code stringlengths 114 1.05M | path stringlengths 3 312 | quality_prob float64 0.5 0.99 | learning_prob float64 0.2 1 | filename stringlengths 3 168 | kind stringclasses 1
value |
|---|---|---|---|---|---|
from typing import Any, Callable, Dict, List
import time
from threading import RLock
class EventSummarizer:
"""Utility that aggregates related log messages to reduce log spam."""
def __init__(self):
self.events_by_key: Dict[str, int] = {}
# Messages to send in next summary batch.
self... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/autoscaler/_private/event_summarizer.py | 0.881487 | 0.198938 | event_summarizer.py | pypi |
try:
from prometheus_client import (
CollectorRegistry,
Counter,
Gauge,
Histogram,
)
# The metrics in this class should be kept in sync with
# python/ray/tests/test_metrics_agent.py
class AutoscalerPrometheusMetrics:
def __init__(self, registry: CollectorReg... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/autoscaler/_private/prom_metrics.py | 0.643441 | 0.446314 | prom_metrics.py | pypi |
from contextlib import suppress
import logging
import math
import requests
from typing import Any, Dict, Optional
import json
from ray.autoscaler._private.kuberay import node_provider
from ray.autoscaler._private.util import validate_config
logger = logging.getLogger(__name__)
# Logical group name for the KubeRay ... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/autoscaler/_private/kuberay/autoscaling_config.py | 0.87937 | 0.301992 | autoscaling_config.py | pypi |
from typing import Tuple, List
from ray.autoscaler.node_provider import NodeProvider
from ray.autoscaler.tags import (
TAG_RAY_NODE_KIND,
NODE_KIND_HEAD,
TAG_RAY_USER_NODE_TYPE,
TAG_RAY_NODE_NAME,
TAG_RAY_NODE_STATUS,
STATUS_UP_TO_DATE,
)
from ray.autoscaler._private.util import format_readonly... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/autoscaler/_private/readonly/node_provider.py | 0.872843 | 0.223012 | node_provider.py | pypi |
import json
import logging
from http.client import RemoteDisconnected
from ray.autoscaler.node_provider import NodeProvider
from ray.autoscaler.tags import TAG_RAY_CLUSTER_NAME
logger = logging.getLogger(__name__)
class CoordinatorSenderNodeProvider(NodeProvider):
"""NodeProvider for automatically managed priva... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/autoscaler/_private/local/coordinator_node_provider.py | 0.681621 | 0.173113 | coordinator_node_provider.py | pypi |
from contextlib import contextmanager
from typing import Any, Callable, Dict, Iterator, List, Optional, Union
import json
import os
import tempfile
from ray.autoscaler._private import commands
from ray.autoscaler._private.event_system import ( # noqa: F401
CreateClusterEvent, # noqa: F401
global_event_syste... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/autoscaler/sdk/sdk.py | 0.920294 | 0.221435 | sdk.py | pypi |
import math
from typing import Callable, Optional, List, TYPE_CHECKING
from ray.util.annotations import PublicAPI
from ray.data.block import T, U, KeyType, AggType, KeyFn, _validate_key_fn
from ray.data.impl.null_aggregate import (
_null_wrap_init,
_null_wrap_accumulate,
_null_wrap_merge,
_null_wrap_fi... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/aggregate.py | 0.940072 | 0.360517 | aggregate.py | pypi |
import bisect
import logging
import random
import time
from collections import defaultdict
from typing import List, Any, Generic, Optional, TYPE_CHECKING
import ray
from ray.types import ObjectRef
from ray.data.block import T, BlockAccessor
from ray.data.impl.remote_fn import cached_remote_fn
if TYPE_CHECKING:
fr... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/random_access_dataset.py | 0.790652 | 0.232484 | random_access_dataset.py | pypi |
import inspect
import itertools
import logging
import time
from typing import (
Any,
Callable,
List,
Iterator,
Iterable,
Generic,
Union,
Optional,
TYPE_CHECKING,
)
import ray
from ray.data.context import DatasetContext
from ray.data.dataset import Dataset, T, U
from ray.data.impl.pi... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/dataset_pipeline.py | 0.899845 | 0.427098 | dataset_pipeline.py | pypi |
import os
import logging
from typing import (
List,
Any,
Dict,
Union,
Optional,
Tuple,
Callable,
TypeVar,
TYPE_CHECKING,
)
import uuid
import numpy as np
if TYPE_CHECKING:
import pyarrow
import pandas
import dask
import mars
import modin
import pyspark
impo... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/read_api.py | 0.806434 | 0.275784 | read_api.py | pypi |
import math
from typing import List, Iterator, Tuple, Any, Union, Optional, TYPE_CHECKING
if TYPE_CHECKING:
import pyarrow
import numpy as np
import ray
from ray.types import ObjectRef
from ray.data.block import Block, BlockMetadata, BlockAccessor
from ray.data.impl.remote_fn import cached_remote_fn
class Bloc... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/block_list.py | 0.907976 | 0.533458 | block_list.py | pypi |
import ray
from ray.data.block import BlockAccessor
from ray.data.impl.block_list import BlockList
from ray.data.impl.plan import ExecutionPlan
from ray.data.impl.progress_bar import ProgressBar
from ray.data.impl.remote_fn import cached_remote_fn
from ray.data.impl.shuffle import _shuffle_reduce
from ray.data.impl.st... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/fast_repartition.py | 0.477554 | 0.350505 | fast_repartition.py | pypi |
from typing import Any
import ray
from ray import cloudpickle
_ray_initialized = False
class SizeEstimator:
"""Efficiently estimates the Ray serialized size of a stream of items.
For efficiency, this only samples a fraction of the added items for real
Ray-serialization.
"""
def __init__(self):... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/size_estimator.py | 0.949693 | 0.309089 | size_estimator.py | pypi |
from typing import Optional
from ray.data.block import Block, BlockAccessor
from ray.data.impl.delegating_block_builder import DelegatingBlockBuilder
class Batcher:
"""Chunks blocks into batches.
Implementation Note: When there are multiple batches per block,
this batcher will slice off and return each ... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/batcher.py | 0.956462 | 0.566978 | batcher.py | pypi |
import math
from typing import Callable, List, Iterator, Tuple
import numpy as np
import ray
from ray.types import ObjectRef
from ray.data.block import (
Block,
BlockMetadata,
BlockPartitionMetadata,
MaybeBlockPartition,
)
from ray.data.context import DatasetContext
from ray.data.impl.block_list impor... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/lazy_block_list.py | 0.794783 | 0.475423 | lazy_block_list.py | pypi |
import collections
import itertools
from typing import Iterator, Iterable, Union, Optional, TYPE_CHECKING
if TYPE_CHECKING:
import pyarrow
import pandas
import numpy as np
import ray
from ray.types import ObjectRef
from ray.data.block import Block, BlockAccessor
from ray.data.impl.batcher import Batcher
from... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/block_batching.py | 0.918713 | 0.389111 | block_batching.py | pypi |
from typing import Any, Callable, List, Optional, TYPE_CHECKING
import time
import concurrent.futures
import logging
import ray
from ray.data.context import DatasetContext
from ray.data.dataset import Dataset, T
from ray.data.impl.progress_bar import ProgressBar
from ray.data.impl import progress_bar
logger = logging... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/pipeline_executor.py | 0.732113 | 0.246545 | pipeline_executor.py | pypi |
from contextlib import contextmanager
from typing import List, Optional, Set, Dict, Tuple, Union
import time
import collections
import numpy as np
import ray
from ray.data.block import BlockMetadata
from ray.data.impl.block_list import BlockList
def fmt(seconds: float) -> str:
if seconds > 1:
return str(... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/stats.py | 0.850469 | 0.346472 | stats.py | pypi |
from typing import Callable, Tuple, Optional, Union, Iterable, TYPE_CHECKING
import uuid
if TYPE_CHECKING:
import pyarrow
import ray
from ray.data.context import DatasetContext
from ray.data.block import Block
from ray.data.impl.block_list import BlockList
from ray.data.impl.compute import get_compute
from ray.da... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/plan.py | 0.884427 | 0.298159 | plan.py | pypi |
from typing import Any
from ray.data.block import Block, T, BlockAccessor
from ray.data.impl.block_builder import BlockBuilder
from ray.data.impl.simple_block import SimpleBlockBuilder
from ray.data.impl.arrow_block import ArrowRow, ArrowBlockBuilder
from ray.data.impl.pandas_block import PandasRow, PandasBlockBuilder... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/delegating_block_builder.py | 0.655336 | 0.151278 | delegating_block_builder.py | pypi |
from typing import Callable, Any, Optional
from ray.data.block import Block, BlockAccessor
from ray.data.impl.delegating_block_builder import DelegatingBlockBuilder
class BlockOutputBuffer(object):
"""Generates output blocks of a given size given a stream of inputs.
This class is used to turn a stream of it... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/output_buffer.py | 0.947902 | 0.424054 | output_buffer.py | pypi |
from typing import Dict, List, Tuple, Iterator, Any, TypeVar, Optional, TYPE_CHECKING
import collections
import numpy as np
from ray.data.block import BlockAccessor, BlockMetadata, KeyFn
from ray.data.row import TableRow
from ray.data.impl.table_block import TableBlockAccessor, TableBlockBuilder
from ray.data.impl.ar... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/pandas_block.py | 0.6508 | 0.443058 | pandas_block.py | pypi |
from typing import List, Any, Callable, TypeVar, Tuple, Union
import numpy as np
import ray
from ray.types import ObjectRef
from ray.data.block import Block, BlockMetadata, BlockAccessor, BlockExecStats
from ray.data.impl.delegating_block_builder import DelegatingBlockBuilder
from ray.data.impl.block_list import Block... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/sort.py | 0.76207 | 0.451387 | sort.py | pypi |
import math
from typing import TypeVar, List, Optional, Dict, Any, Tuple, Union, Callable, Iterable
import numpy as np
import ray
from ray.data.block import Block, BlockAccessor, BlockMetadata, BlockExecStats
from ray.data.impl.progress_bar import ProgressBar
from ray.data.impl.block_list import BlockList
from ray.da... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/shuffle.py | 0.725551 | 0.262913 | shuffle.py | pypi |
import collections
from typing import Dict, Iterator, List, Union, Any, TypeVar, TYPE_CHECKING
from ray.data.block import Block, BlockAccessor
from ray.data.row import TableRow
from ray.data.impl.block_builder import BlockBuilder
from ray.data.impl.size_estimator import SizeEstimator
if TYPE_CHECKING:
from ray.d... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/impl/table_block.py | 0.871105 | 0.310799 | table_block.py | pypi |
import logging
from typing import (
Callable,
Optional,
List,
Tuple,
Union,
Any,
Dict,
Iterator,
Iterable,
TYPE_CHECKING,
)
import urllib.parse
if TYPE_CHECKING:
import pyarrow
from ray.types import ObjectRef
from ray.data.block import Block, BlockAccessor
from ray.data.con... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/data/datasource/file_based_datasource.py | 0.92345 | 0.249802 | file_based_datasource.py | pypi |
import abc
from typing import TYPE_CHECKING
if TYPE_CHECKING:
import pandas as pd
from ray.data import Dataset
from ray.ml.predictor import DataBatchType
class PreprocessorAlreadyFittedException(RuntimeError):
"""Error raised when the preprocessor cannot be fitted again."""
pass
class PreprocessorNot... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/preprocessor.py | 0.912835 | 0.713874 | preprocessor.py | pypi |
from dataclasses import dataclass
from typing import Dict, Any, Optional, List
from ray.util import PublicAPI
from ray.tune.trainable import PlacementGroupFactory
from ray.tune.callback import Callback
ScalingConfig = Dict[str, Any]
@dataclass
class ScalingConfigDataClass:
"""Configuration for scaling trainin... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/config.py | 0.912397 | 0.39257 | config.py | pypi |
import argparse
from typing import Tuple
import pandas as pd
import ray
from ray.ml.checkpoint import Checkpoint
from ray.ml.predictors.integrations.lightgbm import LightGBMPredictor
from ray.ml.train.integrations.lightgbm import LightGBMTrainer
from ray.data.dataset import Dataset
from ray.ml.result import Result
fr... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/examples/lightgbm_example.py | 0.879302 | 0.413477 | lightgbm_example.py | pypi |
import argparse
from typing import Tuple
import pandas as pd
import ray
from ray.ml.checkpoint import Checkpoint
from ray.ml.predictors.integrations.xgboost import XGBoostPredictor
from ray.ml.train.integrations.xgboost import XGBoostTrainer
from ray.data.dataset import Dataset
from ray.ml.result import Result
from r... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/examples/xgboost_example.py | 0.864196 | 0.406509 | xgboost_example.py | pypi |
import argparse
import ray
from ray import tune
from ray.ml.train.integrations.torch import TorchTrainer
from ray.tune.tune_config import TuneConfig
from ray.tune.tuner import Tuner
from torch_linear_dataset_example import train_func, get_datasets
def tune_linear(num_workers, num_samples, use_gpu):
train_datase... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/examples/pytorch/tune_torch_linear_dataset_example.py | 0.794544 | 0.328476 | tune_torch_linear_dataset_example.py | pypi |
import argparse
from typing import Dict
import torch
from torch import nn
from torch.utils.data import DataLoader
from torchvision import datasets
from torchvision.transforms import ToTensor
import ray.train as train
from ray.ml.train.integrations.torch import TorchTrainer
# Download training data from open datasets... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/examples/pytorch/torch_fashion_mnist_example.py | 0.933423 | 0.600481 | torch_fashion_mnist_example.py | pypi |
import argparse
import numpy as np
import torch
import torch.nn as nn
import ray.train as train
from ray.ml.train.integrations.torch import TorchTrainer
class LinearDataset(torch.utils.data.Dataset):
"""y = a * x + b"""
def __init__(self, a, b, size=1000):
x = np.arange(0, 10, 10 / size, dtype=np.fl... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/examples/pytorch/torch_linear_example.py | 0.916612 | 0.44083 | torch_linear_example.py | pypi |
import argparse
import random
from typing import Tuple
import torch
import torch.nn as nn
import ray
import ray.train as train
from ray.data import Dataset
from ray.ml.checkpoint import Checkpoint
from ray.ml.predictors.integrations.torch import TorchPredictor
from ray.ml.result import Result
from ray.ml.train.integr... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/examples/pytorch/torch_linear_dataset_example.py | 0.913681 | 0.458167 | torch_linear_dataset_example.py | pypi |
import argparse
import ray
from ray import tune
from ray.ml.train.integrations.tensorflow import TensorflowTrainer
from ray.ml.examples.tensorflow.tensorflow_mnist_example import train_func
from ray.tune.tune_config import TuneConfig
from ray.tune.tuner import Tuner
def tune_tensorflow_mnist(
num_workers: int =... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/examples/tensorflow/tune_tensorflow_mnist_example.py | 0.724286 | 0.400456 | tune_tensorflow_mnist_example.py | pypi |
import argparse
import json
import os
import numpy as np
from ray.ml.result import Result
import tensorflow as tf
from tensorflow.keras.callbacks import Callback
import ray.train as train
from ray.ml.train.integrations.tensorflow import TensorflowTrainer
class TrainCheckpointReportCallback(Callback):
def on_epo... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/examples/tensorflow/tensorflow_mnist_example.py | 0.881895 | 0.408513 | tensorflow_mnist_example.py | pypi |
import argparse
import numpy as np
import pandas as pd
import tensorflow as tf
from tensorflow.keras.callbacks import Callback
import ray
import ray.train as train
from ray.data import Dataset
from ray.train.tensorflow import prepare_dataset_shard
from ray.ml.checkpoint import Checkpoint
from ray.ml.train.integratio... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/examples/tensorflow/tensorflow_linear_dataset_example.py | 0.911495 | 0.400632 | tensorflow_linear_dataset_example.py | pypi |
from typing import Dict, Type, Any, Optional
import warnings
import os
import ray.cloudpickle as cpickle
from ray.ml.trainer import GenDataset
from ray.ml.config import ScalingConfig, RunConfig, ScalingConfigDataClass
from ray.ml.preprocessor import Preprocessor
from ray.util.annotations import DeveloperAPI
from ray.m... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/train/gbdt_trainer.py | 0.907435 | 0.346652 | gbdt_trainer.py | pypi |
import inspect
import logging
from pathlib import Path
from typing import Dict, Callable, Optional, Union
import ray
from ray import tune
from ray.ml.constants import TRAIN_DATASET_KEY, PREPROCESSOR_KEY
from ray.ml.trainer import Trainer
from ray.ml.config import ScalingConfig, RunConfig, ScalingConfigDataClass
from r... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/train/data_parallel_trainer.py | 0.90982 | 0.451447 | data_parallel_trainer.py | pypi |
from typing import Callable, Optional, Dict, Union
from ray.train.torch import TorchConfig
from ray.ml.trainer import GenDataset
from ray.ml.train.data_parallel_trainer import DataParallelTrainer
from ray.ml.config import ScalingConfig, RunConfig
from ray.ml.preprocessor import Preprocessor
from ray.ml.checkpoint impo... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/train/integrations/torch/torch_trainer.py | 0.966442 | 0.45181 | torch_trainer.py | pypi |
import os
from ray.ml.train.gbdt_trainer import GBDTTrainer
from ray.util.annotations import PublicAPI
from ray.ml.constants import MODEL_KEY
import xgboost
import xgboost_ray
from xgboost_ray.tune import TuneReportCheckpointCallback
@PublicAPI(stability="alpha")
class XGBoostTrainer(GBDTTrainer):
"""A Trainer ... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/train/integrations/xgboost/xgboost_trainer.py | 0.91621 | 0.391668 | xgboost_trainer.py | pypi |
from typing import Dict, Any
import os
from ray.ml.train.gbdt_trainer import GBDTTrainer
from ray.util.annotations import PublicAPI
from ray.ml.constants import MODEL_KEY
import lightgbm
import lightgbm_ray
from lightgbm_ray.tune import TuneReportCheckpointCallback
@PublicAPI(stability="alpha")
class LightGBMTraine... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/train/integrations/lightgbm/lightgbm_trainer.py | 0.954127 | 0.394522 | lightgbm_trainer.py | pypi |
from typing import Callable, Optional, Dict, Union
from ray.train.tensorflow import TensorflowConfig
from ray.ml.trainer import GenDataset
from ray.ml.train.data_parallel_trainer import DataParallelTrainer
from ray.ml.config import ScalingConfig, RunConfig
from ray.ml.preprocessor import Preprocessor
from ray.ml.check... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/train/integrations/tensorflow/tensorflow_trainer.py | 0.937918 | 0.568775 | tensorflow_trainer.py | pypi |
from typing import Optional, Union, List
import numpy as np
import pandas as pd
import torch
from ray.ml.predictor import Predictor, DataBatchType
from ray.ml.preprocessor import Preprocessor
from ray.ml.checkpoint import Checkpoint
from ray.ml.utils.torch_utils import load_torch_model, convert_pandas_to_torch_tensor... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/predictors/integrations/torch/torch_predictor.py | 0.943491 | 0.669735 | torch_predictor.py | pypi |
from typing import Optional, List, Union, Dict, Any
import os
import shutil
import numpy as np
import pandas as pd
import xgboost
import ray.cloudpickle as cpickle
from ray.ml.checkpoint import Checkpoint
from ray.ml.predictor import Predictor, DataBatchType
from ray.ml.preprocessor import Preprocessor
from ray.ml.co... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/predictors/integrations/xgboost/xgboost_predictor.py | 0.935876 | 0.551996 | xgboost_predictor.py | pypi |
from typing import Optional, List, Union
import os
import shutil
import numpy as np
import pandas as pd
import lightgbm
import ray.cloudpickle as cpickle
from ray.ml.checkpoint import Checkpoint
from ray.ml.predictor import Predictor, DataBatchType
from ray.ml.preprocessor import Preprocessor
from ray.ml.constants im... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/predictors/integrations/lightgbm/lightgbm_predictor.py | 0.93567 | 0.542924 | lightgbm_predictor.py | pypi |
from typing import Callable, Optional, Union, List, Type
import pandas as pd
import tensorflow as tf
from ray.ml.predictor import Predictor, DataBatchType
from ray.ml.preprocessor import Preprocessor
from ray.ml.checkpoint import Checkpoint
from ray.ml.constants import MODEL_KEY, PREPROCESSOR_KEY
class TensorflowPr... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/predictors/integrations/tensorflow/tensorflow_predictor.py | 0.961425 | 0.722245 | tensorflow_predictor.py | pypi |
from typing import List
import pandas as pd
from ray.data import Dataset
from ray.data.aggregate import Mean, Std, Min, Max
from ray.ml.preprocessor import Preprocessor
class StandardScaler(Preprocessor):
"""Scale values within columns based on mean and standard deviation.
For each column, each value will ... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/preprocessors/scaler.py | 0.915455 | 0.707531 | scaler.py | pypi |
from typing import List, Union, Optional, Dict
from numbers import Number
import pandas as pd
from ray.data import Dataset
from ray.data.aggregate import Mean, Max
from ray.ml.preprocessor import Preprocessor
class SimpleImputer(Preprocessor):
"""Populate missing values within columns.
Args:
column... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/preprocessors/imputer.py | 0.918722 | 0.534552 | imputer.py | pypi |
from typing import List, Dict, Set
import pandas as pd
from ray.data import Dataset
from ray.ml.preprocessor import Preprocessor
class OrdinalEncoder(Preprocessor):
"""Encode values within columns as ordered integer values.
Currently, order within a column is based on the values from the fitted
dataset... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/preprocessors/encoder.py | 0.892234 | 0.73538 | encoder.py | pypi |
from typing import Optional, Union, List, Dict
import pandas as pd
import torch
def convert_pandas_to_torch_tensor(
data_batch: pd.DataFrame,
columns: Optional[Union[List[str], List[List[str]]]] = None,
column_dtypes: Optional[Union[torch.dtype, List[torch.dtype]]] = None,
) -> Union[torch.Tensor, List[t... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/ml/utils/torch_utils.py | 0.952431 | 0.762026 | torch_utils.py | pypi |
import collections
from typing import List
from ray.util.timer import _Timer
class MetricsContext:
"""Metrics context object for a local iterator.
This object is accessible by all operators of a local iterator. It can be
used to store and retrieve global execution metrics for the iterator.
It can be... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/iter_metrics.py | 0.845225 | 0.441854 | iter_metrics.py | pypi |
import ray
from ray.util.annotations import PublicAPI
@PublicAPI(stability="beta")
class ActorPool:
"""Utility class to operate on a fixed pool of actors.
Arguments:
actors (list): List of Ray actor handles to use in this pool.
Examples:
>>> a1, a2 = Actor.remote(), Actor.remote()
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/actor_pool.py | 0.869133 | 0.504822 | actor_pool.py | pypi |
import weakref
from dataclasses import dataclass
import logging
from typing import List, TypeVar, Optional, Dict, Type, Tuple
import ray
from ray.actor import ActorHandle
T = TypeVar("T")
ActorMetadata = TypeVar("ActorMetadata")
logger = logging.getLogger(__name__)
@dataclass
class ActorWrapper:
"""Class conta... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/actor_group.py | 0.905123 | 0.21892 | actor_group.py | pypi |
import logging
from typing import Dict, Any, List, Optional, Tuple, Union
from ray._raylet import (
Sum as CythonCount,
Histogram as CythonHistogram,
Gauge as CythonGauge,
) # noqa: E402
# Sum is used for CythonCount because it allows incrementing by positive
# values that are different from one.
from r... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/metrics.py | 0.952959 | 0.363449 | metrics.py | pypi |
from typing import Any, Tuple, Set, Optional
import inspect
import ray.cloudpickle as cp
from contextlib import contextmanager
# Import ray first to use the bundled colorama
import ray # noqa: F401
from ray.util.annotations import DeveloperAPI
import colorama
@contextmanager
def _indent(printer):
printer.level... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/check_serialize.py | 0.847416 | 0.156008 | check_serialize.py | pypi |
import asyncio
from typing import Optional, Any, List, Dict
from collections.abc import Iterable
import ray
from ray.util.annotations import PublicAPI
@PublicAPI(stability="beta")
class Empty(Exception):
pass
@PublicAPI(stability="beta")
class Full(Exception):
pass
@PublicAPI(stability="beta")
class Queu... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/queue.py | 0.92566 | 0.455622 | queue.py | pypi |
from typing import List
import ray
from ray._private.services import get_node_ip_address
from ray.util import iter
from ray.util.annotations import PublicAPI
from ray.util.actor_pool import ActorPool
from ray.util.check_serialize import inspect_serializability
from ray.util.debug import log_once, disable_log_once_glob... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/__init__.py | 0.858926 | 0.210462 | __init__.py | pypi |
def PublicAPI(*args, **kwargs):
"""Annotation for documenting public APIs.
Public APIs are classes and methods exposed to end users of Ray. You
can expect these APIs to remain backwards compatible across minor Ray
releases (e.g., Ray 1.4 -> 1.8).
If "stability" is beta, the API is still public and... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/annotations.py | 0.832475 | 0.606557 | annotations.py | pypi |
from abc import ABCMeta
from abc import abstractmethod
from ray.util.collective.types import (
AllReduceOptions,
BarrierOptions,
ReduceOptions,
AllGatherOptions,
BroadcastOptions,
ReduceScatterOptions,
)
class BaseGroup(metaclass=ABCMeta):
def __init__(self, world_size, rank, group_name):... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/collective/collective_group/base_collective_group.py | 0.923035 | 0.161023 | base_collective_group.py | pypi |
import numpy
import asyncio
try:
import pygloo
except ImportError:
raise ImportError(
"Can not import pygloo. Please run 'pip install pygloo' to install pygloo."
)
import ray
from ray.util.collective.types import ReduceOp, torch_available
from ray.util.queue import _QueueActor
GLOO_REDUCE_OP_MAP ... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/collective/collective_group/gloo_util.py | 0.830834 | 0.525795 | gloo_util.py | pypi |
import numpy
try:
import cupy
from cupy.cuda import nccl
from cupy.cuda import Device # noqa: F401
from cupy.cuda.nccl import get_version
from cupy.cuda.nccl import get_build_version
from cupy.cuda.nccl import NcclCommunicator
from cupy.cuda.nccl import groupStart # noqa: F401
from cu... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/collective/collective_group/nccl_util.py | 0.773131 | 0.217213 | nccl_util.py | pypi |
import logging
import threading
import cupy
from ray.util.collective.collective_group import nccl_util
from ray.util.collective.const import ENV
NCCL_STREAM_POOL_SIZE = 32
MAX_GPU_PER_ACTOR = 16
logger = logging.getLogger(__name__)
class StreamPool:
"""The class that represents a stream pool associated with a ... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/collective/collective_group/cuda_stream.py | 0.782995 | 0.175573 | cuda_stream.py | pypi |
import logging
import datetime
import time
import ray
import cupy
from ray.util.collective.const import ENV
from ray.util.collective.collective_group import nccl_util
from ray.util.collective.collective_group.base_collective_group import BaseGroup
from ray.util.collective.const import get_store_name
from ray.util.col... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/collective/collective_group/nccl_collective_group.py | 0.741955 | 0.185947 | nccl_collective_group.py | pypi |
import logging
import datetime
import time
import os
import shutil
import ray
from ray import ray_constants
import pygloo
import numpy
from ray.util.collective.collective_group import gloo_util
from ray.util.collective.collective_group.base_collective_group import BaseGroup
from ray.util.collective.types import (
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/collective/collective_group/gloo_collective_group.py | 0.797636 | 0.155271 | gloo_collective_group.py | pypi |
import os
import logging
from typing import Dict, Optional, TYPE_CHECKING
if TYPE_CHECKING:
from mlflow.entities import Run
from mlflow.tracking import MlflowClient
logger = logging.getLogger(__name__)
class MLflowLoggerUtil:
"""Util class for setting up and logging to MLflow.
Use this util for any... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/ml_utils/mlflow.py | 0.853058 | 0.247072 | mlflow.py | pypi |
from typing import Dict, List, Union, Optional, TypeVar
import copy
from collections import deque
from collections.abc import Mapping, Sequence
T = TypeVar("T")
def merge_dicts(d1: dict, d2: dict) -> dict:
"""
Args:
d1 (dict): Dict 1.
d2 (dict): Dict 2.
Returns:
dict: A new dict... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/ml_utils/dict.py | 0.889691 | 0.375563 | dict.py | pypi |
from typing import Any
from typing import Dict
from typing import Optional
from ray.util.placement_group import PlacementGroup, check_placement_group_index
options = {
"num_returns": (
int,
lambda x: x >= 0,
"The keyword 'num_returns' only accepts 0 or a positive integer",
),
"num_... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/client/options.py | 0.891475 | 0.34414 | options.py | pypi |
import random
from typing import Iterable
from typing import List, Optional, Union
import pyarrow.parquet as pq
from pandas import DataFrame
from ray.util.annotations import Deprecated
import ray.util.iter as para_iter
from .dataset import MLDataset
from .interface import _SourceShard
class ParquetSourceShard(_Sour... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/data/parquet.py | 0.856782 | 0.428891 | parquet.py | pypi |
from collections import defaultdict
from typing import Iterable
import pandas as pd
from ray.util.data.dataset import MLDataset
from ray.util.data.parquet import read_parquet
from ray.util.iter import T, ParallelIterator
try:
import dataclasses
except: # noqa: E722
pass
else:
from dataclasses import is_... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/data/__init__.py | 0.919453 | 0.540439 | __init__.py | pypi |
import torch
import torch.nn.functional as F
from torch import nn
from torch.utils.data import DataLoader
import ray
import ray.util.data as ml_data
import ray.util.iter as parallel_it
from ray.util.sgd.torch.torch_dataset import TorchMLDataset
from ray.util.sgd.torch.torch_trainer import TorchTrainer
from ray.util.sg... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/data/examples/mlp_identity_torch.py | 0.926744 | 0.472562 | mlp_identity_torch.py | pypi |
from collections import OrderedDict
from collections.abc import Iterator
from operator import getitem
import uuid
import ray
from dask.base import quote
from dask.core import get as get_sync
from dask.utils import apply
try:
from dataclasses import is_dataclass, fields as dataclass_fields
except ImportError:
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/dask/common.py | 0.805861 | 0.326164 | common.py | pypi |
import argparse
import os
from filelock import FileLock
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
import torch.utils.data.distributed
import horovod.torch as hvd
from horovod.ray import RayExecutor
def metric_average(val, name):
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/horovod/horovod_example.py | 0.90048 | 0.304791 | horovod_example.py | pypi |
import collections
from contextlib import contextmanager
import logging
import numpy as np
import time
import ray
from ray.exceptions import RayActorError
logger = logging.getLogger(__name__)
BATCH_COUNT = "batch_count"
NUM_SAMPLES = "num_samples"
BATCH_SIZE = "*batch_size"
class TimerStat:
"""A running stat f... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/utils.py | 0.872782 | 0.404743 | utils.py | pypi |
import logging
from typing import Any, List, Optional
import tensorflow as tf
from ray.util.annotations import Deprecated
from ray.util.data import MLDataset
@Deprecated
class TFMLDataset:
"""A TFMLDataset which converted from MLDataset
.. code-block:: python
ds = ml_dataset.to_tf(feature_columns=... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/tf/tf_dataset.py | 0.801237 | 0.627409 | tf_dataset.py | pypi |
import argparse
import time
from tensorflow.keras.datasets import cifar10
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Activation, Flatten
from tensorflow.keras.layers import Conv2D, MaxPooling2D
i... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/tf/examples/cifar_tf_example.py | 0.903957 | 0.507202 | cifar_tf_example.py | pypi |
import argparse
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
import numpy as np
import ray
from ray import tune
from ray.util.sgd.tf.tf_trainer import TFTrainer, TFTrainable
NUM_TRAIN_SAMPLES = 1000
NUM_TEST_SAMPLES = 400
def create_config(batch_si... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/tf/examples/tensorflow_train_example.py | 0.496094 | 0.472014 | tensorflow_train_example.py | pypi |
import io
import logging
import time
from collections import defaultdict
from datetime import timedelta
import ray
import torch
from ray.exceptions import RayActorError
from ray.util.placement_group import get_current_placement_group, remove_placement_group
from ray.util.sgd.torch.constants import SGD_PLACEMENT_GROUP_... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/worker_group.py | 0.847889 | 0.222806 | worker_group.py | pypi |
import functools
import logging
from collections import Iterator
from collections.abc import Iterable
from typing import Any, Callable, List, Optional
import numpy as np
import torch
import pandas as pd
from torch.utils.data import IterableDataset
from ray.util.annotations import Deprecated
from ray.util.data import ... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/torch_dataset.py | 0.767646 | 0.393851 | torch_dataset.py | pypi |
import logging
import io
import itertools
import ray
import torch
from ray.util.sgd import utils
from ray.util.sgd.torch.utils import choose_amp_backend
logger = logging.getLogger(__name__)
amp = None
apex_amp = None
try:
from apex import amp as apex_amp
except ImportError:
logger.debug("apex is not install... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/torch_runner.py | 0.776792 | 0.210016 | torch_runner.py | pypi |
import torch.nn as nn
import torch.nn.functional as F
class BasicBlock(nn.Module):
expansion = 1
def __init__(self, in_planes, planes, stride=1):
super(BasicBlock, self).__init__()
self.conv1 = nn.Conv2d(
in_planes, planes, kernel_size=3, stride=stride, padding=1, bias=False
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/resnet.py | 0.947817 | 0.595463 | resnet.py | pypi |
import argparse
import numpy as np
import torch
import torch.nn as nn
from ray.util.sgd import TorchTrainer
from ray.util.sgd.torch import TrainingOperator
class LinearDataset(torch.utils.data.Dataset):
"""y = a * x + b"""
def __init__(self, a, b, size=1000):
x = np.arange(0, 10, 10 / size, dtype=np... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/examples/train_example.py | 0.903037 | 0.460168 | train_example.py | pypi |
import torch
import torch.nn as nn
from ray.tune.utils import merge_dicts
from torch.optim.lr_scheduler import ReduceLROnPlateau
from torch.utils.data import DataLoader
import ray
from ray import tune
from ray.util.sgd.torch import TorchTrainer, TrainingOperator
from ray.util.sgd.utils import BATCH_SIZE
from ray.util.... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/examples/tune_example.py | 0.910503 | 0.441432 | tune_example.py | pypi |
import numpy as np
import os
import torch
import torch.nn as nn
import argparse
from filelock import FileLock
from ray import tune
from ray.tune.schedulers import PopulationBasedTraining
from torch.utils.data import DataLoader, Subset
from torchvision.datasets import CIFAR10
import torchvision.transforms as transforms... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/examples/cifar_pytorch_pbt.py | 0.838614 | 0.343204 | cifar_pytorch_pbt.py | pypi |
import os
import torch
import torch.nn as nn
import argparse
from filelock import FileLock
from torch.utils.data import DataLoader, Subset
from torchvision.datasets import CIFAR10
import torchvision.transforms as transforms
from tqdm import trange
import ray
from ray.util.sgd.torch import TorchTrainer, TrainingOpera... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/examples/cifar_pytorch_example.py | 0.755366 | 0.313183 | cifar_pytorch_example.py | pypi |
import argparse
import numpy as np
import os
import torch
import torch.nn as nn
from torch.utils.data import DataLoader, Subset
from torchvision.datasets import CIFAR10
import torchvision.transforms as transforms
import ray
from ray import tune
from ray.tune import CLIReporter
from ray.tune.schedulers import Populatio... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/examples/pytorch_pbt_failure.py | 0.772445 | 0.45744 | pytorch_pbt_failure.py | pypi |
import argparse
import os
import torch
import torch.nn as nn
import torch.optim as optim
import torch.utils.data
import torchvision.datasets as datasets
import torchvision.transforms as transforms
import numpy as np
from filelock import FileLock
from tqdm import trange
from torch.autograd import Variable
from torch.... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/examples/dcgan.py | 0.936959 | 0.451327 | dcgan.py | pypi |
import numpy as np
from PIL import Image
import random
import torch
from torchvision import transforms as T
from torchvision.transforms import functional as F
def pad_if_smaller(img, size, fill=0):
min_size = min(img.size)
if min_size < size:
ow, oh = img.size
padh = size - oh if oh < size el... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/examples/segmentation/transforms.py | 0.821832 | 0.381076 | transforms.py | pypi |
import datetime
import os
import time
import torch
import torch.utils.data
from filelock import FileLock
from torch import nn
import torchvision
import ray
from ray.util.sgd.torch.examples.segmentation.coco_utils import get_coco
import ray.util.sgd.torch.examples.segmentation.transforms as T
import ray.util.sgd.torch... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/examples/segmentation/train_segmentation.py | 0.790692 | 0.359462 | train_segmentation.py | pypi |
from collections import defaultdict, deque
import datetime
import math
import time
import torch
import torch.distributed as dist
import errno
import os
class ConfusionMatrix(object):
def __init__(self, num_classes):
self.num_classes = num_classes
self.mat = None
def update(self, a, b):
... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/examples/segmentation/utils.py | 0.719384 | 0.349838 | utils.py | pypi |
import argparse
import logging
import json
import os
import time
from filelock import FileLock
from dataclasses import dataclass, field
from typing import Optional
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler
from tqdm import trange
import torch.distributed as di... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/examples/transformers/transformers_example.py | 0.82308 | 0.18374 | transformers_example.py | pypi |
import glob
import logging
import os
from tqdm import tqdm
from filelock import FileLock
import numpy as np
import torch
from torch.utils.data import DataLoader, SequentialSampler, TensorDataset
from transformers import glue_processors as processors
from transformers import glue_compute_metrics as compute_metrics
fro... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/torch/examples/transformers/utils.py | 0.812049 | 0.288368 | utils.py | pypi |
from ray.util.annotations import Deprecated
from ray.util.iter import ParallelIterator, from_iterators
@Deprecated
class Dataset:
"""A simple Dataset abstraction for RaySGD.
This dataset is designed to work with RaySGD trainers (currently just
Torch) to provide support for streaming large external datase... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/util/sgd/data/dataset.py | 0.838878 | 0.55923 | dataset.py | pypi |
import abc
import functools
import inspect
import logging
from typing import TYPE_CHECKING, Any, Tuple, Dict, Callable
import uuid
import json
import weakref
import ray
from ray.util.inspect import is_function_or_method, is_class_method, is_static_method
from ray._private import signature
from ray.workflow.common impo... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/workflow/virtual_actor_class.py | 0.879703 | 0.151812 | virtual_actor_class.py | pypi |
import base64
import asyncio
from ray import cloudpickle
from collections import deque
from enum import Enum, unique
import hashlib
import re
from typing import Dict, Generic, List, Optional, Callable, Set, TypeVar, Iterator, Any
import unicodedata
from dataclasses import dataclass
import ray
from ray import ObjectR... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/workflow/common.py | 0.792865 | 0.200049 | common.py | pypi |
import copy
from dataclasses import dataclass, field
import logging
from typing import Optional, List, TYPE_CHECKING
from contextlib import contextmanager
from ray.workflow.common import WorkflowStatus
logger = logging.getLogger(__name__)
if TYPE_CHECKING:
from ray.workflow.common import StepID, CheckpointModeTyp... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/workflow/workflow_context.py | 0.841858 | 0.447883 | workflow_context.py | pypi |
from typing import List, Any, Union, Dict, Callable, Tuple, Optional
import ray
from ray.workflow import workflow_context
from ray.workflow import serialization
from ray.workflow.common import (
Workflow,
StepID,
WorkflowRef,
WorkflowStaticRef,
WorkflowExecutionResult,
StepType,
)
from ray.work... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/workflow/recovery.py | 0.808937 | 0.339691 | recovery.py | pypi |
import asyncio
import contextlib
from dataclasses import dataclass
import logging
import ray
from ray import cloudpickle
from ray.types import ObjectRef
from ray.workflow import common
from ray.workflow import storage
from typing import Any, Dict, Generator, List, Optional, Tuple, TYPE_CHECKING
from collections import... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/workflow/serialization.py | 0.663996 | 0.186391 | serialization.py | pypi |
import asyncio
import json
import logging
import time
from typing import Set, List, Tuple, Optional, TYPE_CHECKING, Dict, Any
import uuid
import ray
from ray.workflow import workflow_context
from ray.workflow import workflow_storage
from ray.workflow.common import (
Workflow,
WorkflowStatus,
WorkflowMetaDa... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/workflow/execution.py | 0.702326 | 0.230931 | execution.py | pypi |
import contextlib
from typing import List, Any, Dict
import ray
import ray.cloudpickle
from ray.util.serialization import register_serializer, deregister_serializer
from ray.workflow.common import Workflow, WorkflowInputs, WorkflowRef
def _resolve_workflow_outputs(index: int) -> Any:
raise ValueError("There is ... | /ray_for_mars-1.12.1-cp38-cp38-manylinux2014_x86_64.whl/ray_for_mars-1.12.1.data/purelib/ray/workflow/serialization_context.py | 0.839142 | 0.351228 | serialization_context.py | pypi |
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