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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structured-nets | structured-nets-master/tensorflow/model_params.py | from utils import *
import pickle as pkl
import datetime, os
class ModelParams:
def __init__(self, dataset_name, transform, test, log_path, input_size,
layer_size, out_size, num_layers, loss, r, steps, batch_size,
lr, mom, init_type, class_type, learn_corner, n_diag_learned,
ini... | 5,989 | 40.597222 | 260 | py |
structured-nets | structured-nets-master/tensorflow/compare_parallel.py | """
Compare methods in parallel, spawning separate thread for each.
"""
import sys, os, datetime
import pickle as pkl
sys.path.insert(0, '../../')
# from optimize import optimize
from utils import *
from model_params import ModelParams
from dataset import Dataset
import argparse
import thread
def create_command(args,... | 2,795 | 43.380952 | 291 | py |
MALUNet | MALUNet-main/engine.py | import numpy as np
from tqdm import tqdm
import torch
from torch.cuda.amp import autocast as autocast
from sklearn.metrics import confusion_matrix
from utils import save_imgs
def train_one_epoch(train_loader,
model,
criterion,
optimizer,
... | 5,851 | 36.037975 | 139 | py |
MALUNet | MALUNet-main/utils.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.backends.cudnn as cudnn
import torchvision.transforms.functional as TF
import numpy as np
import os
import math
import random
import logging
import logging.handlers
from matplotlib import pyplot as plt
def set_seed(seed):
# for hash
... | 11,464 | 29.819892 | 136 | py |
MALUNet | MALUNet-main/train.py | import torch
from torch import nn
from torch.cuda.amp import autocast, GradScaler
from torch.utils.data import DataLoader
from models.malunet import MALUNet
from dataset.npy_datasets import NPY_datasets
from engine import *
import os
import sys
os.environ["CUDA_VISIBLE_DEVICES"] = "0" # "0, 1, 2, 3"
from utils import... | 5,357 | 28.43956 | 153 | py |
MALUNet | MALUNet-main/dataset/npy_datasets.py | from torch.utils.data import Dataset
import numpy as np
import os
from PIL import Image
class NPY_datasets(Dataset):
def __init__(self, path_Data, config, train=True):
super(NPY_datasets, self)
if train:
images_list = os.listdir(path_Data+'train/images/')
masks_list = os.li... | 1,505 | 37.615385 | 87 | py |
MALUNet | MALUNet-main/models/malunet.py | import torch
from torch import nn
import torch.nn.functional as F
from timm.models.layers import trunc_normal_
import math
class DepthWiseConv2d(nn.Module):
def __init__(self, dim_in, dim_out, kernel_size=3, padding=1, stride=1, dilation=1):
super().__init__()
self.conv1 = nn.Conv2d(dim_... | 12,695 | 38.924528 | 143 | py |
MALUNet | MALUNet-main/configs/config_setting.py | from torchvision import transforms
from utils import *
from datetime import datetime
class setting_config:
"""
the config of training setting.
"""
network = 'malunet'
model_config = {
'num_classes': 1,
'input_channels': 3,
'c_list': [8, 16, 24, 32, 48, 64],
'split_... | 8,211 | 52.324675 | 298 | py |
ms-pred | ms-pred-main/src/ms_pred/common/misc_utils.py | """ utils.py """
import sys
import copy
import logging
from pathlib import Path
import json
from itertools import groupby, islice
from typing import Tuple, List
import pandas as pd
import numpy as np
import ms_pred.common.chem_utils as chem_utils
from pytorch_lightning.loggers import LightningLoggerBase
from pytorch_... | 12,709 | 26.751092 | 86 | py |
ms-pred | ms-pred-main/src/ms_pred/common/chem_utils.py | """chem_utils.py"""
import re
import numpy as np
import pandas as pd
from functools import reduce
import torch
from rdkit import Chem
from rdkit.Chem import Atom
from rdkit.Chem.rdMolDescriptors import CalcMolFormula
from rdkit.Chem.Descriptors import ExactMolWt
from rdkit.Chem.MolStandardize import rdMolStandardize
... | 13,164 | 23.37963 | 88 | py |
ms-pred | ms-pred-main/src/ms_pred/scarf_pred/train_inten.py | """train_inten.py
Train model to predict emit intensities for each mol formla
"""
import logging
import yaml
import argparse
from pathlib import Path
import pandas as pd
from datetime import datetime
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_l... | 10,163 | 34.538462 | 92 | py |
ms-pred | ms-pred-main/src/ms_pred/scarf_pred/predict_smis.py | """predict_smis.py
Make both scarf prefix tree and intensity predictions jointly and revert to binned
"""
import logging
import json
from datetime import datetime
import yaml
import argparse
import pickle
from pathlib import Path
import pandas as pd
import numpy as np
import torch
import pytorch_lightning as pl
im... | 9,603 | 33.923636 | 86 | py |
ms-pred | ms-pred-main/src/ms_pred/scarf_pred/inten_hyperopt.py | """inten_hyperopt.py
Hyperopt parameters for scarf model
"""
import os
import copy
import logging
import argparse
from pathlib import Path
import pandas as pd
from typing import List, Dict
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from... | 9,038 | 29.0299 | 83 | py |
ms-pred | ms-pred-main/src/ms_pred/scarf_pred/train_gen.py | """train.py
Train gnn to predict binned specs
"""
import logging
import yaml
import argparse
from pathlib import Path
from datetime import datetime
import pandas as pd
import numpy as np
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from p... | 10,446 | 33.823333 | 92 | py |
ms-pred | ms-pred-main/src/ms_pred/scarf_pred/predict_gen.py | """predict.py
Make predictions with trained model
"""
import logging
from datetime import datetime
import yaml
import argparse
import pickle
from pathlib import Path
import json
import numpy as np
import pandas as pd
from tqdm import tqdm
import torch
from torch.utils.data import DataLoader
import pytorch_lightning... | 6,807 | 32.372549 | 84 | py |
ms-pred | ms-pred-main/src/ms_pred/scarf_pred/scarf_data.py | import logging
from pathlib import Path
from typing import List
from functools import partial
import json
import numpy as np
import pandas as pd
from tqdm import tqdm
from rdkit import Chem
import torch
from torch.utils.data.dataset import Dataset
import dgl
import ms_pred.common as common
import ms_pred.massformer_... | 26,118 | 33.367105 | 87 | py |
ms-pred | ms-pred-main/src/ms_pred/scarf_pred/scarf_model.py | import math
import ipdb
import torch
import pytorch_lightning as pl
import torch.nn as nn
import torch.nn.functional as F
import torch_scatter as ts
import dgl.nn as dgl_nn
import numpy as np
import einops
from rdkit import Chem
import dgl
import ms_pred.common as common
import ms_pred.nn_utils as nn_utils
import ... | 50,839 | 35.549245 | 122 | py |
ms-pred | ms-pred-main/src/ms_pred/scarf_pred/gen_hyperopt.py | """gen_hyperopt.py
Hyperopt parameters for scarf model
"""
import os
import copy
import logging
import argparse
from pathlib import Path
import pandas as pd
from typing import List, Dict
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from p... | 7,593 | 29.620968 | 83 | py |
ms-pred | ms-pred-main/src/ms_pred/scarf_pred/predict_inten.py | """predict_inten.py
Make intensity predictions with trained model
"""
import logging
from datetime import datetime
import yaml
import argparse
import pickle
import json
from pathlib import Path
import pandas as pd
import numpy as np
from tqdm import tqdm
import torch
from torch.utils.data import DataLoader
import p... | 7,922 | 33.447826 | 88 | py |
ms-pred | ms-pred-main/src/ms_pred/ffn_pred/ffn_hyperopt.py | """ffn_hyperopt.py
Hyperopt parameters for FFN model
"""
import os
import copy
import logging
import argparse
from pathlib import Path
import pandas as pd
from typing import List, Dict
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from pyt... | 6,046 | 27.795238 | 79 | py |
ms-pred | ms-pred-main/src/ms_pred/ffn_pred/ffn_model.py | """ ffn_model. """
import torch
import pytorch_lightning as pl
import torch.nn as nn
import numpy as np
import ms_pred.nn_utils as nn_utils
import ms_pred.common as common
class ForwardFFN(pl.LightningModule):
def __init__(
self,
hidden_size: int,
layers: int = 2,
dropout: float =... | 6,781 | 34.139896 | 86 | py |
ms-pred | ms-pred-main/src/ms_pred/ffn_pred/ffn_data.py | import logging
import json
import numpy as np
import torch
from torch.utils.data.dataset import Dataset
import ms_pred.common as common
class BinnedDataset(Dataset):
"""SmiDataset."""
def __init__(
self,
df,
data_dir,
num_bins,
num_workers=0,
upper_limit=1500... | 6,802 | 30.35023 | 86 | py |
ms-pred | ms-pred-main/src/ms_pred/ffn_pred/predict.py | """predict.py
Make predictions with trained model
"""
import logging
from collections import defaultdict
from datetime import datetime
import yaml
import argparse
import pickle
from pathlib import Path
import numpy as np
import pandas as pd
import torch
from torch.utils.data import DataLoader
import pytorch_lightn... | 6,367 | 31.994819 | 84 | py |
ms-pred | ms-pred-main/src/ms_pred/ffn_pred/train.py | """train.py
Train ffn to predict binned specs
"""
import logging
import yaml
import argparse
from pathlib import Path
import pandas as pd
from datetime import datetime
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from pytorch_lightning.ca... | 7,709 | 32.521739 | 99 | py |
ms-pred | ms-pred-main/src/ms_pred/molnetms/molnetms_model.py | """ gnn_model. """
from typing import Tuple
import pytorch_lightning as pl
import numpy as np
import torch
import torch.nn.functional as F
import torch.nn as nn
import ms_pred.nn_utils as nn_utils
import ms_pred.common as common
import ms_pred.molnetms.molnetms_data as molnetms_data
class FCResBlock(nn.Module):
... | 18,504 | 36.611789 | 123 | py |
ms-pred | ms-pred-main/src/ms_pred/molnetms/molnetms_hyperopt.py | """gnn_hyperopt.py
Hyperopt parameters for FFN model
"""
import os
import copy
import logging
import argparse
from pathlib import Path
import pandas as pd
from typing import List, Dict
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from pyt... | 6,481 | 28.330317 | 79 | py |
ms-pred | ms-pred-main/src/ms_pred/molnetms/molnetms_data.py | import logging
import json
import numpy as np
import torch
from rdkit import Chem
from torch.utils.data.dataset import Dataset
import dgl
import ms_pred.common as common
class MolMSFeaturizer():
""" Create a 3D mol featurizer"""
# Hardcoded
char_to_vec = {i: j.tolist() for i,j in common.element_to_posi... | 12,980 | 32.114796 | 138 | py |
ms-pred | ms-pred-main/src/ms_pred/molnetms/predict.py | """predict.py
Make predictions with trained model
"""
import logging
from datetime import datetime
import yaml
import argparse
import pickle
from pathlib import Path
import numpy as np
import pandas as pd
from tqdm import tqdm
import torch
from torch.utils.data import DataLoader
import pytorch_lightning as pl
imp... | 5,741 | 31.811429 | 86 | py |
ms-pred | ms-pred-main/src/ms_pred/molnetms/train.py | """train.py
Train gnn to predict binned specs
"""
import logging
import yaml
import argparse
from pathlib import Path
import pandas as pd
from datetime import datetime
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from pytorch_lightning.ca... | 7,973 | 32.087137 | 92 | py |
ms-pred | ms-pred-main/src/ms_pred/graff_ms/graff_ms_hyperopt.py | """graff_ms_hyperopt.py
Hyperopt parameters for graff ms model
"""
import os
import copy
import logging
import argparse
from pathlib import Path
import pandas as pd
from typing import List, Dict
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_logger... | 7,881 | 30.277778 | 79 | py |
ms-pred | ms-pred-main/src/ms_pred/graff_ms/graff_ms_data.py | from collections import defaultdict
import logging
import json
import numpy as np
from tqdm import tqdm
import torch
from rdkit import Chem
from torch.utils.data.dataset import Dataset
import dgl
import ms_pred.common as common
def array_to_string(array):
"""
Converts a 1D NumPy array into a string.
... | 12,380 | 29.64604 | 87 | py |
ms-pred | ms-pred-main/src/ms_pred/graff_ms/predict.py | """predict.py
Make predictions with trained model
"""
import logging
from datetime import datetime
import yaml
import argparse
import pickle
from pathlib import Path
import numpy as np
import pandas as pd
from tqdm import tqdm
import torch
from torch.utils.data import DataLoader
import pytorch_lightning as pl
imp... | 5,873 | 32 | 86 | py |
ms-pred | ms-pred-main/src/ms_pred/graff_ms/train.py | """train.py
Train graff ms to predict binned specs
"""
import logging
import yaml
import argparse
from pathlib import Path
import pandas as pd
from datetime import datetime
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from pytorch_lightni... | 9,219 | 33.792453 | 95 | py |
ms-pred | ms-pred-main/src/ms_pred/graff_ms/graff_ms_model.py | """ gnn_model. """
import torch
import pytorch_lightning as pl
import numpy as np
import torch.nn as nn
import dgl.nn as dgl_nn
import torch_scatter as ts
import ms_pred.nn_utils as nn_utils
import ms_pred.common as common
class GraffGNN(pl.LightningModule):
def __init__(
self,
hidden_size: int,... | 11,548 | 33.99697 | 98 | py |
ms-pred | ms-pred-main/src/ms_pred/dag_pred/train_inten.py | """train_inten.py
Train model to predict emit intensities for each fragment
"""
import logging
import yaml
import argparse
from pathlib import Path
import pandas as pd
from datetime import datetime
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_log... | 10,066 | 33.713793 | 92 | py |
ms-pred | ms-pred-main/src/ms_pred/dag_pred/predict_smis.py | """predict_smis.py
Make both dag and intensity predictions jointly and revert to binned
"""
import logging
import json
from collections import defaultdict
from datetime import datetime
import yaml
import argparse
import pickle
from pathlib import Path
import pandas as pd
import numpy as np
import torch
import pytor... | 8,442 | 33.321138 | 84 | py |
ms-pred | ms-pred-main/src/ms_pred/dag_pred/joint_model.py | """ joint_model. """
from collections import defaultdict
import numpy as np
import pytorch_lightning as pl
import ms_pred.common as common
import ms_pred.magma.fragmentation as fragmentation
import ms_pred.dag_pred.gen_model as gen_model
import ms_pred.dag_pred.inten_model as inten_model
import ms_pred.dag_pred.dag_da... | 5,385 | 32.042945 | 95 | py |
ms-pred | ms-pred-main/src/ms_pred/dag_pred/dag_data.py | """ dag_data.py
Fragment dataset to build out model class
"""
import logging
from pathlib import Path
from typing import List
import json
import copy
import numpy as np
import pandas as pd
from tqdm import tqdm
import torch
import dgl
from torch.utils.data.dataset import Dataset
import ms_pred.common as common
imp... | 22,426 | 30.498596 | 87 | py |
ms-pred | ms-pred-main/src/ms_pred/dag_pred/inten_model.py | """frag_model."""
import numpy as np
import copy
import torch
import pytorch_lightning as pl
import torch.nn as nn
import torch_scatter as ts
import dgl.nn as dgl_nn
import ms_pred.common as common
import ms_pred.dag_pred.dag_data as dag_data
import ms_pred.nn_utils as nn_utils
import ms_pred.magma.fragmentation as f... | 18,694 | 32.684685 | 88 | py |
ms-pred | ms-pred-main/src/ms_pred/dag_pred/inten_hyperopt.py | """inten_hyperopt.py
Hyperopt parameters for frag tree generation model
"""
import os
import copy
import logging
import argparse
from pathlib import Path
import pandas as pd
from typing import List, Dict
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as ... | 7,566 | 29.512097 | 83 | py |
ms-pred | ms-pred-main/src/ms_pred/dag_pred/train_gen.py | """train.py
Train model to predict tree breakages
"""
import logging
import yaml
import argparse
from pathlib import Path
from datetime import datetime
import pandas as pd
import numpy as np
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
fr... | 9,118 | 32.525735 | 92 | py |
ms-pred | ms-pred-main/src/ms_pred/dag_pred/gen_model.py | """frag_model."""
import numpy as np
import torch
import pytorch_lightning as pl
import torch.nn as nn
import dgl
import dgl.nn as dgl_nn
import ms_pred.common as common
import ms_pred.nn_utils as nn_utils
import ms_pred.magma.fragmentation as fragmentation
import ms_pred.magma.run_magma as magma
import ms_pred.dag_p... | 23,127 | 36.064103 | 89 | py |
ms-pred | ms-pred-main/src/ms_pred/dag_pred/predict_gen.py | """predict.py
Make predictions with trained model
"""
import logging
from datetime import datetime
import yaml
import argparse
import json
from pathlib import Path
import pandas as pd
from tqdm import tqdm
from rdkit import Chem
from rdkit import RDLogger
RDLogger.DisableLog("rdApp.*")
import torch
import pytorc... | 4,918 | 30.132911 | 87 | py |
ms-pred | ms-pred-main/src/ms_pred/dag_pred/gen_hyperopt.py | """frag_hyperopt.py
Hyperopt parameters for frag tree generation model
"""
import os
import copy
import logging
import argparse
from pathlib import Path
import pandas as pd
from typing import List, Dict
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as p... | 7,051 | 28.630252 | 83 | py |
ms-pred | ms-pred-main/src/ms_pred/dag_pred/predict_inten.py | """predict_inten.py
Make intensity predictions with trained model
"""
import logging
from datetime import datetime
import yaml
import argparse
import pickle
import copy
import json
from pathlib import Path
import pandas as pd
import numpy as np
from tqdm import tqdm
import torch
from torch.utils.data import DataLoa... | 8,571 | 34.131148 | 84 | py |
ms-pred | ms-pred-main/src/ms_pred/gnn_pred/gnn_data.py | import logging
import json
import numpy as np
import torch
from rdkit import Chem
from torch.utils.data.dataset import Dataset
import dgl
import ms_pred.common as common
class BinnedDataset(Dataset):
"""SmiDataset."""
def __init__(
self,
df,
data_dir,
num_bins,
graph... | 8,568 | 31.214286 | 86 | py |
ms-pred | ms-pred-main/src/ms_pred/gnn_pred/gnn_model.py | """ gnn_model. """
import torch
import pytorch_lightning as pl
import numpy as np
import torch.nn as nn
import dgl.nn as dgl_nn
import ms_pred.nn_utils as nn_utils
import ms_pred.common as common
class ForwardGNN(pl.LightningModule):
def __init__(
self,
hidden_size: int,
layers: int = 2,... | 8,638 | 33.418327 | 86 | py |
ms-pred | ms-pred-main/src/ms_pred/gnn_pred/gnn_hyperopt.py | """gnn_hyperopt.py
Hyperopt parameters for FFN model
"""
import os
import copy
import logging
import argparse
from pathlib import Path
import pandas as pd
from typing import List, Dict
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from pyt... | 7,020 | 28.876596 | 79 | py |
ms-pred | ms-pred-main/src/ms_pred/gnn_pred/predict.py | """predict.py
Make predictions with trained model
"""
import logging
from datetime import datetime
import yaml
import argparse
import pickle
from pathlib import Path
import numpy as np
import pandas as pd
from tqdm import tqdm
import torch
from torch.utils.data import DataLoader
import pytorch_lightning as pl
imp... | 5,820 | 31.519553 | 84 | py |
ms-pred | ms-pred-main/src/ms_pred/gnn_pred/train.py | """train.py
Train gnn to predict binned specs
"""
import logging
import yaml
import argparse
from pathlib import Path
import pandas as pd
from datetime import datetime
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from pytorch_lightning.ca... | 8,523 | 32.559055 | 92 | py |
ms-pred | ms-pred-main/src/ms_pred/nn_utils/base_hyperopt.py | """ base_hyperopt.py
Abstract away common hyperopt functionality
"""
import logging
import yaml
from pathlib import Path
from datetime import datetime
from typing import Callable
import pytorch_lightning as pl
import ray
from ray import tune
from ray.air.config import RunConfig
from ray.tune.search import Concurren... | 4,204 | 28.405594 | 79 | py |
ms-pred | ms-pred-main/src/ms_pred/nn_utils/dgl_modules.py | """ dgl_modules.
Directly copy dgl modules to patch them
"""
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import init
import dgl.function as fn
from dgl.nn import expand_as_pair
class GatedGraphConv(nn.Module):
r"""Gated Graph Convolution layer from `Gat... | 19,829 | 32.496622 | 98 | py |
ms-pred | ms-pred-main/src/ms_pred/nn_utils/tune_utils.py | import logging
from typing import Dict, List, Optional, Union
from pytorch_lightning import Trainer, LightningModule
from ray.tune.integration.pytorch_lightning import TuneCallback
from ray import tune
logger = logging.getLogger(__name__)
class TuneReportCallback(TuneCallback):
"""PyTorch Lightning to Ray Tune... | 3,407 | 34.5 | 77 | py |
ms-pred | ms-pred-main/src/ms_pred/nn_utils/transformer_layer.py | """transformer_layer.py
Hold pairwise attention enabled transformers
"""
import math
from typing import Optional, Union, Callable, Tuple
import torch
from torch import Tensor
from torch.nn import functional as F
from torch.nn import Module, LayerNorm, Linear, Dropout, Parameter
from torch.nn.init import xavier_unifo... | 28,178 | 42.960998 | 133 | py |
ms-pred | ms-pred-main/src/ms_pred/nn_utils/form_embedder.py | import torch
import torch.nn as nn
import numpy as np
import ms_pred.common as common
class IntFeaturizer(nn.Module):
"""
Base class for mapping integers to a vector representation (primarily to be used as a "richer" embedding for NNs
processing integers).
Subclasses should define `self.int_to_feat_... | 10,244 | 36.254545 | 122 | py |
ms-pred | ms-pred-main/src/ms_pred/nn_utils/mol_graph.py | """ mol_graph.py.
Classes to featurize molecules into a graph with onehot concat feats on atoms
and bonds. Inspired by the dgllife library.
"""
from rdkit import Chem
import numpy as np
import torch
import dgl
import ms_pred.nn_utils.nn_utils as nn_utils
atom_feat_registry = {}
bond_feat_registry = {}
def register... | 10,157 | 23.359712 | 87 | py |
ms-pred | ms-pred-main/src/ms_pred/nn_utils/nn_utils.py | """ nn_utils.py
Hold basic GNN Types:
1. GGNN
2. PNA
These classes should accept graphs and return featurizations at each node
The calling class should be responsible for pooling however is best
"""
import copy
import math
import numpy as np
import scipy.sparse as sparse
import torch
import torch.nn as nn
import t... | 26,588 | 30.99639 | 92 | py |
ms-pred | ms-pred-main/src/ms_pred/massformer_pred/massformer_model.py | import torch
import pytorch_lightning as pl
import numpy as np
import torch.nn as nn
import ms_pred.nn_utils as nn_utils
import ms_pred.common as common
from .massformer_code import gf_model
from .massformer_code import model_extract
class MassFormer(pl.LightningModule):
"""
Implementation of Massformer.
... | 8,014 | 32.395833 | 86 | py |
ms-pred | ms-pred-main/src/ms_pred/massformer_pred/massformer_hyperopt.py | """gnn_hyperopt.py
Hyperopt parameters for FFN model
"""
import os
import copy
import logging
import argparse
from pathlib import Path
import pandas as pd
from typing import List, Dict
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from pyt... | 7,365 | 29.438017 | 79 | py |
ms-pred | ms-pred-main/src/ms_pred/massformer_pred/_massformer_graph_featurizer.py | from rdkit import Chem
from .massformer_code import gf_data_utils
class MassformerGraphFeaturizer:
"""
Thin wrapper over Massformer code to match the API we were using for graph featurizer.
Note that Massformer makes use of Pytorch Geometric Graph datastructures.
"""
def __call__(self, input_mol... | 978 | 38.16 | 107 | py |
ms-pred | ms-pred-main/src/ms_pred/massformer_pred/predict.py | """predict.py
Make predictions with trained model
"""
import logging
from datetime import datetime
import yaml
import argparse
import pickle
from pathlib import Path
import numpy as np
import pandas as pd
from tqdm import tqdm
import torch
from torch.utils.data import DataLoader
import pytorch_lightning as pl
imp... | 5,630 | 31.738372 | 88 | py |
ms-pred | ms-pred-main/src/ms_pred/massformer_pred/massformer_data.py | import logging
import json
import numpy as np
import torch
from rdkit import Chem
from torch.utils.data.dataset import Dataset
import dgl
import ms_pred.common as common
from ._massformer_graph_featurizer import MassformerGraphFeaturizer
class BinnedDataset(Dataset):
"""SmiDataset."""
def __init__(
... | 8,450 | 31.255725 | 94 | py |
ms-pred | ms-pred-main/src/ms_pred/massformer_pred/train.py | """train.py
Train gnn to predict binned specs
"""
import logging
import yaml
import argparse
from pathlib import Path
import pandas as pd
from datetime import datetime
from torch.utils.data import DataLoader
import pytorch_lightning as pl
from pytorch_lightning import loggers as pl_loggers
from pytorch_lightning.ca... | 8,486 | 32.545455 | 92 | py |
ms-pred | ms-pred-main/src/ms_pred/massformer_pred/massformer_code/model_extract.py |
import torch.nn as nn
import torch.nn.functional as F
class LinearBlock(nn.Module):
def __init__(self, in_feats, out_feats, dropout=0.1):
super(LinearBlock, self).__init__()
self.linear = nn.Linear(in_feats, out_feats)
self.bn = nn.BatchNorm1d(out_feats)
self.dropout = nn.Dropout(... | 1,362 | 30.697674 | 65 | py |
ms-pred | ms-pred-main/src/ms_pred/massformer_pred/massformer_code/gf_data_utils.py | import numpy as np
import torch
from torch_geometric.data import Data
from rdkit import Chem
from rdkit.Chem import rdchem
from . import algos2
# allowable multiple choice node and edge features
allowable_features = {
'possible_atomic_num_list': list(range(1, 119)) + ['misc'],
'possible_chirality_list': [
... | 13,299 | 31.758621 | 108 | py |
ms-pred | ms-pred-main/src/ms_pred/massformer_pred/massformer_code/gf_model.py | import logging
import math
from typing import *
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import Tensor
from torch.hub import load_state_dict_from_url
import torch.distributed as dist
import argparse
from . import gf_data_utils
logger = logging.getLogger(__name__)
PRETRAINED_MODEL... | 45,810 | 35.386815 | 130 | py |
ASH | ASH-main/docs/conf.py | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | 2,723 | 29.266667 | 79 | py |
CNTK | CNTK-master/bindings/python/cntk/tensor.py | # Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
"""
Tensor operations.
"""
import warnings
from scipy import sparse
class TensorO... | 9,698 | 35.462406 | 111 | py |
CNTK | CNTK-master/bindings/python/cntk/io/transforms.py | # Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
from .. import cntk_py
from cntk.internal import sanitize_2d_number, sanitize_range... | 8,295 | 53.578947 | 112 | py |
CNTK | CNTK-master/bindings/python/cntk/contrib/__init__.py | # Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
"""
Extra utilities for CNTK, e.g. utilities that bridge to other deep learning tool... | 470 | 26.705882 | 85 | py |
CNTK | CNTK-master/bindings/python/cntk/contrib/crosstalkcaffe/convert.py | # ==============================================================================
# Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
imp... | 1,642 | 33.229167 | 93 | py |
CNTK | CNTK-master/bindings/python/cntk/contrib/crosstalkcaffe/examples/run_convert.py | # ==============================================================================
# Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
'''
... | 1,747 | 39.651163 | 92 | py |
CNTK | CNTK-master/bindings/python/cntk/contrib/crosstalkcaffe/adapter/__init__.py | # ==============================================================================
# Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
fro... | 414 | 33.583333 | 80 | py |
CNTK | CNTK-master/bindings/python/cntk/contrib/crosstalkcaffe/adapter/bvlccaffe/caffeimpl.py | # ==============================================================================
# Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
impo... | 2,180 | 27.324675 | 80 | py |
CNTK | CNTK-master/bindings/python/cntk/contrib/crosstalkcaffe/adapter/bvlccaffe/caffeadapter.py | # ==============================================================================
# Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
imp... | 25,201 | 42.52677 | 129 | py |
CNTK | CNTK-master/bindings/python/cntk/contrib/crosstalkcaffe/adapter/bvlccaffe/caffe_pb2.py | # Generated by the protocol buffer compiler. DO NOT EDIT!
# source: caffe.proto
import sys
_b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1'))
from google.protobuf.internal import enum_type_wrapper
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _mes... | 256,644 | 41.960328 | 29,402 | py |
CNTK | CNTK-master/bindings/python/cntk/contrib/crosstalkcaffe/unimodel/cntkinstance.py | # ==============================================================================
# Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
fro... | 20,497 | 40.9182 | 121 | py |
CNTK | CNTK-master/bindings/python/cntk/contrib/crosstalkcaffe/tests/op2cntk_test.py | # ==============================================================================
# Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
imp... | 8,256 | 31.507874 | 104 | py |
CNTK | CNTK-master/bindings/python/cntk/contrib/crosstalkcaffe/utils/globalconf.py | # ==============================================================================
# Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
fro... | 2,478 | 25.37234 | 98 | py |
CNTK | CNTK-master/bindings/python/cntk/contrib/crosstalkcaffe/validation/validcaffe.py | # ==============================================================================
# Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
imp... | 3,045 | 37.556962 | 105 | py |
CNTK | CNTK-master/bindings/python/cntk/contrib/crosstalkcaffe/validation/validcore.py | # ==============================================================================
# Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
imp... | 3,283 | 35.898876 | 99 | py |
CNTK | CNTK-master/bindings/python/doc/conf.py | import re
try:
import cntk
except ImportError:
raise ImportError("Unable to import cntk; the cntk module needs to be built "
"and importable to generate documentation")
from cntk.sample_installer import module_is_unreleased
try:
import sphinx_rtd_theme
except ImportError:
raise ... | 2,815 | 26.076923 | 89 | py |
CNTK | CNTK-master/Tests/EndToEndTests/CNTKv2Python/Keras/conftest.py | # Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
import os
import zipfile
import shutil
try:
from urllib.request import urlretri... | 1,756 | 39.860465 | 121 | py |
CNTK | CNTK-master/Tests/EndToEndTests/CNTKv2Python/Examples/rpn_unit_test.py | # Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
import os, sys
import pytest
import numpy as np
from cntk import user_function
from... | 10,067 | 43.548673 | 140 | py |
CNTK | CNTK-master/Tests/EndToEndTests/CNTKv2Python/Examples/FlappingBird_with_keras_DQN_test.py | # Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
import numpy as np
import os
import platform
import sys
import pytest
os.environ["... | 2,132 | 32.857143 | 166 | py |
CNTK | CNTK-master/Examples/ReinforcementLearning/FlappingBirdWithKeras/FlappingBird_with_keras_DQN.py | #!/usr/bin/env python
from __future__ import print_function
import argparse
from collections import deque
import json
import numpy as np
import os
import random
import requests
import skimage as skimage
from skimage import transform, color, exposure
from skimage.transform import rotate
from skimage.viewer import Image... | 9,162 | 34.378378 | 131 | py |
CNTK | CNTK-master/Examples/Image/Detection/utils/caffe_layers/default_config.py | # --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
"""Fast R-CNN config system.
This file specifies default config option... | 9,213 | 31.216783 | 91 | py |
CNTK | CNTK-master/Examples/Image/Detection/utils/caffe_layers/proposal_layer.py | # --------------------------------------------------------
# Faster R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick and Sean Bell
# --------------------------------------------------------
#import caffe
import numpy as np
import yaml
from utils... | 6,978 | 37.136612 | 80 | py |
CNTK | CNTK-master/Examples/Image/Detection/utils/caffe_layers/proposal_target_layer.py | # --------------------------------------------------------
# Faster R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick and Sean Bell
# --------------------------------------------------------
#import caffe
import yaml
import numpy as np
import num... | 8,197 | 37.669811 | 106 | py |
CNTK | CNTK-master/Examples/Image/Detection/utils/caffe_layers/anchor_target_layer.py | # --------------------------------------------------------
# Faster R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick and Sean Bell
# --------------------------------------------------------
import os
#import caffe
import yaml
import numpy as np
... | 11,890 | 39.445578 | 95 | py |
CNTK | CNTK-master/Examples/Image/Detection/FastRCNN/BrainScript/fastRCNN/test.py | # --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
"""Test a Fast R-CNN network on an imdb (image database)."""
from __fu... | 13,520 | 38.535088 | 161 | py |
CNTK | CNTK-master/Examples/Image/Classification/GoogLeNet/InceptionV3/Python/InceptionV3_ImageNet_Distributed.py | # Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
import os
import math
import argparse
import numpy as np
import cntk as C
from Inc... | 7,640 | 47.056604 | 167 | py |
CNTK | CNTK-master/Examples/Image/Classification/GoogLeNet/InceptionV3/Python/InceptionV3_ImageNet.py | # Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
import os
import math
import argparse
import numpy as np
import cntk as C
from Inc... | 10,529 | 43.808511 | 171 | py |
CNTK | CNTK-master/Examples/Image/Classification/GoogLeNet/BN-Inception/Python/BN_Inception_CIFAR10_Distributed.py | # Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
from __future__ import print_function
from __future__ import division
import os
im... | 8,349 | 47.265896 | 167 | py |
CNTK | CNTK-master/Examples/Image/Classification/GoogLeNet/BN-Inception/Python/BN_Inception_ImageNet.py | # Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
from __future__ import print_function
from __future__ import division
import os
im... | 10,786 | 42.495968 | 171 | py |
CNTK | CNTK-master/Examples/Image/Classification/GoogLeNet/BN-Inception/Python/BN_Inception_CIFAR10.py | # Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
from __future__ import print_function
from __future__ import division
import os
im... | 10,779 | 42.643725 | 167 | py |
CNTK | CNTK-master/Examples/Image/Classification/GoogLeNet/BN-Inception/Python/BN_Inception_ImageNet_Distributed.py | # Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license. See LICENSE.md file in the project root
# for full license information.
# ==============================================================================
from __future__ import print_function
from __future__ import division
import os
im... | 8,215 | 46.767442 | 167 | py |
tardis | tardis-master/docs/conf.py | # -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
#
# Astropy documentation build configuration file.
#
# 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 file.
#
# All configurati... | 13,520 | 32.634328 | 234 | py |
X-VLM | X-VLM-master/NLVR.py | import argparse
import os
import sys
import math
import ruamel.yaml as yaml
import numpy as np
import random
import time
import datetime
import json
from pathlib import Path
import json
import pickle
import torch
import torch.backends.cudnn as cudnn
import torch.distributed as dist
from models.model_nlvr import XVLM... | 9,554 | 37.22 | 120 | py |
X-VLM | X-VLM-master/Grounding_bbox.py | import argparse
import datetime
import json
import math
import os
import random
import time
from pathlib import Path
import numpy as np
import ruamel.yaml as yaml
import torch
import torch.backends.cudnn as cudnn
import torch.distributed as dist
import utils
from dataset import create_dataset, create_sampler, create_... | 10,756 | 39.746212 | 135 | py |
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