How to use PyPrind - 10 common examples

print('* Number of trainable parameters:', tally_parameters(model))

        epoch_str = 'Epoch {0:d}'.format(epoch + 1)
        print('===> ', run_type, epoch_str)
        batch_end = time.time()

        # The tqdm-bar for Jupyter notebook is under development.
        if progress_style == 'tqdm-bar':
            pbar = tqdm(
                total=len(run_iter) // log_freq,
                bar_format='{l_bar}{bar}{postfix}',
                file=sys.stdout)

        # Use the pyprind bar as the default progress bar.
        if progress_style == 'bar':
            pbar = pyprind.ProgBar(len(run_iter) // log_freq, bar_char='█', width=30)

        for batch_idx, batch in enumerate(run_iter):
            batch_start = time.time()
            datatime += batch_start - batch_end

            output = model(batch)

            # from torchviz import make_dot, make_dot_from_trace
            # dot = make_dot(output.mean(), params=dict(model.named_parameters()))
            # pdb.set_trace()

            loss = float('NaN')
            if criterion:
                loss = criterion(output, getattr(batch, label_attr))

            if hasattr(batch, label_attr):

import sys
import pyprind

n = 1000000
mbar = pyprind.ProgBar(n, stream=sys.stdout)
for i in range(n):
    mbar.update()

mper = pyprind.ProgPercent(n, stream=sys.stdout)
for i in range(n):
    mper.update()

mbar2 = pyprind.ProgBar(n, stream='test')
for i in range(n):
    mbar2.update()

for i in pyprind.prog_bar(range(n), stream=sys.stdout):
    # do something
    pass

for i in pyprind.prog_percent(range(n), stream=sys.stdout):
    # do something
    pass

for i in pyprind.prog_bar(range(n), stream='test'):

print('%s\n' % (80 * '='))
print('Testing Basic Percentage Indicator\n')

n = 100
sleeptime = 0.02

perc = pyprind.ProgPercent(n)
for i in range(n):
    time.sleep(sleeptime)
    perc.update()

print('\n%s' % (80 * '='))
print('%s\n' % (80 * '='))
print('Testing stdout Stream\n')

perc = pyprind.ProgPercent(n, stream=sys.stdout)
for i in range(n):
    time.sleep(sleeptime)
    perc.update()

print('\n%s' % (80 * '='))
print('%s\n' % (80 * '='))
print('Testing Percentage Indicator Generator\n')

for i in pyprind.prog_percent(range(n), stream=sys.stdout):
    time.sleep(sleeptime)


print('\n%s' % (80 * '='))
print('%s\n' % (80 * '='))
print('Testing monitor function\n')

def test_generator():
    for i in pyprind.prog_bar(range(n), stream=sys.stdout):
        time.sleep(sleeptime)

import pyprind

n = 1000000
mbar = pyprind.ProgBar(n, stream=sys.stdout)
for i in range(n):
    mbar.update()

mper = pyprind.ProgPercent(n, stream=sys.stdout)
for i in range(n):
    mper.update()

mbar2 = pyprind.ProgBar(n, stream='test')
for i in range(n):
    mbar2.update()

for i in pyprind.prog_bar(range(n), stream=sys.stdout):
    # do something
    pass

for i in pyprind.prog_percent(range(n), stream=sys.stdout):
    # do something
    pass

for i in pyprind.prog_bar(range(n), stream='test'):
    # do something
    pass

for i in range(n):
    mbar.update()

mper = pyprind.ProgPercent(n, stream=sys.stdout)
for i in range(n):
    mper.update()

mbar2 = pyprind.ProgBar(n, stream='test')
for i in range(n):
    mbar2.update()

for i in pyprind.prog_bar(range(n), stream=sys.stdout):
    # do something
    pass

for i in pyprind.prog_percent(range(n), stream=sys.stdout):
    # do something
    pass

for i in pyprind.prog_bar(range(n), stream='test'):
    # do something
    pass

perc.update()

print('\n%s' % (80 * '='))
print('%s\n' % (80 * '='))
print('Testing stdout Stream\n')

perc = pyprind.ProgPercent(n, stream=sys.stdout)
for i in range(n):
    time.sleep(sleeptime)
    perc.update()

print('\n%s' % (80 * '='))
print('%s\n' % (80 * '='))
print('Testing Percentage Indicator Generator\n')

for i in pyprind.prog_percent(range(n), stream=sys.stdout):
    time.sleep(sleeptime)


print('\n%s' % (80 * '='))
print('%s\n' % (80 * '='))
print('Testing monitor function\n')

perc = pyprind.ProgPercent(n, monitor=True)
for i in range(n):
    time.sleep(sleeptime)
    perc.update()
print(perc)


print('\n%s' % (80 * '='))
print('%s\n' % (80 * '='))

log (boolean): whether to log sampling times
            log_prefix (str) : prefix for logger

        Returns: 
            (dict) : A dict of paths of size [meta_batch_size] x (batch_size) x [5] x (max_path_length)
        """

        # initial setup / preparation
        paths = OrderedDict()
        for i in range(self.meta_batch_size):
            paths[i] = []

        n_samples = 0
        running_paths = [_get_empty_running_paths_dict() for _ in range(self.vec_env.num_envs)]

        pbar = ProgBar(self.total_samples)
        policy_time, env_time = 0, 0

        policy = self.policy
        policy.reset(dones=[True] * self.meta_batch_size)

        # initial reset of envs
        obses = self.vec_env.reset()
        
        while n_samples < self.total_samples:
            
            # execute policy
            t = time.time()
            obs_per_task = np.split(np.asarray(obses), self.meta_batch_size)
            actions, agent_infos = policy.get_actions(obs_per_task)
            policy_time += time.time() - t

try:
        with io.open(emb_file, encoding="utf8") as f:
            lines = [line for line in f]
    # If there are malformed lines, read in binary mode
    # and manually decode each word from utf-8
    except:
        logger.warning("Could not read {} as UTF8 file, "
                        "reading file as bytes and skipping "
                        "words with malformed UTF8.".format(emb_file))
        with open(emb_file, 'rb') as f:
            lines = [line for line in f]
        binary_lines = True

    logger.info("Loading vectors from {}".format(emb_file))

    process_bar = pyprind.ProgPercent(len(lines))
    for line in lines:
        process_bar.update()
        # Explicitly splitting on " " is important, so we don't
        # get rid of Unicode non-breaking spaces in the vectors.
        entries = line.rstrip().split(b" " if binary_lines else " ")

        word, entries = entries[0], entries[1:]
        if dim is None and len(entries) > 1:
            dim = len(entries)
            # add pad_word
            itos.append(pad_word)
            vectors.extend(np.zeros(dim, ))
            # add unk_word
            itos.append(unk_word)
            vectors.extend(np.random.uniform(-0.25, 0.25, (dim, )))