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repo stringlengths 2 152 ⌀ | file stringlengths 15 239 | code stringlengths 0 58.4M | file_length int64 0 58.4M | avg_line_length float64 0 1.81M | max_line_length int64 0 12.7M | extension_type stringclasses 364
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mopo | mopo-master/softlearning/policies/gaussian_policy.py | """GaussianPolicy."""
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import tensorflow_probability as tfp
from softlearning.distributions.squash_bijector import SquashBijector
from softlearning.models.feedforward import feedforward_model
from .base_policy import LatentSpacePolicy
SC... | 8,809 | 33.147287 | 78 | py |
mopo | mopo-master/softlearning/policies/uniform_policy.py | from collections import OrderedDict
import tensorflow as tf
from .base_policy import BasePolicy
class UniformPolicy(BasePolicy):
def __init__(self, input_shapes, output_shape, action_range=(-1.0, 1.0)):
super(UniformPolicy, self).__init__()
self._Serializable__initialize(locals())
self.... | 1,887 | 26.362319 | 77 | py |
mopo | mopo-master/softlearning/policies/utils.py | from copy import deepcopy
from softlearning.preprocessors.utils import get_preprocessor_from_params
def get_gaussian_policy(env, Q, **kwargs):
from .gaussian_policy import FeedforwardGaussianPolicy
policy = FeedforwardGaussianPolicy(
input_shapes=(env.active_observation_shape, ),
output_shape... | 1,378 | 25.519231 | 73 | py |
mopo | mopo-master/softlearning/preprocessors/__init__.py | 0 | 0 | 0 | py | |
mopo | mopo-master/softlearning/preprocessors/convnet.py | import tensorflow as tf
from softlearning.models.feedforward import feedforward_model
from softlearning.utils.keras import PicklableKerasModel
def convnet_preprocessor(
input_shapes,
image_shape,
output_size,
conv_filters=(32, 32),
conv_kernel_sizes=((5, 5), (5, 5)),
p... | 2,328 | 28.858974 | 71 | py |
mopo | mopo-master/softlearning/preprocessors/utils.py | from copy import deepcopy
def get_convnet_preprocessor(observation_shape,
name='convnet_preprocessor',
**kwargs):
from .convnet import convnet_preprocessor
preprocessor = convnet_preprocessor(
input_shapes=(observation_shape, ), name=name, **kw... | 1,654 | 29.090909 | 76 | py |
mopo | mopo-master/softlearning/replay_pools/__init__.py | from .simple_replay_pool import SimpleReplayPool
from .extra_policy_info_replay_pool import ExtraPolicyInfoReplayPool
from .union_pool import UnionPool
from .trajectory_replay_pool import TrajectoryReplayPool
| 209 | 41 | 68 | py |
mopo | mopo-master/softlearning/replay_pools/extra_policy_info_replay_pool.py | from .simple_replay_pool import SimpleReplayPool
class ExtraPolicyInfoReplayPool(SimpleReplayPool):
def __init__(self, *args, **kwargs):
super(ExtraPolicyInfoReplayPool, self).__init__(*args, **kwargs)
fields = {
'raw_actions': {
'shape': self._action_space.shape,
... | 515 | 24.8 | 72 | py |
mopo | mopo-master/softlearning/replay_pools/flexible_replay_pool.py | import gzip
import pickle
import numpy as np
from .replay_pool import ReplayPool
class FlexibleReplayPool(ReplayPool):
def __init__(self, max_size, fields_attrs, obs_filter=False, modify_rew=False):
super(FlexibleReplayPool, self).__init__()
max_size = int(max_size)
self._max_size = max... | 6,109 | 32.944444 | 139 | py |
mopo | mopo-master/softlearning/replay_pools/replay_pool.py | import abc
class ReplayPool(object):
"""A class used to save and replay data."""
@abc.abstractmethod
def add_sample(self, sample):
"""Add a transition tuple."""
pass
@abc.abstractmethod
def terminate_episode(self):
"""Clean up pool after episode termination."""
pa... | 1,036 | 24.925 | 77 | py |
mopo | mopo-master/softlearning/replay_pools/simple_replay_pool.py | from collections import defaultdict
import numpy as np
from gym.spaces import Box, Dict, Discrete
import pdb
from .flexible_replay_pool import FlexibleReplayPool
def normalize_observation_fields(observation_space, name='observations'):
if isinstance(observation_space, Dict):
fields = [
norma... | 3,348 | 30.299065 | 73 | py |
mopo | mopo-master/softlearning/replay_pools/trajectory_replay_pool.py | from collections import deque
import gzip
import pickle
from itertools import islice
import numpy as np
from softlearning.utils.numpy import softmax
from .replay_pool import ReplayPool
def random_int_with_variable_range(mins, maxs):
result = np.floor(np.random.uniform(mins, maxs)).astype(int)
return result
... | 5,429 | 31.51497 | 89 | py |
mopo | mopo-master/softlearning/replay_pools/union_pool.py | import numpy as np
from .replay_pool import ReplayPool
class UnionPool(ReplayPool):
def __init__(self, pools):
pool_sizes = np.array([b.size for b in pools])
self._total_size = sum(pool_sizes)
self._normalized_pool_sizes = pool_sizes / self._total_size
self.pools = pools
def... | 1,263 | 27.088889 | 77 | py |
mopo | mopo-master/softlearning/replay_pools/utils.py | from copy import deepcopy
from . import (
simple_replay_pool,
extra_policy_info_replay_pool,
union_pool,
trajectory_replay_pool)
POOL_CLASSES = {
'SimpleReplayPool': simple_replay_pool.SimpleReplayPool,
'TrajectoryReplayPool': trajectory_replay_pool.TrajectoryReplayPool,
'ExtraPolicyInfoR... | 945 | 26.823529 | 72 | py |
mopo | mopo-master/softlearning/samplers/__init__.py | from .base_sampler import BaseSampler
from .dummy_sampler import DummySampler
from .simple_sampler import SimpleSampler
from .remote_sampler import RemoteSampler
from .extra_policy_info_sampler import ExtraPolicyInfoSampler
from .utils import rollout, rollouts
| 261 | 36.428571 | 61 | py |
mopo | mopo-master/softlearning/samplers/base_sampler.py | from collections import deque, OrderedDict
from itertools import islice
class BaseSampler(object):
def __init__(self,
max_path_length,
min_pool_size,
batch_size,
store_last_n_paths=10):
self._max_path_length = max_path_length
self... | 1,904 | 25.458333 | 65 | py |
mopo | mopo-master/softlearning/samplers/dummy_sampler.py | from .base_sampler import BaseSampler
class DummySampler(BaseSampler):
def __init__(self, batch_size, max_path_length):
super(DummySampler, self).__init__(
max_path_length=max_path_length,
min_pool_size=0,
batch_size=batch_size)
def sample(self):
pass
| 315 | 23.307692 | 52 | py |
mopo | mopo-master/softlearning/samplers/explore_sampler.py | from collections import defaultdict
import numpy as np
from .base_sampler import BaseSampler
class ExploreSampler(BaseSampler):
def __init__(self, **kwargs):
super(ExploreSampler, self).__init__(**kwargs)
self._path_length = 0
self._path_return = 0
self._current_path = defaultdi... | 3,491 | 31.635514 | 72 | py |
mopo | mopo-master/softlearning/samplers/extra_policy_info_sampler.py | """Sampler that stores raw actions and log pis from policy."""
from collections import defaultdict
import numpy as np
from .simple_sampler import SimpleSampler
class ExtraPolicyInfoSampler(SimpleSampler):
def sample(self):
if self._current_observation is None:
self._current_observation = s... | 2,159 | 33.83871 | 76 | py |
mopo | mopo-master/softlearning/samplers/remote_sampler.py | import pickle
from collections import OrderedDict
import ray
import tensorflow as tf
import numpy as np
from .base_sampler import BaseSampler
from .utils import rollout
class RemoteSampler(BaseSampler):
def __init__(self, **kwargs):
super(RemoteSampler, self).__init__(**kwargs)
self._remote_en... | 3,589 | 29.683761 | 76 | py |
mopo | mopo-master/softlearning/samplers/simple_sampler.py | from collections import defaultdict
import numpy as np
from .base_sampler import BaseSampler
class SimpleSampler(BaseSampler):
def __init__(self, **kwargs):
super(SimpleSampler, self).__init__(**kwargs)
self._path_length = 0
self._path_return = 0
self._current_path = defaultdict... | 3,608 | 31.809091 | 76 | py |
mopo | mopo-master/softlearning/samplers/utils.py | from copy import deepcopy
import numpy as np
from softlearning import replay_pools
from . import (
dummy_sampler,
extra_policy_info_sampler,
remote_sampler,
base_sampler,
simple_sampler)
def get_sampler_from_variant(variant, *args, **kwargs):
SAMPLERS = {
'DummySampler': dummy_sample... | 2,515 | 25.765957 | 64 | py |
mopo | mopo-master/softlearning/scripts/__init__.py | 0 | 0 | 0 | py | |
mopo | mopo-master/softlearning/scripts/console_scripts.py | """A command line interface that exposes softlearning examples to user.
This package exposes the functions in examples.instrument module to the user
through a cli, which allows seamless runs of examples in different modes (e.g.
locally, in google compute engine, or ec2).
There are two types of cli commands in this f... | 6,645 | 31.10628 | 79 | py |
mopo | mopo-master/softlearning/utils/keras.py | import tempfile
import tensorflow as tf
class PicklableKerasModel(tf.keras.Model):
def __getstate__(self):
with tempfile.NamedTemporaryFile(suffix='.hdf5', delete=True) as fd:
tf.keras.models.save_model(self, fd.name, overwrite=True)
model_str = fd.read()
d = {'model_str':... | 1,072 | 31.515152 | 76 | py |
mopo | mopo-master/softlearning/utils/numpy.py | import numpy as np
def softmax(x):
max_x = np.max(x)
exp_x = np.exp(x - max_x)
return exp_x / np.sum(exp_x)
| 122 | 14.375 | 32 | py |
mopo | mopo-master/softlearning/value_functions/__init__.py | 0 | 0 | 0 | py | |
mopo | mopo-master/softlearning/value_functions/utils.py | from copy import deepcopy
from softlearning.preprocessors.utils import get_preprocessor_from_params
from . import vanilla
def create_double_value_function(value_fn, *args, **kwargs):
# TODO(hartikainen): The double Q-function should support the same
# interface as the regular ones. Implement the double min-t... | 1,778 | 31.944444 | 73 | py |
mopo | mopo-master/softlearning/value_functions/value_function.py | import tensorflow as tf
import numpy as np
from serializable import Serializable
class SumQFunction(Serializable):
def __init__(self,
observation_shape,
action_shape,
q_functions):
self._Serializable__initialize(locals())
self.q_functions = q_fu... | 1,833 | 30.62069 | 77 | py |
mopo | mopo-master/softlearning/value_functions/vanilla.py | from softlearning.models.feedforward import feedforward_model
def create_feedforward_Q_function(observation_shape,
action_shape,
*args,
observation_preprocessor=None,
name='feedforwa... | 1,143 | 32.647059 | 64 | py |
MNC | MNC-master/README.md | # Instance-aware Semantic Segmentation via Multi-task Network Cascades
By Jifeng Dai, Kaiming He, Jian Sun
This python version is re-implemented by [Haozhi Qi](https://github.com/Oh233) when he was an intern at Microsoft Research.
### Introduction
MNC is an instance-aware semantic segmentation system based on deep ... | 6,766 | 40.012121 | 452 | md |
MNC | MNC-master/data/scripts/fetch_imagenet_models.sh | #!/bin/bash
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd ${DIR}
URL="https://onedrive.live.com/download?resid=F371D9563727B96F!91967&authkey=!AKjrYZBFAfb6JBQ"
echo "Downloading VGG16.mask.caffemodel model..."
mkdir ../imagenet_models/
wget ${URL} -O VGG16.mask.caffemodel
mv VGG16.mask.caffemodel ../... | 563 | 24.636364 | 94 | sh |
MNC | MNC-master/data/scripts/fetch_mcg_data.sh | #!/bin/bash
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd ${DIR}
FILE=MCG-Pascal-Main_trainvaltest_2012-proposals.tgz
URL=https://data.vision.ee.ethz.ch/jpont/mcg/${FILE}
echo "Downloading MCG proposals data..."
wget $URL -O ${FILE}
echo "Unzipping..."
mkdir tmp
tar zxvf ${FILE} -C tmp/ --strip-compo... | 427 | 16.12 | 55 | sh |
MNC | MNC-master/data/scripts/fetch_mnc_model.sh | #!/bin/bash
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd ${DIR}
URL="https://onedrive.live.com/download?resid=571EABC0F8C2A19C!1103&authkey=!ALXduVujs-7r6Ug"
echo "Downloading mnc model..."
mkdir ../mnc_model
wget ${URL} -O mnc_model.caffemodel.h5
mv mnc_model.caffemodel.h5 ../mnc_model/
| 309 | 21.142857 | 93 | sh |
MNC | MNC-master/data/scripts/fetch_sbd_data.sh | #!/bin/bash
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
cd ${DIR}
FILE=benchmark.tgz
URL=http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/semantic_contours/${FILE}
echo "Downloading SBD data..."
wget $URL -O ${FILE}
echo "Unzipping..."
mkdir tmp
tar zxvf ${FILE} -C tmp/ --strip-compon... | 470 | 19.478261 | 95 | sh |
MNC | MNC-master/experiments/cfgs/VGG16/cfm.yml | EXP_DIR: cfm
MASK_SIZE: 21
CFM_MODE: True
MNC_MODE: False
RNG_SEED: 821
TRAIN:
HAS_RPN: False
IMS_PER_BATCH: 1
SCALES: [480, 576, 688, 864, 1024]
MAX_SIZE: 1500
TEST:
SCALES: [480, 576, 688, 864, 1024]
MAX_SIZE: 1500
GROUP_SCALE: 3
MAX_ROIS_GPU: [2000, 500]
USE_TOP_K_MCG: 2000
| 296 | 16.470588 | 36 | yml |
MNC | MNC-master/experiments/cfgs/VGG16/faster_rcnn_end2end.yml | EXP_DIR: faster_rcnn_end2end
MNC_MODE: False
TRAIN:
MIX_INDEX: False
IMS_PER_BATCH: 1
BBOX_NORMALIZE_TARGETS_PRECOMPUTED: True
BATCH_SIZE: 128
FG_FRACTION: [0.25]
BG_FRACTION: [1.0]
BG_THRESH_HI: [0.5]
BG_THRESH_LO: [0.1]
| 238 | 18.916667 | 42 | yml |
MNC | MNC-master/experiments/cfgs/VGG16/mnc_5stage.yml | EXP_DIR: mnc_5stage
MASK_SIZE: 21
TRAIN:
RPN_POST_NMS_TOP_N: 300
IMS_PER_BATCH: 1
BBOX_NORMALIZE_TARGETS_PRECOMPUTED: True
| 129 | 17.571429 | 42 | yml |
MNC | MNC-master/experiments/scripts/cfm.sh | #!/bin/bash
# Usage:
# ./experiments/scripts/cfm.sh GPU NET [--set ...]
# Example:
# ./experiments/scripts/cfm.sh 0 VGG16 \
# --set EXP_DIR foobar RNG_SEED 42 TRAIN.SCALES "[400,500,600,700]"
set -x
set -e
export PYTHONUNBUFFERED="True"
GPU_ID=$1
NET=$2
NET_lc=${NET,,}
ITERS=30000
DATASET_TRAIN=voc_2012_seg_train
... | 1,157 | 23.638298 | 86 | sh |
MNC | MNC-master/experiments/scripts/faster_rcnn_end2end.sh | #!/bin/bash
# Usage:
# ./experiments/scripts/faster_rcnn_end2end.sh GPU NET [--set ...]
# Example:
# ./experiments/scripts/faster_rcnn_end2end.sh 0 VGG16 \
# --set EXP_DIR foobar RNG_SEED 42 TRAIN.SCALES "[400,500,600,700]"
set -x
set -e
export PYTHONUNBUFFERED="True"
GPU_ID=$1
NET=$2
NET_lc=${NET,,}
ITERS=70000
D... | 1,280 | 25.142857 | 100 | sh |
MNC | MNC-master/experiments/scripts/mnc_5stage.sh | #!/bin/bash
# Usage:
# ./experiments/scripts/mnc_5stage.sh GPU NET [--set ...]
# Example:
# ./experiments/scripts/mnc_5stage.sh 0 VGG16 \
# --set EXP_DIR foobar RNG_SEED 42 TRAIN.SCALES "[400,500,600,700]"
set -x
set -e
export PYTHONUNBUFFERED="True"
GPU_ID=$1
NET=$2
NET_lc=${NET,,}
ITERS=25000
DATASET_TRAIN=voc_2... | 1,209 | 24.208333 | 91 | sh |
MNC | MNC-master/lib/mnc_config.py |
"""MNC config system
"""
import numpy as np
import os.path
from easydict import EasyDict as edict
__C = edict()
cfg = __C
# MNC/CFM mode
__C.MNC_MODE = True
__C.CFM_MODE = False
__C.EXP_DIR = 'default'
__C.USE_GPU_NMS = True
__C.GPU_ID = 0
__C.RNG_SEED = 3
__C.EPS = 1e-14
__C.PIXEL_MEANS = np.array([[[102.9801, 115... | 6,958 | 32.618357 | 91 | py |
MNC | MNC-master/lib/setup.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 6,247 | 36.413174 | 90 | py |
MNC | MNC-master/lib/caffeWrapper/SolverWrapper.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
imp... | 6,147 | 43.230216 | 103 | py |
MNC | MNC-master/lib/caffeWrapper/TesterWrapper.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 21,633 | 51.13012 | 123 | py |
MNC | MNC-master/lib/caffeWrapper/__init__.py | 0 | 0 | 0 | py | |
MNC | MNC-master/lib/datasets/__init__.py | 0 | 0 | 0 | py | |
MNC | MNC-master/lib/datasets/pascal_voc.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 3,522 | 27.642276 | 77 | py |
MNC | MNC-master/lib/datasets/pascal_voc_det.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 13,855 | 42.435737 | 134 | py |
MNC | MNC-master/lib/datasets/pascal_voc_seg.py | # --------------------------------------------------------
# Multitask Network Cascade
# Written by Haozhi Qi
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
import cPickle
import os
import scipy.io as sio
import nump... | 10,828 | 46.28821 | 116 | py |
MNC | MNC-master/lib/db/__init__.py | 0 | 0 | 0 | py | |
MNC | MNC-master/lib/db/imdb.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
from... | 970 | 32.482759 | 88 | py |
MNC | MNC-master/lib/db/maskdb.py | # --------------------------------------------------------
# Multitask Network Cascade
# Written by Haozhi Qi
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
from mnc_config import cfg
from db.imdb import get_imdb
d... | 1,162 | 29.605263 | 71 | py |
MNC | MNC-master/lib/db/roidb.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 6,862 | 37.55618 | 112 | py |
MNC | MNC-master/lib/nms/__init__.py | 0 | 0 | 0 | py | |
MNC | MNC-master/lib/nms/gpu_mv.hpp | void _mv(const float* all_boxes, const float* all_masks, const int all_boxes_num,
const int* candidate_inds, const int* candidate_start, const float* candidate_weights, const int candidate_num,
const int image_height, const int image_width, const int box_dim, const int mask_size, const int result_num,
... | 404 | 80 | 119 | hpp |
MNC | MNC-master/lib/nms/gpu_nms.hpp | void _nms(int* keep_out, int* num_out, const float* boxes_host, int boxes_num,
int boxes_dim, float nms_overlap_thresh, int device_id);
| 146 | 48 | 78 | hpp |
MNC | MNC-master/lib/nms/nms_wrapper.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
from... | 2,332 | 31.402778 | 77 | py |
MNC | MNC-master/lib/nms/py_cpu_nms.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 1,118 | 27.692308 | 77 | py |
MNC | MNC-master/lib/pylayer/__init__.py | 0 | 0 | 0 | py | |
MNC | MNC-master/lib/pylayer/anchor_target_layer.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 9,757 | 40.879828 | 94 | py |
MNC | MNC-master/lib/pylayer/cfm_data_layer.py | # --------------------------------------------------------
# Multitask Network Cascade
# Written by Haozhi Qi
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
import cv2
import yaml
import scipy
import numpy as np
impo... | 11,892 | 44.39313 | 122 | py |
MNC | MNC-master/lib/pylayer/mask_layer.py | # --------------------------------------------------------
# Multitask Network Cascade
# Written by Haozhi Qi
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
import caffe
import cv2
import numpy as np
from transform.m... | 3,988 | 37.728155 | 124 | py |
MNC | MNC-master/lib/pylayer/mnc_data_layer.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 5,826 | 37.589404 | 103 | py |
MNC | MNC-master/lib/pylayer/proposal_layer.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 10,386 | 43.965368 | 121 | py |
MNC | MNC-master/lib/pylayer/proposal_target_layer.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 9,255 | 41.654378 | 97 | py |
MNC | MNC-master/lib/pylayer/stage_bridge_layer.py | # --------------------------------------------------------
# Multitask Network Cascade
# Written by Haozhi Qi
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
import caffe
import numpy as np
import yaml
from transform.... | 11,685 | 44.648438 | 112 | py |
MNC | MNC-master/lib/transform/__init__.py | 0 | 0 | 0 | py | |
MNC | MNC-master/lib/transform/anchors.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 3,927 | 28.533835 | 78 | py |
MNC | MNC-master/lib/transform/bbox_transform.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 6,973 | 33.186275 | 97 | py |
MNC | MNC-master/lib/transform/mask_transform.py | # --------------------------------------------------------
# Multitask Network Cascade
# Written by Haozhi Qi
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
import numpy as np
import cv2
from mnc_config import cfg
fr... | 11,105 | 37.696864 | 138 | py |
MNC | MNC-master/lib/utils/__init__.py | 0 | 0 | 0 | py | |
MNC | MNC-master/lib/utils/bbox.c | /* Generated by Cython 0.23.4 */
#define PY_SSIZE_T_CLEAN
#include "Python.h"
#ifndef Py_PYTHON_H
#error Python headers needed to compile C extensions, please install development version of Python.
#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03020000)
#error Cython ... | 298,577 | 42.37905 | 1,009 | c |
MNC | MNC-master/lib/utils/blob.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
"""B... | 3,732 | 33.564815 | 77 | py |
MNC | MNC-master/lib/utils/timer.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 1,016 | 28.911765 | 77 | py |
MNC | MNC-master/lib/utils/unmap.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 745 | 31.434783 | 77 | py |
MNC | MNC-master/lib/utils/vis_seg.py | # --------------------------------------------------------
# Multitask Network Cascade
# Written by Haozhi Qi
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
import numpy as np
import cPickle
import os
import cv2
from... | 5,842 | 38.47973 | 104 | py |
MNC | MNC-master/lib/utils/voc_eval.py | # --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
impo... | 13,824 | 34.088832 | 124 | py |
MNC | MNC-master/tools/_init_paths.py |
import os.path
import sys
"""
Add lib paths and caffe path to system search path
"""
def add_path(path):
if path not in sys.path:
sys.path.insert(0, path)
cur_dir = os.path.dirname(__file__)
# Add caffe python to PYTHONPATH
caffe_path = os.path.join(cur_dir, '..', 'caffe-mnc', 'python')
add_path(caffe... | 417 | 17.173913 | 63 | py |
MNC | MNC-master/tools/demo.py | #!/usr/bin/python
# --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# -------------------------------------------... | 7,538 | 38.265625 | 93 | py |
MNC | MNC-master/tools/prepare_mcg_maskdb.py | # --------------------------------------------------------
# Multitask Network Cascade
# Written by Haozhi Qi
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# --------------------------------------------------------
# System modules
import argparse
import os
import cPickle
i... | 11,222 | 42 | 118 | py |
MNC | MNC-master/tools/test_net.py | #!/usr/bin/env python
# --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# ---------------------------------------... | 2,755 | 31.423529 | 81 | py |
MNC | MNC-master/tools/train_net.py | #!/usr/bin/env python
# --------------------------------------------------------
# Multitask Network Cascade
# Modified from py-faster-rcnn (https://github.com/rbgirshick/py-faster-rcnn)
# Copyright (c) 2016, Haozhi Qi
# Licensed under The MIT License [see LICENSE for details]
# ---------------------------------------... | 3,331 | 32.656566 | 78 | py |
null | AccPPR-main/README.md | # AccPPR
## Overview
Welcome to the repository of Accelerating Personalized PageRank Vector Computation! We build this repository to make our proposed algorithm publicly available and reproduce main experimental results shown in our KDD2023 paper.
## Preparation
### Datasets
We provide DBLP and Web-Stanford in ./... | 1,663 | 26.733333 | 317 | md |
null | AccPPR-main/alg.py | from numba import njit,float64,int32
import numpy as np
STEP=1e5
@njit(cache=True)
def _forward_push_mean(indptr,indices,degree,s,eps,alpha, debug=False):
n = len(degree)
queue = np.zeros(n + 1, dtype=np.int32)
front, rear = np.int32(0), np.int32(2)
gpr_vec, r = np.zeros(n), np.zeros(n + 1)
queue[1... | 20,200 | 27.694602 | 81 | py |
null | AccPPR-main/demo.py | from alg import (forward_push_mean,
forward_push,
power_iteration,
heavy_ball,
nag,
power_push,
forward_push_sor,
power_push_sor)
import scipy.sparse as sp
import numpy as np
method:dict={'forward_push':forward_push,
'forward_push_mean':forward_push_mean,
'power_iteration':power_iteration,
... | 825 | 25.645161 | 73 | py |
null | AccPPR-main/environment.yml | name: ppr
channels:
- defaults
dependencies:
- _libgcc_mutex=0.1=main
- _openmp_mutex=5.1=1_gnu
- appdirs=1.4.4=pyhd3eb1b0_0
- asttokens=2.0.5=pyhd3eb1b0_0
- backcall=0.2.0=pyhd3eb1b0_0
- blas=1.0=mkl
- brotli=1.0.9=h5eee18b_7
- brotli-bin=1.0.9=h5eee18b_7
- brotlipy=0.7.0=py39h27cfd23_1003
- ca-c... | 4,497 | 30.454545 | 42 | yml |
null | AccPPR-main/plots/algo.py | import networkx as nx
import numpy as np
import numba
import scipy.linalg
from numba import jit
import scipy.sparse as sp
from numba import njit, float64, int64, int32, prange
import time
@njit(cache=True)
def _forward_push(indptr, indices, degree, s, eps, alpha):
n = degree.shape[0]
queue = np.zeros(n, dtype... | 76,397 | 33.045455 | 118 | py |
null | AccPPR-main/plots/cal_ppr.py | import argparse
import multiprocessing
import scipy.sparse as sp
import numpy as np
from tqdm import tqdm
import random
import json
import time
import sys
sys.path.append('../')
from alg import (
forward_push,
power_iteration,
heavy_ball,
nag,
power_push,
forward_push_sor,
power_push_sor)
parser = argparse.ArgumentPa... | 2,789 | 27.469388 | 85 | py |
null | AccPPR-main/plots/fig2.py | import numpy as np
import matplotlib.pyplot as plt
import scipy.sparse as sp
from scipy.sparse import csr_matrix
from algo import _forward_push_dummy_bound
import pickle as pkl
import multiprocessing
def single_run_bound(para):
alpha, num_nodes, dataset, seed = para
dblp = np.load(f'../datasets/{dataset}')
... | 4,365 | 37.298246 | 126 | py |
null | AccPPR-main/plots/fig3.py | import numpy as np
import time
from scipy.sparse import csr_matrix
from algo import _forward_push_dummy
from algo import _forward_push_mean
import pickle as pkl
import multiprocessing
def single_run(para):
alpha, num_nodes, eps, dataset, seed = para
dblp = np.load(f'../datasets/{dataset}')
dblp_a = csr_mat... | 5,080 | 39.325397 | 99 | py |
null | AccPPR-main/plots/fig45.py | import json
import matplotlib.pyplot as plt
import numpy as np
markers={'forward_push':'^',
'power_iteration':'o',
'heavy_ball':'<',
'nag':'x',
'power_push':'s',
'forward_push_sor':'v',
'power_push_sor':'h'
}
indexes=['A','B','C'... | 5,808 | 37.986577 | 103 | py |
null | AccPPR-main/plots/fig6.py | import sys
sys.path.append('../')
from alg import forward_push
import scipy.sparse as sp
import numpy as np
import matplotlib.pyplot as plt
from tqdm import tqdm
csrs={
'webs':'../datasets/directed_web-stanford_csr_matrix.npz',
'lj':'../datasets/directed_lj_csr_matrix.npz',
'pokec':'../datasets/directed_pok... | 1,713 | 30.163636 | 98 | py |
realistic-ssl-evaluation | realistic-ssl-evaluation-master/CONTRIBUTING.md | # How to Contribute
We'd love to accept your patches and contributions to this project. There are
just a few small guidelines you need to follow.
## Contributor License Agreement
Contributions to this project must be accompanied by a Contributor License
Agreement. You (or your employer) retain the copyright to your ... | 1,100 | 38.321429 | 80 | md |
realistic-ssl-evaluation | realistic-ssl-evaluation-master/README.md | # realistic-ssl-evaluation
This repository contains the code for
[Realistic Evaluation of Deep Semi-Supervised Learning Algorithms](https://arxiv.org/abs/1804.09170), by Avital Oliver\*, Augustus Odena\*, Colin Raffel\*, Ekin D. Cubuk, and Ian J. Goodfellow, arXiv preprint arXiv:1804.09170.
If you use the code in thi... | 5,819 | 58.387755 | 359 | md |
realistic-ssl-evaluation | realistic-ssl-evaluation-master/build_label_map.py | #!/usr/bin/python3
#
# Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 5,882 | 34.871951 | 79 | py |
realistic-ssl-evaluation | realistic-ssl-evaluation-master/build_tfrecords.py | #!/usr/bin/python3
#
# Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 8,865 | 32.330827 | 79 | py |
realistic-ssl-evaluation | realistic-ssl-evaluation-master/convert_imagenet.py | #!/usr/bin/python3
#
# Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 1,608 | 29.358491 | 79 | py |
realistic-ssl-evaluation | realistic-ssl-evaluation-master/evaluate_checkpoints.py | #!/usr/bin/python3
#
# Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 5,395 | 31.506024 | 112 | py |
realistic-ssl-evaluation | realistic-ssl-evaluation-master/evaluate_model.py | #!/usr/bin/python3
#
# Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 12,231 | 32.883657 | 86 | py |