python_code stringlengths 0 187k | repo_name stringlengths 8 46 | file_path stringlengths 6 135 |
|---|---|---|
import random
import numpy as np
import pytorch_lightning as pl
import torch
import wandb
from pytorch_lightning.callbacks import LearningRateMonitor, ModelCheckpoint
from pytorch_lightning.loggers import WandbLogger
from pytorch_lightning.utilities.seed import seed_everything
from src.lightning.data_modules.receptacl... | CSR-main | src/lightning/trainers/linear_probe_trainer.py |
import pytorch_lightning as pl
import torch
import torch.nn.functional as F
import wandb
from src.models.backbones import FeatureLearner
from torch.optim import SGD, Adam
from torch.optim.lr_scheduler import CosineAnnealingLR
from torchmetrics import Accuracy, ConfusionMatrix
class ReceptacleModule(pl.LightningModule... | CSR-main | src/lightning/modules/receptacle_module.py |
CSR-main | src/lightning/modules/__init__.py | |
import os
from src.lightning.modules.sim_siam_module import SimSiamModule
from src.lightning.modules.moco2_module_old import MocoV2
from src.shared.utils import check_none_or_empty, load_lightning_inference, load_lightning_train
import pytorch_lightning as pl
import torch
import torch.nn.functional as F
import wandb
fr... | CSR-main | src/lightning/modules/linear_probe_module.py |
"""
Adapted from: https://github.com/facebookresearch/moco
Original work is: Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
This implementation is: Copyright (c) PyTorch Lightning, Inc. and its affiliates. All Rights Reserved
This implementation is licensed under Attribution-NonCommercial 4.0 In... | CSR-main | src/lightning/modules/moco2_module.py |
"""
Adapted from: https://github.com/facebookresearch/moco
Original work is: Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
This implementation is: Copyright (c) PyTorch Lightning, Inc. and its affiliates. All Rights Reserved
This implementation is licensed under Attribution-NonCommercial 4.0 In... | CSR-main | src/lightning/modules/moco2_module_old.py |
from src.shared.utils import worker_init_fn
import pytorch_lightning as pl
import src.dataloaders.augmentations as A
from src.dataloaders.contrastive_dataset import ContrastiveDataset
from src.dataloaders.contrastive_dataset_old import ContrastiveDatasetOld
from src.dataloaders.contrastive_dataset_object import Contras... | CSR-main | src/lightning/data_modules/contrastive_data_module.py |
CSR-main | src/lightning/data_modules/__init__.py | |
from src.dataloaders.pickupable_dataset import PickupableDataset
from src.shared.utils import worker_init_fn
import pytorch_lightning as pl
import src.dataloaders.augmentations as A
from src.dataloaders.contrastive_dataset import ContrastiveDataset
from src.shared.constants import (COLOR_JITTER_BRIGHTNESS,
... | CSR-main | src/lightning/data_modules/pickupable_data_module.py |
import pytorch_lightning as pl
import src.dataloaders.augmentations as A
from src.dataloaders.receptacle_dataset import ReceptacleDataset
from src.shared.constants import (COLOR_JITTER_BRIGHTNESS,
COLOR_JITTER_CONTRAST, COLOR_JITTER_HUE,
COLOR_JITTER_S... | CSR-main | src/lightning/data_modules/receptacle_data_module.py |
import itertools
import json
import os
import random
import numpy as np
import torch
from PIL import Image
from src.shared.constants import CLASSES_TO_IGNORE, DATALOADER_BOX_FRAC_THRESHOLD, IMAGE_SIZE
from src.shared.data_split import DataSplit
from src.shared.utils import get_box
from torch.utils.data import Dataset
... | CSR-main | src/dataloaders/contrastive_dataset_old.py |
from genericpath import exists
import json
import os
import torch
import torch
from src.shared.data_split import DataSplit
from torch.utils.data import Dataset
class AverageFeatureDataset(Dataset):
def __init__(self, root_dir, data_split: DataSplit):
# set the root directory
self.feat_dir = os.p... | CSR-main | src/dataloaders/average_feature_dataset.py |
import itertools
import json
import os
import random
import numpy as np
import torch
from PIL import Image
from src.shared.constants import CLASSES_TO_IGNORE, DATALOADER_BOX_FRAC_THRESHOLD, IMAGE_SIZE
from src.shared.data_split import DataSplit
from src.shared.utils import get_box
from torch.utils.data import Dataset
... | CSR-main | src/dataloaders/contrastive_dataset.py |
import json
import os
import random
import shutil
from typing import Any, Dict, List, cast
import numpy as np
import src.dataloaders.augmentations as A
from src.shared.constants import IMAGE_SIZE
from src.shared.utils import compute_3d_dist
from src.simulation.constants import ROOMR_CONTROLLER_COMMIT_ID
from src.simul... | CSR-main | src/dataloaders/roomr_dataset_utils.py |
import itertools
import json
import os
import random
import numpy as np
import torch
from PIL import Image
from src.shared.constants import CLASSES_TO_IGNORE, DATALOADER_BOX_FRAC_THRESHOLD, IMAGE_SIZE
from src.shared.data_split import DataSplit
from src.shared.utils import get_box
from torch.utils.data import Dataset
... | CSR-main | src/dataloaders/contrastive_dataset_object.py |
import json
import os
import random
from src.shared.utils import get_box
from src.shared.constants import CLASSES_TO_IGNORE
from PIL import Image
from src.shared.data_split import DataSplit
from torch.utils.data import Dataset
class ReceptacleDataset(Dataset):
def __init__(self, root_dir, transform, data_split:... | CSR-main | src/dataloaders/receptacle_dataset.py |
import random
import torchvision.transforms.functional as F
from src.shared.constants import (COLOR_JITTER_BRIGHTNESS,
COLOR_JITTER_CONTRAST, COLOR_JITTER_HUE,
COLOR_JITTER_SATURATION,
GRAYSCALE_PROBABILITY, IMAGE_SIZ... | CSR-main | src/dataloaders/augmentations.py |
import sys
import cv2
import numpy as np
import torch
import torchvision.transforms as T
from detectron2 import model_zoo
from detectron2.config import get_cfg
from detectron2.data import MetadataCatalog
from detectron2.engine import DefaultPredictor
from detectron2.utils.logger import setup_logger
from PIL import Ima... | CSR-main | src/simulation/module_box.py |
import itertools
import json
import os
import random
import numpy as np
import src.dataloaders.augmentations as A
import torch
import torch.nn.functional as F
from ai2thor.controller import Controller
from PIL import Image, ImageDraw
from scipy.optimize import linear_sum_assignment
from sklearn.metrics.cluster import ... | CSR-main | src/simulation/agent_obj_nav_expert.py |
from src.simulation.module_planner import PlannerModule
from src.simulation.environment import RearrangeTHOREnvironment
from typing import Any, Dict
import numpy as np
from sklearn.metrics.cluster import adjusted_rand_score, rand_score
def rand_metrics(assignments, gt_assignments):
gt_labels = []
for i, c in... | CSR-main | src/simulation/metrics.py |
# based on https://github.com/allenai/ai2thor-rearrangement/blob/main/rearrange/expert.py#L41
import copy
from typing import (
Dict,
Tuple,
Any,
Optional,
Union,
List,
Sequence,
)
import ai2thor.controller
import ai2thor.server
import networkx as nx
from torch.distributions.utils import la... | CSR-main | src/simulation/shortest_path_navigator.py |
import os
import numpy as np
import src.dataloaders.augmentations as A
import torch
import torch.nn.functional as F
import torchvision.transforms as T
from PIL import Image, ImageDraw
from pytorch_lightning import seed_everything
from src.dataloaders.roomr_dataset_utils import get_rearrange_task_spec
from src.shared.c... | CSR-main | src/simulation/agent_data_gen.py |
from dataclasses import dataclass
@dataclass
class RearrangementArgs(object):
instance_id: int = -1
room_id: int = -1
num_steps: int = 250,
render_instance_segmentation: bool = False
visibility_distance: float = 20.0
rotation_degrees: int = 30
box_frac_threshold: float = 0.008
box_conf... | CSR-main | src/simulation/rearrangement_args.py |
import json
import os
import random
from time import time
from typing import Dict
from PIL import Image
from ai2thor.controller import RECEPTACLE_OBJECTS
from src.dataloaders.roomr_dataset_utils import find_waypoint_plan
from src.models.exploration_model import StatefulExplorationModel
from src.shared.utils import che... | CSR-main | src/simulation/module_exploration.py |
import matplotlib.pyplot as plt
from networkx import draw_networkx
from networkx.algorithms.shortest_paths.generic import shortest_path
from networkx.classes.digraph import DiGraph
from PIL import ImageChops
from src.simulation.constants import ACTION_NEGATIONS
from src.simulation.state import State
class StateGraphM... | CSR-main | src/simulation/module_state_graph.py |
# modified from https://github.com/allenai/ai2thor-rearrangement/blob/main/rearrange/constants.py
import colorsys
import random
import numpy as np
random.seed(0)
MAX_HAND_METERS = 0.5
FOV = 90
STEP_SIZE = 0.25
# fmt: off
REARRANGE_SIM_OBJECTS = [
# A
"AlarmClock", "AluminumFoil", "Apple", "AppleSliced", "Arm... | CSR-main | src/simulation/constants.py |
CSR-main | src/simulation/__init__.py | |
import json
import os
import random
from itertools import combinations
from src.simulation.constants import CONTROLLER_COMMIT_ID
from string import ascii_letters
import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
import pandas as pd
import seaborn as sns
import torch
from ai2thor.controller impor... | CSR-main | src/simulation/agent_receptacle.py |
import itertools
import json
import os
from time import time
import numpy as np
import src.dataloaders.augmentations as A
import torch
import torch.nn.functional as F
import torchvision.transforms as T
from PIL import Image, ImageDraw
from pytorch_lightning import seed_everything
from src.dataloaders.roomr_dataset_uti... | CSR-main | src/simulation/agent_roomr.py |
import random
from collections import defaultdict
from typing import Any, Dict, List, Optional, Set
import numpy as np
from ai2thor.controller import Controller
import torch
from src.shared.constants import CLASSES_TO_IGNORE
from src.simulation.constants import \
OBJECT_TYPES_THAT_CAN_HAVE_IDENTICAL_MESHES
def v... | CSR-main | src/simulation/utils.py |
from dataclasses import dataclass
import hashlib
from typing import Dict, List
from src.simulation.shortest_path_navigator import AgentLocKeyType
@dataclass
class DataEntry(object):
first_name: str = ''
second_name: str = ''
receptacle: int = 0
receptacle_sibling: int = 0
room_id: int = 0
traj... | CSR-main | src/simulation/data_entry.py |
import json
import logging
import os
import random
from contextlib import contextmanager
from typing import Dict, Callable, Tuple, Union, List, Any, Optional, Sequence
import ai2thor.controller
import compress_pickle
import lru
import numpy as np
from scipy.spatial.qhull import ConvexHull, Delaunay
from allenact_plug... | CSR-main | src/simulation/rearrange_utils.py |
import enum
import math
import pprint
import random
import traceback
from collections import OrderedDict
from typing import Dict, Any, Tuple, Optional, Callable, List, Union, Sequence
import ai2thor
import ai2thor.controller
import ai2thor.fifo_server
import ai2thor.server
import ai2thor.wsgi_server
import numpy as np... | CSR-main | src/simulation/environment.py |
import itertools
import json
import time
import numpy as np
import src.dataloaders.augmentations as A
import torch
import torch.nn.functional as F
from PIL import Image
from scipy.optimize import linear_sum_assignment
from src.lightning.modules import moco2_module_old
from src.lightning.modules import moco2_module
fro... | CSR-main | src/simulation/module_relation_tracking.py |
import json
import os
from copy import deepcopy
from itertools import permutations
import torch
from networkx.algorithms.shortest_paths.weighted import dijkstra_path
from PIL import Image
from scipy.optimize import linear_sum_assignment
from src.shared.utils import render_adj_diff_matrix, render_sim_matrix
from src.si... | CSR-main | src/simulation/module_planner.py |
from dataclasses import dataclass
from typing import Dict, List
from PIL import Image
@dataclass
class State:
instance_cluster_ids: List = None
# boxes: None
# instance_names: None
pickupable_points: Dict = None
openable_points: Dict = None
pickupable: List = None
openable: List = None
... | CSR-main | src/simulation/state.py |
NORMALIZE_RGB_MEAN = (0.485, 0.456, 0.406)
NORMALIZE_RGB_STD = (0.229, 0.224, 0.225)
DEFAULT_NUM_WORKERS = 8
COLOR_JITTER_BRIGHTNESS = 0.4
COLOR_JITTER_CONTRAST = 0.4
COLOR_JITTER_SATURATION = 0.4
COLOR_JITTER_HUE = 0.2
GRAYSCALE_PROBABILITY = 0.2
ROTATIONS = (0., 90., 180., 270.)
# splits from ai2 rearrangement: http... | CSR-main | src/shared/constants.py |
CSR-main | src/shared/__init__.py | |
from enum import IntEnum
class DataSplit(IntEnum):
TRAIN = 1
VAL = 2
TEST = 3 | CSR-main | src/shared/data_split.py |
import io
import os
import random
from typing import List
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sn
import torch
from PIL import Image
from pytorch_lightning.utilities.seed import seed_everything
from src.shared.constants import (IMAGE_SIZE, NORMALIZE_RGB_MEAN,
... | CSR-main | src/shared/utils.py |
# from open lth
# https://github.com/facebookresearch/open_lth/blob/2ce732fe48abd5a80c10a153c45d397b048e980c/models/imagenet_resnet.py
# and torchvision
# https://pytorch.org/vision/0.8/_modules/torchvision/models/resnet.html
import torch
import torchvision
from torchvision.models.resnet import BasicBlock, Bottleneck
... | CSR-main | src/models/imagenet_resnet.py |
import torch.nn as nn
from src.models.backbones import FeatureLearner
from src.models.layers import *
class ResUNet(nn.Module):
def __init__(self, in_channels=3, out_channels=1):
super().__init__()
self.feature_extractor = FeatureLearner(in_channels)
self.up_head = ResUpHead(out_channels)... | CSR-main | src/models/unet.py |
CSR-main | src/models/__init__.py | |
from collections import OrderedDict
import torch
import torch.nn as nn
from src.models.imagenet_resnet import resnet18, resnet34, resnet50
def get_torchvision_model_class(class_str: str):
if class_str == 'resnet18':
return resnet18
elif class_str == 'resnet34':
return resnet34
elif clas... | CSR-main | src/models/backbones.py |
"""Baseline models for use in the object navigation task.
Object navigation is currently available as a Task in AI2-THOR and
Facebook's Habitat.
"""
import platform
from datetime import datetime
from typing import Optional, Tuple, cast
from allenact.algorithms.onpolicy_sync.storage import RolloutStorage
from allenact.... | CSR-main | src/models/exploration_model.py |
from src.simulation import flow
import torch
import torch.nn as nn
import torch.nn.functional as F
def upshuffle(in_planes, out_planes, upscale_factor, kernel_size=3, stride=1, padding=1):
return nn.Sequential(
nn.Conv2d(in_planes, out_planes * upscale_factor ** 2,
kernel_size=kernel_siz... | CSR-main | src/models/layers.py |
import torch
import torch.nn as nn
from functools import partial
import math
from timm.models.vision_transformer import VisionTransformer, _cfg
from timm.models.registry import register_model
from timm.models.layers import trunc_normal_, DropPath, to_2tuple
import pdb
__all__ = [
'deit_tiny_patch16_224', 'deit_sma... | container-main | models.py |
# Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
"""
A script to run multinode training with submitit.
"""
import argparse
import os
import uuid
from pathlib import Path
import main as classification
import submitit
def parse_args():
classification_parser = classification.get_args_parser()
... | container-main | run_with_submitit.py |
# Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
import os
import json
from torchvision import datasets, transforms
from torchvision.datasets.folder import ImageFolder, default_loader
from timm.data.constants import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from timm.data import create_transform
... | container-main | datasets.py |
# Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
"""
Train and eval functions used in main.py
"""
import math
import sys
from typing import Iterable, Optional
import torch
from timm.data import Mixup
from timm.utils import accuracy, ModelEma
from losses import DistillationLoss
import utils
def t... | container-main | engine.py |
# Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
"""
Misc functions, including distributed helpers.
Mostly copy-paste from torchvision references.
"""
import io
import os
import time
from collections import defaultdict, deque
import datetime
import torch
import torch.distributed as dist
class Smo... | container-main | utils.py |
# Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
"""
Implements the knowledge distillation loss
"""
import torch
from torch.nn import functional as F
class DistillationLoss(torch.nn.Module):
"""
This module wraps a standard criterion and adds an extra knowledge distillation loss by
taki... | container-main | losses.py |
# Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
from models import *
dependencies = ["torch", "torchvision", "timm"]
| container-main | hubconf.py |
# Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
import argparse
import datetime
import numpy as np
import time
import torch
import torch.backends.cudnn as cudnn
import json
from pathlib import Path
from timm.data import Mixup
from timm.models import create_model
from timm.loss import LabelSmoothin... | container-main | main.py |
# Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
import torch
import torch.distributed as dist
import math
class RASampler(torch.utils.data.Sampler):
"""Sampler that restricts data loading to a subset of the dataset for distributed,
with repeated augmentation.
It ensures that different ... | container-main | samplers.py |
"""
Unit tests for multilabel_average_precision_metric.py
"""
import unittest
import numpy as np
from torch import Tensor
from relex.multilabel_average_precision_metric import MultilabelAveragePrecision
class TestUtil(unittest.TestCase):
@classmethod
def test_get_metrics(cls):
np.seterr(divide='ign... | comb_dist_direct_relex-master | tests/test_multilabel_average_precision_metric.py |
import json
from sklearn.metrics import precision_recall_curve
from scipy.interpolate import spline
import matplotlib.pyplot as plt
with open('scripts/PR_curves.json') as f:
x = json.load(f)
plt.step(x['belagy_et_al_best'][0], x['belagy_et_al_best'][1], where='post')
plt.step(x['belagy_et_al_baseline'][0], x['bel... | comb_dist_direct_relex-master | scripts/plot_pr_curves.py |
"""
Relation Extraction.
"""
__version__ = 0.3
| comb_dist_direct_relex-master | relex/__init__.py |
from typing import Tuple
import logging
from overrides import overrides
from allennlp.common.util import JsonDict
from allennlp.data import Instance
from allennlp.predictors.predictor import Predictor
log = logging.getLogger(__name__) # pylint: disable=invalid-name
@Predictor.register('relex')
class RelationExtract... | comb_dist_direct_relex-master | relex/relation_extraction_predictor.py |
import logging
from overrides import overrides
import numpy as np
import torch
from torch import nn
from sklearn.metrics import precision_recall_curve
from allennlp.common.checks import ConfigurationError
from allennlp.training.metrics.metric import Metric
logger = logging.getLogger(__name__) # pylint: disable=invali... | comb_dist_direct_relex-master | relex/multilabel_average_precision_metric.py |
from typing import Set, Tuple, List, Dict
import logging
import random
from collections import defaultdict
from overrides import overrides
import tqdm
from allennlp.common.file_utils import cached_path
from allennlp.data.dataset_readers.dataset_reader import DatasetReader
from allennlp.data.fields import TextField, ... | comb_dist_direct_relex-master | relex/relation_instances_reader.py |
from typing import Dict
import logging
from overrides import overrides
import torch
from torch import nn
import numpy as np
from allennlp.data import Vocabulary
from allennlp.modules.seq2vec_encoders import CnnEncoder
from allennlp.models.model import Model
from allennlp.nn import util
from allennlp.training.metrics.a... | comb_dist_direct_relex-master | relex/comb_dist_direct_relex.py |
import os
from pathlib import Path
ABS_PATH_OF_TOP_LEVEL_DIR = os.path.abspath(os.path.dirname(Path(__file__)))
ABS_PATH_OF_DOCS_DIR = os.path.join(ABS_PATH_OF_TOP_LEVEL_DIR, "docs")
| allenact-main | constants.py |
#!/usr/bin/env python3
"""Entry point to training/validating/testing for a user given experiment
name."""
import allenact.main
if __name__ == "__main__":
allenact.main.main()
| allenact-main | main.py |
allenact-main | projects/__init__.py | |
allenact-main | projects/gym_baselines/__init__.py | |
from abc import ABC
from typing import Dict, Sequence, Optional, List, Any
from allenact.base_abstractions.experiment_config import ExperimentConfig
from allenact.base_abstractions.sensor import Sensor
class GymBaseConfig(ExperimentConfig, ABC):
SENSORS: Optional[Sequence[Sensor]] = None
def _get_sampler_a... | allenact-main | projects/gym_baselines/experiments/gym_base.py |
from abc import ABC
from typing import Dict, Any
from allenact.utils.viz_utils import VizSuite, AgentViewViz
from projects.gym_baselines.experiments.gym_base import GymBaseConfig
class GymHumanoidBaseConfig(GymBaseConfig, ABC):
@classmethod
def machine_params(cls, mode="train", **kwargs) -> Dict[str, Any]:
... | allenact-main | projects/gym_baselines/experiments/gym_humanoid_base.py |
from abc import ABC
from typing import Dict, Any
from allenact.utils.viz_utils import VizSuite, AgentViewViz
from projects.gym_baselines.experiments.gym_base import GymBaseConfig
class GymMoJoCoBaseConfig(GymBaseConfig, ABC):
@classmethod
def machine_params(cls, mode="train", **kwargs) -> Dict[str, Any]:
... | allenact-main | projects/gym_baselines/experiments/gym_mujoco_base.py |
from abc import ABC
from typing import cast
import torch.optim as optim
from torch.optim.lr_scheduler import LambdaLR
from allenact.algorithms.onpolicy_sync.losses.ppo import PPO
from allenact.utils.experiment_utils import (
TrainingPipeline,
Builder,
PipelineStage,
LinearDecay,
)
from projects.gym_... | allenact-main | projects/gym_baselines/experiments/gym_humanoid_ddppo.py |
allenact-main | projects/gym_baselines/experiments/__init__.py | |
from abc import ABC
from typing import cast
import torch.optim as optim
from torch.optim.lr_scheduler import LambdaLR
from allenact.algorithms.onpolicy_sync.losses.ppo import PPO
from allenact.utils.experiment_utils import (
TrainingPipeline,
Builder,
PipelineStage,
LinearDecay,
)
from projects.gym_... | allenact-main | projects/gym_baselines/experiments/gym_mujoco_ddppo.py |
from typing import Dict, List, Any
import gym
import torch.nn as nn
from allenact.base_abstractions.experiment_config import TaskSampler
from allenact.base_abstractions.sensor import SensorSuite
from allenact_plugins.gym_plugin.gym_models import MemorylessActorCritic
from allenact_plugins.gym_plugin.gym_sensors impor... | allenact-main | projects/gym_baselines/experiments/mujoco/gym_mujoco_swimmer_ddppo.py |
from typing import Dict, List, Any
import gym
import torch.nn as nn
from allenact.base_abstractions.experiment_config import TaskSampler
from allenact.base_abstractions.sensor import SensorSuite
from allenact_plugins.gym_plugin.gym_models import MemorylessActorCritic
from allenact_plugins.gym_plugin.gym_sensors impor... | allenact-main | projects/gym_baselines/experiments/mujoco/gym_mujoco_reacher_ddppo.py |
from typing import Dict, List, Any
import gym
import torch.nn as nn
from allenact.base_abstractions.experiment_config import TaskSampler
from allenact.base_abstractions.sensor import SensorSuite
from allenact_plugins.gym_plugin.gym_models import MemorylessActorCritic
from allenact_plugins.gym_plugin.gym_sensors impor... | allenact-main | projects/gym_baselines/experiments/mujoco/gym_mujoco_walker2d_ddppo.py |
allenact-main | projects/gym_baselines/experiments/mujoco/__init__.py | |
from typing import Dict, List, Any
import gym
import torch.nn as nn
from allenact.base_abstractions.experiment_config import TaskSampler
from allenact.base_abstractions.sensor import SensorSuite
from allenact_plugins.gym_plugin.gym_models import MemorylessActorCritic
from allenact_plugins.gym_plugin.gym_sensors impor... | allenact-main | projects/gym_baselines/experiments/mujoco/gym_mujoco_halfcheetah_ddppo.py |
from typing import Dict, List, Any
import gym
import torch.nn as nn
from allenact.base_abstractions.experiment_config import TaskSampler
from allenact.base_abstractions.sensor import SensorSuite
from allenact_plugins.gym_plugin.gym_models import MemorylessActorCritic
from allenact_plugins.gym_plugin.gym_sensors impor... | allenact-main | projects/gym_baselines/experiments/mujoco/gym_mujoco_humanoid_ddppo.py |
from typing import Dict, List, Any
import gym
import torch.nn as nn
from allenact.base_abstractions.experiment_config import TaskSampler
from allenact.base_abstractions.sensor import SensorSuite
from allenact_plugins.gym_plugin.gym_models import MemorylessActorCritic
from allenact_plugins.gym_plugin.gym_sensors impor... | allenact-main | projects/gym_baselines/experiments/mujoco/gym_mujoco_inverteddoublependulum_ddppo.py |
from typing import Dict, List, Any
import gym
import torch.nn as nn
from allenact.base_abstractions.experiment_config import TaskSampler
from allenact.base_abstractions.sensor import SensorSuite
from allenact_plugins.gym_plugin.gym_models import MemorylessActorCritic
from allenact_plugins.gym_plugin.gym_sensors impor... | allenact-main | projects/gym_baselines/experiments/mujoco/gym_mujoco_ant_ddppo.py |
from typing import Dict, List, Any
import gym
import torch.nn as nn
from allenact.base_abstractions.experiment_config import TaskSampler
from allenact.base_abstractions.sensor import SensorSuite
from allenact_plugins.gym_plugin.gym_models import MemorylessActorCritic
from allenact_plugins.gym_plugin.gym_sensors impor... | allenact-main | projects/gym_baselines/experiments/mujoco/gym_mujoco_hopper_ddppo.py |
from typing import Dict, List, Any
import gym
import torch.nn as nn
from allenact.base_abstractions.experiment_config import TaskSampler
from allenact.base_abstractions.sensor import SensorSuite
from allenact_plugins.gym_plugin.gym_models import MemorylessActorCritic
from allenact_plugins.gym_plugin.gym_sensors impor... | allenact-main | projects/gym_baselines/experiments/mujoco/gym_mujoco_invertedpendulum_ddppo.py |
allenact-main | projects/gym_baselines/models/__init__.py | |
"""
Note: I add this file just for the format consistence with other baselines in the project, so it is just the same as
`allenact_plugins.gym_models.py` so far. However, if it is in the Gym Robotics, some modification is need.
For example, for `state_dim`:
if input_uuid == 'gym_robotics_data':
# co... | allenact-main | projects/gym_baselines/models/gym_models.py |
from typing import Sequence, Union, Optional, Dict, Tuple, Type
import attr
import gym
import torch
import torch.nn as nn
import torch.optim as optim
from torch.optim.lr_scheduler import LambdaLR
from torchvision import models
from allenact.algorithms.onpolicy_sync.losses import PPO
from allenact.algorithms.onpolicy_... | allenact-main | projects/objectnav_baselines/mixins.py |
allenact-main | projects/objectnav_baselines/__init__.py | |
allenact-main | projects/objectnav_baselines/experiments/__init__.py | |
import glob
import os
import platform
from abc import ABC
from math import ceil
from typing import Dict, Any, List, Optional, Sequence, Tuple, cast
import ai2thor
import ai2thor.build
import gym
import numpy as np
import torch
from packaging import version
from allenact.base_abstractions.experiment_config import Mach... | allenact-main | projects/objectnav_baselines/experiments/objectnav_thor_base.py |
from abc import ABC
from typing import Optional, Sequence, Union
from allenact.base_abstractions.experiment_config import ExperimentConfig
from allenact.base_abstractions.preprocessor import Preprocessor
from allenact.base_abstractions.sensor import Sensor
from allenact.utils.experiment_utils import Builder
class Ob... | allenact-main | projects/objectnav_baselines/experiments/objectnav_base.py |
from typing import Sequence, Union
import torch.nn as nn
from allenact.base_abstractions.preprocessor import Preprocessor
from allenact.utils.experiment_utils import Builder, TrainingPipeline
from allenact_plugins.ithor_plugin.ithor_sensors import (
RGBSensorThor,
GoalObjectTypeThorSensor,
)
from allenact_plu... | allenact-main | projects/objectnav_baselines/experiments/robothor/objectnav_robothor_rgbd_resnet18gru_ddppo.py |
from typing import Sequence, Union
import torch.nn as nn
from allenact.base_abstractions.preprocessor import Preprocessor
from allenact.utils.experiment_utils import Builder, TrainingPipeline
from allenact_plugins.ithor_plugin.ithor_sensors import (
GoalObjectTypeThorSensor,
RGBSensorThor,
)
from projects.obj... | allenact-main | projects/objectnav_baselines/experiments/robothor/objectnav_robothor_rgb_resnet50gru_ddppo.py |
import os
from abc import ABC
from typing import Optional, List, Any, Dict
import torch
from allenact.utils.misc_utils import prepare_locals_for_super
from projects.objectnav_baselines.experiments.objectnav_thor_base import (
ObjectNavThorBaseConfig,
)
class ObjectNavRoboThorBaseConfig(ObjectNavThorBaseConfig, ... | allenact-main | projects/objectnav_baselines/experiments/robothor/objectnav_robothor_base.py |
from typing import Sequence, Union
import torch.nn as nn
from allenact.base_abstractions.preprocessor import Preprocessor
from allenact.utils.experiment_utils import Builder, TrainingPipeline
from allenact_plugins.ithor_plugin.ithor_sensors import (
GoalObjectTypeThorSensor,
RGBSensorThor,
)
from projects.obj... | allenact-main | projects/objectnav_baselines/experiments/robothor/objectnav_robothor_rgb_resnet18gru_ddppo.py |
allenact-main | projects/objectnav_baselines/experiments/robothor/__init__.py | |
from typing import Sequence, Union
import torch.nn as nn
from allenact.base_abstractions.preprocessor import Preprocessor
from allenact.base_abstractions.sensor import ExpertActionSensor
from allenact.utils.experiment_utils import Builder, TrainingPipeline
from allenact_plugins.ithor_plugin.ithor_sensors import (
... | allenact-main | projects/objectnav_baselines/experiments/robothor/objectnav_robothor_rgb_resnet18gru_dagger.py |
import torch.nn as nn
from allenact.utils.experiment_utils import TrainingPipeline
from allenact_plugins.ithor_plugin.ithor_sensors import (
RGBSensorThor,
GoalObjectTypeThorSensor,
)
from projects.objectnav_baselines.experiments.robothor.objectnav_robothor_base import (
ObjectNavRoboThorBaseConfig,
)
from... | allenact-main | projects/objectnav_baselines/experiments/robothor/objectnav_robothor_rgb_unfrozenresnet18gru_ddppo.py |
from typing import Sequence, Union
import torch.nn as nn
from allenact.base_abstractions.preprocessor import Preprocessor
from allenact.utils.experiment_utils import Builder, TrainingPipeline
from allenact_plugins.ithor_plugin.ithor_sensors import GoalObjectTypeThorSensor
from allenact_plugins.robothor_plugin.robotho... | allenact-main | projects/objectnav_baselines/experiments/robothor/objectnav_robothor_depth_resnet18gru_ddppo.py |
allenact-main | projects/objectnav_baselines/experiments/robothor/beta/__init__.py | |
import torch.optim as optim
from torch.optim.lr_scheduler import LambdaLR
from allenact.algorithms.onpolicy_sync.losses import PPO
from allenact.algorithms.onpolicy_sync.losses.grouped_action_imitation import (
GroupedActionImitation,
)
from allenact.algorithms.onpolicy_sync.losses.ppo import PPOConfig
from allena... | allenact-main | projects/objectnav_baselines/experiments/robothor/beta/objectnav_robothor_rgb_resnetgru_ddppo_and_gbc.py |
from typing import Union, Optional, Any
import gym
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from torch.optim.lr_scheduler import LambdaLR
from allenact.algorithms.onpolicy_sync.losses import PPO
from allenact.algorithms.onpolicy_sync.losses.ppo import PPOConfig
from allenact.a... | allenact-main | projects/objectnav_baselines/experiments/robothor/beta/objectnav_robothor_rgb_unfrozenresnet18gru_vdr_ddppo.py |
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