from deeplodocus.utils.flag import Flag
#
# DATA MEMORIZATION CONDITION
#
DEEP_MEMORIZE_BATCHES = Flag("Memorize batches",
description="Memorize info at each batch",
names=["default", "batch", "batches"])
DEEP_MEMORIZE_EPOCHS = Flag("Memorize epochs",
description="Memorize info at each epoch",
names=["epoch", "epochs"])
from deeplodocus.utils.flag import Flag
#
# DATA TYPE FLAGS
#
DEEP_DTYPE_STRING = Flag(name="String",
description="String type",
names=["string", "str"])
DEEP_DTYPE_IMAGE = Flag(name="Image",
description="Image type",
names=["image", "images", "img"])
DEEP_DTYPE_VIDEO = Flag(name="Video",
description="Video type",
names=["video", "videos", "vid"])
DEEP_DTYPE_INTEGER = Flag(name="Int",
description="Integer type",
names=["integer", "int"])
DEEP_DTYPE_FLOAT = Flag(name="Float",
description="Float type",
names=["float", "flt"])
DEEP_DTYPE_BOOLEAN = Flag(name="Bool",
description="Boolean type",
names=["boolean", "bool"])
DEEP_DTYPE_AUDIO = Flag(name="Sound",
description="Sound type",
names=["audio", "sound", "mp3", "cda"])
DEEP_DTYPE_SEQUENCE = Flag(name="Sequence",
description="Sequence type",
names=["sequence"])
from deeplodocus.utils.flag import Flag
#
# NOTIFICATION FLAGS
#
DEEP_NOTIF_INFO = Flag(
name="Info notification",
description="Blue info notification",
names=["info"]
)
DEEP_NOTIF_DEBUG = Flag(
name="Debug notification",
description="Purple debug notification",
names=["debug"]
)
DEEP_NOTIF_SUCCESS = Flag(
name="Success notification",
description="Green success notification",
names=["success"]
)
DEEP_NOTIF_WARNING = Flag(
name="Warning notification",
description="Orange warning notification",
names=["warning"]
)
DEEP_NOTIF_ERROR = Flag(
name="Error notification",
description="Red error notification",
names=["error"]
)
from deeplodocus.utils.flag import Flag
#
# EVENT TYPES
#
DEEP_EVENT_UNDEFINED = Flag(name="Undefined",
description="Event : Undefined",
names=["none", "undefined"])
DEEP_EVENT_ON_BATCH_END = Flag(
name="On Batch End",
description="Event : On Batch End",
names=["batch end", "end batch", "end_batch", "on_batch_end"])
DEEP_EVENT_ON_EPOCH_END = Flag(
name="On Epoch End",
description="Event : On Epoch End",
names=["epoch end", "end epoch", "on epoch end"])
DEEP_EVENT_ON_TRAINING_START = Flag(
name="On Training Start",
description="Event : On Training Start",
names=["training start", "on training start"])
DEEP_EVENT_ON_TRAINING_END = Flag(name="On Training End",
description="Event : On Training End",
names=["training end", "on training end"])
DEEP_EVENT_ON_UPDATE_ALL = Flag(name="On Update all",
description="Event : On Update All",
names=["update all"])
DEEP_EVENT_ON_UPDATE_MODEL = Flag(name="On Update Model",
description="Event : On Update Model",
names=["update model"])
DEEP_EVENT_ON_UPDATE_OPTIMIZER = Flag(
# List the method used to load the data in the dataset
DEEP_LOAD_METHOD_MEMORY = 0
DEEP_LOAD_METHOD_HARDDRIVE = 1
DEEP_LOAD_METHOD_SERVER = 2
# List all the methods
DEEP_LOAD_METHOD_LIST = [DEEP_LOAD_METHOD_MEMORY,
DEEP_LOAD_METHOD_HARDDRIVE,
DEEP_LOAD_METHOD_SERVER]
# List the method used to load the data in the dataset
# High level methods
DEEP_LOAD_METHOD_ONLINE = Flag(name="Online",
description="Load the data during training",
names=["default", "online", "on line", "on-line", "on_line"])
DEEP_LOAD_METHOD_SEMI_ONLINE = Flag(name="Semi-online",
description="Load the source before the training and the data during the training",
names=["semi-online", "semionline", "semi online", "semi_online"])
DEEP_LOAD_METHOD_OFFLINE = Flag(name="Offline",
description="Load the data before training",
names=["offline", "off line", "off-line", "off_line", "memory"])
# Low level methods
DEEP_LOAD_METHOD_MEMORY_ = Flag(name="Memory",
description="Load from memory",
names=["memory"])
from deeplodocus.utils.flag import Flag
#
# SHUFFLE
#
DEEP_SHUFFLE_NONE = Flag(name="No shuffling",
description="No shuffling",
names=["none", "no", "false"])
DEEP_SHUFFLE_BATCHES = Flag(name="Batch shuffling",
description="Batch shuffling",
names=[
"batches", "batch", "shuffle batches",
"shuffle_batches", "shuffle-batches"
])
DEEP_SHUFFLE_ALL = Flag(
name="Shuffle all",
description="Shuffling all the dataset",
names=["all", "default", "shuffle all", "shuffle_all", "shuffle-all"])
DEEP_SHUFFLE_RANDOM_PICK = Flag(
name="Pick random indices",
description="Pick randomly indices in the list available",
names=["pick", "random_pick", "random pick", "random-pick"])
from deeplodocus.utils.flag import Flag
#
# LOAD_AS FLAGS
#
DEEP_LOAD_AS_STRING = Flag(name="String",
description="String type",
names=["string", "str"])
DEEP_LOAD_AS_IMAGE = Flag(name="Image",
description="Image type",
names=["image", "images", "img"])
DEEP_LOAD_AS_VIDEO = Flag(name="Video",
description="Video type",
names=["video", "videos", "vid"])
DEEP_LOAD_AS_INTEGER = Flag(name="Int",
description="Integer type",
names=["integer", "int"])
DEEP_LOAD_AS_FLOAT = Flag(name="Float",
description="Float type",
names=["float", "flt"])
DEEP_LOAD_AS_BOOLEAN = Flag(name="Bool",
description="Boolean type",
names=["boolean", "bool"])
DEEP_LOAD_AS_AUDIO = Flag(name="Sound",
description="Sound type",
names=["audio", "sound", "mp3", "cda"])
DEEP_LOAD_AS_SEQUENCE = Flag(name="Sequence",
description="Sequence type",
from deeplodocus.utils import get_main_path
from deeplodocus.utils.flag import Flag
#
# ENTRIES
#
DEEP_ENTRY_INPUT = 0
DEEP_ENTRY_LABEL = 1
DEEP_ENTRY_OUTPUT = 2
DEEP_ENTRY_ADDITIONAL_DATA = 3
DEEP_ENTRY_INPUT = Flag(name="Input",
description="Input entry",
names=["input", "inputs", "inp", "x"])
DEEP_ENTRY_LABEL = Flag(name="Label",
description="Label entry",
names=[
"label", "labels", "lab", "expected output",
"expected_output", "y_expected", "y_hat"
])
DEEP_ENTRY_OUTPUT = Flag(name="Output",
description="Output entry",
names=["output", "outputs", "y"])
DEEP_ENTRY_ADDITIONAL_DATA = Flag(name="Additional data",
description="Additional Data entry",
names=["additional_data", "additional data"])
DEEP_ENTRY_BASE_FILE_NAME = get_main_path(
) + "/data/auto-generated_dataset_%s_entry_%s_%i_source_%i.dat"
from deeplodocus.utils.flag import Flag
#
# POSSIBLE SOURCES
#
DEEP_SOURCE_FILE = Flag(name="File",
description="Source : local file",
names=["file"])
DEEP_SOURCE_FOLDER = Flag(name="Folder",
description="Source : local folder",
names=["folder", "dir", "directory"])
DEEP_SOURCE_DATABASE = Flag(name="Database",
description="Source : database",
names=["database", "db"])
DEEP_SOURCE_SERVER = Flag(name="Server",
description="Source : server",
names=["server", "remote"])
DEEP_SOURCE_SPARK = Flag(name="Spark",
description="Source: Spark access",
names=["spark"])
DEEP_SOURCE_PREMADE_DATASET = Flag(name="Pre-made dataset",
description="Source: A pre-made dataset",
names=["dataset", "premade", "pre-made"])
from deeplodocus.utils.flag import Flag
DEEP_ADMIN_START_PROJECT = Flag(
name="Start Project",
description="startproject : Start a deeplodocus project",
names=["start_project", "startproject"])
DEEP_ADMIN_VERSION = Flag(name="Version",
description="version : Display Deeplodocus Version",
names=["version"])
DEEP_ADMIN_HELP = Flag(name="Help",
description="help : Display the Deeplodocus commands",
names=["help"])
from deeplodocus.utils.flag import Flag
DEEP_DATASET_TRAIN = Flag(name="Training",
description="Training portion of the dataset",
names=["train", "training"])
DEEP_DATASET_VAL = Flag(name="Validation",
description="Validation portion of the dataset",
names=["validation", "val"])
DEEP_DATASET_TEST = Flag(name="Test",
description="Testportion of the dataset",
names=["test", "testing"])
DEEP_DATASET_PREDICTION = Flag(name="Prediction",
description="Prediction portion of the dataset",
names=["predict", "prediction", "pred"])
from deeplodocus.utils.flag import Flag
DEEP_REDUCE_MEAN = Flag(name="Mean",
description="Reduction by mean",
names=["mean"])
DEEP_REDUCE_SUM = Flag(name="Sum",
description="Reduction by sum",
names=["sum"])
DEEP_REDUCE_LAST = Flag(name="Last",
description="Reduction by taking last value",
names=["last", "latest"])
from deeplodocus.utils.flag import Flag
#
# SHUFFLE
#
DEEP_SHUFFLE_NONE = Flag(
name="No shuffling",
description="No shuffling",
names=["none", "no", "false"]
)
DEEP_SHUFFLE_BATCHES = Flag(
name="Batch shuffling",
description="Batch shuffling",
names=["batches", "batch", "shuffle batches", "shuffle_batches", "shuffle-batches"]
)
DEEP_SHUFFLE_ALL = Flag(
name="Shuffle all",
description="Shuffling all the dataset",
names=["all", "default", "shuffle all", "shuffle_all", "shuffle-all"]
)
from deeplodocus.utils.flag import Flag
#
# VERBOSE
#
DEEP_VERBOSE_BATCH = Flag(
name="Verbose Batch",
description="Print information at the end of every batch",
names=["batch", "batches", "default"]
)
DEEP_VERBOSE_EPOCH = Flag(
name="Verbose Epoch",
description="Print information at the end of every epoch",
names=["epoch", "epochs"]
)
DEEP_VERBOSE_TRAINING = Flag(
name="Verbose Training",
description="Print information at the end of the training",
names=["training"]
)
from deeplodocus.utils.flag import Flag
#
# LIBRARIES
#
#DEEP_LIB_PIL = 0
#DEEP_LIB_OPENCV = 1
DEEP_LIB_PIL = Flag(name="PIL",
description="Computer vision library : PIL",
names=["pil"])
DEEP_LIB_OPENCV = Flag(name="OpenCV",
description="Computer vision library : OpenCV",
names=["opencv"])
from deeplodocus.utils.flag import Flag
#
# FLOATS
#
DEEP_DTYPE_FLOAT8 = Flag(name="float8",
description="Float8 format",
names=["float8"])
DEEP_DTYPE_FLOAT16 = Flag(name="float16",
description="Float16 format",
names=["float16"])
DEEP_DTYPE_FLOAT32 = Flag(name="float32",
description="Float32 format",
names=["float32", "float"])
DEEP_DTYPE_FLOAT64 = Flag(name="float64",
description="Float64 format",
names=["float64"])
#
# INTEGERS
#
DEEP_DTYPE_INT8 = Flag(name="int8", description="Int8 format", names=["int8"])
DEEP_DTYPE_INT16 = Flag(name="int16",
description="Int16 format",
names=["int16"])
from deeplodocus.utils.flag import Flag
#
# SAVE FORMATS
#
DEEP_SAVE_FORMAT_ONNX = Flag(name="ONNX",
description="Open Neural Network eXchange format",
names=["onnx"])
DEEP_SAVE_FORMAT_PYTORCH = Flag(
name="PyTorch",
description="Saving with Python's pickle module",
names=["pytorch", "pt", "pth", "default"])
#
# SAVE CONDITIONS
#
DEEP_SAVE_CONDITION_LESS = Flag(
name="Less than",
description=
"Call saver when given metric is smaller than all previous values",
names=["<", "smaller", "less", "default"])
DEEP_SAVE_CONDITION_GREATER = Flag(
name="Greater than",
description=
"Call saver when given metric is greater than all previous values",
names=[">", "bigger", "greater"])
from deeplodocus.utils.flag import Flag
DEEP_ADMIN_NEW_PROJECT = Flag(
name="Start Project",
description="new-project : Initialise a new deeplodocus project",
names=["new-project", "newproject", "new_project"])
DEEP_ADMIN_RUN = Flag(
name="Run",
description="run : Run a deeplodocus project",
names=["run", "run-project", "runproject", "run_project"])
DEEP_ADMIN_VERSION = Flag(name="Version",
description="version : Display Deeplodocus Version",
names=["version"])
DEEP_ADMIN_HELP = Flag(name="Help",
description="help : Display the Deeplodocus commands",
names=["help"])
DEEP_ADMIN_TRANSFORMER = Flag(
name="Transformer",
description="transformer : Create a template transformer file",
names=["transformer"])
DEEP_ADMIN_OUTPUT_TRANSFORMER = Flag(
name="Output Transformer",
description=
"output-transformer : Create a template output transformer file",
names=["outputtransformer", "output-transformer", "output_transformer"])
