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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messenger-emma | messenger-emma-main/messenger/models/emma.py | '''
Implements the EMMA model
'''
import random
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.distributions import Categorical
from numpy import sqrt as sqrt
from transformers import AutoModel, AutoTokenizer
from messenger.models.utils import nonzero_mean, Encoder
class EMMA(nn.Modul... | 4,862 | 34.49635 | 95 | py |
messenger-emma | messenger-emma-main/messenger/models/utils.py | '''
Common code and utilities used by the models
'''
import torch
class ObservationBuffer:
'''
Maintains a buffer of observations along the 0-dim. Observations
are currently expected to be a dict of np arrays. Currently keeps
observations in a list and then stacks them via torch.stack().
TODO: pre... | 4,077 | 35.738739 | 89 | py |
GraphGPS | GraphGPS-main/main.py | import datetime
import os
import torch
import logging
import graphgps # noqa, register custom modules
from graphgps.agg_runs import agg_runs
from graphgps.optimizer.extra_optimizers import ExtendedSchedulerConfig
from torch_geometric.graphgym.cmd_args import parse_args
from torch_geometric.graphgym.config import (cf... | 7,245 | 39.937853 | 80 | py |
GraphGPS | GraphGPS-main/unittests/test_eigvecs.py | import unittest as ut
import networkx as nx
import numpy as np
import torch
from torch_geometric.utils import to_scipy_sparse_matrix, get_laplacian, \
from_networkx
from graphgps.transform.posenc_stats import (eigvec_normalizer,
get_heat_kernels,
... | 9,153 | 41.775701 | 116 | py |
GraphGPS | GraphGPS-main/unittests/test_negate_edge_index.py | import shutil
import tempfile
import unittest
import networkx as nx
import numpy as np
import torch
from torch_geometric.data import Data, Batch
from torch_geometric.datasets import TUDataset
from torch_geometric.loader import DataLoader
from torch_geometric.utils import from_networkx, to_networkx
from graphgps.utils... | 5,986 | 34.850299 | 80 | py |
GraphGPS | GraphGPS-main/graphgps/agg_runs.py | import logging
import os
import numpy as np
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.utils.io import (
dict_list_to_json,
dict_list_to_tb,
dict_to_json,
json_to_dict_list,
makedirs_rm_exist,
string_to_python,
)
try:
from tensorboardX import SummaryWrit... | 5,225 | 31.06135 | 78 | py |
GraphGPS | GraphGPS-main/graphgps/metric_wrapper.py | import operator as op
from copy import deepcopy
from typing import Union, Callable, Optional, Dict, Any
import warnings
import torch
from torchmetrics.functional import (
accuracy,
average_precision,
confusion_matrix,
f1_score,
fbeta_score,
precision_recall_curve,
precision,
recall,
... | 10,779 | 31.567976 | 106 | py |
GraphGPS | GraphGPS-main/graphgps/utils.py | import logging
from typing import List
import torch
from torch import Tensor
from torch_geometric.utils import degree
from torch_geometric.utils import remove_self_loops
from torch_geometric.utils import scatter
from yacs.config import CfgNode
def negate_edge_index(edge_index, batch=None):
"""Negate batched spar... | 6,427 | 33.374332 | 79 | py |
GraphGPS | GraphGPS-main/graphgps/logger.py | import logging
import time
import numpy as np
import torch
from scipy.stats import stats
from sklearn.metrics import accuracy_score, precision_score, recall_score, \
f1_score, roc_auc_score, mean_absolute_error, mean_squared_error, \
confusion_matrix
from sklearn.metrics import r2_score
from torch_geometric.gr... | 12,799 | 38.875389 | 91 | py |
GraphGPS | GraphGPS-main/graphgps/finetuning.py | import logging
import os
import os.path as osp
import torch
from torch_geometric.graphgym.config import set_cfg
from yacs.config import CfgNode
def get_final_pretrained_ckpt(ckpt_dir):
if osp.exists(ckpt_dir):
names = os.listdir(ckpt_dir)
epochs = [int(name.split('.')[0]) for name in names]
... | 5,727 | 37.442953 | 86 | py |
GraphGPS | GraphGPS-main/graphgps/pooling/example.py | from torch_geometric.graphgym.register import register_pooling
from torch_geometric.utils import scatter
@register_pooling('example')
def global_example_pool(x, batch, size=None):
size = batch.max().item() + 1 if size is None else size
return scatter(x, batch, dim=0, dim_size=size, reduce='sum')
| 307 | 33.222222 | 64 | py |
GraphGPS | GraphGPS-main/graphgps/pooling/graph_token.py | from torch_geometric.graphgym.register import register_pooling
from torch_geometric.utils import to_dense_batch
@register_pooling('graph_token')
def graph_token_pooling(x, batch, *args):
"""Extracts the graph token from a batch to perform graph-level prediction.
Typically used together with Graphormer when Gr... | 492 | 36.923077 | 79 | py |
GraphGPS | GraphGPS-main/graphgps/config/wandb_config.py | from torch_geometric.graphgym.register import register_config
from yacs.config import CfgNode as CN
@register_config('cfg_wandb')
def set_cfg_wandb(cfg):
"""Weights & Biases tracker configuration.
"""
# WandB group
cfg.wandb = CN()
# Use wandb or not
cfg.wandb.use = False
# Wandb entity... | 558 | 22.291667 | 79 | py |
GraphGPS | GraphGPS-main/graphgps/config/example.py | from torch_geometric.graphgym.register import register_config
from yacs.config import CfgNode as CN
@register_config('example')
def set_cfg_example(cfg):
r'''
This function sets the default config value for customized options
:return: customized configuration use by the experiment.
'''
# --------... | 707 | 28.5 | 79 | py |
GraphGPS | GraphGPS-main/graphgps/config/posenc_config.py | from torch_geometric.graphgym.register import register_config
from yacs.config import CfgNode as CN
@register_config('posenc')
def set_cfg_posenc(cfg):
"""Extend configuration with positional encoding options.
"""
# Argument group for each Positional Encoding class.
cfg.posenc_LapPE = CN()
cfg.po... | 3,149 | 34.795455 | 83 | py |
GraphGPS | GraphGPS-main/graphgps/config/dataset_config.py | from torch_geometric.graphgym.register import register_config
@register_config('dataset_cfg')
def dataset_cfg(cfg):
"""Dataset-specific config options.
"""
# The number of node types to expect in TypeDictNodeEncoder.
cfg.dataset.node_encoder_num_types = 0
# The number of edge types to expect in ... | 603 | 29.2 | 79 | py |
GraphGPS | GraphGPS-main/graphgps/config/defaults_config.py | from torch_geometric.graphgym.register import register_config
@register_config('overwrite_defaults')
def overwrite_defaults_cfg(cfg):
"""Overwrite the default config values that are first set by GraphGym in
torch_geometric.graphgym.config.set_cfg
WARNING: At the time of writing, the order in which custom... | 1,277 | 33.540541 | 80 | py |
GraphGPS | GraphGPS-main/graphgps/config/custom_gnn_config.py | from torch_geometric.graphgym.register import register_config
@register_config('custom_gnn')
def custom_gnn_cfg(cfg):
"""Extending config group of GraphGym's built-in GNN for purposes of our
CustomGNN network model.
"""
# Use residual connections between the GNN layers.
cfg.gnn.residual = False
| 319 | 25.666667 | 76 | py |
GraphGPS | GraphGPS-main/graphgps/config/optimizers_config.py | from torch_geometric.graphgym.register import register_config
@register_config('extended_optim')
def extended_optim_cfg(cfg):
"""Extend optimizer config group that is first set by GraphGym in
torch_geometric.graphgym.config.set_cfg
"""
# Number of batches to accumulate gradients over before updating ... | 979 | 32.793103 | 80 | py |
GraphGPS | GraphGPS-main/graphgps/config/split_config.py | from torch_geometric.graphgym.register import register_config
@register_config('split')
def set_cfg_split(cfg):
"""Reconfigure the default config value for dataset split options.
Returns:
Reconfigured split configuration use by the experiment.
"""
# Default to selecting the standard split th... | 754 | 30.458333 | 75 | py |
GraphGPS | GraphGPS-main/graphgps/config/pretrained_config.py | from torch_geometric.graphgym.register import register_config
from yacs.config import CfgNode as CN
@register_config('cfg_pretrained')
def set_cfg_pretrained(cfg):
"""Configuration options for loading a pretrained model.
"""
cfg.pretrained = CN()
# Directory path to a saved experiment, if set, load ... | 681 | 31.47619 | 80 | py |
GraphGPS | GraphGPS-main/graphgps/config/graphormer_config.py | from torch_geometric.graphgym.register import register_config
from yacs.config import CfgNode as CN
@register_config('cfg_graphormer')
def set_cfg_gt(cfg):
cfg.graphormer = CN()
cfg.graphormer.num_layers = 6
cfg.graphormer.embed_dim = 80
cfg.graphormer.num_heads = 4
cfg.graphormer.dropout = 0.0
... | 819 | 33.166667 | 61 | py |
GraphGPS | GraphGPS-main/graphgps/config/gt_config.py | from torch_geometric.graphgym.register import register_config
from yacs.config import CfgNode as CN
@register_config('cfg_gt')
def set_cfg_gt(cfg):
"""Configuration for Graph Transformer-style models, e.g.:
- Spectral Attention Network (SAN) Graph Transformer.
- "vanilla" Transformer / Performer.
- Ge... | 1,867 | 24.589041 | 79 | py |
GraphGPS | GraphGPS-main/graphgps/head/example.py | import torch.nn as nn
from torch_geometric.graphgym.register import register_head
@register_head('head')
class ExampleNodeHead(nn.Module):
'''Head of GNN, node prediction'''
def __init__(self, dim_in, dim_out):
super().__init__()
self.layer_post_mp = nn.Linear(dim_in, dim_out, bias=True)
... | 769 | 31.083333 | 72 | py |
GraphGPS | GraphGPS-main/graphgps/head/infer_links.py | import torch
from torch_geometric.graphgym import cfg
from torch_geometric.graphgym.register import register_head
@register_head('infer_links')
class InferLinksHead(torch.nn.Module):
"""
InferLinks prediction head for graph prediction tasks.
Args:
dim_in (int): Input dimension.
dim_out (i... | 872 | 28.1 | 94 | py |
GraphGPS | GraphGPS-main/graphgps/head/inductive_node.py | import torch.nn as nn
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.models.layer import new_layer_config, MLP
from torch_geometric.graphgym.register import register_head
@register_head('inductive_node')
class GNNInductiveNodeHead(nn.Module):
"""
GNN prediction head for inductiv... | 960 | 31.033333 | 74 | py |
GraphGPS | GraphGPS-main/graphgps/head/ogb_code_graph.py | import torch.nn as nn
import torch_geometric.graphgym.register as register
from torch_geometric.graphgym import cfg
from torch_geometric.graphgym.register import register_head
@register_head('ogb_code_graph')
class OGBCodeGraphHead(nn.Module):
"""
Sequence prediction head for ogbg-code2 graph-level predictio... | 1,447 | 30.478261 | 79 | py |
GraphGPS | GraphGPS-main/graphgps/head/san_graph.py | import torch.nn as nn
import torch_geometric.graphgym.register as register
from torch_geometric.graphgym import cfg
from torch_geometric.graphgym.register import register_head
@register_head('san_graph')
class SANGraphHead(nn.Module):
"""
SAN prediction head for graph prediction tasks.
Args:
dim... | 1,453 | 32.813953 | 74 | py |
GraphGPS | GraphGPS-main/graphgps/head/inductive_edge.py | import numpy as np
import torch
import torch.nn as nn
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.models.layer import new_layer_config, MLP
from torch_geometric.graphgym.register import register_head
@register_head('inductive_edge')
class GNNInductiveEdgeHead(nn.Module):
""" GNN ... | 6,374 | 39.865385 | 85 | py |
GraphGPS | GraphGPS-main/graphgps/head/graphormer_graph.py | import torch
import torch_geometric.graphgym.register as register
from torch_geometric.graphgym import cfg
from torch_geometric.graphgym.register import register_head
@register_head('graphormer_graph')
class GraphormerHead(torch.nn.Module):
"""
Graphormer prediction head for graph prediction tasks.
Args... | 1,155 | 29.421053 | 74 | py |
GraphGPS | GraphGPS-main/graphgps/network/custom_gnn.py | import torch
import torch_geometric.graphgym.models.head # noqa, register module
import torch_geometric.graphgym.register as register
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.models.gnn import FeatureEncoder, GNNPreMP
from torch_geometric.graphgym.register import register_network
... | 2,002 | 34.767857 | 73 | py |
GraphGPS | GraphGPS-main/graphgps/network/example.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch_geometric.graphgym.models.head # noqa, register module
import torch_geometric.graphgym.register as register
import torch_geometric.nn as pyg_nn
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import ... | 1,532 | 30.9375 | 72 | py |
GraphGPS | GraphGPS-main/graphgps/network/big_bird.py | import torch
import torch_geometric.graphgym.register as register
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.models.gnn import FeatureEncoder, GNNPreMP
from torch_geometric.graphgym.register import register_network
from graphgps.layer.bigbird_layer import BigBirdModel as BackboneBigB... | 1,739 | 36.021277 | 116 | py |
GraphGPS | GraphGPS-main/graphgps/network/gps_model.py | import torch
import torch_geometric.graphgym.register as register
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.models.gnn import GNNPreMP
from torch_geometric.graphgym.models.layer import (new_layer_config,
BatchNorm1dNode)
from torch_g... | 4,313 | 38.577982 | 80 | py |
GraphGPS | GraphGPS-main/graphgps/network/graphormer.py | import torch
import torch_geometric.graphgym.register as register
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.models.gnn import FeatureEncoder, GNNPreMP
from torch_geometric.graphgym.register import register_network
from graphgps.layer.graphormer_layer import GraphormerLayer
@regist... | 1,958 | 35.962264 | 80 | py |
GraphGPS | GraphGPS-main/graphgps/network/san_transformer.py | import torch
import torch_geometric.graphgym.register as register
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.models.gnn import FeatureEncoder, GNNPreMP
from torch_geometric.graphgym.register import register_network
from graphgps.layer.san_layer import SANLayer
from graphgps.layer.san... | 2,186 | 37.368421 | 73 | py |
GraphGPS | GraphGPS-main/graphgps/network/performer.py | import torch
import torch_geometric.graphgym.register as register
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.models.gnn import FeatureEncoder, GNNPreMP
from torch_geometric.graphgym.register import register_network
from graphgps.layer.performer_layer import Performer as BackbonePerfo... | 1,492 | 32.931818 | 103 | py |
GraphGPS | GraphGPS-main/graphgps/train/example.py | import logging
import time
import torch
from torch_geometric.graphgym.checkpoint import (
clean_ckpt,
load_ckpt,
save_ckpt,
)
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.loss import compute_loss
from torch_geometric.graphgym.register import register_train
from torch_geome... | 2,697 | 34.038961 | 77 | py |
GraphGPS | GraphGPS-main/graphgps/train/custom_train.py | import logging
import time
import numpy as np
import torch
from torch_geometric.graphgym.checkpoint import load_ckpt, save_ckpt, clean_ckpt
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.loss import compute_loss
from torch_geometric.graphgym.register import register_train
from torch_geom... | 16,045 | 40.569948 | 96 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/example.py | import torch
from ogb.utils.features import get_bond_feature_dims
from torch_geometric.graphgym.register import (
register_edge_encoder,
register_node_encoder,
)
@register_node_encoder('example')
class ExampleNodeEncoder(torch.nn.Module):
"""
Provides an encoder for integer node features
... | 1,525 | 28.921569 | 78 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/laplace_pos_encoder.py | import torch
import torch.nn as nn
import torch_geometric.graphgym.register as register
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import register_node_encoder
@register_node_encoder('LapPE')
class LapPENodeEncoder(torch.nn.Module):
"""Laplace Positional Embedding node ... | 6,296 | 42.427586 | 106 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/equivstable_laplace_pos_encoder.py | import torch
import torch.nn as nn
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import register_node_encoder
@register_node_encoder('EquivStableLapPE')
class EquivStableLapPENodeEncoder(torch.nn.Module):
"""Equivariant and Stable Laplace Positional Embedding node encoder.... | 1,831 | 34.230769 | 84 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/kernel_pos_encoder.py | import torch
import torch.nn as nn
import torch_geometric.graphgym.register as register
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import register_node_encoder
class KernelPENodeEncoder(torch.nn.Module):
"""Configurable kernel-based Positional Encoding node encoder.
... | 5,202 | 40.624 | 83 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/ast_encoder.py | import torch
from torch_geometric.graphgym.register import (register_node_encoder,
register_edge_encoder)
"""
=== Description of the ogbg-code2 dataset ===
* Node Encoder code based on OGB's:
https://github.com/snap-stanford/ogb/blob/master/examples/graphproppred/code2/u... | 3,086 | 34.895349 | 98 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/linear_node_encoder.py | import torch
from torch_geometric.graphgym import cfg
from torch_geometric.graphgym.register import register_node_encoder
@register_node_encoder('LinearNode')
class LinearNodeEncoder(torch.nn.Module):
def __init__(self, emb_dim):
super().__init__()
self.encoder = torch.nn.Linear(cfg.share... | 430 | 25.9375 | 67 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/composed_encoders.py | import torch
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.models.encoder import AtomEncoder
from torch_geometric.graphgym.register import register_node_encoder
from graphgps.encoder.ast_encoder import ASTNodeEncoder
from graphgps.encoder.kernel_pos_encoder import RWSENodeEncoder, \
... | 6,343 | 39.666667 | 131 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/voc_superpixels_encoder.py | import torch
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import (register_node_encoder,
register_edge_encoder)
"""
=== Description of the VOCSuperpixels dataset ===
Each graph is a tuple (x, edge_attr, edge_index, y)
Shape of x ... | 1,373 | 30.227273 | 86 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/type_dict_encoder.py | import torch
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import (register_node_encoder,
register_edge_encoder)
"""
Generic Node and Edge encoders for datasets with node/edge features that
consist of only one type dictionary thus ... | 3,370 | 27.811966 | 108 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/dummy_edge_encoder.py | import torch
from torch_geometric.graphgym.register import register_edge_encoder
@register_edge_encoder('DummyEdge')
class DummyEdgeEncoder(torch.nn.Module):
def __init__(self, emb_dim):
super().__init__()
self.encoder = torch.nn.Embedding(num_embeddings=1,
... | 590 | 31.833333 | 74 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/ppa_encoder.py | import torch
from torch_geometric.graphgym.register import (register_node_encoder,
register_edge_encoder)
@register_node_encoder('PPANode')
class PPANodeEncoder(torch.nn.Module):
"""
Uniform input node embedding for PPA that has no node features.
"""
def... | 813 | 26.133333 | 69 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/graphormer_encoder.py | import networkx as nx
import torch
import torch.nn.functional as F
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import register_node_encoder
from torch_geometric.utils import to_dense_adj, to_networkx
# Permutes from (batch, node, node, head) to (batch, head, node, node)
BATCH... | 11,444 | 40.467391 | 128 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/signnet_pos_encoder.py | """
SignNet https://arxiv.org/abs/2202.13013
based on https://github.com/cptq/SignNet-BasisNet
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import register_node_encoder
from torch_geometric.nn import GINConv... | 12,140 | 42.516129 | 109 | py |
GraphGPS | GraphGPS-main/graphgps/encoder/linear_edge_encoder.py | import torch
from torch_geometric.graphgym import cfg
from torch_geometric.graphgym.register import register_edge_encoder
@register_edge_encoder('LinearEdge')
class LinearEdgeEncoder(torch.nn.Module):
def __init__(self, emb_dim):
super().__init__()
if cfg.dataset.name in ['MNIST', 'CIFAR10']:
... | 697 | 33.9 | 80 | py |
GraphGPS | GraphGPS-main/graphgps/loader/master_loader.py | import logging
import os.path as osp
import time
from functools import partial
import numpy as np
import torch
import torch_geometric.transforms as T
from numpy.random import default_rng
from ogb.graphproppred import PygGraphPropPredDataset
from torch_geometric.datasets import (Actor, GNNBenchmarkDataset, Planetoid,
... | 24,859 | 37.783151 | 99 | py |
GraphGPS | GraphGPS-main/graphgps/loader/split_generator.py | import json
import logging
import os
import numpy as np
from sklearn.model_selection import KFold, StratifiedKFold, ShuffleSplit
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.loader import index2mask, set_dataset_attr
def prepare_splits(dataset):
"""Ready train/val/test splits.
... | 10,280 | 36.797794 | 100 | py |
GraphGPS | GraphGPS-main/graphgps/loader/ogbg_code2_utils.py | """
Util functions copied from OGB for ogbg-code2 dataset:
https://github.com/snap-stanford/ogb/blob/master/examples/graphproppred/code2/utils.py
"""
import numpy as np
import torch
idx2vocab = []
def get_vocab_mapping(seq_list, num_vocab):
'''
Input:
seq_list: a list of sequences
... | 6,576 | 30.927184 | 127 | py |
GraphGPS | GraphGPS-main/graphgps/loader/dataset/peptides_structural.py | import hashlib
import os.path as osp
import pickle
import shutil
import pandas as pd
import torch
from ogb.utils import smiles2graph
from ogb.utils.torch_util import replace_numpy_with_torchtensor
from ogb.utils.url import decide_download
from torch_geometric.data import Data, InMemoryDataset, download_url
from tqdm i... | 6,952 | 40.885542 | 134 | py |
GraphGPS | GraphGPS-main/graphgps/loader/dataset/aqsol_molecules.py | import os
import os.path as osp
import shutil
import pickle
import torch
from tqdm import tqdm
from torch_geometric.data import (InMemoryDataset, Data, download_url,
extract_zip)
from torch_geometric.utils import add_self_loops
class AQSOL(InMemoryDataset):
r"""The AQSOL dataset... | 5,886 | 42.932836 | 113 | py |
GraphGPS | GraphGPS-main/graphgps/loader/dataset/peptides_functional.py | import hashlib
import os.path as osp
import pickle
import shutil
import pandas as pd
import torch
from ogb.utils import smiles2graph
from ogb.utils.torch_util import replace_numpy_with_torchtensor
from ogb.utils.url import decide_download
from torch_geometric.data import Data, InMemoryDataset, download_url
from tqdm i... | 5,670 | 37.842466 | 124 | py |
GraphGPS | GraphGPS-main/graphgps/loader/dataset/malnet_tiny.py | from typing import Optional, Callable, List
import os
import glob
import os.path as osp
import torch
from torch_geometric.data import (InMemoryDataset, Data, download_url,
extract_tar, extract_zip)
from torch_geometric.utils import remove_isolated_nodes
"""
This is a local copy of M... | 5,513 | 43.112 | 97 | py |
GraphGPS | GraphGPS-main/graphgps/loader/dataset/coco_superpixels.py | import os
import os.path as osp
import shutil
import pickle
import torch
from tqdm import tqdm
from torch_geometric.data import (InMemoryDataset, Data, download_url,
extract_zip)
class COCOSuperpixels(InMemoryDataset):
r"""The COCOSuperpixels dataset which contains image superpi... | 8,717 | 45.37234 | 128 | py |
GraphGPS | GraphGPS-main/graphgps/loader/dataset/voc_superpixels.py | import os
import os.path as osp
import shutil
import pickle
import torch
from tqdm import tqdm
from torch_geometric.data import (InMemoryDataset, Data, download_url,
extract_zip)
class VOCSuperpixels(InMemoryDataset):
r"""The VOCSuperpixels dataset which contains image superpixe... | 7,995 | 46.313609 | 127 | py |
GraphGPS | GraphGPS-main/graphgps/loader/dataset/pcqm4mv2_contact.py | import hashlib
import os.path as osp
import shutil
import numpy as np
import pandas as pd
import torch
from joblib import Parallel, delayed
from ogb.utils.features import atom_to_feature_vector, bond_to_feature_vector
from ogb.utils.torch_util import replace_numpy_with_torchtensor
from ogb.utils.url import decide_down... | 21,553 | 38.694291 | 115 | py |
GraphGPS | GraphGPS-main/graphgps/loss/multilabel_classification_loss.py | import torch.nn as nn
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import register_loss
@register_loss('multilabel_cross_entropy')
def multilabel_cross_entropy(pred, true):
"""Multilabel cross-entropy loss.
"""
if cfg.dataset.task_type == 'classification_multilabe... | 692 | 39.764706 | 76 | py |
GraphGPS | GraphGPS-main/graphgps/loss/subtoken_prediction_loss.py | import torch
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import register_loss
@register_loss('subtoken_cross_entropy')
def subtoken_cross_entropy(pred_list, true):
"""Subtoken prediction cross-entropy loss for ogbg-code2.
"""
if cfg.dataset.task_type == 'subtoken... | 801 | 37.190476 | 91 | py |
GraphGPS | GraphGPS-main/graphgps/loss/weighted_cross_entropy.py | import torch
import torch.nn.functional as F
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import register_loss
@register_loss('weighted_cross_entropy')
def weighted_cross_entropy(pred, true):
"""Weighted cross-entropy for unbalanced classes.
"""
if cfg.model.loss_... | 1,232 | 40.1 | 79 | py |
GraphGPS | GraphGPS-main/graphgps/loss/l1.py | import torch.nn as nn
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import register_loss
@register_loss('l1_losses')
def l1_losses(pred, true):
if cfg.model.loss_fun == 'l1':
l1_loss = nn.L1Loss()
loss = l1_loss(pred, true)
return loss, pred
eli... | 453 | 27.375 | 59 | py |
GraphGPS | GraphGPS-main/graphgps/optimizer/extra_optimizers.py | import logging
import math
from typing import Iterator
from dataclasses import dataclass
import torch.optim as optim
from torch.nn import Parameter
from torch.optim import Adagrad, AdamW, Optimizer
from torch.optim.lr_scheduler import ReduceLROnPlateau
from torch_geometric.graphgym.optim import SchedulerConfig
import... | 9,939 | 40.244813 | 115 | py |
GraphGPS | GraphGPS-main/graphgps/act/example.py | from functools import partial
import torch
import torch.nn as nn
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import register_act
class SWISH(nn.Module):
def __init__(self, inplace=False):
super().__init__()
self.inplace = inplace
def forward(self, x... | 675 | 24.037037 | 77 | py |
GraphGPS | GraphGPS-main/graphgps/transform/task_preprocessing.py | import torch
def shuffle(tensor):
idx = torch.randperm(len(tensor))
return tensor[idx]
def task_specific_preprocessing(data, cfg):
"""Task-specific preprocessing before the dataset is logged and finalized.
Args:
data: PyG graph
cfg: Main configuration node
Returns:
Exte... | 2,172 | 31.924242 | 111 | py |
GraphGPS | GraphGPS-main/graphgps/transform/posenc_stats.py | from copy import deepcopy
import numpy as np
import torch
import torch.nn.functional as F
from numpy.linalg import eigvals
from torch_geometric.utils import (get_laplacian, to_scipy_sparse_matrix,
to_undirected, to_dense_adj, scatter)
from torch_geometric.utils.num_nodes import maybe... | 17,150 | 41.558313 | 119 | py |
GraphGPS | GraphGPS-main/graphgps/transform/transforms.py | import logging
import torch
from torch_geometric.utils import subgraph
from tqdm import tqdm
def pre_transform_in_memory(dataset, transform_func, show_progress=False):
"""Pre-transform already loaded PyG dataset object.
Apply transform function to a loaded PyG dataset object so that
the transformed resu... | 2,870 | 34.012195 | 77 | py |
GraphGPS | GraphGPS-main/graphgps/stage/example.py | import torch.nn as nn
import torch.nn.functional as F
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.models.layer import GeneralLayer
from torch_geometric.graphgym.register import register_stage
def GNNLayer(dim_in, dim_out, has_act=True):
return GeneralLayer(cfg.gnn.layer_type, di... | 944 | 30.5 | 69 | py |
GraphGPS | GraphGPS-main/graphgps/layer/example.py | import torch
import torch.nn as nn
from torch.nn import Parameter
from torch_geometric.graphgym.config import cfg
from torch_geometric.graphgym.register import register_layer
from torch_geometric.nn.conv import MessagePassing
from torch_geometric.nn.inits import glorot, zeros
# Note: A registered GNN layer should tak... | 2,868 | 26.32381 | 72 | py |
GraphGPS | GraphGPS-main/graphgps/layer/san2_layer.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_geometric.utils.num_nodes import maybe_num_nodes
from torch_scatter import scatter, scatter_max, scatter_add
from graphgps.utils import negate_edge_index
def pyg_softmax(src, index, num_nodes=None):
r"""Computes a sp... | 8,847 | 36.020921 | 120 | py |
GraphGPS | GraphGPS-main/graphgps/layer/gps_layer.py | import numpy as np
import torch
import torch.nn as nn
import torch_geometric.graphgym.register as register
import torch_geometric.nn as pygnn
from performer_pytorch import SelfAttention
from torch_geometric.data import Batch
from torch_geometric.nn import Linear as Linear_pyg
from torch_geometric.utils import to_dense_... | 11,931 | 44.026415 | 87 | py |
GraphGPS | GraphGPS-main/graphgps/layer/san_layer.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_scatter import scatter
from graphgps.utils import negate_edge_index
class MultiHeadAttentionLayer(nn.Module):
"""Multi-Head Graph Attention Layer.
Ported to PyG from original repo:
https://github.com/DevinKr... | 8,080 | 36.239631 | 111 | py |
GraphGPS | GraphGPS-main/graphgps/layer/graphormer_layer.py | import torch
from torch_geometric.utils import to_dense_batch
class GraphormerLayer(torch.nn.Module):
def __init__(self, embed_dim: int, num_heads: int, dropout: float,
attention_dropout: float, mlp_dropout: float):
"""Implementation of the Graphormer layer.
This layer is based on... | 2,047 | 39.96 | 93 | py |
GraphGPS | GraphGPS-main/graphgps/layer/performer_layer.py | """
Thanks LucidRains!
https://github.com/lucidrains/performer-pytorch/blob/main/performer_pytorch/performer_pytorch.py
MIT License
Copyright (c) 2020 Phil Wang
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
i... | 23,601 | 34.122024 | 148 | py |
GraphGPS | GraphGPS-main/graphgps/layer/bigbird_layer.py | """
Source code adapted from HuggingFace: https://huggingface.co/transformers/v4.9.2/_modules/transformers/models/big_bird/modeling_big_bird.html#BigBirdModel
"""
# Copyright 2021 Google Research and The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# ... | 76,761 | 43.942623 | 201 | py |
GraphGPS | GraphGPS-main/graphgps/layer/gine_conv_layer.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch_geometric.nn as pyg_nn
from torch_geometric.graphgym.models.layer import LayerConfig
from torch_geometric.graphgym.register import register_layer
from torch_geometric.nn import Linear as Linear_pyg
class GINEConvESLapPE(pyg_nn.conv.Messa... | 4,693 | 34.293233 | 79 | py |
GraphGPS | GraphGPS-main/graphgps/layer/gatedgcn_layer.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch_geometric.graphgym.register as register
import torch_geometric.nn as pyg_nn
from torch_geometric.graphgym.models.layer import LayerConfig
from torch_geometric.graphgym.register import register_layer
from torch_scatter import scatter
class... | 5,341 | 33.24359 | 124 | py |
RoadNet-RT | RoadNet-RT-main/roadnet_train.py | import os
#os.environ['CUDA_VISIBLE_DEVICES'] = '4'
import json
import cv2
import keras
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from keras import backend as K
import segmentation_models as sm
from roadnet.utils import visualize
from roadnet.data_loader import Dataset, Dataloder
fro... | 8,150 | 32.821577 | 120 | py |
RoadNet-RT | RoadNet-RT-main/roadnet_test.py | import os
#os.environ['CUDA_VISIBLE_DEVICES'] = '3'
from shutil import rmtree
#import cv2
import json
import keras
import numpy as np
import matplotlib.pyplot as plt
import PIL.Image as Image
import segmentation_models as sm
from roadnet.utils import visualize, denormalize
from roadnet.data_loader import Dataset, D... | 8,775 | 30.797101 | 107 | py |
RoadNet-RT | RoadNet-RT-main/segmentation_models/utils.py | """ Utility functions for segmentation models """
from keras_applications import get_submodules_from_kwargs
from . import inject_global_submodules
def set_trainable(model, recompile=True, **kwargs):
"""Set all layers of model trainable and recompile it
Note:
Model is recompiled using same optimizer,... | 3,002 | 32.366667 | 87 | py |
RoadNet-RT | RoadNet-RT-main/segmentation_models/__init__.py | import os
import functools
from .__version__ import __version__
from . import base
_KERAS_FRAMEWORK_NAME = 'keras'
_TF_KERAS_FRAMEWORK_NAME = 'tf.keras'
_DEFAULT_KERAS_FRAMEWORK = _KERAS_FRAMEWORK_NAME
_KERAS_FRAMEWORK = None
_KERAS_BACKEND = None
_KERAS_LAYERS = None
_KERAS_MODELS = None
_KERAS_UTILS = None
_KERAS_L... | 4,041 | 27.464789 | 103 | py |
RoadNet-RT | RoadNet-RT-main/segmentation_models/models/pspnet.py | from keras_applications import get_submodules_from_kwargs
from ._common_blocks import Conv2dBn
from ._utils import freeze_model
from ..backbones.backbones_factory import Backbones
backend = None
layers = None
models = None
keras_utils = None
# ---------------------------------------------------------------------
# ... | 8,413 | 33.342857 | 113 | py |
RoadNet-RT | RoadNet-RT-main/segmentation_models/models/_utils.py | from keras_applications import get_submodules_from_kwargs
def freeze_model(model, **kwargs):
"""Set all layers non trainable, excluding BatchNormalization layers"""
_, layers, _, _ = get_submodules_from_kwargs(kwargs)
for layer in model.layers:
if not isinstance(layer, layers.BatchNormalization):
... | 367 | 32.454545 | 75 | py |
RoadNet-RT | RoadNet-RT-main/segmentation_models/models/linknet.py | from keras_applications import get_submodules_from_kwargs
from ._common_blocks import Conv2dBn
from ._utils import freeze_model
from ..backbones.backbones_factory import Backbones
backend = None
layers = None
models = None
keras_utils = None
# ---------------------------------------------------------------------
# ... | 9,676 | 33.935018 | 125 | py |
RoadNet-RT | RoadNet-RT-main/segmentation_models/models/unet.py | from keras_applications import get_submodules_from_kwargs
from ._common_blocks import Conv2dBn
from ._utils import freeze_model
from ..backbones.backbones_factory import Backbones
backend = None
layers = None
models = None
keras_utils = None
# ---------------------------------------------------------------------
# ... | 8,328 | 32.051587 | 121 | py |
RoadNet-RT | RoadNet-RT-main/segmentation_models/models/fpn.py | from keras_applications import get_submodules_from_kwargs
from ._common_blocks import Conv2dBn
from ._utils import freeze_model
from ..backbones.backbones_factory import Backbones
backend = None
layers = None
models = None
keras_utils = None
# ---------------------------------------------------------------------
# ... | 9,008 | 34.468504 | 125 | py |
RoadNet-RT | RoadNet-RT-main/segmentation_models/models/_common_blocks.py | from keras_applications import get_submodules_from_kwargs
def Conv2dBn(
filters,
kernel_size,
strides=(1, 1),
padding='valid',
data_format=None,
dilation_rate=(1, 1),
activation=None,
kernel_initializer='glorot_uniform',
bias_initializer='zeros',... | 2,133 | 29.485714 | 82 | py |
RoadNet-RT | RoadNet-RT-main/segmentation_models/base/functional.py | SMOOTH = 1e-5
# ----------------------------------------------------------------
# Helpers
# ----------------------------------------------------------------
def _gather_channels(x, indexes, **kwargs):
"""Slice tensor along channels axis by given indexes"""
backend = kwargs['backend']
if backend.image_... | 11,668 | 36.763754 | 118 | py |
RoadNet-RT | RoadNet-RT-main/segmentation_models/backbones/inception_v3.py | """Inception V3 model for Keras.
Note that the input image format for this model is different than for
the VGG16 and ResNet models (299x299 instead of 224x224),
and that the input preprocessing function is also different (same as Xception).
# Reference
- [Rethinking the Inception Architecture for Computer Vision](
... | 14,611 | 36.180662 | 80 | py |
RoadNet-RT | RoadNet-RT-main/segmentation_models/backbones/inception_resnet_v2.py | """Inception-ResNet V2 model for Keras.
Model naming and structure follows TF-slim implementation
(which has some additional layers and different number of
filters from the original arXiv paper):
https://github.com/tensorflow/models/blob/master/research/slim/nets/inception_resnet_v2.py
Pre-trained ImageNet weights are ... | 14,925 | 41.645714 | 90 | py |
RoadNet-RT | RoadNet-RT-main/tests/test_models.py | import os
import pytest
import random
import six
import numpy as np
import segmentation_models as sm
from segmentation_models import Unet
from segmentation_models import Linknet
from segmentation_models import PSPNet
from segmentation_models import FPN
from segmentation_models import get_available_backbone_names
if s... | 3,550 | 24.919708 | 80 | py |
RoadNet-RT | RoadNet-RT-main/tests/test_metrics.py | import pytest
import numpy as np
import segmentation_models as sm
from segmentation_models.metrics import IOUScore, FScore
from segmentation_models.losses import JaccardLoss, DiceLoss
if sm.framework() == sm._TF_KERAS_FRAMEWORK_NAME:
from tensorflow import keras
elif sm.framework() == sm._KERAS_FRAMEWORK_NAME:
... | 4,481 | 19.280543 | 95 | py |
RoadNet-RT | RoadNet-RT-main/tests/test_utils.py | import pytest
import numpy as np
import segmentation_models as sm
from segmentation_models.utils import set_regularization
from segmentation_models import Unet
if sm.framework() == sm._TF_KERAS_FRAMEWORK_NAME:
from tensorflow import keras
elif sm.framework() == sm._KERAS_FRAMEWORK_NAME:
import keras
else:
... | 3,143 | 26.823009 | 91 | py |
RoadNet-RT | RoadNet-RT-main/roadnet/test.py | import keras as K
import keras.layers as L
import keras.models as M
def ConvBNReLU(x, filter=64, kernel_size=3, strides=1, use_bias=True, name="ConvBNReLU"):
x = L.Conv2D(filters=filter, kernel_size=kernel_size, strides=(strides, strides),
padding="same", use_bias=use_bias, name=name+"_conv")(x)... | 2,438 | 36.523077 | 119 | py |
RoadNet-RT | RoadNet-RT-main/roadnet/data_loader.py | import numpy as np
import os
import cv2
import keras
import matplotlib.pyplot as plt
# classes for data loading and preprocessing
class Dataset:
"""CamVid Dataset. Read images, apply augmentation and preprocessing transformations.
Args:
images_dir (str): path to images folder
masks_dir (str): ... | 8,754 | 33.742063 | 95 | py |
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