Revision 0f9ce693bda1e6591173af4de60a2cfa610f4957 authored by Marie Roald on 06 June 2021, 08:48:42 UTC, committed by Marie Roald on 06 June 2021, 08:48:42 UTC
Only making the constrained factor matrices non-negative seemed to make the fitting procedure less stable (higher likelihood of all-zero components).
1 parent 5f08046
Makefile
# Automate testing etc
BACKEND?='numpy'
.PHONY: all test install clean debug
all: install test
install:
pip install -e .
debug:
TENSORLY_BACKEND=$(BACKEND) pytest -v --pdb tensorly
test:
TENSORLY_BACKEND=$(BACKEND) pytest -v tensorly
test-all:
TENSORLY_BACKEND='numpy' pytest -v tensorly
TENSORLY_BACKEND='cupy' pytest -v tensorly
TENSORLY_BACKEND='pytorch' pytest -v tensorly
TENSORLY_BACKEND='mxnet' pytest -v tensorly
TENSORLY_BACKEND='jax' pytest -v tensorly
TENSORLY_BACKEND='tensorflow' pytest -v tensorly
test-coverage:
TENSORLY_BACKEND=$(BACKEND) pytest -v --cov tensorly tensorly
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