Save and load weights in keras

Question

Im trying to save and load weights from the model i have trained.

the code im using to save the model is.

TensorBoard(log_dir='/output')
model.fit_generator(image_a_b_gen(batch_size), steps_per_epoch=1, epochs=1)
model.save_weights('model.hdf5')
model.save_weights('myModel.h5')

Let me know if this an incorrect way to do it,or if there is a better way to do it.

but when i try to load them,using this,

from keras.models import load_model
model = load_model('myModel.h5')

but i get this error:

ValueError                                Traceback (most recent call 
last)
<ipython-input-7-27d58dc8bb48> in <module>()
      1 from keras.models import load_model
----> 2 model = load_model('myModel.h5')

/home/decentmakeover2/anaconda3/lib/python3.5/site-
packages/keras/models.py in load_model(filepath, custom_objects, compile)
    235         model_config = f.attrs.get('model_config')
    236         if model_config is None:
--> 237             raise ValueError('No model found in config file.')
    238         model_config = json.loads(model_config.decode('utf-8'))
    239         model = model_from_config(model_config, 
custom_objects=custom_objects)

ValueError: No model found in config file.

Any suggestions on what i may be doing wrong? Thank you in advance.

User · Answer

For loading weights  you need to have a model first  It must be   existingModel save weights  weightsfile h5   existingModel load weights  weightsfile h5          If you want to save and load the entire model  this includes the model s configuration  it s weights and the optimizer states for further training    model save model  filename   model   load model  filename

User · Answer

Here is a YouTube video that explains exactly what you re wanting to do  Save and load a Keras model  There are three different saving methods that Keras makes available  These are described in the video link above  with examples   as well as below    First  the reason you re receiving the error is because you re calling load model incorrectly   To save and load the weights of the model  you would first use   model save weights  my model weights h5     to save the weights  as you ve displayed  To load the weights  you would first need to build your model  and then call load weights on the model  as in  model load weights  my model weights h5     Another saving technique is model save filepath   This save function saves    The architecture of the model  allowing to re-create the model  The weights of the model  The training configuration  loss  optimizer   The state of the optimizer  allowing to resume training exactly where you left off    To load this saved model  you would use the following   from keras models import load model new model   load model filepath     Lastly  model to json    saves only the architecture of the model  To load the architecture  you would use   from keras models import model from json model   model from json json string

User · Answer

Since this question is quite old  but still comes up in google searches  I thought it would be good to point out the newer  and recommended  way to save Keras models  Instead of saving them using the older h5 format like has been shown before  it is now advised to use the SavedModel format  which is actually a dictionary that contains both the model configuration and the weights   More information can be found here  https   www tensorflow org guide keras save and serialize  The snippets to save  amp  load can be found below   model fit test input  test target    Calling save  my model   creates a SavedModel folder  my model   model save  my model      It can be used to reconstruct the model identically  reconstructed model   keras models load model  my model     A sample output of this

[python] Save and load weights in keras

The answer is

Examples related to python

Examples related to keras

Tags