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 |
|---|---|---|---|---|---|---|---|---|---|---|
NPairLoss | # 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.triton_helpers import math as tl_math
assert_size_s... | bm2-lab/scPrivacy | NPairLoss | false | 6,431 | [
"MIT"
] | 1 | 444c8f3a5e7b890c299cd823359e5414f73d6205 | https://github.com/bm2-lab/scPrivacy/tree/444c8f3a5e7b890c299cd823359e5414f73d6205 |
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
from torch import optim as optim
import torch.utils.data
import torch.onnx.opera... | Maria-philna/unilm | BiaffineAttention | false | 14,009 | [
"MIT"
] | 5,129 | 5550a335c6d2ae5838b1a90e50cb46f81edcd50f | https://github.com/Maria-philna/unilm/tree/5550a335c6d2ae5838b1a90e50cb46f81edcd50f |
Conv2D | import torch
import torch.nn as nn
import torch.utils.data
class Conv2D(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size=3, dilation_h
=1, dilation_w=1, causal=True, use_wn_bias=True):
super(Conv2D, self).__init__()
self.causal = causal
self.use_wn_bias = use_... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 ... | yhgon/NanoFlow | Conv2D | false | 16,763 | [
"BSD-3-Clause"
] | 62 | 73b24dfd4d607e73d6167897b83e9f61fcaaca3b | https://github.com/yhgon/NanoFlow/tree/73b24dfd4d607e73d6167897b83e9f61fcaaca3b |
ILN | # 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
import torch.uti... | JW9MsjwjnpdRLFw/RMT | ILN | false | 593 | [
"MIT"
] | 0 | a877fd78639a8d4c534d0373b9d0ad023e0fa2dd | https://github.com/JW9MsjwjnpdRLFw/RMT/tree/a877fd78639a8d4c534d0373b9d0ad023e0fa2dd |
ConvGelu | # 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 ... | NVIDIA/Torch-TensorRT | ConvGelu | false | 14,076 | [
"BSD-3-Clause"
] | 430 | 1a22204fecec690bc3c2a318dab4f57b98c57f05 | https://github.com/NVIDIA/Torch-TensorRT/tree/1a22204fecec690bc3c2a318dab4f57b98c57f05 |
SimpleMinModule | import torch
import torch.jit
import torch.onnx
import torch.nn
class SimpleMinModule(torch.nn.Module):
def __init__(self):
super(SimpleMinModule, self).__init__()
def forward(self, a, b):
return torch.min(a + a, b + b)
def get_inputs():
return [torch.rand([4, 4, 4, 4]), 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.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.... | andreas-hommel/glow | SimpleMinModule | false | 3,342 | [
"Apache-2.0"
] | 0 | 2bbbf8188a2a941e85677c83f2146bbd076a262e | https://github.com/andreas-hommel/glow/tree/2bbbf8188a2a941e85677c83f2146bbd076a262e |
LogSumExpPooling1d | # 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
from torch import nn as nn
assert_size_stride = torch._C._dynamo.guards.a... | UKPLab/coling2018-graph-neural-networks-question-answering | LogSumExpPooling1d | false | 14,522 | [
"Apache-2.0"
] | 164 | 389558d6570195debea570834944507de4f21d65 | https://github.com/UKPLab/coling2018-graph-neural-networks-question-answering/tree/389558d6570195debea570834944507de4f21d65 |
PairwiseNetwork | # 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 ... | GrantXie/wikidata-wikifier | PairwiseNetwork | false | 17,307 | [
"MIT"
] | 3 | a65c9b71596e390999af9de7638eb8c8c13c1581 | https://github.com/GrantXie/wikidata-wikifier/tree/a65c9b71596e390999af9de7638eb8c8c13c1581 |
EqualLinear | # 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.autograd import Function
import math
from torch import nn
assert_size... | BinahHu/stylegan2-pytorch | EqualLinear | false | 175 | [
"MIT",
"BSD-2-Clause",
"Apache-2.0"
] | 0 | 9975707ffd93872fce02f7e3654eb588a09e23e4 | https://github.com/BinahHu/stylegan2-pytorch/tree/9975707ffd93872fce02f7e3654eb588a09e23e4 |
WeightedBCEFocalLoss | import torch
import torch.utils.data
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
class WeightedBCEFocalLoss(nn.Module):
"""Weighted binary focal loss with logits.
"""
def __init__(self, gamma=2.0, alpha=0.25, eps=0.0):
super().__init__()
self.eps = eps
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | Atharva-Peshkar/pytorch_connectomics | WeightedBCEFocalLoss | false | 13,332 | [
"MIT"
] | 99 | 8eccd9640a9a454d4df095a3529a030e58f882f5 | https://github.com/Atharva-Peshkar/pytorch_connectomics/tree/8eccd9640a9a454d4df095a3529a030e58f882f5 |
TorchMulScalar | import torch
import torch.nn as nn
import torch.nn.parallel
from torch.nn.quantized.modules import FloatFunctional
class TorchMulScalar(nn.Module):
"""Wrapper around torch.mul so that all ops can be found at build
y must be a scalar, needed for quantization
"""
def __init__(self):
super()... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
from torch.nn.quantized.modules import FloatFunctional
assert_size_stride = torch._C._dynamo.... | a1004123217/pytorch-mobile | TorchMulScalar | false | 1,326 | [
"MIT"
] | 0 | 97974af3259a2073efbc334d57841efbd3eaadfb | https://github.com/a1004123217/pytorch-mobile/tree/97974af3259a2073efbc334d57841efbd3eaadfb |
EQ | import torch
class EQ(torch.nn.Module):
def __init__(self):
super(EQ, self).__init__()
def forward(self, x, y):
return x == y
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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | ahangchen/torch2trt | EQ | false | 6,098 | [
"MIT"
] | 1 | 53c663f0e0570ef7ffd6771354ae3478f63bd328 | https://github.com/ahangchen/torch2trt/tree/53c663f0e0570ef7ffd6771354ae3478f63bd328 |
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.... | CS475-NLP/cs475-nlp-project | SelfAttention | false | 2,071 | [
"MIT"
] | 0 | d73ec7d4b08abd3a5ba6445b99705fe8716a0151 | https://github.com/CS475-NLP/cs475-nlp-project/tree/d73ec7d4b08abd3a5ba6445b99705fe8716a0151 |
MultiHeadDense | # 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... | afperezm/DeepGlobe-Road-Extraction-Challenge | MultiHeadDense | false | 1,380 | [
"MIT"
] | 0 | d3e0a8123d64baa3975663ece053edbc4bbdc4e6 | https://github.com/afperezm/DeepGlobe-Road-Extraction-Challenge/tree/d3e0a8123d64baa3975663ece053edbc4bbdc4e6 |
Deconv2d | # 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... | RQuispeC/pytorch-ACSCP | Deconv2d | false | 8,685 | [
"MIT"
] | 25 | c83f08632012c2245250ff9c5140814461db575c | https://github.com/RQuispeC/pytorch-ACSCP/tree/c83f08632012c2245250ff9c5140814461db575c |
PositionEncoder | # 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 numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dyna... | benedictleedm/sgnlp | PositionEncoder | false | 1,531 | [
"MIT"
] | 0 | 03f0fda8c517d9ca4baf737ce4c46b2495bbd3ba | https://github.com/benedictleedm/sgnlp/tree/03f0fda8c517d9ca4baf737ce4c46b2495bbd3ba |
BartClassificationHead | import torch
import torch.utils.data
from torch import nn
class BartClassificationHead(nn.Module):
"""Head for sentence-level classification tasks."""
def __init__(self, input_dim, inner_dim, num_classes, pooler_dropout):
super().__init__()
self.dense = nn.Linear(input_dim, inner_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
import torch.utils.... | awslabs/gap-text2sql | BartClassificationHead | false | 14,930 | [
"Apache-2.0"
] | 75 | 83af3f08a6c108f7cbacb8125e2a7ec9255c81b0 | https://github.com/awslabs/gap-text2sql/tree/83af3f08a6c108f7cbacb8125e2a7ec9255c81b0 |
RecurrentNeuralRegressor | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.optim import Adam
from torch.utils.data import BatchSampler
from torch.utils.data import SubsetRandomSampler
class RecurrentNeuralRegressor(nn.Module):
def __init__(self, sizes, prior, nonlin='relu'):
super(RecurrentNeuralRegre... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | TheCamusean/sds | RecurrentNeuralRegressor | false | 9,535 | [
"MIT"
] | 0 | 65e1736eb27dcd8829f5bff452fc09ccab3e0ae2 | https://github.com/TheCamusean/sds/tree/65e1736eb27dcd8829f5bff452fc09ccab3e0ae2 |
WidthXHeightXFeatureLinear | # 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... | dattientran/attorch | WidthXHeightXFeatureLinear | false | 12,398 | [
"MIT"
] | 0 | 469b225846c6d8a7d833ebac19d040c7a407a0ff | https://github.com/dattientran/attorch/tree/469b225846c6d8a7d833ebac19d040c7a407a0ff |
CNN_attention | import torch
import torch.nn as nn
class CNN_attention(nn.Module):
def __init__(self, channel_size):
super(CNN_attention, self).__init__()
self.attention = nn.Conv2d(channel_size, channel_size, kernel_size=1)
self.softmax = nn.Softmax(dim=-1)
self._initialize_weights()
def fo... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Jiangtong-Li/ZHSIR | CNN_attention | false | 17,500 | [
"Apache-2.0"
] | 8 | fd2c0a7e79f22cbf565ccd5e13342f1b317ac9b7 | https://github.com/Jiangtong-Li/ZHSIR/tree/fd2c0a7e79f22cbf565ccd5e13342f1b317ac9b7 |
FaceMask | # 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 ... | VrajeshPatel20/FaceMask-Detection | FaceMask | false | 11,958 | [
"MIT"
] | 0 | 1527f47a94a1b40b470eab633cf4a655c9a3e44e | https://github.com/VrajeshPatel20/FaceMask-Detection/tree/1527f47a94a1b40b470eab633cf4a655c9a3e44e |
GeneralizedDiceLoss | import collections
import torch
import warnings
from typing import Optional
from typing import Union
from typing import Any
from typing import Callable
from typing import Tuple
import torch.nn
from torch.nn.modules.loss import _Loss
from enum import Enum
import collections.abc
def issequenceiterable(obj: 'Any') ->boo... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import collections
from typi... | LucasFidon/MONAI | GeneralizedDiceLoss | false | 2,619 | [
"Apache-2.0"
] | 0 | a7ef9d567775dd7a222f93bab08191c0e3532c92 | https://github.com/LucasFidon/MONAI/tree/a7ef9d567775dd7a222f93bab08191c0e3532c92 |
double_decoder_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_... | mhakyash/UNet-MNIST-denoising | double_decoder_conv | false | 10,574 | [
"MIT"
] | 0 | 0e3c20cbb3f34af575e33209425ae4d7cb0bcd82 | https://github.com/mhakyash/UNet-MNIST-denoising/tree/0e3c20cbb3f34af575e33209425ae4d7cb0bcd82 |
Tanh | import math
import torch
class Tanh(torch.nn.Tanh):
"""
Class that extends ``torch.nn.Tanh`` additionally computing the log diagonal
blocks of the Jacobian.
"""
def forward(self, inputs, grad: 'torch.Tensor'=None):
"""
Parameters
----------
inputs : ``torch.Tensor`... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
assert_size_stride = torch._C._dynamo.guards.assert_size_strid... | ralphc1212/BNAF | Tanh | false | 4,167 | [
"MIT"
] | 0 | b6e331aa96cdd4496b6eed6c6ce65512a99f4149 | https://github.com/ralphc1212/BNAF/tree/b6e331aa96cdd4496b6eed6c6ce65512a99f4149 |
MaxElementwise | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | bunderhi/torch2trt | MaxElementwise | false | 1,588 | [
"MIT"
] | 0 | fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d | https://github.com/bunderhi/torch2trt/tree/fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d |
DilatedResidualLayer | # 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_... | tonnidas/sign-segmentation | DilatedResidualLayer | false | 10,904 | [
"MIT"
] | 0 | 5332ccd1dbef311daa594ed6faa45cbd618a76a0 | https://github.com/tonnidas/sign-segmentation/tree/5332ccd1dbef311daa594ed6faa45cbd618a76a0 |
InstanceNorm2dPlus | import torch
import torch.nn as nn
class InstanceNorm2dPlus(nn.Module):
def __init__(self, num_features, bias=True):
super().__init__()
self.num_features = num_features
self.bias = bias
self.instance_norm = nn.InstanceNorm2d(num_features, affine=False,
track_running_st... | 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_... | DeepTitan/PNDM | InstanceNorm2dPlus | false | 13,584 | [
"Apache-2.0"
] | 61 | 4037a4f40011c9a0d47b92303e64d47fcc7ed56a | https://github.com/DeepTitan/PNDM/tree/4037a4f40011c9a0d47b92303e64d47fcc7ed56a |
BipolarSigmoid | # 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... | fmhoward/pysurvival | BipolarSigmoid | false | 12,373 | [
"Apache-2.0"
] | 0 | 3fea55f09477e9f0844845e09d6ea60434436e2e | https://github.com/fmhoward/pysurvival/tree/3fea55f09477e9f0844845e09d6ea60434436e2e |
Decoder | import torch
import torch.utils.data
from torch import nn
from torch.nn import functional
class Decoder(nn.Module):
def __init__(self, z_dim, hidden_dim, output_dim):
"""
Args:
z_dim: A integer indicating the latent size.
hidden_dim: A integer indicating the size o... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | MaurizioFD/recsys-challenge-2020-twitter | Decoder | false | 8,537 | [
"Apache-2.0"
] | 44 | 95dc024fb4f8777aa62e1304536daece640428de | https://github.com/MaurizioFD/recsys-challenge-2020-twitter/tree/95dc024fb4f8777aa62e1304536daece640428de |
Critic | import torch
import torch.nn as nn
import torch.nn.functional as F
class Critic(nn.Module):
def __init__(self, state_dim, action_dim):
super(Critic, self).__init__()
self.l1 = nn.Linear(state_dim + action_dim, 400)
self.l2 = nn.Linear(400, 300)
self.l3 = nn.Linear(300, 1)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | DanielTakeshi/DCUR | Critic | false | 352 | [
"MIT"
] | 0 | 1cdb00e7e68060ad3bba9a497106c327f6b5a663 | https://github.com/DanielTakeshi/DCUR/tree/1cdb00e7e68060ad3bba9a497106c327f6b5a663 |
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 torch.nn.functional as... | FranckNdame/drlkit | Critic | false | 8,118 | [
"MIT"
] | 33 | 698f3c182036cc5eed68f2a05b53a3e3670146bf | https://github.com/FranckNdame/drlkit/tree/698f3c182036cc5eed68f2a05b53a3e3670146bf |
CAModel | # 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_... | PWhiddy/Growing-Neural-Cellular-Automata-Pytorch | CAModel | false | 14,148 | [
"Apache-2.0"
] | 47 | 73a68e9a9cd0c3c14e590238f098937dc0f5c888 | https://github.com/PWhiddy/Growing-Neural-Cellular-Automata-Pytorch/tree/73a68e9a9cd0c3c14e590238f098937dc0f5c888 |
DeepSet | import torch
import torch.nn as nn
class DeepSet(nn.Module):
"""Aggregate object-level embeddings with a mean reduction.
This module evaluates each object individually (using a object level
embedding) and then aggregates the embeddings with a mean reduction.
Parameters
----------
n_features ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | kiudee/cs-ranking | DeepSet | false | 15,845 | [
"Apache-2.0"
] | 65 | 47cf648fa286c37b9214bbad1926004d4d7d9796 | https://github.com/kiudee/cs-ranking/tree/47cf648fa286c37b9214bbad1926004d4d7d9796 |
Resize | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torc... | rlmwang/torch-tools | Resize | false | 10,794 | [
"MIT"
] | 0 | 822132534d73414f26045bad38a0a345661b057f | https://github.com/rlmwang/torch-tools/tree/822132534d73414f26045bad38a0a345661b057f |
ResNetV2 | import torch
from torch import nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
import torch.nn
from torch.nn import functional as F
from collections import OrderedDict
def conv1x1(in_planes, out_planes, stride=1):
"""1x1 convolution"""
return nn.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.... | bethgelab/robustness | ResNetV2 | false | 16,458 | [
"Apache-2.0"
] | 67 | aa0a6798fe3973bae5f47561721b59b39f126ab7 | https://github.com/bethgelab/robustness/tree/aa0a6798fe3973bae5f47561721b59b39f126ab7 |
SpeakNet | # 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.... | aaronmueller/discourse-hw3 | SpeakNet | false | 1,350 | [
"MIT"
] | 0 | 93313a2ce83fde9480914384be52ec9160e967af | https://github.com/aaronmueller/discourse-hw3/tree/93313a2ce83fde9480914384be52ec9160e967af |
SimpleSoftmaxModel | import torch
import torch.nn.functional as F
import torch.jit
import torch.onnx
import torch.nn
class SimpleSoftmaxModel(torch.nn.Module):
def __init__(self, dimension):
super(SimpleSoftmaxModel, self).__init__()
self.dimension = dimension
def forward(self, tensor):
return F.softmax(... | 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.jit
impor... | briancoutinho/glow | SimpleSoftmaxModel | false | 12,591 | [
"Apache-2.0"
] | 0 | 4c919d60b3c33296c4109aec8020a1733c98f5b5 | https://github.com/briancoutinho/glow/tree/4c919d60b3c33296c4109aec8020a1733c98f5b5 |
FeatureNorm | # 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 as nn
assert_size_stride = torch._C._dynamo.guards.assert_... | Luckygyana/Fabric-Defect-Detection | FeatureNorm | false | 787 | [
"Apache-2.0"
] | 0 | 83cd8936ada6ef097993650c6db6286928666036 | https://github.com/Luckygyana/Fabric-Defect-Detection/tree/83cd8936ada6ef097993650c6db6286928666036 |
NeuralNetwork | import torch
import torch.nn as nn
class NeuralNetwork(nn.Module):
def __init__(self, input_dim, hidden_dim, output_dim, action_bound):
super(NeuralNetwork, self).__init__()
self.input_layer = nn.Linear(input_dim, hidden_dim)
self.hidden_layer = nn.Linear(hidden_dim, hidden_dim)
s... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | keyshor/homework | NeuralNetwork | false | 12,679 | [
"MIT"
] | 0 | 687f9edf73bbac8fc492dfd82d634c19a38f5aab | https://github.com/keyshor/homework/tree/687f9edf73bbac8fc492dfd82d634c19a38f5aab |
DiceLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
emp... | LovreAB17/Eff-UNet | DiceLoss | false | 17,601 | [
"MIT"
] | 5 | b1e76a68d96e55324b6859c64ad2367653143e5e | https://github.com/LovreAB17/Eff-UNet/tree/b1e76a68d96e55324b6859c64ad2367653143e5e |
InteractiveKLLoss | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.parallel
import torch.optim
import torch.utils.data
from typing import *
class InteractiveKLLoss(nn.Module):
def __init__(self, temperature):
super().__init__()
self.temperature = temperature
self.kl_loss =... | 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... | Johnsonms/NNI_master | InteractiveKLLoss | false | 11,587 | [
"MIT"
] | 0 | e5e5c7aed89cf3189cffe1056464833c15eb54ff | https://github.com/Johnsonms/NNI_master/tree/e5e5c7aed89cf3189cffe1056464833c15eb54ff |
BilinearUpsampler | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch as th
import torch.utils.data
assert_size_stride = torch._C._dynamo... | IlyaBizyaev/ttools | BilinearUpsampler | false | 8,312 | [
"MIT"
] | 11 | b1435b19f397ce1baff9daed3cb287e52a029fdb | https://github.com/IlyaBizyaev/ttools/tree/b1435b19f397ce1baff9daed3cb287e52a029fdb |
BinaryCrossEntropyLoss | import torch
import torch.nn as nn
class BinaryCrossEntropyLoss(nn.Module):
"""Cross entropy loss with label smoothing regularizer.
Reference:
Szegedy et al. Rethinking the Inception Architecture for Computer Vision. CVPR 2016.
With label smoothing, the label :math:`y` for a class is computed by... | 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... | RndmVariableQ/deep-person-reid | BinaryCrossEntropyLoss | false | 11,858 | [
"MIT"
] | 0 | 9ab8343b2fc2ac130aeca5bc2bd1ae808e9ce1b9 | https://github.com/RndmVariableQ/deep-person-reid/tree/9ab8343b2fc2ac130aeca5bc2bd1ae808e9ce1b9 |
MulticlassDiceLoss | # 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... | LanXiangExcavator/python-classifier-2021 | MulticlassDiceLoss | false | 11,630 | [
"BSD-2-Clause"
] | 0 | 851079e76db8e5070132d1120dba941967e1245b | https://github.com/LanXiangExcavator/python-classifier-2021/tree/851079e76db8e5070132d1120dba941967e1245b |
TransformerEncoderLayer | import torch
import torch.nn.functional as F
import torch.nn as nn
import torch.utils.data
class Linear(nn.Linear):
def __init__(self, in_dim, out_dim, bias=True, w_init_gain='linear'):
super(Linear, self).__init__(in_dim, out_dim, bias)
nn.init.xavier_uniform_(self.weight, gain=nn.init.calculate... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Deepest-Project/AlignTTS | TransformerEncoderLayer | false | 13,597 | [
"MIT"
] | 70 | ed9c29d845f65ceb44c87f293b2919b9bbc6a6de | https://github.com/Deepest-Project/AlignTTS/tree/ed9c29d845f65ceb44c87f293b2919b9bbc6a6de |
PcamPool | import torch
from torch import nn
class PcamPool(nn.Module):
def __init__(self):
super(PcamPool, self).__init__()
def forward(self, feat_map, logit_map):
assert logit_map is not None
prob_map = torch.sigmoid(logit_map)
weight_map = prob_map / prob_map.sum(dim=2, keepdim=True)... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | iampartho/EEE426 | PcamPool | false | 3,644 | [
"Apache-2.0"
] | 0 | a706660c0efcd4adea44d54c57a34bcaa4439ec1 | https://github.com/iampartho/EEE426/tree/a706660c0efcd4adea44d54c57a34bcaa4439ec1 |
US | import torch
from torch import nn as nn
from torch.nn import functional as F
from torch.nn import init as init
from torch.utils import data as data
import torch.onnx
class US(nn.Module):
"""Up-sampling block
"""
def __init__(self, num_feat, scale):
super(US, self).__init__()
self.scale = ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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 as nn
from torch.nn import init as init
from torch.utils im... | aesrgan/A-ESRGAN | US | false | 14,751 | [
"BSD-3-Clause"
] | 58 | e1a71deb4a47e332cad6b3d6bbbbb21a56bdd9c6 | https://github.com/aesrgan/A-ESRGAN/tree/e1a71deb4a47e332cad6b3d6bbbbb21a56bdd9c6 |
convTranspose23DUnit | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import numpy as np
from torch import nn
import torch.utils.data
import torch.nn.... | ForrestPi/Unsupervised-Defect-Segmentation | convTranspose23DUnit | false | 8,221 | [
"MIT"
] | 17 | e366ac7c757bb1b45f38ebbc502dfee7ccb72398 | https://github.com/ForrestPi/Unsupervised-Defect-Segmentation/tree/e366ac7c757bb1b45f38ebbc502dfee7ccb72398 |
ConvEncoder | import torch
import torch.nn as nn
import torch.autograd
def pytorch_activation(name='relu'):
if name == 'tanh':
return nn.Tanh()
if name == 'identity':
return nn.Identity()
if name == 'hardtanh':
return nn.Hardtanh()
if name == 'prelu':
return nn.PReLU()
if name ==... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | amyhemmeter/baseline | ConvEncoder | false | 3,093 | [
"Apache-2.0"
] | 0 | 101a393398570747d14a32eb3af72664e2774c8b | https://github.com/amyhemmeter/baseline/tree/101a393398570747d14a32eb3af72664e2774c8b |
MainClassifier | # 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... | janhenriklambrechts/Task-Oriented-Feature-Distillation | MainClassifier | false | 12,602 | [
"MIT"
] | 0 | 87ab75677b02441bce045e76e96afb078e9df2ea | https://github.com/janhenriklambrechts/Task-Oriented-Feature-Distillation/tree/87ab75677b02441bce045e76e96afb078e9df2ea |
MultiRelu | import torch
from torch import Tensor
from typing import Tuple
import torch.nn as nn
from typing import no_type_check
class MultiRelu(nn.Module):
def __init__(self, inplace: 'bool'=False) ->None:
super().__init__()
self.relu1 = nn.ReLU(inplace=inplace)
self.relu2 = nn.ReLU(inplace=inplace... | 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... | YNNEKUW/captum | MultiRelu | false | 11,993 | [
"BSD-3-Clause"
] | 0 | c8b5357b21f2ddf440e5f0ce25635977292aa5d1 | https://github.com/YNNEKUW/captum/tree/c8b5357b21f2ddf440e5f0ce25635977292aa5d1 |
EquivariantLayer | import math
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
import torch.nn.functional as F
from torch.nn.modules.batchnorm import _BatchNorm
class MyBatchNorm1d(_BatchNorm):
"""Applies Batch Normalization over a 2d or 3d input that is seen as a
mini-batch.
.. math::
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import math
import torch.nn a... | doudoulaile/RL-GAN-Net | EquivariantLayer | false | 15,224 | [
"MIT"
] | 112 | 9c221223d1878bc24f0f39ad34928c1bb2974ae3 | https://github.com/doudoulaile/RL-GAN-Net/tree/9c221223d1878bc24f0f39ad34928c1bb2974ae3 |
Attn | # 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.... | AuCson/SEDST | Attn | false | 7,739 | [
"MIT"
] | 23 | 1c1691e2abc50eb2120ed49c874090f6c4f741d3 | https://github.com/AuCson/SEDST/tree/1c1691e2abc50eb2120ed49c874090f6c4f741d3 |
MatchingTensor | import torch
import torch.nn as nn
import torch.nn.functional as F
class MatchingTensor(nn.Module):
"""
Module that captures the basic interactions between two tensors.
:param matching_dims: Word dimension of two interaction texts.
:param channels: Number of word interaction tensor channels.
:par... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Ambitioner-c/MatchZoo-py | MatchingTensor | false | 13,273 | [
"Apache-2.0"
] | 468 | bb088edce8e01c2c2326ca1a8ac647f0d23f088d | https://github.com/Ambitioner-c/MatchZoo-py/tree/bb088edce8e01c2c2326ca1a8ac647f0d23f088d |
NAC | # 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... | Caerisse/deep_focus | NAC | false | 188 | [
"MIT"
] | 0 | a6549e0b222a01569b224fb651666ef5dbb5072f | https://github.com/Caerisse/deep_focus/tree/a6549e0b222a01569b224fb651666ef5dbb5072f |
CeCriterion | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch.nn.modules.... | kiminh/mt-dnn | CeCriterion | false | 7,025 | [
"MIT"
] | 1 | 133884b380244dbe74acc4d7507e551b2c5035b3 | https://github.com/kiminh/mt-dnn/tree/133884b380244dbe74acc4d7507e551b2c5035b3 |
Sum | import torch
import torch.nn as nn
class Sum(nn.Module):
def __init__(self, n, weight=False):
super(Sum, self).__init__()
self.weight = weight
self.iter = range(n - 1)
if weight:
self.w = nn.Parameter(-torch.arange(1.0, n) / 2, requires_grad=True
)
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | Alex-Beh/hand_tracking | Sum | false | 11,150 | [
"Apache-2.0"
] | 0 | 40ac39e10ed5815d9400d6a87149015ad6ab9686 | https://github.com/Alex-Beh/hand_tracking/tree/40ac39e10ed5815d9400d6a87149015ad6ab9686 |
LinearI_Neg | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.distributions
import torch.utils.data
class LinearI_Neg(nn.Linear):
def forward(self, x):
return F.linear(x, -self.weight.exp(), self.bias)
def ibp_forward(self, l, u):
weight = -self.weight.exp()
if 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.triton_helpers import math as tl_math
import torch.... | AlexMeinke/Provable-OOD-Detection | LinearI_Neg | false | 7,695 | [
"MIT"
] | 21 | 9a132aec994ff718c96b81885736ab866df60d87 | https://github.com/AlexMeinke/Provable-OOD-Detection/tree/9a132aec994ff718c96b81885736ab866df60d87 |
NonLocalBlock2D | # 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.... | zhouhuanxiang/EDSR-PyTorch | NonLocalBlock2D | false | 13,181 | [
"MIT"
] | 0 | ca2f0eea49476a0acde59dd76aa4ae257389d98c | https://github.com/zhouhuanxiang/EDSR-PyTorch/tree/ca2f0eea49476a0acde59dd76aa4ae257389d98c |
LogicProjection | import torch
from torch import nn
import torch.nn.functional as F
class LogicProjection(nn.Module):
def __init__(self, entity_dim, relation_dim, hidden_dim, num_layers,
bounded):
super(LogicProjection, self).__init__()
self.entity_dim = entity_dim
self.relation_dim = relation_dim
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
assert_s... | HKUST-KnowComp/EFO-1-QA-benchmark | LogicProjection | false | 17,366 | [
"MIT"
] | 9 | 600fb02c76ab631f93ee362ceb789216ec085790 | https://github.com/HKUST-KnowComp/EFO-1-QA-benchmark/tree/600fb02c76ab631f93ee362ceb789216ec085790 |
GlobalPerceptron | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.fft
class GlobalPerceptron(nn.Module):
def __init__(self, input_channels, internal_neurons):
super(GlobalPerceptron, self).__init__()
self.fc1 = nn.Conv2d(in_channels=input_channels, out_channels=
internal... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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 ... | liuruiyang98/Jittor-MLP | GlobalPerceptron | false | 15,934 | [
"MIT"
] | 49 | b86656b65cf5f18ba9eb760d1f7565ed95e7e96e | https://github.com/liuruiyang98/Jittor-MLP/tree/b86656b65cf5f18ba9eb760d1f7565ed95e7e96e |
SAN | # 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.... | yuriy-os/russian-reviews-bert-e2e-absa | SAN | false | 16,784 | [
"Apache-2.0"
] | 293 | 369a6179353e3bf28643e8e9347b624078e38bf4 | https://github.com/yuriy-os/russian-reviews-bert-e2e-absa/tree/369a6179353e3bf28643e8e9347b624078e38bf4 |
GymDqn | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch.nn import function... | xssstory/Rainbow | GymDqn | false | 4,608 | [
"MIT"
] | 0 | 919a48f5fd67b6860906188b02c1b4dbe729033e | https://github.com/xssstory/Rainbow/tree/919a48f5fd67b6860906188b02c1b4dbe729033e |
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
from torchvision.transforms i... | ljjyxz123/CenterMask | SEModule | false | 7,136 | [
"BSD-2-Clause"
] | 1 | 443eebde30e209eeb3b953f7ef35d3f7f14aaca5 | https://github.com/ljjyxz123/CenterMask/tree/443eebde30e209eeb3b953f7ef35d3f7f14aaca5 |
ResizeConv2d | # 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.optim
import torch.utils.da... | AhmadQasim/MedAL | ResizeConv2d | false | 7,635 | [
"MIT"
] | 13 | 0ad6064d0d07f23722034b866ba86d93b62517f4 | https://github.com/AhmadQasim/MedAL/tree/0ad6064d0d07f23722034b866ba86d93b62517f4 |
QNetworkSmall | import torch
import torch.nn as nn
import torch.nn.functional as F
class QNetworkSmall(nn.Module):
def __init__(self, state_size, action_size, seed):
"""
Build a fully connected neural network
state_size (int): State dimension
action_size (int): Action dimension
seed (int... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | Yigit-Arisoy/deep-rts | QNetworkSmall | false | 14,690 | [
"MIT"
] | 144 | a5ed2c29b76789830df9f7075480c7229ccf0f4d | https://github.com/Yigit-Arisoy/deep-rts/tree/a5ed2c29b76789830df9f7075480c7229ccf0f4d |
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._inductor.runtime.... | jxgu1016/MNIST_with_centerloss.pytorch | Net | false | 15,812 | [
"MIT"
] | 346 | 4e94cc77fe94056a7f1f081fcaf0325781ba0224 | https://github.com/jxgu1016/MNIST_with_centerloss.pytorch/tree/4e94cc77fe94056a7f1f081fcaf0325781ba0224 |
_ShiftedSoftPlus | import math
import torch
import torch.jit
import torch.nn.functional
import torch.nn
class _ShiftedSoftPlus(torch.nn.Module):
"""
Shifted softplus as defined in SchNet, NeurIPS 2017.
:param beta: value for the a more general softplus, default = 1
:param threshold: values above are linear function, de... | 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
import math
import torch.jit
import torch.nn.functional
import... | leoil/nequip | _ShiftedSoftPlus | false | 7,077 | [
"MIT"
] | 1 | 83b888797025c94b9963a508bc213a7c98da5bcb | https://github.com/leoil/nequip/tree/83b888797025c94b9963a508bc213a7c98da5bcb |
FixupBasicBlock | # 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_... | IlanPrice/DCTpS | FixupBasicBlock | false | 8,321 | [
"MIT"
] | 12 | e3219ac132959f484724e0d0bd48a0cb8af3d0fa | https://github.com/IlanPrice/DCTpS/tree/e3219ac132959f484724e0d0bd48a0cb8af3d0fa |
OscBase | import torch
import numpy as np
import torch.nn as nn
def init(module, weight_init, bias_init, gain=1):
weight_init(module.weight.data, gain=gain)
bias_init(module.bias.data)
return module
class NNBase(nn.Module):
def __init__(self, recurrent, recurrent_input_size, hidden_size):
super(NNBas... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | aupilot/a2c | OscBase | false | 12,142 | [
"MIT"
] | 0 | cd7e8892f91ce0c8b4c221eb6be31ebbee81d663 | https://github.com/aupilot/a2c/tree/cd7e8892f91ce0c8b4c221eb6be31ebbee81d663 |
Generator | # 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... | Anas-Alamri/vegans | Generator | false | 4,837 | [
"MIT"
] | 1 | 2e8513c9cbebf18d0125cebdc7d924dd6345883a | https://github.com/Anas-Alamri/vegans/tree/2e8513c9cbebf18d0125cebdc7d924dd6345883a |
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
import torch.distributed
import torch
import torch.nn as nn
assert_size_stride =... | JackInTaiwan/BertSum | Classifier | false | 11,533 | [
"Apache-2.0"
] | 0 | 5b6f372b13358473d17c49bfc45f1e15c80f9fce | https://github.com/JackInTaiwan/BertSum/tree/5b6f372b13358473d17c49bfc45f1e15c80f9fce |
Scaler | # 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 abc import ABC
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_stri... | kernc/hummingbird | Scaler | false | 12,658 | [
"MIT"
] | 0 | 8c9d5b1f19054d521b22ad7fcffa8ee10e405ac3 | https://github.com/kernc/hummingbird/tree/8c9d5b1f19054d521b22ad7fcffa8ee10e405ac3 |
Debayer2x2 | # 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
import torch.... | tasptz/pytorch-debayer | Debayer2x2 | false | 13,022 | [
"MIT"
] | 0 | ec35f34a57c045eb2319f4ef87f371d95f7394c3 | https://github.com/tasptz/pytorch-debayer/tree/ec35f34a57c045eb2319f4ef87f371d95f7394c3 |
Correlation | # 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
import torch.optim
assert_size_stride = torch._C._d... | RylanSchaeffer/RepDistiller | Correlation | false | 5,806 | [
"BSD-2-Clause"
] | 1 | 3612d9d8f6f913527c7aaec7e5ea557e72ed7c5e | https://github.com/RylanSchaeffer/RepDistiller/tree/3612d9d8f6f913527c7aaec7e5ea557e72ed7c5e |
DDM_Decoder | # 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
... | MLforHealth/state_representations_for_RLinHealth | DDM_Decoder | false | 8,515 | [
"MIT"
] | 24 | aa8dbb7d56caa95bf4380e3e745e134996291b66 | https://github.com/MLforHealth/state_representations_for_RLinHealth/tree/aa8dbb7d56caa95bf4380e3e745e134996291b66 |
ResBlock2d | # 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... | ldlasso2/hologan-pytorch | ResBlock2d | false | 15,893 | [
"BSD-3-Clause"
] | 61 | baec67d3673cc68e51434516d19465f3d6dd0a1b | https://github.com/ldlasso2/hologan-pytorch/tree/baec67d3673cc68e51434516d19465f3d6dd0a1b |
NormedLinear | # 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.... | EricZsy/BalancedKnowledgeDistillation | NormedLinear | false | 8,072 | [
"MIT"
] | 22 | 88a2de840a3fc6eb2ee881c729f293b8e78714aa | https://github.com/EricZsy/BalancedKnowledgeDistillation/tree/88a2de840a3fc6eb2ee881c729f293b8e78714aa |
LayerNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | Hritikbansal/RNNs_SVA_OOD | LayerNorm | false | 17,385 | [
"MIT"
] | 4 | a1c73955342d9d35c49da5fcb7b315e37b0f75d1 | https://github.com/Hritikbansal/RNNs_SVA_OOD/tree/a1c73955342d9d35c49da5fcb7b315e37b0f75d1 |
Generator | # 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... | odb9402/MAT | Generator | false | 4,107 | [
"MIT"
] | 0 | 95d8083170da2c8ce1f5898b3a556bcf54eac8cc | https://github.com/odb9402/MAT/tree/95d8083170da2c8ce1f5898b3a556bcf54eac8cc |
NetDropout | import torch
from torch import nn
from torch.nn import functional as F
class NetDropout(nn.Module):
def __init__(self, nclasses, img, nchans1=10, dropout_prob=0.4):
super().__init__()
nchannels, _nrows, _ncols = img.shape
self.conv1 = nn.Conv2d(nchannels, nchans1, kernel_size=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.... | arpitvaghela/probml-notebooks | NetDropout | false | 14,899 | [
"MIT"
] | 166 | 32ecb309dd474b989fd1c6ce4ad6dab7a25bbead | https://github.com/arpitvaghela/probml-notebooks/tree/32ecb309dd474b989fd1c6ce4ad6dab7a25bbead |
ClassifierEnd | import torch
import torch.nn as nn
class ClassifierEnd(nn.Module):
def __init__(self, num_classes: 'int'):
super(ClassifierEnd, self).__init__()
self.num_classes = num_classes
self.fc_net1 = nn.Conv2d(21, self.num_classes, kernel_size=1, stride=1)
self.fc_net2 = nn.Conv2d(self.num... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | EadCat/Road-Extraction | ClassifierEnd | false | 17,246 | [
"MIT"
] | 4 | 9d4831b6c3a5ef07676cbe1c79b03045fda427ea | https://github.com/EadCat/Road-Extraction/tree/9d4831b6c3a5ef07676cbe1c79b03045fda427ea |
adaILN | import torch
import torch.nn as nn
from torch.nn.parameter import Parameter
class adaILN(nn.Module):
def __init__(self, num_features, eps=1e-05, momentum=0.9,
using_moving_average=True, using_bn=False):
super(adaILN, self).__init__()
self.eps = eps
self.momentum = momentum
... | 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... | Elvinky/IEGAN | adaILN | false | 8,057 | [
"MIT"
] | 29 | db072e38fb022b367da24d3210c59136fbad224e | https://github.com/Elvinky/IEGAN/tree/db072e38fb022b367da24d3210c59136fbad224e |
RankCrossEntropyLoss | # 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
... | ChrisRBXiong/MatchZoo-py | RankCrossEntropyLoss | false | 13,474 | [
"Apache-2.0"
] | 468 | 8883d0933a62610d71fec0215dce643630e03b1c | https://github.com/ChrisRBXiong/MatchZoo-py/tree/8883d0933a62610d71fec0215dce643630e03b1c |
TripletMarginCosineLoss | # 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
from torch.nn import Module
... | ZhangShiyue/oposum | TripletMarginCosineLoss | false | 14,724 | [
"Apache-2.0"
] | 97 | 5aefea20c5c0846b4cf09a5b4643ffb0b2ff39d8 | https://github.com/ZhangShiyue/oposum/tree/5aefea20c5c0846b4cf09a5b4643ffb0b2ff39d8 |
DDPGConvBody | # 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 ... | Rajawat23/DeepRL | DDPGConvBody | false | 11,832 | [
"MIT"
] | 0 | 9f77dfbc593f9c9055254c781f97983b9630dad2 | https://github.com/Rajawat23/DeepRL/tree/9f77dfbc593f9c9055254c781f97983b9630dad2 |
Conv2d | # 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_... | Bazinga0426/Crowd-Counting-for-FYP | Conv2d | false | 8,845 | [
"MIT"
] | 0 | a5ef9de5d7b69bd76980aa4312700601cf7d9adb | https://github.com/Bazinga0426/Crowd-Counting-for-FYP/tree/a5ef9de5d7b69bd76980aa4312700601cf7d9adb |
Bc | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
import torch.utils
class Bc(nn.Module):
def __init__(self, nc):
super(Bc, self).__init__()
self.nn = nn.Linear(nc, 1)
def forward(self, input):
return torch.sigmoid(self.nn(input))
def get_inputs():... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
import torch.utils.data
import to... | AyufhSri/GANAccImprover | Bc | false | 83 | [
"MIT"
] | 0 | eff3a944bd6e5d9761ec815f28c0d32c87096308 | https://github.com/AyufhSri/GANAccImprover/tree/eff3a944bd6e5d9761ec815f28c0d32c87096308 |
DisConvModule | import torch
import torch.nn as nn
from torch.nn.utils import spectral_norm as spectral_norm_fn
from torch.nn.utils import weight_norm as weight_norm_fn
def dis_conv(input_dim, output_dim, kernel_size=5, stride=2, padding=0,
rate=1, activation='lrelu', weight_norm='none'):
return Conv2dBlock(input_dim, output... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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 import spectral_norm as spectral_norm_... | jacobwjs/generative-inpainting-pytorch | DisConvModule | false | 3,692 | [
"MIT"
] | 0 | 5cd5e818aa7394444b6c21df448d8b395492e4d7 | https://github.com/jacobwjs/generative-inpainting-pytorch/tree/5cd5e818aa7394444b6c21df448d8b395492e4d7 |
CAM_Module | # 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.... | KonarkPaul/COVID_Adv_attack_vulnerability_study | CAM_Module | false | 5,456 | [
"MIT"
] | 1 | f0d1256d0d57a933dd86ccd5fe12d83f9f79ca9c | https://github.com/KonarkPaul/COVID_Adv_attack_vulnerability_study/tree/f0d1256d0d57a933dd86ccd5fe12d83f9f79ca9c |
ConcatSquashConv2d | # 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... | D-hash-code/ffjord-rnode-finalweek-mnist | ConcatSquashConv2d | false | 2,155 | [
"MIT"
] | 0 | 4cabcbadda79c68df53ec25f1f8fe03cfeee78f9 | https://github.com/D-hash-code/ffjord-rnode-finalweek-mnist/tree/4cabcbadda79c68df53ec25f1f8fe03cfeee78f9 |
Block | import torch
from torch import nn
from torch.optim.lr_scheduler import *
from torch.optim import *
def drop_path(x, drop_prob: 'float'=0.0, training: 'bool'=False):
"""Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).
This is the same as the DropConnect impl I created fo... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Challyfilio/NAIC2021 | Block | false | 299 | [
"MIT"
] | 0 | 11b38a920dcc902f9b798dc43ae360062862e6e4 | https://github.com/Challyfilio/NAIC2021/tree/11b38a920dcc902f9b798dc43ae360062862e6e4 |
BERTEmbedding3 | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
from itertools import chain as chain
import torch.... | EddieMG/LateTemporalModeling3DCNN | BERTEmbedding3 | false | 2,268 | [
"MIT"
] | 0 | 94c87dc1d31d09bc310d0e735a2e55453976cb0d | https://github.com/EddieMG/LateTemporalModeling3DCNN/tree/94c87dc1d31d09bc310d0e735a2e55453976cb0d |
NeuralNet | # 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... | Silent-Zebra/sequential_social_dilemma_games | NeuralNet | false | 2,842 | [
"MIT"
] | 0 | 8cf8faebf7de727bac55bd8020be7cd9cc243ccc | https://github.com/Silent-Zebra/sequential_social_dilemma_games/tree/8cf8faebf7de727bac55bd8020be7cd9cc243ccc |
FusedLeakyReLU | # 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
import torch.nn.functional as F
assert_size_stride = torch._C._dynamo.guards.asse... | Theomat/colorization-av-enseirb-2020 | FusedLeakyReLU | false | 14,486 | [
"Apache-2.0"
] | 1,422 | c54c2388ea39a62289fa2f1c51b4757bf55d3c4f | https://github.com/Theomat/colorization-av-enseirb-2020/tree/c54c2388ea39a62289fa2f1c51b4757bf55d3c4f |
SimpleAtariNet | import torch
import torch.nn as nn
import torch.nn.functional as functional
class SimpleAtariNet(nn.Module):
def __init__(self):
super(SimpleAtariNet, self).__init__()
self.conv0 = nn.Conv2d(3, 16, 12, stride=(2, 8))
self.conv1 = nn.Conv2d(16, 32, 8, stride=4)
self.conv2 = 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 import triton_helpers
import torch.nn as nn
assert_... | aaronmckinstry706/pytorch-practice | SimpleAtariNet | false | 12,064 | [
"MIT"
] | 0 | d3fd28733ea6de6a2e522ec52ff3e748df21b85a | https://github.com/aaronmckinstry706/pytorch-practice/tree/d3fd28733ea6de6a2e522ec52ff3e748df21b85a |
ImgSenRanking | import torch
import numpy as np
import torch.utils.data
def l2norm(input, p=2.0, dim=1, eps=1e-12):
"""
Compute L2 norm, row-wise
"""
l2_inp = input / input.norm(p, dim, keepdim=True).clamp(min=eps)
return l2_inp.expand_as(input)
def xavier_weight(tensor):
nin, nout = tensor.size()[0], tenso... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ypxie/HDGan | ImgSenRanking | false | 16,770 | [
"MIT"
] | 160 | d98e2a85f7ae6ce7bfacd1c15e519558d97cb931 | https://github.com/ypxie/HDGan/tree/d98e2a85f7ae6ce7bfacd1c15e519558d97cb931 |
LxmertAttentionOutput | import torch
from torch import nn
from itertools import *
class LxmertAttentionOutput(nn.Module):
def __init__(self, hidden_size, hidden_dropout_prob):
super().__init__()
self.dense = nn.Linear(hidden_size, hidden_size)
self.LayerNorm = nn.LayerNorm(hidden_size, eps=1e-12)
self.dr... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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... | ashutoshbsathe/SmBop | LxmertAttentionOutput | false | 9,800 | [
"MIT"
] | 0 | ce5f67ec070df55b84d7f3617659011732020c96 | https://github.com/ashutoshbsathe/SmBop/tree/ce5f67ec070df55b84d7f3617659011732020c96 |
TransformerLayer | # 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.... | GoalballAnalysis/GUI | TransformerLayer | false | 2,315 | [
"MIT"
] | 0 | c7f1cc27f4fd7f861c3ca09f5ca25d1a3f19a8a7 | https://github.com/GoalballAnalysis/GUI/tree/c7f1cc27f4fd7f861c3ca09f5ca25d1a3f19a8a7 |
ScaledDotProductAttention | import torch
import numpy as np
import torch.utils.data
class ScaledDotProductAttention(torch.nn.Module):
"""
Scaled, softmax attention module for Transformer as defined by
Attention(Q, K, V) on pg 4. Returns the final attention vectors as well as
the attention matrices (pairwise scores). """
def... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | hengwei-chan/protein_transformer | ScaledDotProductAttention | false | 15,505 | [
"BSD-3-Clause"
] | 77 | 988bb0fcbb94b37e5a02071bd345ea073ad605f8 | https://github.com/hengwei-chan/protein_transformer/tree/988bb0fcbb94b37e5a02071bd345ea073ad605f8 |
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