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 |
|---|---|---|---|---|---|---|---|---|---|---|
MFH | # 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_... | JoannaLXY/block.bootstrap.pytorch | MFH | false | 11,562 | [
"BSD-3-Clause"
] | 0 | 42c3e7616b704e05c6ff2376ff68b5b18044fe77 | https://github.com/JoannaLXY/block.bootstrap.pytorch/tree/42c3e7616b704e05c6ff2376ff68b5b18044fe77 |
WordPredictor | # 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... | Jeffyrao/translate | WordPredictor | false | 2,445 | [
"BSD-3-Clause"
] | 0 | ab928e0b692f476c0a43ee7f9d0fbd3ecbada2b4 | https://github.com/Jeffyrao/translate/tree/ab928e0b692f476c0a43ee7f9d0fbd3ecbada2b4 |
GEGLU | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | DannielSilva/MMBERT | GEGLU | false | 17,199 | [
"MIT"
] | 4 | 2c9069b59b66b8f3fec6de2e68ec42b489a3a437 | https://github.com/DannielSilva/MMBERT/tree/2c9069b59b66b8f3fec6de2e68ec42b489a3a437 |
_DynamicGates | from _paritybench_helpers import _mock_config
import torch
import torch.nn as nn
class _DynamicGates(nn.Module):
"""Internal class to wrap the dynamic gate parameters into a dedicated PyTorch Module"""
def __init__(self, cfg: 'Config', input_size: 'int'):
super(_DynamicGates, self).__init__()
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | NHoose/neuralhydrology | _DynamicGates | false | 1,898 | [
"BSD-3-Clause"
] | 0 | f320b417fe747a923ff8ef685ad33fd8b34effad | https://github.com/NHoose/neuralhydrology/tree/f320b417fe747a923ff8ef685ad33fd8b34effad |
PatchEmbedding | import torch
from torch import nn
class PatchEmbedding(nn.Module):
"""Image to Patch Embedding
"""
def __init__(self, patch_size=16, embed_dim=768):
super().__init__()
self.proj = nn.Conv2d(3, embed_dim, patch_size, patch_size)
def forward(self, x: 'torch.Tensor'):
x = self.p... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_st... | sithu31296/image_classification | PatchEmbedding | false | 16,464 | [
"MIT"
] | 57 | 6b8cbce96100225621cee3166a73e852ba216cc3 | https://github.com/sithu31296/image_classification/tree/6b8cbce96100225621cee3166a73e852ba216cc3 |
AttnConnector | # 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 ... | BinLiu777/NeuralDialog-LAED | AttnConnector | false | 11,256 | [
"Apache-2.0"
] | 0 | 3f52a75e5bcb314e567cafe94925cca32ccfbba1 | https://github.com/BinLiu777/NeuralDialog-LAED/tree/3f52a75e5bcb314e567cafe94925cca32ccfbba1 |
SplitCosineLinear | # 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.... | JosephKJ/class-incremental-learning | SplitCosineLinear | false | 17,520 | [
"MIT"
] | 8 | 689271b84f2e553930ca6687d036ac99bd84b311 | https://github.com/JosephKJ/class-incremental-learning/tree/689271b84f2e553930ca6687d036ac99bd84b311 |
DCHR | # 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... | XiaotaoChen/model-quantization | DCHR | false | 14,599 | [
"BSD-2-Clause"
] | 66 | a745ef691e9329b9c973a2dd795761cd3da8b6ae | https://github.com/XiaotaoChen/model-quantization/tree/a745ef691e9329b9c973a2dd795761cd3da8b6ae |
RMSELoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert... | kamomehz/waveletCodingCNN | RMSELoss | false | 3,794 | [
"MIT"
] | 0 | 50c7db9d986039ded38999b7e4f4265e2250fb90 | https://github.com/kamomehz/waveletCodingCNN/tree/50c7db9d986039ded38999b7e4f4265e2250fb90 |
generator | import torch
import torch.nn as nn
class generator(nn.Module):
def __init__(self, p_dim, c_dim):
super(generator, self).__init__()
self.p_dim = p_dim
self.c_dim = c_dim
convex_layer_weights = torch.zeros((self.p_dim, self.c_dim))
self.convex_layer_weights = nn.Parameter(co... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | luixiao1223/BSP-NET-pytorch | generator | false | 3,945 | [
"MIT"
] | 0 | f871c8ce6a9d52ac922e110702c47cd1c89d0a73 | https://github.com/luixiao1223/BSP-NET-pytorch/tree/f871c8ce6a9d52ac922e110702c47cd1c89d0a73 |
TiledConv2d | # 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... | mkarmann/conway-reversed | TiledConv2d | false | 10,678 | [
"MIT"
] | 0 | a3ae10dd5768affb9caf193a246395ee0fb2bc6f | https://github.com/mkarmann/conway-reversed/tree/a3ae10dd5768affb9caf193a246395ee0fb2bc6f |
DownsampleA | import torch
import torch.nn as nn
class DownsampleA(nn.Module):
def __init__(self, nIn, nOut, stride):
super(DownsampleA, self).__init__()
assert stride == 2
self.avg = nn.AvgPool2d(kernel_size=1, stride=stride)
def forward(self, x):
x = self.avg(x)
return torch.cat(... | 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... | hamedomidvar/associativeconv | DownsampleA | false | 6,772 | [
"MIT"
] | 1 | 9930915abd3625871354df676865fc44eb92abf3 | https://github.com/hamedomidvar/associativeconv/tree/9930915abd3625871354df676865fc44eb92abf3 |
BinarySigmoid | # 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 abc
import inspect
import warnings
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
from typ... | Johnsonms/NNI_master | BinarySigmoid | false | 11,567 | [
"MIT"
] | 0 | e5e5c7aed89cf3189cffe1056464833c15eb54ff | https://github.com/Johnsonms/NNI_master/tree/e5e5c7aed89cf3189cffe1056464833c15eb54ff |
Discriminator | # 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
assert_size_stride = torch._C._dynamo.gu... | bzrry/lightning-bolts | Discriminator | false | 14,993 | [
"Apache-2.0"
] | 822 | bd392ad858039290c72c20cc3f10df39384e90b9 | https://github.com/bzrry/lightning-bolts/tree/bd392ad858039290c72c20cc3f10df39384e90b9 |
MPNetSelfAttention | from _paritybench_helpers import _mock_config
import math
import torch
from torch import nn
import torch.utils.checkpoint
class MPNetSelfAttention(nn.Module):
def __init__(self, config):
super().__init__()
if (config.hidden_size % config.num_attention_heads != 0 and not
hasattr(config... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Clemens123/transformers | MPNetSelfAttention | false | 13,218 | [
"Apache-2.0"
] | 0 | 22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 | https://github.com/Clemens123/transformers/tree/22abe7bbc587c16ec30f9d1aa549dcbeba6e9e26 |
CNNCifar | from _paritybench_helpers import _mock_config
import torch
from torch import nn
import torch.nn.functional as F
class CNNCifar(nn.Module):
def __init__(self, args):
super(CNNCifar, self).__init__()
self.conv1 = nn.Conv2d(3, 6, 5)
self.pool = nn.MaxPool2d(2, 2)
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
from torch._inductor.runtime.... | Ilcyb/Federated-Learning-PyTorch | CNNCifar | false | 5,636 | [
"MIT"
] | 1 | 4830a89ffa1ac0ad0e52a4551338532cfb4ca210 | https://github.com/Ilcyb/Federated-Learning-PyTorch/tree/4830a89ffa1ac0ad0e52a4551338532cfb4ca210 |
RAddFloat | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | bunderhi/torch2trt | RAddFloat | false | 1,595 | [
"MIT"
] | 0 | fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d | https://github.com/bunderhi/torch2trt/tree/fa5e31e742a0f0c9a9ee38909a6fa56bb07ba96d |
CharbonnierCompLoss | import functools
import torch
import torch.nn as nn
from torch.nn import functional as F
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Returns:
Tensor: Reduced lo... | 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 functools
import torc... | Juggernaut93/mmediting | CharbonnierCompLoss | false | 13,899 | [
"Apache-2.0"
] | 1,884 | 8ef46ace29756dd2df1d92f2f73a33646e33e007 | https://github.com/Juggernaut93/mmediting/tree/8ef46ace29756dd2df1d92f2f73a33646e33e007 |
InstanceNorm | import torch
import torch.utils.data
import torch.nn as nn
from torch.nn.parameter import Parameter
class InstanceNorm(nn.Module):
def __init__(self, num_features, affine=True, eps=1e-05):
"""`num_features` number of feature channels
"""
super(InstanceNorm, self).__init__()
self.n... | 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.utils.data
import torch.nn as nn
from torch.nn.parameter import Pa... | doantientai/augmented_cyclegan | InstanceNorm | false | 15,197 | [
"MIT"
] | 133 | 821274577e71c412198356ad6302c982554d558c | https://github.com/doantientai/augmented_cyclegan/tree/821274577e71c412198356ad6302c982554d558c |
normalize | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import... | EVA4-RS-Group/Phase2 | normalize | false | 387 | [
"Apache-2.0"
] | 0 | 7c551e3894979cc425dd51baeddbfa5a51b7878d | https://github.com/EVA4-RS-Group/Phase2/tree/7c551e3894979cc425dd51baeddbfa5a51b7878d |
BasicModel6_MultiTensor | # 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... | aravipati12/captum | BasicModel6_MultiTensor | false | 10,097 | [
"BSD-3-Clause"
] | 0 | ef3e81d89c8c4404a49c384cf0727f2e7d393f5f | https://github.com/aravipati12/captum/tree/ef3e81d89c8c4404a49c384cf0727f2e7d393f5f |
TranslateY | # 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
import torch.nn as ... | Hayoung93/UDA | TranslateY | false | 961 | [
"Apache-2.0"
] | 0 | a587b01c76141d64e7cead55b62e0f3ed75890bf | https://github.com/Hayoung93/UDA/tree/a587b01c76141d64e7cead55b62e0f3ed75890bf |
GlobalAvgPool2d | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
import torch.nn.parallel
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C... | HotaekHan/detr_pytorch | GlobalAvgPool2d | false | 547 | [
"MIT"
] | 0 | 730e02db0ac8910ef782234a3990587771ad67f9 | https://github.com/HotaekHan/detr_pytorch/tree/730e02db0ac8910ef782234a3990587771ad67f9 |
GEGLU | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | idolumbantobing/vit-pytorch | GEGLU | false | 15,573 | [
"MIT"
] | 9,373 | eb70d8dca041cc387b3e1f72d965d8814eeab29a | https://github.com/idolumbantobing/vit-pytorch/tree/eb70d8dca041cc387b3e1f72d965d8814eeab29a |
UpBlock | # 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... | parth-shettiwar/Image-Toonification | UpBlock | false | 12,859 | [
"MIT"
] | 0 | a24d76fa9737558ac38a2fdf23469376f25c0abd | https://github.com/parth-shettiwar/Image-Toonification/tree/a24d76fa9737558ac38a2fdf23469376f25c0abd |
Attention | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | Romero027/ImageCaptioning.pytorch | Attention | false | 4,309 | [
"MIT"
] | 0 | 069c95f5d343fb126afa8b10ec18e472f30b7b35 | https://github.com/Romero027/ImageCaptioning.pytorch/tree/069c95f5d343fb126afa8b10ec18e472f30b7b35 |
ClassificationModel | # 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_... | DvdNss/FaceMaskDetection | ClassificationModel | false | 422 | [
"Apache-2.0"
] | 0 | 3a4efe2bf8fb224d72636c853684a563b4e7a2e4 | https://github.com/DvdNss/FaceMaskDetection/tree/3a4efe2bf8fb224d72636c853684a563b4e7a2e4 |
FiLMLayer | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import math as tl_math
from torch im... | PeterouZh/CIPS-3D | FiLMLayer | false | 14,173 | [
"MIT"
] | 308 | 9b8bfa0fb23f642af042e150ccd70408f9d137c6 | https://github.com/PeterouZh/CIPS-3D/tree/9b8bfa0fb23f642af042e150ccd70408f9d137c6 |
GELU | # 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... | endaaman/augmix | GELU | false | 6,645 | [
"Apache-2.0"
] | 1 | 11c86a126c7b261ca178a715763763ca22b20b81 | https://github.com/endaaman/augmix/tree/11c86a126c7b261ca178a715763763ca22b20b81 |
FocalLoss | import torch
from torch import nn
import torch.nn.functional as F
class FocalLoss(nn.Module):
def __init__(self, alpha=1, gamma=2):
super().__init__()
self.alpha = alpha
self.gamma = gamma
def forward(self, x, y):
ce = F.binary_cross_entropy_with_logits(x, y)
fc = 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 import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
from torch ... | agrawalshubham01/FracNet | FocalLoss | false | 9,714 | [
"Apache-2.0"
] | 0 | 8b912ca65651ff0ee203d9d73cf6ca18539728ac | https://github.com/agrawalshubham01/FracNet/tree/8b912ca65651ff0ee203d9d73cf6ca18539728ac |
SequenceClassifier | import torch
import torch.nn as nn
import torch.nn.functional as F
def transformer_weights_init(module, std_init_range=0.02, xavier=True):
"""
Initialize different weights in Transformer model.
Args:
module: torch.nn.Module to be initialized
std_init_range: standard deviation of normal ini... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | ngxingyu/Domain-Transfer-for-Punctuation-Retrieval | SequenceClassifier | false | 7,340 | [
"Apache-2.0"
] | 1 | f5aa0ea0946c68aaf7fcf49a5085e6c823766a2f | https://github.com/ngxingyu/Domain-Transfer-for-Punctuation-Retrieval/tree/f5aa0ea0946c68aaf7fcf49a5085e6c823766a2f |
Conv | import torch
from torch import nn
class Conv(nn.Module):
def __init__(self, in_channels, out_channels, kernel_size, stride=1,
padding=0, dilation=1, equal_lr=True):
super().__init__()
self.stride = stride
self.padding = padding
self.dilation = dilation
norm_const =... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import 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... | moritztng/stylegan2-pytorch | Conv | false | 4,030 | [
"MIT"
] | 0 | 8827eae2e76c54b7406b34b2d49563ae53b04001 | https://github.com/moritztng/stylegan2-pytorch/tree/8827eae2e76c54b7406b34b2d49563ae53b04001 |
MaxPool2d | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import numpy as np
import torch.nn as nn
from numbers import N... | SaumilShah66/dqn_uav | MaxPool2d | false | 9,579 | [
"MIT"
] | 0 | 2bf780369e964b870624aebcff16c0714cad03c1 | https://github.com/SaumilShah66/dqn_uav/tree/2bf780369e964b870624aebcff16c0714cad03c1 |
GCNLayer | # 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... | ashutoshml/lightning-tutorials | GCNLayer | false | 6,253 | [
"Apache-2.0"
] | 1 | 898b8b6f9852c0b80f034a3187bc1cd34dd521ce | https://github.com/ashutoshml/lightning-tutorials/tree/898b8b6f9852c0b80f034a3187bc1cd34dd521ce |
ConstractiveLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import numpy as np
import to... | kensakurada/SceneChangeDet | ConstractiveLoss | false | 15,791 | [
"MIT"
] | 199 | 0530e0162863fec0c5296188526f0d27e0109814 | https://github.com/kensakurada/SceneChangeDet/tree/0530e0162863fec0c5296188526f0d27e0109814 |
SmoothL1Loss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import torch.utils.dat... | BorisLestsov/retinamask | SmoothL1Loss | false | 13,399 | [
"MIT"
] | 706 | 265a65f018c64220bcea946d306fc7b07a692b16 | https://github.com/BorisLestsov/retinamask/tree/265a65f018c64220bcea946d306fc7b07a692b16 |
Downsample | import torch
import torch.nn as nn
import torch.utils.model_zoo
def avg_pool_nd(dims, *args, **kwargs):
"""
Create a 1D, 2D, or 3D average pooling module.
"""
if dims == 1:
return nn.AvgPool1d(*args, **kwargs)
elif dims == 2:
return nn.AvgPool2d(*args, **kwargs)
elif dims == 3:... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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.model_zoo
assert_size_stride = torch._C... | KamilDeja/guided-diffusion | Downsample | false | 2,448 | [
"MIT"
] | 0 | d0eeeb4637379a3ece40c4dd38ccdf5d8ed5e837 | https://github.com/KamilDeja/guided-diffusion/tree/d0eeeb4637379a3ece40c4dd38ccdf5d8ed5e837 |
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
from torch ... | bobo0810/RepDistiller | DistillKL | false | 10,165 | [
"BSD-2-Clause"
] | 0 | 0a4cea2142221b9b31c8e995920273f5619b37f8 | https://github.com/bobo0810/RepDistiller/tree/0a4cea2142221b9b31c8e995920273f5619b37f8 |
CNN | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
import ... | MarkClemens301/OpenNRE | CNN | false | 9,329 | [
"MIT"
] | 0 | 14c0f77e5716814cba6d651088ec1f1e5d6f7d5c | https://github.com/MarkClemens301/OpenNRE/tree/14c0f77e5716814cba6d651088ec1f1e5d6f7d5c |
SimpleCeilModule | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.jit
import torch.onnx
import torch.nn
assert_size_stride = torch._... | YaronBenAtar/glow | SimpleCeilModule | false | 14,655 | [
"Apache-2.0"
] | 2,838 | a13706a4239fa7eaf059c670dc573e3eb0768f86 | https://github.com/YaronBenAtar/glow/tree/a13706a4239fa7eaf059c670dc573e3eb0768f86 |
SiQU | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_strided_cuda
@triton.j... | Irlirion/ocp | SiQU | false | 13,842 | [
"MIT",
"BSD-3-Clause"
] | 242 | 6fb3e794eef31559db990300198eca20f41d8f37 | https://github.com/Irlirion/ocp/tree/6fb3e794eef31559db990300198eca20f41d8f37 |
SplitConcatNet | # 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.functional
assert_size_stride = torch._C._dynamo.guards.assert_s... | elad-c/model_optimization | SplitConcatNet | false | 10,662 | [
"Apache-2.0"
] | 0 | b0ecf41c3f9434008d57d7fe724ff8585e19d4cc | https://github.com/elad-c/model_optimization/tree/b0ecf41c3f9434008d57d7fe724ff8585e19d4cc |
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
assert_size_stride = torch._C... | Hyunmok-Park/modular-metalearning-master | Net | false | 11,501 | [
"MIT"
] | 0 | a7be61d7c48a62ec8c333b1031521977baed792b | https://github.com/Hyunmok-Park/modular-metalearning-master/tree/a7be61d7c48a62ec8c333b1031521977baed792b |
Downsample | import torch
import torch.nn as nn
def conv_nd(dims, *args, **kwargs):
"""
Create a 1D, 2D, or 3D convolution module.
"""
if dims == 1:
return nn.Conv1d(*args, **kwargs)
elif dims == 2:
return nn.Conv2d(*args, **kwargs)
elif dims == 3:
return nn.Conv3d(*args, **kwargs)
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import 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... | Jack000/improved-diffusion | Downsample | false | 11,532 | [
"MIT"
] | 0 | e2abfc8072f9007b558b697b79d2affdae0eca3b | https://github.com/Jack000/improved-diffusion/tree/e2abfc8072f9007b558b697b79d2affdae0eca3b |
PixWiseBCELoss | import torch
import torch.nn as nn
class PixWiseBCELoss(nn.Module):
def __init__(self, beta=0.5):
super().__init__()
self.criterion = nn.BCELoss()
self.beta = beta
def forward(self, net_mask, net_label, target_mask, target_label):
pixel_loss = self.criterion(net_mask, target_... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice, math as tl_math
import torc... | Clayrisee/BanchelorsProject-FAS | PixWiseBCELoss | false | 295 | [
"MIT"
] | 0 | 3da199fb2e7be04eed7f28374ef753383511dbee | https://github.com/Clayrisee/BanchelorsProject-FAS/tree/3da199fb2e7be04eed7f28374ef753383511dbee |
HLoss | import torch
from torch import nn
import torch.nn.functional as F
class HLoss(nn.Module):
"""
Entropy loss used for entropy maximization.
"""
def __init__(self, ignore_index=-1):
super(HLoss, self).__init__()
self.ignore_index = ignore_index
def forward(self, x, labels):
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | lemon234071/oc_parlai | HLoss | false | 3,883 | [
"MIT"
] | 0 | 33a0e57c48e58903cb1666e367a7bb9ef012de0c | https://github.com/lemon234071/oc_parlai/tree/33a0e57c48e58903cb1666e367a7bb9ef012de0c |
CoralLayer | import torch
import torch.nn as nn
class CoralLayer(nn.Module):
"""Implements CORAL layer
Parameters
-----------
size_in : int
Number of input features for the inputs to the forward method, which
are expected to have shape=(num_examples, num_features).
num_classes : int
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
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | Dineswar11/dretino | CoralLayer | false | 8,964 | [
"MIT"
] | 0 | f6b1e1043a62f88b1853df1bfaada296710223f7 | https://github.com/Dineswar11/dretino/tree/f6b1e1043a62f88b1853df1bfaada296710223f7 |
CAT_TemporalEmbedding | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import math
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guar... | mkmysk123456789/Informer2020 | CAT_TemporalEmbedding | false | 7,254 | [
"Apache-2.0"
] | 1 | ad4b895169a17db580aab6d2c09fd07e06c9b6fa | https://github.com/mkmysk123456789/Informer2020/tree/ad4b895169a17db580aab6d2c09fd07e06c9b6fa |
Transition_nobn | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | daroczyb/tangent_sensitivity | Transition_nobn | false | 10,006 | [
"MIT"
] | 0 | 925258ab381ca5ab95620c411f72836a90baeb7f | https://github.com/daroczyb/tangent_sensitivity/tree/925258ab381ca5ab95620c411f72836a90baeb7f |
MaskIOULoss | import torch
import torch.nn as nn
import torch.utils.data
class MaskIOULoss(nn.Module):
def __init__(self):
super(MaskIOULoss, self).__init__()
def forward(self, pred, target, weight):
total = torch.stack([pred, target], -1)
l_max = total.max(dim=2)[0]
l_min = total.min(dim=... | 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
... | shunya-toyokawa/qanet_human_parts_segmentatiom | MaskIOULoss | false | 16,443 | [
"MIT"
] | 72 | 5527b247acd65534b455c26e3692a14b31669602 | https://github.com/shunya-toyokawa/qanet_human_parts_segmentatiom/tree/5527b247acd65534b455c26e3692a14b31669602 |
ToMono | # 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... | icyda17/very-deep-CNNs | ToMono | false | 10,216 | [
"Apache-2.0"
] | 0 | c275ef222d50dae90e508345ec3be5adfa5e33ce | https://github.com/icyda17/very-deep-CNNs/tree/c275ef222d50dae90e508345ec3be5adfa5e33ce |
Swish | # 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
@triton.jit
def triton_poi_fused_mul_sigmoid_0(in_pt... | Nigel233/Different-Backbones-for-YOLO-v3 | Swish | false | 9,353 | [
"MIT"
] | 0 | 030e7860e966b079afc9b53a320a41f3eb7950be | https://github.com/Nigel233/Different-Backbones-for-YOLO-v3/tree/030e7860e966b079afc9b53a320a41f3eb7950be |
Attention | import torch
import torch.nn as nn
import torch.nn.functional as F
class Attention(nn.Module):
def __init__(self, enc_hid_dim, dec_hid_dim):
super().__init__()
self.enc_hid_dim = enc_hid_dim
self.dec_hid_dim = dec_hid_dim
self.attn = nn.Linear(enc_hid_dim + dec_hid_dim, dec_hid_di... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.... | MaZhanyu007/MSDGAN | Attention | false | 17,660 | [
"MIT"
] | 8 | 037ad33025c29869dbc9cb233a45b8762d31179d | https://github.com/MaZhanyu007/MSDGAN/tree/037ad33025c29869dbc9cb233a45b8762d31179d |
outputCNN | # 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.cuda
import torc... | EricPengShuai/CoLive | outputCNN | false | 11,416 | [
"MIT"
] | 0 | 6e49c3bf204307167a8b7cc1495c6270c7375444 | https://github.com/EricPengShuai/CoLive/tree/6e49c3bf204307167a8b7cc1495c6270c7375444 |
AutoEncoder | # 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... | quickgrid/CodeLab | AutoEncoder | false | 10,718 | [
"MIT"
] | 0 | 710ebf107b7938f09c055e806c1fed5574d91308 | https://github.com/quickgrid/CodeLab/tree/710ebf107b7938f09c055e806c1fed5574d91308 |
PytorchMultiClass | import torch
import torch.nn as nn
import torch.nn.functional as F
class PytorchMultiClass(nn.Module):
def __init__(self, num_features):
super(PytorchMultiClass, self).__init__()
self.layer_1 = nn.Linear(num_features, 80)
self.layer_2 = nn.Linear(80, 100)
self.layer_out = nn.Linea... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | HninPwint/beer_type_prediction | PytorchMultiClass | false | 5,314 | [
"MIT"
] | 1 | 6845920821bedc059dbe92af5c4a7689cb616023 | https://github.com/HninPwint/beer_type_prediction/tree/6845920821bedc059dbe92af5c4a7689cb616023 |
TransformerLayer | import math
import torch
import uuid
from torch import Tensor
from typing import Tuple
import torch.nn as nn
import torch.nn.functional as F
from typing import Optional
from typing import Dict
from torch.nn import Parameter
def gelu(x):
"""Implementation of the gelu activation function.
For information: Open... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | qinwang-ai/Contact-Distil | TransformerLayer | false | 4,193 | [
"Apache-2.0"
] | 0 | 5e98389de70e0d9c4d16bd91ca1326689dc220a6 | https://github.com/qinwang-ai/Contact-Distil/tree/5e98389de70e0d9c4d16bd91ca1326689dc220a6 |
GCNConv | import torch
import torch.nn.functional as F
import torch.nn as nn
class GCNConv(nn.Module):
"""
Description
-----------
GCN convolutional layer.
Parameters
----------
in_features : int
Dimension of input features.
out_features : int
Dimension of output 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.functional as F
import torch.nn as nn
assert_size_stride = torch... | sigeisler/grb | GCNConv | false | 16,452 | [
"MIT"
] | 51 | c89e21076dc05d1edb87dfe2eff20c29ba6bd0c1 | https://github.com/sigeisler/grb/tree/c89e21076dc05d1edb87dfe2eff20c29ba6bd0c1 |
FBACompLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import functools
impor... | yaochaorui/mmediting | FBACompLoss | false | 4,607 | [
"Apache-2.0"
] | 0 | e292abd1f86b1560856d8c4e8c40ababe8a90630 | https://github.com/yaochaorui/mmediting/tree/e292abd1f86b1560856d8c4e8c40ababe8a90630 |
SelfAttnLayer | import torch
import torch.nn as nn
import torch.nn.functional as F
def get_activation_fn(activation):
if activation == 'relu':
return F.relu
elif activation == 'gelu':
return F.gelu
raise RuntimeError('activation should be relu/gelu, not {}'.format(
activation))
class Transformer... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | mensudza/C-Tran | SelfAttnLayer | false | 7,237 | [
"MIT"
] | 1 | 4895ccb0e675ae2dcd2b619a9e47f30707062668 | https://github.com/mensudza/C-Tran/tree/4895ccb0e675ae2dcd2b619a9e47f30707062668 |
SpatialTransformerXPooled3d | import torch
from torch import nn
from torch.nn import Parameter
from torch.nn import functional as F
def positive(weight, cache=None):
weight.data *= weight.data.ge(0).float()
return cache
class SpatialTransformerXPooled3d(nn.Module):
def __init__(self, in_shape, outdims, pool_steps=1, positive=False,... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch import nn
from torch.nn import Parameter
assert_size_stride = torch._C._dynamo... | dattientran/attorch | SpatialTransformerXPooled3d | false | 12,399 | [
"MIT"
] | 0 | 469b225846c6d8a7d833ebac19d040c7a407a0ff | https://github.com/dattientran/attorch/tree/469b225846c6d8a7d833ebac19d040c7a407a0ff |
DQN | # 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_... | alvinwan/explore | DQN | false | 12,092 | [
"MIT"
] | 0 | 358c076b8250f561394e32b1ee2de9bc5562dcdb | https://github.com/alvinwan/explore/tree/358c076b8250f561394e32b1ee2de9bc5562dcdb |
GRUCell | import torch
import torch.nn as nn
from torch.nn import functional as F
class GRUCell(nn.Module):
"""Plain vanilla policy gradient network."""
def __init__(self, obs_size, act_size, hid_size=128):
super().__init__()
self.fc1 = nn.GRUCell(obs_size, hid_size)
self.output = nn.Linear(hid... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
import torch.nn as nn
assert_... | ayjabri/DeepRL | GRUCell | false | 1,512 | [
"MIT"
] | 0 | 0be095e3a3d04f60b4cdc97ed330dffc17b3024a | https://github.com/ayjabri/DeepRL/tree/0be095e3a3d04f60b4cdc97ed330dffc17b3024a |
GatedRNNCell | # 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... | tarepan/HiPPO | GatedRNNCell | false | 16,548 | [
"Apache-2.0"
] | 57 | bc23e2dba13da6c307cb5a4ae248c2d2c56d465f | https://github.com/tarepan/HiPPO/tree/bc23e2dba13da6c307cb5a4ae248c2d2c56d465f |
ArcFace | # 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.... | wangxianliang/FaceX-Zoo | ArcFace | false | 13,092 | [
"Apache-2.0"
] | 0 | b0555c88a0350fa7b59c317f3a171f551fef4e6e | https://github.com/wangxianliang/FaceX-Zoo/tree/b0555c88a0350fa7b59c317f3a171f551fef4e6e |
StandardNLL | import torch
import torch.multiprocessing
import torch.utils.data
class StandardNLL(torch.nn.modules.loss._Loss):
"""
Shape:
log_prob: batch x time x class
y_true: batch x time
mask: batch x time
output: batch
"""
def forward(self, log_prob, y_true, mas... | 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.multiprocessing
import torch.utils.data
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = to... | WuDiDaBinGe/TAKG | StandardNLL | false | 1,217 | [
"MIT"
] | 0 | 83e608e677a4ee74722d18cb5ef430f4f6c6ad31 | https://github.com/WuDiDaBinGe/TAKG/tree/83e608e677a4ee74722d18cb5ef430f4f6c6ad31 |
LayerNorm | import torch
import torch.nn as nn
class LayerNorm(nn.LayerNorm):
def __init__(self, normalized_shape, eps=1e-05, elementwise_affine=True):
"""Layer Norm."""
super(LayerNorm, self).__init__(normalized_shape, eps=eps,
elementwise_affine=elementwise_affine)
def forward(self, x):
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_... | TraceOnBrainOff/pytorch-dc-tts | LayerNorm | false | 18,006 | [
"MIT"
] | 4 | 993a0fbace561729b04df2179b41a0a7ea502e93 | https://github.com/TraceOnBrainOff/pytorch-dc-tts/tree/993a0fbace561729b04df2179b41a0a7ea502e93 |
Attention | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import Parameter
def new_parameter(*size):
out = Parameter(torch.FloatTensor(*size))
torch.nn.init.xavier_normal_(out)
return out
class Attention(nn.Module):
def __init__(self, attention_size):
super(Attention,... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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.... | Danil328/Comment-classification | Attention | false | 8,960 | [
"Apache-2.0"
] | 0 | 5b355458d7f1fc28921e0df6257564db3da63201 | https://github.com/Danil328/Comment-classification/tree/5b355458d7f1fc28921e0df6257564db3da63201 |
OneDilate | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.nn as nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | williamyang1991/DeepPS | OneDilate | false | 11,093 | [
"MIT"
] | 0 | f3eb6ba4b0f2ef068361a4bbbd3d6c2c2f6726b4 | https://github.com/williamyang1991/DeepPS/tree/f3eb6ba4b0f2ef068361a4bbbd3d6c2c2f6726b4 |
RoundPass | import torch
import torch as t
import torch.utils.data
class RoundPass(t.nn.Module):
def forward(self, x):
y = x.round()
y_grad = x
return (y - y_grad).detach() + y_grad
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
import torch as t
import torch.utils.data
assert_size_stride = torch._C._dynamo... | HumberMe/lsq-net | RoundPass | false | 544 | [
"MIT"
] | 0 | 7dcd75bff4aa7ff2d9c8a7902198fe411a38eb4c | https://github.com/HumberMe/lsq-net/tree/7dcd75bff4aa7ff2d9c8a7902198fe411a38eb4c |
SimpleGate | # 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.cuda
import torch.distributed
assert_size_stride = torch._C._dynamo... | chardmeier/OpenNMT-py | SimpleGate | false | 3,277 | [
"MIT"
] | 0 | 8ef64d10c507418102af42551c0f335270cb5b51 | https://github.com/chardmeier/OpenNMT-py/tree/8ef64d10c507418102af42551c0f335270cb5b51 |
MedianPool2d | # 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
from torch.nn.modules.utils import _pair
from torch... | jammer345/3DGNN_pytorch | MedianPool2d | false | 15,670 | [
"MIT"
] | 231 | 34a5b3890f23e03fa6cc316c79498eeaea635664 | https://github.com/jammer345/3DGNN_pytorch/tree/34a5b3890f23e03fa6cc316c79498eeaea635664 |
BCE_disc_sm_v4 | # AOT ID: ['2_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... | Sampson-Lee/SIB-Net | BCE_disc_sm_v4 | false | 2,833 | [
"MIT"
] | 0 | 650399082e9237327fa38168ccfc7d48153a1db5 | https://github.com/Sampson-Lee/SIB-Net/tree/650399082e9237327fa38168ccfc7d48153a1db5 |
SelfGating | import torch
import torch.utils.data
import torch as th
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data.distributed
class SelfGating(nn.Module):
def __init__(self, input_dim):
super(SelfGating, self).__init__()
self.fc = nn.Linear(input_dim, input_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
import torch.utils.data
import torch.nn as nn
import torch.nn.parallel
import to... | bryant1410/MIL-NCE_HowTo100M | SelfGating | false | 1,578 | [
"Apache-2.0"
] | 0 | 9ba876bd67160e24a5ce379a07d18a8036be0d36 | https://github.com/bryant1410/MIL-NCE_HowTo100M/tree/9ba876bd67160e24a5ce379a07d18a8036be0d36 |
BalancedL1Loss | import functools
import torch
import numpy as np
import torch.nn.functional as F
import torch.nn as nn
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Return:
Tenso... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import math as tl_math
import functools
impor... | ChHanXiao/mmdetection | BalancedL1Loss | false | 9,146 | [
"Apache-2.0"
] | 0 | 324aa5a042857a9b57abe37385e1210709a20d02 | https://github.com/ChHanXiao/mmdetection/tree/324aa5a042857a9b57abe37385e1210709a20d02 |
ISAB | 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.... | KohavTal/SCAE_Project | ISAB | false | 8,416 | [
"Apache-2.0"
] | 40 | bc6d1c3697fcb9327dd96e9657c3299b47cf355e | https://github.com/KohavTal/SCAE_Project/tree/bc6d1c3697fcb9327dd96e9657c3299b47cf355e |
LinkClassifier | # 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.... | BlackReap-er/Sia | LinkClassifier | false | 7,801 | [
"MIT"
] | 13 | 70654d55caa3315187282c88a59cf9b6e0b7c52b | https://github.com/BlackReap-er/Sia/tree/70654d55caa3315187282c88a59cf9b6e0b7c52b |
PlainRefiner | import torch
import torch.nn as nn
class PlainRefiner(nn.Module):
"""Simple refiner from Deep Image Matting.
Args:
conv_channels (int): Number of channels produced by the three main
convolutional layer.
loss_refine (dict): Config of the loss of the refiner. Default: None.
... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | Juggernaut93/mmediting | PlainRefiner | false | 13,910 | [
"Apache-2.0"
] | 1,884 | 8ef46ace29756dd2df1d92f2f73a33646e33e007 | https://github.com/Juggernaut93/mmediting/tree/8ef46ace29756dd2df1d92f2f73a33646e33e007 |
Net | import math
import torch
import torch.nn as nn
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
for m in self.modules():
if isinstance(m, nn.Conv2d):
n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels
m.weight.data.normal_(0, ... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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... | Groenbech96/Learning-to-See-in-the-Dark | Net | false | 5,319 | [
"MIT"
] | 1 | a068c8642a651e4af195cd71e253694d88dfe3c5 | https://github.com/Groenbech96/Learning-to-See-in-the-Dark/tree/a068c8642a651e4af195cd71e253694d88dfe3c5 |
LearnedPositionalEncoding | # AOT ID: ['0_forward']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _alig... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
from torch import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_s... | minhnn-tiny/vietocr | LearnedPositionalEncoding | false | 16,097 | [
"Apache-2.0"
] | 307 | 80ed99b5d29df3f04c54ae394c525117846b503a | https://github.com/minhnn-tiny/vietocr/tree/80ed99b5d29df3f04c54ae394c525117846b503a |
AffineConstantFlow | import torch
import torch.nn as nn
class AffineConstantFlow(nn.Module):
"""
Scales + Shifts the flow by (learned) constants per dimension.
In NICE paper there is a Scaling layer which is a special case of this where t is None
"""
def __init__(self, dim, scale=True, shift=True):
super(Affi... | 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... | MattiaVarrone/nnest | AffineConstantFlow | false | 830 | [
"MIT"
] | 0 | 9e12be0135ba2e7fa186a904bc33480c3b0c655a | https://github.com/MattiaVarrone/nnest/tree/9e12be0135ba2e7fa186a904bc33480c3b0c655a |
FiLMLayerEqualFC | import math
import torch
import torch.nn.functional as F
from torch import nn
class EqualLinear(nn.Module):
def __init__(self, in_dim, out_dim, bias=True, bias_init=0, lr_mul=1.0,
activation=None):
"""
:param in_dim:
:param out_dim:
:param bias:
:param bias_init:
:param lr_mu... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language 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 math
i... | PeterouZh/CIPS-3D | FiLMLayerEqualFC | false | 14,178 | [
"MIT"
] | 308 | 9b8bfa0fb23f642af042e150ccd70408f9d137c6 | https://github.com/PeterouZh/CIPS-3D/tree/9b8bfa0fb23f642af042e150ccd70408f9d137c6 |
Generator | import torch
from torch import nn
import torch.utils.data
class Generator(nn.Module):
def __init__(self):
super(Generator, self).__init__()
self.relu = nn.ReLU(inplace=True)
self.e_conv1 = nn.Conv2d(3, 3, 1, 1, 0, bias=True)
self.e_conv2 = nn.Conv2d(3, 3, 3, 1, 1, bias=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
from torch._inductor.runtime import triton_helpers
from torch import nn
import t... | goldenbili/SRGAN_Test | Generator | false | 10,198 | [
"MIT"
] | 0 | 06705c92abd5b7084ae878a4746060760bcff5c3 | https://github.com/goldenbili/SRGAN_Test/tree/06705c92abd5b7084ae878a4746060760bcff5c3 |
down_shifted_conv2d | import torch
import torch.nn as nn
from torch.nn.utils import weight_norm as wn
def down_shift(x, pad=None):
xs = [int(y) for y in x.size()]
x = x[:, :, :xs[2] - 1, :]
pad = nn.ZeroPad2d((0, 0, 1, 0)) if pad is None else pad
return pad(x)
class down_shifted_conv2d(nn.Module):
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._inductor.runtime.triton_helpers import libdevice
import torch.nn as ... | elahekhodaie/PixelCnnPP | down_shifted_conv2d | false | 10,100 | [
"MIT"
] | 0 | ab1e245ed8c24009364b1f891288eb1a526b0121 | https://github.com/elahekhodaie/PixelCnnPP/tree/ab1e245ed8c24009364b1f891288eb1a526b0121 |
SqueezeAndExcitationModule | import torch
import torch.nn as nn
import torch.nn.functional as F
class Swish(nn.Module):
def __init__(self):
super(Swish, self).__init__()
def forward(self, x):
return x * x.sigmoid()
class Conv1d(nn.Conv1d):
def __init__(self, in_channels, out_channels, kernel_size, 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 ... | gheyret/EfficientConformer | SqueezeAndExcitationModule | false | 15,436 | [
"Apache-2.0"
] | 101 | b28a0aaa3b182f72abaccbeb12df0402adf96097 | https://github.com/gheyret/EfficientConformer/tree/b28a0aaa3b182f72abaccbeb12df0402adf96097 |
Upsample | # 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... | ZGCTroy/guided-diffusion | Upsample | false | 1,290 | [
"MIT"
] | 0 | af987bb2b65db2875148a5466df79736ea5ae6a1 | https://github.com/ZGCTroy/guided-diffusion/tree/af987bb2b65db2875148a5466df79736ea5ae6a1 |
series_decomp_multi | # 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.... | MAZiqing/FEDformer | series_decomp_multi | false | 17,652 | [
"MIT"
] | 7 | 7914d39df829494a8172afb9676982c3789d491d | https://github.com/MAZiqing/FEDformer/tree/7914d39df829494a8172afb9676982c3789d491d |
CapsuleLoss | # 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... | Xiangs18/CapsNet | CapsuleLoss | false | 2,967 | [
"MIT"
] | 0 | 79cd0ed1e726750968cd8658370f78aa86a62170 | https://github.com/Xiangs18/CapsNet/tree/79cd0ed1e726750968cd8658370f78aa86a62170 |
SPPblock | import torch
import torch.nn as nn
import torch.nn.functional as F
class SPPblock(nn.Module):
def __init__(self, in_channels):
super(SPPblock, self).__init__()
self.pool1 = nn.MaxPool2d(kernel_size=[2, 2], stride=2)
self.pool2 = nn.MaxPool2d(kernel_size=[3, 3], stride=3)
self.pool... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | JACKYLUO1991/HybridNet | SPPblock | false | 17,522 | [
"Apache-2.0"
] | 6 | eb97d8a048ca4bb4087bc542360172e169a08dbf | https://github.com/JACKYLUO1991/HybridNet/tree/eb97d8a048ca4bb4087bc542360172e169a08dbf |
Bar | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
import torch.onnx
import torch.nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guar... | geoffberry/glow | Bar | false | 12,415 | [
"Apache-2.0"
] | 0 | 24b2827c830eb58af56a0704e899968026832e9c | https://github.com/geoffberry/glow/tree/24b2827c830eb58af56a0704e899968026832e9c |
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
import torch.... | ThomasRigoni7/Audio-emotion-recognition-RAVDESS | Encoder | false | 17,992 | [
"MIT"
] | 5 | ae44256edfcb320a32696444cd301264e1800866 | https://github.com/ThomasRigoni7/Audio-emotion-recognition-RAVDESS/tree/ae44256edfcb320a32696444cd301264e1800866 |
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.... | BUPT-GAMMA/OpenHGNN | SelfAttention | false | 13,403 | [
"Apache-2.0"
] | 235 | 5f218dad4ed1415aa6d842bc20785c61e74e5405 | https://github.com/BUPT-GAMMA/OpenHGNN/tree/5f218dad4ed1415aa6d842bc20785c61e74e5405 |
MedianPool2d | # 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
from torch.nn.modules.utils import _pair
from torch... | Arnakii/invertinggradients | MedianPool2d | false | 8,871 | [
"MIT"
] | 0 | c4f66fc9c73f0a18e9ddf01650c0e82fe3998013 | https://github.com/Arnakii/invertinggradients/tree/c4f66fc9c73f0a18e9ddf01650c0e82fe3998013 |
GNN_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
from torch.nn import Module
i... | Zhen-Tan-dmml/GFCIL | GNN_Encoder | false | 18,174 | [
"MIT"
] | 7 | 9b78210418711a795280c588f55aef63f7df5b3b | https://github.com/Zhen-Tan-dmml/GFCIL/tree/9b78210418711a795280c588f55aef63f7df5b3b |
PSNRLoss | # AOT ID: ['0_inference']
from ctypes import c_void_p, c_long, c_int
import torch
import math
import random
import os
import tempfile
from math import inf, nan
from torch._inductor.hooks import run_intermediate_hooks
from torch._inductor.utils import maybe_profile
from torch._inductor.codegen.memory_planning import _al... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
from t... | IEM-Computer-Vision/kornia | PSNRLoss | false | 9,261 | [
"ECL-2.0",
"Apache-2.0"
] | 0 | f98bd9a2158a6e59cda076d55d476acf13f4e0af | https://github.com/IEM-Computer-Vision/kornia/tree/f98bd9a2158a6e59cda076d55d476acf13f4e0af |
ConvBlock | # 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 ... | AjaybirRandhawa/Face-Generator | ConvBlock | false | 18,428 | [
"Apache-2.0"
] | 2 | 9cac0822b6e6337c3599e949154ce44eeae5746b | https://github.com/AjaybirRandhawa/Face-Generator/tree/9cac0822b6e6337c3599e949154ce44eeae5746b |
TorchModule | import torch
import torch.nn
class TorchLinearModule(torch.nn.Module):
def __init__(self, in_size, out_size):
super(TorchLinearModule, self).__init__()
self._linear = torch.nn.Linear(in_size, out_size)
def forward(self, x):
return self._linear(x)
class TorchModule(torch.nn.Module):... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn
ass... | VedPatwardhan/ivy | TorchModule | false | 5,935 | [
"Apache-2.0"
] | 1 | 7b2105fa8cf38879444a1029bfaa7f0b2f27717a | https://github.com/VedPatwardhan/ivy/tree/7b2105fa8cf38879444a1029bfaa7f0b2f27717a |
SageLayer | import torch
import torch.nn as nn
import torch.nn.functional as F
class SageLayer(nn.Module):
"""
一层SageLayer
"""
def __init__(self, input_size, out_size, gcn=False):
super(SageLayer, self).__init__()
self.input_size = input_size
self.out_size = out_size
self.gcn = gc... | import torch
from torch._inductor.select_algorithm import extern_kernels
import triton
import triton.language as tl
from 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_... | OuYangg/GNNs | SageLayer | false | 9,456 | [
"Apache-2.0"
] | 0 | ef5b1944490507684d603de3ae0b2aa7b5168f47 | https://github.com/OuYangg/GNNs/tree/ef5b1944490507684d603de3ae0b2aa7b5168f47 |
HardSigmoid | # 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 import nn
assert_size_stride = torch._C._dynamo.guards.assert_size_stride
empty_strided_cuda = torch._C._dynamo.guards._empty_str... | gentlebreeze1/dbnet | HardSigmoid | false | 3,530 | [
"Apache-2.0"
] | 0 | be28a7ae835af7d6f8b7c2b636b875adc9fc187c | https://github.com/gentlebreeze1/dbnet/tree/be28a7ae835af7d6f8b7c2b636b875adc9fc187c |
Norm | import torch
import torch.nn as nn
import torch.nn.parallel
import torch.optim
import torch.utils.data
from torch.optim.lr_scheduler import *
import torch.optim.lr_scheduler
import torch.quantization
import torch.onnx
import torch.testing
class Norm(nn.Module):
"""
A module wrapper for vector/matrix norm
... | import torch
import triton
import triton.language as tl
from torch._inductor.runtime.triton_heuristics import grid
from torch._C import _cuda_getCurrentRawStream as get_raw_stream
from torch._inductor.runtime import triton_helpers
from torch._inductor.runtime.triton_helpers import libdevice
import torch.nn as nn
import... | Donfa1con/distiller | Norm | false | 11,529 | [
"Apache-2.0"
] | 0 | 645ee41bfebc463523b228ff087e41619607d8b2 | https://github.com/Donfa1con/distiller/tree/645ee41bfebc463523b228ff087e41619607d8b2 |
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