example_config.toml

[general]
use_gpu = true

# Destination of log messages
# 'stderr' and 'stdout' specify the console.
log_destination = "stderr"
# A path name specifies a file e.g.
# log = "fibad_log.txt"

# Lowest log level to emit.
# As you go down the list, fibad will become more verbose in the log.
#
# log_level = "critical" # Only emit the most severe of errors
# log_level = "error"    # Emit all errors
# log_level = "warning"  # Emit warnings and all errors
log_level = "info"     # Emit informational messages, warnings and all errors
# log_level = "debug"    # Very verbose, emit all log messages.

data_dir = "/home/drew/code/fibad/data/"
results_dir = "./results" # Results get named <verb>-<timestamp> under this directory

[download]
sw = "22asec"
sh = "22asec"
filter = ["HSC-G", "HSC-R", "HSC-I", "HSC-Z", "HSC-Y"]
type = "coadd"
rerun = "pdr3_wide"
username = false
password = false
num_sources = -1 # Values below 1 here indicate all sources in the catalog will be downloaded
offset = 0
concurrent_connections = 4
stats_print_interval = 60
fits_file = "./catalog.fits"

# These control the downloader's HTTP requests and retries
# `retry_wait` How long to wait before retrying a failed HTTP request in seconds. Default 30s
retry_wait = 30
# `retries` How many times to retry a failed HTTP request before moving on to the next one. Default 3 times
retries = 3
# `timepout` How long should we wait to get a full HTTP response from the server. Default 3600s (1hr)
timeout = 3600
# `chunksize` How many sky location rectangles should we request in a single request. Default is 990
chunk_size = 990

# Whether to retrieve the image layer
image = true
# Whether to retrieve the variance layer
variance = false
# Whether to retrieve the mask layer
mask = false

[model]
# The name of the built-in model to use or the libpath to an external model
# e.g. "user_package.submodule.ExternalModel" or "ExampleAutoencoder"
name = "kbmod_ml.models.resnet50.RESNET50"

weights_filepath = "resnet50.pth"
epochs = 10

num_classes = 10


[data_set]
# Name of the built-in data loader to use or the libpath to an external data loader
# e.g. "user_package.submodule.ExternalDataLoader" or "HSCDataLoader"
name = "CifarDataLoader"

[data_loader]
# Pixel dimensions used to crop all images prior to loading. Will prune any images that are too small.
#
# If not provided by user, the default of 'false' scans the directory for the smallest dimensioned files, and 
# uses those pixel dimensions as the crop size.
#
#crop_to = [100,100]
crop_to = false

# Limit data loader to only particular filters when there are more in the data set.
#
# When not provided by the user, the number of filters will be automatically gleaned from the data set.
# Defaults behavior is produced by the false value.
#
#filters = ["HSC-G", "HSC-R", "HSC-I", "HSC-Z", "HSC-Y"]
filters = false

# Default PyTorch DataLoader parameters
batch_size = 10
shuffle = true
num_workers = 10

[predict]
model_weights_file = false
batch_size = 32