(from_tensor,
to_tensor,
attention_mask=None,
num_attention_heads=1,
size_per_head=512,
query_act=None,
key_act=None,
value_act=None,
attention_probs_dropout_prob=0.0,
initializer_range=0.02,
do_return_2d_tensor=False,
batch_size=None,
from_seq_length=None,
to_seq_length=None,
tf_datatype=tf.float32)
| 36 | |
| 37 | |
| 38 | def attention_layer(from_tensor, |
| 39 | to_tensor, |
| 40 | attention_mask=None, |
| 41 | num_attention_heads=1, |
| 42 | size_per_head=512, |
| 43 | query_act=None, |
| 44 | key_act=None, |
| 45 | value_act=None, |
| 46 | attention_probs_dropout_prob=0.0, |
| 47 | initializer_range=0.02, |
| 48 | do_return_2d_tensor=False, |
| 49 | batch_size=None, |
| 50 | from_seq_length=None, |
| 51 | to_seq_length=None, |
| 52 | tf_datatype=tf.float32): |
| 53 | |
| 54 | def transpose_for_scores(input_tensor, batch_size, num_attention_heads, |
| 55 | seq_length, width): |
| 56 | output_tensor = tf.reshape( |
| 57 | input_tensor, [batch_size, seq_length, num_attention_heads, width]) |
| 58 | |
| 59 | output_tensor = tf.transpose(output_tensor, [0, 2, 1, 3]) |
| 60 | return output_tensor |
| 61 | |
| 62 | from_shape = get_shape_list(from_tensor, expected_rank=[2, 3]) |
| 63 | to_shape = get_shape_list(to_tensor, expected_rank=[2, 3]) |
| 64 | |
| 65 | if len(from_shape) != len(to_shape): |
| 66 | raise ValueError( |
| 67 | "The rank of `from_tensor` must match the rank of `to_tensor`.") |
| 68 | |
| 69 | if len(from_shape) == 3: |
| 70 | batch_size = from_shape[0] |
| 71 | from_seq_length = from_shape[1] |
| 72 | to_seq_length = to_shape[1] |
| 73 | elif len(from_shape) == 2: |
| 74 | if (batch_size is None or from_seq_length is None or to_seq_length is None): |
| 75 | raise ValueError( |
| 76 | "When passing in rank 2 tensors to attention_layer, the values " |
| 77 | "for `batch_size`, `from_seq_length`, and `to_seq_length` " |
| 78 | "must all be specified.") |
| 79 | |
| 80 | from_tensor_2d = reshape_to_matrix(from_tensor) |
| 81 | to_tensor_2d = reshape_to_matrix(to_tensor) |
| 82 | |
| 83 | # `query_layer` = [B*F, N*H] |
| 84 | query_layer = tf.layers.dense( |
| 85 | from_tensor_2d, |
| 86 | num_attention_heads * size_per_head, |
| 87 | activation=query_act, |
| 88 | name="query", |
| 89 | use_bias=True, |
| 90 | bias_initializer=create_initializer(initializer_range, tf_datatype), |
| 91 | kernel_initializer=create_initializer(initializer_range, tf_datatype)) |
| 92 | |
| 93 | # `key_layer` = [B*T, N*H] |
| 94 | key_layer = tf.layers.dense( |
| 95 | to_tensor_2d, |
no test coverage detected