sparkocr.transformers.visual_encoder_decoder.utils#

Classes#

Functions#

class MetricLogger(delimiter='\t')#

Bases: object

delimiter = '\t'#

meters#

add_meter(name, meter)#

log_every(iterable, print_freq, header=None)#

synchronize_between_processes()#

update(**kwargs)#

class NativeScalerWithGradNormCount#

state_dict_key = 'amp_scaler'#

load_state_dict(state_dict)#

state_dict()#

class SmoothedValue(window_size=20, fmt=None)#

Bases: object

Track a series of values and provide access to smoothed values over a window or the global series average.

count = 0#

deque#

fmt = None#

total = 0.0#

synchronize_between_processes()#

Warning: does not synchronize the deque!

update(value, n=1)#

class TensorboardLogger(log_dir)#

Bases: object

step = 0#

writer#

flush()#

set_step(step=None)#

update(head='scalar', step=None, **kwargs)#

auto_load_model(args, model, model_without_ddp, optimizer, loss_scaler, model_ema=None)#

cosine_scheduler(base_value, final_value, epochs, niter_per_ep, warmup_epochs=0, start_warmup_value=0, warmup_steps=-1)#

create_ds_config(args)#

get_grad_norm_(parameters, norm_type: float = 2.0) → torch.Tensor#

get_rank()#

get_world_size()#

init_distributed_mode(args)#

is_dist_avail_and_initialized()#

is_main_process()#

load_state_dict(model, state_dict, prefix='', ignore_missing='relative_position_index')#

save_model(args, epoch, model, model_without_ddp, optimizer, loss_scaler, model_ema=None)#

save_on_master(*args, **kwargs)#

setup_for_distributed(is_master)#

This function disables printing when not in master process