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 |
|---|---|---|---|---|---|---|---|---|---|---|
ResNormLayer | # 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.... | dqshuai/MetaFormer | ResNormLayer | false | 15,268 | [
"MIT"
] | 67 | 669bf18c35fdb51e35b0a79fa86224a18cd38ac5 | https://github.com/dqshuai/MetaFormer/tree/669bf18c35fdb51e35b0a79fa86224a18cd38ac5 |
SqueezeExcite | # 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 ... | EileenWang90/mmpose | SqueezeExcite | false | 2,185 | [
"Apache-2.0"
] | 0 | 3fa1328a3b6351bf9b35df60d4d959973a6f8a71 | https://github.com/EileenWang90/mmpose/tree/3fa1328a3b6351bf9b35df60d4d959973a6f8a71 |
AttentionConv | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.init as init
class AttentionConv(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, stride=1,
padding=0, groups=1, bias=False):
super(AttentionConv, self).__init__()
self.out_channels = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.... | jhvics1/pytorch-stand-alone-self-attention | AttentionConv | false | 10,307 | [
"MIT"
] | 0 | 77375d99250ab9d8089e73bd4803afae30843748 | https://github.com/jhvics1/pytorch-stand-alone-self-attention/tree/77375d99250ab9d8089e73bd4803afae30843748 |
SeparableConv2d_same | import torch
from torch import nn
from torch.nn import functional as F
def fixed_padding(inputs, kernel_size, rate):
kernel_size_effective = kernel_size + (kernel_size - 1) * (rate - 1)
pad_total = kernel_size_effective - 1
pad_beg = pad_total // 2
pad_end = pad_total - pad_beg
padded_inputs = F.p... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
from torch.nn import functional as F
assert_size_stride = t... | Gummary/Pytorch-Project-Template | SeparableConv2d_same | false | 505 | [
"MIT"
] | 0 | 56bc5e253627d40fb8771eccdb2bb663c833beb3 | https://github.com/Gummary/Pytorch-Project-Template/tree/56bc5e253627d40fb8771eccdb2bb663c833beb3 |
ResidualBlock | import torch
import torch.optim
import torch.nn as nn
class ResidualBlock(nn.Module):
def __init__(self, in_f, out_f):
super(ResidualBlock, self).__init__()
self.conv = nn.Conv2d(in_f, out_f, 1, 1, padding=0, bias=False)
def forward(self, x):
residual = x
out = self.conv(x)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.optim
import torch.nn as nn
assert_size_stride = torch._C._dynamo.g... | ajiljalal/code-cs-fairness | ResidualBlock | false | 18,228 | [
"MIT"
] | 9 | 2025c1c8520444df800a1fc03d91d63d1415db54 | https://github.com/ajiljalal/code-cs-fairness/tree/2025c1c8520444df800a1fc03d91d63d1415db54 |
AugCNN | # 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.nn.functional as F
assert_size_stride = torch... | jajajag/auto-drac | AugCNN | false | 10,231 | [
"MIT"
] | 0 | 2241f9f5f10a4d863a8b9d198da1d39e5feb59a0 | https://github.com/jajajag/auto-drac/tree/2241f9f5f10a4d863a8b9d198da1d39e5feb59a0 |
UNetModule | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | ArmenGhambaryan/kaggle_carvana_segmentation | UNetModule | false | 13,296 | [
"MIT"
] | 447 | 648a6b5c807cb69011316fe6501241dacc027db2 | https://github.com/ArmenGhambaryan/kaggle_carvana_segmentation/tree/648a6b5c807cb69011316fe6501241dacc027db2 |
CausalConv1d | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | gaetangate/FewRel | CausalConv1d | false | 12,405 | [
"MIT"
] | 0 | 150199d1060571315b1f370b3b3352d7a7c72dd5 | https://github.com/gaetangate/FewRel/tree/150199d1060571315b1f370b3b3352d7a7c72dd5 |
ParallelAttention | # 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.... | alasin/vqa_pytorch | ParallelAttention | false | 6,169 | [
"MIT"
] | 1 | 8a311226d8eea56ef79f6be3c864ec05768e2895 | https://github.com/alasin/vqa_pytorch/tree/8a311226d8eea56ef79f6be3c864ec05768e2895 |
RDivInt | # 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... | ahangchen/torch2trt | RDivInt | false | 6,104 | [
"MIT"
] | 1 | 53c663f0e0570ef7ffd6771354ae3478f63bd328 | https://github.com/ahangchen/torch2trt/tree/53c663f0e0570ef7ffd6771354ae3478f63bd328 |
BinaryLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | jishnujayakumar/specter | BinaryLoss | false | 3,740 | [
"Apache-2.0"
] | 0 | 40e3b5e538004b00b0955f17dd3d71fb1f96b922 | https://github.com/jishnujayakumar/specter/tree/40e3b5e538004b00b0955f17dd3d71fb1f96b922 |
BertCrossAttention | from _paritybench_helpers import _mock_config
import math
import torch
from torch import nn
class BertSelfAttention(nn.Module):
def __init__(self, model_config):
super().__init__()
if model_config.hidden_size % model_config.num_attention_heads != 0:
raise ValueError(
'... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | HS-YN/PanoAVQA | BertCrossAttention | false | 18,390 | [
"MIT"
] | 3 | 657b83421ce64ea18b3e79fb580afc7034403ccc | https://github.com/HS-YN/PanoAVQA/tree/657b83421ce64ea18b3e79fb580afc7034403ccc |
NegModule | # 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... | mirecta/nncase | NegModule | false | 4,176 | [
"Apache-2.0"
] | 0 | d2efa59677a26f4259b3b6a5b6ec05ea16d4e40c | https://github.com/mirecta/nncase/tree/d2efa59677a26f4259b3b6a5b6ec05ea16d4e40c |
PointLoss | # 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.parallel
import torch.utils.data
import torch.nn as nn
assert_size_stride... | HeunSeungLim/hl_point | PointLoss | false | 13,809 | [
"MIT"
] | 204 | 866f9e216d1f47517093720f6ff70ef2f0338bbe | https://github.com/HeunSeungLim/hl_point/tree/866f9e216d1f47517093720f6ff70ef2f0338bbe |
WrapperKLDiv | # 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 ... | PaccMann/paccmann_datasets | WrapperKLDiv | false | 8,623 | [
"MIT"
] | 14 | 0cb0cee349ffab8e227f09f7df0a8bca6a71f22e | https://github.com/PaccMann/paccmann_datasets/tree/0cb0cee349ffab8e227f09f7df0a8bca6a71f22e |
ActorNetwork | import torch
import torch.nn as nn
import torch.nn.functional as F
class ActorNetwork(nn.Module):
def __init__(self, input_shape, output_shape, **kwargs):
super(ActorNetwork, self).__init__()
n_input = input_shape[-1]
n_output = output_shape[0]
self._h = nn.Linear(n_input, n_outpu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | PuzeLiu/mushroom-rl | ActorNetwork | false | 14,248 | [
"MIT"
] | 344 | 99942b425e66b4ddcc26009d7105dde23841e95d | https://github.com/PuzeLiu/mushroom-rl/tree/99942b425e66b4ddcc26009d7105dde23841e95d |
InstanceNorm | # 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.nn import Module
from torch import nn
import torch.utils.data
import... | Aarsh2001/annotated_deep_learning_paper_implementations | InstanceNorm | false | 4,775 | [
"MIT"
] | 1 | ff0d5c065da1a46769f5f66fddc252c178f8fa37 | https://github.com/Aarsh2001/annotated_deep_learning_paper_implementations/tree/ff0d5c065da1a46769f5f66fddc252c178f8fa37 |
ActivationQuantizer | from torch.autograd import Function
import torch
import torch.nn as nn
class Round(Function):
@staticmethod
def forward(self, input):
sign = torch.sign(input)
output = sign * torch.floor(torch.abs(input) + 0.5)
return output
@staticmethod
def backward(self, grad_output):
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch.... | XueYue404/QNN | ActivationQuantizer | false | 1,249 | [
"MIT"
] | 0 | 43cea970404156b591088d77672df58261edf1eb | https://github.com/XueYue404/QNN/tree/43cea970404156b591088d77672df58261edf1eb |
RefineDoublePendulumModel | import torch
import numpy as np
import torch.nn as nn
class SirenLayer(nn.Module):
def __init__(self, in_f, out_f, w0=30, is_first=False, is_last=False):
super().__init__()
self.in_f = in_f
self.w0 = w0
self.linear = nn.Linear(in_f, out_f)
self.is_first = is_first
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
import numpy ... | BoyuanChen/neural-state-variables | RefineDoublePendulumModel | false | 7,871 | [
"MIT"
] | 17 | 10483d93ac8c006f3786c434fb57d70d9ab465ec | https://github.com/BoyuanChen/neural-state-variables/tree/10483d93ac8c006f3786c434fb57d70d9ab465ec |
ConvWS2d | import torch
import torch.nn as nn
from torch.nn import functional as F
import torch.nn.parallel
def conv_ws_2d(input, weight, bias=None, stride=1, padding=0, dilation=1,
groups=1, eps=1e-05):
c_in = weight.size(0)
weight_flat = weight.view(c_in, -1)
mean = weight_flat.mean(dim=1, keepdim=True).view(c... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | Fanzhongjie/ARFE | ConvWS2d | false | 475 | [
"Apache-2.0"
] | 0 | 4b96b8c5bc0895d3d30acec2a490f81a860fe860 | https://github.com/Fanzhongjie/ARFE/tree/4b96b8c5bc0895d3d30acec2a490f81a860fe860 |
Dense | import torch
import torch.nn as nn
import torch.nn.functional as functions
class Dense(nn.Module):
def __init__(self):
super(Dense, self).__init__()
self.fc1 = nn.Linear(6 * 7, 32)
self.fc2 = nn.Linear(32, 16)
self.probhead = nn.Linear(16, 7)
self.valuehead = nn.Linear(16,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | IvLabs/model-based-RL | Dense | false | 17,444 | [
"MIT"
] | 7 | 8d22eabf7bf2601629015ef6c869e3850c306d6f | https://github.com/IvLabs/model-based-RL/tree/8d22eabf7bf2601629015ef6c869e3850c306d6f |
MinusRbfHSIC | import torch
import torch.nn as nn
import torch.utils.data
class HSIC(nn.Module):
"""Base class for the finite sample estimator of Hilbert-Schmidt Independence Criterion (HSIC)
..math:: HSIC (X, Y) := || C_{x, y} ||^2_{HS}, where HSIC (X, Y) = 0 iif X and Y are independent.
Empirically, we use the finite... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | EIDOSlab/bridging-debiasing-privacy-deep-learning | MinusRbfHSIC | false | 5,092 | [
"MIT"
] | 1 | b30ab798d5ffd7d44a6d7136523400c14a4d08f5 | https://github.com/EIDOSlab/bridging-debiasing-privacy-deep-learning/tree/b30ab798d5ffd7d44a6d7136523400c14a4d08f5 |
ComplexRotationComposition | # 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
from abc import abstractmethod
import torch.utils.data
assert_size_s... | DimitrisAlivas/StarQE | ComplexRotationComposition | false | 7,969 | [
"MIT"
] | 11 | c17676e5f1e3f19c0c4c117a50abe2ce22ffef28 | https://github.com/DimitrisAlivas/StarQE/tree/c17676e5f1e3f19c0c4c117a50abe2ce22ffef28 |
BinaryReg | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.utils.dat... | HarshSulakhe/pytorch_connectomics | BinaryReg | false | 9,852 | [
"MIT"
] | 0 | 73402e654afde69a43a5836cc90a32ef75c75dc2 | https://github.com/HarshSulakhe/pytorch_connectomics/tree/73402e654afde69a43a5836cc90a32ef75c75dc2 |
Encoder | import math
import torch
from torch import nn
class NormLayer(nn.Module):
"""
Implementation of Layer Normalization (https://arxiv.org/abs/1607.06450)
It consists of Batch Normalization Transform to speed up learning with mean and std computed according to the above paper
normWeights:
weights for this n... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | simonepreite/QABERT | Encoder | false | 4,362 | [
"MIT"
] | 0 | ed3e49f6619f3ff660068291231909693cb8f5d5 | https://github.com/simonepreite/QABERT/tree/ed3e49f6619f3ff660068291231909693cb8f5d5 |
RMSNorm | # 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
from torch import nn
assert_... | ncoop57/x-transformers | RMSNorm | false | 10,607 | [
"MIT"
] | 0 | b65f25384349abfc101001b42482b05745c861fa | https://github.com/ncoop57/x-transformers/tree/b65f25384349abfc101001b42482b05745c861fa |
SimpleAvgPool1dModule | # 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... | YaronBenAtar/glow | SimpleAvgPool1dModule | false | 14,653 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
SoftDiceLoss | # 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.nn.modules.loss import _Loss
assert_size_stride = torch._C._dynamo.guards.asse... | WdBlink/AugMix-3DOCUNet-Brats2019 | SoftDiceLoss | false | 5,962 | [
"MIT"
] | 1 | 125c6c8682b51a550eeac9173d13d0a211576abc | https://github.com/WdBlink/AugMix-3DOCUNet-Brats2019/tree/125c6c8682b51a550eeac9173d13d0a211576abc |
CustomBatchNormAutograd | import torch
import torch.nn as nn
class CustomBatchNormAutograd(nn.Module):
"""
This nn.module implements a custom version of the batch norm operation for MLPs.
The operations called in self.forward track the history if the input tensors have the
flag requires_grad set to True. The backward pass does... | 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_... | davide-belli/deep-learning-labs | CustomBatchNormAutograd | false | 1,802 | [
"MIT"
] | 0 | 1acd37a527711dccdc00c1935724cc5de7c10955 | https://github.com/davide-belli/deep-learning-labs/tree/1acd37a527711dccdc00c1935724cc5de7c10955 |
TOP1_max | import torch
import torch.nn as nn
import torch.nn.functional as F
class TOP1_max(nn.Module):
def __init__(self):
super(TOP1_max, self).__init__()
def forward(self, logit):
logit_softmax = F.softmax(logit, dim=1)
diff = -(logit.diag().view(-1, 1).expand_as(logit) - logit)
los... | 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
... | hungthanhpham94/GRU4REC-pytorch | TOP1_max | false | 15,553 | [
"Apache-2.0"
] | 184 | 666b84264c4afae757fe55c6997dcf0a4da1d44e | https://github.com/hungthanhpham94/GRU4REC-pytorch/tree/666b84264c4afae757fe55c6997dcf0a4da1d44e |
Emo16 | import torch
import numpy as np
from torch import nn
import torch.nn.functional as F
class Emo16(nn.Module):
def __init__(self, input_size: 'int', num_channels: 'int'=40):
"""
Speech emotion recognition model proposed in:
`Trigeorgis, G., Ringeval, F., Brueckner, R., Marchi, E.,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import numpy as np
from torch... | tfyd/myEnd2you | Emo16 | false | 4,421 | [
"BSD-3-Clause"
] | 0 | 455d5404a19dd4867cb5db4f30705041d425d2b3 | https://github.com/tfyd/myEnd2you/tree/455d5404a19dd4867cb5db4f30705041d425d2b3 |
BasicModel_ConvNet | import torch
from torch import Tensor
import torch.nn as nn
from typing import no_type_check
class BasicModel_ConvNet(nn.Module):
def __init__(self) ->None:
super().__init__()
self.conv1 = nn.Conv2d(1, 2, 3, 1)
self.relu1 = nn.ReLU()
self.pool1 = nn.MaxPool2d(2)
self.conv2... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | YNNEKUW/captum | BasicModel_ConvNet | false | 12,009 | [
"BSD-3-Clause"
] | 0 | c8b5357b21f2ddf440e5f0ce25635977292aa5d1 | https://github.com/YNNEKUW/captum/tree/c8b5357b21f2ddf440e5f0ce25635977292aa5d1 |
LayerNorm | import torch
from torch import nn
class LayerNorm(nn.Module):
def __init__(self, num_channels, eps=1e-05):
super().__init__()
self.num_channels = num_channels
self.eps = eps
self.weight = nn.Parameter(torch.Tensor(num_channels))
self.bias = nn.Parameter(torch.Tensor(num_ch... | 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... | yoshipon/spl2021_neural-fca | LayerNorm | false | 11,082 | [
"MIT"
] | 0 | a316026667dd6bd888547c8348cab8cd3d88e84c | https://github.com/yoshipon/spl2021_neural-fca/tree/a316026667dd6bd888547c8348cab8cd3d88e84c |
LocalConv2d | import torch
import torch.nn as nn
import torch.nn.functional as F
class LocalConv2d(nn.Module):
def __init__(self, num_rows, num_feats_in, num_feats_out, kernel=1,
padding=0):
super(LocalConv2d, self).__init__()
self.num_rows = num_rows
self.out_channels = num_feats_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... | syKevinPeng/M3D-RPN | LocalConv2d | false | 10,835 | [
"MIT"
] | 0 | ae43248f0d64a83d7deef63308dd5ade25e7b751 | https://github.com/syKevinPeng/M3D-RPN/tree/ae43248f0d64a83d7deef63308dd5ade25e7b751 |
Task | import torch
import torch.nn
import torch.utils.data.distributed
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
class Task(nn.Module):
def __init__(self):
super().__init__()
self.p = nn.Parameter(torch.ones(2, 2))
def forward(self, x):
retur... | 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
import torch.utils.data.distributed
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.dat... | woqidaideshi/bagua | Task | false | 16,723 | [
"MIT"
] | 635 | 0ee96da598685748519d58d24ce983499cb36721 | https://github.com/woqidaideshi/bagua/tree/0ee96da598685748519d58d24ce983499cb36721 |
FCChain | import torch
import torch.utils.data
import torch.nn as nn
def _get_activation(activation):
valid = ['relu', 'leaky_relu', 'lrelu', 'tanh', 'sigmoid']
assert activation in valid, 'activation should be one of {}'.format(valid)
if activation == 'relu':
return nn.ReLU(inplace=True)
if activation ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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
impor... | IlyaBizyaev/ttools | FCChain | false | 8,308 | [
"MIT"
] | 11 | b1435b19f397ce1baff9daed3cb287e52a029fdb | https://github.com/IlyaBizyaev/ttools/tree/b1435b19f397ce1baff9daed3cb287e52a029fdb |
MFH | import torch
import torch.nn as nn
import torch.nn.functional as F
class MFH(nn.Module):
def __init__(self, input_dims, output_dim, mm_dim=1200, factor=2,
activ_input='relu', activ_output='relu', normalize=False,
dropout_input=0.0, dropout_pre_lin=0.0, dropout_output=0.0):
super(MFH, self... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | JoannaLXY/block.bootstrap.pytorch | MFH | false | 11,562 | [
"BSD-3-Clause"
] | 0 | 42c3e7616b704e05c6ff2376ff68b5b18044fe77 | https://github.com/JoannaLXY/block.bootstrap.pytorch/tree/42c3e7616b704e05c6ff2376ff68b5b18044fe77 |
DQNGridworld | # 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... | jlebensold/flrl-ddpg | DQNGridworld | false | 6,962 | [
"MIT"
] | 1 | d91e9f4aedf48d0614e33bd22c7f684ecda089b1 | https://github.com/jlebensold/flrl-ddpg/tree/d91e9f4aedf48d0614e33bd22c7f684ecda089b1 |
aeEncoder | # 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... | XiaoyuanGuo/TEND_MedicalNoveltyDetection | aeEncoder | false | 1,264 | [
"MIT"
] | 0 | 5c2144f0592373d814540cc0fa8e60197ea51756 | https://github.com/XiaoyuanGuo/TEND_MedicalNoveltyDetection/tree/5c2144f0592373d814540cc0fa8e60197ea51756 |
PositionwiseFeedForward | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import math
from to... | AdrianVandierAst/fast-bert | PositionwiseFeedForward | false | 8,861 | [
"Apache-2.0"
] | 0 | f5adb426accee4a1882cdd4372fced4ef922c978 | https://github.com/AdrianVandierAst/fast-bert/tree/f5adb426accee4a1882cdd4372fced4ef922c978 |
ResidualBlock | import torch
import torch.nn as nn
import torch.utils.data
class ResidualBlock(nn.Module):
def __init__(self, channels):
super(ResidualBlock, self).__init__()
self.conv1 = nn.Conv2d(channels, channels, kernel_size=3, padding=1)
self.prelu = nn.PReLU()
self.conv2 = nn.Conv2d(channe... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | alsgkals2/SRResCGAN | ResidualBlock | false | 14,824 | [
"MIT"
] | 81 | a71201a93e1819045f9c7711743812546d3a1f31 | https://github.com/alsgkals2/SRResCGAN/tree/a71201a93e1819045f9c7711743812546d3a1f31 |
ProductOfExperts | # 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... | liuyangdh/multimodal-vae-public | ProductOfExperts | false | 15,932 | [
"MIT"
] | 98 | ba5941d010b0164094f5818b93baad9df546494e | https://github.com/liuyangdh/multimodal-vae-public/tree/ba5941d010b0164094f5818b93baad9df546494e |
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,... | ahangchen/torch2trt | IAdd | false | 6,101 | [
"MIT"
] | 1 | 53c663f0e0570ef7ffd6771354ae3478f63bd328 | https://github.com/ahangchen/torch2trt/tree/53c663f0e0570ef7ffd6771354ae3478f63bd328 |
SAModule_Head | # 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.... | vghost2008/C-3-Framework | SAModule_Head | false | 11,100 | [
"MIT"
] | 0 | dc6f1f67e403aff4dbb60f8ed06461c843407501 | https://github.com/vghost2008/C-3-Framework/tree/dc6f1f67e403aff4dbb60f8ed06461c843407501 |
NodeMaxpool3by3 | # 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.cuda
assert_size_stride = torch._C._dynamo.guards.asse... | HanseulJo/COMBO_NKmodel | NodeMaxpool3by3 | false | 8,223 | [
"BSD-2-Clause-FreeBSD"
] | 38 | 6dcee4c39d4cf200f44677925712ce57255d1489 | https://github.com/HanseulJo/COMBO_NKmodel/tree/6dcee4c39d4cf200f44677925712ce57255d1489 |
LocalLinearCF | # 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
from torch import Tensor
from typing import Optional
from torch impo... | Rikorose/DeepFilterNet | LocalLinearCF | false | 14,314 | [
"ECL-2.0",
"Apache-2.0",
"MIT"
] | 54 | afe6bfb53efae70207e18df7ed372c2cfe337fee | https://github.com/Rikorose/DeepFilterNet/tree/afe6bfb53efae70207e18df7ed372c2cfe337fee |
ResBlockWithFusedBN | # 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
from tor... | JinYAnGHe/openvino_training_extensions | ResBlockWithFusedBN | false | 2,716 | [
"Apache-2.0"
] | 0 | a0b4456a3c9fe6c1b7eabc9d5eb4e74d01453dee | https://github.com/JinYAnGHe/openvino_training_extensions/tree/a0b4456a3c9fe6c1b7eabc9d5eb4e74d01453dee |
ShiftSoftplus | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch.nn import Softplus
assert_size_stride = torch._C._d... | mufeili/Alchemy | ShiftSoftplus | false | 16,109 | [
"MIT"
] | 116 | 659c59fbbe93d406f8b3e0711e5a048e58c9c43c | https://github.com/mufeili/Alchemy/tree/659c59fbbe93d406f8b3e0711e5a048e58c9c43c |
NormedConv2d | import torch
from torch import nn
import torch.onnx
class NormedConv2d(nn.Conv2d):
"""Normalized Conv2d Layer.
Args:
tempeature (float, optional): Tempeature term. Default to 20.
power (int, optional): Power term. Default to 1.0.
eps (float, optional): The minimal value of divisor to
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import n... | ENOT-AutoDL/mmdetection-enot | NormedConv2d | false | 5,100 | [
"Apache-2.0"
] | 1 | f541749554436e3327bac00eee89b84f66c03551 | https://github.com/ENOT-AutoDL/mmdetection-enot/tree/f541749554436e3327bac00eee89b84f66c03551 |
Conv2dMtl | from torch.nn import Module
import math
import torch
from torch.nn.parameter import Parameter
from torch.nn import functional as F
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
from torch.nn.modules.module import Module
from torch.nn.modules.utils import _pair
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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.nn.parameter import Parameter... | mhd-medfa/class-incremental-learning | Conv2dMtl | false | 16,043 | [
"MIT"
] | 241 | c7c0a217d07b285f215672b3021beee52d4ef74f | https://github.com/mhd-medfa/class-incremental-learning/tree/c7c0a217d07b285f215672b3021beee52d4ef74f |
gconv_RNN | import torch
import torch.utils.data
import torch.nn as nn
class gconv_RNN(nn.Module):
def __init__(self):
super(gconv_RNN, self).__init__()
def forward(self, x, A):
x = torch.einsum('nvc,nvw->nwc', (x, A))
return x.contiguous()
def get_inputs():
return [torch.rand([4, 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.utils.data
import torch.nn as nn
assert_size_stride = torch._C._dyn... | kevin-xuan/Traffic-Benchmark | gconv_RNN | false | 15,815 | [
"MIT"
] | 120 | b9f8e40b4df9b58f5ad88432dc070cbbbcdc0228 | https://github.com/kevin-xuan/Traffic-Benchmark/tree/b9f8e40b4df9b58f5ad88432dc070cbbbcdc0228 |
ModAssign | import torch
class ModAssign(torch.nn.Module):
def __init__(self):
super(ModAssign, self).__init__()
def forward(self, x, y):
x %= y
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
from torch._inductor.runtime.triton_helpers import libdevice
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
@triton.jit
d... | Ilyabasharov/torch2trt | ModAssign | false | 2,550 | [
"MIT"
] | 0 | 76bf298b3da408509665e23e2494922b131afb10 | https://github.com/Ilyabasharov/torch2trt/tree/76bf298b3da408509665e23e2494922b131afb10 |
EncoderImagePrecomp | import torch
import numpy as np
import torch.nn as nn
from collections import OrderedDict
import torch.nn.init
def l2norm(x, dim=-1):
return x / x.norm(2, dim=dim, keepdim=True).clamp(min=1e-06)
class EncoderImagePrecomp(nn.Module):
""" image encoder """
def __init__(self, img_dim, embed_size, no_imgno... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | jefflai108/VGNSL | EncoderImagePrecomp | false | 6,931 | [
"MIT"
] | 1 | 0edc3db3691abbad2a505b2165bd99e7a62d784f | https://github.com/jefflai108/VGNSL/tree/0edc3db3691abbad2a505b2165bd99e7a62d784f |
LanguageModelCriterion | import torch
import torch.nn as nn
from torch.autograd import *
import torch.nn.init
def to_contiguous(tensor):
if tensor.is_contiguous():
return tensor
else:
return tensor.contiguous()
class LanguageModelCriterion(nn.Module):
def __init__(self):
super(LanguageModelCriterion, se... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from torch.autograd import *
import torch.nn.init
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empt... | WuJie1010/Fine-Grained-Image-Captioning | LanguageModelCriterion | false | 18,065 | [
"MIT"
] | 9 | 340bc1868634f3bf0fdd62d439fec32ee1b45407 | https://github.com/WuJie1010/Fine-Grained-Image-Captioning/tree/340bc1868634f3bf0fdd62d439fec32ee1b45407 |
BCNN | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
class BCNN(nn.Module):
"""Bilinear Pool
implementation of Bilinear CNN (BCNN)
https://arxiv.org/abs/1504.07889v5
Args:
thresh: small positive nu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | lvyilin/fast-MPN-COV | BCNN | false | 15,970 | [
"MIT"
] | 257 | d21c3fd2863c12f885faf20bd177dc066a25856c | https://github.com/lvyilin/fast-MPN-COV/tree/d21c3fd2863c12f885faf20bd177dc066a25856c |
PPMConcat | # 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._C
import torch.serialization
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strid... | ImportPaddle/APCNet | PPMConcat | false | 2,387 | [
"MIT"
] | 0 | 68ade1f83827b4cdd60ee4b6ac25454397100316 | https://github.com/ImportPaddle/APCNet/tree/68ade1f83827b4cdd60ee4b6ac25454397100316 |
Attention | import torch
import torch.nn.functional as F
class Attention(torch.nn.Module):
"""Scaled dot product attention."""
def __init__(self, hidden_dim, **kwargs):
super(Attention, self).__init__(**kwargs)
self.projection_layer = torch.nn.Linear(hidden_dim, 1)
def forward(self, atten_post):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | isspek/Cross-Lingual-Cyberbullying | Attention | false | 6,900 | [
"MIT"
] | 1 | 710c136b9233f0be87af72e43e25722e73158c52 | https://github.com/isspek/Cross-Lingual-Cyberbullying/tree/710c136b9233f0be87af72e43e25722e73158c52 |
FRN | # 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.nn as nn
assert... | UdonDa/StarGAN-v2-pytorch-nonofficial | FRN | false | 18,028 | [
"MIT"
] | 9 | 219df6b7fd4bd533686e2093ee914a337914ca9b | https://github.com/UdonDa/StarGAN-v2-pytorch-nonofficial/tree/219df6b7fd4bd533686e2093ee914a337914ca9b |
Critic | import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
def hidden_init(layer):
fan_in = layer.weight.data.size()[0]
lim = 1.0 / np.sqrt(fan_in)
return -lim, lim
class Critic(nn.Module):
"""Critic (Value) Model."""
def __init__(self, full_state_size, full_action_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.triton_helpers import libdevice
import numpy as np
... | monimoyd/project_deep_reinforcement_learning_collaboration_competition | Critic | false | 12,796 | [
"MIT"
] | 0 | 3782abb839b671ea53ece1435a4d481d7871cd39 | https://github.com/monimoyd/project_deep_reinforcement_learning_collaboration_competition/tree/3782abb839b671ea53ece1435a4d481d7871cd39 |
Generator | import torch
import torch.nn as nn
import torch.nn.functional as F
class Generator(nn.Module):
"""Define standard linear + softmax generation step."""
def __init__(self, d_model, vocab):
super(Generator, self).__init__()
self.proj = nn.Linear(d_model, vocab)
def forward(self, x):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | BruceWen120/neurips-reproducibility-challenge-2019 | Generator | false | 8,957 | [
"Apache-2.0"
] | 0 | b0635aefe83e3f895ce0991913824e861bb7d02d | https://github.com/BruceWen120/neurips-reproducibility-challenge-2019/tree/b0635aefe83e3f895ce0991913824e861bb7d02d |
multi_scale_spatial | # 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... | fabro66/Online-Skeleton-based-Action-Recognition | multi_scale_spatial | false | 15,338 | [
"MIT"
] | 63 | de00cbf17ceea98a7d07f68bbbd966bfd02d3b40 | https://github.com/fabro66/Online-Skeleton-based-Action-Recognition/tree/de00cbf17ceea98a7d07f68bbbd966bfd02d3b40 |
Gating | # 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.... | vislearn/esac | Gating | false | 16,705 | [
"BSD-3-Clause"
] | 62 | 4004b251525fa238a1cb6e1043fb41a4719a4ff2 | https://github.com/vislearn/esac/tree/4004b251525fa238a1cb6e1043fb41a4719a4ff2 |
Encoder | # 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
assert_size_stride ... | onimaru/Generative_models | Encoder | false | 12,862 | [
"Apache-2.0"
] | 0 | 915750066996aa3d4dce6ae605778b4eee3f0f3d | https://github.com/onimaru/Generative_models/tree/915750066996aa3d4dce6ae605778b4eee3f0f3d |
IRevInjectivePad | # 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... | iofthetiger/pkuad | IRevInjectivePad | false | 6,895 | [
"Apache-2.0"
] | 1 | 07496d108c614c84be028f344830becc9cac8fe5 | https://github.com/iofthetiger/pkuad/tree/07496d108c614c84be028f344830becc9cac8fe5 |
Vgg16 | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
import t... | agermanidis/HiDT | Vgg16 | false | 18,249 | [
"BSD-3-Clause"
] | 4 | 69192bb26785fc4e05038c45d05f2f880dd362d0 | https://github.com/agermanidis/HiDT/tree/69192bb26785fc4e05038c45d05f2f880dd362d0 |
BAP | # 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... | amobiny/hide_and_seek | BAP | false | 6,188 | [
"MIT"
] | 1 | e298d9a352a6ee58e9beedf15ef3d700473b7f27 | https://github.com/amobiny/hide_and_seek/tree/e298d9a352a6ee58e9beedf15ef3d700473b7f27 |
marginLoss | import torch
import torch.nn as nn
class marginLoss(nn.Module):
def __init__(self):
super(marginLoss, self).__init__()
def forward(self, pos, neg, margin):
val = pos - neg + margin
return torch.sum(torch.max(val, torch.zeros_like(val)))
def get_inputs():
return [torch.rand([4, ... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | DSRnD/UMLs | marginLoss | false | 2,121 | [
"MIT"
] | 0 | a524bc45bc3f2dc8b4a90f73f69e23ee36ba8be9 | https://github.com/DSRnD/UMLs/tree/a524bc45bc3f2dc8b4a90f73f69e23ee36ba8be9 |
CTLSTMCell | import torch
import torch.nn as nn
import torch.nn.functional as F
class CTLSTMCell(nn.Module):
def __init__(self, hidden_dim, beta=1.0, device=None):
super(CTLSTMCell, self).__init__()
device = device or 'cpu'
self.device = torch.device(device)
self.hidden_dim = 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.triton_helpers import libdevice, math as tl_math
im... | Anirudh-Murali/neural-hawkes-particle-smoothing | CTLSTMCell | false | 7,691 | [
"BSD-3-Clause"
] | 37 | 96b258838bdab33b781008daeedfa61dec0d553c | https://github.com/Anirudh-Murali/neural-hawkes-particle-smoothing/tree/96b258838bdab33b781008daeedfa61dec0d553c |
Agent | # 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_... | mpgussert/fundamentalRL | Agent | false | 7,277 | [
"MIT"
] | 1 | 4f45436226e0823c21cac316dec8bbf1df697467 | https://github.com/mpgussert/fundamentalRL/tree/4f45436226e0823c21cac316dec8bbf1df697467 |
Net2 | import torch
import torch.nn as nn
import torch.nn.functional as F
class Net2(nn.Module):
def __init__(self):
super(Net2, self).__init__()
self.conv1 = nn.Conv2d(3, 64, 3, padding=1)
self.conv2 = nn.Conv2d(64, 128, 3, padding=1)
self.conv3 = nn.Conv2d(128, 256, 3, 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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | SarodYatawatta/federated-pytorch-test | Net2 | false | 8,763 | [
"Apache-2.0"
] | 33 | 42a51ba12a92b32fa19273340d5b61e74e11d8e0 | https://github.com/SarodYatawatta/federated-pytorch-test/tree/42a51ba12a92b32fa19273340d5b61e74e11d8e0 |
simple_decoder | import torch
from torch import nn
import torch.utils
import torch.distributions
class simple_decoder(nn.Module):
def __init__(self, channels, width, height, dropout):
super(simple_decoder, self).__init__()
self.width = width
self.height = height
self.channels = channels
se... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
import torch.utils
import torch.distributions
assert_size_s... | Butters-cloud/denoising-normalizing-flow | simple_decoder | false | 7,839 | [
"MIT"
] | 12 | 12d56a0d069e10a744acabf5e78fdbfba8df54ee | https://github.com/Butters-cloud/denoising-normalizing-flow/tree/12d56a0d069e10a744acabf5e78fdbfba8df54ee |
AE_Net | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.optim import *
fro... | Paratra/IoTAnalytics_pub | AE_Net | false | 926 | [
"MIT"
] | 0 | 8c1d02b60ef609c3cba654ce4a5568c39fc63edf | https://github.com/Paratra/IoTAnalytics_pub/tree/8c1d02b60ef609c3cba654ce4a5568c39fc63edf |
InputInjection | # 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._C
import torch.serialization
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strid... | AlexanderDokuchaev/mmsegmentation | InputInjection | false | 11,181 | [
"Apache-2.0"
] | 0 | 0c443ee370cce6227661b802184072174c4e3f64 | https://github.com/AlexanderDokuchaev/mmsegmentation/tree/0c443ee370cce6227661b802184072174c4e3f64 |
ResidualConvUnit | # 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_... | maayan-myheritage/3d-photo-inpainting | ResidualConvUnit | false | 10,590 | [
"MIT"
] | 0 | 6293eecfeb55ceba019655723f6efe31e8ecb177 | https://github.com/maayan-myheritage/3d-photo-inpainting/tree/6293eecfeb55ceba019655723f6efe31e8ecb177 |
ClampExp | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.utils.dat... | pkulwj1994/normalizing-flows | ClampExp | false | 16,255 | [
"MIT"
] | 96 | 326321c4aea4a3f6ab703f82e21277a79cd7d9e4 | https://github.com/pkulwj1994/normalizing-flows/tree/326321c4aea4a3f6ab703f82e21277a79cd7d9e4 |
EncoderLayer | import math
import torch
from torch.nn import functional as F
from torch import nn
def matmul(x, y):
if x.dim() == y.dim():
return torch.matmul(x, y)
if x.dim() == y.dim() - 1:
return torch.matmul(x.unsqueeze(-2), y).squeeze(-2)
return torch.matmul(x, y.unsqueeze(-2)).squeeze(-2)
class F... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | TheShadow29/vognet-pytorch | EncoderLayer | false | 14,505 | [
"MIT"
] | 70 | 238e93c37cf9f03a2fd376a14760bb3d334a113d | https://github.com/TheShadow29/vognet-pytorch/tree/238e93c37cf9f03a2fd376a14760bb3d334a113d |
SelfAttention | import torch
import torch.nn as nn
import torch.nn.functional as F
class SelfAttention(nn.Module):
def __init__(self, hidden_size, attention_size=100, n_attention_heads=1):
super().__init__()
self.hidden_size = hidden_size
self.attention_size = attention_size
self.n_attention_head... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | maltevogl/CVDD-PyTorch | SelfAttention | false | 15,987 | [
"MIT"
] | 48 | 9299894720a8d3d0a329d92c9d2702f43112ff63 | https://github.com/maltevogl/CVDD-PyTorch/tree/9299894720a8d3d0a329d92c9d2702f43112ff63 |
LogSTFTMagnitudeLoss | import torch
import torch.utils.data
import torch.nn.functional as F
class LogSTFTMagnitudeLoss(torch.nn.Module):
"""Log STFT magnitude loss module."""
def __init__(self):
"""Initilize los STFT magnitude loss module."""
super(LogSTFTMagnitudeLoss, self).__init__()
def forward(self, x_mag... | 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... | ChanganVR/hifigan-denoiser | LogSTFTMagnitudeLoss | false | 13,455 | [
"Apache-2.0"
] | 100 | 9bd77c53556e1372b4bbff8dce8b120297cc4e5c | https://github.com/ChanganVR/hifigan-denoiser/tree/9bd77c53556e1372b4bbff8dce8b120297cc4e5c |
StateInitZero | import torch
from torch import nn
from torchvision import models as models
import torch.onnx
import torch.nn
class StateInitZero(nn.Module):
def __init__(self, hidden_size, num_layers=1, batch_first=False):
super(StateInitZero, self).__init__()
self.hidden_size = hidden_size
self.num_laye... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
from torchvision import models as models
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards... | dqawami/openvino_training_extensions | StateInitZero | false | 15,213 | [
"Apache-2.0"
] | 256 | dddda1dfd651eaae2d59cecda84275b1b03bd0ad | https://github.com/dqawami/openvino_training_extensions/tree/dddda1dfd651eaae2d59cecda84275b1b03bd0ad |
NonBlurryLoss | # 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... | GuYuanjie/Deep-Retinex-fusion | NonBlurryLoss | false | 17,348 | [
"MIT"
] | 5 | ffa2a1689fd512c8820fd87cbf665c09bcb142b4 | https://github.com/GuYuanjie/Deep-Retinex-fusion/tree/ffa2a1689fd512c8820fd87cbf665c09bcb142b4 |
Downsample | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | EmanuelNk/semantic-segmentation | Downsample | false | 2,193 | [
"MIT"
] | 0 | 20ff16da49691fb407724909d9c7e84b47e2fee0 | https://github.com/EmanuelNk/semantic-segmentation/tree/20ff16da49691fb407724909d9c7e84b47e2fee0 |
BinaryTreeLeafModule | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.onnx
class BinaryTreeLeafModule(nn.Module):
"""
local input = nn.Identity()()
local c = nn.Linear(self.in_dim, self.mem_dim)(input)
local h
if self.gate_output then
local o = nn.Sigmoid()(nn.Linear(self.in_dim, self.mem_di... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | supunab/Lantern | BinaryTreeLeafModule | false | 16,511 | [
"BSD-3-Clause"
] | 158 | 932a031816617d71c46653f3b2245129a6a8a7c8 | https://github.com/supunab/Lantern/tree/932a031816617d71c46653f3b2245129a6a8a7c8 |
ReduceMinModule | import torch
class ReduceMinModule(torch.nn.Module):
def __init__(self):
super(ReduceMinModule, self).__init__()
def forward(self, x):
return torch.min(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
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | mirecta/nncase | ReduceMinModule | false | 4,179 | [
"Apache-2.0"
] | 0 | d2efa59677a26f4259b3b6a5b6ec05ea16d4e40c | https://github.com/mirecta/nncase/tree/d2efa59677a26f4259b3b6a5b6ec05ea16d4e40c |
ResidualBlock | import torch
import torch.nn as nn
class ResidualBlock(nn.Module):
def __init__(self, channels):
super(ResidualBlock, self).__init__()
self.conv1 = nn.Conv2d(channels, channels, kernel_size=3, padding=1)
self.in1 = nn.InstanceNorm2d(channels)
self.prelu = nn.PReLU()
self.c... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | EKami/EzeeML | ResidualBlock | false | 8,052 | [
"MIT"
] | 35 | 21753a0ede7cc1dc675a2dcd09b6306cea2cad56 | https://github.com/EKami/EzeeML/tree/21753a0ede7cc1dc675a2dcd09b6306cea2cad56 |
Net | import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
self.conv1 = nn.Conv2d(3, 16, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(16, 32, 5)
self.fc1 = nn.Linear(32 * 5 * 5, 120)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | juliowaissman/cifar10-jwv | Net | false | 12,639 | [
"MIT"
] | 0 | a279ccf51f0e8cbacfcc34a9eee381c16ae536fc | https://github.com/juliowaissman/cifar10-jwv/tree/a279ccf51f0e8cbacfcc34a9eee381c16ae536fc |
encoder3 | # 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.... | guswl8033/ARtists | encoder3 | false | 3,570 | [
"Apache-2.0"
] | 0 | d353195872c1ef1a1aa68659a32fb47779a416fc | https://github.com/guswl8033/ARtists/tree/d353195872c1ef1a1aa68659a32fb47779a416fc |
ResBlock | import torch
import torch.nn as nn
def conv3x3(in_planes, out_planes, stride=1):
"""3x3 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=1, bias=False)
def norm(dim):
return nn.GroupNorm(min(32, dim), dim)
class ResBlock(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
from torch._inductor.runtime.... | Teemo341/BDNN | ResBlock | false | 2,880 | [
"Apache-2.0"
] | 0 | d53d4634a7a43d038faa049d7dfd10b3578ae267 | https://github.com/Teemo341/BDNN/tree/d53d4634a7a43d038faa049d7dfd10b3578ae267 |
Coder | # 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.functional
im... | CarlosPena00/pytorchvision | Coder | false | 216 | [
"MIT"
] | 0 | 824b3a5a8940f3ee6b4da5de7a391a88e5aa36a2 | https://github.com/CarlosPena00/pytorchvision/tree/824b3a5a8940f3ee6b4da5de7a391a88e5aa36a2 |
Normalize | import torch
import torch.nn as nn
from torch.nn import functional as F
class Normalize(nn.Module):
"""Performs :math:`L_p` normalization of inputs over specified dimension.
Does:
.. math::
v = \\frac{v}{\\max(\\lVert v \\rVert_p, \\epsilon)}
for each subtensor v over dimension dim of input... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | WillyChen123/CDFNet | Normalize | false | 1,207 | [
"MIT"
] | 0 | 12d6b288aa2a8301683395a75bd44a7be44b7f2a | https://github.com/WillyChen123/CDFNet/tree/12d6b288aa2a8301683395a75bd44a7be44b7f2a |
ConvLayer | import torch
class ConvLayer(torch.nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, stride):
super(ConvLayer, self).__init__()
reflection_padding = kernel_size // 2
self.reflection_pad = torch.nn.ReflectionPad2d(reflection_padding)
self.conv2d = torch.nn.Conv... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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_s... | JEF1056/Reconstruction-Style | ConvLayer | false | 17,447 | [
"MIT"
] | 6 | 3430d9e9f05c6980ae251cf15b619148a2c899d6 | https://github.com/JEF1056/Reconstruction-Style/tree/3430d9e9f05c6980ae251cf15b619148a2c899d6 |
gMLPBlock | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | nima1999nikkhah/SimSiam_gMLP | gMLPBlock | false | 4,103 | [
"MIT"
] | 0 | 9cccd1092c02267951d39ae77c0fe5a91d735903 | https://github.com/nima1999nikkhah/SimSiam_gMLP/tree/9cccd1092c02267951d39ae77c0fe5a91d735903 |
SharpenedCosineSimilarity_ConvImpl | # 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... | enzokro/sharpened_cosine_similarity_torch | SharpenedCosineSimilarity_ConvImpl | false | 12,352 | [
"MIT"
] | 0 | 150c84f5cf81721baf097abdc0d4ac772fb39fc4 | https://github.com/enzokro/sharpened_cosine_similarity_torch/tree/150c84f5cf81721baf097abdc0d4ac772fb39fc4 |
AffineLayer | # 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.utils.data
import torch
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cud... | JeyesHan/DeFRCN_Custom | AffineLayer | false | 9,129 | [
"MIT"
] | 0 | 6a536408a61bb10a5ef84ce6683b6278e6e01f43 | https://github.com/JeyesHan/DeFRCN_Custom/tree/6a536408a61bb10a5ef84ce6683b6278e6e01f43 |
LogitsSelfAttention | # 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.cuda
import torch.distributed
assert_size_str... | KaijuML/dtt-multi-branch | LogitsSelfAttention | false | 18,360 | [
"Apache-2.0"
] | 8 | a49850a95034e58d387b9d48c647cfc2b83c45b5 | https://github.com/KaijuML/dtt-multi-branch/tree/a49850a95034e58d387b9d48c647cfc2b83c45b5 |
CLSHead | # 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.... | MSU-MLSys-Lab/CATE | CLSHead | false | 8,770 | [
"Apache-2.0"
] | 15 | 654c393d7df888d2c3f3b90f9e6752faa061157e | https://github.com/MSU-MLSys-Lab/CATE/tree/654c393d7df888d2c3f3b90f9e6752faa061157e |
LocAndConf | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
from math import sqrt as sqrt
from itertools import produc... | beichen2012/ssd.pytorch | LocAndConf | false | 1,529 | [
"MIT"
] | 0 | 90b68a6903d2bef4c358e295d88b25e6fc6daf54 | https://github.com/beichen2012/ssd.pytorch/tree/90b68a6903d2bef4c358e295d88b25e6fc6daf54 |
SDRLoss | # 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... | PandoraLS/SpeechEnhancement | SDRLoss | false | 17,787 | [
"MIT"
] | 6 | f548eaafbe524a40c8cfd2221f7adf3a444b7a7d | https://github.com/PandoraLS/SpeechEnhancement/tree/f548eaafbe524a40c8cfd2221f7adf3a444b7a7d |
BalancedL1Loss | # 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... | AllenPeng0209/SaccadeNet | BalancedL1Loss | false | 7,636 | [
"Apache-2.0"
] | 30 | 0fce4266cbffc9a2c5f70335efa636da849ce70c | https://github.com/AllenPeng0209/SaccadeNet/tree/0fce4266cbffc9a2c5f70335efa636da849ce70c |
EncoderLayer | # 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.... | sd2001/seqModeling | EncoderLayer | false | 12,969 | [
"MIT"
] | 0 | 393f680de711ea8477e5450633b492298d253368 | https://github.com/sd2001/seqModeling/tree/393f680de711ea8477e5450633b492298d253368 |
GLU | # 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
from torch.nn.utils.rnn import *
import torch.nn.parallel
assert_size_stride = torch._C._dynamo.guards.assert_size_str... | ArunKodnani/StackGAN-v2 | GLU | false | 8,850 | [
"MIT"
] | 0 | e2ef678049b2e18b4a076cecfbe220cf270e59e6 | https://github.com/ArunKodnani/StackGAN-v2/tree/e2ef678049b2e18b4a076cecfbe220cf270e59e6 |
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