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I"m running into this error:
ValueError: You are trying to load a weight file containing 532 layers into a model with 526 layers.
My keras version is:
`>>> keras.__version__
'2.2…
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My code is:
m = NASNetLarge(include_top=False,weights='imagenet',input_shape=(224,224,3))
But this line of code gives me this error:
ValueError: When setting`include_top=True` and loading `…
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@tensorflow/micro
**System information**
- Windows 10
- tensorflow install from pip
- tensorflow: 2.1.0
- traget platform : I run simply on windows
**Describe the problem**
I made app like…
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**System information**
- Have I written custom code (as opposed to using example directory): yes
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Linux Ubuntu 16.04
- TensorFlow backe…
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Initializing MobileNet for small dimensions of input_shape fails with unclear error messages
Running
```python
from keras.applications.mobilenet import MobileNet
model = MobileNet(weights='imagene…
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I used code below to combine 2 mobile-net model. After combine i save model as combined.hdf5.
Keras version: 2.2.0 Using TensorFlow backend.
TensorFlow version: 1.8.0
```
model_A = load_model('mob…
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@fchollet Is there any interest in the addition of NASNet models to Keras Applications?
Based on the paper [Learning Transferable Architectures for Scalable Image Recognition](https://arxiv.org/abs…
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Hello,
I am facing the specified error with the following config :
OS : Ubuntu 18.04
Tensorflow: 1.15.04
Keras : 2.3.1
JSON:
```
{
"model" : {
"type": "Classi…
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Hello everyone, i have been running various experiments using the parameter-server strategy for distributed tensorflow. My shows uneven distribution on workload for parameter servers replicas (some …