Description
Quickstart training procedure as described in Docs throws AttributeError.
AttributeError: module 'numpy' has no attribute 'float'.
np.float was a deprecated alias for the builtin float. To avoid this error in existing code, use float by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64 here.
The aliases was originally deprecated in NumPy 1.20;
Reproduce
Run tranining procedure with nlu_engine.fit() on virtenv with python 3.8 and numbpy == > 1.20.
`import io
import json
from snips_nlu import SnipsNLUEngine
with io.open() as f:
sample_dataset = json.load(f)
nlu_engine = SnipsNLUEngine()
nlu_engine.fit(sample_dataset)
parsing = nlu_engine.parse("Whats the weather today in Tokyo?")
print(json.dumps(parsing, indent=2))`
Expected behavior
Output json as described in the docs quickstart.
If run with numbpy == < 1.20 output is generated as expected.
Environment:
- OS: MacOS 12.6.3
- python version: 3.8
- snips-nlu version: 0.20.2
Description
Quickstart training procedure as described in Docs throws AttributeError.
Reproduce
Run tranining procedure with nlu_engine.fit() on virtenv with python 3.8 and numbpy == > 1.20.
`import io
import json
from snips_nlu import SnipsNLUEngine
with io.open() as f:
sample_dataset = json.load(f)
nlu_engine = SnipsNLUEngine()
nlu_engine.fit(sample_dataset)
parsing = nlu_engine.parse("Whats the weather today in Tokyo?")
print(json.dumps(parsing, indent=2))`
Expected behavior
Output json as described in the docs quickstart.
If run with numbpy == < 1.20 output is generated as expected.
Environment: