add everything

Author: SkafteNicki

README.md

@@ -1,2 +1,58 @@
-# torchplot
-Plotting pytorch tensors made easy!
+# torchplot - Plotting pytorch tensors made easy!
+
+Ask yourself the following:
+* Are you using `matplotlib.pyplot` to plot pytorch tensors?
+* Do you forget to call `.cpu().detach().numpy()` everytime you want to plot a tensor
+
+Then `torchplot` may be something for you. `torchplot` is a simple drop-in replacement
+for plotting pytorch tensors. We simply override every `matplotlib.pyplot` function such
+that pytorch tensors are automatically converted.
+
+Simply just change your default `matplotlib` import statement:
+
+
+Instead of
+```
+from matplotlib.pyplot import *
+```
+use
+```
+from torchplot import *
+```
+and instead of
+```
+import matplotlib.pyplot as plt
+```
+use
+```
+import torchplot as plt
+```
+Herafter, then you can remove every `.cpu().detach().numpy()` (or variations heroff) from
+your code and everything should just work. If you do not want to mix implementations, 
+we recommend importing `torchplot` as seperaly package:
+```
+import torchplot as tp
+```
+
+## Installation
+Simple as
+```
+pip install torchplot
+```
+
+## Example
+
+```
+# lets make a scatter plot of two pytorch variables
+import torch
+import torchplot as plt
+x = torch.randn(100, requires_grad=True, device='cuda')
+y = torch.randn(100, requires_grad=True, device='cuda')
+plt.plot(x, y, '.') # easy and simple
+```
+
+
+
+
+
+

pyproject.toml

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+[build-system]
+requires = [
+    "setuptools",
+    "wheel",
+]
+
+[tool.autopep8]
+max_line_length = 120
+ignore = ["W504", "W504", "E402", "E731", "C40", "E741", "F40", "F841"]
+
+[tool.black]
+# https://github.com/psf/black
+line-length = 120
+target-version = ["py38"]
+exclude = "(.eggs|.git|.hg|.mypy_cache|.nox|.tox|.venv|.svn|_build|buck-out|build|dist|docs)"
+
+[tool.isort]
+known_first_party = [
+    "benchmarks",
+    "docs",
+    "pl_examples",
+    "pytorch_lightning",
+    "tests",
+]
+skip_glob = [
+    "pytorch_lightning/accelerators/*",
+    "pytorch_lightning/callbacks/*",
+    "pytorch_lightning/cluster_environments/*",
+    "pytorch_lightning/core/*",
+    "pytorch_lightning/distributed/*",
+    "pytorch_lightning/loggers/*",
+    "pytorch_lightning/metrics/*",
+    "pytorch_lightning/overrides/*",
+    "pytorch_lightning/plugins/*",
+    "pytorch_lightning/profiler/*",
+    "pytorch_lightning/trainer/*",
+    "pytorch_lightning/tuner/*",
+    "pytorch_lightning/utilities/*",
+    "tests/backends/*",
+    "tests/base/*",
+    "tests/callbacks/*",
+    "tests/checkpointing/*",
+    "tests/core/*",
+    "tests/loggers/*",
+    "tests/metrics/*",
+    "tests/models/*",
+    "tests/plugins/*",
+    "tests/trainer/*",
+    "tests/tuner/*",
+    "tests/utilities/*",
+]
+profile = "black"
+line_length = 120
+force_sort_within_sections = "False"
+order_by_type = "False"

requirements.txt

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+torch>=1.3
+numpy>=1.16.4

setup.cfg

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+[metadata]
+description-file = README.md
+
+[flake8]
+# TODO: this should be 88 or 100 according PEP8
+max-line-length = 120
+exclude = .tox,*.egg,build,temp
+select = E,W,F
+doctests = True
+verbose = 2
+# https://pep8.readthedocs.io/en/latest/intro.html#error-codes
+format = pylint
+ignore = E731,W504,F401,F841,E722,W503
+
+[build_sphinx]
+source-dir = doc/source
+build-dir  = doc/build
+all_files  = 1
+
+[upload_sphinx]
+upload-dir = doc/build/html

setup.py

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+# Copyright The GeoML Team
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import os
+from io import open
+
+from setuptools import setup, find_packages, Command
+
+try:
+    import builtins
+except ImportError:
+    import __builtin__ as builtins
+
+PATH_ROOT = os.path.dirname(__file__)
+builtins.__STOCHMAN_SETUP__ = True
+
+import torchplot
+
+
+class CleanCommand(Command):
+    """Custom clean command to tidy up the project root."""
+
+    user_options = []
+
+    def initialize_options(self):
+        pass
+
+    def finalize_options(self):
+        pass
+
+    def run(self):
+        os.system("rm -vrf ./build ./dist ./*.pyc ./*.tgz ./*.egg-info")
+
+
+PATH_ROOT = os.path.dirname(__file__)
+
+
+def load_readme(path_dir=PATH_ROOT):
+    with open(os.path.join(path_dir, "README.md"), encoding="utf-8") as f:
+        long_description = f.read()
+    return long_description
+
+
+setup(
+    name="torchplot",
+    version=torchplot.__version__,
+    description=torchplot.__docs__,
+    long_description=load_readme(PATH_ROOT),
+    author=torchplot.__author__,
+    author_email=torchplot.__author_email__,
+    license=torchplot.__license__,
+    packages=find_packages(exclude=["tests", "tests/*"]),
+    python_requires=">=3.8",
+    install_requires=['torch>=1.3', 'matplotlib>=3.3.3'],
+    download_url="https://github.com/CenterBioML/torchplot/archive/0.1.0.zip",
+    classifiers=[
+        "Environment :: Console",
+        "Natural Language :: English",
+        # How mature is this project? Common values are
+        #   3 - Alpha, 4 - Beta, 5 - Production/Stable
+        "Development Status :: 3 - Alpha",
+        # Indicate who your project is intended for
+        "Intended Audience :: Developers",
+        "Topic :: Scientific/Engineering :: Artificial Intelligence",
+        # Pick your license as you wish
+        "License :: OSI Approved :: Apache Software License",
+        "Operating System :: OS Independent",
+        # Specify the Python versions you support here. In particular, ensure
+        # that you indicate whether you support Python 2, Python 3 or both.
+        "Programming Language :: Python :: 3.8",
+    ],
+)

tests/__init__.py

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+

tests/test_torchplot.py

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+# Copyright The GeoML Team
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import pytest
+from inspect import getmembers, isfunction
+from collections import namedtuple
+import string
+
+import torch
+import numpy as np
+
+import matplotlib.pyplot as plt
+import torchplot as tp
+
+Inputs = namedtuple("case", ["x", "y"])
+
+_cpu_cases = [Inputs(x=torch.randn(100,), y=torch.randn(100,)),
+              Inputs(x=torch.randn(100, requires_grad=True), y=torch.randn(100,requires_grad=True)),
+              # test that list/numpy arrays still works
+              Inputs(x=[1,2,3,4], y=[1,2,3,4]),
+              Inputs(x=np.random.randn(100,), y=np.random.randn(100,)),
+              # test that we can mix
+              Inputs(x=torch.randn(100,), y=torch.randn(100, requires_grad=True)),
+              Inputs(x=np.random.randn(100,), y=torch.randn(100, requires_grad=True)),
+              Inputs(x=torch.randn(5,), y=[1,2,3,4,5]),
+              ]
+
+_gpu_cases = [Inputs(x=torch.randn(100, device='cuda'), y=torch.randn(100, device='cuda')),
+              Inputs(x=torch.randn(100,requires_grad=True, device='cuda'), y=torch.randn(100,requires_grad=True, device='cuda')),
+              ]
+
+
+
+_members_to_check = [name for name, member in getmembers(plt) 
+                     if isfunction(member) and not name.startswith('_')]
+
+
+def string_compare(text1, text2):
+    if text1 is None and text2 is None:
+        return True
+    remove = string.punctuation + string.whitespace
+    return text1.translate(str.maketrans(dict.fromkeys(remove))) == text2.translate(str.maketrans(dict.fromkeys(remove)))
+
+
+@pytest.mark.parametrize("member", _members_to_check)
+def test_members(member):
+    """ test that all members have been copied """
+    assert member in dir(plt)
+    assert member in dir(tp)
+
+
+@pytest.mark.parametrize('test_case', _cpu_cases)
+def test_cpu(test_case):
+    """ test that it works on cpu """
+    assert tp.plot(test_case.x, test_case.y, '.')
+
+
+@pytest.mark.skipif(not torch.cuda.is_available(), reason='test requires cuda')
+@pytest.mark.parametrize('test_case', _gpu_cases)
+def test_gpu(test_case):
+    """ test that it works on gpu """
+    assert tp.plot(test_case.x, test_case.y, '.')
+

torchplot/__init__.py

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+# Copyright The GeoML Team
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Root package info."""
+import os
+import time
+
+_this_year = time.strftime("%Y")
+__version__ = "0.1"
+__author__ = "Nicki Skafte Detlefsen et al."
+__author_email__ = "[email protected]"
+__license__ = "Apache-2.0"
+__copyright__ = f"Copyright (c) 2018-{_this_year}, {__author__}."
+__homepage__ = "https://github.com/CenterBioML/torchplot"
+
+__docs__ = "Plotting pytorch tensors made easy"
+
+PACKAGE_ROOT = os.path.dirname(__file__)
+PROJECT_ROOT = os.path.dirname(PACKAGE_ROOT)
+
+from .core import *

torchplot/core.py

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+# Copyright The GeoML Team
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import matplotlib.pyplot as plt
+import torch
+from inspect import getmembers, isfunction, getdoc
+
+# Function to convert a list of arguments containing torch tensors, into
+# a corresponding list of arguments containing numpy arrays
+def _torch2np(*args, **kwargs):
+    def convert(arg):
+        return arg.detach().cpu().numpy() if isinstance(arg, torch.Tensor) else arg
+
+    # first unnamed arguments
+    outargs = [convert(arg) for arg in args]
+
+    # then keyword arguments
+    outkwargs = dict()
+    for key, value in kwargs.items():
+        outkwargs[key] = convert(value)
+
+    return outargs, kwargs
+
+# Iterate over all members of 'plt' in order to duplicate them
+for name, member in getmembers(plt):
+    if isfunction(member):
+        doc = getdoc(member)
+        strdoc = "" if doc is None else doc
+        exec(('def {name}(*args, **kwargs):\n' +
+              '\t"""{doc}"""\n' +
+              '\tnew_args, new_kwargs = _torch2np(*args, **kwargs)\n' +
+              '\treturn plt.{name}(*new_args, **new_kwargs)').format(name=name, doc=strdoc))
+    else:
+        exec('{name} = plt.{name}'.format(name=name))
+    #break