utils

Classes

AddTensors	Adds all its inputs together.
MinMaxNormalize	Albumentations transform that normalizes image to desired min and max values.
ONNXRuntimeAdapter	Wrapper around ONNX-runtime that behaves like a PyTorch nn.Module.
Parallel	Passes inputs through multiple `nn.Module`s in parallel. Returns a tuple of outputs.
SplitTensor	Wrapper around torch.split

Functions

adjust_conv_channels(old_conv, in_channels)
aggregate_metrics(outputs[, exclude_keys])	Aggregate the output of validate_step at the end of the epoch.
channel_groups_to_imgs(x, channel_groups)
compute_conf_mat(out, y, num_labels)
compute_conf_mat_metrics(conf_mat, label_names)
deserialize_albumentation_transform(tf_dict)	Deserialize an albumentations transform serialized by serialize_albumentation_transform().
get_learner_config_from_bundle_dir(...)
log_metrics_to_csv(csv_path, metrics)	Append epoch metrics to CSV file.
log_system_details()	Log some system details.
plot_channel_groups(axs, imgs, channel_groups)
serialize_albumentation_transform(tf[, ...])	Serialize an albumentations transform to a dict.
validate_albumentation_transform(tf_dict)	Validate a serialized albumentation transform by attempting to deserialize it.