Module `recsys.types`

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from enum import Enum
from typing import Dict

import torch


class ModelType(str, Enum):
    MANY_TO_ONE = 1
    MANY_TO_MANY = 2


class WeightType(str, Enum):
    UNWEIGHTED = 1
    UNIFORM = 2
    CUMSUM_CORRECTED = 3


class RecurrentType(str, Enum):
    GRU = 1
    LSTM = 2


class FeatureProjectionType(str, Enum):
    CONCATENATION = 1
    MULTIPLICATION = 2


class OptimizerType(str, Enum):
    ADAM = 1
    ADAMW = 2


BatchType = Dict[str, torch.Tensor]

Classes

class FeatureProjectionType (value, names=None, *, module=None, qualname=None, type=None, start=1)

An enumeration.

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class FeatureProjectionType(str, Enum):
    CONCATENATION = 1
    MULTIPLICATION = 2

Ancestors

builtins.str
enum.Enum

Class variables

var CONCATENATION
var MULTIPLICATION

class ModelType (value, names=None, *, module=None, qualname=None, type=None, start=1)

An enumeration.

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class ModelType(str, Enum):
    MANY_TO_ONE = 1
    MANY_TO_MANY = 2

Ancestors

builtins.str
enum.Enum

Class variables

var MANY_TO_MANY
var MANY_TO_ONE

class OptimizerType (value, names=None, *, module=None, qualname=None, type=None, start=1)

An enumeration.

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class OptimizerType(str, Enum):
    ADAM = 1
    ADAMW = 2

Ancestors

builtins.str
enum.Enum

Class variables

var ADAM
var ADAMW

class RecurrentType (value, names=None, *, module=None, qualname=None, type=None, start=1)

An enumeration.

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class RecurrentType(str, Enum):
    GRU = 1
    LSTM = 2

Ancestors

builtins.str
enum.Enum

Class variables

var GRU
var LSTM

class WeightType (value, names=None, *, module=None, qualname=None, type=None, start=1)

An enumeration.

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class WeightType(str, Enum):
    UNWEIGHTED = 1
    UNIFORM = 2
    CUMSUM_CORRECTED = 3

Ancestors

builtins.str
enum.Enum

Class variables

var CUMSUM_CORRECTED
var UNIFORM
var UNWEIGHTED