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[For discussion] Add testcase for AutoHoot taco doing the right job #246

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[For discussion] Add testcase for AutoHoot taco doing the right job #246

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23 changes: 23 additions & 0 deletions tests/sparse_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -73,3 +73,26 @@ def test_sparse_einsum_graph():
expected_yval = T.einsum("ab,bc->ac", x1_val, x2_val)
assert float_eq(y_val, expected_yval)
assert isinstance(y_val, pt.pytensor.taco_tensor.tensor)


def test_sparse_optimize():

T.set_backend("taco")
size = 1000
coo = formats.SparseFormat([formats.compressed, formats.compressed])

X = ad.Variable(name="X", shape=[size, size], format=coo)
A = ad.Variable(name="A", shape=[size, size])
B = ad.Variable(name="B", shape=[size, size])
y = ad.einsum('ij,is,js->ij', X, A, B, out_format=coo)
executor = ad.Executor([y])

X_val = T.random([size, size], format='coo', density=0.1)
B_val = T.random([size, size])
A_val = T.random([size, size])

y_val, = executor.run(feed_dict={A: A_val, B: B_val, X: X_val}, debug=True)

expected_yval = T.einsum("ij, is, js->ij", X_val, A_val, B_val)
assert float_eq(y_val, expected_yval)
assert isinstance(y_val, pt.pytensor.taco_tensor.tensor)