Rename bink -> torchbearer (#205)

pytorchbearer · Jul 18, 2018 · 17d90be · 17d90be
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diff --git a/.travis.yml b/.travis.yml
@@ -7,6 +7,6 @@ install:
   - python setup.py develop
 # command to run tests
 script:
-  - nosetests tests -v --with-coverage --cover-package=bink
+  - nosetests tests -v --with-coverage --cover-package=torchbearer
 after_success:
   - bash <(curl -s https://codecov.io/bash)
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -12,7 +12,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Changed the order of the arguments to the lambda function in the EpochLambda metric for consistency with pytorch and other metrics
 - Checkpointers now create directory to savepath if it doesn't exist
 - Changed the 'on_forward_criterion' callback method to 'on_criterion'
-- Changed epoch number in printer callbacks to be consistent with the rest of bink
+- Changed epoch number in printer callbacks to be consistent with the rest of torchbearer
 ### Deprecated
 ### Removed
 ### Fixed
@@ -24,8 +24,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ## [0.1.2] - 2018-06-08
 ### Added
-- Added support for tuple outputs from generators, bink expects output to be length 2. Specifically, x, y = next() is possible, where x and y can be tuples of arbitrary size or depth
-- Added support for torch dtypes in bink Model.to(...)
+- Added support for tuple outputs from generators, torchbearer expects output to be length 2. Specifically, x, y = next() is possible, where x and y can be tuples of arbitrary size or depth
+- Added support for torch dtypes in torchbearer Model.to(...)
 - Added pickle_module and pickle_protocol to checkpointers for consistency with torch.save
 ### Changed
 - Changed the learning rate scheduler callbacks to no longer require an optimizer and to have the proper arguments

diff --git a/Example/example.py b/Example/example.py
@@ -7,9 +7,9 @@
 from torch.utils.data import DataLoader
 
 from Example import inception_network as nm
-from bink import Model
-from bink.metrics import RocAucScore
-from bink.callbacks import EarlyStopping, TensorBoard, L2WeightDecay, L1WeightDecay
+from torchbearer import Model
+from torchbearer.metrics import RocAucScore
+from torchbearer.callbacks import EarlyStopping, TensorBoard, L2WeightDecay, L1WeightDecay
 
 ####### Paths #######
 dataset_path = '/home/matt/datasets/cifar'

diff --git a/Jenkinsfile b/Jenkinsfile
diff --git a/README.md b/README.md
@@ -1,5 +1,5 @@
-# PyBink
+# torchbearer
 
-[![Build Status](https://travis-ci.com/ecs-vlc/PyBink.svg?branch=master)](https://travis-ci.com/ecs-vlc/PyBink) [![codecov](https://codecov.io/gh/ecs-vlc/PyBink/branch/master/graph/badge.svg)](https://codecov.io/gh/ecs-vlc/PyBink) [![Documentation Status](https://readthedocs.org/projects/pybink/badge/?version=latest)](https://pybink.readthedocs.io/en/latest/?badge=latest)
+[![Build Status](https://travis-ci.com/ecs-vlc/torchbearer.svg?branch=master)](https://travis-ci.com/ecs-vlc/torchbearer) [![codecov](https://codecov.io/gh/ecs-vlc/torchbearer/branch/master/graph/badge.svg)](https://codecov.io/gh/ecs-vlc/torchbearer) [![Documentation Status](https://readthedocs.org/projects/pytorchbearer/badge/?version=latest)](https://pytorchbearer.readthedocs.io/en/latest/?badge=latest)
 
-bink: A model training library for researchers using PyTorch
+torchbearer: A model training library for researchers using PyTorch
diff --git a/docs/code/callbacks.rst b/docs/code/callbacks.rst
@@ -1,6 +1,6 @@
-bink.callbacks
+torchbearer.callbacks
 ====================================
 
-..  automodule:: bink.callbacks
+..  automodule:: torchbearer.callbacks
 	:members:
 	:undoc-members:
diff --git a/docs/code/main.rst b/docs/code/main.rst
@@ -1,6 +1,6 @@
-bink
+torchbearer
 ====================================
 
-..  automodule:: bink
+..  automodule:: torchbearer
 	:members:
 	:undoc-members:
diff --git a/docs/code/metrics.rst b/docs/code/metrics.rst
@@ -1,6 +1,6 @@
-bink.metrics
+torchbearer.metrics
 ====================================
 
-..  automodule:: bink.metrics
+..  automodule:: torchbearer.metrics
 	:members:
 	:undoc-members:
diff --git a/docs/conf.py b/docs/conf.py
@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 #
-# PyBink documentation build configuration file, created by
+# torchbearer documentation build configuration file, created by
 # sphinx-quickstart on Mon Jul 16 14:35:09 2018.
 #
 # This file is execfile()d with the current directory set to its
@@ -59,7 +59,7 @@ def __getattr__(cls, name):
 master_doc = 'index'
 
 # General information about the project.
-project = 'PyBink'
+project = 'torchbearer'
 copyright = '2018, Ethan Harris and Matthew Painter'
 author = 'Ethan Harris and Matthew Painter'
 
@@ -128,7 +128,7 @@ def __getattr__(cls, name):
 # -- Options for HTMLHelp output ------------------------------------------
 
 # Output file base name for HTML help builder.
-htmlhelp_basename = 'PyBinkdoc'
+htmlhelp_basename = 'torchbearerdoc'
 
 
 # -- Options for LaTeX output ---------------------------------------------
@@ -155,7 +155,7 @@ def __getattr__(cls, name):
 # (source start file, target name, title,
 #  author, documentclass [howto, manual, or own class]).
 latex_documents = [
-    (master_doc, 'PyBink.tex', 'PyBink Documentation',
+    (master_doc, 'torchbearer.tex', 'torchbearer Documentation',
      'Ethan Harris and Matthew Painter', 'manual'),
 ]
 
@@ -165,7 +165,7 @@ def __getattr__(cls, name):
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
 man_pages = [
-    (master_doc, 'pybink', 'PyBink Documentation',
+    (master_doc, 'pytorchbearer', 'torchbearer Documentation',
      [author], 1)
 ]
 
@@ -176,8 +176,8 @@ def __getattr__(cls, name):
 # (source start file, target name, title, author,
 #  dir menu entry, description, category)
 texinfo_documents = [
-    (master_doc, 'PyBink', 'PyBink Documentation',
-     author, 'PyBink', 'One line description of project.',
+    (master_doc, 'torchbearer', 'torchbearer Documentation',
+     author, 'torchbearer', 'One line description of project.',
      'Miscellaneous'),
 ]
 

diff --git a/docs/examples/quickstart.rst b/docs/examples/quickstart.rst
@@ -1,19 +1,19 @@
 Quickstart Guide
 ====================================
 
-This guide will give a quick intro to training PyTorch models with PyBink. We'll start by loading in some data and defining a model, then we'll train it for a few epochs and see how well it does.
+This guide will give a quick intro to training PyTorch models with torchbearer. We'll start by loading in some data and defining a model, then we'll train it for a few epochs and see how well it does.
 
 Defining the Model
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Let's get using bink. Here's some data from Cifar10 and a simple 3 layer strided CNN:
+Let's get using torchbearer. Here's some data from Cifar10 and a simple 3 layer strided CNN:
 
 .. literalinclude:: ../../examples/quickstart.py
    :language: python
    :lines: 7-45
 
 Typically we would need a training loop and a series of calls to backward, step etc.
-Instead, with bink, we can define our optimiser and some metrics (just 'acc' and 'loss' for now) and let it do the work.
+Instead, with torchbearer, we can define our optimiser and some metrics (just 'acc' and 'loss' for now) and let it do the work.
 
 Training on Cifar10
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

diff --git a/docs/index.rst b/docs/index.rst
@@ -1,9 +1,9 @@
-.. PyBink documentation master file, created by
+.. torchbearer documentation master file, created by
    sphinx-quickstart on Mon Jul 16 14:35:09 2018.
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-Welcome to PyBink's documentation!
+Welcome to torchbearer's documentation!
 ====================================
 
 .. toctree::

diff --git a/examples/quickstart.py b/examples/quickstart.py
@@ -47,7 +47,7 @@ def forward(self, x):
 optimizer = optim.Adam(filter(lambda p: p.requires_grad, model.parameters()), lr=0.001)
 loss = nn.CrossEntropyLoss()
 
-from bink import Model
+from torchbearer import Model
 
-bink_model = Model(model, optimizer, loss, metrics=['acc', 'loss']).to('cuda')
-bink_model.fit_generator(traingen, epochs=10, validation_generator=testgen)
+torchbearer_model = Model(model, optimizer, loss, metrics=['acc', 'loss']).to('cuda')
+torchbearer_model.fit_generator(traingen, epochs=10, validation_generator=testgen)
diff --git a/setup.py b/setup.py
@@ -1,11 +1,11 @@
 from setuptools import setup
 
 setup(
-    name='bink',
+    name='torchbearer',
     version='0.1.3',
-    packages=['bink', 'bink.metrics', 'bink.callbacks', 'tests', 'tests.metrics', 'tests.callbacks'],
-    url='https://github.com/ecs-vlc/PyBink',
-    download_url='https://github.com/ecs-vlc/PyBink/archive/v0.1.3.tar.gz',
+    packages=['torchbearer', 'torchbearer.metrics', 'torchbearer.callbacks', 'tests', 'tests.metrics', 'tests.callbacks'],
+    url='https://github.com/ecs-vlc/torchbearer',
+    download_url='https://github.com/ecs-vlc/torchbearer/archive/v0.1.3.tar.gz',
     license='GPL-3.0',
     author='Matt Painter',
     author_email='mp2u16@ecs.soton.ac.uk',

diff --git a/tests/callbacks/test_callbacks.py b/tests/callbacks/test_callbacks.py
@@ -1,7 +1,7 @@
 from unittest import TestCase
 from unittest.mock import MagicMock
 
-from bink.callbacks import CallbackList
+from torchbearer.callbacks import CallbackList
 
 
 class TestCallbackList(TestCase):