Simplify embedding docstring
@@ -57,10 +57,10 @@ class Embedding(Layer):
(without it, the shape of the dense outputs cannot be computed).
# Input shape
- N-D tensor with shape: `(batch_size, sequence_length_1, ..., sequence_length_N-1)`.
+ 2D tensor with shape: `(batch_size, sequence_length)`.
# Output shape
- (N+1)-D tensor with shape: `(batch_size, sequence_length_1, ..., sequence_length_N-1, output_dim)`.
+ 3D tensor with shape: `(batch_size, sequence_length, output_dim)`.
# References
- [A Theoretically Grounded Application of Dropout in Recurrent Neural Networks](http://arxiv.org/abs/1512.05287)
