logo
Tags down

shadow

Tuning number of hidden layers in Keras


By : Tony
Date : October 16 2020, 06:10 PM
I wish this help you I'm just trying to explore keras and tensorflow with the famous MNIST dataset. I already applied some basic neural networks, but when it comes to tuning some hyperparameters, especially the number of layers, thanks to the sklearn wrapper GridSearchCV, I get the error below: , You should add:
code :
for i in range(int(hidden_layers)):
    # Add one hidden layer
    model.add(Dense(16, activation=activation))
params_grid={"hidden_layers": [3]}


Share : facebook icon twitter icon

Which layers should I freeze for fine tuning a resnet model on keras?


By : Franco Narciso Romer
Date : March 29 2020, 07:55 AM
I wish did fix the issue. I think that there is no a state of the art strategy for this but I may share you my thoughts on this topic (names of layers are similar to these presented here:

hpneural parameter tuning - variable number of hidden layers (in do loop)


By : Tyrnavan Janne
Date : March 29 2020, 07:55 AM
this one helps. In your second macro use a %do loop to emit the desired source code. In the first macro use a macro invocation instead of a macro variable resolution
code :
%macro hidden_layers (layers=, neurons=);

  %local i;
  %do i = 1 %to &layers;
    hidden &neurons;   /* macro will emit this source code &layer times */
  %end;

%mend;
            … 
            target MSRP / level=int;
            hidden &neurons.;
            train outmodel=model_neural_network maxiter=1000
            … 
            target MSRP / level=int;
            %hidden_layers (3, &neurons)
            train outmodel=model_neural_network maxiter=1000
%macro build_predictions
  %do neurons = 1 % to 10;
        proc hpneural data=train;
            input Make -- Horsepower / level=nom;
            target MSRP / level=int;

            %local index;
            %do index = 1 %to 3; hidden &neurons.; %end;

            train outmodel=model_neural_network maxiter=1000;
        run;
        …
    %end; %* neurons loop;
%mend;

Setting the hidden state for each minibatch with different hidden sizes and multiple LSTM layers in Keras


By : Patrick
Date : March 29 2020, 07:55 AM
To fix the issue you can do States in LSTM
An LSTM is made up of gates which calculate the cell state and hidden state.
code :
batch_size = 2
num_steps = 5
num_input = num_output = 1
hidden_size = 8

inputs = Input(batch_shape=(batch_size,num_steps, num_input))
lstm, state_h, state_c = LSTM(hidden_size, return_state=True, return_sequences=True)(inputs)
model = Model(inputs=inputs, outputs=[state_h, state_c])

print (model.predict(np.zeros((batch_size, num_steps, num_input))))
print (model.layers[1].cell.state_size)
 print (model.layers[0].states[0], hex(id(model.layers[0].states[0])))
 model.layers[0].states[0]= K.variable(np.random.randn(10,2))
 print (model.layers[0].states[0], hex(id(model.layers[0].states[0])))
<tf.Variable 'lstm_18/Variable:0' shape=(10, 8) dtype=float32_ref> 0x7f8812e6ee10
<tf.Variable 'Variable_2:0' shape=(10, 2) dtype=float32_ref> 0x7f881269afd0
 print (model.layers[0].states[0], hex(id(model.layers[0].states[0])))
 K.set_value(model.layers[0].states[0], np.random.randn(10,8))
 print (model.layers[0].states[0], hex(id(model.layers[0].states[0])))
<tf.Variable 'lstm_20/Variable:0' shape=(10, 8) dtype=float32_ref> 0x7f881138eb70
<tf.Variable 'lstm_20/Variable:0' shape=(10, 8) dtype=float32_ref> 0x7f881138eb70
K.set_value(model.layers[0].states[0], np.random.randn(10,2))

Grid Search the number of hidden layers with keras


By : sameera
Date : March 29 2020, 07:55 AM
Hope this helps If you want to make the number of hidden layers a hyperparameter you have to add it as parameter to your KerasClassifier build_fn like:
code :
def create_model(optimizer='adam', activation = 'sigmoid', hidden_layers=1):
  # Initialize the constructor
  model = Sequential()
  # Add an input layer
  model.add(Dense(5, activation=activation, input_shape=(5,)))

  for i in range(hidden_layers):
      # Add one hidden layer
      model.add(Dense(8, activation=activation))

  # Add an output layer 
  model.add(Dense(1, activation=activation))
  #compile model
  model.compile(loss='binary_crossentropy', optimizer=optimizer, metrics=
  ['accuracy'])
  return model

Neural network tuning number of hidden layers using grid search


By : Michael
Date : March 29 2020, 07:55 AM
Related Posts Related Posts :
  • Python hex string encoding
  • Get week start date from week number
  • How to use imports from requirements.txt in python
  • Removing tab indent in ipython shell
  • I need to remove duplicates from a list but add the numeric value in them
  • Delay default arguments being read until function is called
  • Interpolate / fillna with a decay formula in pandas
  • What python package can translate Greek letter to ASCII requivalent?
  • How to get output of OS command from Jupyter notebook?
  • Printing AND writing the RIGHTLY formatted number
  • How do I create a shortcut to import most used python modules?
  • Matplotlib: Show selected date labels on x axis
  • Understanding memoization in Python
  • why does the len function return 2 on some iterations when they are all the same length?
  • Change in preference value does not affect the results of Affinity propagation Clustering
  • returning values inside a function
  • Why cant I use a variable in str slicing?
  • Section divider in Spyder
  • Conditional statement in selenium if element does not exists
  • Pandas : how to select index/row label in dataframe that matches a condition
  • What does zero do in A[0] in this code? Why not empty or another number?
  • Google App Engine urlfetch PayloadTooLargeError: Request exceeds 10 MiB limit for URL
  • Is there a way to set up optional arguments to bypass input arguments?
  • Suppress OpenMP debug messages when running Tensorflow on CPU
  • How to do GridSearchCV for F1-score in classification problem with scikit-learn?
  • Why does .pop() eventually stop and not keep removing items from a list until the list is empty?
  • How do I acess my Spider data from my main.py script?
  • Python Pandas Expand a Column of List of Lists to Two New Column
  • Overhead of python multiprocessing initialization is worse than benefits
  • Python Joining List and adding and removing characters
  • Adding an lxml library to project
  • Concatenating tensors in Tensorflow with None axis
  • Need help understanding why i get attribute error
  • How to force a MIDI device to report control status?
  • What does *** mean in Python -3?
  • How to get GFCC instead of MFCC in python?
  • How do I print a number n times in python?
  • How do i split a string wherever there are digits?
  • List Comprehension Python Prime numbers
  • "list index out of range" when reading data from file
  • What's the correct datetime format for the specified date string?
  • I cannot import CSV file?
  • Matplotlib pyplot plots look different after calling pandas profiling. How can I fix this?
  • Stopping all the instances of a specific region
  • Deal with Birtish summer time
  • Unable to use ColorWheel without loading kv (AttributeError)
  • What are these characters called: 。. !?etc Trying to split sentences stops working with non standard characters
  • rand.randint returning same number over and over?
  • Find longest sequence that does not contain a certain number
  • How do I convert a map object to list and also assign to a variable
  • sympy error: 'Symbol' object has no attribute 'pi'
  • How to remove words without vowels from a list in python
  • Downloading python to macbook
  • TypeError: __init__() missing 1 required positional argument: 'units'
  • Check if a class is a dataclass in Python
  • Unable to scrape google news heading via their class
  • Array of structs with dynamic allocation runs very slow in C in comparison to Python
  • Python Pandas - find all unique combinations of rows of a DataFrame without repeating values in the columns
  • How do I change the numbers in a cell to the word 'Bus' in Pandas Python
  • 'ascii' codec can't encode character : ordinal not in range (128)
  • shadow
    Privacy Policy - Terms - Contact Us © 35dp-dentalpractice.co.uk