All Questions
9 questions
0
votes
1
answer
660
views
Unrecognized keyword arguments passed to Embedding: {'input_length': 10}
I am trying to build this RNN below,
import keras
model = Sequential()
input_dim=3
output_dim=1
input_length=1
model.add(keras.layers.Embedding(input_dim, output_dim, input_length=input_length))
...
- 1
0
votes
1
answer
613
views
Pre-trained embedding layer: tf.constant with unsupported shape
I am going to use pre-trained word embeddings in Keras model. my matrix weights are stored in ;matrix.w2v.wv.vectors.npy; and it has shape (150854, 100).
Now when I add the embedding layer in the ...
- 25
0
votes
1
answer
570
views
Bag of Words embedding layer in Keras?
I have a very simple Keras model that looks like:
model = Sequential()
model.add(Dense(hidden_size, input_dim=n_inputs, activation='relu'))
model.add(Dense(n_outputs, activation='softmax'))
The ...
- 57
0
votes
2
answers
2k
views
How does keras Embedding layer works if input value greater than input_dim?
How does Embedding layer works if input value greater than input_dim?
Why keras doesn't raise an exception?
from keras.models import Sequential
from keras.layers import Embedding
model = Sequential(...
- 1,763
1
vote
1
answer
199
views
error embedding input shape: expected embedding_1_input to have shape (25,) but got array with shape (1,)
I'm not sure why I keep getting this error. I've checked the length of my actual tokenised + encoded text data and it matches the input length I selected. The code is below:
from keras.preprocessing....
- 43
0
votes
1
answer
650
views
Keras - Embedding Layer and GRU Layer Shape Error
# input_shape = (137861, 21, 1)
# output_sequence_length = 21
# english_vocab_size = 199
# french_vocab_size = 344
def embed_model(input_shape, output_sequence_length, english_vocab_size, ...
- 61
3
votes
1
answer
857
views
get the before last feature of network for embedding, is not working
I would like to have an image embedding to understand which images the network is seing as closer and which one seemed to be very different for him.
First, I wanted to use Tensorboard callbacks in ...
- 659
6
votes
2
answers
6k
views
Keras Layer Concatenation
I'm trying to see how I can create a model in Keras with multiple Embedding Layers and other inputs. Here's how my model is structured(E=Embedding Layer, [....]=Input Layer):
E E [V V V]
\ | /
\...
- 375
0
votes
1
answer
688
views
Keras: Dense vs. Embedding - ValueError: Input 0 is incompatible with layer repeat_vector_9: expected ndim=2, found ndim=3
I have the following network which works fine:
left = Sequential()
left.add(Dense(EMBED_DIM,input_shape=(ENCODE_DIM,)))
left.add(RepeatVector(look_back))
However, I need to replace the Dense layer ...
- 25.3k