|Logo|

tqdm

|DOI-URI| |LICENCE|

tqdm means "progress" in Arabic (taqadum, تقدّم) and an abbreviation for "I love you so much" in Spanish (te quiero demasiado).

Instantly make your loops show a smart progress meter - just wrap any iterable with tqdm(iterable), and you're done!

.. code:: python

from tqdm import tqdm
for i in tqdm(range(10000)):
    ...

76%|████████████████████████████ | 7568/10000 [00:33<00:10, 229.00it/s]

trange(N) can be also used as a convenient shortcut for tqdm(xrange(N)).

|Screenshot| REPL: ptpython <https://github.com/jonathanslenders/ptpython>__

It can also be executed as a module with pipes:

.. code:: sh

$ seq 9999999 | tqdm --unit_scale | wc -l
10.0Mit [00:02, 3.58Mit/s]
9999999
$ 7z a -bd -r backup.7z docs/ | grep Compressing | \
    tqdm --total $(find docs/ -type f | wc -l) --unit files >> backup.log
100%|███████████████████████████████▉| 8014/8014 [01:37<00:00, 82.29files/s]

Overhead is low -- about 60ns per iteration (80ns with tqdm_gui), and is unit tested against performance regression. By comparison, the well established ProgressBar <https://github.com/niltonvolpato/python-progressbar>__ has an 800ns/iter overhead.

In addition to its low overhead, tqdm uses smart algorithms to predict the remaining time and to skip unnecessary iteration displays, which allows for a negligible overhead in most cases.

tqdm works on any platform (Linux, Windows, Mac, FreeBSD, Solaris/SunOS), in any console or in a GUI, and is also friendly with IPython/Jupyter notebooks.

tqdm does not require any library (not even curses!) to run, just a vanilla Python interpreter will do and an environment supporting carriage return \r and line feed \n control characters.

.. contents:: Table of contents :backlinks: top :local:

Installation

Latest PyPI stable release


|PyPI-Status|

.. code:: sh

    pip install tqdm

Latest development release on github

Pull and install in the current directory:

.. code:: sh

pip install -e git+https://github.com/tqdm/[email protected]#egg=tqdm

Latest Conda release


|Conda-Forge-Status|

.. code:: sh

    conda install -c conda-forge tqdm

Changelog
---------

The list of all changes is available either on GitHub's Releases:
|GitHub-Status| or on crawlers such as
`allmychanges.com <https://allmychanges.com/p/python/tqdm/>`_.

Usage
-----

``tqdm`` is very versatile and can be used in a number of ways.
The three main ones are given below.

Iterable-based

Wrap tqdm() around any iterable:

.. code:: python

text = ""
for char in tqdm(["a", "b", "c", "d"]):
    text = text + char

trange(i) is a special optimised instance of tqdm(range(i)):

.. code:: python

for i in trange(100):
    pass

Instantiation outside of the loop allows for manual control over tqdm():

.. code:: python

pbar = tqdm(["a", "b", "c", "d"])
for char in pbar:
    pbar.set_description("Processing %s" % char)

Manual


Manual control on ``tqdm()`` updates by using a ``with`` statement:

.. code:: python

    with tqdm(total=100) as pbar:
        for i in range(10):
            pbar.update(10)

If the optional variable ``total`` (or an iterable with ``len()``) is
provided, predictive stats are displayed.

``with`` is also optional (you can just assign ``tqdm()`` to a variable,
but in this case don't forget to ``del`` or ``close()`` at the end:

.. code:: python

    pbar = tqdm(total=100)
    for i in range(10):
        pbar.update(10)
    pbar.close()

Module

Perhaps the most wonderful use of tqdm is in a script or on the command line. Simply inserting tqdm (or python -m tqdm) between pipes will pass through all stdin to stdout while printing progress to stderr.

The example below demonstrated counting the number of lines in all python files in the current directory, with timing information included.

.. code:: sh

$ time find . -name '*.py' -exec cat \{} \; | wc -l
857365

real    0m3.458s
user    0m0.274s
sys     0m3.325s

$ time find . -name '*.py' -exec cat \{} \; | tqdm | wc -l
857366it [00:03, 246471.31it/s]
857365

real    0m3.585s
user    0m0.862s
sys     0m3.358s

Note that the usual arguments for tqdm can also be specified.

.. code:: sh

$ find . -name '*.py' -exec cat \{} \; |
    tqdm --unit loc --unit_scale --total 857366 >> /dev/null
100%|███████████████████████████████████| 857K/857K [00:04<00:00, 246Kloc/s]

Backing up a large directory?

.. code:: sh

$ 7z a -bd -r backup.7z docs/ | grep Compressing |
    tqdm --total $(find docs/ -type f | wc -l) --unit files >> backup.log
100%|███████████████████████████████▉| 8014/8014 [01:37<00:00, 82.29files/s]

FAQ and Known Issues

The most common issues relate to excessive output on multiple lines, instead of a neat one-line progress bar.

Consoles in general: require support for carriage return (CR, \r).
Nested progress bars:
- Consoles in general: require support for moving cursors up to the previous line. For example, IDLE <https://github.com/tqdm/tqdm/issues/191#issuecomment-230168030>, ConEmu <https://github.com/tqdm/tqdm/issues/254> and PyCharm <https://github.com/tqdm/tqdm/issues/203> (also here <https://github.com/tqdm/tqdm/issues/208> and here <https://github.com/tqdm/tqdm/issues/307>__) lack full support.
- Windows: additionally may require the python module colorama.
Wrapping enumerated iterables: use enumerate(tqdm(...)) instead of tqdm(enumerate(...))`. The same applies tonumpy.ndenumerate. This is because enumerate functions tend to hide the length of iterables. tqdm`` does not.
Wrapping zipped iterables has similar issues due to internal optimisations. tqdm(zip(a, b)) should be replaced with zip(tqdm(a), b) or even zip(tqdm(a), tqdm(b))

If you come across any other difficulties, browse/open issues here <https://github.com/tqdm/tqdm/issues?q=is%3Aissue>__.

Documentation

|PyPI-Versions| |README-Hits| (Since 19 May 2016)

.. code:: python

class tqdm(object):
  """
  Decorate an iterable object, returning an iterator which acts exactly
  like the original iterable, but prints a dynamically updating
  progressbar every time a value is requested.
  """

  def __init__(self, iterable=None, desc=None, total=None, leave=True,
               file=sys.stderr, ncols=None, mininterval=0.1,
               maxinterval=10.0, miniters=None, ascii=None, disable=False,
               unit='it', unit_scale=False, dynamic_ncols=False,
               smoothing=0.3, bar_format=None, initial=0, position=None,
               postfix=None):

Parameters


* iterable  : iterable, optional  
    Iterable to decorate with a progressbar.
    Leave blank to manually manage the updates.
* desc  : str, optional  
    Prefix for the progressbar.
* total  : int, optional  
    The number of expected iterations. If (default: None),
    len(iterable) is used if possible. As a last resort, only basic
    progress statistics are displayed (no ETA, no progressbar).
    If ``gui`` is True and this parameter needs subsequent updating,
    specify an initial arbitrary large positive integer,
    e.g. int(9e9).
* leave  : bool, optional  
    If [default: True], keeps all traces of the progressbar
    upon termination of iteration.
* file  : ``io.TextIOWrapper`` or ``io.StringIO``, optional  
    Specifies where to output the progress messages
    [default: sys.stderr]. Uses ``file.write(str)`` and ``file.flush()``
    methods.
* ncols  : int, optional  
    The width of the entire output message. If specified,
    dynamically resizes the progressbar to stay within this bound.
    If unspecified, attempts to use environment width. The
    fallback is a meter width of 10 and no limit for the counter and
    statistics. If 0, will not print any meter (only stats).
* mininterval  : float, optional  
    Minimum progress display update interval, in seconds [default: 0.1].
* maxinterval  : float, optional  
    Maximum progress display update interval, in seconds [default: 10].
    Automatically adjusts ``miniters`` to correspond to ``mininterval``
    after long display update lag. Only works if ``dynamic_miniters``
    or monitor thread is enabled.
* miniters  : int, optional  
    Minimum progress display update interval, in iterations.
    If 0 and ``dynamic_miniters``, will automatically adjust to equal
    ``mininterval`` (more CPU efficient, good for tight loops).
    If > 0, will skip display of specified number of iterations.
    Tweak this and ``mininterval`` to get very efficient loops.
    If your progress is erratic with both fast and slow iterations
    (network, skipping items, etc) you should set miniters=1.
* ascii  : bool, optional  
    If unspecified or False, use unicode (smooth blocks) to fill
    the meter. The fallback is to use ASCII characters ``1-9 #``.
* disable  : bool, optional  
    Whether to disable the entire progressbar wrapper
    [default: False].
* unit  : str, optional  
    String that will be used to define the unit of each iteration
    [default: it].
* unit_scale  : bool, optional  
    If set, the number of iterations will be reduced/scaled
    automatically and a metric prefix following the
    International System of Units standard will be added
    (kilo, mega, etc.) [default: False].
* dynamic_ncols  : bool, optional  
    If set, constantly alters ``ncols`` to the environment (allowing
    for window resizes) [default: False].
* smoothing  : float, optional  
    Exponential moving average smoothing factor for speed estimates
    (ignored in GUI mode). Ranges from 0 (average speed) to 1
    (current/instantaneous speed) [default: 0.3].
* bar_format  : str, optional  
    Specify a custom bar string formatting. May impact performance.
    If unspecified, will use '{l_bar}{bar}{r_bar}', where l_bar is
    '{desc}{percentage:3.0f}%|' and r_bar is
    '| {n_fmt}/{total_fmt} [{elapsed}<{remaining}, {rate_fmt}]'
    Possible vars: bar, n, n_fmt, total, total_fmt, percentage,
    rate, rate_fmt, elapsed, remaining, l_bar, r_bar, desc.
* initial  : int, optional  
    The initial counter value. Useful when restarting a progress
    bar [default: 0].
* position  : int, optional  
    Specify the line offset to print this bar (starting from 0)
    Automatic if unspecified.
    Useful to manage multiple bars at once (eg, from threads).
* postfix  : dict, optional  
    Specify additional stats to display at the end of the bar.

Extra CLI Options

delim : chr, optional
Delimiting character [default: '\n']. Use '\0' for null. N.B.: on Windows systems, Python converts '\n' to '\r\n'.
buf_size : int, optional
String buffer size in bytes [default: 256] used when delim is specified.
bytes : bool, optional
If true, will count bytes and ignore delim.

Returns


* out  : decorated iterator.

.. code:: python

      def update(self, n=1):
          """
          Manually update the progress bar, useful for streams
          such as reading files.
          E.g.:
          >>> t = tqdm(total=filesize) # Initialise
          >>> for current_buffer in stream:
          ...    ...
          ...    t.update(len(current_buffer))
          >>> t.close()
          The last line is highly recommended, but possibly not necessary if
          ``t.update()`` will be called in such a way that ``filesize`` will be
          exactly reached and printed.

          Parameters
          ----------
          n  : int
              Increment to add to the internal counter of iterations
              [default: 1].
          """

      def close(self):
          """
          Cleanup and (if leave=False) close the progressbar.
          """

      def clear(self):
          """
          Clear current bar display
          """

      def refresh(self):
          """
          Force refresh the display of this bar
          """

      def write(cls, s, file=sys.stdout, end="\n"):
          """
          Print a message via tqdm (without overlap with bars)
          """

      def set_description(self, desc=None):
          """
          Set/modify description of the progress bar.
          """

      def set_postfix(self, **kwargs):
          """
          Set/modify postfix (additional stats)
          with automatic formatting based on datatype.
          """

    def trange(*args, **kwargs):
        """
        A shortcut for tqdm(xrange(*args), **kwargs).
        On Python3+ range is used instead of xrange.
        """

    class tqdm_gui(tqdm):
        """
        Experimental GUI version of tqdm!
        """

    def tgrange(*args, **kwargs):
        """
        Experimental GUI version of trange!
        """

    class tqdm_notebook(tqdm):
        """
        Experimental IPython/Jupyter Notebook widget using tqdm!
        """

    def tnrange(*args, **kwargs):
        """
        Experimental IPython/Jupyter Notebook widget using tqdm!
        """

Examples and Advanced Usage
---------------------------

- See the `examples <https://github.com/tqdm/tqdm/tree/master/examples>`__
  folder;
- import the module and run ``help()``, or
- consult the `wiki <https://github.com/tqdm/tqdm/wiki>`__.
    - this has an `excellent article <https://github.com/tqdm/tqdm/wiki/How-to-make-a-great-Progress-Bar>`__ on how to make a **great** progressbar.

Description and additional stats

Custom information can be displayed and updated dynamically on tqdm bars with the desc and postfix arguments:

.. code:: python

from tqdm import trange
from random import random, randint
from time import sleep

t = trange(100)
for i in t:
    # Description will be displayed on the left
    t.set_description('GEN %i' % i)
    # Postfix will be displayed on the right, and will format automatically 
    # based on argument's datatype
    t.set_postfix(loss=random(), gen=randint(1,999), str='h', lst=[1, 2])
    sleep(0.1)

Nested progress bars


``tqdm`` supports nested progress bars. Here's an example:

.. code:: python

    from tqdm import trange
    from time import sleep

    for i in trange(10, desc='1st loop'):
        for j in trange(5, desc='2nd loop', leave=False):
            for k in trange(100, desc='3nd loop'):
                sleep(0.01)

On Windows `colorama <https://github.com/tartley/colorama>`__ will be used if
available to produce a beautiful nested display.

For manual control over positioning (e.g. for multi-threaded use),
you may specify `position=n` where `n=0` for the outermost bar,
`n=1` for the next, and so on.

Hooks and callbacks

tqdm can easily support callbacks/hooks and manual updates. Here's an example with urllib:

urllib.urlretrieve documentation

| [...]
| If present, the hook function will be called once
| on establishment of the network connection and once after each
  block read
| thereafter. The hook will be passed three arguments; a count of
  blocks
| transferred so far, a block size in bytes, and the total size of
  the file.
| [...]

.. code:: python

import urllib
from tqdm import tqdm

def my_hook(t):
  """
  Wraps tqdm instance. Don't forget to close() or __exit__()
  the tqdm instance once you're done with it (easiest using `with` syntax).

  Example
  -------

  >>> with tqdm(...) as t:
  ...     reporthook = my_hook(t)
  ...     urllib.urlretrieve(..., reporthook=reporthook)

  """
  last_b = [0]

  def inner(b=1, bsize=1, tsize=None):
    """
    b  : int, optional
        Number of blocks just transferred [default: 1].
    bsize  : int, optional
        Size of each block (in tqdm units) [default: 1].
    tsize  : int, optional
        Total size (in tqdm units). If [default: None] remains unchanged.
    """
    if tsize is not None:
        t.total = tsize
    t.update((b - last_b[0]) * bsize)
    last_b[0] = b
  return inner

eg_link = 'http://www.doc.ic.ac.uk/~cod11/matryoshka.zip'
with tqdm(unit='B', unit_scale=True, miniters=1,
          desc=eg_link.split('/')[-1]) as t:  # all optional kwargs
    urllib.urlretrieve(eg_link, filename='/dev/null',
                       reporthook=my_hook(t), data=None)

It is recommend to use miniters=1 whenever there is potentially large differences in iteration speed (e.g. downloading a file over a patchy connection).

Pandas Integration


Due to popular demand we've added support for ``pandas`` -- here's an example
for ``DataFrame.progress_apply`` and ``DataFrameGroupBy.progress_apply``:

.. code:: python

    import pandas as pd
    import numpy as np
    from tqdm import tqdm

    df = pd.DataFrame(np.random.randint(0, 100, (100000, 6)))

    # Register `pandas.progress_apply` and `pandas.Series.map_apply` with `tqdm`
    # (can use `tqdm_gui`, `tqdm_notebook`, optional kwargs, etc.)
    tqdm.pandas(desc="my bar!")

    # Now you can use `progress_apply` instead of `apply`
    # and `progress_map` instead of `map`
    df.progress_apply(lambda x: x**2)
    # can also groupby:
    # df.groupby(0).progress_apply(lambda x: x**2)

In case you're interested in how this works (and how to modify it for your
own callbacks), see the
`examples <https://github.com/tqdm/tqdm/tree/master/examples>`__
folder or import the module and run ``help()``.

IPython/Jupyter Integration

IPython/Jupyter is supported via the tqdm_notebook submodule:

.. code:: python

from tqdm import tnrange, tqdm_notebook
from time import sleep

for i in tnrange(10, desc='1st loop'):
    for j in tqdm_notebook(xrange(100), desc='2nd loop'):
        sleep(0.01)

In addition to tqdm features, the submodule provides a native Jupyter widget (compatible with IPython v1-v4 and Jupyter), fully working nested bars and color hints (blue: normal, green: completed, red: error/interrupt, light blue: no ETA); as demonstrated below.

Writing messages


Since ``tqdm`` uses a simple printing mechanism to display progress bars,
you should not write any message in the terminal using ``print()``.

To write messages in the terminal without any collision with ``tqdm`` bar
display, a ``.write()`` method is provided:

.. code:: python

    from tqdm import tqdm, trange
    from time import sleep

    bar = trange(10)
    for i in bar:
        # Print using tqdm class method .write()
        sleep(0.1)
        if not (i % 3):
            tqdm.write("Done task %i" % i)
        # Can also use bar.write()

By default, this will print to standard output ``sys.stdout``. but you can
specify any file-like object using the ``file`` argument. For example, this
can be used to redirect the messages writing to a log file or class.

Redirecting writing

If using a library that can print messages to the console, editing the library by replacing print() with tqdm.write() may not be desirable. In that case, redirecting sys.stdout to tqdm.write() is an option.

To redirect sys.stdout, create a file-like class that will write any input string to tqdm.write(), and supply the arguments file=sys.stdout, dynamic_ncols=True.

A reusable canonical example is given below:

.. code:: python

from time import sleep

import contextlib
import sys

from tqdm import tqdm

class DummyTqdmFile(object):
    """Dummy file-like that will write to tqdm"""
    file = None
    def __init__(self, file):
        self.file = file

    def write(self, x):
        # Avoid print() second call (useless \n)
        if len(x.rstrip()) > 0:
            tqdm.write(x, file=self.file)

@contextlib.contextmanager
def stdout_redirect_to_tqdm():
    save_stdout = sys.stdout
    try:
        sys.stdout = DummyTqdmFile(sys.stdout)
        yield save_stdout
    # Relay exceptions
    except Exception as exc:
        raise exc
    # Always restore sys.stdout if necessary
    finally:
        sys.stdout = save_stdout

def blabla():
    print("Foo blabla")

# Redirect stdout to tqdm.write() (don't forget the `as save_stdout`)
with stdout_redirect_to_tqdm() as save_stdout:
    # tqdm call need to specify sys.stdout, not sys.stderr (default)
    # and dynamic_ncols=True to autodetect console width
    for _ in tqdm(range(3), file=save_stdout, dynamic_ncols=True):
        blabla()
        sleep(.5)

# After the `with`, printing is restored
print('Done!')

Monitoring thread, intervals and miniters



``tqdm`` implements a few tricks to to increase efficiency and reduce overhead.

1. Avoid unnecessary frequent bar refreshing: ``mininterval`` defines how long
   to wait between each refresh. ``tqdm`` always gets updated in the background,
   but it will diplay only every ``mininterval``.
2. Reduce number of calls to check system clock/time.
3. ``mininterval`` is more intuitive to configure than ``miniters``.
   A clever adjustment system ``dynamic_miniters`` will automatically adjust
   ``miniters`` to the amount of iterations that fit into time ``mininterval``.
   Essentially, ``tqdm`` will check if it's time to print without actually
   checking time. This behavior can be still be bypassed by manually setting
   ``miniters``.

However, consider a case with a combination of fast and slow iterations.
After a few fast iterations, ``dynamic_miniters`` will set ``miniters`` to a
large number. When interation rate subsequently slows, ``miniters`` will
remain large and thus reduce display update frequency. To address this:

4. ``maxinterval`` defines the maximum time between display refreshes.
   A concurrent monitoring thread checks for overdue updates and forces one
   where necessary.

The monitoring thread should not have a noticeable overhead, and guarantees
updates at least every 10 seconds by default.
This value can be directly changed by setting the ``monitor_interval`` of
any ``tqdm`` instance (i.e. ``t = tqdm.tqdm(...); t.monitor_interval = 2``).
The monitor thread may be disabled application-wide by setting
``tqdm.tqdm.monitor_interval = 0`` before instantiatiation of any ``tqdm`` bar.

Contributions
-------------

All source code is hosted on `GitHub <https://github.com/tqdm/tqdm>`__.
Contributions are welcome.

See the
`CONTRIBUTING <https://raw.githubusercontent.com/tqdm/tqdm/master/CONTRIBUTING.md>`__
file for more information.

LICENCE
-------

Open Source (OSI approved): |LICENCE|

Citation information: |DOI-URI|

Authors
-------

Ranked by contributions.

-  Casper da Costa-Luis (casperdcl)
-  Stephen Larroque (lrq3000)
-  Hadrien Mary (hadim)
-  Noam Yorav-Raphael (noamraph)*
-  Ivan Ivanov (obiwanus)
-  Mikhail Korobov (kmike)

`*` Original author

|README-Hits| (Since 19 May 2016)

.. |Logo| image:: https://raw.githubusercontent.com/tqdm/tqdm/master/images/logo.gif
.. |Screenshot| image:: https://raw.githubusercontent.com/tqdm/tqdm/master/images/tqdm.gif
.. |Build-Status| image:: https://travis-ci.org/tqdm/tqdm.svg?branch=master
   :target: https://travis-ci.org/tqdm/tqdm
.. |Coverage-Status| image:: https://coveralls.io/repos/tqdm/tqdm/badge.svg
   :target: https://coveralls.io/r/tqdm/tqdm
.. |Branch-Coverage-Status| image:: https://codecov.io/github/tqdm/tqdm/coverage.svg?branch=master
   :target: https://codecov.io/github/tqdm/tqdm?branch=master
.. |Codacy-Grade| image:: https://api.codacy.com/project/badge/Grade/3f965571598f44549c7818f29cdcf177
   :target: https://www.codacy.com/app/tqdm/tqdm?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=tqdm/tqdm&amp;utm_campaign=Badge_Grade
.. |GitHub-Status| image:: https://img.shields.io/github/tag/tqdm/tqdm.svg?maxAge=2592000
   :target: https://github.com/tqdm/tqdm/releases
.. |GitHub-Forks| image:: https://img.shields.io/github/forks/tqdm/tqdm.svg
   :target: https://github.com/tqdm/tqdm/network
.. |GitHub-Stars| image:: https://img.shields.io/github/stars/tqdm/tqdm.svg
   :target: https://github.com/tqdm/tqdm/stargazers
.. |PyPI-Status| image:: https://img.shields.io/pypi/v/tqdm.svg
   :target: https://pypi.python.org/pypi/tqdm
.. |PyPI-Downloads| image:: https://img.shields.io/pypi/dm/tqdm.svg
   :target: https://pypi.python.org/pypi/tqdm
.. |PyPI-Versions| image:: https://img.shields.io/pypi/pyversions/tqdm.svg
   :target: https://pypi.python.org/pypi/tqdm
.. |Conda-Forge-Status| image:: https://anaconda.org/conda-forge/tqdm/badges/version.svg
   :target: https://anaconda.org/conda-forge/tqdm
.. |LICENCE| image:: https://img.shields.io/pypi/l/tqdm.svg
   :target: https://raw.githubusercontent.com/tqdm/tqdm/master/LICENCE
.. |DOI-URI| image:: https://zenodo.org/badge/21637/tqdm/tqdm.svg
   :target: https://zenodo.org/badge/latestdoi/21637/tqdm/tqdm
.. |Screenshot-Jupyter1| image:: https://raw.githubusercontent.com/tqdm/tqdm/master/images/tqdm-jupyter-1.gif
.. |Screenshot-Jupyter2| image:: https://raw.githubusercontent.com/tqdm/tqdm/master/images/tqdm-jupyter-2.gif
.. |Screenshot-Jupyter3| image:: https://raw.githubusercontent.com/tqdm/tqdm/master/images/tqdm-jupyter-3.gif
.. |README-Hits| image:: https://caspersci.uk.to/cgi-bin/hits.cgi?q=tqdm&style=social&r=https://github.com/tqdm/tqdm&l=https://caspersci.uk.to/images/tqdm.png&f=https://raw.githubusercontent.com/tqdm/tqdm/master/images/logo.gif
   :target: https://caspersci.uk.to/cgi-bin/hits.cgi?q=tqdm&a=plot&r=https://github.com/tqdm/tqdm&l=https://caspersci.uk.to/images/tqdm.png&f=https://raw.githubusercontent.com/tqdm/tqdm/master/images/logo.gif&style=social

tqdm 0,1,2,0,5,4,4,0

tqdm

Installation

FAQ and Known Issues

Documentation

Related Repositories

deconvfaces

DQN-tensorflow

deep-rl-tensorflow

tqdm-ruby

moviemon

Top Contributors

Releases