============================= test session starts ==============================
platform linux -- Python 3.8.3, pytest-5.4.3, py-1.8.2, pluggy-0.13.1
rootdir: /home/aryaman4/sbi, inifile: setup.cfg
plugins: pep8-1.0.6
collected 150 items

tests/inference_with_NaN_simulator_test.py .......                       [  4%]
tests/linearGaussian_simulator_test.py ....                              [  7%]
tests/linearGaussian_snle_test.py ..........                             [ 14%]
tests/linearGaussian_snpe_test.py ....x.x....                            [ 21%]
tests/linearGaussian_snre_test.py ...........                            [ 28%]
tests/multiprocessing_test.py ...                                        [ 30%]
tests/posterior_nn_test.py .                                             [ 31%]
tests/pyroutils_test.py .                                                [ 32%]
tests/simulator_utils_test.py .........                                  [ 38%]
tests/torchutils_test.py ..............                                  [ 47%]
tests/user_input_checks_test.py ......xxxx.......xx..................... [ 74%]
.....xxxx....                                                            [ 82%]
tests/mcmc_slice_pyro/test_slice.py ssss.........sssssssssssss           [100%]

=============================== warnings summary ===============================
tests/inference_with_NaN_simulator_test.py: 1 test with warning
tests/linearGaussian_snpe_test.py: 10 tests with warnings
tests/posterior_nn_test.py: 1 test with warning
tests/user_input_checks_test.py: 8 tests with warnings
  /home/aryaman4/anaconda3/envs/sbi_env/lib/python3.8/site-packages/nflows/transforms/standard.py:76: DeprecationWarning: Use PointwiseAffineTransform
    warnings.warn("Use PointwiseAffineTransform", DeprecationWarning)

tests/inference_with_NaN_simulator_test.py: 12 tests with warnings
  /home/aryaman4/anaconda3/envs/sbi_env/lib/python3.8/site-packages/sklearn/neural_network/_multilayer_perceptron.py:582: ConvergenceWarning: Stochastic Optimizer: Maximum iterations (1000) reached and the optimization hasn't converged yet.
    warnings.warn(

tests/inference_with_NaN_simulator_test.py: 2 tests with warnings
tests/linearGaussian_snle_test.py: 9 tests with warnings
tests/linearGaussian_snpe_test.py: 1 test with warning
tests/linearGaussian_snre_test.py: 9 tests with warnings
  /home/aryaman4/sbi/sbi/inference/posterior.py:504: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).
    return torch.tensor(samples, dtype=torch.float32)

tests/linearGaussian_snle_test.py::test_api_snl_on_linearGaussian[1]
tests/linearGaussian_snle_test.py::test_c2st_snl_on_linearGaussian[uniform-1]
tests/linearGaussian_snle_test.py::test_c2st_snl_on_linearGaussian[gaussian-1]
  /home/aryaman4/sbi/sbi/utils/get_nn_models.py:379: UserWarning: In one-dimensional data spaces, MAFs are limited to a Gaussian density. Consider setting `density_estimator="mdn"` instead.
    warn(

tests/linearGaussian_snle_test.py::test_c2st_snl_on_linearGaussian[uniform-1]
tests/linearGaussian_snle_test.py::test_c2st_snl_on_linearGaussian[uniform-2]
  /home/aryaman4/sbi/sbi/inference/posterior.py:245: UserWarning: The log probability from SNL is only correct up to a normalizing constant.
    warn(

tests/linearGaussian_snpe_test.py::test_c2st_snpe_on_linearGaussian[1-gaussian]
  /home/aryaman4/sbi/sbi/utils/get_nn_models.py:379: UserWarning: In one-dimensional parameter spaces, MAFs are limited to a Gaussian density. Consider setting `density_estimator="mdn"` instead.
    warn(

tests/linearGaussian_snre_test.py::test_c2st_sre_on_linearGaussian[2-gaussian-aalr]
  /home/aryaman4/sbi/sbi/inference/posterior.py:231: UserWarning: The log probability from SRE is only correct up to a normalizing constant.
    warn(

tests/multiprocessing_test.py::test_benchmarking_sp[1]
tests/multiprocessing_test.py::test_benchmarking_sp[10]
  /home/aryaman4/anaconda3/envs/sbi_env/lib/python3.8/site-packages/torch/storage.py:34: FutureWarning: pickle support for Storage will be removed in 1.5. Use `torch.save` instead
    warnings.warn("pickle support for Storage will be removed in 1.5. Use `torch.save` instead", FutureWarning)

tests/user_input_checks_test.py::test_prior_wrappers[CustomPytorchWrapper-prior0]
tests/user_input_checks_test.py::test_process_prior[prior7]
tests/user_input_checks_test.py::test_process_prior[prior8]
tests/user_input_checks_test.py::test_process_simulator[numpy_linear_gaussian-prior2]
tests/user_input_checks_test.py::test_prepare_sbi_problem[numpy_linear_gaussian-prior1-x_shape1]
tests/user_input_checks_test.py::test_prepare_sbi_problem[numpy_linear_gaussian-prior4-x_shape4]
tests/user_input_checks_test.py::test_inference_with_user_sbi_problems[numpy_linear_gaussian-user_prior2-user_x_shape2]
tests/user_input_checks_test.py::test_inference_with_user_sbi_problems[numpy_linear_gaussian-user_prior6-user_x_shape6]
  /home/aryaman4/sbi/sbi/user_input/user_input_checks_utils.py:60: UserWarning: Prior is lacking mean attribute, estimating prior mean from samples...
    warnings.warn(

tests/user_input_checks_test.py::test_prior_wrappers[CustomPytorchWrapper-prior0]
tests/user_input_checks_test.py::test_process_prior[prior7]
tests/user_input_checks_test.py::test_process_prior[prior8]
tests/user_input_checks_test.py::test_process_simulator[numpy_linear_gaussian-prior2]
tests/user_input_checks_test.py::test_prepare_sbi_problem[numpy_linear_gaussian-prior1-x_shape1]
tests/user_input_checks_test.py::test_prepare_sbi_problem[numpy_linear_gaussian-prior4-x_shape4]
tests/user_input_checks_test.py::test_inference_with_user_sbi_problems[numpy_linear_gaussian-user_prior2-user_x_shape2]
tests/user_input_checks_test.py::test_inference_with_user_sbi_problems[numpy_linear_gaussian-user_prior6-user_x_shape6]
  /home/aryaman4/sbi/sbi/user_input/user_input_checks_utils.py:71: UserWarning: Prior is lacking variance attribute, estimating prior variance from samples...
    warnings.warn(

tests/user_input_checks_test.py::test_process_matrix_observation
  /home/aryaman4/sbi/sbi/user_input/user_input_checks.py:250: UserWarning: Beware: The observed data (x_o) you passed was interpreted to have
              matrix shape: [2, 2]. The current implementation of sbi
              might not provide stable support for this and result in shape mismatches.
              
    warnings.warn(

tests/user_input_checks_test.py::test_prepare_sbi_problem[diagonal_linear_gaussian-prior5-x_shape5]
tests/user_input_checks_test.py::test_inference_with_user_sbi_problems[diagonal_linear_gaussian-user_prior7-user_x_shape7]
  /home/aryaman4/sbi/sbi/user_input/user_input_checks.py:43: UserWarning: Prior was provided as a sequence of 3 priors. They will be
              interpreted as independent of each other and matched in order to the
              components of the parameter.
    warnings.warn(

tests/mcmc_slice_pyro/test_slice.py::test_logistic_regression[2-JIT=False]
tests/mcmc_slice_pyro/test_slice.py::test_logistic_regression[2-JIT=True]
  /home/aryaman4/sbi/sbi/mcmc/mcmc.py:117: UserWarning: num_chains=2 is more than available_cpu=1. Chains will be drawn sequentially.
    warnings.warn(

-- Docs: https://docs.pytest.org/en/latest/warnings.html
============================ slowest test durations ============================
246.61s call     tests/inference_with_NaN_simulator_test.py::test_inference_with_nan_simulator[SNLE_A-True-0.05]
241.14s call     tests/linearGaussian_snle_test.py::test_c2st_snl_on_linearGaussian_different_dims
207.60s call     tests/linearGaussian_snle_test.py::test_c2st_multi_round_snl_on_linearGaussian
95.90s call     tests/linearGaussian_snpe_test.py::test_multi_round_snpe_deterministic_simulator[1e-07]
68.77s call     tests/linearGaussian_snle_test.py::test_c2st_snl_on_linearGaussian[gaussian-2]
62.11s call     tests/linearGaussian_snle_test.py::test_c2st_snl_on_linearGaussian[uniform-2]
59.65s call     tests/linearGaussian_snpe_test.py::test_c2st_multi_round_snpe_on_linearGaussian[snpe_c]
57.43s call     tests/inference_with_NaN_simulator_test.py::test_inference_with_nan_simulator[SNRE_B-True-0.05]
54.13s call     tests/linearGaussian_snpe_test.py::test_c2st_snpe_on_linearGaussian_different_dims
47.68s call     tests/linearGaussian_snre_test.py::test_c2st_sre_on_linearGaussian_different_dims
40.12s call     tests/linearGaussian_snpe_test.py::test_c2st_snpe_on_linearGaussian[2-uniform]
40.00s call     tests/inference_with_NaN_simulator_test.py::test_inference_with_nan_simulator[SNPE_C-True-0.05]
39.92s call     tests/linearGaussian_snle_test.py::test_c2st_snl_on_linearGaussian[uniform-1]
39.19s call     tests/linearGaussian_snpe_test.py::test_c2st_snpe_on_linearGaussian[2-gaussian]
35.48s call     tests/linearGaussian_snle_test.py::test_c2st_snl_on_linearGaussian[gaussian-1]
28.17s call     tests/linearGaussian_snpe_test.py::test_c2st_snpe_on_linearGaussian[1-gaussian]
25.18s call     tests/posterior_nn_test.py::test_log_prob_with_different_x
18.03s call     tests/linearGaussian_snre_test.py::test_c2st_sre_on_linearGaussian[2-gaussian-sre]
17.68s call     tests/linearGaussian_snre_test.py::test_c2st_sre_on_linearGaussian[2-gaussian-aalr]
17.31s call     tests/linearGaussian_snpe_test.py::test_api_snpe_c_posterior_correction[True-slice_np-gaussian]
16.38s call     tests/linearGaussian_snre_test.py::test_c2st_sre_on_linearGaussian[2-uniform-sre]
13.82s call     tests/mcmc_slice_pyro/test_slice.py::test_logistic_regression[2-JIT=False]
10.46s call     tests/linearGaussian_snre_test.py::test_c2st_sre_on_linearGaussian[1-gaussian-sre]
10.05s call     tests/multiprocessing_test.py::test_benchmarking_sp[100]
9.99s call     tests/linearGaussian_snle_test.py::test_api_snl_on_linearGaussian[3]
7.59s call     tests/linearGaussian_snpe_test.py::test_api_snpe_c_posterior_correction[True-slice-gaussian]
7.56s call     tests/mcmc_slice_pyro/test_slice.py::test_logistic_regression[1-JIT=False]
6.43s call     tests/multiprocessing_test.py::test_benchmarking_sp[1]
6.26s call     tests/linearGaussian_snpe_test.py::test_multi_round_snpe_deterministic_simulator[0.0]
6.23s call     tests/linearGaussian_snre_test.py::test_api_sre_on_linearGaussian[3]
6.07s call     tests/mcmc_slice_pyro/test_slice.py::test_logistic_regression[2-JIT=True]
5.54s call     tests/multiprocessing_test.py::test_benchmarking_sp[10]
5.53s call     tests/linearGaussian_snle_test.py::test_api_snl_on_linearGaussian[1]
5.41s call     tests/linearGaussian_snle_test.py::test_api_snl_sampling_methods[slice-gaussian]
4.96s call     tests/mcmc_slice_pyro/test_slice.py::test_beta_bernoulli
4.38s call     tests/linearGaussian_snle_test.py::test_api_snl_sampling_methods[slice-uniform]
4.01s call     tests/mcmc_slice_pyro/test_slice.py::test_gamma_normal[JIT=False]
3.50s call     tests/mcmc_slice_pyro/test_slice.py::test_dirichlet_categorical[JIT=False]
3.34s call     tests/mcmc_slice_pyro/test_slice.py::test_logistic_regression[1-JIT=True]
3.14s call     tests/linearGaussian_snre_test.py::test_api_sre_sampling_methods[slice_np-gaussian]
2.84s call     tests/linearGaussian_snre_test.py::test_api_sre_sampling_methods[slice_np-uniform]
2.57s call     tests/linearGaussian_snre_test.py::test_api_sre_on_linearGaussian[1]
2.26s call     tests/linearGaussian_snpe_test.py::test_api_snpe_c_posterior_correction[False-rejection-uniform]
1.89s call     tests/torchutils_test.py::test_dkl_gauss
1.89s call     tests/linearGaussian_snre_test.py::test_api_sre_sampling_methods[slice-gaussian]
1.69s call     tests/linearGaussian_snre_test.py::test_api_sre_sampling_methods[slice-uniform]
1.62s call     tests/mcmc_slice_pyro/test_slice.py::test_gamma_normal[JIT=True]
1.46s call     tests/mcmc_slice_pyro/test_slice.py::test_dirichlet_categorical[JIT=True]
1.22s call     tests/user_input_checks_test.py::test_inference_with_user_sbi_problems[diagonal_linear_gaussian-user_prior0-user_x_shape0]
1.05s call     tests/user_input_checks_test.py::test_inference_with_user_sbi_problems[diagonal_linear_gaussian-user_prior7-user_x_shape7]
0.74s call     tests/user_input_checks_test.py::test_inference_with_user_sbi_problems[linear_gaussian_no_batch-user_prior1-user_x_shape1]
0.73s call     tests/user_input_checks_test.py::test_inference_with_user_sbi_problems[numpy_linear_gaussian-user_prior2-user_x_shape2]
0.71s call     tests/user_input_checks_test.py::test_inference_with_user_sbi_problems[numpy_linear_gaussian-user_prior6-user_x_shape6]
0.49s call     tests/user_input_checks_test.py::test_inference_with_user_sbi_problems[diagonal_linear_gaussian-user_prior3-user_x_shape3]
0.44s call     tests/user_input_checks_test.py::test_inference_with_user_sbi_problems[linear_gaussian_no_batch-user_prior4-user_x_shape4]
0.42s call     tests/user_input_checks_test.py::test_inference_with_user_sbi_problems[list_simulator-user_prior5-user_x_shape5]
0.02s call     tests/simulator_utils_test.py::test_simulate_in_batches[1-1000]
0.01s call     tests/linearGaussian_simulator_test.py::test_linearGaussian_simulator[5-100000]
0.01s call     tests/linearGaussian_simulator_test.py::test_standardlinearGaussian_simulator[5-100000]

(0.00 durations hidden.  Use -vv to show these durations.)
==== 121 passed, 17 skipped, 12 xfailed, 83 warnings in 1606.22s (0:26:46) =====
