| Command: ptyrad run /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/f005_simulation_data6_b0cc2a63__sample_000013.yaml |
| Started: Tue Jun 23 23:42:15 2026 |
|
|
| 2026-06-23 23:42:18,317 - ### PtyRAD LoggingManager configuration ### |
| 2026-06-23 23:42:18,318 - log_file = 'ptyrad_log.txt'. If log_file = None, no log file will be created. |
| 2026-06-23 23:42:18,318 - log_dir = 'auto'. If log_dir = 'auto', then log will be saved to `output_path` or 'logs/'. |
| 2026-06-23 23:42:18,318 - flush_file = True. Automatically set to True if `log_file is not None` |
| 2026-06-23 23:42:18,318 - prefix_time = datetime. If true, preset strings ('date', 'time', 'datetime'), or a string of time format, a datetime str is prefixed to the `log_file`. |
| 2026-06-23 23:42:18,318 - prefix_jobid = '0'. If not 0, it'll be prefixed to the log file. This is used for hypertune mode with multiple GPUs. |
| 2026-06-23 23:42:18,318 - append_to_file = True. If true, logs will be appended to the existing file. If false, the log file will be overwritten. |
| 2026-06-23 23:42:18,318 - show_timestamp = True. If true, the printed information will contain a timestamp. |
| 2026-06-23 23:42:18,318 - |
| [RANK 0] Detected kernel version 4.18.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher. |
| 2026-06-23 23:42:18,427 - ### Initializing HuggingFace accelerator ### |
| 2026-06-23 23:42:18,427 - Accelerator.distributed_type = DistributedType.NO |
| 2026-06-23 23:42:18,427 - Accelerator.num_process = 1 |
| 2026-06-23 23:42:18,428 - Accelerator.mixed_precision = no |
| 2026-06-23 23:42:18,450 - 'accelerate' is available but NOT using distributed mode or mixed precision |
| 2026-06-23 23:42:18,450 - If you want to utilize 'accelerate' for multiGPU or mixed precision, |
| 2026-06-23 23:42:18,450 - Run `accelerate launch --multi_gpu --num_processes=2 --mixed_precision='no' -m ptyrad run <PTYRAD_ARGUMENTS> --gpuid 'acc'` in your terminal |
| 2026-06-23 23:42:18,450 - |
| 2026-06-23 23:42:18,450 - ### System information ### |
| 2026-06-23 23:42:18,450 - Platform: Linux-4.18.0-553.69.1.el8_10.x86_64-x86_64-with-glibc2.28 |
| 2026-06-23 23:42:18,450 - Operating System: Linux 4.18.0-553.69.1.el8_10.x86_64 |
| 2026-06-23 23:42:18,450 - OS Version: #1 SMP Thu Aug 7 18:10:00 EDT 2025 |
| 2026-06-23 23:42:18,450 - Machine: x86_64 |
| 2026-06-23 23:42:18,450 - Processor: x86_64 |
| 2026-06-23 23:42:18,450 - Available CPU cores: 8 |
| 2026-06-23 23:42:18,450 - SLURM-Allocated Total Memory: 78.12 GB |
| 2026-06-23 23:42:18,450 - |
| 2026-06-23 23:42:18,450 - ### GPU information ### |
| 2026-06-23 23:42:18,450 - CUDA Available: True |
| 2026-06-23 23:42:18,450 - CUDA Version: 13.0 |
| 2026-06-23 23:42:18,451 - Available CUDA GPUs: ['NVIDIA A100 80GB PCIe'] |
| 2026-06-23 23:42:18,451 - CUDA Compute Capability: ['8.0'] |
| 2026-06-23 23:42:18,451 - INFO: For torch.compile with Triton, you'll need CUDA GPU with Compute Capability >= 7.0. |
| 2026-06-23 23:42:18,451 - In addition, Triton does not directly support Windows. |
| 2026-06-23 23:42:18,451 - For Windows users, please follow the instruction and download `triton-windows` from https://github.com/woct0rdho/triton-windows. |
| 2026-06-23 23:42:18,466 - MIG (Multi-Instance GPU) mode = False |
| 2026-06-23 23:42:18,466 - INFO: MIG splits a physical GPU into multiple GPU slices, but multiGPU does not support these MIG slices. |
| 2026-06-23 23:42:18,466 - In addition, multiGPU is currently only available on Linux due to the limited NCCL support. |
| 2026-06-23 23:42:18,466 - -> If you're doing normal reconstruction/hypertune, you can safely ignore this. |
| 2026-06-23 23:42:18,466 - -> If you want to do multiGPU, you must provide multiple 'full' GPUs that are not in MIG mode. |
| 2026-06-23 23:42:18,466 - |
| 2026-06-23 23:42:18,466 - ### Python information ### |
| 2026-06-23 23:42:18,468 - Python Executable: /home/tnguye11/anaconda3/envs/ptyrad/bin/python3.12 |
| 2026-06-23 23:42:18,468 - Python Version: 3.12.13 | packaged by Anaconda, Inc. | (main, Mar 19 2026, 20:20:58) [GCC 14.3.0] |
| 2026-06-23 23:42:18,468 - |
| 2026-06-23 23:42:18,468 - ### Packages information ### |
| 2026-06-23 23:42:18,469 - Numpy Version (metadata): 2.4.6 |
| 2026-06-23 23:42:18,469 - PyTorch Version (metadata): 2.12.0 |
| 2026-06-23 23:42:18,470 - Optuna Version (metadata): 4.9.0 |
| 2026-06-23 23:42:18,471 - Accelerate Version (metadata): 1.13.0 |
| 2026-06-23 23:42:18,471 - PtyRAD Version (ptyrad/__init__.py): 1.0.0 |
| 2026-06-23 23:42:18,471 - PtyRAD is located at: /home/tnguye11/anaconda3/envs/ptyrad/lib/python3.12/site-packages/ptyrad/__init__.py |
| 2026-06-23 23:42:18,471 - |
| 2026-06-23 23:42:18,471 - ### Loading params file ### |
| 2026-06-23 23:42:18,471 - params_path = /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/params/f005_simulation_data6_b0cc2a63__sample_000013.yaml |
| 2026-06-23 23:42:18,478 - validate = True: Filling defaults and validating the params file... |
| 2026-06-23 23:42:18,479 - Success! Params file validated and defaults applied. |
| 2026-06-23 23:42:18,479 - |
| 2026-06-23 23:42:18,479 - ### Setting GPU Device ### |
| 2026-06-23 23:42:18,479 - Selected GPU device: cuda:0 (NVIDIA A100 80GB PCIe) |
| 2026-06-23 23:42:18,479 - |
| 2026-06-23 23:42:18,479 - Random seed: 20260626 provided by params file |
| 2026-06-23 23:42:18,480 - ### Initializing Initializer ### |
| 2026-06-23 23:42:18,480 - init_params are displayed below: |
| 2026-06-23 23:42:18,480 - random_seed: 20260626 |
| 2026-06-23 23:42:18,480 - probe_illum_type: electron |
| 2026-06-23 23:42:18,480 - probe_kv: 200.0 |
| 2026-06-23 23:42:18,480 - probe_conv_angle: 9.91810131072998 |
| 2026-06-23 23:42:18,480 - probe_aberrations: {'C10': -401.252, 'C12': -13.184, 'phi12': 72.353, 'C21': 187.379, 'phi21': 351.034, 'C23': -814.688, 'phi23': 252.041, 'C30': 10371734.0, 'C32': 10346.336, 'phi32': 336.446, 'C34': -11791.021, 'phi34': 116.397, 'C41': -443766.781, 'phi41': 331.936, 'C43': 234443.188, 'phi43': 56.552, 'C45': -299696.406, 'phi45': 128.453, 'C50': 12290260.0, 'C52': -17827392.0, 'phi52': 330.065, 'C54': 1032114.562, 'phi54': 356.457, 'C56': -15998074.0, 'phi56': 75.251} |
| 2026-06-23 23:42:18,480 - beam_kev: None |
| 2026-06-23 23:42:18,480 - probe_dRn: None |
| 2026-06-23 23:42:18,480 - probe_Rn: None |
| 2026-06-23 23:42:18,480 - probe_D_H: None |
| 2026-06-23 23:42:18,480 - probe_D_FZP: None |
| 2026-06-23 23:42:18,480 - probe_Ls: None |
| 2026-06-23 23:42:18,480 - meas_Npix: 128 |
| 2026-06-23 23:42:18,480 - pos_N_scans: 256 |
| 2026-06-23 23:42:18,480 - pos_N_scan_slow: 16 |
| 2026-06-23 23:42:18,480 - pos_N_scan_fast: 16 |
| 2026-06-23 23:42:18,480 - pos_scan_step_size: 0.5299999713897705 |
| 2026-06-23 23:42:18,480 - meas_calibration: {'mode': 'kMax', 'value': 2.5} |
| 2026-06-23 23:42:18,480 - probe_pmode_max: 6 |
| 2026-06-23 23:42:18,480 - probe_pmode_init_pows: [0.02] |
| 2026-06-23 23:42:18,480 - obj_omode_max: 1 |
| 2026-06-23 23:42:18,480 - obj_omode_init_occu: {'occu_type': 'uniform', 'init_occu': None} |
| 2026-06-23 23:42:18,480 - obj_Nlayer: 1 |
| 2026-06-23 23:42:18,480 - obj_slice_thickness: 20.0 |
| 2026-06-23 23:42:18,480 - simu_Npix: None |
| 2026-06-23 23:42:18,480 - simu_match_mode: None |
| 2026-06-23 23:42:18,480 - meas_permute: None |
| 2026-06-23 23:42:18,480 - meas_reshape: [256, 128, 128] |
| 2026-06-23 23:42:18,480 - meas_flipT: [0, 0, 0] |
| 2026-06-23 23:42:18,481 - meas_crop: None |
| 2026-06-23 23:42:18,481 - meas_pad: None |
| 2026-06-23 23:42:18,481 - meas_resample: None |
| 2026-06-23 23:42:18,481 - meas_add_source_size: None |
| 2026-06-23 23:42:18,481 - meas_add_detector_blur: None |
| 2026-06-23 23:42:18,481 - meas_remove_neg_values: {'mode': 'clip_neg', 'value': None, 'force': False} |
| 2026-06-23 23:42:18,481 - meas_normalization: {'mode': 'max_at_one', 'value': None} |
| 2026-06-23 23:42:18,481 - meas_add_poisson_noise: None |
| 2026-06-23 23:42:18,481 - meas_export: None |
| 2026-06-23 23:42:18,481 - probe_permute: None |
| 2026-06-23 23:42:18,481 - probe_z_shift: None |
| 2026-06-23 23:42:18,481 - probe_normalization: {'mode': 'mean_total_ints', 'value': None} |
| 2026-06-23 23:42:18,481 - pos_scan_flipT: None |
| 2026-06-23 23:42:18,481 - pos_scan_affine: None |
| 2026-06-23 23:42:18,481 - pos_scan_rand_std: 0.15 |
| 2026-06-23 23:42:18,481 - obj_z_crop: None |
| 2026-06-23 23:42:18,481 - obj_z_pad: None |
| 2026-06-23 23:42:18,481 - obj_z_resample: None |
| 2026-06-23 23:42:18,481 - meas_source: file |
| 2026-06-23 23:42:18,481 - meas_params: {'path': '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_inputs/f005_simulation_data6_b0cc2a63__sample_000013_measurement.h5', 'key': 'measurement', 'shape': None, 'offset': None, 'gap': None, 'selection': None, 'zarr_kwargs': None} |
| 2026-06-23 23:42:18,481 - probe_source: simu |
| 2026-06-23 23:42:18,481 - probe_params: None |
| 2026-06-23 23:42:18,481 - pos_source: simu |
| 2026-06-23 23:42:18,481 - pos_params: None |
| 2026-06-23 23:42:18,481 - obj_source: simu |
| 2026-06-23 23:42:18,481 - obj_params: None |
| 2026-06-23 23:42:18,481 - tilt_source: simu |
| 2026-06-23 23:42:18,481 - tilt_params: {'tilt_type': 'all', 'init_tilts': [[0, 0]]} |
| 2026-06-23 23:42:18,481 - |
| 2026-06-23 23:42:18,481 - ### Initializing cache ### |
| 2026-06-23 23:42:18,481 - use_cached_obj = False |
| 2026-06-23 23:42:18,481 - use_cached_probe = False |
| 2026-06-23 23:42:18,481 - use_cached_pos = False |
| 2026-06-23 23:42:18,481 - |
| 2026-06-23 23:42:18,481 - ### Initializing measurements ### |
| 2026-06-23 23:42:18,481 - Loading measurements from source = 'file' |
| 2026-06-23 23:42:18,481 - Detected measurement file type = '.h5' |
| 2026-06-23 23:42:18,560 - Original measurements dtype is float32, casting to float32 (single precision) for computational efficiency. |
| 2026-06-23 23:42:18,560 - Imported meausrements shape / dtype = (16, 16, 128, 128), dtype = float32 |
| 2026-06-23 23:42:18,562 - Imported meausrements int. statistics (min, mean, max) = (0.0000, 0.0001, 0.0044) |
| 2026-06-23 23:42:18,562 - Reshaping measurements to shape = [256, 128, 128] |
| 2026-06-23 23:42:18,562 - Flipping measurements with [flipud, fliplr, transpose] = [0, 0, 0] |
| 2026-06-23 23:42:18,564 - No negative values found in measurements. Skipping non-neg correction. |
| 2026-06-23 23:42:18,564 - Normalizing measurements with mode = 'max_at_one' and value = 'None' |
| 2026-06-23 23:42:18,565 - Normalizing by max of the 2D mean pattern intensity: 0.0030127415 |
| 2026-06-23 23:42:18,566 - meausrements shape / dtype = (256, 128, 128), dtype = float32 |
| 2026-06-23 23:42:18,567 - meausrements int. statistics (min, mean, max) = (0.0000, 0.0202, 1.4464) |
| 2026-06-23 23:42:18,568 - No negative values found in measurements. Skipping non-neg correction. |
| 2026-06-23 23:42:18,569 - Pattern total int. statistics (min, mean, max) = (328.6686, 331.1643, 333.0232), with min/max = 98.7% |
| 2026-06-23 23:42:18,570 - Global meausrements int. statistics (min, mean, max) = (0.0000, 0.0202, 1.4464) |
| 2026-06-23 23:42:18,570 - measurements (N, Ky, Kx) = float32, (256, 128, 128) |
| 2026-06-23 23:42:18,570 - |
| 2026-06-23 23:42:18,570 - ### Setting up calibration ### |
| 2026-06-23 23:42:18,570 - meas_calibration mode = 'kMax', value = 2.5 |
| 2026-06-23 23:42:18,571 - Using loaded raw averaged measurement (before crop/pad/resample) to fit RBF as a part of the meas calibration |
| 2026-06-23 23:42:18,571 - Radius of fitted bright field disk (RBF) = 10.06 px with meas_Npix = 128 |
| 2026-06-23 23:42:18,571 - Suggested probe_mask_k radius (RBF*2/Npix) > 0.1572 |
| 2026-06-23 23:42:18,571 - Fitting raw averaged measurement with center, radius, and Gaussian blur std as a sanity check |
| 2026-06-23 23:42:18,571 - Note that the fitted Gaussian blur std (detector blur) would be affected by overlapping Bragg disks |
| 2026-06-23 23:42:18,798 - Initial guess: center=(63.65, 63.61), radius=10.06, Gaussian blur std=0.50 |
| 2026-06-23 23:42:18,807 - Final fit: center=(63.65, 63.61), radius=10.06, Gaussian blur std=0.54 |
| 2026-06-23 23:42:18,807 - Using init_params, the inferred RBF (conv_angle / 1e3 * Npix * dx / wavelength) = 10.12 px with Npix = 128 |
| 2026-06-23 23:42:18,807 - dx (real space pixel size of probe and object) set to 0.2000 Ang with Npix = 128 |
| 2026-06-23 23:42:18,807 - |
| 2026-06-23 23:42:18,807 - ### Setting init_variables dict ### |
| 2026-06-23 23:42:18,807 - Derived values given input init_params: |
| 2026-06-23 23:42:18,807 - kv = 200.0 kV |
| 2026-06-23 23:42:18,807 - wavelength = 0.0251 Ang |
| 2026-06-23 23:42:18,807 - conv_angle = 9.91810131072998 mrad |
| 2026-06-23 23:42:18,807 - Npix = 128 px |
| 2026-06-23 23:42:18,807 - dk = 0.0391 Ang^-1 |
| 2026-06-23 23:42:18,807 - kMax = 2.5000 Ang^-1 |
| 2026-06-23 23:42:18,807 - da = 0.9797 mrad |
| 2026-06-23 23:42:18,807 - angleMax = 62.6984 mrad |
| 2026-06-23 23:42:18,807 - RBF = 10.1240 px (Inferred from the given calibration, NOT necessarily from the loaded measurement data) |
| 2026-06-23 23:42:18,807 - n_alpha = 6.3216 (# conv_angle) |
| 2026-06-23 23:42:18,807 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang |
| 2026-06-23 23:42:18,807 - Rayleigh-limited resolution = 1.5425 Ang (0.61*lambda/alpha for focused probe ) |
| 2026-06-23 23:42:18,807 - Real space probe extent = 25.6000 Ang |
| 2026-06-23 23:42:18,808 - |
| 2026-06-23 23:42:18,808 - ### Initializing probe ### |
| 2026-06-23 23:42:18,808 - Loading probe from source = 'simu' |
| 2026-06-23 23:42:18,808 - Using experimental parameters specified by 'init_params' for initial probe simulation. |
| 2026-06-23 23:42:18,808 - Start simulating STEM probe |
| 2026-06-23 23:42:18,808 - kv = 200.0 kV |
| 2026-06-23 23:42:18,808 - wavelength = 0.0251 Ang |
| 2026-06-23 23:42:18,808 - conv_angle = 9.91810131072998 mrad |
| 2026-06-23 23:42:18,808 - Npix = 128 px |
| 2026-06-23 23:42:18,808 - dk = 0.0391 Ang^-1 |
| 2026-06-23 23:42:18,808 - kMax = 2.5000 Ang^-1 |
| 2026-06-23 23:42:18,808 - alpha_max = 62.6984 mrad |
| 2026-06-23 23:42:18,808 - dx = 0.2000 Ang, Nyquist-limited dmin = 2*dx = 0.4000 Ang |
| 2026-06-23 23:42:18,808 - Rayleigh-limited resolution = 1.5425 Ang (0.61*lambda/alpha for focused probe ) |
| 2026-06-23 23:42:18,808 - Real space probe extent = 25.6000 Ang |
| 2026-06-23 23:42:18,808 - Krivanek Haider Magnitude Angle (°) Description |
| 2026-06-23 23:42:18,808 - ------------------------------------------------------------------------------------ |
| 2026-06-23 23:42:18,808 - C1,0 C1 -401.2520 - Defocus (C10 = -df) |
| 2026-06-23 23:42:18,808 - C1,2 A1 -13.1840 72.35 2-fold astigmatism |
| 2026-06-23 23:42:18,808 - C2,1 3*B2 187.3790 351.03 Axial coma |
| 2026-06-23 23:42:18,808 - C2,3 A2 -814.6880 252.04 3-fold astigmatism |
| 2026-06-23 23:42:18,808 - C3,0 C3 10371734.0000 - Spherical aberration |
| 2026-06-23 23:42:18,808 - C3,2 4*S3 10346.3360 336.45 Axial star aberration |
| 2026-06-23 23:42:18,808 - C3,4 A3 -11791.0210 116.40 4-fold astigmatism |
| 2026-06-23 23:42:18,808 - C4,1 4*B4 -443766.7810 331.94 Axial coma(4th) |
| 2026-06-23 23:42:18,809 - C4,3 4*D4 234443.1880 56.55 3-lobe aberration |
| 2026-06-23 23:42:18,809 - C4,5 A4 -299696.4060 128.45 5-fold astigmatism |
| 2026-06-23 23:42:18,809 - C5,0 C5 12290260.0000 - Spherical aberration (5th) |
| 2026-06-23 23:42:18,809 - C5,2 6*S5 -17827392.0000 330.06 Axial star aberration(5th) |
| 2026-06-23 23:42:18,809 - C5,4 6*R5 1032114.5620 356.46 4-lobe aberration |
| 2026-06-23 23:42:18,809 - C5,6 A5 -15998074.0000 75.25 6-fold astigmatism |
| 2026-06-23 23:42:18,812 - Loaded probe shape = (1, 128, 128), dtype = complex128 |
| 2026-06-23 23:42:18,812 - pmode_now: 1 and pmode_max: 6, padding the pmode. |
| 2026-06-23 23:42:18,812 - Creating 5 new probe modes from the major mode |
| 2026-06-23 23:42:18,812 - Start making mixed-state STEM probe with 6 incoherent probe modes |
| 2026-06-23 23:42:18,909 - Relative power of probe modes = [0.9 0.02 0.02 0.02 0.02 0.02] |
| 2026-06-23 23:42:18,911 - Orthogonalizing 6 pmodes |
| 2026-06-23 23:42:18,914 - Sorting 6 pmodes by their intensities |
| 2026-06-23 23:42:18,914 - Normalizing probe intensity with mode = 'mean_total_ints' and value = 'None' |
| 2026-06-23 23:42:18,915 - sum(|probe_data|**2) = 331.16, while meas_total_ints (min, mean, max) = (328.6686, 331.1643, 333.0232) |
| 2026-06-23 23:42:18,915 - probe (pmode, Ny, Nx) = complex64, (6, 128, 128) |
| 2026-06-23 23:42:18,915 - |
| 2026-06-23 23:42:18,915 - ### Initializing probe positions ### |
| 2026-06-23 23:42:18,915 - Loading probe positions from source = 'simu' |
| 2026-06-23 23:42:18,915 - Using experimental parameters specified by 'init_params' (dx, scan_step size, N_scan_slow, N_scan_fast) for initial position simulation. |
| 2026-06-23 23:42:18,915 - Simulating probe positions with dx = 0.2000, scan_step_size = 0.5300, N_scan_fast = 16, N_scan_slow = 16 |
| 2026-06-23 23:42:18,915 - Applying Gaussian distributed random displacement with std = 0.15 px to scan positions |
| 2026-06-23 23:42:18,917 - crop_pos (N,2) = int16, (256, 2) |
| 2026-06-23 23:42:18,917 - crop_pos 1st and last px coords (y,x) = ([16, 16], [56, 56]) |
| 2026-06-23 23:42:18,918 - crop_pos extent (Ang) = [8. 8.] |
| 2026-06-23 23:42:18,918 - probe_pos_shifts (N,2) = float32, (256, 2) |
| 2026-06-23 23:42:18,918 - |
| 2026-06-23 23:42:18,918 - ### Initializing object ### |
| 2026-06-23 23:42:18,918 - Loading object from source = 'simu' |
| 2026-06-23 23:42:18,918 - Using experimental parameters specified by 'init_params' for initial object simulation. |
| 2026-06-23 23:42:18,919 - omode_now: 1 and omode_max: 1, leaving the omode unchanged. |
| 2026-06-23 23:42:18,919 - object (omode, Nz, Ny, Nx) = complex64, (1, 1, 202, 202) |
| 2026-06-23 23:42:18,920 - object extent (Z, Y, X) (Ang) = [20. 40.4 40.4] |
| 2026-06-23 23:42:18,920 - |
| 2026-06-23 23:42:18,920 - ### Initializing omode_occu from 'uniform' ### |
| 2026-06-23 23:42:18,920 - omode_occu (omode) = float32, (1,) |
| 2026-06-23 23:42:18,920 - |
| 2026-06-23 23:42:18,920 - ### Initializing H (Fresnel propagator) ### |
| 2026-06-23 23:42:18,920 - Calculating H with probe_shape = (128, 128) px, dx = 0.2000 Ang, slice_thickness = 20.0000 Ang, lambd = 0.0251 Ang |
| 2026-06-23 23:42:18,920 - H (Ky, Kx) = complex64, (128, 128) |
| 2026-06-23 23:42:18,920 - |
| 2026-06-23 23:42:18,921 - ### Initializing obj tilts from = 'simu' ### |
| 2026-06-23 23:42:18,921 - Initialized obj_tilts with init_tilts = [[0, 0]] (theta_y, theta_x) mrad |
| 2026-06-23 23:42:18,921 - obj_tilts (N, 2) = float32, (1, 2) |
| 2026-06-23 23:42:18,921 - |
| 2026-06-23 23:42:18,921 - ### Checking consistency between input params with the initialized variables ### |
| 2026-06-23 23:42:18,921 - meas_Npix, simu_Npix, DP measurements, probe, and H shapes are consistent as '128' |
| 2026-06-23 23:42:18,921 - N_scans, len(meas), N_scan_slow*N_scan_fast, len(crop_pos), and len(probe_pos_shifts) are consistent as '256' |
| 2026-06-23 23:42:18,921 - obj.shape[0] is consistent with len(omode_occu) as '1' |
| 2026-06-23 23:42:18,921 - obj.shape[1] is consistent with Nlayer as '1' |
| 2026-06-23 23:42:18,921 - crop positions (yx_min=[16 16], yx_max=[184 184]) are well contained inside object canvas (Ny,Nx) = (202, 202). |
| 2026-06-23 23:42:18,921 - obj_tilts is consistent with either 1 or N_scans |
| 2026-06-23 23:42:18,921 - Pass the consistency check of initialized variables, initialization is done! |
| 2026-06-23 23:42:18,921 - |
| 2026-06-23 23:42:18,921 - ### Collecting reconstruction provenance ### |
| 2026-06-23 23:42:18,921 - Reconstruction provenance is collected and initialized. |
| 2026-06-23 23:42:18,921 - |
| 2026-06-23 23:42:18,921 - ### Initializing loss function ### |
| 2026-06-23 23:42:18,921 - Active loss types: |
| 2026-06-23 23:42:18,921 - loss_single : {'state': True, 'weight': 1.0, 'dp_pow': 0.5} |
| 2026-06-23 23:42:18,921 - |
| 2026-06-23 23:42:18,921 - ### Initializing constraint function ### |
| 2026-06-23 23:42:18,922 - Active constraint types: |
| 2026-06-23 23:42:18,922 - ortho_pmode : {'start_iter': 1, 'step': 1, 'end_iter': None} |
| 2026-06-23 23:42:18,922 - fix_probe_int : {'start_iter': 1, 'step': 1, 'end_iter': None} |
| 2026-06-23 23:42:18,922 - obj_zblur : {'start_iter': 1, 'step': 1, 'end_iter': None, 'obj_type': 'both', 'kernel_size': 5, 'std': 1.0} |
| 2026-06-23 23:42:18,922 - obja_thresh : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0, 'thresh': [0.96, 1.04]} |
| 2026-06-23 23:42:18,922 - pos_recenter : {'start_iter': 1, 'step': 1, 'end_iter': None, 'relax': 0.0} |
| 2026-06-23 23:42:18,922 - |
| 2026-06-23 23:42:18,922 - ### Done initializing PtyRADSolver ### |
| 2026-06-23 23:42:18,922 - |
| 2026-06-23 23:42:19,046 - ### Starting the PtyRADSolver in reconstruct mode ### |
| 2026-06-23 23:42:19,046 - |
| 2026-06-23 23:42:19,046 - ### Initializing PtychoModel model ### |
| 2026-06-23 23:42:19,117 - ### PtychoModel optimizable variables ### |
| 2026-06-23 23:42:19,117 - obja : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 |
| 2026-06-23 23:42:19,117 - objp : torch.Size([1, 1, 202, 202]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 |
| 2026-06-23 23:42:19,117 - obj_tilts : torch.Size([1, 2]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 |
| 2026-06-23 23:42:19,117 - slice_thickness : torch.Size([]) , torch.float32 , device:cuda:0, grad:False, lr:0e+00 |
| 2026-06-23 23:42:19,117 - probe : torch.Size([6, 128, 128, 2]) , torch.float32 , device:cuda:0, grad:True , lr:1e-04 |
| 2026-06-23 23:42:19,117 - probe_pos_shifts: torch.Size([256, 2]) , torch.float32 , device:cuda:0, grad:True , lr:5e-04 |
| 2026-06-23 23:42:19,117 - |
| 2026-06-23 23:42:19,117 - ### Optimizable variables statitsics ### |
| 2026-06-23 23:42:19,117 - Total measurement values : 4,194,304 |
| 2026-06-23 23:42:19,117 - Total optimizing variables: 278,728 |
| 2026-06-23 23:42:19,118 - Overdetermined ratio : 15.05 |
| 2026-06-23 23:42:19,118 - |
| 2026-06-23 23:42:19,118 - ### Model behavior ### |
| 2026-06-23 23:42:19,118 - Tilt propagator : False |
| 2026-06-23 23:42:19,118 - Change slice thickness : False |
| 2026-06-23 23:42:19,118 - Detector blur : False |
| 2026-06-23 23:42:19,118 - Preload data : True |
| 2026-06-23 23:42:19,118 - On-the-fly meas padding : False |
| 2026-06-23 23:42:19,118 - On-the-fly meas resample : False |
| 2026-06-23 23:42:19,118 - On-the-fly simu match mode: None |
| 2026-06-23 23:42:19,118 - |
| 2026-06-23 23:42:19,160 - ### Done initializing PtychoModel model ### |
| 2026-06-23 23:42:19,160 - |
| 2026-06-23 23:42:19,160 - ### Creating PyTorch 'Adam' optimizer with configs = {} ### |
| 2026-06-23 23:42:19,160 - |
| 2026-06-23 23:42:19,160 - ### Generating indices, batches, and output_path ### |
| 2026-06-23 23:42:19,162 - d90 = 51.000 px or 10.200 Ang |
| 2026-06-23 23:42:19,162 - Selecting indices with the 'full' mode |
| 2026-06-23 23:42:19,620 - Generated 8 'random' groups of ~32 scan positions in 0.000 sec |
| 2026-06-23 23:42:19,695 - The effective batch size (i.e., how many probe positions are simultaneously used for 1 update of ptychographic parameters) is batch_size * grad_accumulation = 32 * 1 = 32 |
| 2026-06-23 23:42:19,695 - Original recon_dir_affixes = ['default'] |
| 2026-06-23 23:42:19,695 - Expanded recon_dir_affixes = ['indices', 'meas', 'batch', 'pmode', 'omode', 'nlayer', 'lr', 'model', 'constraint', 'loss', 'affine', 'tilt', 'aberrations'] |
| 2026-06-23 23:42:19,702 - Path corrected for compatibility: |
| 2026-06-23 23:42:19,702 - Original: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi32_336_C34_-1.18e+04_phi34_116_C41_-4.44e+05_phi41_332_C43_2.34e+05_phi43_56.6_C45_-3e+05_phi45_128_C50_1.23e+07_C52_-1.78e+07_phi52_330_C54_1.03e+06_phi54_356_C56_-1.6e+07_phi56_75.3 |
| 2026-06-23 23:42:19,702 - Corrected: /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3 |
| 2026-06-23 23:42:19,703 - output_path = '/gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3' is generated! |
| 2026-06-23 23:42:19,856 - |
| 2026-06-23 23:42:19,857 - ### Log file is flushed (created) as /gpfs/scratch/ailab/ai4physic/ptyrad_workspace/ptyrad_eval_test_100samples_seed20260624/ptyrad_output/f005_simulation_data6_b0cc2a63__sample_000013/f005_simulation_data6_b0cc2a63__sample_000013_full_N256_dp128_flipT000_random32_p6_1obj_1slice_plr1e-4_oalr5e-4_oplr5e-4_slr5e-4_ozblur1.0_oathr0.96_sng1.0_C10_-401_C12_-13.2_phi12_72.4_C21_187_phi21_351_C23_-815_phi23_252_C30_1.04e+07_C32_1.03e+04_phi3.3/20260623_234219_ptyrad_log.txt ### |
| 2026-06-23 23:42:19,857 - |
| 2026-06-23 23:42:19,859 - ### Creating ConvergenceMonitor with {'tensors': ['obja', 'objp', 'probe', 'probe_pos_shifts'], 'every_n_iters': None, 'percentile_range': [15.0, 85.0]} ### |
| 2026-06-23 23:42:19,859 - ### Start the PtyRAD iterative ptycho reconstruction ### |
| 2026-06-23 23:42:19,859 - Setting up PyTorch compiler with {'fullgraph': False, 'dynamic': None, 'backend': 'inductor', 'mode': 'default', 'options': None, 'disable': True} |
| 2026-06-23 23:42:21,039 - Iter: 1, Total Loss: 1.0180, loss_single: 1.0180, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.432 sec |
| 2026-06-23 23:42:21,077 - Iter: 2, Total Loss: 0.9724, loss_single: 0.9724, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.037 sec |
| 2026-06-23 23:42:21,114 - Iter: 3, Total Loss: 0.9346, loss_single: 0.9346, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec |
| 2026-06-23 23:42:21,150 - Iter: 4, Total Loss: 0.9055, loss_single: 0.9055, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,186 - Iter: 5, Total Loss: 0.8820, loss_single: 0.8820, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,221 - Iter: 6, Total Loss: 0.8534, loss_single: 0.8534, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,256 - Iter: 7, Total Loss: 0.8190, loss_single: 0.8190, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,292 - Iter: 8, Total Loss: 0.7906, loss_single: 0.7906, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,327 - Iter: 9, Total Loss: 0.7642, loss_single: 0.7642, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,362 - Iter: 10, Total Loss: 0.7377, loss_single: 0.7377, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,398 - Iter: 11, Total Loss: 0.7158, loss_single: 0.7158, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,467 - Iter: 12, Total Loss: 0.6924, loss_single: 0.6924, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,502 - Iter: 13, Total Loss: 0.6651, loss_single: 0.6651, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,537 - Iter: 14, Total Loss: 0.6349, loss_single: 0.6349, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,573 - Iter: 15, Total Loss: 0.6029, loss_single: 0.6029, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,608 - Iter: 16, Total Loss: 0.5762, loss_single: 0.5762, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,644 - Iter: 17, Total Loss: 0.5576, loss_single: 0.5576, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,682 - Iter: 18, Total Loss: 0.5393, loss_single: 0.5393, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec |
| 2026-06-23 23:42:21,718 - Iter: 19, Total Loss: 0.5207, loss_single: 0.5207, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,753 - Iter: 20, Total Loss: 0.5062, loss_single: 0.5062, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,789 - Iter: 21, Total Loss: 0.4934, loss_single: 0.4934, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,824 - Iter: 22, Total Loss: 0.4823, loss_single: 0.4823, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,859 - Iter: 23, Total Loss: 0.4735, loss_single: 0.4735, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,895 - Iter: 24, Total Loss: 0.4633, loss_single: 0.4633, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec |
| 2026-06-23 23:42:21,930 - Iter: 25, Total Loss: 0.4534, loss_single: 0.4534, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:21,965 - Iter: 26, Total Loss: 0.4456, loss_single: 0.4456, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,001 - Iter: 27, Total Loss: 0.4402, loss_single: 0.4402, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,036 - Iter: 28, Total Loss: 0.4351, loss_single: 0.4351, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,071 - Iter: 29, Total Loss: 0.4296, loss_single: 0.4296, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,107 - Iter: 30, Total Loss: 0.4246, loss_single: 0.4246, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,143 - Iter: 31, Total Loss: 0.4207, loss_single: 0.4207, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,181 - Iter: 32, Total Loss: 0.4175, loss_single: 0.4175, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec |
| 2026-06-23 23:42:22,217 - Iter: 33, Total Loss: 0.4143, loss_single: 0.4143, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,253 - Iter: 34, Total Loss: 0.4110, loss_single: 0.4110, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,288 - Iter: 35, Total Loss: 0.4077, loss_single: 0.4077, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,324 - Iter: 36, Total Loss: 0.4049, loss_single: 0.4049, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,359 - Iter: 37, Total Loss: 0.4024, loss_single: 0.4024, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,394 - Iter: 38, Total Loss: 0.4000, loss_single: 0.4000, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,430 - Iter: 39, Total Loss: 0.3980, loss_single: 0.3980, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,465 - Iter: 40, Total Loss: 0.3961, loss_single: 0.3961, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,504 - Iter: 41, Total Loss: 0.3947, loss_single: 0.3947, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,539 - Iter: 42, Total Loss: 0.3935, loss_single: 0.3935, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,575 - Iter: 43, Total Loss: 0.3922, loss_single: 0.3922, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,610 - Iter: 44, Total Loss: 0.3910, loss_single: 0.3910, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,646 - Iter: 45, Total Loss: 0.3900, loss_single: 0.3900, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,681 - Iter: 46, Total Loss: 0.3891, loss_single: 0.3891, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,717 - Iter: 47, Total Loss: 0.3880, loss_single: 0.3880, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,755 - Iter: 48, Total Loss: 0.3869, loss_single: 0.3869, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec |
| 2026-06-23 23:42:22,791 - Iter: 49, Total Loss: 0.3858, loss_single: 0.3858, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,826 - Iter: 50, Total Loss: 0.3847, loss_single: 0.3847, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,862 - Iter: 51, Total Loss: 0.3837, loss_single: 0.3837, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,898 - Iter: 52, Total Loss: 0.3827, loss_single: 0.3827, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,933 - Iter: 53, Total Loss: 0.3817, loss_single: 0.3817, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:22,968 - Iter: 54, Total Loss: 0.3809, loss_single: 0.3809, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,004 - Iter: 55, Total Loss: 0.3800, loss_single: 0.3800, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,039 - Iter: 56, Total Loss: 0.3792, loss_single: 0.3792, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,074 - Iter: 57, Total Loss: 0.3784, loss_single: 0.3784, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,110 - Iter: 58, Total Loss: 0.3777, loss_single: 0.3777, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,145 - Iter: 59, Total Loss: 0.3769, loss_single: 0.3769, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,180 - Iter: 60, Total Loss: 0.3760, loss_single: 0.3760, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,215 - Iter: 61, Total Loss: 0.3752, loss_single: 0.3752, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,253 - Iter: 62, Total Loss: 0.3744, loss_single: 0.3744, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec |
| 2026-06-23 23:42:23,289 - Iter: 63, Total Loss: 0.3738, loss_single: 0.3738, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec |
| 2026-06-23 23:42:23,325 - Iter: 64, Total Loss: 0.3730, loss_single: 0.3730, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,360 - Iter: 65, Total Loss: 0.3723, loss_single: 0.3723, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,395 - Iter: 66, Total Loss: 0.3716, loss_single: 0.3716, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,431 - Iter: 67, Total Loss: 0.3708, loss_single: 0.3708, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,466 - Iter: 68, Total Loss: 0.3701, loss_single: 0.3701, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,501 - Iter: 69, Total Loss: 0.3694, loss_single: 0.3694, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,536 - Iter: 70, Total Loss: 0.3688, loss_single: 0.3688, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,571 - Iter: 71, Total Loss: 0.3681, loss_single: 0.3681, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,606 - Iter: 72, Total Loss: 0.3673, loss_single: 0.3673, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,642 - Iter: 73, Total Loss: 0.3667, loss_single: 0.3667, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,677 - Iter: 74, Total Loss: 0.3661, loss_single: 0.3661, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,712 - Iter: 75, Total Loss: 0.3654, loss_single: 0.3654, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,747 - Iter: 76, Total Loss: 0.3646, loss_single: 0.3646, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,783 - Iter: 77, Total Loss: 0.3639, loss_single: 0.3639, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,821 - Iter: 78, Total Loss: 0.3633, loss_single: 0.3633, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.038 sec |
| 2026-06-23 23:42:23,856 - Iter: 79, Total Loss: 0.3627, loss_single: 0.3627, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.034 sec |
| 2026-06-23 23:42:23,891 - Iter: 80, Total Loss: 0.3621, loss_single: 0.3621, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,926 - Iter: 81, Total Loss: 0.3615, loss_single: 0.3615, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,961 - Iter: 82, Total Loss: 0.3609, loss_single: 0.3609, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:23,996 - Iter: 83, Total Loss: 0.3603, loss_single: 0.3603, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,031 - Iter: 84, Total Loss: 0.3597, loss_single: 0.3597, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,067 - Iter: 85, Total Loss: 0.3592, loss_single: 0.3592, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,103 - Iter: 86, Total Loss: 0.3586, loss_single: 0.3586, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,138 - Iter: 87, Total Loss: 0.3580, loss_single: 0.3580, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,173 - Iter: 88, Total Loss: 0.3574, loss_single: 0.3574, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,209 - Iter: 89, Total Loss: 0.3567, loss_single: 0.3567, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,244 - Iter: 90, Total Loss: 0.3563, loss_single: 0.3563, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,280 - Iter: 91, Total Loss: 0.3558, loss_single: 0.3558, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,315 - Iter: 92, Total Loss: 0.3553, loss_single: 0.3553, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,351 - Iter: 93, Total Loss: 0.3548, loss_single: 0.3548, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.036 sec |
| 2026-06-23 23:42:24,386 - Iter: 94, Total Loss: 0.3544, loss_single: 0.3544, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,422 - Iter: 95, Total Loss: 0.3539, loss_single: 0.3539, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,457 - Iter: 96, Total Loss: 0.3535, loss_single: 0.3535, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,492 - Iter: 97, Total Loss: 0.3530, loss_single: 0.3530, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,528 - Iter: 98, Total Loss: 0.3525, loss_single: 0.3525, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,563 - Iter: 99, Total Loss: 0.3519, loss_single: 0.3519, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,599 - Iter: 100, Total Loss: 0.3515, loss_single: 0.3515, loss_poissn: 0.0000, loss_pacbed: 0.0000, loss_sparse: 0.0000, loss_simlar: 0.0000, in 0.035 sec |
| 2026-06-23 23:42:24,714 - Saving summary figures for iter 100 |
| 2026-06-23 23:42:28,376 - ### Finished 100 iterations, averaged iter_t = 0.039138 with std = 0.039 ### |
| 2026-06-23 23:42:28,376 - |
| 2026-06-23 23:42:28,376 - ### The PtyRADSolver is finished in 9.330 sec ### |
| 2026-06-23 23:42:28,376 - |
| |
| Finished: Tue Jun 23 23:42:29 2026 |
| Return code: 0 |
| |
