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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 
Reverted back so all factor matrices are initialised non-negative
 
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
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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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