deeptrain | Full knowledge and control of the train state | Graph Database library
kandi X-RAY | deeptrain Summary
kandi X-RAY | deeptrain Summary
Full knowledge and control of the train state.
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Top functions reviewed by kandi - BETA
- Calculate gradient l2 - norm
- Gather data over a given function
- Get scales from environment variable
- Set size of matplotlib figure
- Load a configuration file
- Apply callbacks to the given stage
- Loads the optimizer state
- Write data to HDF5 file
- Check if a file exists
- Destroy the train generator
- Decorator for capturing arguments
- Gets the scales from the environment variable
- Create autoencoder
- Compute metrics
- Transform labels and preds
- Interrupt training
- Write a 2D numpy array to a csv file
- Process command line arguments
- Generate name for name processing
- Computes gradient sum over dataset
- Convert numpy arrays to numpy sets
- Save the attributes of the generator
- Create a function that returns the default name processor
- Infer the data from the data and set it
- Validate set_nums
- Convert numpy array to lz4f compressed
- Train the model
deeptrain Key Features
deeptrain Examples and Code Snippets
Community Discussions
Trending Discussions on deeptrain
QUESTION
make html
and sphinx-build 'source' 'build\html' -a -E
give the same results; an .rst
file in docs/source
I modified is being overridden when I add to :exclude-members:
here, generating docs with said member present. Same behavior if simply wiping the entire .rst file clean; seems like the changes are being ignored entirely, and Sphinx is using some cached .rst
's instead (despite -a -E
).
I don't recall having to do anything other than make html
. I also tried preceding with make clean
, and commenting out an app.connect
which was noted to be potentially unstable. Is there some command to make Sphinx use the current .rst
files?
ANSWER
Answered 2020-Jun-17 at 17:51You are editing .rst.txt
files in build
, which are what's generated by Sphinx by reading .rst
in source
. Big brain.
QUESTION
:data:`~package._module._DICT_NAME`
...ANSWER
Answered 2020-Jun-07 at 02:07Before trying to reference _DICT_NAME
verify it's been put in the general index (and thus became cross-referenceable!!). If using an autodoc directive without :undoc-members:
option the dictionary won't be include if it doesn't have a comment. Variables can't have docstrings, so you need to use a comment #:
before or """
immediately after, in the py
for autodoc to pick it up.
Unless you are explicitly including the dictionary in the .rst
with py:data:
, using Domains and roles. Or, by including it in the .rst
(using autodata or autoattribute, in case your automodule
or autoclass
doesn't pick it up and you're using directives of the autodoc extension.
Then your _DICT_NAME
is also a private variable, so you need to check the conf.py
settings to see if it's included like napoleon_include_private_with_doc = True
, if you're using Sphinx Napoleon extension.
_DICT_NAME is rendered as if referenced, but no hyperlink.
First check that it shows up documented in the final rendering of you documentation be it HTML or other. If it is included and has a comment it can be then be cross-referenced and the link will be generated.
How to reference a dict with sphinx-autodoc?
Notice you aren't referencing with autodoc. Autodoc is extracting the docstring where you write its directive in your .rst
. Your :data:
cross-referencing is done by domain and roles. Although you can have referencing inside your docstring that is afterwards extracted by autodoc and finally rendered, altogether, by the Sphinx tool.
EDIT after OP added MCVE:
First problem I see is this, your dictionary _DEFAULT_TRAINGEN_CFG
is in module _default_configs.py
...
So, the cross-reference you wrote should be right :data:~deeptrain.util._default_configs._DEFAULT_TRAINGEN_CFG\
....BUT, did you actually include this module in any .rst
file? I don't think so, looking at deeptrain.util.rst the _default_configs.py
module is not present in any automodule
directive, so there's nothing to reference (that's why the hyperlink isn't generated)...
Three examples of cross-references:
A module level dictionary, dict_document.py
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Install deeptrain
To run, DeepTrain requires (1) a compiled model; (2) data directories (train & val). Below is a minimalistic example. Checkpointing, visualizing, callbacks & more can be accomplished via additional arguments; see Basic and Advanced examples. Also see Recommended Usage.
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