Exemplos de StrOrFct em Python

Exemplo n.º 1

Arquivo: recurrent.py Projeto: gzcf/polyaxon-schemas

class LSTMSchema(RecurrentSchema):
    units = fields.Int()
    activation = StrOrFct(allow_none=True,
                          validate=validate.OneOf(ACTIVATION_VALUES))
    use_bias = fields.Bool(default=True, missing=True)
    recurrent_activation = StrOrFct(allow_none=True,
                                    validate=validate.OneOf(ACTIVATION_VALUES))
    kernel_initializer = fields.Nested(InitializerSchema,
                                       default=None,
                                       missing=None)
    recurrent_initializer = fields.Nested(InitializerSchema,
                                          default=None,
                                          missing=None)
    bias_initializer = fields.Nested(InitializerSchema,
                                     default=None,
                                     missing=None)
    unit_forget_bias = fields.Bool(default=True, missing=True)
    kernel_regularizer = fields.Nested(RegularizerSchema,
                                       default=None,
                                       missing=None)
    recurrent_regularizer = fields.Nested(RegularizerSchema,
                                          default=None,
                                          missing=None)
    bias_regularizer = fields.Nested(RegularizerSchema,
                                     default=None,
                                     missing=None)
    activity_regularizer = fields.Nested(RegularizerSchema,
                                         default=None,
                                         missing=None)
    kernel_constraint = fields.Nested(ConstraintSchema,
                                      default=None,
                                      missing=None)
    recurrent_constraint = fields.Nested(ConstraintSchema,
                                         default=None,
                                         missing=None)
    bias_constraint = fields.Nested(ConstraintSchema,
                                    default=None,
                                    missing=None)
    dropout = fields.Float(default=0., missing=0.)
    recurrent_dropout = fields.Float(default=0., missing=0.)

    class Meta:
        ordered = True

    @post_load
    def make(self, data):
        return LSTMConfig(**data)

    @post_dump
    def unmake(self, data):
        return LSTMConfig.remove_reduced_attrs(data)

Exemplo n.º 2

class Conv2DSchema(BaseLayerSchema):
    filters = fields.Int()
    kernel_size = ObjectOrListObject(fields.Int, min=2, max=2)
    strides = ObjectOrListObject(fields.Int, min=2, max=2, default=(1, 1), missing=(1, 1))
    padding = fields.Str(default='valid', missing='valid',
                         validate=validate.OneOf(['same', 'valid']))
    data_format = fields.Str(default=None, missing=None,
                             validate=validate.OneOf('channels_first', 'channels_last'))
    dilation_rate = ObjectOrListObject(fields.Int, min=2, max=2, default=(1, 1), missing=(1, 1))
    activation = StrOrFct(allow_none=True, validate=validate.OneOf(ACTIVATION_VALUES))
    use_bias = fields.Bool(default=True, missing=True)
    kernel_initializer = fields.Nested(InitializerSchema, allow_none=True)
    bias_initializer = fields.Nested(InitializerSchema, allow_none=True)
    kernel_regularizer = fields.Nested(RegularizerSchema, allow_none=True)
    bias_regularizer = fields.Nested(RegularizerSchema, allow_none=True)
    activity_regularizer = fields.Nested(RegularizerSchema, allow_none=True)
    kernel_constraint = fields.Nested(ConstraintSchema, allow_none=True)
    bias_constraint = fields.Nested(ConstraintSchema, allow_none=True)

    class Meta:
        ordered = True

    @post_load
    def make_load(self, data):
        return Conv2DConfig(**data)

Exemplo n.º 3

class LSTMSchema(RecurrentSchema):
    units = fields.Int()
    activation = StrOrFct(allow_none=True,
                          validate=validate.OneOf(ACTIVATION_VALUES))
    use_bias = fields.Bool(default=True, missing=True)
    recurrent_activation = StrOrFct(allow_none=True,
                                    validate=validate.OneOf(ACTIVATION_VALUES))
    kernel_initializer = fields.Nested(InitializerSchema,
                                       default=None,
                                       missing=None)
    recurrent_initializer = fields.Nested(InitializerSchema,
                                          default=None,
                                          missing=None)
    bias_initializer = fields.Nested(InitializerSchema,
                                     default=None,
                                     missing=None)
    unit_forget_bias = fields.Bool(default=True, missing=True)
    kernel_regularizer = fields.Nested(RegularizerSchema,
                                       default=None,
                                       missing=None)
    recurrent_regularizer = fields.Nested(RegularizerSchema,
                                          default=None,
                                          missing=None)
    bias_regularizer = fields.Nested(RegularizerSchema,
                                     default=None,
                                     missing=None)
    activity_regularizer = fields.Nested(RegularizerSchema,
                                         default=None,
                                         missing=None)
    kernel_constraint = fields.Nested(ConstraintSchema,
                                      default=None,
                                      missing=None)
    recurrent_constraint = fields.Nested(ConstraintSchema,
                                         default=None,
                                         missing=None)
    bias_constraint = fields.Nested(ConstraintSchema,
                                    default=None,
                                    missing=None)
    dropout = fields.Float(default=0., missing=0.)
    recurrent_dropout = fields.Float(default=0., missing=0.)

    @staticmethod
    def schema_config():
        return LSTMConfig

Exemplo n.º 4

Arquivo: core.py Projeto: mouradmourafiq/polyaxon-schemas

class ActivationSchema(BaseLayerSchema):
    activation = StrOrFct(allow_none=True,
                          validate=validate.OneOf(ACTIVATION_VALUES))

    class Meta:
        ordered = True

    @post_load
    def make_load(self, data):
        return ActivationConfig(**data)

Exemplo n.º 5

Arquivo: local.py Projeto: gzcf/polyaxon-schemas

class LocallyConnected1DSchema(BaseLayerSchema):
    filters = fields.Int()
    kernel_size = ObjectOrListObject(fields.Int, min=1, max=1)
    strides = ObjectOrListObject(fields.Int,
                                 min=1,
                                 max=1,
                                 default=1,
                                 missing=1)
    padding = fields.Str(default='valid',
                         missing='valid',
                         validate=validate.OneOf(['same', 'valid']))
    data_format = fields.Str(default=None,
                             missing=None,
                             validate=validate.OneOf('channels_first',
                                                     'channels_last'))
    activation = StrOrFct(allow_none=True,
                          validate=validate.OneOf(ACTIVATION_VALUES))
    use_bias = fields.Bool(default=True, missing=True)
    kernel_initializer = fields.Nested(InitializerSchema,
                                       default=None,
                                       missing=None)
    bias_initializer = fields.Nested(InitializerSchema,
                                     default=None,
                                     missing=None)
    kernel_regularizer = fields.Nested(RegularizerSchema,
                                       default=None,
                                       missing=None)
    bias_regularizer = fields.Nested(RegularizerSchema,
                                     default=None,
                                     missing=None)
    activity_regularizer = fields.Nested(RegularizerSchema,
                                         default=None,
                                         missing=None)
    kernel_constraint = fields.Nested(RegularizerSchema,
                                      default=None,
                                      missing=None)
    bias_constraint = fields.Nested(RegularizerSchema,
                                    default=None,
                                    missing=None)

    class Meta:
        ordered = True

    @post_load
    def make(self, data):
        return LocallyConnected1DConfig(**data)

    @post_dump
    def unmake(self, data):
        return LocallyConnected1DConfig.remove_reduced_attrs(data)

Exemplo n.º 6

Arquivo: core.py Projeto: polyaxon-team/polyaxon-schemas

class ActivationSchema(BaseLayerSchema):
    activation = StrOrFct(allow_none=True,
                          validate=validate.OneOf(ACTIVATION_VALUES))

    class Meta:
        ordered = True

    @post_load
    def make(self, data):
        return ActivationConfig(**data)

    @post_dump
    def unmake(self, data):
        return ActivationConfig.remove_reduced_attrs(data)

Exemplo n.º 7

class DenseSchema(BaseLayerSchema):
    units = fields.Int()
    activation = StrOrFct(allow_none=True, validate=validate.OneOf(ACTIVATION_VALUES))
    use_bias = fields.Bool(allow_none=True)
    kernel_initializer = fields.Nested(InitializerSchema, allow_none=True)
    bias_initializer = fields.Nested(InitializerSchema, allow_none=True)
    kernel_regularizer = fields.Nested(RegularizerSchema, allow_none=True)
    bias_regularizer = fields.Nested(RegularizerSchema, allow_none=True)
    activity_regularizer = fields.Nested(RegularizerSchema, allow_none=True)
    kernel_constraint = fields.Nested(ConstraintSchema, allow_none=True)
    bias_constraint = fields.Nested(ConstraintSchema, allow_none=True)

    @staticmethod
    def schema_config():
        return DenseConfig

Exemplo n.º 8

class SimpleRNNSchema(RecurrentSchema):
    units = fields.Int()
    activation = StrOrFct(allow_none=True,
                          validate=validate.OneOf(ACTIVATION_VALUES))
    use_bias = fields.Bool(default=True, missing=True)
    kernel_initializer = fields.Nested(InitializerSchema,
                                       default=None,
                                       missing=None)
    recurrent_initializer = fields.Nested(InitializerSchema,
                                          default=None,
                                          missing=None)
    bias_initializer = fields.Nested(InitializerSchema,
                                     default=None,
                                     missing=None)
    kernel_regularizer = fields.Nested(RegularizerSchema,
                                       default=None,
                                       missing=None)
    recurrent_regularizer = fields.Nested(RegularizerSchema,
                                          default=None,
                                          missing=None)
    bias_regularizer = fields.Nested(RegularizerSchema,
                                     default=None,
                                     missing=None)
    activity_regularizer = fields.Nested(RegularizerSchema,
                                         default=None,
                                         missing=None)
    kernel_constraint = fields.Nested(ConstraintSchema,
                                      default=None,
                                      missing=None)
    recurrent_constraint = fields.Nested(ConstraintSchema,
                                         default=None,
                                         missing=None)
    bias_constraint = fields.Nested(ConstraintSchema,
                                    default=None,
                                    missing=None)
    dropout = fields.Float(default=0., missing=0.)
    recurrent_dropout = fields.Float(default=0., missing=0.)

    class Meta:
        ordered = True

    @post_load
    def make_load(self, data):
        return SimpleRNNConfig(**data)

Exemplo n.º 9

Arquivo: core.py Projeto: mouradmourafiq/polyaxon-schemas

class DenseSchema(BaseLayerSchema):
    units = fields.Int()
    activation = StrOrFct(allow_none=True,
                          validate=validate.OneOf(ACTIVATION_VALUES))
    use_bias = fields.Bool(allow_none=True)
    kernel_initializer = fields.Nested(InitializerSchema, allow_none=True)
    bias_initializer = fields.Nested(InitializerSchema, allow_none=True)
    kernel_regularizer = fields.Nested(RegularizerSchema, allow_none=True)
    bias_regularizer = fields.Nested(RegularizerSchema, allow_none=True)
    activity_regularizer = fields.Nested(RegularizerSchema, allow_none=True)
    kernel_constraint = fields.Nested(ConstraintSchema, allow_none=True)
    bias_constraint = fields.Nested(ConstraintSchema, allow_none=True)

    class Meta:
        ordered = True

    @post_load
    def make_load(self, data):
        return DenseConfig(**data)

Exemplo n.º 10

Arquivo: local.py Projeto: tpimentelms/polyaxon-schemas

class LocallyConnected2DSchema(BaseLayerSchema):
    filters = fields.Int()
    kernel_size = ObjectOrListObject(fields.Int, min=2, max=2)
    strides = ObjectOrListObject(fields.Int,
                                 min=2,
                                 max=2,
                                 default=(1, 1),
                                 missing=(1, 1))
    padding = fields.Str(default='valid',
                         missing='valid',
                         validate=validate.OneOf(['same', 'valid']))
    data_format = fields.Str(default=None,
                             missing=None,
                             validate=validate.OneOf('channels_first',
                                                     'channels_last'))
    activation = StrOrFct(allow_none=True,
                          validate=validate.OneOf(ACTIVATION_VALUES))
    use_bias = fields.Bool(default=True, missing=True)
    kernel_initializer = fields.Nested(InitializerSchema,
                                       default=None,
                                       missing=None)
    bias_initializer = fields.Nested(InitializerSchema,
                                     default=None,
                                     missing=None)
    kernel_regularizer = fields.Nested(RegularizerSchema,
                                       default=None,
                                       missing=None)
    bias_regularizer = fields.Nested(RegularizerSchema,
                                     default=None,
                                     missing=None)
    activity_regularizer = fields.Nested(RegularizerSchema,
                                         default=None,
                                         missing=None)
    kernel_constraint = fields.Nested(RegularizerSchema,
                                      default=None,
                                      missing=None)
    bias_constraint = fields.Nested(RegularizerSchema,
                                    default=None,
                                    missing=None)

    @staticmethod
    def schema_config():
        return LocallyConnected2DConfig

Exemplo n.º 11

class ActivationSchema(BaseLayerSchema):
    activation = StrOrFct(allow_none=True, validate=validate.OneOf(ACTIVATION_VALUES))

    @staticmethod
    def schema_config():
        return ActivationConfig