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55 lines
1.6 KiB
55 lines
1.6 KiB
import os
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class EXPERIMENT_TYPES_LONG(object):
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# If this Enum is modified
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# modify `experiment/experiment_schema.json` accordingly
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pnf = "predict_numeric_fields"
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pcf = "predict_categorical_fields"
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dno = "detect_numeric_outliers"
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dco = "detect_categorical_outliers"
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fts = "forecast_time_series"
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sf = "smart_forecast"
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sod = "smart_outlier_detection"
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sc = "smart_clustering"
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sp = "smart_prediction"
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cne = "cluster_numeric_events"
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EXPERIMENT_TYPES_MAP = {
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EXPERIMENT_TYPES_LONG.pnf: "pnf",
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EXPERIMENT_TYPES_LONG.pcf: "pcf",
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EXPERIMENT_TYPES_LONG.dno: "dno",
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EXPERIMENT_TYPES_LONG.dco: "dco",
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EXPERIMENT_TYPES_LONG.fts: "fts",
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EXPERIMENT_TYPES_LONG.sf: "sf",
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EXPERIMENT_TYPES_LONG.sod: "sod",
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EXPERIMENT_TYPES_LONG.sc: "sc",
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EXPERIMENT_TYPES_LONG.cne: "cne",
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}
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DEFAULT_LOOKUPS_DIR = os.path.join(os.path.dirname(os.path.dirname(__file__)), "lookups")
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CSV_FILESIZE_LIMIT = 2**30
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EXPERIMENT_MODEL_PREFIX = "_exp_"
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EXPERMENT_DRAFT_MODEL_PREFIX = 'draft_'
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MODEL_EXTENSION = '.mlmodel'
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ONNX_MODEL_EXTENSION = ".onnx"
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MODEL_FILE_REGEX = r'.*__mlspl_(?P<model_name>[a-zA-Z_][a-zA-Z0-9_]*){}'.format(MODEL_EXTENSION)
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ONNX_MODEL_FILE_REGEX = r'.*__mlspl_(?P<model_name>[a-zA-Z_][a-zA-Z0-9_]*){}'.format(
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ONNX_MODEL_EXTENSION
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)
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TELEMETRY_ID_REGEX = r'^(?:_exp_)?(?:draft_)?([0-9a-f]+)(?:_[a-zA-z]+_[0-9]+)?$'
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HOWTO_CONFIGURE_MLSPL_LIMITS = (
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'To configure limits, use mlspl.conf or the "Settings" tab in the app navigation bar.'
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)
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NUM_PCA_COMPONENTS = 1
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DEAFULTS_ONNX = {
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'namespace': 'user',
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'is_onnx': False,
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'model_param_activation': 'softmax',
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'model_param_thresh': 0.5,
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}
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