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 |
|---|---|---|---|---|---|---|---|---|---|---|
MultiHead | # 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.... | iml1111/machine-translation | MultiHead | false | 6,885 | [
"MIT"
] | 1 | a7dd673efbe8a172c1df49e0d50482dc84008c37 | https://github.com/iml1111/machine-translation/tree/a7dd673efbe8a172c1df49e0d50482dc84008c37 |
Cat | import torch
import torch.nn as nn
class Cat(nn.Module):
def __init__(self):
super(Cat, self).__init__()
def forward(self, x):
addition = torch.split(x, 2, dim=1)[0]
None
x = torch.cat([x, addition], dim=1)
return x
def get_inputs():
return [torch.rand([4, 4, 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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | yifanpu001/PytorchToCaffe | Cat | false | 4,702 | [
"MIT"
] | 0 | 37c1ebfc3547e93b1c174721036d03c831c60e48 | https://github.com/yifanpu001/PytorchToCaffe/tree/37c1ebfc3547e93b1c174721036d03c831c60e48 |
OneHotEncode | import torch
import torch.optim
import torch.nn as nn
import torch.nn.utils
import torch.autograd
def one_hot_encoding(input_tensor, num_labels):
""" One-hot encode labels from input """
xview = input_tensor.view(-1, 1)
onehot = torch.zeros(xview.size(0), num_labels, device=input_tensor.
device, d... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.optim
import torch.nn as nn
import torch.nn.utils
import torch.autograd
assert_size_stride = torch._C._dynamo.guards.assert_siz... | galatolofederico/vel | OneHotEncode | false | 15,399 | [
"MIT"
] | 273 | 0473648cffb3f34fb784d12dbb25844ab58ffc3c | https://github.com/galatolofederico/vel/tree/0473648cffb3f34fb784d12dbb25844ab58ffc3c |
MLPBlock | import torch
from torch import nn
class MLPBlock(nn.Module):
def __init__(self, in_features, out_features, bias=True, layer_norm=
True, dropout=0.3, activation=nn.ReLU):
super().__init__()
self.linear = nn.Linear(in_features, out_features, bias)
self.activation = 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
from torch._inductor.runtime.... | THinnerichs/deepgozero | MLPBlock | false | 2,873 | [
"BSD-3-Clause"
] | 0 | 5f1481c41f879f7ec1b5eea22dcccdb8bf8825e2 | https://github.com/THinnerichs/deepgozero/tree/5f1481c41f879f7ec1b5eea22dcccdb8bf8825e2 |
Actor | import torch
import numpy as np
import torch.nn.functional as F
from torch import nn
def hidden_init(layer):
fan_in = layer.weight.data.size()[0]
lim = 1.0 / np.sqrt(fan_in)
return -lim, lim
class Actor(nn.Module):
"""Actor (Policy) Model."""
def __init__(self, state_size, action_size, seed, fc... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | tjkemp/ubik-agent | Actor | false | 4,429 | [
"MIT"
] | 0 | 34e4dd0d6319b8f5c5dba0cd9e087490720b723b | https://github.com/tjkemp/ubik-agent/tree/34e4dd0d6319b8f5c5dba0cd9e087490720b723b |
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, state_size, action_size, seed, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import numpy as np
import tor... | rbak/deep-rl-udacity-project-3 | Critic | false | 12,927 | [
"MIT"
] | 0 | 4bf2aec6b0ef27636ebd11dfd4b442554208cffb | https://github.com/rbak/deep-rl-udacity-project-3/tree/4bf2aec6b0ef27636ebd11dfd4b442554208cffb |
ClassHead | import torch
from torch import nn
import torch.cuda
class ClassHead(nn.Module):
"""
ClassHead
RetinaFace head for classification branch.
Args:
inchannels (`int`):
number of input channels.
num_anchors (`int`):
number of anchors.
"""
def __init__(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 import nn
import torch.cuda
assert_size_stride = torch._C._dynamo.gua... | LoveEachDay/towhee | ClassHead | false | 11,712 | [
"Apache-2.0"
] | 0 | 513c9c2626676cadaaf0a16ac3c828d96bec91a1 | https://github.com/LoveEachDay/towhee/tree/513c9c2626676cadaaf0a16ac3c828d96bec91a1 |
MiniBatchAverageLayer | import torch
import torch.nn as nn
import torch.fft
class MiniBatchAverageLayer(nn.Module):
"""Minibatch stat concatenation layer. Implementation is from https://github.com/shanexn/pytorch-pggan."""
def __init__(self, offset=1e-08):
super().__init__()
self.offset = offset
def forward(sel... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.fft
assert_size_stride = torch._C._dynamo.gu... | catherine-qian/image2reverb | MiniBatchAverageLayer | false | 3,290 | [
"MIT"
] | 0 | 0fbcb35d6252dc8652cf98af0e64371cb81967e4 | https://github.com/catherine-qian/image2reverb/tree/0fbcb35d6252dc8652cf98af0e64371cb81967e4 |
Conv1dSamePadding | # 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
import torch.nn.functional as F
assert_size_stride = torch.... | UlysseCoteAllard/LongShortNetworkBipolar | Conv1dSamePadding | false | 5,921 | [
"Apache-2.0"
] | 1 | f6d146b967b4747f02d6589a0483d6c67394ee87 | https://github.com/UlysseCoteAllard/LongShortNetworkBipolar/tree/f6d146b967b4747f02d6589a0483d6c67394ee87 |
UpsamplingBilinear | # 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
from torch.quantization import QuantStub
from torch.quantization im... | cli99/tvm | UpsamplingBilinear | false | 6,462 | [
"Apache-2.0"
] | 1 | 6c6e873a1325a32418108daad6e38f3df8c37660 | https://github.com/cli99/tvm/tree/6c6e873a1325a32418108daad6e38f3df8c37660 |
BMNLoss | import torch
from torch import nn as nn
import torch.nn.functional as F
def binary_logistic_regression_loss(reg_score, label, threshold=0.5,
ratio_range=(1.05, 21), eps=1e-05):
"""Binary Logistic Regression Loss."""
label = label.view(-1)
reg_score = reg_score.contiguous().view(-1)
pmask = (label ... | import torch
from torch import device
import triton
import triton.language as tl
from 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_ma... | HypnosXC/mmaction2 | BMNLoss | false | 13,826 | [
"Apache-2.0"
] | 549 | a26d5f981449445a5e22a0a60d8b285e06c3dd6e | https://github.com/HypnosXC/mmaction2/tree/a26d5f981449445a5e22a0a60d8b285e06c3dd6e |
HardSigmoid | import torch
from torch import nn
class HardSigmoid(nn.Module):
def __init__(self, slope=0.1666667, offset=0.5):
super().__init__()
self.slope = slope
self.offset = offset
def forward(self, input):
return torch.where(input >= 3, torch.tensor(1.0, dtype=torch.float)
... | 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... | DocYard-ai/UCR | HardSigmoid | false | 8,002 | [
"Apache-2.0"
] | 10 | 7618aa336f56e71d9fd8cdc2d591e3d138e3dc68 | https://github.com/DocYard-ai/UCR/tree/7618aa336f56e71d9fd8cdc2d591e3d138e3dc68 |
PytorchBinary | # 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_... | freescania/advdsi_at2 | PytorchBinary | false | 10,150 | [
"MIT"
] | 0 | 13fa0b8beaeccc28975aea40ee5a1db3dd3e33be | https://github.com/freescania/advdsi_at2/tree/13fa0b8beaeccc28975aea40ee5a1db3dd3e33be |
DilateContourLoss | import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
class DilateContourLoss(nn.Module):
def __init__(self):
super(DilateContourLoss, self).__init__()
self.kernel = np.ones((3, 3), np.uint8)
def forward(self, y_pred, y_true):
assert y_pred.size() == y... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import numpy as np
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.ass... | chexqi/Tube_Contour_Detection | DilateContourLoss | false | 6,433 | [
"MIT"
] | 1 | d629c992022f22fb3338b6436fcaadab438f8bfb | https://github.com/chexqi/Tube_Contour_Detection/tree/d629c992022f22fb3338b6436fcaadab438f8bfb |
MLP | # 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 Tensor
from torch import nn
assert_size_stride = torch._C._dyn... | sithu31296/multimodal | MLP | false | 4,340 | [
"MIT"
] | 0 | 78f57956cc84273579eb9e2e2be2a58fa1f38814 | https://github.com/sithu31296/multimodal/tree/78f57956cc84273579eb9e2e2be2a58fa1f38814 |
rSoftMax | # 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 import nn
a... | Kwongy/Pretrained-backbone-Pytorch | rSoftMax | false | 2,484 | [
"MIT"
] | 0 | 1b24bb677e0fd420cce32715c1ead8f0c804d707 | https://github.com/Kwongy/Pretrained-backbone-Pytorch/tree/1b24bb677e0fd420cce32715c1ead8f0c804d707 |
Conv2dBlock | # 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... | CompVis/interactive-image2video-synthesis | Conv2dBlock | false | 7,924 | [
"MIT"
] | 20 | 05ea449d3a2704b6d79a5f08683035220d615576 | https://github.com/CompVis/interactive-image2video-synthesis/tree/05ea449d3a2704b6d79a5f08683035220d615576 |
LabelSmoothingBCE | import torch
import torch.nn as nn
import torch.utils.data
import torch.utils.data.distributed
class LabelSmoothingBCE(nn.Module):
def __init__(self, smoothing=0.0):
super(LabelSmoothingBCE, self).__init__()
self.criterion = nn.BCEWithLogitsLoss(reduction='none')
self.confidence = 1.0 - s... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | boldsort/craftassist | LabelSmoothingBCE | false | 14,968 | [
"MIT"
] | 626 | 8058d115a250e30deb60d969b7b1a5fefd6e974c | https://github.com/boldsort/craftassist/tree/8058d115a250e30deb60d969b7b1a5fefd6e974c |
Gaussian | # 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 import device
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 libd... | userVector/GMVAE | Gaussian | false | 4,475 | [
"MIT"
] | 0 | 2d0330c4174aa614f3817888798f88798313e01f | https://github.com/userVector/GMVAE/tree/2d0330c4174aa614f3817888798f88798313e01f |
ActorNetwork | # 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 ... | godnpeter/DMC_Clustering_PICA | ActorNetwork | false | 6,751 | [
"BSD-2-Clause"
] | 1 | 1b3e14dd4034f3941af1caa06c1d4b6f9d606408 | https://github.com/godnpeter/DMC_Clustering_PICA/tree/1b3e14dd4034f3941af1caa06c1d4b6f9d606408 |
AlexNet | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
class AlexNet(nn.Module):
def __init__(self):
super(AlexNet, self).__init__()
self.conv1 = nn.Conv2d(3, 64, (11, 11), stride=(4, 4), padding=(2, 2))
self.conv2 = nn.Conv2d(64, 192, (5, 5), stride=(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 ... | Fritingo/AlexNet_on_browser | AlexNet | false | 11,528 | [
"MIT"
] | 0 | 3e674dd84e25ee74f2efde77882b4faa788907c2 | https://github.com/Fritingo/AlexNet_on_browser/tree/3e674dd84e25ee74f2efde77882b4faa788907c2 |
FocalLoss | # 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
... | earlbabson/torchflare | FocalLoss | false | 6,632 | [
"Apache-2.0"
] | 1 | 15db06d313a53a3ec4640869335ba87730562b28 | https://github.com/earlbabson/torchflare/tree/15db06d313a53a3ec4640869335ba87730562b28 |
AddPositionEmb | # 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 typing import Sequence
import torch.nn as nn
import torch._C
import torch.serialization
import torch.nn.parallel
assert_size_stride = t... | dumpmemory/poolformer | AddPositionEmb | false | 15,273 | [
"Apache-2.0"
] | 677 | d108be054469da760141f4789bf87c915c4fd0b2 | https://github.com/dumpmemory/poolformer/tree/d108be054469da760141f4789bf87c915c4fd0b2 |
SAB | import math
import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
def qkv_attention(queries, keys, values, presence=None):
"""
Transformer-like self-attention.
Args:
queries: Tensor of shape [B, N, d_k].
keys: Tensor of shape [B, M, d_k].
values: : Tensor... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | karayanni/torch-scae | SAB | false | 10,430 | [
"Apache-2.0"
] | 0 | e044662d8942d8d1923d13d071f375144cf4a1e8 | https://github.com/karayanni/torch-scae/tree/e044662d8942d8d1923d13d071f375144cf4a1e8 |
Fp32GroupNorm | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.utils.data
import torch.onnx.operators
impor... | Ashprakash/roberta | Fp32GroupNorm | false | 11,482 | [
"MIT"
] | 0 | 5ee7abda64d752a467218c247855ddc20c09a779 | https://github.com/Ashprakash/roberta/tree/5ee7abda64d752a467218c247855ddc20c09a779 |
ComplexConvTranspose2d | # 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... | JamesLiao714/FullSubNet | ComplexConvTranspose2d | false | 615 | [
"MIT"
] | 0 | dad740bac35b5d7544c97740ae59101455acdc40 | https://github.com/JamesLiao714/FullSubNet/tree/dad740bac35b5d7544c97740ae59101455acdc40 |
NNTest | # 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_... | tassotirap/data-science | NNTest | false | 13,029 | [
"Apache-2.0"
] | 0 | 644bc351740cda90c0d8c907132d9da9630266c9 | https://github.com/tassotirap/data-science/tree/644bc351740cda90c0d8c907132d9da9630266c9 |
AlphaEntropy | # 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... | shinoyuki222/torch-light | AlphaEntropy | false | 16,423 | [
"MIT"
] | 310 | 4799805d9bcae82a9f12a574dcf9fdd838c92ee9 | https://github.com/shinoyuki222/torch-light/tree/4799805d9bcae82a9f12a574dcf9fdd838c92ee9 |
SoftmaxAttention | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | nlpcl-lab/msent-cred-predictor | SoftmaxAttention | false | 12,842 | [
"Apache-2.0"
] | 0 | 1ac75953583e427dd37717a522a1aaa5b2d1a6a9 | https://github.com/nlpcl-lab/msent-cred-predictor/tree/1ac75953583e427dd37717a522a1aaa5b2d1a6a9 |
DWT | import torch
import torch.nn as nn
import torch.fft
class DWT(nn.Module):
"""
2D Discrete Wavelet Transform as implemented in [1]_.
References
----------
.. [1] Liu, Pengju, et al. “Multi-Level Wavelet-CNN for Image Restoration.” ArXiv:1805.07071 [Cs], May 2018.
arXiv.org, http://arxiv.org/a... | 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.fft
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo... | directgroup/direct | DWT | false | 15,187 | [
"Apache-2.0"
] | 55 | 78cdd530b3c93e31c11d8963880e6329f0989243 | https://github.com/directgroup/direct/tree/78cdd530b3c93e31c11d8963880e6329f0989243 |
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 as nn
assert_... | Code-Notebook/RL_with_pytorch_gym | Critic | false | 5,015 | [
"MIT"
] | 1 | 5417e450ba8b6eb991c6970ffd42f26911de3d6a | https://github.com/Code-Notebook/RL_with_pytorch_gym/tree/5417e450ba8b6eb991c6970ffd42f26911de3d6a |
BasicModel_ConvNet_One_Conv | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | LMdeLiangMi/captum | BasicModel_ConvNet_One_Conv | false | 5,489 | [
"BSD-3-Clause"
] | 1 | 8bd9686013fe0ba8996e9b1cbeb0ea8e91512787 | https://github.com/LMdeLiangMi/captum/tree/8bd9686013fe0ba8996e9b1cbeb0ea8e91512787 |
CondUpsampler | import torch
import torch.nn.functional as F
import torch.nn as nn
class CondUpsampler(nn.Module):
def __init__(self, cond_length, target_dim):
super().__init__()
self.linear1 = nn.Linear(cond_length, target_dim // 2)
self.linear2 = nn.Linear(target_dim // 2, target_dim)
def forward(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | ZhuangweiKang/pytorch-ts | CondUpsampler | false | 2,993 | [
"Apache-2.0",
"MIT"
] | 0 | 076d456358fd1bac96becba4f1ba38ec5a5fcf4d | https://github.com/ZhuangweiKang/pytorch-ts/tree/076d456358fd1bac96becba4f1ba38ec5a5fcf4d |
BCE_LOSS | import math
import torch
from torch.nn.modules.loss import _Loss
import torch.optim
import torch._utils
import torch.nn
class BCE_LOSS(_Loss):
def __init__(self, loss_weight=1.0, bias=False):
super().__init__()
self.bce_loss = torch.nn.BCEWithLogitsLoss()
self.loss_weight = loss_weight
... | 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.... | ModelTC/EOD | BCE_LOSS | false | 14,056 | [
"Apache-2.0"
] | 196 | 164bff80486e9ae6a095a97667b365c46ceabd86 | https://github.com/ModelTC/EOD/tree/164bff80486e9ae6a095a97667b365c46ceabd86 |
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
from torch import nn
assert_s... | google/dynamic-video-depth | ResidualConvUnit | false | 15,451 | [
"Apache-2.0"
] | 144 | 7dab8f9e156fa35735301695ea020aee7221fb31 | https://github.com/google/dynamic-video-depth/tree/7dab8f9e156fa35735301695ea020aee7221fb31 |
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... | bronemos/contrastive-unpaired-translation-focal | FusedLeakyReLU | false | 3,249 | [
"BSD-3-Clause"
] | 0 | 50b9008d08a86439ede081a910d02df5da8e32df | https://github.com/bronemos/contrastive-unpaired-translation-focal/tree/50b9008d08a86439ede081a910d02df5da8e32df |
Lookahead | # 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.utils.data.distributed
import torch.nn as nn
assert_size_stride = t... | Chudbrochil/deepspeech.pytorch-2.1 | Lookahead | false | 7,893 | [
"MIT"
] | 13 | d5d01e33ef383edb79c6a5b1584c134587108deb | https://github.com/Chudbrochil/deepspeech.pytorch-2.1/tree/d5d01e33ef383edb79c6a5b1584c134587108deb |
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_... | gntoni/pytorch-ddpg-naf | LayerNorm | false | 12,457 | [
"MIT"
] | 0 | d208d0c0c38a9d2d2041f1e7e95695359eba430e | https://github.com/gntoni/pytorch-ddpg-naf/tree/d208d0c0c38a9d2d2041f1e7e95695359eba430e |
AddCoords | # 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... | HexagonPrime/pixel-nerf | AddCoords | false | 2,413 | [
"BSD-2-Clause"
] | 0 | 298aa7a3451c01e6f19f73f0c756672d3de54bf9 | https://github.com/HexagonPrime/pixel-nerf/tree/298aa7a3451c01e6f19f73f0c756672d3de54bf9 |
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 import triton_helpers
import torch.nn as nn
assert_... | YoniSchirris/SimCLR | Encoder | false | 1,300 | [
"MIT"
] | 0 | a99b7f7d0fdbc5a9747abf70a8b216b328608796 | https://github.com/YoniSchirris/SimCLR/tree/a99b7f7d0fdbc5a9747abf70a8b216b328608796 |
Hflip | # 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... | ChristophReich1996/kornia | Hflip | false | 277 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | 35f955b46e8015da1cb9faa28c6943ec2b09cc2a | https://github.com/ChristophReich1996/kornia/tree/35f955b46e8015da1cb9faa28c6943ec2b09cc2a |
ScaledDotProductAttention | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | awesome-archive/FEAT | ScaledDotProductAttention | false | 6,291 | [
"MIT"
] | 1 | 940d525fcbf2a40528d284392a03e4b0193344a7 | https://github.com/awesome-archive/FEAT/tree/940d525fcbf2a40528d284392a03e4b0193344a7 |
ResBlock | import torch
import torch.nn as nn
def get_same_padding(kernel_size, dilation):
kernel_size = kernel_size + (kernel_size - 1) * (dilation - 1)
padding = (kernel_size - 1) // 2
return padding
class ResBlock(nn.Module):
def __init__(self, inplanes, planes, kernel_size=3, stride=1, dilation=1):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | Flemingjp/CDVD-TSP | ResBlock | false | 13,686 | [
"MIT"
] | 232 | a2621476deb9386b1bc02570706f490d582930c8 | https://github.com/Flemingjp/CDVD-TSP/tree/a2621476deb9386b1bc02570706f490d582930c8 |
Mul | import torch
class Mul(torch.nn.Module):
def __init__(self, weight):
super(Mul, self).__init__()
self.weight = weight
def forward(self, x):
return x * self.weight
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {'weight': 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
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | NehzUx/autodl | Mul | false | 8,594 | [
"Apache-2.0"
] | 25 | c80fdc4b297ed1ec2b9e6911d313f1fe31d83cb9 | https://github.com/NehzUx/autodl/tree/c80fdc4b297ed1ec2b9e6911d313f1fe31d83cb9 |
ConvolutionModule | import torch
from torch import Tensor
from torch import nn
class Swish(torch.nn.Module):
"""Construct an Swish object."""
def forward(self, x: 'Tensor') ->Tensor:
"""Return Swich activation function."""
return x * torch.sigmoid(x)
class ConvolutionModule(nn.Module):
"""ConvolutionModule... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 T... | thangdepzai/icefall | ConvolutionModule | false | 13,037 | [
"Apache-2.0"
] | 0 | 8c7995d493c4309c3d09bdabfa1ab12b4eec2657 | https://github.com/thangdepzai/icefall/tree/8c7995d493c4309c3d09bdabfa1ab12b4eec2657 |
CAM | # 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._utils
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dyn... | henbucuoshanghai/crowed-count- | CAM | false | 15,507 | [
"MIT"
] | 81 | 3353c0a8011b6b83e6e0392258a88706378b443b | https://github.com/henbucuoshanghai/crowed-count-/tree/3353c0a8011b6b83e6e0392258a88706378b443b |
VAE | import torch
import torch.nn as nn
import torch.nn.functional as F
class VAE(nn.Module):
def __init__(self, state_dim, action_dim, latent_dim, max_action, device):
super(VAE, self).__init__()
self.e1 = nn.Linear(state_dim + action_dim, 750)
self.e2 = nn.Linear(750, 750)
self.mean ... | import torch
from torch import device
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | cedesu/BCQ | VAE | false | 12,211 | [
"MIT"
] | 0 | 424548510349a85c31809431494dcc6f64b611ba | https://github.com/cedesu/BCQ/tree/424548510349a85c31809431494dcc6f64b611ba |
AvgLayer | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C.... | pYtoner/EasyOCR | AvgLayer | false | 7,437 | [
"Apache-2.0"
] | 1 | cbb2df77ae789dd4c7807541e0357d9a698ba801 | https://github.com/pYtoner/EasyOCR/tree/cbb2df77ae789dd4c7807541e0357d9a698ba801 |
VAE | # 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 import device
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | lenaguignard/examples | VAE | false | 15,941 | [
"BSD-3-Clause"
] | 19,783 | 973e77b725a6028289a90170f0b237ea2e71d4f2 | https://github.com/lenaguignard/examples/tree/973e77b725a6028289a90170f0b237ea2e71d4f2 |
SELayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.utils.data
impor... | CrazyStoneonRoad/pytorch_image_classification | SELayer | false | 17,170 | [
"MIT"
] | 4 | 1dcf6d0ee8f4a102ca93cc6e5e325a2e9153918b | https://github.com/CrazyStoneonRoad/pytorch_image_classification/tree/1dcf6d0ee8f4a102ca93cc6e5e325a2e9153918b |
VAE | import torch
import torch.nn as nn
import torch.nn.functional as F
class VAE(nn.Module):
def __init__(self):
super(VAE, self).__init__()
self.fc1 = nn.Linear(784, 400)
self.fc21 = nn.Linear(400, 20)
self.fc22 = nn.Linear(400, 20)
self.fc3 = nn.Linear(20, 400)
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
import ... | momohatt/chainer-compiler | VAE | false | 16,111 | [
"MIT"
] | 116 | 26782cd29a5becf8e2badf268b47d98b3a6aea1d | https://github.com/momohatt/chainer-compiler/tree/26782cd29a5becf8e2badf268b47d98b3a6aea1d |
CCAMDec | # 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.... | bfjei2825401/siamban | CCAMDec | false | 10,403 | [
"Apache-2.0"
] | 0 | c41d58742b146dfc8960053453227c6e9fec1bac | https://github.com/bfjei2825401/siamban/tree/c41d58742b146dfc8960053453227c6e9fec1bac |
CORblock_Z | # 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... | emaliemcmahon/dl-final-proj-spring21-group2 | CORblock_Z | false | 10,030 | [
"MIT"
] | 0 | 51abed6633c4b326e62d26c1600256a959b39510 | https://github.com/emaliemcmahon/dl-final-proj-spring21-group2/tree/51abed6633c4b326e62d26c1600256a959b39510 |
Normalize | # 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 itertools import product as product
import torch.onn... | Janus1984/Msnhnet | Normalize | false | 13,872 | [
"MIT"
] | 546 | 4e09f2501ba8db789f0a20441a357de3ba468f10 | https://github.com/Janus1984/Msnhnet/tree/4e09f2501ba8db789f0a20441a357de3ba468f10 |
DotProductLoss | import torch
import torch.nn as nn
class DotProductLoss(nn.Module):
def __init__(self):
super(DotProductLoss, self).__init__()
def forward(self, output, target):
return -torch.dot(target.view(-1), output.view(-1)) / target.nelement()
def get_inputs():
return [torch.rand([4, 4, 4, 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... | ehsanik/dogTorch | DotProductLoss | false | 15,282 | [
"MIT"
] | 74 | 3a898862f6283e6603833991eeb62427216f2af7 | https://github.com/ehsanik/dogTorch/tree/3a898862f6283e6603833991eeb62427216f2af7 |
CoPredictor | # 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.autogr... | yifding/W2NER | CoPredictor | false | 13,150 | [
"MIT"
] | 0 | d13128e45f3930a8b8faa794318939dc90a75974 | https://github.com/yifding/W2NER/tree/d13128e45f3930a8b8faa794318939dc90a75974 |
LSTMCell | # 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... | ppvalluri09/annotated_deep_learning_paper_implementations | LSTMCell | false | 11,069 | [
"MIT"
] | 0 | 387b6dfd1ef1f6d295e9394c24b5798071d9a3e4 | https://github.com/ppvalluri09/annotated_deep_learning_paper_implementations/tree/387b6dfd1ef1f6d295e9394c24b5798071d9a3e4 |
MaxPool3x3 | # 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... | jack-willturner/nas-without-training | MaxPool3x3 | false | 12,545 | [
"MIT"
] | 0 | d5e915b5f391f51d902f33b1d4beedfe3b09d2e0 | https://github.com/jack-willturner/nas-without-training/tree/d5e915b5f391f51d902f33b1d4beedfe3b09d2e0 |
SAModule | # 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_... | whkwls2653/Pytorch_Face_Recognition- | SAModule | false | 16,708 | [
"MIT"
] | 62 | 60f3849def589957d9080457a1a9833112a71f6c | https://github.com/whkwls2653/Pytorch_Face_Recognition-/tree/60f3849def589957d9080457a1a9833112a71f6c |
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
import torch.nn as nn
import ... | ChangQingAAS/Deep-Reinforcement-Learning | Net | false | 233 | [
"MIT"
] | 0 | 3bc1381c632b1730a48e63e972aea62086c4287c | https://github.com/ChangQingAAS/Deep-Reinforcement-Learning/tree/3bc1381c632b1730a48e63e972aea62086c4287c |
LeNet | # 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 ... | amazon-research/network-deconvolution-pp | LeNet | false | 18,353 | [
"Apache-2.0"
] | 6 | 99e27ecec7d27c7c4c3fb230e96005bdcbf6f2ce | https://github.com/amazon-research/network-deconvolution-pp/tree/99e27ecec7d27c7c4c3fb230e96005bdcbf6f2ce |
LearnedPositionalEmbedding1D | # 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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | styler00dollar/Colab-animesion | LearnedPositionalEmbedding1D | false | 16,500 | [
"MIT"
] | 67 | 0fa603689fec3ed4ede098fd7c15b519dbb76a09 | https://github.com/styler00dollar/Colab-animesion/tree/0fa603689fec3ed4ede098fd7c15b519dbb76a09 |
ConvNet | import torch
import torch.nn as nn
class ConvNet(nn.Module):
def __init__(self):
super(ConvNet, self).__init__()
self.conv1 = nn.Conv2d(1, 5, 6, 2)
self.pool1 = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(5, 8, 3, 1)
self.drp1 = nn.Dropout2d(0.25)
self.pool2 = nn.Max... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | iOsnaaente/Faculdade_ECA-UFSM | ConvNet | false | 3,650 | [
"MIT"
] | 0 | aea8b8d66169b073c439b47ad990e45695cbe953 | https://github.com/iOsnaaente/Faculdade_ECA-UFSM/tree/aea8b8d66169b073c439b47ad990e45695cbe953 |
BertSelfOutput | from _paritybench_helpers import _mock_config
import torch
import torch.utils.data
import torch.nn as nn
import torch
import torch.nn.parallel
class BertLayerNorm(nn.Module):
def __init__(self, hidden_size, eps=1e-12):
"""Construct a layernorm module in the TF style (epsilon inside the square root).
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | adymaharana/VLCStoryGan | BertSelfOutput | false | 18,269 | [
"MIT"
] | 10 | 74112404689e8144c2ed2d375e1e5a1cde09debb | https://github.com/adymaharana/VLCStoryGan/tree/74112404689e8144c2ed2d375e1e5a1cde09debb |
MultiheadAttention | import torch
import torch.nn.functional as F
from torch import nn
import torch.utils.data
from torch.nn import Parameter
import torch.onnx.operators
import torch.optim
import torch.optim.lr_scheduler
class MultiheadAttention(nn.Module):
"""Multi-headed attention.
See "Attention Is All You Need" for more deta... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Ivan-Dimitrov/ml_systems_code_pruning | MultiheadAttention | false | 9,208 | [
"BSD-3-Clause"
] | 0 | 54cc9f35a87e52c1fef870b7cb54cb03239d5c96 | https://github.com/Ivan-Dimitrov/ml_systems_code_pruning/tree/54cc9f35a87e52c1fef870b7cb54cb03239d5c96 |
MinusRbfHSIC | import torch
import torch.nn as nn
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 sample estimator of HSIC... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | naver-ai/cgl_fairness | MinusRbfHSIC | false | 7,330 | [
"MIT"
] | 1 | 00d3bec233c9b3e0f88496118abaed8321ca3159 | https://github.com/naver-ai/cgl_fairness/tree/00d3bec233c9b3e0f88496118abaed8321ca3159 |
ShuffleCatChunk | import torch
import torch.nn as nn
class ShuffleCatChunk(nn.Module):
def forward(self, a, b):
assert a.size() == b.size()
_n, c, _h, _w = a.size()
a = torch.chunk(a, chunks=c, dim=1)
b = torch.chunk(b, chunks=c, dim=1)
x = [None] * (c * 2)
x[::2] = a
x[1::2... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | AbhinandanVellanki/yolact_edge | ShuffleCatChunk | false | 1,956 | [
"MIT"
] | 0 | 06d6318cf70ef511b19aa1c14f0476e4ffac2722 | https://github.com/AbhinandanVellanki/yolact_edge/tree/06d6318cf70ef511b19aa1c14f0476e4ffac2722 |
ZeroOneTest | # 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... | mxuq/Imbalance-PU | ZeroOneTest | false | 7,312 | [
"MIT"
] | 1 | fd4403b05f98ca6bc8156783e8275888d63f6435 | https://github.com/mxuq/Imbalance-PU/tree/fd4403b05f98ca6bc8156783e8275888d63f6435 |
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, 12, 5)
self.pool = nn.MaxPool2d(2, 2)
self.conv2 = nn.Conv2d(12, 16, 5)
self.fc1 = nn.Linear(16 * 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_... | tassotirap/data-science | Net | false | 13,032 | [
"Apache-2.0"
] | 0 | 644bc351740cda90c0d8c907132d9da9630266c9 | https://github.com/tassotirap/data-science/tree/644bc351740cda90c0d8c907132d9da9630266c9 |
GroupedLinearCF | import math
import torch
from torch import Tensor
from typing import Optional
from torch import nn
from torch.nn import init
from torch.nn.parameter import Parameter
class GroupedLinearCF(nn.Module):
def __init__(self, in_ch: 'int', out_ch: 'int', n_freqs: 'int',
n_groups: 'int', bias: 'bool'=True):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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 | GroupedLinearCF | false | 14,316 | [
"ECL-2.0",
"Apache-2.0",
"MIT"
] | 54 | afe6bfb53efae70207e18df7ed372c2cfe337fee | https://github.com/Rikorose/DeepFilterNet/tree/afe6bfb53efae70207e18df7ed372c2cfe337fee |
CrossEntropyLoss | import torch
import torch.nn as nn
from torch.nn import functional as F
import torch.nn.parallel
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Return:
Tensor: Red... | 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
... | Fanzhongjie/ARFE | CrossEntropyLoss | false | 442 | [
"Apache-2.0"
] | 0 | 4b96b8c5bc0895d3d30acec2a490f81a860fe860 | https://github.com/Fanzhongjie/ARFE/tree/4b96b8c5bc0895d3d30acec2a490f81a860fe860 |
RelativePositionalEmbedding | import torch
import torch.nn as nn
class RelativePositionalEmbedding(nn.Module):
def __init__(self, n_model, max_len=1024):
super().__init__()
self.embed = nn.Embedding(max_len, n_model)
self.reset_parameters()
@torch.no_grad()
def reset_parameters(self):
w = self.embed.w... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | yzhangcs/parser | RelativePositionalEmbedding | false | 16,804 | [
"MIT"
] | 439 | 3abebde1c9fe0bf2e99adce845aaf2a04b194f8a | https://github.com/yzhangcs/parser/tree/3abebde1c9fe0bf2e99adce845aaf2a04b194f8a |
NeuralNetMultiplePositionalArguments | # 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
import torch.... | almiliMSFT/onnxruntime | NeuralNetMultiplePositionalArguments | false | 14,811 | [
"MIT"
] | 6,036 | c002dc86a364852859ca9642698fcfc5edf22c9d | https://github.com/almiliMSFT/onnxruntime/tree/c002dc86a364852859ca9642698fcfc5edf22c9d |
DistillKL | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | Johnsonms/NNI_master | DistillKL | false | 11,575 | [
"MIT"
] | 0 | e5e5c7aed89cf3189cffe1056464833c15eb54ff | https://github.com/Johnsonms/NNI_master/tree/e5e5c7aed89cf3189cffe1056464833c15eb54ff |
RSoftmax | # 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
... | AlexanderDokuchaev/mmsegmentation | RSoftmax | false | 11,171 | [
"Apache-2.0"
] | 0 | 0c443ee370cce6227661b802184072174c4e3f64 | https://github.com/AlexanderDokuchaev/mmsegmentation/tree/0c443ee370cce6227661b802184072174c4e3f64 |
GEGLU | import torch
from torch import nn
import torch.nn.functional as F
class GEGLU(nn.Module):
def forward(self, x):
x, gates = x.chunk(2, dim=-1)
return x * F.gelu(gates)
def get_inputs():
return [torch.rand([4, 4, 4, 4])]
def get_init_inputs():
return [[], {}]
| import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | adam-mehdi/TimeSformer-pytorch | GEGLU | false | 9,662 | [
"MIT"
] | 0 | 4e6484dba2d3f9aeaaad09a3a310c0ea36b459e3 | https://github.com/adam-mehdi/TimeSformer-pytorch/tree/4e6484dba2d3f9aeaaad09a3a310c0ea36b459e3 |
DecoderBlock | # 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.... | howardchenhd/Transformer-pytorch | DecoderBlock | false | 6,850 | [
"MIT"
] | 1 | ae71ed5767272feb7e717be6d5bfce46f80ec57a | https://github.com/howardchenhd/Transformer-pytorch/tree/ae71ed5767272feb7e717be6d5bfce46f80ec57a |
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 import triton_helpers
from torch._inductor.runtime.... | Romero027/OmniNet | PositionwiseFeedForward | false | 2,786 | [
"Apache-2.0"
] | 0 | c1cda1738c80925e5468b3ffc7aae2153bcd9e62 | https://github.com/Romero027/OmniNet/tree/c1cda1738c80925e5468b3ffc7aae2153bcd9e62 |
FCUDown | # 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 ... | Huzhen757/Conformer | FCUDown | false | 5,327 | [
"Apache-2.0"
] | 1 | 4f7a80cec28b9ced8c0225a85a32997f7cd2b93c | https://github.com/Huzhen757/Conformer/tree/4f7a80cec28b9ced8c0225a85a32997f7cd2b93c |
Encoder | import torch
from torch import nn as nn
def conv3d(in_channels, out_channels, kernel_size, bias, padding=1):
return nn.Conv3d(in_channels, out_channels, kernel_size, padding=
padding, bias=bias)
def create_conv(in_channels, out_channels, kernel_size, order, num_groups,
padding=1):
"""
Create... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | cviaai/TMJ_tracking | Encoder | false | 1,767 | [
"MIT"
] | 0 | 464ca21dbeb538dc9504bd5d0e5c4d92591e69c4 | https://github.com/cviaai/TMJ_tracking/tree/464ca21dbeb538dc9504bd5d0e5c4d92591e69c4 |
Net16 | # 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_... | gautam-sharma1/Imitation-Learning | Net16 | false | 3,522 | [
"MIT"
] | 0 | 20b6fcd2a8d6de8eb95e6831f5b379a083306361 | https://github.com/gautam-sharma1/Imitation-Learning/tree/20b6fcd2a8d6de8eb95e6831f5b379a083306361 |
DeConvNet64 | # 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_... | Neural-Diffusion-Research/normalized-autoencoders | DeConvNet64 | false | 8,709 | [
"MIT"
] | 30 | 0c77f7e29289e336c0fe5e941aaec8baa4a4fb82 | https://github.com/Neural-Diffusion-Research/normalized-autoencoders/tree/0c77f7e29289e336c0fe5e941aaec8baa4a4fb82 |
Conv2dZeroInit | import torch
import torch.nn as nn
class Conv2dZeroInit(nn.Conv2d):
def __init__(self, channels_in, channels_out, filter_size, stride=1,
padding=0, logscale=3.0):
super().__init__(channels_in, channels_out, filter_size, stride=
stride, padding=padding)
self.register_parameter(... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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.... | lingzenan/invertible-resnet | Conv2dZeroInit | false | 7,092 | [
"MIT"
] | 1 | 57b1c0de51a885aed074b77628f3b0c85c548e70 | https://github.com/lingzenan/invertible-resnet/tree/57b1c0de51a885aed074b77628f3b0c85c548e70 |
ConvNet2FC | # 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_... | GloryyrolG/normalized-autoencoders | ConvNet2FC | false | 519 | [
"MIT"
] | 0 | 27ccb74bb725768f9ba9ea6fa03a7a40867eebb1 | https://github.com/GloryyrolG/normalized-autoencoders/tree/27ccb74bb725768f9ba9ea6fa03a7a40867eebb1 |
SiSdr | # 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 libdevice
from torch import n... | Rikorose/DeepFilterNet | SiSdr | false | 14,308 | [
"ECL-2.0",
"Apache-2.0",
"MIT"
] | 54 | afe6bfb53efae70207e18df7ed372c2cfe337fee | https://github.com/Rikorose/DeepFilterNet/tree/afe6bfb53efae70207e18df7ed372c2cfe337fee |
SeparableConvBlock | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
class SeparableConvBlock(nn.Module):
def __init__(self, inplanes, planes):
super(SeparableConvBlock, self).__init__()
self.depthwise_conv = nn.Conv2d(inplanes, inplanes, kernel_size=3,
stride=1, padding=1, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
import torch.optim
assert_size_st... | carol007/pytorch-ImageNet-CIFAR-COCO-VOC-training | SeparableConvBlock | false | 6,389 | [
"MIT"
] | 1 | e8b37046e6fbe914f6a68bbde1fe419c46373c1d | https://github.com/carol007/pytorch-ImageNet-CIFAR-COCO-VOC-training/tree/e8b37046e6fbe914f6a68bbde1fe419c46373c1d |
ShuffleBlock | # 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... | P2333/Bag-of-Tricks-for-AT | ShuffleBlock | false | 14,122 | [
"Apache-2.0"
] | 192 | 314683adcfe9ea7c7bfbff50007da510b21f56e1 | https://github.com/P2333/Bag-of-Tricks-for-AT/tree/314683adcfe9ea7c7bfbff50007da510b21f56e1 |
BerHuLoss | import torch
import torch.nn as nn
class BerHuLoss(nn.Module):
"""Class implementing the BerHu loss."""
def __init__(self, threshold=0.2):
"""
Initializes the BerHuLoss class.
Parameters
----------
threshold : float
Mask parameter
"""
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
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.nn as nn
... | pection/packnet-sfm | BerHuLoss | false | 7,444 | [
"MIT"
] | 1 | d5673567b649e6bfda292c894cacdeb06aa80913 | https://github.com/pection/packnet-sfm/tree/d5673567b649e6bfda292c894cacdeb06aa80913 |
IRW_L1_Loss | import torch
import torch.utils.data
import torch
import torch.nn as nn
class IRW_L1_Loss(nn.Module):
def __init__(self, threshold):
super(IRW_L1_Loss, self).__init__()
self.threshold = threshold
def forward(self, x, y, beta):
beta = beta.view(len(x), 1, 1, 1)
beta = torch.nn... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.utils.dat... | Mid-Push/IrwGAN | IRW_L1_Loss | false | 8,547 | [
"BSD-3-Clause"
] | 31 | f56e7274cf7de3362459549dd807b66b93dc5e89 | https://github.com/Mid-Push/IrwGAN/tree/f56e7274cf7de3362459549dd807b66b93dc5e89 |
LabelSmoothCELoss | import torch
import torch.nn.functional as F
import torch.nn as nn
import torch.utils.data
def one_hot(val: 'torch.LongTensor', num: 'int', num_first: 'bool'=False
) ->torch.FloatTensor:
"""
Overview:
Convert a ``torch.LongTensor`` to one hot encoding.
This implementation can be slightly f... | 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
... | L-Net-1992/DI-engine | LabelSmoothCELoss | false | 5,494 | [
"Apache-2.0"
] | 1 | 06803b4e18fa64bbed0fd1d44952242c0c063b0f | https://github.com/L-Net-1992/DI-engine/tree/06803b4e18fa64bbed0fd1d44952242c0c063b0f |
SelfAttentionGated | import torch
import torch.utils.data
import torch.nn.functional as F
def masked_softmax(x, m=None, dim=-1):
"""
Softmax with mask
:param x:
:param m:
:param dim:
:return:
"""
if m is not None:
m = m.float()
x = x * m
e_x = torch.exp(x - torch.max(x, dim=dim, keepdim... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | jamaalhay/Final_Proj | SelfAttentionGated | false | 15,672 | [
"MIT"
] | 104 | 3f524a90fee5a3cb21466ab76f630d060792045d | https://github.com/jamaalhay/Final_Proj/tree/3f524a90fee5a3cb21466ab76f630d060792045d |
ContrastiveEmbeddingLoss | # 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.modules.loss i... | pokidyshev/catalyst | ContrastiveEmbeddingLoss | false | 16,259 | [
"Apache-2.0"
] | 46 | bfe2cc2af7b02bd954fb0b4a0cae8b350f56789a | https://github.com/pokidyshev/catalyst/tree/bfe2cc2af7b02bd954fb0b4a0cae8b350f56789a |
AdaILN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import torch.utils.cpp_extension
assert_size_stride = tor... | STomoya/animeface | AdaILN | false | 15,247 | [
"MIT"
] | 61 | 37b3cd26097d7874559d4c152e41e5712b7a1a42 | https://github.com/STomoya/animeface/tree/37b3cd26097d7874559d4c152e41e5712b7a1a42 |
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Khanhnn00/kernel-prior-diffusion | Downsample | false | 731 | [
"MIT"
] | 0 | 6f38d3a645c5f6a2b33b8ab60b6f15a12bf245dd | https://github.com/Khanhnn00/kernel-prior-diffusion/tree/6f38d3a645c5f6a2b33b8ab60b6f15a12bf245dd |
GDN | from torch.autograd import Function
import torch
import torch.nn.functional as F
import torch.nn as nn
class LowerBound(Function):
@staticmethod
def forward(ctx, inputs, bound):
ctx.save_for_backward(inputs, inputs.new_ones(1) * bound)
return inputs.clamp(min=bound)
@staticmethod
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.... | agr17/pytorch-msssim | GDN | false | 1,388 | [
"MIT"
] | 0 | 69aec4113ccceafa5568d1191e98c1db525c0c0f | https://github.com/agr17/pytorch-msssim/tree/69aec4113ccceafa5568d1191e98c1db525c0c0f |
MLP | # 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... | EE559DeepLearningEPFL/Project1 | MLP | false | 381 | [
"MIT"
] | 0 | cbafdfee26771ae0ba3cd36375e68d92e9f108b2 | https://github.com/EE559DeepLearningEPFL/Project1/tree/cbafdfee26771ae0ba3cd36375e68d92e9f108b2 |
AttentionPool2d | # 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.... | litevxx/glid-3 | AttentionPool2d | false | 10,447 | [
"MIT"
] | 0 | d7bd53e671d642b0cbc8af81197170b585c7e624 | https://github.com/litevxx/glid-3/tree/d7bd53e671d642b0cbc8af81197170b585c7e624 |
Affine | import torch
import torch.nn as nn
class Affine(nn.Module):
def __init__(self, dim):
super().__init__()
self.alpha = nn.Parameter(torch.ones(dim))
self.beta = nn.Parameter(torch.zeros(dim))
def forward(self, x):
return self.alpha * x + self.beta
def get_inputs():
return... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_st... | Uzair-Khattak/deit | Affine | false | 9,640 | [
"Apache-2.0"
] | 0 | 896004fc84d4ad2c4c9aa792822df7426af5903d | https://github.com/Uzair-Khattak/deit/tree/896004fc84d4ad2c4c9aa792822df7426af5903d |
ConcatBlock | import torch
import torch.nn as nn
import torch.nn.functional
class ConcatBlock(nn.Module):
def __init__(self, in_channels, out_channels):
super(ConcatBlock, self).__init__()
self.in_chns = in_channels
self.out_chns = out_channels
self.conv1 = nn.Conv2d(self.in_chns, self.in_chns,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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
assert_size_stride = torch._C._... | Luoxd1996/awesome-semi-supervised-learning-for-medical-image-segmentation | ConcatBlock | false | 17,706 | [
"MIT"
] | 6 | 34d78f41e4fa5927b03cb9f9b2fd473cd16f5e57 | https://github.com/Luoxd1996/awesome-semi-supervised-learning-for-medical-image-segmentation/tree/34d78f41e4fa5927b03cb9f9b2fd473cd16f5e57 |
Conv2dDynamicSamePadding | # 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... | ANI717/effecientnet_b7_pneumonia | Conv2dDynamicSamePadding | false | 4,773 | [
"MIT"
] | 1 | f8bf71c92bc1ae5a80b8e37b685bf314004001b3 | https://github.com/ANI717/effecientnet_b7_pneumonia/tree/f8bf71c92bc1ae5a80b8e37b685bf314004001b3 |
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