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add float32 testing

This commit is contained in:
zhujingxuan 2021-11-29 10:52:03 +08:00
parent 745c1eaff8
commit 2aa8dc28cf
1 changed files with 26 additions and 15 deletions
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41
tests/st/scipy_st/sparse/test_linalg.py
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@ -110,32 +110,34 @@ def test_cg_against_numpy(dtype, shape):
onp.testing.assert_allclose(expected, actual_sta.asnumpy(), **kw)
def gmres_compare_with_scipy_incremental(A, b, x, M):
gmres_x, _ = msp.sparse.linalg.gmres(Tensor(A), Tensor(b), Tensor(
x), tol=1e-07, atol=0, solve_method='incremental')
scipy_x, _ = osp.sparse.linalg.gmres(A, b, x, tol=1e-07, atol=0)
onp.testing.assert_almost_equal(scipy_x, gmres_x.asnumpy(), decimal=5)
@pytest.mark.level0
@pytest.mark.platform_x86_cpu
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
@pytest.mark.parametrize('n', [5])
@pytest.mark.parametrize('dtype', [onp.float64])
@pytest.mark.parametrize('dtype,tol', [(onp.float64, 7), (onp.float32, 3)])
@pytest.mark.parametrize('preconditioner', [None, 'identity', 'exact', 'random'])
def test_gmres_incremental_against_scipy(n, dtype, preconditioner):
def test_gmres_incremental_against_scipy(n, tol, dtype, preconditioner):
"""
Feature: ALL TO ALL
Description: test cases for [N x N] X [N X 1]
Expectation: the result match scipy
"""
context.set_context(mode=context.PYNATIVE_MODE)
# add Identity matrix to make matrix A non-singular
A = create_full_rank_matrix((n, n), dtype)
b = onp.random.rand(n).astype(dtype)
x0 = onp.zeros_like(b).astype(dtype)
M = _fetch_preconditioner(preconditioner, A)
gmres_compare_with_scipy_incremental(A, b, onp.zeros_like(b).astype(dtype), M)
scipy_x, _ = osp.sparse.linalg.gmres(A, b, x0, tol=1e-07, atol=0, M=M)
A = Tensor(A)
b = Tensor(b)
x0 = Tensor(x0)
if M is not None:
M = Tensor(M)
gmres_x, _ = msp.sparse.linalg.gmres(A, b, x0, tol=1e-07, atol=0, solve_method='incremental', M=M)
onp.testing.assert_almost_equal(scipy_x, gmres_x.asnumpy(), decimal=tol)
@pytest.mark.level0
@ -143,20 +145,29 @@ def test_gmres_incremental_against_scipy(n, dtype, preconditioner):
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
@pytest.mark.parametrize('n', [5])
@pytest.mark.parametrize('dtype', [onp.float64])
@pytest.mark.parametrize('dtype, tol', [(onp.float64, 7), (onp.float32, 3)])
@pytest.mark.parametrize('preconditioner', [None, 'identity', 'exact', 'random'])
def test_gmres_incremental_against_scipy_graph(n, dtype, preconditioner):
def test_gmres_incremental_against_scipy_graph(n, tol, dtype, preconditioner):
"""
Feature: ALL TO ALL
Description: test cases for [N x N] X [N X 1]
Expectation: the result match scipy
"""
context.set_context(mode=context.GRAPH_MODE)
# add Identity matrix to make matrix A non-singular
A = create_full_rank_matrix((n, n), dtype)
b = onp.random.rand(n).astype(dtype)
x0 = onp.zeros_like(b).astype(dtype)
M = _fetch_preconditioner(preconditioner, A)
gmres_compare_with_scipy_incremental(A, b, onp.zeros_like(b).astype(dtype), M)
scipy_x, _ = osp.sparse.linalg.gmres(A, b, x0, tol=1e-07, atol=0, M=M)
A = Tensor(A)
b = Tensor(b)
x0 = Tensor(x0)
if M is not None:
M = Tensor(M)
gmres_x, _ = msp.sparse.linalg.gmres(A, b, x0, tol=1e-07, atol=0, solve_method='incremental', M=M)
onp.testing.assert_almost_equal(scipy_x, gmres_x.asnumpy(), decimal=tol)
@pytest.mark.level0