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 |
|---|---|---|---|---|---|---|---|---|---|---|
SSIM | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | Siddharth-Shrivastava7/DANNet | SSIM | false | 14,418 | [
"Apache-2.0"
] | 61 | 8db10056a4e445d24fc899505923615457cae5b7 | https://github.com/Siddharth-Shrivastava7/DANNet/tree/8db10056a4e445d24fc899505923615457cae5b7 |
GlobalAvgPool | import torch
import torch as th
from torch import nn
class GlobalAvgPool(nn.Module):
def __init__(self):
super(GlobalAvgPool, self).__init__()
def forward(self, x):
return th.mean(x, dim=[-2, -1])
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | bjuncek/video_feature_extractor | GlobalAvgPool | false | 12,168 | [
"Apache-2.0"
] | 0 | cac06b450d1164beb3f3710d5018c19091bce348 | https://github.com/bjuncek/video_feature_extractor/tree/cac06b450d1164beb3f3710d5018c19091bce348 |
_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.... | cplusx/SIGN | _SelfAttention_ | false | 1,743 | [
"Apache-2.0"
] | 0 | 9777fc3ddd4c6f799caeefe1e72482d5b1ecd8ae | https://github.com/cplusx/SIGN/tree/9777fc3ddd4c6f799caeefe1e72482d5b1ecd8ae |
FCDiscriminator | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
import torch.nn.functional as F
class FCDiscriminator(nn.Module):
def __init__(self, options):
"""
The fully connected generator is initialized by creating a chain of
fully connected layers that perform trans... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | unicredit/ganzo | FCDiscriminator | false | 16,647 | [
"Apache-2.0"
] | 73 | fb1d270f5091073e8f27da76ab508ab24e5d40e9 | https://github.com/unicredit/ganzo/tree/fb1d270f5091073e8f27da76ab508ab24e5d40e9 |
UpSampleLayer | # 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 torch_nn
import torch.nn.functional as torch_nn_func
assert_size_stride = torch._C._dynamo.guards... | Ninushkat/Impact-Synth-Hardware | UpSampleLayer | false | 14,090 | [
"MIT"
] | 55 | 37a2ecfec51b052b39d1ad0d4676f09d5f00e3c2 | https://github.com/Ninushkat/Impact-Synth-Hardware/tree/37a2ecfec51b052b39d1ad0d4676f09d5f00e3c2 |
ResidualBlock_thefirstone | # 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 ... | nathalia-kim/nu_gan | ResidualBlock_thefirstone | false | 10,725 | [
"MIT"
] | 0 | c1d0891945bd7ac3d95869db91f490f57f203110 | https://github.com/nathalia-kim/nu_gan/tree/c1d0891945bd7ac3d95869db91f490f57f203110 |
ISAB | import math
import torch
import torch.nn.functional as F
import torch.nn as nn
class MAB(nn.Module):
def __init__(self, dim_Q, dim_K, dim_V, num_heads, ln=False):
super(MAB, self).__init__()
self.dim_V = dim_V
self.num_heads = num_heads
self.fc_q = nn.Linear(dim_Q, dim_V)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | AntonValk/BagGraph-Graph-MIL | ISAB | false | 16,957 | [
"MIT"
] | 8 | 1447b52b32995cf6c71e731dd1261104cd66ced0 | https://github.com/AntonValk/BagGraph-Graph-MIL/tree/1447b52b32995cf6c71e731dd1261104cd66ced0 |
GLU | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | L-Net-1992/DI-engine | GLU | false | 5,510 | [
"Apache-2.0"
] | 1 | 06803b4e18fa64bbed0fd1d44952242c0c063b0f | https://github.com/L-Net-1992/DI-engine/tree/06803b4e18fa64bbed0fd1d44952242c0c063b0f |
SimpleNotModule | # 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 | SimpleNotModule | false | 3,349 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
MultiHeadAttentionBlock | import math
import torch
import torch.nn.parallel
import torch.nn as nn
import torch.utils.data
import torch.backends.cudnn
def mask_logits(inputs, mask, mask_value=-1e+30):
mask = mask.type(torch.float32)
return inputs + (1.0 - mask) * mask_value
class Conv1D(nn.Module):
def __init__(self, in_dim, out... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | MicroTensor-ai/episodic-memory | MultiHeadAttentionBlock | false | 11,709 | [
"MIT"
] | 0 | 295a3752ab94c7a6f45355aa2c54bffbf84b574f | https://github.com/MicroTensor-ai/episodic-memory/tree/295a3752ab94c7a6f45355aa2c54bffbf84b574f |
SimpleMatmulModule | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleMatmulModule(torch.nn.Module):
def __init__(self):
super(SimpleMatmulModule, self).__init__()
def forward(self, a, b):
return a.matmul(b + b)
def get_inputs():
return [torch.rand([4, 4, 4, 4]), torch.rand([4, 4... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | YaronBenAtar/glow | SimpleMatmulModule | false | 14,667 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
GGCL_D | # 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.... | marblet/DeepRobust | GGCL_D | false | 10,557 | [
"MIT"
] | 0 | 126c05818e38062c2423cd40dc8937ccc43c738b | https://github.com/marblet/DeepRobust/tree/126c05818e38062c2423cd40dc8937ccc43c738b |
DQN_RAM | # 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_... | transedward/pytoch-dqn | DQN_RAM | false | 16,621 | [
"MIT"
] | 358 | 1ffda6f3724b3bb37c3195b09b651b1682d4d4fd | https://github.com/transedward/pytoch-dqn/tree/1ffda6f3724b3bb37c3195b09b651b1682d4d4fd |
Message_Passing_Unit_v1 | # 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.utils.data
from ... | champon1020/scene_graph_benchmark | Message_Passing_Unit_v1 | false | 9,984 | [
"MIT"
] | 0 | 970a7499f8fa2854810bd650f6c991bcad5748db | https://github.com/champon1020/scene_graph_benchmark/tree/970a7499f8fa2854810bd650f6c991bcad5748db |
Classifier | # 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.... | a-coles/fast-accent-detector | Classifier | false | 6,037 | [
"MIT"
] | 1 | e5b993fba7397cd8c4071479bd92d1e0ba54d363 | https://github.com/a-coles/fast-accent-detector/tree/e5b993fba7397cd8c4071479bd92d1e0ba54d363 |
Sine | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert... | FinbarArgus/phynn | Sine | false | 2,238 | [
"Apache-2.0"
] | 0 | 436bfd6fa4ad86692bf12b4f76c92bc177626c40 | https://github.com/FinbarArgus/phynn/tree/436bfd6fa4ad86692bf12b4f76c92bc177626c40 |
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
from torch._inductor.runtime.triton_helpers import math as tl_math
import functools
impor... | dkswxd/Swin-Spectral | DiceLoss | false | 6,593 | [
"Apache-2.0"
] | 1 | 5d8c364b0d89e4dd21590bb58f7a434a5b97254c | https://github.com/dkswxd/Swin-Spectral/tree/5d8c364b0d89e4dd21590bb58f7a434a5b97254c |
_leaky_relu | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | maxuanquang/SfmLearner-Redesign | _leaky_relu | false | 7,180 | [
"MIT"
] | 1 | 0250a9cc443b5754ba45f69153a03ca26f903a7b | https://github.com/maxuanquang/SfmLearner-Redesign/tree/0250a9cc443b5754ba45f69153a03ca26f903a7b |
Correlation | import torch
from torch import nn
class Correlation(nn.Module):
"""Correlation Congruence for Knowledge Distillation, ICCV 2019.
The authors nicely shared the code with me. I restructured their code to be
compatible with my running framework. Credits go to the original author"""
def __init__(self):
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_... | UBCDingXin/RepDistiller | Correlation | false | 14,510 | [
"BSD-2-Clause"
] | 1,347 | dcc043277f2820efafd679ffb82b8e8195b7e222 | https://github.com/UBCDingXin/RepDistiller/tree/dcc043277f2820efafd679ffb82b8e8195b7e222 |
MLPDecoder | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | AlenUbuntu/Fashion-AI | MLPDecoder | false | 18,434 | [
"Apache-2.0"
] | 3 | d0e77cea81448fb20697828ee12fa57889df302c | https://github.com/AlenUbuntu/Fashion-AI/tree/d0e77cea81448fb20697828ee12fa57889df302c |
WeightNet | # 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... | Alexis-Fab/mmaction2 | WeightNet | false | 11,207 | [
"Apache-2.0"
] | 0 | 6f76bb465a7164f907318cf58f77fc3d613f8f0f | https://github.com/Alexis-Fab/mmaction2/tree/6f76bb465a7164f907318cf58f77fc3d613f8f0f |
GraphConvSparse | import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
def glorot_init(input_dim, output_dim):
init_range = np.sqrt(6.0 / (input_dim + output_dim))
initial = torch.rand(input_dim, output_dim) * 2 * init_range - init_range
return nn.Parameter(initial)
class GraphConvSparse(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | ksuchoi216/learn-to-cluster | GraphConvSparse | false | 3,939 | [
"MIT"
] | 0 | bef44f92be14e00a96545061a5ecfa7a27da267e | https://github.com/ksuchoi216/learn-to-cluster/tree/bef44f92be14e00a96545061a5ecfa7a27da267e |
DQNLoss | import torch
import numpy as np
import torch.nn.functional as F
from torch.nn.modules.loss import _Loss
class DQNLoss(_Loss):
def __init__(self, mode='huber', size_average=None, reduce=None,
reduction='mean'):
super().__init__(size_average, reduce, reduction)
self.mode = mode
self... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn.functional as F
from torch.nn.modules.loss import _Loss
a... | opium-sh/prl | DQNLoss | false | 16,211 | [
"MIT"
] | 51 | 3e21f8c7c87cfc7aee84d9e264c3a8b2bc549076 | https://github.com/opium-sh/prl/tree/3e21f8c7c87cfc7aee84d9e264c3a8b2bc549076 |
FeatureFusion | # 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.... | zhangzhengde0225/SwinTrack | FeatureFusion | false | 16,842 | [
"MIT"
] | 143 | 526be17f8ef266cb924c6939bd8dda23e9b73249 | https://github.com/zhangzhengde0225/SwinTrack/tree/526be17f8ef266cb924c6939bd8dda23e9b73249 |
mfm | # 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... | AnimeshKoratana/blurryface | mfm | false | 59 | [
"Apache-2.0"
] | 0 | c6cb5feec02f6d5af3acb1678336800390715d65 | https://github.com/AnimeshKoratana/blurryface/tree/c6cb5feec02f6d5af3acb1678336800390715d65 |
ResidualMLP | import torch
import torch.nn as nn
class ResidualMLP(nn.Module):
def __init__(self, input_dim, target_dim, hidden_dim=64):
super(ResidualMLP, self).__init__()
self.linear1 = nn.Linear(input_dim, hidden_dim)
self.linear2 = nn.Linear(hidden_dim, hidden_dim)
self.linear3 = nn.Linear(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | greydanus/piecewise_node | ResidualMLP | false | 6,776 | [
"Apache-2.0"
] | 1 | 9d218d4ec1bab486ae954ad2e84732a5f952770f | https://github.com/greydanus/piecewise_node/tree/9d218d4ec1bab486ae954ad2e84732a5f952770f |
RNN | import torch
import torch.nn as nn
from torch.autograd import Variable
class RNN(nn.Module):
def __init__(self, category_size, input_size, hidden_size, output_size):
super(RNN, self).__init__()
self.category_size = category_size
self.input_size = input_size
self.hidden_size = hidd... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.autograd import Variable
assert_size_stride = t... | igorwood/practical-pytorch | RNN | false | 15,604 | [
"MIT"
] | 4,847 | c08fc28ba1f7d6838c3938076cc1b03d90dccace | https://github.com/igorwood/practical-pytorch/tree/c08fc28ba1f7d6838c3938076cc1b03d90dccace |
ChanNorm | import torch
from torch import nn
class ChanNorm(nn.Module):
def __init__(self, dim, eps=1e-05):
super().__init__()
self.eps = eps
self.g = nn.Parameter(torch.ones(1, dim, 1, 1))
self.b = nn.Parameter(torch.zeros(1, dim, 1, 1))
def forward(self, x):
std = torch.var(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
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Netruk44/stylegan2-deepspeed | ChanNorm | false | 5,651 | [
"MIT"
] | 1 | d6efe64a2f8cdfa9477d2229652c5e1a2348d52d | https://github.com/Netruk44/stylegan2-deepspeed/tree/d6efe64a2f8cdfa9477d2229652c5e1a2348d52d |
Gate | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | albert-dot-ai/MnemonicReader | Gate | false | 12,066 | [
"BSD-3-Clause"
] | 0 | eb51eb679a58677a405953c0c579568377c0b0f8 | https://github.com/albert-dot-ai/MnemonicReader/tree/eb51eb679a58677a405953c0c579568377c0b0f8 |
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
from torch._inductor.runtime.... | kidconan/fast_speech_trans | FFN | false | 3,844 | [
"MIT"
] | 0 | 4d1d8fe0a871e37165e2a6333a11751ce2a017c0 | https://github.com/kidconan/fast_speech_trans/tree/4d1d8fe0a871e37165e2a6333a11751ce2a017c0 |
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.... | Sala7efelninja/GST-Tacotron | MultiHeadAttention | false | 11,854 | [
"MIT"
] | 0 | e69a5663832a2c3639d4afbb85092a35be621380 | https://github.com/Sala7efelninja/GST-Tacotron/tree/e69a5663832a2c3639d4afbb85092a35be621380 |
PytorchMultiClass | # 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.... | freescania/advdsi_at2 | PytorchMultiClass | false | 10,149 | [
"MIT"
] | 0 | 13fa0b8beaeccc28975aea40ee5a1db3dd3e33be | https://github.com/freescania/advdsi_at2/tree/13fa0b8beaeccc28975aea40ee5a1db3dd3e33be |
Mish | import torch
import torch.nn.functional as F
from torch import nn
class Mish(nn.Module):
def forward(self, x):
return x * F.softplus(x).tanh()
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, math as tl_math
from torch import nn
assert_size_stride = torch._C._dynamo.gua... | Cris-zj/mmdetection | Mish | false | 8,919 | [
"Apache-2.0"
] | 0 | ede648b93e7ba2562f835f338b778f3e705f7119 | https://github.com/Cris-zj/mmdetection/tree/ede648b93e7ba2562f835f338b778f3e705f7119 |
MaskedCrossEntropyCriterion | import torch
import torch.nn as nn
from torch.nn.modules.loss import _WeightedLoss
class MaskedCrossEntropyCriterion(_WeightedLoss):
def __init__(self, ignore_index=[-100], reduce=None):
super(MaskedCrossEntropyCriterion, self).__init__()
self.padding_idx = ignore_index
self.reduce = redu... | 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.modules.... | awesome-archive/inversecooking | MaskedCrossEntropyCriterion | false | 14,920 | [
"MIT"
] | 591 | bd07fad6e2efb7ed3bf496f0e19913ed063b3729 | https://github.com/awesome-archive/inversecooking/tree/bd07fad6e2efb7ed3bf496f0e19913ed063b3729 |
ScalableTanh | # 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... | hongyehu/NeuralRG | ScalableTanh | false | 15,550 | [
"Apache-2.0"
] | 65 | ff4eb18f7f9e083dac6f3da3995f3f69ecf381e8 | https://github.com/hongyehu/NeuralRG/tree/ff4eb18f7f9e083dac6f3da3995f3f69ecf381e8 |
IAdd | # 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_add_0(in_ptr0, in_ptr1, out_ptr1, xnumel,... | PogChamper/torch2trt | IAdd | false | 14,185 | [
"MIT"
] | 3,363 | 43b12627ec0de4d212efb6d02b07570205085ccc | https://github.com/PogChamper/torch2trt/tree/43b12627ec0de4d212efb6d02b07570205085ccc |
BasicModel_ConvNet_One_Conv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | Europium248/captum | BasicModel_ConvNet_One_Conv | false | 445 | [
"BSD-3-Clause"
] | 0 | ac02fae2651b8d68a44bcb9d03b91cbb3959f2fc | https://github.com/Europium248/captum/tree/ac02fae2651b8d68a44bcb9d03b91cbb3959f2fc |
Square | import torch
import torch.nn as nn
class Square(nn.Module):
def __init__(self):
super(Square, self).__init__()
def forward(self, X):
return torch.square(X)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | Mrswolf/brainda | Square | false | 8,571 | [
"MIT"
] | 24 | cbd2fa6334d9e6243324dbaf086be4eb4047e801 | https://github.com/Mrswolf/brainda/tree/cbd2fa6334d9e6243324dbaf086be4eb4047e801 |
MSELoss | import torch
import torch.nn as nn
class MSELoss(nn.Module):
""" Mean-squared error loss """
def __init__(self, reduction='mean', eps=1e-08):
super().__init__()
if reduction not in ('mean', 'sum'):
raise ValueError(
'`reduction` not recognized. must be "mean" or "s... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | KAGRA-TW-ML/deepclean-prod | MSELoss | false | 11,594 | [
"MIT"
] | 0 | 9fb834cb4027fd3b377bc0e763c237235c98eabd | https://github.com/KAGRA-TW-ML/deepclean-prod/tree/9fb834cb4027fd3b377bc0e763c237235c98eabd |
SoftKLDivLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
assert_size... | PiaCuk/KD_Lib | SoftKLDivLoss | false | 14,209 | [
"MIT"
] | 360 | 153299d484e4c6b33793749709dbb0f33419f190 | https://github.com/PiaCuk/KD_Lib/tree/153299d484e4c6b33793749709dbb0f33419f190 |
BinaryCrossEntropyLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch.... | MacOS/torchkge | BinaryCrossEntropyLoss | false | 13,999 | [
"BSD-3-Clause"
] | 248 | 89ed724368f3a5279c0f79c6ba1f948ed2a5696f | https://github.com/MacOS/torchkge/tree/89ed724368f3a5279c0f79c6ba1f948ed2a5696f |
AttentionHead | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | DocYard-ai/UCR | AttentionHead | false | 8,102 | [
"Apache-2.0"
] | 10 | 7618aa336f56e71d9fd8cdc2d591e3d138e3dc68 | https://github.com/DocYard-ai/UCR/tree/7618aa336f56e71d9fd8cdc2d591e3d138e3dc68 |
DataEmbedding_wo_pos | # 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
import torch.fft
assert_size_stride = torch._C... | jianzhnie/TsFormer | DataEmbedding_wo_pos | false | 3,759 | [
"Apache-2.0"
] | 0 | 47e362f02445ba00d5ab8db206667767e72faca7 | https://github.com/jianzhnie/TsFormer/tree/47e362f02445ba00d5ab8db206667767e72faca7 |
_MLP_B | # 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... | colorfulbrain/brain2020 | _MLP_B | false | 15,072 | [
"MIT"
] | 91 | 1dde5d34fd2ba1f38bcc38f2c973d167c8c3a168 | https://github.com/colorfulbrain/brain2020/tree/1dde5d34fd2ba1f38bcc38f2c973d167c8c3a168 |
Conv1dCompression | from torch.nn import Module
import torch
from torch import nn
import torch.utils.data
import torch.nn.functional
import torch.autograd
class Conv1dCompression(Module):
"""
## 1D Convolution Compression $f_c$
This is a simple wrapper around
[`nn.Conv1d`](https://pytorch.org/docs/stable/generated/torch... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch.nn import Module
from torch import nn
import torch.utils.data
import ... | techthiyanes/annotated_deep_learning_paper_implementations | Conv1dCompression | false | 16,552 | [
"MIT"
] | 3,714 | 8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 | https://github.com/techthiyanes/annotated_deep_learning_paper_implementations/tree/8af24da2dd39a9a87482a4d18c2dc829bbd3fd47 |
BasicModel_ConvNet_One_Conv | import torch
import torch.nn as nn
class BasicModel_ConvNet_One_Conv(nn.Module):
def __init__(self, inplace=False):
super().__init__()
self.conv1 = nn.Conv2d(1, 2, 3, 1)
self.relu1 = nn.ReLU(inplace=inplace)
self.fc1 = nn.Linear(8, 4)
self.conv1.weight = nn.Parameter(torch... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | ngduduong/captum | BasicModel_ConvNet_One_Conv | false | 4,080 | [
"BSD-3-Clause"
] | 0 | 6fe5f0f23ea975e73e0c0dee79bdc01b4223d283 | https://github.com/ngduduong/captum/tree/6fe5f0f23ea975e73e0c0dee79bdc01b4223d283 |
PetarVGAT | # 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.... | zxhhh97/cogdl | PetarVGAT | false | 4,718 | [
"MIT"
] | 0 | de21c78d9bbbf0c6cafbc72ff241cda35693ec37 | https://github.com/zxhhh97/cogdl/tree/de21c78d9bbbf0c6cafbc72ff241cda35693ec37 |
SEModule | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from to... | AdityaSidharta/kaggle_humpback_new_whale | SEModule | false | 1,918 | [
"MIT"
] | 0 | 779d60746f8eba99d0336836200150fa7a08388e | https://github.com/AdityaSidharta/kaggle_humpback_new_whale/tree/779d60746f8eba99d0336836200150fa7a08388e |
EncoderImage | # 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 as np
... | Chris-cbc/SGRAF | EncoderImage | false | 13,498 | [
"Apache-2.0"
] | 110 | 785535168ad417dda523888f2f047359231fcbf7 | https://github.com/Chris-cbc/SGRAF/tree/785535168ad417dda523888f2f047359231fcbf7 |
PMA | # 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.... | karayanni/torch-scae | PMA | false | 10,441 | [
"Apache-2.0"
] | 0 | e044662d8942d8d1923d13d071f375144cf4a1e8 | https://github.com/karayanni/torch-scae/tree/e044662d8942d8d1923d13d071f375144cf4a1e8 |
DiceLoss | import torch
import torch.nn as nn
class DiceLoss(nn.Module):
def __init__(self):
super(DiceLoss, self).__init__()
def forward(self, input, target):
N, _H, _W = target.size(0), target.size(2), target.size(3)
smooth = 1
input_flat = input.view(N, -1)
target_flat = targ... | 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... | MargeryLab/Inf-Net | DiceLoss | false | 2,631 | [
"MIT"
] | 0 | e2f16b64b3d91f45961bf627277b249f8211c143 | https://github.com/MargeryLab/Inf-Net/tree/e2f16b64b3d91f45961bf627277b249f8211c143 |
make_dense_LReLU | # 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... | BJTU-MIMO/Channel_estimation_MRDN | make_dense_LReLU | false | 137 | [
"MIT"
] | 0 | f41972998a5403c901bc3e5d68d4acd05e9a7f6c | https://github.com/BJTU-MIMO/Channel_estimation_MRDN/tree/f41972998a5403c901bc3e5d68d4acd05e9a7f6c |
BalancedL1Loss | import torch
import numpy as np
import torch.nn as nn
import torch.onnx
def balanced_l1_loss(pred, target, beta=1.0, alpha=0.5, gamma=1.5,
reduction='none'):
assert beta > 0
assert pred.size() == target.size() and target.numel() > 0
diff = torch.abs(pred - target)
b = np.e ** (gamma / alpha) - 1
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import numpy as np
imp... | Xiangzhaohong/LidarNet | BalancedL1Loss | false | 5,988 | [
"Apache-2.0"
] | 1 | 42d025a7b629e387c9b9b01ead3558a8da81a3b0 | https://github.com/Xiangzhaohong/LidarNet/tree/42d025a7b629e387c9b9b01ead3558a8da81a3b0 |
StackTime | import torch
from torchvision.models.quantization import *
class StackTime(torch.nn.Module):
__constants__ = ['factor']
def __init__(self, factor):
super().__init__()
self.factor = int(factor)
def forward(self, x, x_lens):
r = torch.transpose(x, 0, 1)
s = r.shape
... | 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 torchvision.models.quantization import *
assert_size_stride = torch._C._dy... | mlperf/inference | StackTime | false | 16,156 | [
"Apache-2.0"
] | 388 | b284212941bcce7a558813c31ba2d356bac71885 | https://github.com/mlperf/inference/tree/b284212941bcce7a558813c31ba2d356bac71885 |
Adjust_naive | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
def get_conv2d_layer(in_c, out_c, k, s, p=0, dilation=1, groups=1):
return nn.Conv2d(in_channels=in_c, out_channels=out_c, kernel_size=k,
stride=s, padding=p, dilation=dilation, groups=groups)
class Adjust_naive(nn.Module):... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | AndersonYong/URetinex-Net-Retinex-based-Deep-Unfolding-Network-for-Low-light-Image-Enhancem | Adjust_naive | false | 10,313 | [
"MIT"
] | 0 | 9d837b8df9c761defb1eca390b3a60aa4a6fbb1a | https://github.com/AndersonYong/URetinex-Net-Retinex-based-Deep-Unfolding-Network-for-Low-light-Image-Enhancem/tree/9d837b8df9c761defb1eca390b3a60aa4a6fbb1a |
BertSelfAttention | import math
import torch
import torch.nn as nn
from sklearn.metrics import *
def sequence_mask(lengths, max_len=None):
"""
Creates a boolean mask from sequence lengths.
"""
batch_size = lengths.numel()
max_len = max_len or lengths.max()
return torch.arange(0, max_len).type_as(lengths).repeat(b... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Dio990521/LSTM_emo_classifier | BertSelfAttention | false | 5,197 | [
"MIT"
] | 1 | aaf2bf2d6a3e60c1acfcff5b82ab256f86ba0dbc | https://github.com/Dio990521/LSTM_emo_classifier/tree/aaf2bf2d6a3e60c1acfcff5b82ab256f86ba0dbc |
VGG_block | import torch
import torch.nn as nn
from torch.nn import init
class VGG_block(nn.Module):
""" 1. default have the bias
2. using ReLU and 3 * max pooling
3. 10 layers of VGG original
4. 2 extra layers by CMU
5. default in_dim = 3,out_dim = 128
6. all kernal_size = 3, stride =... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
from to... | H-Liu1997/Pytorch_Pose_Estimation_Framework | VGG_block | false | 5,315 | [
"MIT"
] | 1 | 06616b3459ff639f8486e6ea4f93922597788b2a | https://github.com/H-Liu1997/Pytorch_Pose_Estimation_Framework/tree/06616b3459ff639f8486e6ea4f93922597788b2a |
ConcatELU | import torch
import torch.nn as nn
import torch.nn.functional as F
def concat_elu(x):
"""Like concatenated ReLU (http://arxiv.org/abs/1603.05201), but with ELU instead."""
return F.elu(torch.cat([x, -x], dim=1))
class ConcatELU(nn.Module):
"""Like concatenated ReLU (http://arxiv.org/abs/1603.05201), but... | 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.functional as F
assert_size_stride = torc... | Nintorac/survae_experiments | ConcatELU | false | 900 | [
"MIT"
] | 0 | d68cc25e2604aab08b53617c1f3ffe4716f166c4 | https://github.com/Nintorac/survae_experiments/tree/d68cc25e2604aab08b53617c1f3ffe4716f166c4 |
ScoreNetwork | # 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.nn impor... | stungkit/Copycat-abstractive-opinion-summarizer | ScoreNetwork | false | 16,502 | [
"MIT"
] | 51 | 04fe5393a7bb6883516766b762f6a0c530e95375 | https://github.com/stungkit/Copycat-abstractive-opinion-summarizer/tree/04fe5393a7bb6883516766b762f6a0c530e95375 |
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
from torch._inductor.runtime.... | danielrjiang/Ax | CNN | false | 12,247 | [
"MIT"
] | 0 | 43014b28683b3037b5c7307869cb9b75ca31ffb6 | https://github.com/danielrjiang/Ax/tree/43014b28683b3037b5c7307869cb9b75ca31ffb6 |
MaskedSoftmax | import torch
from torch.nn import functional as F
import torch.utils.data
import torch.nn as nn
class MaskedSoftmax(nn.Module):
def __init__(self, dim):
super(MaskedSoftmax, self).__init__()
self.dim = dim
def forward(self, logit, mask=None):
if mask is None:
dist = F.sof... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.utils.dat... | Nullius-2020/TAKG-Paddle | MaskedSoftmax | false | 14,127 | [
"MIT"
] | 130 | 7ebb5c4cdd1d2c68b1ca4a518b73c5e815fc5812 | https://github.com/Nullius-2020/TAKG-Paddle/tree/7ebb5c4cdd1d2c68b1ca4a518b73c5e815fc5812 |
SELayer | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
class SELayer(nn.Module):
def __init__(self, in_channels, reduction):
super(SELayer, self).__init__()
mid_channels = in_channels // reduction
self.fc1 = nn.Linear(in_channels, mid_channels)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | ChengBin1997/pytorch_image_classification | SELayer | false | 257 | [
"MIT"
] | 0 | f7c39efceb86d961489514917d11b96f44699094 | https://github.com/ChengBin1997/pytorch_image_classification/tree/f7c39efceb86d961489514917d11b96f44699094 |
TonemappedMSE | import torch
def _tonemap(im):
"""Helper Reinhards tonemapper.
Args:
im(torch.Tensor): image to tonemap.
Returns:
(torch.Tensor) tonemaped image.
"""
im = torch.clamp(im, min=0)
return im / (1 + im)
class TonemappedMSE(torch.nn.Module):
"""Mean-squared error on tonemaped ... | 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... | Mephisto405/WCMC-Public | TonemappedMSE | false | 8,551 | [
"BSD-2-Clause"
] | 19 | bd54f218d5239db84f404fbe1b465f9497bcf9e4 | https://github.com/Mephisto405/WCMC-Public/tree/bd54f218d5239db84f404fbe1b465f9497bcf9e4 |
CBAM | import torch
from torch import nn
class ChannelAttention(nn.Module):
def __init__(self, in_planes, ratio=8):
super(ChannelAttention, self).__init__()
self.avg_pool = nn.AdaptiveAvgPool2d(1)
self.max_pool = nn.AdaptiveMaxPool2d(1)
self.fc1 = nn.Conv2d(in_planes, ratio, 1, bias=Fals... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | HT-hlf/mmdetection_miner-2.22.0 | CBAM | false | 2,338 | [
"Apache-2.0"
] | 0 | 76eb94d6547f9f95cd58f41bb5c91941e82322b9 | https://github.com/HT-hlf/mmdetection_miner-2.22.0/tree/76eb94d6547f9f95cd58f41bb5c91941e82322b9 |
SEModule | # 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_... | ArronHZG/ABD-Net | SEModule | false | 9,591 | [
"MIT"
] | 0 | 4f6d15f4d389a55549ea10a2e00d4a5cdecb5753 | https://github.com/ArronHZG/ABD-Net/tree/4f6d15f4d389a55549ea10a2e00d4a5cdecb5753 |
MultiHeadAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.distributed
import torch.optim.lr_scheduler
import torch.utils.data
class MultiHeadAttention(nn.Module):
def __init__(self, idim, odim, nhead=1, use_bias=True):
super(MultiHeadAttention, self).__init__()
self.idim = i... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | CFM-MSG/SDN | MultiHeadAttention | false | 204 | [
"MIT"
] | 0 | f309602dc2bb73117355003f3744f8e5450dbccc | https://github.com/CFM-MSG/SDN/tree/f309602dc2bb73117355003f3744f8e5450dbccc |
ImageDiscriminator | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
class ImageDiscriminator(nn.Module):
def __init__(self):
super(ImageDiscriminator, self).__init__()
self.conv1 = nn.Conv2d(in_channels=6, out_channels=64, kernel_size=
3, stride=2, padding=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
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dyn... | HotaekHan/Synthetically_Supervised_Text_Recognition | ImageDiscriminator | false | 17,391 | [
"MIT"
] | 8 | a6bb7d3039b1280c6efe177b69d8b985d2e13285 | https://github.com/HotaekHan/Synthetically_Supervised_Text_Recognition/tree/a6bb7d3039b1280c6efe177b69d8b985d2e13285 |
Gated_Recurrent_Unit | # 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_... | EricssonResearch/scott-eu | Gated_Recurrent_Unit | false | 8,065 | [
"Apache-2.0"
] | 19 | aad7fd2f767a3c5e7d89223a593fd979ad596db3 | https://github.com/EricssonResearch/scott-eu/tree/aad7fd2f767a3c5e7d89223a593fd979ad596db3 |
DenseGraphConv | import math
import torch
from torch.nn import Parameter
import torch.utils.data
def uniform(size, tensor):
bound = 1.0 / math.sqrt(size)
if tensor is not None:
tensor.data.uniform_(-bound, bound)
class DenseGraphConv(torch.nn.Module):
"""See :class:`torch_geometric.nn.conv.GraphConv`.
"""
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
from torch.nn import Parameter
import torch.utils.data
assert_size_s... | KuangenZhang/pytorch_geometric | DenseGraphConv | false | 5,464 | [
"MIT"
] | 1 | 0bfc79a5eaccfcd16a82395e8578a90c5e44759f | https://github.com/KuangenZhang/pytorch_geometric/tree/0bfc79a5eaccfcd16a82395e8578a90c5e44759f |
BiaffineAttention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.nn import Module as Layer
assert_size_stride = ... | verages/PaddleOCR2Pytorch | BiaffineAttention | false | 4,662 | [
"Apache-2.0"
] | 0 | 201f0d5d6007f49620c49af7d222c3b220eb3e70 | https://github.com/verages/PaddleOCR2Pytorch/tree/201f0d5d6007f49620c49af7d222c3b220eb3e70 |
Actor | import torch
from torch import nn
from torch.distributions import Categorical
from torch.distributions import Normal
from torch.distributions import Independent
class Actor(nn.Module):
def __init__(self, obs_dim: 'int', ac_lim: 'float', ac_dim: 'int',
discrete: 'bool'=True):
super().__init__()
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | MIMUW-RL/spp-rl | Actor | false | 17,647 | [
"MIT"
] | 7 | 86b96cdd220cc4eae86f7cfd26924c69b498dcc6 | https://github.com/MIMUW-RL/spp-rl/tree/86b96cdd220cc4eae86f7cfd26924c69b498dcc6 |
CSDN_Tem | # 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... | Lundez/londogard-backend | CSDN_Tem | false | 11,667 | [
"MIT"
] | 0 | 90d9e405b832c2157e6fde00f58b9312cfc4ddbc | https://github.com/Lundez/londogard-backend/tree/90d9e405b832c2157e6fde00f58b9312cfc4ddbc |
ChannelPool | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | Sapio-S/Neural-SLAM | ChannelPool | false | 14,370 | [
"MIT"
] | 171 | 3a1e429fc54fe5682833bfe541512c8d62c2e2f7 | https://github.com/Sapio-S/Neural-SLAM/tree/3a1e429fc54fe5682833bfe541512c8d62c2e2f7 |
AttentionBlock | import math
import torch
from torch.nn import functional as F
from torch import nn
import torch.utils.data
import torch.optim
def convert_pad_shape(pad_shape):
"""
Used to get arguments for F.pad
"""
l = pad_shape[::-1]
pad_shape = [item for sublist in l for item in sublist]
return pad_shape
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | JINHXu/NeMo | AttentionBlock | false | 11,626 | [
"Apache-2.0"
] | 0 | 835db62e39919436824ce022fd3b3f6bac301cd6 | https://github.com/JINHXu/NeMo/tree/835db62e39919436824ce022fd3b3f6bac301cd6 |
TerLinear | # 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 ... | ninfueng/a-PyTorch-Tutorial-to-Object-Detection | TerLinear | false | 10,639 | [
"MIT"
] | 0 | fc7544720a7e939f5a56f4f7214e4965b7775f77 | https://github.com/ninfueng/a-PyTorch-Tutorial-to-Object-Detection/tree/fc7544720a7e939f5a56f4f7214e4965b7775f77 |
SDFNetwork | import torch
import numpy as np
import torch.nn as nn
def get_embedder(multires, input_dims=3):
embed_kwargs = {'include_input': True, 'input_dims': input_dims,
'max_freq_log2': multires - 1, 'num_freqs': multires,
'log_sampling': True, 'periodic_fns': [torch.sin, torch.cos]}
embedder_obj = Em... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | hzwangjl/NeuS | SDFNetwork | false | 10,242 | [
"MIT"
] | 0 | f1b89176ec18e19b3848d787416dab9a1ce5300b | https://github.com/hzwangjl/NeuS/tree/f1b89176ec18e19b3848d787416dab9a1ce5300b |
FocalLossSimple | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim
class FocalLossSimple(nn.Module):
def __init__(self, gamma=2, alpha=0.25):
super().__init__()
self.gamma = gamma
self.alpha = alpha
def forward(self, logit, target, epoch=0):
target = 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... | LiubovSobolevskaya/hpa-single-cell | FocalLossSimple | false | 17,602 | [
"MIT"
] | 6 | ebe6d046b651a1c45095f26e99cfb13adefb63d9 | https://github.com/LiubovSobolevskaya/hpa-single-cell/tree/ebe6d046b651a1c45095f26e99cfb13adefb63d9 |
BalancedL1Loss | import functools
import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as 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:
Tenso... | 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... | CityU-AIM-Group/HTD | BalancedL1Loss | false | 17,132 | [
"MIT"
] | 5 | 0be9fd844118c275abc6053b3cbd5ffb589e62ee | https://github.com/CityU-AIM-Group/HTD/tree/0be9fd844118c275abc6053b3cbd5ffb589e62ee |
EncoderLayer | import torch
import torch.nn as nn
import torch.nn.functional as F
class XavierLinear(nn.Module):
def __init__(self, d_in, d_out, bias=True):
super().__init__()
self.linear = nn.Linear(d_in, d_out, bias=bias)
nn.init.xavier_normal_(self.linear.weight)
def forward(self, x):
re... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | muberraozmen/MrMP | EncoderLayer | false | 4,057 | [
"MIT"
] | 0 | da6bcccbad85a682c848ff4aa1121c773d779e57 | https://github.com/muberraozmen/MrMP/tree/da6bcccbad85a682c848ff4aa1121c773d779e57 |
Linear_sigmoid | import torch
import torch.nn as nn
class Linear_sigmoid(nn.Module):
def __init__(self, dim_in, dim_out, bias=True):
super().__init__()
self.linear = nn.Linear(dim_in, dim_out, bias=bias)
self.activation = nn.Sigmoid()
def forward(self, x):
out = self.linear(x)
out = 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Armand-Morin/AutoML | Linear_sigmoid | false | 68 | [
"MIT"
] | 0 | 189867e2c7734d9afb87a9f51fd42bd6cc527a64 | https://github.com/Armand-Morin/AutoML/tree/189867e2c7734d9afb87a9f51fd42bd6cc527a64 |
VdLinear | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
def calculate_kl(log_alpha):
return 0.5 * torch.sum(torch.log1p(torch.exp(-log_alpha)))
class VdLinear(nn.Module):
"""
variational dropout
"""
def __init__(self, n_in, n_out, alpha_shape=(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.triton_helpers import libdevice, math as tl_math
im... | Neronjust2017/Bayesian-neural-networks | VdLinear | false | 17,763 | [
"MIT"
] | 4 | 9d7f781f5c2dfa8fadf26300b4b5b64366c939cd | https://github.com/Neronjust2017/Bayesian-neural-networks/tree/9d7f781f5c2dfa8fadf26300b4b5b64366c939cd |
PopulationColourRGBTransforms | from _paritybench_helpers import _mock_config
import torch
import numpy as np
class PopulationColourRGBTransforms(torch.nn.Module):
"""RGB color transforms and ordering of patches."""
def __init__(self, config, device, num_patches=1, pop_size=1,
requires_grad=True):
super(PopulationColourRGBT... | 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 numpy as np
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_... | deepmind/arnheim | PopulationColourRGBTransforms | false | 15,174 | [
"Apache-2.0"
] | 186 | cc9d2dd12391faa460b58bff1cc5be82145a5965 | https://github.com/deepmind/arnheim/tree/cc9d2dd12391faa460b58bff1cc5be82145a5965 |
BertOutput | # 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... | Cyndi-Tokyotech/Fin_Text_Analysis_ML | BertOutput | false | 11,026 | [
"MIT"
] | 0 | 7f9b6c1ea78f8e6f32c003b2de32809722df88d4 | https://github.com/Cyndi-Tokyotech/Fin_Text_Analysis_ML/tree/7f9b6c1ea78f8e6f32c003b2de32809722df88d4 |
BinaryFocalLossWithLogits | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import warn... | YanivHollander/kornia | BinaryFocalLossWithLogits | false | 14,631 | [
"ECL-2.0",
"Apache-2.0"
] | 418 | ccd258d0956da89b1feca96448eff8e4969d405a | https://github.com/YanivHollander/kornia/tree/ccd258d0956da89b1feca96448eff8e4969d405a |
BatchMLP | # 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... | VersElectronics/Neural-Processes | BatchMLP | false | 18,032 | [
"MIT"
] | 5 | 6eb7552a0d1c489189d6dd0f83704dcdbeaed24b | https://github.com/VersElectronics/Neural-Processes/tree/6eb7552a0d1c489189d6dd0f83704dcdbeaed24b |
FocalL2Loss | import torch
import torch.nn as nn
import torch.utils.data
import torch.nn.parallel
import torch.optim
import torch.utils.data.distributed
import torch.multiprocessing
class FocalL2Loss(nn.Module):
"""
Compute focal l2 loss between predict and groundtruth
:param thre: the threshold to distinguish between ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
import torch.utils.data
import torch.nn.parallel
im... | ducongju/Scale-sensitive-Heatmap | FocalL2Loss | false | 1,868 | [
"MIT"
] | 0 | 4016610ba96a6a6645895bbf4bcdb3ff4690a2d8 | https://github.com/ducongju/Scale-sensitive-Heatmap/tree/4016610ba96a6a6645895bbf4bcdb3ff4690a2d8 |
SigmoidFocalClassificationLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | ShashwatNigam99/PointRCNN | SigmoidFocalClassificationLoss | false | 9,452 | [
"MIT"
] | 0 | eee5f90fe4215cff0156e1f8cecf485e18dce1f8 | https://github.com/ShashwatNigam99/PointRCNN/tree/eee5f90fe4215cff0156e1f8cecf485e18dce1f8 |
RewardCriterion | import torch
import torch.nn as nn
from torch.autograd import *
def to_contiguous(tensor):
if tensor.is_contiguous():
return tensor
else:
return tensor.contiguous()
class RewardCriterion(nn.Module):
def __init__(self):
super(RewardCriterion, self).__init__()
def forward(sel... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.autograd import *
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | Maxi-0902/DRAN | RewardCriterion | false | 835 | [
"MIT"
] | 0 | c3dbfcbc018446544150dc4e151442d6a9fcd4d9 | https://github.com/Maxi-0902/DRAN/tree/c3dbfcbc018446544150dc4e151442d6a9fcd4d9 |
Critic | # 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... | joyce-fang/deep-reinforcement-learning | Critic | false | 3,777 | [
"MIT"
] | 0 | 62cedab584465bd1c3ef112eb149e8fc611546e3 | https://github.com/joyce-fang/deep-reinforcement-learning/tree/62cedab584465bd1c3ef112eb149e8fc611546e3 |
DataEmbedding_wo_pos | # 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... | MAZiqing/FEDformer | DataEmbedding_wo_pos | false | 17,657 | [
"MIT"
] | 7 | 7914d39df829494a8172afb9676982c3789d491d | https://github.com/MAZiqing/FEDformer/tree/7914d39df829494a8172afb9676982c3789d491d |
PerceptualLoss | # 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
import torch.nn as nn
assert_... | aadhithya/mobilenet-styletransfer | PerceptualLoss | false | 9,668 | [
"MIT"
] | 0 | 58e2c29020864d82d92d52d01427618bc35773fd | https://github.com/aadhithya/mobilenet-styletransfer/tree/58e2c29020864d82d92d52d01427618bc35773fd |
ResidualBlock_noBN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | jtang98/FFDNet-speckle | ResidualBlock_noBN | false | 7,000 | [
"MIT"
] | 1 | 084fa2782f0197d0e01ee8c595a16414aaf4ab8d | https://github.com/jtang98/FFDNet-speckle/tree/084fa2782f0197d0e01ee8c595a16414aaf4ab8d |
MNIST_FC | # 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.... | lihebi/AdvAE | MNIST_FC | false | 7,084 | [
"MIT"
] | 1 | 56dea2a33c7da64bcc577b0c061a38406fdde101 | https://github.com/lihebi/AdvAE/tree/56dea2a33c7da64bcc577b0c061a38406fdde101 |
decoder3 | # 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.... | czczup/URST | decoder3 | false | 15,105 | [
"Apache-2.0"
] | 119 | 000ec9f7728f12ffad989ec1d07b1dd579514133 | https://github.com/czczup/URST/tree/000ec9f7728f12ffad989ec1d07b1dd579514133 |
FocalLossSigmoid | import torch
import torch.nn as nn
from math import sqrt as sqrt
from itertools import product as product
class FocalLossSigmoid(nn.Module):
"""
sigmoid version focal loss
"""
def __init__(self, alpha=0.25, gamma=2, size_average=False):
super(FocalLossSigmoid, self).__init__()
self.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
... | yqyao/SSD_Pytorch | FocalLossSigmoid | false | 16,767 | [
"MIT"
] | 163 | 6060bbb650e7a1df7c12d7c9650a38eaba4ab6a8 | https://github.com/yqyao/SSD_Pytorch/tree/6060bbb650e7a1df7c12d7c9650a38eaba4ab6a8 |
SelfAttn | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.checkpoint
import torch as th
import torch.jit
class SelfAttn(nn.Module):
def __init__(self, hidden_size):
super(SelfAttn, self).__init__()
self.query = nn.Linear(hidden_size, 1)
def forward(self, keys, val... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | RoderickGu/Pretraining_GPT | SelfAttn | false | 17,860 | [
"Apache-2.0"
] | 4 | 0a3ecd38116dc271e273f57490b9b45b660bf401 | https://github.com/RoderickGu/Pretraining_GPT/tree/0a3ecd38116dc271e273f57490b9b45b660bf401 |
SelfAttention | import torch
from torch.nn import init
from torch.nn.parameter import Parameter
class SelfAttention(torch.nn.Module):
def __init__(self, wv_dim: 'int', maxlen: 'int'):
super(SelfAttention, self).__init__()
self.wv_dim = wv_dim
self.maxlen = maxlen
self.M = Parameter(torch.empty(si... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | xlwreally/Graduation-project-ABAE | SelfAttention | false | 4,587 | [
"MIT"
] | 0 | 7c389acfff0fd207e4588b4333521e2dfbf12ec7 | https://github.com/xlwreally/Graduation-project-ABAE/tree/7c389acfff0fd207e4588b4333521e2dfbf12ec7 |
EncModel | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.utils.... | Spacider/comp9444_assignment | EncModel | false | 2,849 | [
"Apache-2.0"
] | 0 | 149db9a562c579d03b3ea06c9de2020c8f3ef310 | https://github.com/Spacider/comp9444_assignment/tree/149db9a562c579d03b3ea06c9de2020c8f3ef310 |
CDFLayer | # 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
from torch.nn.parameter import Parameter
assert_size_stri... | asifr/armisc | CDFLayer | false | 3,250 | [
"MIT"
] | 0 | 486220ba498353faeb94f70cd8ffe917109526d2 | https://github.com/asifr/armisc/tree/486220ba498353faeb94f70cd8ffe917109526d2 |
AvgPool2dSame | # 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 math
import numpy as np
from typing import List
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
assert_... | Hcnaeg/DI-engine | AvgPool2dSame | false | 2,383 | [
"Apache-2.0"
] | 0 | aba0c629f87649854091e9e59d948f83962e3e1e | https://github.com/Hcnaeg/DI-engine/tree/aba0c629f87649854091e9e59d948f83962e3e1e |
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