def build(self, input_shape):
if isinstance(input_shape, list):
assert len(input_shape) == 2
input_ids_shape, token_type_ids_shape = input_shape
self.input_spec = [tf.keras.layers.InputSpec(shape=input_ids_shape),
tf.keras.layers.InputSpec(shape=token_type_ids_shape)]
else:
input_ids_shape = input_shape
self.input_spec = tf.keras.layers.InputSpec(shape=input_ids_shape)
self.embeddings_layer = AdvBertEmbeddingsLayer.from_params(
self.params,
name="embeddings"
)
# create all transformer encoder sub-layers
self.encoders_layer = TransformerEncoderLayer.from_params(
self.params,
name="encoder"
)
self.dropout_layer = tf.keras.layers.Dropout(rate=self.params.hidden_dropout)
self.pooler_layer = PoolerLayer(self.params.hidden_size, name="pooler")
super(BertModelLayer, self).build(input_shape)
def _construct(self, **kwargs):
super()._construct(**kwargs)
self.embeddings_layer = BertEmbeddingsLayer.from_params(
self.params, name="embeddings")
# create all transformer encoder sub-layers
self.encoders_layer = TransformerEncoderLayer.from_params(
self.params, name="encoder")
self.support_masking = True
def build(self, input_shape):
if isinstance(input_shape, list):
assert len(input_shape) == 2
input_ids_shape, token_type_ids_shape = input_shape
self.input_spec = [
keras.layers.InputSpec(shape=input_ids_shape),
keras.layers.InputSpec(shape=token_type_ids_shape)
]
else:
input_ids_shape = input_shape
self.input_spec = keras.layers.InputSpec(shape=input_ids_shape)
self.embeddings_layer = BertEmbeddingsLayer.from_params(self.params, name="embeddings")
# create all transformer encoder sub-layers
self.encoders_layer = TransformerEncoderLayer.from_params(self.params, name="encoder")
super(BertModelLayer, self).build(input_shape)