v.0.6.3 to Master #384
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v.0.6.3 to Master #384
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v.0.6 to Dev
v.0.6.2 to Dev
backward compatibility merge daily-dev << master
- cleaned up Scan() namespace - added one example to docs
…ement - `experiment_name` is now compulsory - Addresses #207 and prepare for browser based "command center" - Added 'trees' reduction strategy - Added 'forrest' reduction strategy - added `scan_utils.py` as a home for helper functions for /scan - fixed tests to handle the new changes
This is used in one of the examples in docs, which is now also corrected.
- invoked through `reduction_method='gamify'` - checks and updates a parameter map in the experiment folder each permutation - if parameter value status is changed to 'inactive' in the .json locally, then reduction will be applied (all permutations with that value will be removed) - Related with this, check out http://github.com/autonomio/gamify ... an add-on for live monitoring of experiments and analysis of experiment results, with coming features for controlling the experiment as well
- Related with #343 it's now possible to avoid saving model weights in `scan_object`, which might be desirable for very long runs with very large networks, due to the memory cost of keeping the weights throughout the experiment. - fixed a small bug in `AutoParams` where choosing `network=False` resulted in 'dense' to be split into characters - `max_param_values` is now optional in `AutoScan` and instead created the issue to handle the underlying problem properly #367 - fixed all the tests accordingly to the change in `AutoScan` arguments
- improved PR template - improved issue template - created feature request template - created bugs template - Actually added the `Scan(...save_weights=False...)` (this slipped through the cracks last night) - Added `Scan(...save_weights=False...)` to tests
- changed the deploy test so local folder does not end up with garbage
...and more small fixes on the templates.
- Also fixes #367 (setting 4 per paramater as the default for automatic mode)
This will be added to docs later, but for now bare in mind that in order to have some metric stored in Talos experiment log, you have to use talos.utils.TorchHistory and use it like so:
Before the epoch iteration loop starts:
`history = History() # NOTE: this is required by Talos`
Then for example:
```
for epoch in range(params['epochs']):
optimizer.zero_grad()
out = model(x_train)
loss = criterion(out, y_train)
loss.backward()
optimizer.step()
print(out == out.data.max())
history.append(loss) # NOTE: this is required by Talos
```
Also...
- fixed some issues in AutoModel
- added a couple of initializers to AutoParams
v.0.6.3 to Dev (actual)
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Hello @mikkokotila! Thanks for opening this PR. We checked the lines you've touched for PEP 8 issues, and found:
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Pull Request Test Coverage Report for Build 561
💛 - Coveralls |
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