Mixing
Getting a part of a Keras Model
0
I have a model for an AutoEncoder as follows:
height, width = 28, 28
input_img = Input(shape=(height * width,))
encoding_dim = height * width//256
x = Dense(height * width, activation='relu')(input_img)
encoded1 = Dense(height * width//2, activation='relu')(x)
encoded2 = Dense(height * width//8, activation='relu')(encoded1)
y = Dense(encoding_dim, activation='relu')(encoded2)
decoded2 = Dense(height * width//8, activation='relu')(y)
decoded1 = Dense(height * width//2, activation='relu')(decoded2)
z = Dense(height * width, activation='sigmoid')(decoded1)
autoencoder = Model(input_img, z)
#encoder is the model of the autoencoder slice in the middle
encoder = Model(input_img, y)
decoder = Model(y, z)
print(encoder)
print(decoder)
The encoder part is retrived using the code above, however I can't get the decoder part using the code I added above:
I recieve the following error:
ValueError: Graph disconnected: cannot obtain value for tensor Tensor("input_39:0", shape=(?, 784), dtype=float32) at layer "input_39". The following previous layers were accessed without issue:
Could you please guide me how to get that part?
python tensorflow keras autoencoder
edited Nov 20 '18 at 6:41
Milo Lu
1,60311327
asked Nov 19 '18 at 21:33
AhmadAhmad
2,77333058
add a comment |
0
I have a model for an AutoEncoder as follows:
height, width = 28, 28
input_img = Input(shape=(height * width,))
encoding_dim = height * width//256
x = Dense(height * width, activation='relu')(input_img)
encoded1 = Dense(height * width//2, activation='relu')(x)
encoded2 = Dense(height * width//8, activation='relu')(encoded1)
y = Dense(encoding_dim, activation='relu')(encoded2)
decoded2 = Dense(height * width//8, activation='relu')(y)
decoded1 = Dense(height * width//2, activation='relu')(decoded2)
z = Dense(height * width, activation='sigmoid')(decoded1)
autoencoder = Model(input_img, z)
#encoder is the model of the autoencoder slice in the middle
encoder = Model(input_img, y)
decoder = Model(y, z)
print(encoder)
print(decoder)
The encoder part is retrived using the code above, however I can't get the decoder part using the code I added above:
I recieve the following error:
ValueError: Graph disconnected: cannot obtain value for tensor Tensor("input_39:0", shape=(?, 784), dtype=float32) at layer "input_39". The following previous layers were accessed without issue:
Could you please guide me how to get that part?
python tensorflow keras autoencoder
edited Nov 20 '18 at 6:41
Milo Lu
1,60311327
asked Nov 19 '18 at 21:33
AhmadAhmad
2,77333058
add a comment |
0
0
0
I have a model for an AutoEncoder as follows:
height, width = 28, 28
input_img = Input(shape=(height * width,))
encoding_dim = height * width//256
x = Dense(height * width, activation='relu')(input_img)
encoded1 = Dense(height * width//2, activation='relu')(x)
encoded2 = Dense(height * width//8, activation='relu')(encoded1)
y = Dense(encoding_dim, activation='relu')(encoded2)
decoded2 = Dense(height * width//8, activation='relu')(y)
decoded1 = Dense(height * width//2, activation='relu')(decoded2)
z = Dense(height * width, activation='sigmoid')(decoded1)
autoencoder = Model(input_img, z)
#encoder is the model of the autoencoder slice in the middle
encoder = Model(input_img, y)
decoder = Model(y, z)
print(encoder)
print(decoder)
The encoder part is retrived using the code above, however I can't get the decoder part using the code I added above:
I recieve the following error:
ValueError: Graph disconnected: cannot obtain value for tensor Tensor("input_39:0", shape=(?, 784), dtype=float32) at layer "input_39". The following previous layers were accessed without issue:
Could you please guide me how to get that part?
python tensorflow keras autoencoder
edited Nov 20 '18 at 6:41
Milo Lu
1,60311327
asked Nov 19 '18 at 21:33
AhmadAhmad
2,77333058
I have a model for an AutoEncoder as follows:
height, width = 28, 28
input_img = Input(shape=(height * width,))
encoding_dim = height * width//256
x = Dense(height * width, activation='relu')(input_img)
encoded1 = Dense(height * width//2, activation='relu')(x)
encoded2 = Dense(height * width//8, activation='relu')(encoded1)
y = Dense(encoding_dim, activation='relu')(encoded2)
decoded2 = Dense(height * width//8, activation='relu')(y)
decoded1 = Dense(height * width//2, activation='relu')(decoded2)
z = Dense(height * width, activation='sigmoid')(decoded1)
autoencoder = Model(input_img, z)
#encoder is the model of the autoencoder slice in the middle
encoder = Model(input_img, y)
decoder = Model(y, z)
print(encoder)
print(decoder)
The encoder part is retrived using the code above, however I can't get the decoder part using the code I added above:
I recieve the following error:
ValueError: Graph disconnected: cannot obtain value for tensor Tensor("input_39:0", shape=(?, 784), dtype=float32) at layer "input_39". The following previous layers were accessed without issue:
Could you please guide me how to get that part?
python tensorflow keras autoencoder
python tensorflow keras autoencoder
edited Nov 20 '18 at 6:41
Milo Lu
1,60311327
asked Nov 19 '18 at 21:33
AhmadAhmad
2,77333058
edited Nov 20 '18 at 6:41
Milo Lu
1,60311327
asked Nov 19 '18 at 21:33
AhmadAhmad
2,77333058
edited Nov 20 '18 at 6:41
Milo Lu
1,60311327
edited Nov 20 '18 at 6:41
Milo Lu
1,60311327
edited Nov 20 '18 at 6:41
Milo Lu
1,60311327
1,60311327
asked Nov 19 '18 at 21:33
AhmadAhmad
2,77333058
asked Nov 19 '18 at 21:33
AhmadAhmad
2,77333058
asked Nov 19 '18 at 21:33
AhmadAhmad
2,77333058
2,77333058
add a comment |
add a comment |
1 Answer
1
active
oldest
votes
1
The decoder Model needs to have an input layer. For example, the decoder_input here:
height, width = 28, 28
# Encoder layers
input_img = Input(shape=(height * width,))
encoding_dim = height * width//256
x = Dense(height * width, activation='relu')(input_img)
encoded1 = Dense(height * width//2, activation='relu')(x)
encoded2 = Dense(height * width//8, activation='relu')(encoded1)
y = Dense(encoding_dim, activation='relu')(encoded2)
# Decoder layers
decoder_input = Input(shape=(encoding_dim,))
decoded2 = Dense(height * width//8, activation='relu')(decoder_input)
decoded1 = Dense(height * width//2, activation='relu')(decoded2)
z = Dense(height * width, activation='sigmoid')(decoded1)
# Build the encoder and decoder models
encoder = Model(input_img, y)
decoder = Model(decoder_input, z)
# Finally, glue encoder and decoder together by feeding the encoder
# output to the decoder
autoencoder = Model(input_img, decoder(y))
answered Nov 19 '18 at 22:47
Kilian BatznerKilian Batzner
2,42311832
Thanks, but for the linedecoded2 = Dense(...)(decoder_input, it gives the errorfloat() argument must be a string or a number, not 'Dimension'
– Ahmad
Nov 20 '18 at 9:58
Sorry, I was testing the code withtf.kerasinstead ofkeras. I updated my answer, now it should work.
– Kilian Batzner
Nov 20 '18 at 10:14
add a comment |
Your Answer
StackExchange.ifUsing("editor", function () {
StackExchange.using("externalEditor", function () {
StackExchange.using("snippets", function () {
StackExchange.snippets.init();
});
});
}, "code-snippets");
StackExchange.ready(function() {
var channelOptions = {
tags: "".split(" "),
id: "1"
};
initTagRenderer("".split(" "), "".split(" "), channelOptions);
StackExchange.using("externalEditor", function() {
// Have to fire editor after snippets, if snippets enabled
if (StackExchange.settings.snippets.snippetsEnabled) {
StackExchange.using("snippets", function() {
createEditor();
});
}
else {
createEditor();
}
});
function createEditor() {
StackExchange.prepareEditor({
heartbeatType: 'answer',
autoActivateHeartbeat: false,
convertImagesToLinks: true,
noModals: true,
showLowRepImageUploadWarning: true,
reputationToPostImages: 10,
bindNavPrevention: true,
postfix: "",
imageUploader: {
brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
allowUrls: true
},
onDemand: true,
discardSelector: ".discard-answer"
,immediatelyShowMarkdownHelp:true
});
}
});
draft saved
draft discarded
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53382944%2fgetting-a-part-of-a-keras-model%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
1
The decoder Model needs to have an input layer. For example, the decoder_input here:
height, width = 28, 28
# Encoder layers
input_img = Input(shape=(height * width,))
encoding_dim = height * width//256
x = Dense(height * width, activation='relu')(input_img)
encoded1 = Dense(height * width//2, activation='relu')(x)
encoded2 = Dense(height * width//8, activation='relu')(encoded1)
y = Dense(encoding_dim, activation='relu')(encoded2)
# Decoder layers
decoder_input = Input(shape=(encoding_dim,))
decoded2 = Dense(height * width//8, activation='relu')(decoder_input)
decoded1 = Dense(height * width//2, activation='relu')(decoded2)
z = Dense(height * width, activation='sigmoid')(decoded1)
# Build the encoder and decoder models
encoder = Model(input_img, y)
decoder = Model(decoder_input, z)
# Finally, glue encoder and decoder together by feeding the encoder
# output to the decoder
autoencoder = Model(input_img, decoder(y))
answered Nov 19 '18 at 22:47
Kilian BatznerKilian Batzner
2,42311832
Thanks, but for the linedecoded2 = Dense(...)(decoder_input, it gives the errorfloat() argument must be a string or a number, not 'Dimension'
– Ahmad
Nov 20 '18 at 9:58
Sorry, I was testing the code withtf.kerasinstead ofkeras. I updated my answer, now it should work.
– Kilian Batzner
Nov 20 '18 at 10:14
add a comment |
1
The decoder Model needs to have an input layer. For example, the decoder_input here:
height, width = 28, 28
# Encoder layers
input_img = Input(shape=(height * width,))
encoding_dim = height * width//256
x = Dense(height * width, activation='relu')(input_img)
encoded1 = Dense(height * width//2, activation='relu')(x)
encoded2 = Dense(height * width//8, activation='relu')(encoded1)
y = Dense(encoding_dim, activation='relu')(encoded2)
# Decoder layers
decoder_input = Input(shape=(encoding_dim,))
decoded2 = Dense(height * width//8, activation='relu')(decoder_input)
decoded1 = Dense(height * width//2, activation='relu')(decoded2)
z = Dense(height * width, activation='sigmoid')(decoded1)
# Build the encoder and decoder models
encoder = Model(input_img, y)
decoder = Model(decoder_input, z)
# Finally, glue encoder and decoder together by feeding the encoder
# output to the decoder
autoencoder = Model(input_img, decoder(y))
answered Nov 19 '18 at 22:47
Kilian BatznerKilian Batzner
2,42311832
Thanks, but for the linedecoded2 = Dense(...)(decoder_input, it gives the errorfloat() argument must be a string or a number, not 'Dimension'
– Ahmad
Nov 20 '18 at 9:58
Sorry, I was testing the code withtf.kerasinstead ofkeras. I updated my answer, now it should work.
– Kilian Batzner
Nov 20 '18 at 10:14
add a comment |
1
1
1
The decoder Model needs to have an input layer. For example, the decoder_input here:
height, width = 28, 28
# Encoder layers
input_img = Input(shape=(height * width,))
encoding_dim = height * width//256
x = Dense(height * width, activation='relu')(input_img)
encoded1 = Dense(height * width//2, activation='relu')(x)
encoded2 = Dense(height * width//8, activation='relu')(encoded1)
y = Dense(encoding_dim, activation='relu')(encoded2)
# Decoder layers
decoder_input = Input(shape=(encoding_dim,))
decoded2 = Dense(height * width//8, activation='relu')(decoder_input)
decoded1 = Dense(height * width//2, activation='relu')(decoded2)
z = Dense(height * width, activation='sigmoid')(decoded1)
# Build the encoder and decoder models
encoder = Model(input_img, y)
decoder = Model(decoder_input, z)
# Finally, glue encoder and decoder together by feeding the encoder
# output to the decoder
autoencoder = Model(input_img, decoder(y))
answered Nov 19 '18 at 22:47
Kilian BatznerKilian Batzner
2,42311832
The decoder Model needs to have an input layer. For example, the decoder_input here:
height, width = 28, 28
# Encoder layers
input_img = Input(shape=(height * width,))
encoding_dim = height * width//256
x = Dense(height * width, activation='relu')(input_img)
encoded1 = Dense(height * width//2, activation='relu')(x)
encoded2 = Dense(height * width//8, activation='relu')(encoded1)
y = Dense(encoding_dim, activation='relu')(encoded2)
# Decoder layers
decoder_input = Input(shape=(encoding_dim,))
decoded2 = Dense(height * width//8, activation='relu')(decoder_input)
decoded1 = Dense(height * width//2, activation='relu')(decoded2)
z = Dense(height * width, activation='sigmoid')(decoded1)
# Build the encoder and decoder models
encoder = Model(input_img, y)
decoder = Model(decoder_input, z)
# Finally, glue encoder and decoder together by feeding the encoder
# output to the decoder
autoencoder = Model(input_img, decoder(y))
answered Nov 19 '18 at 22:47
Kilian BatznerKilian Batzner
2,42311832
edited Nov 20 '18 at 10:13
answered Nov 19 '18 at 22:47
Kilian BatznerKilian Batzner
2,42311832
answered Nov 19 '18 at 22:47
Kilian BatznerKilian Batzner
2,42311832
answered Nov 19 '18 at 22:47
Kilian BatznerKilian Batzner
2,42311832
2,42311832
Thanks, but for the linedecoded2 = Dense(...)(decoder_input, it gives the errorfloat() argument must be a string or a number, not 'Dimension'
– Ahmad
Nov 20 '18 at 9:58
Sorry, I was testing the code withtf.kerasinstead ofkeras. I updated my answer, now it should work.
– Kilian Batzner
Nov 20 '18 at 10:14
add a comment |
Thanks, but for the linedecoded2 = Dense(...)(decoder_input, it gives the errorfloat() argument must be a string or a number, not 'Dimension'
– Ahmad
Nov 20 '18 at 9:58
Sorry, I was testing the code withtf.kerasinstead ofkeras. I updated my answer, now it should work.
– Kilian Batzner
Nov 20 '18 at 10:14
Thanks, but for the line
decoded2 = Dense(...)(decoder_input, it gives the error float() argument must be a string or a number, not 'Dimension'– Ahmad
Nov 20 '18 at 9:58
Thanks, but for the line
decoded2 = Dense(...)(decoder_input, it gives the error float() argument must be a string or a number, not 'Dimension'– Ahmad
Nov 20 '18 at 9:58
Sorry, I was testing the code with
tf.keras instead of keras. I updated my answer, now it should work.– Kilian Batzner
Nov 20 '18 at 10:14
Sorry, I was testing the code with
tf.keras instead of keras. I updated my answer, now it should work.– Kilian Batzner
Nov 20 '18 at 10:14
add a comment |
draft saved
draft discarded
Thanks for contributing an answer to Stack Overflow!
- Please be sure to answer the question. Provide details and share your research!
But avoid …
- Asking for help, clarification, or responding to other answers.
- Making statements based on opinion; back them up with references or personal experience.
To learn more, see our tips on writing great answers.
draft saved
draft discarded
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53382944%2fgetting-a-part-of-a-keras-model%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
