repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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tlp | tlp-main/scripts/tlp_make_dataset.py | import torch
import os
import glob
import json
import pickle
from random import random
from tvm import auto_scheduler
from common import (load_and_register_tasks, get_measure_record_filename, get_to_measure_filename)
import threading
import multiprocessing
from tvm.tir.expr import FloatImm
import numpy as np
import ran... | 7,331 | 32.788018 | 136 | py |
tlp | tlp-main/scripts/tlp_fine_tune.py | import os
import pickle
import torch
import time
import numpy as np
import random
import math
from torch import nn
from torch import optim
import argparse
class AttentionModule(nn.Module):
def __init__(self):
super().__init__()
self.fea_size = args.fea_size
self.step_size = args.step_siz... | 12,727 | 34.752809 | 105 | py |
tlp | tlp-main/scripts/train_model.py | """Train a cost model with a dataset."""
import argparse
import logging
import pickle
import random
import torch
import numpy as np
import tvm
from tvm.auto_scheduler.utils import to_str_round
from tvm.auto_scheduler.cost_model import RandomModelInternal
from common import load_and_register_tasks, str2bool
from tv... | 5,926 | 31.927778 | 100 | py |
tlp | tlp-main/scripts/nni_hyperparameter_opt.py | """Train a cost model with a dataset."""
import argparse
import logging
import pickle
import random
import multiprocessing
import nni
import torch
import numpy as np
import tvm
from tvm.auto_scheduler.utils import to_str_round
from tvm.auto_scheduler.cost_model import RandomModelInternal
from common import load_an... | 6,092 | 31.238095 | 100 | py |
tlp | tlp-main/scripts/tlp_train.py | import os
import pickle
import torch
import time
import numpy as np
import random
import math
from torch import nn
from torch import optim
import argparse
def get_cosine_schedule_with_warmup(
optimizer: optim.Optimizer,
num_warmup_steps: int,
num_training_steps: int,
num_cycles: float = 0.5,
last_epoch: int = -1... | 26,402 | 33.156533 | 113 | py |
tlp | tlp-main/scripts/common.py | from collections import defaultdict, namedtuple
import pickle
import tvm
from tvm import relay, auto_scheduler
from tvm.auto_scheduler.utils import to_str_round
####################################
##### Network Utilities
####################################
def convert_to_nhwc(mod):
"""Convert to NHWC layout"""
... | 2,921 | 28.22 | 84 | py |
tlp | tlp-main/scripts/tlp_eval.py | import pickle
import numpy as np
import torch
import argparse
from tlp_train import *
from mtl_tlp_train import MTLTLPAttentionModule
top_ks = [1, 5, 10, 20]
def pred_a_dataset(datas, task_pred_dict, model):
datas_new = []
for data_idx, data in enumerate([datas]):
file, file_idx, workloadkey_idx, w... | 4,916 | 36.25 | 107 | py |
tlp | tlp-main/scripts/dump_network_info.py | """Dump relay IR and task information for networks"""
import argparse
from collections import namedtuple
import gc
import glob
import multiprocessing
import os
import pickle
from tqdm import tqdm
import tvm
from tvm import relay
from tvm import auto_scheduler
from common import (convert_to_nhwc, dtype2torch, NETWOR... | 8,740 | 35.26971 | 106 | py |
tlp | tlp-main/scripts/mtl_tlp_train.py | import os
import pickle
import torch
import time
import numpy as np
import random
from torch import nn
from torch import optim
import argparse
class MTLTLPAttentionModule(nn.Module):
def __init__(self):
super().__init__()
self.fea_size = args.fea_size
self.step_size = args.step_size
... | 14,420 | 37.050132 | 197 | py |
tlp | tlp-main/scripts/minGPT/gpt_model.py | import torch
from .mingpt.model import GPT, GPTConfig
from torch import nn
class gpt_args:
pass
class GPUModel:
def __init__(self, self_sup_model) -> None:
vocab_size = 42336
args = gpt_args()
args.block_size = 24
args.one_hot_len = 12
args.type_loss_factor = 10
... | 899 | 30.034483 | 68 | py |
tlp | tlp-main/scripts/minGPT/train_gpt.py | import pickle
import logging
import torch
import torch.nn as nn
from mingpt.model import GPT, GPTConfig
from mingpt.trainer import Trainer, TrainerConfig
from mingpt.utils import set_seed
import argparse
set_seed(42)
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s",
datefmt... | 3,816 | 31.905172 | 126 | py |
tlp | tlp-main/scripts/minGPT/mingpt/utils.py | import random
import numpy as np
import torch
import torch.nn as nn
from torch.nn import functional as F
def set_seed(seed):
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
torch.cuda.manual_seed_all(seed)
def top_k_logits(logits, k):
v, ix = torch.topk(logits, k)
out = logits.c... | 1,718 | 34.8125 | 95 | py |
tlp | tlp-main/scripts/minGPT/mingpt/model.py | """
GPT model:
- the initial stem consists of a combination of token encoding and a positional encoding
- the meat of it is a uniform sequence of Transformer blocks
- each Transformer is a sequential combination of a 1-hidden-layer MLP block and a self-attention block
- all blocks feed into a central residual p... | 9,253 | 42.04186 | 138 | py |
tlp | tlp-main/scripts/minGPT/mingpt/trainer.py | """
Simple training loop; Boilerplate that could apply to any arbitrary neural network,
so nothing in this file really has anything to do with GPT specifically.
"""
import math
import logging
from tqdm import tqdm
import numpy as np
import torch
import torch.optim as optim
from torch.optim.lr_scheduler import Lambda... | 5,775 | 38.561644 | 140 | py |
tlp | tlp-main/scripts/bert/bert_model.py | import torch
from transformers import RobertaConfig, RobertaForMaskedLM, AdamW
from torch import nn
class BertModel:
def __init__(self, self_sup_model) -> None:
########### RobertaConfig
config = RobertaConfig(
vocab_size=42335 + 3, # we align this to the tokenizer vocab_size... | 856 | 25.78125 | 78 | py |
tlp | tlp-main/scripts/bert/train_bert.py | import argparse
import pickle
from transformers import RobertaConfig, RobertaForMaskedLM, AdamW
import torch
from torch import nn
from tqdm.auto import tqdm
import math
class BertSegmentDataLoader:
def __init__(
self,
dataset,
batch_size,
shuffle,
):
self... | 5,812 | 32.028409 | 114 | py |
tlp | tlp-main/nnvm/amalgamation/amalgamation.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 3,549 | 25.893939 | 99 | py |
tlp | tlp-main/tests/python/conftest.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 1,922 | 43.72093 | 92 | py |
tlp | tlp-main/tests/python/unittest/test_custom_datatypes.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 17,978 | 30.934281 | 142 | py |
tlp | tlp-main/tests/python/unittest/test_autotvm_xgboost_model.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 2,068 | 27.736111 | 82 | py |
tlp | tlp-main/tests/python/driver/tvmc/conftest.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 6,048 | 32.41989 | 99 | py |
tlp | tlp-main/tests/python/driver/tvmc/test_frontends.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 7,563 | 35.019048 | 96 | py |
tlp | tlp-main/tests/python/driver/tvmc/test_compiler.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 7,998 | 33.627706 | 97 | py |
tlp | tlp-main/tests/python/frontend/mxnet/test_qnn_ops_utils.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 7,755 | 33.471111 | 99 | py |
tlp | tlp-main/tests/python/frontend/mxnet/test_forward.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 92,936 | 38.716667 | 104 | py |
tlp | tlp-main/tests/python/frontend/mxnet/test_graph.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 3,841 | 29.983871 | 80 | py |
tlp | tlp-main/tests/python/frontend/mxnet/model_zoo/resnet.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 10,688 | 31.688073 | 100 | py |
tlp | tlp-main/tests/python/frontend/mxnet/model_zoo/squeezenet.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 3,892 | 38.72449 | 96 | py |
tlp | tlp-main/tests/python/frontend/mxnet/model_zoo/vgg.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 4,491 | 40.211009 | 98 | py |
tlp | tlp-main/tests/python/frontend/mxnet/model_zoo/mlp.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 1,950 | 45.452381 | 100 | py |
tlp | tlp-main/tests/python/frontend/mxnet/model_zoo/dqn.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 1,745 | 40.571429 | 93 | py |
tlp | tlp-main/tests/python/frontend/mxnet/model_zoo/dcgan.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 3,190 | 33.684783 | 98 | py |
tlp | tlp-main/tests/python/frontend/mxnet/model_zoo/inception_v3.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 11,306 | 29.642276 | 127 | py |
tlp | tlp-main/tests/python/frontend/caffe2/test_forward.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 7,882 | 30.035433 | 100 | py |
tlp | tlp-main/tests/python/frontend/caffe2/test_graph.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 1,507 | 34.904762 | 81 | py |
tlp | tlp-main/tests/python/frontend/caffe2/model_zoo/__init__.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 1,497 | 29.571429 | 90 | py |
tlp | tlp-main/tests/python/frontend/tflite/test_forward.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 154,612 | 34.864765 | 135 | py |
tlp | tlp-main/tests/python/frontend/onnx/test_forward.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 141,914 | 32.813438 | 100 | py |
tlp | tlp-main/tests/python/frontend/keras/test_forward.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 26,378 | 42.032626 | 99 | py |
tlp | tlp-main/tests/python/frontend/caffe/test_forward.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 27,553 | 28.917481 | 99 | py |
tlp | tlp-main/tests/python/frontend/pytorch/test_lstm.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 13,044 | 34.161725 | 111 | py |
tlp | tlp-main/tests/python/frontend/pytorch/test_forward.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 128,492 | 31.529873 | 115 | py |
tlp | tlp-main/tests/python/frontend/pytorch/qnn_test.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 20,687 | 32.803922 | 123 | py |
tlp | tlp-main/tests/python/frontend/pytorch/test_object_detection.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 5,259 | 30.878788 | 91 | py |
tlp | tlp-main/tests/python/frontend/tensorflow/test_forward.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 191,571 | 34.118607 | 113 | py |
tlp | tlp-main/tests/python/nightly/quantization/test_quantization_accuracy.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 6,803 | 30.5 | 126 | py |
tlp | tlp-main/tests/python/contrib/test_dlpack.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 2,256 | 33.723077 | 82 | py |
tlp | tlp-main/tests/python/contrib/test_tensorrt.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 48,785 | 34.766862 | 133 | py |
tlp | tlp-main/tests/python/contrib/test_mxnet_bridge.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 2,038 | 30.859375 | 81 | py |
tlp | tlp-main/tests/python/contrib/test_arm_compute_lib/test_network.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 5,647 | 29.695652 | 135 | py |
tlp | tlp-main/vta/tutorials/frontend/deploy_classification.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 11,496 | 38.644828 | 100 | py |
tlp | tlp-main/vta/tutorials/autotvm/tune_relay_vta.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 21,420 | 40.756335 | 322 | py |
tlp | tlp-main/vta/scripts/tune_resnet.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 11,949 | 33.240688 | 98 | py |
tlp | tlp-main/docs/conf.py | # -*- coding: utf-8 -*-
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# ... | 12,868 | 30.235437 | 92 | py |
tlp | tlp-main/rust/tvm/examples/resnet/src/build_resnet.py | #!/usr/bin/env python3
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "L... | 5,391 | 33.126582 | 100 | py |
tlp | tlp-main/3rdparty/vta-hw/apps/deploy/resnet_export.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 5,296 | 38.827068 | 98 | py |
tlp | tlp-main/3rdparty/dmlc-core/tracker/dmlc_tracker/opts.py | # pylint: disable=invalid-name
"""Command line options of job submission script."""
import os
import argparse
def get_cache_file_set(args):
"""Get the list of files to be cached.
Parameters
----------
args: ArgumentParser.Argument
The arguments returned by the parser.
Returns
-------
... | 9,424 | 51.071823 | 110 | py |
tlp | tlp-main/3rdparty/dmlc-core/doc/conf.py | # -*- coding: utf-8 -*-
#
# documentation build configuration file, created by
# sphinx-quickstart on Thu Jul 23 19:40:08 2015.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All confi... | 5,609 | 32.795181 | 88 | py |
met | met-master/code/networks/SiameseNet.py | import torch.nn as nn
from code.networks.backbone import Embedder
class siamese_network(nn.Module):
'''Network architecture for contrastive learning.
'''
def __init__(self,backbone,pooling = "gem",pretrained = True,
emb_proj = False,init_emb_projector= None):
super(siamese_network,self).__init__()
n... | 686 | 23.535714 | 70 | py |
met | met-master/code/networks/backbone.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.parameter import Parameter
import torchvision.models as models
OUTPUT_DIM = {
'resnet18' : 512,
'resnet50' : 2048,
'r18_sw-sup' : 512,
}
class GeM(nn.Module):
'''Credits to Filip Radenovic ... | 4,008 | 26.087838 | 126 | py |
met | met-master/code/examples/train_contrastive.py | import argparse
import os
import sys
import pickle
import math
import numpy as np
from code.utils.train_utils import *
from code.networks.SiameseNet import *
from code.utils.datasets import *
from code.utils.utils import *
from code.utils.losses import *
from code.utils.augmentations import augmentation
import torch... | 10,186 | 38.332046 | 147 | py |
met | met-master/code/examples/extract_descriptors.py | import os
import sys
import pickle
import json
import numpy as np
import argparse
from collections import OrderedDict
import torch
from torchvision import transforms
from torch.utils.model_zoo import load_url
from code.utils.datasets import *
from code.utils.utils import *
from code.networks.backbone import *
from co... | 7,872 | 34.786364 | 263 | py |
met | met-master/code/utils/losses.py | import torch
import torch.nn as nn
import torch.nn.functional as F
class ContrastiveLoss(nn.Module):
'''Contrastive loss.
Takes as inputs the embeddings of two samples and a target label == 1 if samples come
from the same class or 0 otherwise.
Credits to https://github.com/adambielski/siamese-triple... | 835 | 28.857143 | 111 | py |
met | met-master/code/utils/augmentations.py | from torchvision import transforms
def augmentation(key,imsize = 500):
'''Using ImageNet statistics for normalization.
'''
augment_dict = {
"augment_train":
transforms.Compose([
transforms.RandomResizedCrop(imsize, scale=(0.7,1.0),ratio = (0.99,1/0.99)),
transforms.RandomApply([transforms.ColorJitt... | 700 | 22.366667 | 80 | py |
met | met-master/code/utils/utils.py | import torch
import numpy as np
from code.networks.backbone import *
def gap(pred, score, class_ids):
'''Implementation of the GAP metric described in the paper.
Expects everything as np array.
'''
rel = np.zeros(len(pred)) #rel is the binary indicator, 1 if correct prediction, 0 if false
rel ... | 4,248 | 25.067485 | 109 | py |
met | met-master/code/utils/train_utils.py | import sys
import math
import faiss
import numpy as np
import torch
import torch.nn as nn
from code.utils.utils import *
from code.classifiers.knn_classifier import *
def train_contrastive_1epoch_virtual(model,criterion,optimizer,train_loader,epoch,vbsizemul):
'''Train model with the contrastive loss for one-epo... | 5,078 | 23.77561 | 109 | py |
met | met-master/code/utils/datasets.py | import os
import os.path
import json
import pickle
import numpy as np
from typing import Any, Callable, cast, Dict, List, Optional, Tuple
from torch.utils.data import Dataset
from torchvision.datasets.vision import VisionDataset
from torchvision.datasets.folder import default_loader
from code.utils.train_utils import... | 9,873 | 29.475309 | 129 | py |
tkMapper | tkMapper-master/docs/conf.py | # -*- coding: utf-8 -*-
#
# KeplerMapper documentation build configuration file, created by
# sphinx-quickstart on Mon Feb 19 11:19:26 2018.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
... | 6,044 | 29.530303 | 133 | py |
tkMapper | tkMapper-master/depricated/km.py | from __future__ import division
import numpy as np
from collections import defaultdict
import json
import itertools
from sklearn import cluster, preprocessing, manifold
from datetime import datetime
import sys
class KeplerMapper(object):
def __init__(self, cluster_algorithm=cluster.DBSCAN(eps=0.5,min_samples=3), nr_... | 13,395 | 41.526984 | 336 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/main.py | """
Teacher free KD, main.py
"""
import argparse
import logging
import os
import random
import warnings
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
import utils
import model.net as net
import data_loader as data_loader
import model.resnet as resnet
import model.mobilenetv2 as mobi... | 13,805 | 46.771626 | 130 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/evaluate.py | """Evaluates the model"""
import argparse
import logging
from torch.autograd import Variable
import utils
parser = argparse.ArgumentParser()
parser.add_argument('--model_dir', default='experiments/base_model', help="Directory of params.json")
parser.add_argument('--restore_file', default='best', help="name of the fi... | 3,972 | 37.95098 | 113 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/my_loss_function.py | import torch
import torch.nn as nn
import torch.nn.functional as F
def loss_kd(outputs, labels, teacher_outputs, params):
"""
loss function for Knowledge Distillation (KD)
"""
alpha = params.alpha
T = params.temperature
loss_CE = F.cross_entropy(outputs, labels)
D_KL = nn.KLDivLoss()(F.lo... | 2,212 | 31.544118 | 186 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/train_kd.py | import os
import time
import math
import utils
from tqdm import tqdm
import logging
from torch.autograd import Variable
from evaluate import evaluate, evaluate_kd
from tensorboardX import SummaryWriter
from torch.optim.lr_scheduler import StepLR, MultiStepLR
# KD train and evaluate
def train_and_evaluate_kd(model, tea... | 9,755 | 37.258824 | 142 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/data_loader.py | """
CIFAR-10 CIFAR-100, Tiny-ImageNet data loader
"""
import random
import os
import numpy as np
from PIL import Image
import torch
import torchvision
import torchvision.transforms as transforms
from torch.utils.data.sampler import SubsetRandomSampler
def fetch_dataloader(types, params):
"""
Fetch and retu... | 6,917 | 43.922078 | 160 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/utils.py | """
Tensorboard logger code referenced from:
https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/04-utils/
Other helper functions:
https://github.com/cs230-stanford/cs230-stanford.github.io
"""
import json
import logging
import os
import shutil
import torch
from collections import OrderedDict
from torch.o... | 8,449 | 30.180812 | 109 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/model/shufflenetv2.py | """shufflenetv2 in pytorch
[1] Ningning Ma, Xiangyu Zhang, Hai-Tao Zheng, Jian Sun
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
https://arxiv.org/abs/1807.11164
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
def channel_split(x, split):
"""split a tens... | 4,802 | 30.392157 | 101 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/model/resnet.py | '''ResNet in PyTorch.
For Pre-activation ResNet, see 'preact_resnet.py'.
Reference:
[1] Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Deep Residual Learning for Image Recognition. arXiv:1512.03385
'''
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd im... | 5,966 | 34.730539 | 119 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/model/mobilenetv2.py | """mobilenetv2 in pytorch
[1] Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen
MobileNetV2: Inverted Residuals and Linear Bottlenecks
https://arxiv.org/abs/1801.04381
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
class LinearBottleNeck(nn.Module):
de... | 2,829 | 27.877551 | 109 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/model/utils.py | try:
from torch.hub import load_state_dict_from_url
except ImportError:
from torch.utils.model_zoo import load_url as load_state_dict_from_url | 150 | 36.75 | 74 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/model/densenet.py | """
dense net in pytorch
[1] Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger.
Densely Connected Convolutional Networks
https://arxiv.org/abs/1608.06993v5
"""
import torch
import torch.nn as nn
#"""Bottleneck layers. Although each layer only produces k
#output feature-maps, it typically h... | 5,141 | 39.488189 | 147 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/model/googlenet.py | """google net in pytorch
[1] Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed,
Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich.
Going Deeper with Convolutions
https://arxiv.org/abs/1409.4842v1
"""
import torch
import torch.nn as nn
class Inception(nn.Module):
... | 4,371 | 33.15625 | 94 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/model/resnext.py | from __future__ import division
"""
Creates a ResNeXt Model as defined in:
Xie, S., Girshick, R., Dollar, P., Tu, Z., & He, K. (2016).
Aggregated residual transformations for deep neural networks.
arXiv preprint arXiv:1611.05431.
import from https://github.com/prlz77/ResNeXt.pytorch/blob/master/models/model.py
"""
i... | 6,323 | 42.315068 | 144 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/model/net.py | """
Baseline CNN, losss function and metrics
Also customizes knowledge distillation (KD) loss function here
"""
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
class Net(nn.Module):
"""
This is the standard way to define your own network in PyTorch. You typically ch... | 4,030 | 50.025316 | 116 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/model/alexnet.py | '''AlexNet for CIFAR10. FC layers are removed. Paddings are adjusted.
Without BN, the start learning rate should be 0.01
(c) YANG, Wei
'''
import torch.nn as nn
__all__ = ['alexnet']
class AlexNet(nn.Module):
def __init__(self, num_classes=100):
super(AlexNet, self).__init__()
self.features = n... | 1,358 | 29.886364 | 69 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/model/wrn.py | import numpy as np
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
# __all__ = ['wrn']
class BasicBlock(nn.Module):
def __init__(self, in_planes, out_planes, stride, dropRate=0.0):
super(BasicBlock, self).__init__()
self.bn1 = nn.BatchNorm2d(in_planes)
self.r... | 5,085 | 39.688 | 119 | py |
Teacher-free-Knowledge-Distillation | Teacher-free-Knowledge-Distillation-master/ImageNet_train/main.py | import argparse
import os
import random
import shutil
import time
import warnings
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.distributed as dist
import torch.optim
import torch.multiprocessing as mp
import torch.utils.data
import torch.utils.data.distr... | 21,167 | 40.182879 | 147 | py |
OccamNet_Public | OccamNet_Public-main/implicit/ExperimentTimeConstantPower.py | import torch
import torch.nn as nn
import numpy as np
import Bases
from DataGenerators import FunctionDataGenerator,ImplicitFunctionDataGenerator,MultivariateFunctionDataGenerator,ImplicitFunctionDataGeneratorSample,FunctionDataGeneratorSample
from Losses import CrossEntropyLoss,CELTrivialRegularization,CELTrivialConst... | 1,803 | 37.382979 | 374 | py |
OccamNet_Public | OccamNet_Public-main/implicit/Bases.py | from abc import ABC,abstractmethod
import torch
import sympy as sp
import numpy as np
#Nan represents unfixed units. Not wrong units.
def checkNan(input):
return np.isnan(input[0])
#Inf represents wrong units that need to be propagated further
def checkInf(input):
return np.isinf(input[0])
def matchUnits(uni... | 9,524 | 25.02459 | 79 | py |
OccamNet_Public | OccamNet_Public-main/implicit/ExperimentTimeCircle.py | import torch
import torch.nn as nn
import numpy as np
import Bases
from DataGenerators import FunctionDataGenerator,ImplicitFunctionDataGenerator,MultivariateFunctionDataGenerator,ImplicitFunctionDataGeneratorSample
from Losses import CrossEntropyLoss,CELTrivialRegularization,CELTrivialConstantRegularization,CELFlagReg... | 1,854 | 36.857143 | 240 | py |
OccamNet_Public | OccamNet_Public-main/implicit/SparseSetters.py | import torch
import math
from NetworkRegularization import ActivationLayer
class SetPartialSparse:
def __init__(self, sparseInputs):
self.sparseInputs = sparseInputs
def getActivationsSparsity(self, inputSize, activationLists, outputSize):
numItems = [outputSize]
for i in range(len(act... | 6,203 | 34.861272 | 111 | py |
OccamNet_Public | OccamNet_Public-main/implicit/ExperimentTimeCosine.py | import torch
import torch.nn as nn
import numpy as np
import Bases
from DataGenerators import FunctionDataGenerator,ImplicitFunctionDataGenerator,MultivariateFunctionDataGenerator,ImplicitFunctionDataGeneratorSample,FunctionDataGeneratorSample
from Losses import CrossEntropyLoss,CELTrivialRegularization,CELTrivialConst... | 1,827 | 35.56 | 200 | py |
OccamNet_Public | OccamNet_Public-main/implicit/ExperimentTimeDivide.py | import torch
import torch.nn as nn
import numpy as np
import Bases
from DataGenerators import FunctionDataGenerator,ImplicitFunctionDataGenerator,MultivariateFunctionDataGenerator,ImplicitFunctionDataGeneratorSample
from Losses import CrossEntropyLoss,CELTrivialRegularization,CELTrivialConstantRegularization,CELFlagReg... | 1,647 | 33.333333 | 240 | py |
OccamNet_Public | OccamNet_Public-main/implicit/ExperimentTimeTaylor.py | import torch
import torch.nn as nn
import numpy as np
import Bases
from DataGenerators import FunctionDataGenerator,ImplicitFunctionDataGenerator,MultivariateFunctionDataGenerator,ImplicitFunctionDataGeneratorSample,FunctionDataGeneratorSample
from Losses import CrossEntropyLoss,CELTrivialRegularization,CELTrivialConst... | 1,884 | 35.960784 | 249 | py |
OccamNet_Public | OccamNet_Public-main/implicit/NetworkRegularization.py | from numpy.lib.npyio import save
import torch
import torch.nn as nn
import numpy as np
import math
import matplotlib.pyplot as plt
import Bases
from DataGenerators import FunctionDataGenerator,ImplicitFunctionDataGenerator
from Losses import CrossEntropyLoss,CELFlagRegularization
import argparse
import sympy as sp
from... | 37,276 | 38.280295 | 265 | py |
OccamNet_Public | OccamNet_Public-main/implicit/ExperimentTimeMomentum.py | import torch
import torch.nn as nn
import numpy as np
import Bases
from DataGenerators import FunctionDataGenerator,ImplicitFunctionDataGenerator,MultivariateFunctionDataGenerator,ImplicitFunctionDataGeneratorSample
from Losses import CrossEntropyLoss,CELTrivialRegularization,CELTrivialConstantRegularization,CELFlagReg... | 1,792 | 36.354167 | 240 | py |
OccamNet_Public | OccamNet_Public-main/implicit/ExperimentTimeArccos.py | import torch
import torch.nn as nn
import numpy as np
import Bases
from DataGenerators import FunctionDataGenerator,ImplicitFunctionDataGenerator,MultivariateFunctionDataGenerator,ImplicitFunctionDataGeneratorSample
from Losses import CrossEntropyLoss,CELTrivialRegularization,CELTrivialConstantRegularization,CELFlagReg... | 1,789 | 35.530612 | 240 | py |
OccamNet_Public | OccamNet_Public-main/implicit/Losses.py | import torch
import math
class CrossEntropyLoss:
def __init__(self, var, topNumber):
self.setVar(var)
self.topNumber = topNumber
self.weighting = torch.tensor([1.0/(n) for n in range(topNumber, 0, -1)])
def setVar(self, var):
self.var = var
def getError(self, y, predic... | 7,400 | 42.02907 | 149 | py |
OccamNet_Public | OccamNet_Public-main/implicit/ExperimentTimeHyperbola.py | import torch
import torch.nn as nn
import numpy as np
import Bases
from DataGenerators import FunctionDataGenerator,ImplicitFunctionDataGenerator,MultivariateFunctionDataGenerator,ImplicitFunctionDataGeneratorSample
from Losses import CrossEntropyLoss,CELTrivialRegularization,CELTrivialConstantRegularization,CELFlagReg... | 1,661 | 32.918367 | 240 | py |
OccamNet_Public | OccamNet_Public-main/implicit/DataGenerators.py | import torch
class FunctionDataGenerator:
def __init__(self, batchSize, dataRange, function):
self.batchSize = batchSize
self.dataRange = dataRange
self.function = function
def getBatch(self):
x = (torch.rand([self.batchSize], dtype = torch.float)*(self.dataRange[1]-self.da... | 3,632 | 38.48913 | 160 | py |
OccamNet_Public | OccamNet_Public-main/constant-fitting/ExperimentTimeConstantPower.py | import torch
import Bases
from Losses import CrossEntropyLoss
from Network import NetworkConstants, ActivationLayer
from SparseSetters import SetPartialSparse as SPS
from SparseSetters import SetNoSparse as SNS
def func(x):
return 10.5*torch.pow(x,3.1)
if __name__ == '__main__':
fileName = "constantPower"
... | 1,007 | 36.333333 | 373 | py |
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