def from_config(cls, config):
config["pretraining"] = hyperparameters.deserialize(config["pretraining"])
config["dropout"] = hyperparameters.deserialize(config["dropout"])
config["embedding_dim"] = hyperparameters.deserialize(
config["embedding_dim"]
)
return cls(**config)
def from_config(cls, config):
config["bidirectional"] = hyperparameters.deserialize(
config["bidirectional"]
)
config["num_layers"] = hyperparameters.deserialize(config["num_layers"])
config["layer_type"] = hyperparameters.deserialize(config["layer_type"])
return cls(**config)
def from_config(cls, config):
config["kernel_size"] = hyperparameters.deserialize(config["kernel_size"])
config["num_blocks"] = hyperparameters.deserialize(config["num_blocks"])
config["num_layers"] = hyperparameters.deserialize(config["num_layers"])
config["filters"] = hyperparameters.deserialize(config["filters"])
config["dropout"] = hyperparameters.deserialize(config["dropout"])
return cls(**config)
def from_config(cls, config):
config["max_sequence_length"] = hyperparameters.deserialize(
config["max_sequence_length"]
)
return cls(**config)
def from_config(cls, config):
config["num_layers"] = hyperparameters.deserialize(config["num_layers"])
config["num_units"] = hyperparameters.deserialize(config["num_units"])
config["dropout"] = hyperparameters.deserialize(config["dropout"])
return cls(**config)
def from_config(cls, config):
config["rotation_factor"] = hyperparameters.deserialize(
config["rotation_factor"]
)
return cls(**config)