bacalhau-project / bacalhau

Compute over Data framework for public, transparent, and optionally verifiable computation
https://docs.bacalhau.org
Apache License 2.0
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Golang is wrapping output - should never wrap (allow client terminal to do so) #4230

Open aronchick opened 4 months ago

aronchick commented 4 months ago

All linebreaks below were added by the bacalhau client


❯ bacalhau job describe j-86588a34-9abf-414d-9148-94e21ddcb71b
ID            = j-86588a34-9abf-414d-9148-94e21ddcb71b
Name          = Run Over Share
Namespace     = science
Type          = batch
State         = Completed
Count         = 1
Created Time  = 2024-07-12 12:43:37
Modified Time = 2024-07-12 12:43:44
Version       = 0

Summary
Completed = 1

Job History
 TIME                 REV.  STATE      TOPIC       EVENT
 2024-07-12 12:43:37  1     Pending    Submission  Job submitted
 2024-07-12 12:43:37  2     Running
 2024-07-12 12:43:44  3     Completed

Executions
 ID          NODE ID     STATE      DESIRED  REV.  CREATED  MODIFIED  COMMENT
 e-fc8b8316  n-d8d2ea18  Completed  Stopped  6     9s ago   2s ago    Accepted job

Execution e-fc8b8316 History
 TIME                 REV.  STATE              TOPIC            EVENT
 2024-07-12 12:43:37  1     New
 2024-07-12 12:43:37  2     AskForBid
 2024-07-12 12:43:37  3     AskForBidAccepted  Requesting Node  Accepted job
 2024-07-12 12:43:37  4     AskForBidAccepted
 2024-07-12 12:43:37  5     BidAccepted
 2024-07-12 12:43:44  6     Completed

Standard Output

 Running - No Comment at Header - 2024-07-12 12:43:37.331093
------------------------------------------------------------

h5py version: 3.11.0
h5py info:
  HDF5 version: 1.14.2
  MPI enabled: False
  ROS3 enabled: False
  Direct VFD enabled: False
File path:
/azureshare/spliced_blc0001020304050607_guppi_57532_10225_HIP56445_0029.gpuspec.
0000.h5

File Structure:
Group:
  Attributes: {'CLASS': 'FILTERBANK', 'VERSION': '1.0'}
  data:
    Dataset:
      Shape: (16, 1, 318230528)
      Dtype: float32
      Attributes: {'DIMENSION_LABELS': ['frequency', 'feed_id', 'time'],
'az_start': np.float64(0.0), 'data_type': np.int64(1), 'fch1':
np.float64(1926.26953125), 'foff': np.float64(-2.835503418452676e-06),
'machine_id': np.int64(20), 'nbits': np.int64(32), 'nchans':
np.int64(318230528), 'nifs': np.int64(1), 'source_name': 'HIP56445', 'src_dej':
np.float64(3.0594441666666667), 'src_raj': np.float64(11.57269388888889),
'telescope_id': np.int64(6), 'tsamp': np.float64(17.986224128), 'tstart':
np.float64(57532.11834490741), 'za_start': np.float64(0.0)}
  mask:
    Dataset:
      Shape: (16, 1, 318230528)
      Dtype: uint8
      Attributes: {'DIMENSION_LABELS': ['frequency', 'feed_id', 'time']}

Data Analysis:

Path: //data
  Type: float32
  Shape: (16, 1, 318230528)
  Size: 5091688448
  Compression: None
  Compression Opts: None

Path: //mask
  Type: uint8
  Shape: (16, 1, 318230528)
  Size: 5091688448
  Compression: None
  Compression Opts: None
  Sample Min: 0
  Sample Max: 0
  Sample Mean: 0.0
wdbaruni commented 4 months ago

Can you give more info about the submitted job, and what the expected output should be?