1):
input_rows = input.size(2)
filter_rows = weight.size(2)
effective_filter_size_rows = (filter_rows - 1) * dilation[0] + 1
out_rows = (input_rows + str... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.nn.functional as F
assert_size_stride = torch.... | hulaba/pycrop-yield-prediction | Conv2dSamePadding | false | 6,830 | [
"MIT"
] | 1 | b4790dc2f87a73e8a0604e8c22466314090c5abf | https://github.com/hulaba/pycrop-yield-prediction/tree/b4790dc2f87a73e8a0604e8c22466314090c5abf |
Mask | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | pkuyym/nni | Mask | false | 10,990 | [
"MIT"
] | 0 | fe533e3bc65ea27997e16250adb503638548d500 | https://github.com/pkuyym/nni/tree/fe533e3bc65ea27997e16250adb503638548d500 |
Norm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | abcdefg-dev-dd/asxdcvfg | Norm | false | 6,048 | [
"Apache-2.0"
] | 1 | 83421d4a133810968d6e04b256a9312895452941 | https://github.com/abcdefg-dev-dd/asxdcvfg/tree/83421d4a133810968d6e04b256a9312895452941 |
MaxPPVPool1d | from torch.nn import Module
import torch
import torch.multiprocessing
import torch
class MaxPPVPool1d(Module):
"""Drop-in replacement for AdaptiveConcatPool1d - multiplies nf by 2"""
def forward(self, x):
_max = x.max(dim=-1).values
_ppv = torch.gt(x, 0).sum(dim=-1).float() / x.shape[-1]
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn import Module
import torch.multiprocessing
import torch
assert_size_stride ... | MOREDataset/tsai | MaxPPVPool1d | false | 9,285 | [
"Apache-2.0"
] | 0 | 54987a579365ca7722475fff2fc4a24dc054e82c | https://github.com/MOREDataset/tsai/tree/54987a579365ca7722475fff2fc4a24dc054e82c |
outconv | # 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... | allen-q/pytorch | outconv | false | 3,085 | [
"MIT"
] | 0 | 76947f8d6f0bcee04425ad69f93b9a5e3a5060ae | https://github.com/allen-q/pytorch/tree/76947f8d6f0bcee04425ad69f93b9a5e3a5060ae |
AdaptiveCatAvgMaxPool2d | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
import tor... | Alicegaz/torchok | AdaptiveCatAvgMaxPool2d | false | 16,923 | [
"Apache-2.0"
] | 8 | 7b8f95df466a25b1ad8ee93bed1a3c7516440cf4 | https://github.com/Alicegaz/torchok/tree/7b8f95df466a25b1ad8ee93bed1a3c7516440cf4 |
MultiHeadAttn | import torch
import torch.cuda
from torch.nn import functional as F
from torch import nn
import torch.distributed
import torch.utils.data
import torch.optim
class MultiHeadAttn(nn.Module):
def __init__(self, n_head, d_model, d_head, dropout, dropatt=0.1,
pre_lnorm=False):
super(MultiHeadAttn, sel... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Oreoluwa1234/NeMo | MultiHeadAttn | false | 9,722 | [
"Apache-2.0"
] | 0 | b01e3ceed34efe31fd43866685dbdd19a6b30928 | https://github.com/Oreoluwa1234/NeMo/tree/b01e3ceed34efe31fd43866685dbdd19a6b30928 |
RBFExpansion | # 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 numpy as np
import torch.nn as nn
assert_size_stride = torch._C._d... | VoVAllen/dgl-lifesci | RBFExpansion | false | 11,954 | [
"Apache-2.0"
] | 0 | 96895f2bddf255ad326f0bc4e8064bc3ed5c3044 | https://github.com/VoVAllen/dgl-lifesci/tree/96895f2bddf255ad326f0bc4e8064bc3ed5c3044 |
EncoderBias | # 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... | xiaoyanLi629/single_cell_data_analysis | EncoderBias | false | 13,114 | [
"MIT"
] | 0 | 39d6bbd64249385d2005a775ea1d05e210f41fbe | https://github.com/xiaoyanLi629/single_cell_data_analysis/tree/39d6bbd64249385d2005a775ea1d05e210f41fbe |
DotProd | import torch
import numpy as np
import torch.nn as nn
class DotProd(nn.Module):
def __init__(self):
nn.Module.__init__(self)
def forward(self, s, t):
if isinstance(s, np.ndarray):
s = torch.from_numpy(s).float()
if isinstance(t, np.ndarray):
t = torch.from_num... | 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... | mrernst/rl_robotics_research | DotProd | false | 10,612 | [
"MIT"
] | 0 | 0bc446cfb69591cb4ee3ce8d39815c463090a5f6 | https://github.com/mrernst/rl_robotics_research/tree/0bc446cfb69591cb4ee3ce8d39815c463090a5f6 |
GateConv | # 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 | GateConv | false | 7,949 | [
"Apache-2.0"
] | 40 | 5f7a060167790789d5e29a3d14d3c2ef8a34e765 | https://github.com/DQiaole/ZITS/tree/5f7a060167790789d5e29a3d14d3c2ef8a34e765 |
PixelNormLayer | import torch
import torch.nn as nn
class PixelNormLayer(nn.Module):
"""
Pixelwise feature vector normalization.
"""
def __init__(self, eps=1e-08):
super(PixelNormLayer, self).__init__()
self.eps = eps
def forward(self, x):
return x / torch.sqrt(torch.mean(x ** 2, dim=1, k... | 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_... | ferngonzalezp/turbulence-GAN | PixelNormLayer | false | 6,688 | [
"MIT"
] | 1 | a215a3c5af2dc9a723f95c344e295ecc08954f26 | https://github.com/ferngonzalezp/turbulence-GAN/tree/a215a3c5af2dc9a723f95c344e295ecc08954f26 |
Batch33MatVec3Mul | # 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... | ElliotHYLee/MyPyTorchAPI | Batch33MatVec3Mul | false | 11,399 | [
"MIT"
] | 0 | edb25b724372367e96e3bd2f420c023c4efbfcd7 | https://github.com/ElliotHYLee/MyPyTorchAPI/tree/edb25b724372367e96e3bd2f420c023c4efbfcd7 |
PairwiseBCELoss | import torch
from abc import abstractmethod
import torch.utils.data.dataloader
import torch.nn.functional as F
import torch.nn as nn
import torch.nn
class SimilarityLoss(nn.Module):
def __init__(self):
super(SimilarityLoss, self).__init__()
@abstractmethod
def forward(self, inputs, targets):
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from abc im... | FranziskaKuhls/flair | PairwiseBCELoss | false | 2,237 | [
"MIT"
] | 0 | 2bd9e72c961651c7c020076cb8fd80cbbb36da7c | https://github.com/FranziskaKuhls/flair/tree/2bd9e72c961651c7c020076cb8fd80cbbb36da7c |
SimpleTextClassifier | import torch
import torch.nn as nn
import torch.nn.functional as F
class SimpleTextClassifier(nn.Module):
"""Text Classifier with 1 hidden layer
"""
def __init__(self, num_labels, vocab_size):
super(SimpleTextClassifier, self).__init__()
self.linear1 = nn.Linear(vocab_size, 128)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | goodmike31/pytorch_active_learning | SimpleTextClassifier | false | 15,442 | [
"MIT"
] | 629 | 1224efad1f8022efa933cd36e30f78ed06eaaea7 | https://github.com/goodmike31/pytorch_active_learning/tree/1224efad1f8022efa933cd36e30f78ed06eaaea7 |
ScoringFunction | import torch
import torch.utils.data
import torch
import torch.nn as nn
class Conv2dAct(nn.Module):
def __init__(self, in_channels, out_channels, ksize=1, activation='relu'):
super(Conv2dAct, self).__init__()
self.conv = nn.Conv2d(in_channels, out_channels, ksize)
if activation == 'sigmoi... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
import torch.nn as nn
assert_size_stride = ... | caixin1998/pl-template | ScoringFunction | false | 10,117 | [
"BSD-3-Clause"
] | 0 | 6918f0289ab2b32d107e5722617d25c9a683399c | https://github.com/caixin1998/pl-template/tree/6918f0289ab2b32d107e5722617d25c9a683399c |
ExponentialEnvelope | import torch
class ExponentialEnvelope(torch.nn.Module):
"""
Exponential envelope function that ensures a smooth cutoff,
as proposed in Unke, Chmiela, Gastegger, Schütt, Sauceda, Müller 2021.
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom
and Nonlocal Effects
"""
def ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_str... | Open-Catalyst-Project/baselines | ExponentialEnvelope | false | 17,796 | [
"MIT"
] | 10 | 89948582edfb8debb736406d54db9813a5f2c88d | https://github.com/Open-Catalyst-Project/baselines/tree/89948582edfb8debb736406d54db9813a5f2c88d |
AttBlockV2 | # 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.... | Ajax0564/Cornell-Birdcall-Identification | AttBlockV2 | false | 18,415 | [
"MIT"
] | 2 | af13f2a73a3a665aa27722855a1c6a4d915d46db | https://github.com/Ajax0564/Cornell-Birdcall-Identification/tree/af13f2a73a3a665aa27722855a1c6a4d915d46db |
SelfAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | h851206/NLP | SelfAttention | false | 3,566 | [
"MIT"
] | 0 | f6dd78db78536f203cf9a6748075351df9daeba3 | https://github.com/h851206/NLP/tree/f6dd78db78536f203cf9a6748075351df9daeba3 |
Net | import torch
import torch.nn as nn
import torch.nn.functional as functional
class Net(nn.Module):
def __init__(self):
super().__init__()
self.layer1 = nn.Linear(28 ** 2, 64)
self.layer2 = nn.Linear(64, 10)
def forward(self, x):
x = x.view(-1, 28 ** 2)
x = self.layer1(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | AlexTaguchi/ml-tutorial | Net | false | 11,161 | [
"MIT"
] | 0 | 5b2693cd1648a72e9bcd6cee1223eedadba4b837 | https://github.com/AlexTaguchi/ml-tutorial/tree/5b2693cd1648a72e9bcd6cee1223eedadba4b837 |
DAInsHead | import torch
import torch.utils.data
from torchvision.transforms import functional as F
from torch import nn
import torch.nn.functional as F
class DAInsHead(nn.Module):
"""
Adds a simple Instance-level Domain Classifier head
"""
def __init__(self, in_channels):
"""
Arguments:
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | Flsahkong/Domain-Adaptive-Faster-RCNN-PyTorch | DAInsHead | false | 5,258 | [
"MIT"
] | 1 | 2d3ed73714ea5d5ff52d0b2ea51396a498ae6abe | https://github.com/Flsahkong/Domain-Adaptive-Faster-RCNN-PyTorch/tree/2d3ed73714ea5d5ff52d0b2ea51396a498ae6abe |
LinearZeros | # 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
from torch im... | americast/glow-pytorch | LinearZeros | false | 6,185 | [
"MIT"
] | 1 | bbc576b96a5218417d25ae76b60f04ae24621de3 | https://github.com/americast/glow-pytorch/tree/bbc576b96a5218417d25ae76b60f04ae24621de3 |
BatchedVectorAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
class BatchedVectorAttention(nn.Module):
"""vector attention"""
def __init__(self, input_dim, hidden_dim):
super(BatchedVectorAttention, self).__init__()
self.theta = nn.Linear(input_dim, hidden_dim)
self.phi = nn.Line... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Crazy-Jack/BigGAN-PyTorch | BatchedVectorAttention | false | 326 | [
"MIT"
] | 0 | 1a5644e9c87cc399580c96cfeb180052076888da | https://github.com/Crazy-Jack/BigGAN-PyTorch/tree/1a5644e9c87cc399580c96cfeb180052076888da |
Split | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | XinZhang525/fGAIL | Split | false | 18,106 | [
"MIT"
] | 4 | 682d70286685612558e072d9a1668779b8ae325b | https://github.com/XinZhang525/fGAIL/tree/682d70286685612558e072d9a1668779b8ae325b |
PosEnc | import torch
import torch.nn as nn
import torch.utils.data
import torch.utils
from matplotlib import cm as cm
from torch.nn.parallel import *
from torchvision.models import *
from torchvision.datasets import *
class PosEnc(nn.Module):
def __init__(self, C, ks):
super().__init__()
self.weight = nn... | 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
import torch.utils
from matplotlib import cm as cm
from torch.nn.parallel import *
from torchv... | evdcush/ppuda | PosEnc | false | 15,344 | [
"MIT"
] | 262 | 22783ac92207da6730ee618c953af230c5c39f28 | https://github.com/evdcush/ppuda/tree/22783ac92207da6730ee618c953af230c5c39f28 |
ParallelPolarizedSelfAttention | import torch
from torch import nn
class ParallelPolarizedSelfAttention(nn.Module):
def __init__(self, channel=512):
super().__init__()
self.ch_wv = nn.Conv2d(channel, channel // 2, kernel_size=(1, 1))
self.ch_wq = nn.Conv2d(channel, 1, kernel_size=(1, 1))
self.softmax_channel = nn... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | LeftAttention/Attention-Codebase | ParallelPolarizedSelfAttention | false | 17,661 | [
"Apache-2.0"
] | 6 | 348ec66233a7c0f95a3cb5f0f11641e2a7a9b9c3 | https://github.com/LeftAttention/Attention-Codebase/tree/348ec66233a7c0f95a3cb5f0f11641e2a7a9b9c3 |
Fire | import torch
from torch import nn
from collections import OrderedDict
class Fire(nn.Module):
def __init__(self, inplanes, squeeze_planes, expand1x1_planes,
expand3x3_planes):
super(Fire, self).__init__()
self.inplanes = inplanes
self.group1 = nn.Sequential(OrderedDict([('squeeze',... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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
from col... | Alibaba-AAIG/Beyond-ImageNet-Attack | Fire | false | 7,690 | [
"MIT"
] | 23 | c14b4844b64a8035b8fe033a617c0567224a9fa4 | https://github.com/Alibaba-AAIG/Beyond-ImageNet-Attack/tree/c14b4844b64a8035b8fe033a617c0567224a9fa4 |
RGBBlock | import torch
import torch.nn.functional as F
import torch.nn as nn
class Conv2DMod(nn.Module):
def __init__(self, in_chan, out_chan, kernel, demod=True, stride=1,
dilation=1, **kwargs):
super().__init__()
self.filters = out_chan
self.demod = demod
self.kernel = kernel
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | SongweiGe/DoodlerGAN | RGBBlock | false | 14,454 | [
"MIT"
] | 92 | d435d9b3c0579937cd3c22aa2051960ceb921785 | https://github.com/SongweiGe/DoodlerGAN/tree/d435d9b3c0579937cd3c22aa2051960ceb921785 |
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.... | hamjam/NeMo | MultiHeadAttention | false | 15,502 | [
"Apache-2.0"
] | 4,145 | b3484d32e1317666151f931bfa39867d88ed8658 | https://github.com/hamjam/NeMo/tree/b3484d32e1317666151f931bfa39867d88ed8658 |
ResidualConvUnit | import torch
import torch.nn as nn
import torch.fft
import torch.utils.cpp_extension
import torch.nn
class ResidualConvUnit(nn.Module):
def __init__(self, cin, activation, bn):
super().__init__()
self.conv = nn.Conv2d(cin, cin, kernel_size=3, stride=1, padding=1,
bias=True)
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
import torch.nn as nn
import torch.fft
import torch.utils.cpp_extension
import t... | autonomousvision/stylegan_xl | ResidualConvUnit | false | 14,965 | [
"MIT"
] | 214 | 8c76531bcbf0931c295ecd1d32f75af998d1411f | https://github.com/autonomousvision/stylegan_xl/tree/8c76531bcbf0931c295ecd1d32f75af998d1411f |
RpowInt | # 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_c... | Ilyabasharov/torch2trt | RpowInt | false | 2,541 | [
"MIT"
] | 0 | 76bf298b3da408509665e23e2494922b131afb10 | https://github.com/Ilyabasharov/torch2trt/tree/76bf298b3da408509665e23e2494922b131afb10 |
CFRB | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from co... | wwjfsfs/wwjyyds | CFRB | false | 13,137 | [
"MIT"
] | 0 | 80cd6267fde7cd98838078a0d5178a557ceb7414 | https://github.com/wwjfsfs/wwjyyds/tree/80cd6267fde7cd98838078a0d5178a557ceb7414 |
Project | import torch
import torch.nn as nn
class Project(nn.Module):
def __init__(self, batch_size, height, width, eps=1e-07):
super(Project, self).__init__()
self.batch_size = batch_size
self.height = height
self.width = width
self.eps = eps
def forward(self, points, K, 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
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | ArminMasoumian/GCNDepth | Project | false | 7,731 | [
"MIT"
] | 32 | 9fa77812fa944c2701a45f09acf988815ca50aee | https://github.com/ArminMasoumian/GCNDepth/tree/9fa77812fa944c2701a45f09acf988815ca50aee |
PhonyLanguageModel | # 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
... | daemon/vivi | PhonyLanguageModel | false | 9,942 | [
"MIT"
] | 0 | 6b7819006c944a756bf8a7b6d8beed92d19eb51a | https://github.com/daemon/vivi/tree/6b7819006c944a756bf8a7b6d8beed92d19eb51a |
bottleneck_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 | bottleneck_block | false | 9,783 | [
"MIT"
] | 0 | ad1196a4d33830f3219dbe2260a69364a745f094 | https://github.com/Zacchaeus14/lang-seg/tree/ad1196a4d33830f3219dbe2260a69364a745f094 |
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 torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | mzz235711/IAM | LayerNorm | false | 12,884 | [
"Apache-2.0"
] | 0 | e42c2b766442b666224b107b671eeab65f9b8efd | https://github.com/mzz235711/IAM/tree/e42c2b766442b666224b107b671eeab65f9b8efd |
LastBlock | import torch
import numpy as np
import torch.nn as nn
class BatchNormLayer(nn.Module):
"""Implements batch normalization layer."""
def __init__(self, channels, gamma=False, beta=True, decay=0.9, epsilon
=1e-05):
"""Initializes with basic settings.
Args:
channels: Number of 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 numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | lelechen63/idinvert_pytorch | LastBlock | false | 10,450 | [
"MIT"
] | 0 | 0469e1e5460ee4dd626c05bd35a83d52f9dc2cac | https://github.com/lelechen63/idinvert_pytorch/tree/0469e1e5460ee4dd626c05bd35a83d52f9dc2cac |
PairwiseCrossCorrelation | # 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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | vzinche/inferno | PairwiseCrossCorrelation | false | 4,512 | [
"Apache-2.0"
] | 0 | 91b22dfcd1b6a9ec415f0bbb6ae66caea42f4034 | https://github.com/vzinche/inferno/tree/91b22dfcd1b6a9ec415f0bbb6ae66caea42f4034 |
ResnetBlock | import torch
import torch.nn as nn
import torch.nn.functional as F
def actvn(x):
out = F.leaky_relu(x, 0.2)
return out
class ResnetBlock(nn.Module):
def __init__(self, fin, fout, fhidden=None, is_bias=True):
super().__init__()
self.is_bias = is_bias
self.learned_shortcut = fin !... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | DrLSimon/precision-recall-distributions-icml19 | ResnetBlock | false | 2,170 | [
"Apache-2.0"
] | 0 | 364188eaa26ac1bf39ebf038136c79aeee97da3a | https://github.com/DrLSimon/precision-recall-distributions-icml19/tree/364188eaa26ac1bf39ebf038136c79aeee97da3a |
CAE_ENC | import torch
import torch.nn as nn
import torch.nn.functional as F
class CAE_ENC(nn.Module):
def __init__(self):
super().__init__()
self.conv1 = nn.Conv2d(3, 32, kernel_size=5, padding=2, stride=2)
self.conv2 = nn.Conv2d(32, 64, kernel_size=3, padding=1, stride=2)
self.conv3 = nn.... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | positivevaib/semi-supervised-imagenet-classification | CAE_ENC | false | 4,188 | [
"MIT"
] | 0 | 4fb6427f5a72951c1b866a1ddbc2599811bb5770 | https://github.com/positivevaib/semi-supervised-imagenet-classification/tree/4fb6427f5a72951c1b866a1ddbc2599811bb5770 |
ActorNetwork | import torch
import torch.nn as nn
import torch.nn.functional as F
class ActorNetwork(nn.Module):
def __init__(self, state_size, action_size, hidden_size, seed=1412):
super(ActorNetwork, self).__init__()
self.seed = torch.manual_seed(seed)
self.fc1 = nn.Linear(state_size, hidden_size)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | vlgiitr/Workshop-Spring-2022 | ActorNetwork | false | 16,682 | [
"MIT"
] | 69 | 003ed62c75a876e946eaa481c27224dd38914015 | https://github.com/vlgiitr/Workshop-Spring-2022/tree/003ed62c75a876e946eaa481c27224dd38914015 |
CELoss | import torch
import torch.nn.functional as F
from torch import nn
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Return:
Tensor: Reduced loss tensor.
"""
r... | 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.functi... | JiYuanFeng/MCTrans | CELoss | false | 13,876 | [
"Apache-2.0"
] | 84 | 9b8b5677eef584b423d5e1630680a4b667cbe823 | https://github.com/JiYuanFeng/MCTrans/tree/9b8b5677eef584b423d5e1630680a4b667cbe823 |
A2Block | # 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.... | zj1008/GALD-DGCNet | A2Block | false | 16,832 | [
"MIT"
] | 127 | be7ebfe2b3d28ea28a2b4714852999d4af2a785e | https://github.com/zj1008/GALD-DGCNet/tree/be7ebfe2b3d28ea28a2b4714852999d4af2a785e |
SimpleClampMinModel | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.... | andreas-hommel/glow | SimpleClampMinModel | false | 3,324 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
SEBlock | # 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... | Vivianyzw/Dual.DBNet.pytorch | SEBlock | false | 1,193 | [
"Apache-2.0",
"MIT"
] | 0 | 19d823ed7c05076c087a3f7ad1127c71c1c0d692 | https://github.com/Vivianyzw/Dual.DBNet.pytorch/tree/19d823ed7c05076c087a3f7ad1127c71c1c0d692 |
ClassificationCircleLoss | # 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
... | lingtengqiu/LearnableTreeFilterV2 | ClassificationCircleLoss | false | 7,096 | [
"Apache-2.0"
] | 1 | 3814a5a84c0a5c33d6538749eaf5aed4827366de | https://github.com/lingtengqiu/LearnableTreeFilterV2/tree/3814a5a84c0a5c33d6538749eaf5aed4827366de |
ConvNet | # 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_... | iOsnaaente/Faculdade_ECA-UFSM | ConvNet | false | 3,650 | [
"MIT"
] | 0 | aea8b8d66169b073c439b47ad990e45695cbe953 | https://github.com/iOsnaaente/Faculdade_ECA-UFSM/tree/aea8b8d66169b073c439b47ad990e45695cbe953 |
VectorQuantizeLayer_GB | import torch
from torch import nn
import torch.nn.functional as F
class VectorQuantizeLayer_GB(nn.Module):
def __init__(self, input_dim, vq_size, vq_dim, temp=(1.0, 0.1, 0.99),
groups=1, combine_groups=True, time_first=True, activation=nn.GELU(
), weight_proj_depth=1, weight_proj_factor=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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | jefflai108/Self-Supervised-Speech-Pretraining-and-Representation-Learning | VectorQuantizeLayer_GB | false | 6,934 | [
"MIT"
] | 1 | bb8df008397d5a0360ab7d4b68e91588ed648270 | https://github.com/jefflai108/Self-Supervised-Speech-Pretraining-and-Representation-Learning/tree/bb8df008397d5a0360ab7d4b68e91588ed648270 |
MaskedSmoothL1 | # 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
... | ngerstle/soccerontable | MaskedSmoothL1 | false | 16,176 | [
"BSD-2-Clause"
] | 465 | 25426ff0f8fe0ce008b99c5c0fdbb35091d8d92c | https://github.com/ngerstle/soccerontable/tree/25426ff0f8fe0ce008b99c5c0fdbb35091d8d92c |
eca_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 math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.a... | RuidongDavidLin/YOLOV4-tiny-Pytorch | eca_block | false | 2,783 | [
"MIT"
] | 0 | f2bb941ff894e12551bf285eb09fd42db2fb3dee | https://github.com/RuidongDavidLin/YOLOV4-tiny-Pytorch/tree/f2bb941ff894e12551bf285eb09fd42db2fb3dee |
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