From 767171593f2a98a26b9a39bf110a45085e3b982e Mon Sep 17 00:00:00 2001 From: Nathan Cassereau <84033440+ncassereau-idris@users.noreply.github.com> Date: Thu, 24 Mar 2022 10:53:47 +0100 Subject: [MRG] Domain adaptation and unbalanced solvers with backend support (#343) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * First draft * Add matrix inverse and square root to backend * Eigen decomposition for older versions of pytorch (1.8.1 and older) * Corrected eigen decomposition for pytorch 1.8.1 and older * Spectral theorem is a thing * Optimization * small optimization * More functions converted * pep8 * remove a warning and prepare torch meshgrid for future torch release (which will change default indexing) * dots and pep8 * Meshgrid corrected for older version and prepared for future versions changes * New backend functions * Base transport * LinearTransport * All transport classes + pep8 * PR added to release file * Jcpot barycenter test * unbalanced with backend * pep8 * bug solve * test of domain adaptation with backends * solve bug for tic toc & macos * solving scipy deprecation warning * solving scipy deprecation warning attempt2 * solving scipy deprecation warning attempt3 * A warning is triggered when a float->int conversion is detected * bug solve * docs * release file updated * Better handling of float->int conversion in EMD * Corrected test for is_floating_point * docs * release file updated * cupy does not allow implicit cast * fromnumpy * added test * test da tf jax * test unbalanced with no provided histogram * using type_as argument in unif function correctly * pep8 * transport plan cast in emd changed behaviour, now trying to cast as histogram's dtype, defaulting to cost matrix Co-authored-by: Rémi Flamary --- test/test_1d_solver.py | 28 +++++++--------------------- 1 file changed, 7 insertions(+), 21 deletions(-) (limited to 'test/test_1d_solver.py') diff --git a/test/test_1d_solver.py b/test/test_1d_solver.py index 6a42cfe..20f307a 100644 --- a/test/test_1d_solver.py +++ b/test/test_1d_solver.py @@ -66,9 +66,7 @@ def test_wasserstein_1d(nx): rho_v = np.abs(rng.randn(n)) rho_v /= rho_v.sum() - xb = nx.from_numpy(x) - rho_ub = nx.from_numpy(rho_u) - rho_vb = nx.from_numpy(rho_v) + xb, rho_ub, rho_vb = nx.from_numpy(x, rho_u, rho_v) # test 1 : wasserstein_1d should be close to scipy W_1 implementation np.testing.assert_almost_equal(wasserstein_1d(xb, xb, rho_ub, rho_vb, p=1), @@ -98,9 +96,7 @@ def test_wasserstein_1d_type_devices(nx): for tp in nx.__type_list__: print(nx.dtype_device(tp)) - xb = nx.from_numpy(x, type_as=tp) - rho_ub = nx.from_numpy(rho_u, type_as=tp) - rho_vb = nx.from_numpy(rho_v, type_as=tp) + xb, rho_ub, rho_vb = nx.from_numpy(x, rho_u, rho_v, type_as=tp) res = wasserstein_1d(xb, xb, rho_ub, rho_vb, p=1) @@ -122,17 +118,13 @@ def test_wasserstein_1d_device_tf(): # Check that everything stays on the CPU with tf.device("/CPU:0"): - xb = nx.from_numpy(x) - rho_ub = nx.from_numpy(rho_u) - rho_vb = nx.from_numpy(rho_v) + xb, rho_ub, rho_vb = nx.from_numpy(x, rho_u, rho_v) res = wasserstein_1d(xb, xb, rho_ub, rho_vb, p=1) nx.assert_same_dtype_device(xb, res) if len(tf.config.list_physical_devices('GPU')) > 0: # Check that everything happens on the GPU - xb = nx.from_numpy(x) - rho_ub = nx.from_numpy(rho_u) - rho_vb = nx.from_numpy(rho_v) + xb, rho_ub, rho_vb = nx.from_numpy(x, rho_u, rho_v) res = wasserstein_1d(xb, xb, rho_ub, rho_vb, p=1) nx.assert_same_dtype_device(xb, res) assert nx.dtype_device(res)[1].startswith("GPU") @@ -190,9 +182,7 @@ def test_emd1d_type_devices(nx): for tp in nx.__type_list__: print(nx.dtype_device(tp)) - xb = nx.from_numpy(x, type_as=tp) - rho_ub = nx.from_numpy(rho_u, type_as=tp) - rho_vb = nx.from_numpy(rho_v, type_as=tp) + xb, rho_ub, rho_vb = nx.from_numpy(x, rho_u, rho_v, type_as=tp) emd = ot.emd_1d(xb, xb, rho_ub, rho_vb) emd2 = ot.emd2_1d(xb, xb, rho_ub, rho_vb) @@ -214,9 +204,7 @@ def test_emd1d_device_tf(): # Check that everything stays on the CPU with tf.device("/CPU:0"): - xb = nx.from_numpy(x) - rho_ub = nx.from_numpy(rho_u) - rho_vb = nx.from_numpy(rho_v) + xb, rho_ub, rho_vb = nx.from_numpy(x, rho_u, rho_v) emd = ot.emd_1d(xb, xb, rho_ub, rho_vb) emd2 = ot.emd2_1d(xb, xb, rho_ub, rho_vb) nx.assert_same_dtype_device(xb, emd) @@ -224,9 +212,7 @@ def test_emd1d_device_tf(): if len(tf.config.list_physical_devices('GPU')) > 0: # Check that everything happens on the GPU - xb = nx.from_numpy(x) - rho_ub = nx.from_numpy(rho_u) - rho_vb = nx.from_numpy(rho_v) + xb, rho_ub, rho_vb = nx.from_numpy(x, rho_u, rho_v) emd = ot.emd_1d(xb, xb, rho_ub, rho_vb) emd2 = ot.emd2_1d(xb, xb, rho_ub, rho_vb) nx.assert_same_dtype_device(xb, emd) -- cgit v1.2.3