&gt; Edit: Starting from **1.52** it&#39;s possible from keybindings GUI:

[![keybindings gui context menu add keybinding][1]][1]

---

What stops you from editing `keybindings.json`?

&lt;!-- language: lang-json --&gt;

    {
    	&quot;key&quot;: &quot;left&quot;,
    	&quot;command&quot;: &quot;cursorLeft&quot;,
    	&quot;when&quot;: &quot;textInputFocus&quot;
    },
    {
        &quot;key&quot;: &quot;alt+a&quot;,
        &quot;command&quot;: &quot;cursorLeft&quot;
    }

It can be opened from Command Palette `Preferences: Open Keyboard Shortcuts (JSON)`

Or by clicking the file icon from keybindings GUI page:

[![enter image description here][2]][2]


  [1]: https://i.stack.imgur.com/H5CVb.png
  [2]: https://i.stack.imgur.com/KzWNR.png

Updating the previous answer and adding tiny more details, atleast in the current 2020 version it seems like after changing the keybindings (atleasy cursor up &amp; down), VSCode creates an entry in the JSON file that can be accessed from Alex&#39;s answer. The JSON will contain the new entry you made but also the changed entry with a &#39;-&#39; negative sign on the key instruction. Just remove the &#39;-&#39; negative sign and both your keybindings should work like a charm! Obviously don&#39;t forget to save!

I have a model that I&#39;ve trained for 40 epochs. I kept checkpoints for each epochs, and I have also saved the model with `model.save()`. The code for training is:

    n_units = 1000
    model = Sequential()
    model.add(LSTM(n_units, input_shape=(None, vec_size), return_sequences=True))
    model.add(Dropout(0.2))
    model.add(LSTM(n_units, return_sequences=True))
    model.add(Dropout(0.2))
    model.add(LSTM(n_units))
    model.add(Dropout(0.2))
    model.add(Dense(vec_size, activation=&#39;linear&#39;))
    model.compile(loss=&#39;mean_squared_error&#39;, optimizer=&#39;adam&#39;)
    # define the checkpoint
    filepath=&quot;word2vec-{epoch:02d}-{loss:.4f}.hdf5&quot;
    checkpoint = ModelCheckpoint(filepath, monitor=&#39;loss&#39;, verbose=1, save_best_only=True, mode=&#39;min&#39;)
    callbacks_list = [checkpoint]
    # fit the model
    model.fit(x, y, epochs=40, batch_size=50, callbacks=callbacks_list)

However, when I load the model and try training it again, it starts all over as if it hasn&#39;t been trained before. The loss doesn&#39;t start from the last training.

What confuses me is when I load the model and redefine the model structure and use `load_weight`, `model.predict()` works well. Thus, I believe the model weights are loaded:

    model = Sequential()
    model.add(LSTM(n_units, input_shape=(None, vec_size), return_sequences=True))
    model.add(Dropout(0.2))
    model.add(LSTM(n_units, return_sequences=True))
    model.add(Dropout(0.2))
    model.add(LSTM(n_units))
    model.add(Dropout(0.2))
    model.add(Dense(vec_size, activation=&#39;linear&#39;))
    filename = &quot;word2vec-39-0.0027.hdf5&quot;
    model.load_weights(filename)
    model.compile(loss=&#39;mean_squared_error&#39;, optimizer=&#39;adam&#39;)

However, When I continue training with this, the loss is as high as the initial stage:

    filepath=&quot;word2vec-{epoch:02d}-{loss:.4f}.hdf5&quot;
    checkpoint = ModelCheckpoint(filepath, monitor=&#39;loss&#39;, verbose=1, save_best_only=True, mode=&#39;min&#39;)
    callbacks_list = [checkpoint]
    # fit the model
    model.fit(x, y, epochs=40, batch_size=50, callbacks=callbacks_list)

I searched and found some examples of saving and loading models [here][1] and [here][2]. However, none of them work.

---

**Update 1**

I looked at [this question][3], tried it and it works: 

    model.save(&#39;partly_trained.h5&#39;)
    del model
    load_model(&#39;partly_trained.h5&#39;)

But when I close Python and reopen it, then run `load_model` again, it fails. The loss is as high as the initial state.

---

**Update 2**

I tried [Yu-Yang&#39;s example code][4] and it works. However, when I use my code again, it still failed.

This is result form the original training. The second epoch should start with loss = 3.1***:

    13700/13846 [============================&gt;.] - ETA: 0s - loss: 3.0519
    13750/13846 [============================&gt;.] - ETA: 0s - loss: 3.0511
    13800/13846 [============================&gt;.] - ETA: 0s - loss: 3.0512Epoch 00000: loss improved from inf to 3.05101, saving model to LPT-00-3.0510.h5
    
    13846/13846 [==============================] - 81s - loss: 3.0510    
    Epoch 2/60
    
       50/13846 [..............................] - ETA: 80s - loss: 3.1754
      100/13846 [..............................] - ETA: 78s - loss: 3.1174
      150/13846 [..............................] - ETA: 78s - loss: 3.0745

I closed Python, reopened it, loaded the model with `model = load_model(&quot;LPT-00-3.0510.h5&quot;)` then train with:

    filepath=&quot;LPT-{epoch:02d}-{loss:.4f}.h5&quot;
    checkpoint = ModelCheckpoint(filepath, monitor=&#39;loss&#39;, verbose=1, save_best_only=True, mode=&#39;min&#39;)
    callbacks_list = [checkpoint]
    # fit the model
    model.fit(x, y, epochs=60, batch_size=50, callbacks=callbacks_list)

The loss starts with 4.54:

    Epoch 1/60
       50/13846 [..............................] - ETA: 162s - loss: 4.5451
       100/13846 [..............................] - ETA: 113s - loss: 4.3835


  [1]: http://machinelearningmastery.com/save-load-keras-deep-learning-models/
  [2]: https://github.com/fchollet/keras/issues/1872
  [3]: https://stackoverflow.com/questions/42666046/loading-a-trained-keras-model-and-continue-training
  [4]: https://stackoverflow.com/a/45428197/5305519

Keras: How to save model and continue training?

I&#39;m using the React 16 beta (react-fiber) with server side rendering

What I am to understand this to mean?

    warning.js:36 Warning: Did not expect server HTML to contain a &lt;div&gt; in &lt;div&gt;.



React 16 warning &quot;warning.js:36 Warning: Did not expect server HTML to contain a &lt;div&gt; in &lt;div&gt;.&quot;

Is there any way to set two keyboard shortcuts for one action in VS code? For example, I want to move the cursor to the left by pressing left arrow key or &lt;kbd&gt;Alt&lt;/kbd&gt;+&lt;kbd&gt;A&lt;/kbd&gt;.

Visual Studio Code - multiple keyboard shortcuts?

<p>Is there any way to set two keyboard shortcuts for one action in VS code? For example, I want to move the cursor to the left by pressing left arrow key or <kbd>Alt</kbd>+<kbd>A</kbd>.</p>


See the image below. My .gitignore file should be ignoring all files in src/dist, but isn&#39;t.

[![enter image description here][1]][1]


  [1]: https://i.stack.imgur.com/1qVzG.png

Why is .gitignore not ignoring my files?

I&#39;m using Visual Studio Code 1.14.2, and I&#39;m trying to change name of variables to camelCase eg.
`set_nominal_wavelength` to `setNominalWavelength`.

Regular expression: `_([a-z])`

Replace: `\U$1\E`

does not work. Any idea how to achieve it?

How to change lower case to upper using regular expressions in Visual Studio Code

I want to show references count in Visual Studio Code. How can I do it?

[![Enter image description here][1]][1]

  [1]: https://i.stack.imgur.com/rbwem.png


How do I show reference count in Visual Studio Code?

Here&#39;s an example of my `tasks.json`:

    {
      &quot;version&quot;: &quot;0.1.0&quot;,
      &quot;tasks&quot;: [
        {
          &quot;taskName&quot;: &quot;test&quot;,
          &quot;suppressTaskName&quot;: true,
          &quot;command&quot;: &quot;python&quot;,
          &quot;args&quot;: [
            &quot;tests/brewer_tests.py&quot;
          ],
          &quot;isTestCommand&quot;: true
        }
      ]
    }

I can run this with `shift+cmd+alt+b`. I can also run it with `alt+t`, and choose it from the menu. Is it possible to pass additional arguments in that menu? e.g.
[![enter image description here][1]][1]


  [1]: https://i.stack.imgur.com/Lg4cA.png

And you could build it into your task like so:

    {
      &quot;version&quot;: &quot;0.1.0&quot;,
      &quot;tasks&quot;: [
        {
          &quot;taskName&quot;: &quot;test&quot;,
          &quot;suppressTaskName&quot;: true,
          &quot;command&quot;: &quot;python&quot;,
          &quot;args&quot;: [
            &quot;tests/brewer_tests.py&quot;,
            $arg1                        # would resolve to &quot;ARG1&quot;
          ],
          &quot;isTestCommand&quot;: true
        }
      ]
    }
Or something similar?

Is it possible to pass arguments to a task in Visual Studio Code

I am using Visual Studio Code in my C++ project. I installed *Microsoft C/C++ Extension for VS Code*. I got the following error:
&gt; \#include errors detected. Please update your includePath. IntelliSense features for this translation unit (`/path/to/project/file.cpp`) will be provided by the Tag Parser.


Content Type	Original Author	Original Content on Stackoverflow
Question	Younghoon Jeong	View Question on Stackoverflow
Solution 1 - Visual Studio-Code	Alex	View Answer on Stackoverflow
Solution 2 - Visual Studio-Code	Yashank	View Answer on Stackoverflow

Visual Studio Code - multiple keyboard shortcuts?

Visual Studio-Code Problem Overview

Visual Studio-Code Solutions

Solution 1 - Visual Studio-Code

Solution 2 - Visual Studio-Code

React 16 warning "warning.js:36 Warning: Did not expect server HTML to contain a <div> in <div>."

Keras: How to save model and continue training?

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