https://github.com/breuleux/myia_debug
Debugging tools for Myia
https://github.com/breuleux/myia_debug
Last synced: about 1 month ago
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Debugging tools for Myia
- Host: GitHub
- URL: https://github.com/breuleux/myia_debug
- Owner: breuleux
- Created: 2018-06-11T18:41:44.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2019-04-01T21:58:09.000Z (about 6 years ago)
- Last Synced: 2025-04-14T20:09:05.107Z (about 1 month ago)
- Language: Python
- Size: 35.2 KB
- Stars: 1
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# myia_debug
Utility to debug Myia.
You can call this with ` python -m myia_debug `, or alias `python -m myia_debug` to a shortcut like `dm`.
```
Debug Myia
Usage:
dm
[-f FUNCTION...] [-a ARG...] [-g...]
[-t TYPE...]
[--shapes SHAPE...]
[-O OPT...]
[--config FILE...]
[--pipeline PIP...]
[--scalar]
[--no-beautify]
[--function-nodes]
[...]
Options:
-f --fn FUNCTION... The function to run.
-a --args ARG... Arguments to feed to the function.
-g Apply gradient once for each occurrence of the flag.
-t --types TYPE... Types of the arguments.
--shapes SHAPE... Shapes of the arguments.
-c --config FILE... Use given configuration.
-O --opt OPT... Run given optimizations.
-p --pipeline PIP... The pipeline to use.
--scalar Use the scalar pipeline.
--no-beautify Don't beautify graphs.
--function-nodes Show individual nodes for functions called.
```
This requires `buche` to be installed: https://github.com/breuleux/buche/releases
The value for most arguments and options can be of the form `module:variable`,
in which case the corresponding module is imported and the variable is read
from it. Multiple values for arguments or types are separated by either `,` or
`;`.
The `-g` flag doesn't do anything right now.
## Examples
Suppose `x.py` contains the following code:
```python
import numpy
x1 = 4
x2 = 8.5
x3 = numpy.random.random((4, 6))
def hibou(x, y):
return x + y
```
Running the function on test inputs:
```
dm run x:hibou --args 4,7
dm run x:hibou --args x:x1,x:x2
dm run x:hibou --args x:x2,x:x3
```
Showing the graph.
```
buche dm show x:hibou
buche dm show x:hibou --pipeline parse,resolve,infer,specialize,opt --types i64,i64
buche dm show x:hibou --pipeline '!opt' --types i64,i64
buche dm show x:hibou --pipeline '!opt' --args x:x2,x:x3
buche dm show x:hibou --pipeline '!opt' --types i64,i64 -O inline
```
The `!opt` pipeline is the same as `parse,resolve,infer,specialize,opt`.
There is also a `cconv` step.
## Custom operations
Suppose `y.py` contains the following code:
```python
from myia_debug import steps
def inferred(o):
res = o.run(default=[steps.parse,
steps.infer,
steps.specialize])
if 'error' in res:
raise res['error']
print(res['inference_results'])
```
Then you can run this, and it will print the inference results:
```
dm y:inferred x:hibou --args x:x2,x:x3
```
The call to `o.run` handles most parameters for you, so you can provide
types, shapes, and customize the pipeline.