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Developer Docs
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Section Navigation
adapters
transforms
AsSet
AsTimeSeries
Broadcast
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Constrain
ConvertDType
Drop
ElementwiseTransform
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Log
MapTransform
NumpyTransform
OneHot
Rename
Scale
SerializableCustomTransform
Shift
Split
Sqrt
Standardize
ToArray
ToDict
Transform
Adapter
approximators
Approximator
ContinuousApproximator
ModelComparisonApproximator
PointApproximator
datasets
DiskDataset
OfflineDataset
OnlineDataset
RoundsDataset
diagnostics
calibration_ecdf
calibration_ecdf_from_quantiles
calibration_error
calibration_histogram
loss
mc_calibration
mc_confusion_matrix
mmd_hypothesis_test
pairs_posterior
pairs_samples
posterior_contraction
recovery
recovery_from_estimates
root_mean_squared_error
z_score_contraction
distributions
DiagonalNormal
DiagonalStudentT
Distribution
Mixture
experimental
CIF
ContinuousTimeConsistencyModel
FreeFormFlow
links
Ordered
OrderedQuantiles
PositiveDefinite
metrics
functional
maximum_mean_discrepancy
root_mean_squared_error
MaximumMeanDiscrepancy
RootMeanSquaredError
networks
ConsistencyModel
CouplingFlow
DeepSet
FlowMatching
FusionTransformer
InferenceNetwork
MLP
PointInferenceNetwork
SetTransformer
SummaryNetwork
TimeSeriesNetwork
TimeSeriesTransformer
scores
MeanScore
MedianScore
MultivariateNormalScore
NormedDifferenceScore
ParametricDistributionScore
QuantileScore
ScoringRule
simulators
make_simulator
BernoulliGLM
BernoulliGLMRaw
GaussianLinear
GaussianLinearUniform
GaussianMixture
HierarchicalSimulator
InverseKinematics
LambdaSimulator
LotkaVolterra
ModelComparisonSimulator
SIR
SLCP
SLCPDistractors
SequentialSimulator
Simulator
TwoMoons
types
utils
keras_utils
inverse_shifted_softplus
inverse_softplus
shifted_softplus
logging
critical
debug
error
exception
info
log
warn_once
warning
numpy_utils
inverse_shifted_softplus
inverse_sigmoid
inverse_softplus
one_hot
shifted_softplus
softplus
add_metric
add_titles_and_labels
batched_call
calibration_curve
check_estimates_prior_shapes
check_lengths_same
concatenate_valid
confusion_matrix
convert_args
convert_kwargs
deserialize_value_or_type
detailed_loss_callback
devices
expand
expand_as
expand_left
expand_left_as
expand_left_to
expand_right
expand_right_as
expand_right_to
expand_tile
expand_to
fill_triangular_matrix
filter_kwargs
find_batch_size
find_distribution
find_inference_network
find_memory_budget
find_network
find_permutation
find_pooling
find_recurrent_net
find_summary_network
format_bytes
integrate
jacobian
jacobian_trace
jvp
layer_kwargs
make_quadratic
model_kwargs
optimal_transport
pad
parse_bytes
pickle_load
prepare_plot_data
prettify_subplots
searchsorted
sequential_kwargs
serialize_value_or_type
simultaneous_ecdf_bands
size_of
split_arrays
split_tensors
squeeze_inner_estimates_dict
stack_valid
tile_axis
tree_concatenate
tree_stack
vjp
weighted_mean
workflows
BasicWorkflow
wrappers
mamba
mamba
Mamba
mamba_block
MambaBlock
API Reference
utils
logging
debug
debug
#
bayesflow.utils.logging.
debug
(
msg
,
*
args
,
**
kwargs
)
[source]
#
On this page
debug()
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