add float32 to Batch Gmres

This commit is contained in:
zhujingxuan 2021-11-30 17:25:40 +08:00
parent 95c0cafef4
commit 7e16e6d8cb
1 changed files with 15 additions and 10 deletions

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@ -23,8 +23,6 @@ from mindspore.common import Tensor
from mindspore.scipy.sparse.linalg import cg as msp_cg
from tests.st.scipy_st.utils import create_sym_pos_matrix, create_full_rank_matrix
onp.random.seed(0)
def _fetch_preconditioner(preconditioner, A):
"""
@ -58,6 +56,7 @@ def test_cg_against_scipy(dtype_tol, shape, preconditioner, maxiter):
Description: test cases for cg
Expectation: the result match scipy
"""
onp.random.seed(0)
dtype, tol = dtype_tol
A = create_sym_pos_matrix(shape, dtype)
b = onp.random.random(shape[:1]).astype(dtype)
@ -93,6 +92,7 @@ def test_cg_against_numpy(dtype, shape):
Description: test cases for cg
Expectation: the result match numpy
"""
onp.random.seed(0)
A = create_sym_pos_matrix(shape, dtype)
b = onp.random.random(shape[:1]).astype(dtype)
expected = onp.linalg.solve(A, b)
@ -114,7 +114,7 @@ def test_cg_against_numpy(dtype, shape):
@pytest.mark.platform_x86_cpu
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
@pytest.mark.parametrize('n', [5])
@pytest.mark.parametrize('n', [3, 5, 7])
@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, tol, dtype, preconditioner):
@ -123,6 +123,7 @@ def test_gmres_incremental_against_scipy(n, tol, dtype, preconditioner):
Description: test cases for [N x N] X [N X 1]
Expectation: the result match scipy
"""
onp.random.seed(0)
context.set_context(mode=context.PYNATIVE_MODE)
A = create_full_rank_matrix((n, n), dtype)
b = onp.random.rand(n).astype(dtype)
@ -144,7 +145,7 @@ def test_gmres_incremental_against_scipy(n, tol, dtype, preconditioner):
@pytest.mark.platform_x86_cpu
@pytest.mark.platform_x86_gpu_training
@pytest.mark.env_onecard
@pytest.mark.parametrize('n', [5])
@pytest.mark.parametrize('n', [3, 5, 7])
@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, tol, dtype, preconditioner):
@ -153,6 +154,7 @@ def test_gmres_incremental_against_scipy_graph(n, tol, dtype, preconditioner):
Description: test cases for [N x N] X [N X 1]
Expectation: the result match scipy
"""
onp.random.seed(0)
context.set_context(mode=context.GRAPH_MODE)
A = create_full_rank_matrix((n, n), dtype)
b = onp.random.rand(n).astype(dtype)
@ -175,15 +177,17 @@ def test_gmres_incremental_against_scipy_graph(n, tol, dtype, preconditioner):
@pytest.mark.platform_x86_cpu
@pytest.mark.env_onecard
@pytest.mark.parametrize('n', [4, 5, 6])
@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'])
@pytest.mark.parametrize('maxiter', [1, 2])
def test_pynative_batched_gmres_against_scipy(n, dtype, preconditioner, maxiter):
def test_pynative_batched_gmres_against_scipy(n, dtype, tol, preconditioner, maxiter):
"""
Feature: ALL TO ALL
Description: test cases for gmres
Expectation: the result match scipy
"""
onp.random.seed(0)
context.set_context(mode=context.PYNATIVE_MODE)
shape = (n, n)
a = create_full_rank_matrix(shape, dtype)
b = onp.random.rand(n).astype(dtype=dtype)
@ -196,7 +200,7 @@ def test_pynative_batched_gmres_against_scipy(n, dtype, preconditioner, maxiter)
msp_x, _ = msp.sparse.linalg.gmres(tensor_a, tensor_b, maxiter=maxiter, M=M, atol=1e-6,
solve_method='batched')
assert onp.allclose(msp_x.asnumpy(), osp_x)
onp.testing.assert_almost_equal(msp_x.asnumpy(), osp_x, decimal=tol)
@pytest.mark.level0
@ -204,15 +208,16 @@ def test_pynative_batched_gmres_against_scipy(n, dtype, preconditioner, maxiter)
@pytest.mark.platform_x86_cpu
@pytest.mark.env_onecard
@pytest.mark.parametrize('n', [5, 6])
@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'])
@pytest.mark.parametrize('maxiter', [1, 2])
def test_graph_batched_gmres_against_scipy(n, dtype, preconditioner, maxiter):
def test_graph_batched_gmres_against_scipy(n, dtype, tol, preconditioner, maxiter):
"""
Feature: ALL TO ALL
Description: test cases for gmres
Expectation: the result match scipy
"""
onp.random.seed(0)
context.set_context(mode=context.GRAPH_MODE)
shape = (n, n)
a = create_full_rank_matrix(shape, dtype)
@ -223,4 +228,4 @@ def test_graph_batched_gmres_against_scipy(n, dtype, preconditioner, maxiter):
M = Tensor(M) if M is not None else M
osp_x, _ = osp.sparse.linalg.gmres(a, b, maxiter=maxiter, atol=0.0)
msp_x, _ = msp.sparse.linalg.gmres(tensor_a, tensor_b, maxiter=maxiter, M=M, atol=0.0, solve_method='batched')
assert onp.allclose(msp_x.asnumpy(), osp_x)
onp.testing.assert_almost_equal(msp_x.asnumpy(), osp_x, decimal=tol)