class MaxPooling2DSchema(BaseLayerSchema):
pool_size = ObjectOrListObject(fields.Int, min=2, max=2, default=(2, 2), missing=(2, 2))
strides = ObjectOrListObject(fields.Int, min=2, max=2, default=None, missing=None)
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'))
@staticmethod
def schema_config():
return MaxPooling2DConfig
class GraphSchema(BaseSchema):
input_layers = ObjectOrListObject(Tensor)
output_layers = ObjectOrListObject(Tensor)
layers = fields.Nested(LayerSchema, many=True)
name = fields.Str(allow_none=True)
class Meta:
unknown = EXCLUDE
@staticmethod
def schema_config():
return GraphConfig
class ConvRecurrent2DSchema(RecurrentSchema):
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(allow_none=True,
validate=validate.OneOf('channels_first', 'channels_last'))
dilation_rate = ObjectOrListObject(fields.Int, min=2, max=2, default=(1, 1), missing=(1, 1))
return_sequences = fields.Bool(default=False, missing=False)
go_backwards = fields.Bool(default=False, missing=False)
stateful = fields.Bool(default=False, missing=False)
@staticmethod
def schema_config():
return ConvRecurrent2DConfig
class EpisodeLoggingTensorHookSchema(BaseSchema):
tensors = ObjectOrListObject(fields.Str)
every_n_episodes = fields.Int()
@staticmethod
def schema_config():
return EpisodeLoggingTensorHookConfig
class DotSchema(BaseLayerSchema):
axes = ObjectOrListObject(fields.Int)
normalize = fields.Bool(allow_none=True)
@staticmethod
def schema_config():
return DotConfig
class StepLoggingTensorHookSchema(BaseSchema):
tensors = ObjectOrListObject(fields.Str)
every_n_iter = fields.Int(allow_none=True)
every_n_secs = fields.Int(allow_none=True)
@staticmethod
def schema_config():
return StepLoggingTensorHookConfig
class BaseLayerSchema(BaseSchema):
name = fields.Str(allow_none=True)
trainable = fields.Bool(default=True, missing=True)
dtype = DType(allow_none=True)
inbound_nodes = ObjectOrListObject(Tensor, allow_none=True)
class Meta:
unknown = EXCLUDE
ordered = True
def get_attribute(self, obj, attr, default):
return get_value(attr, obj, default)
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)
@staticmethod
def schema_config():
return LocallyConnected1DConfig
class BaseModelSchema(BaseSchema):
graph = fields.Nested(GraphSchema)
loss = fields.Nested(LossSchema, allow_none=True)
optimizer = fields.Nested(OptimizerSchema, allow_none=True)
metrics = fields.Nested(MetricSchema, many=True, allow_none=True)
summaries = ObjectOrListObject(fields.Str, allow_none=True)
clip_gradients = fields.Float(allow_none=True)
clip_embed_gradients = fields.Float(allow_none=True)
name = fields.Str(allow_none=True)
@staticmethod
def schema_config():
return BaseModelConfig
class PReLUSchema(BaseLayerSchema):
alpha_initializer = fields.Nested(InitializerSchema,
default=None,
missing=None)
alpha_regularizer = fields.Nested(RegularizerSchema,
default=None,
missing=None)
alpha_constraint = fields.Nested(ConstraintSchema,
default=None,
missing=None)
shared_axes = ObjectOrListObject(fields.Int, default=None, missing=None)
@staticmethod
def schema_config():
return PReLUConfig
class RunSchema(BaseSchema):
cmd = ObjectOrListObject(fields.Str)
@staticmethod
def schema_config():
return RunConfig
class FinalOpsHookSchema(BaseSchema):
final_ops = ObjectOrListObject(fields.Str)
@staticmethod
def schema_config():
return FinalOpsHookConfig
class BaseBridgeSchema(BaseSchema):
state_size = ObjectOrListObject(fields.Int, allow_none=True)
name = fields.Str(allow_none=True)