Merge branch 'master' of gitlab.fel.cvut.cz:mishkdmy/mpv-python-assignment-templates

README.md

@@ -35,6 +35,26 @@ conda env create -f environment-cpu.yml
 conda env create -f environment-gpu.yml
 ```
 
+If way above does not work for you (e.g. you are on Windows), try the following for CPU:
 
+```bash
+conda create --name mpv-assignments-cpu-only python=3.6
+conda activate mpv-assignments-cpu-only
+conda install pytorch torchvision cpuonly -c pytorch
+pip install kornia tqdm notebook matplotlib opencv-contrib-python seaborn tensorboard tensorboardX
+conda install -c conda-forge widgetsnbextension
+conda install -c conda-forge ipywidgets
+```
+
+And following for GPU:
+
+```bash
+conda create --name mpv-assignments-gpu python=3.6
+conda activate mpv-assignments-gpu
+conda install pytorch torchvision cudatoolkit=10.1 -c pytorch
+pip install kornia tqdm notebook matplotlib opencv-contrib-python seaborn tensorboard tensorboardX
+conda install -c conda-forge widgetsnbextension
+conda install -c conda-forge ipywidgets
+```
 
 **Keep in mind that the assignments and the assignment templates will be updated during the semester.  Always pull the current template version before starting to work on an assignment!**

assignment_6_7_cnn_template/cnn_training.py

@@ -7,18 +7,22 @@ import typing
 from typing import Tuple, List
 from PIL import Image
 import os
-from tqdm import tqdm
+from tqdm import tqdm_notebook as tqdm
 from time import time
 
 
 def get_dataset_statistics(dataset: torch.utils.data.Dataset) -> Tuple[List, List]:
-    '''Function, that calculates mean and std of a dataset (pixelwise)'''
+    '''Function, that calculates mean and std of a dataset (pixelwise)
+    Return:
+        tuple of Lists of floats. len of each list should equal to number of input image/tensor channels
+    '''
     mean = [0., 0., 0.]
     std = [1.0, 1.0, 1.0]
-    return mean, std     
+    return mean, std
 
 
 class SimpleCNN(nn.Module):
+    """Class, which implements image classifier. """
     def __init__(self, num_classes = 10):
         super(SimpleCNN, self).__init__()
         self.features = nn.Sequential(
@@ -49,43 +53,68 @@ class SimpleCNN(nn.Module):
                                 nn.Flatten(),
                                 nn.Linear(512, num_classes))
         return
-    
     def forward(self, input):
+        """ 
+        Shape:
+        - Input :math:`(B, C, H, W)` 
+        - Output: :math:`(B, NC)`, where NC is num_classes
+        """
         x = self.features(input)
         return self.clf(x)
 
 
-def weight_init(m: nn.Module):
+def weight_init(m: nn.Module) -> None:
     '''Function, which fills-in weights and biases for convolutional and linear layers'''
     if isinstance(m, nn.Conv2d) or isinstance(m, nn.Linear):
-     pass #do something
+        #do something here. You can access layer weight or bias by m.weight or m.bias
+        pass #do something
     return
 
-def train_single_epoch(model: torch.nn.Module,
+def train_and_val_single_epoch(model: torch.nn.Module,
                        train_loader: torch.utils.data.DataLoader,
+                       val_loader: torch.utils.data.DataLoader,
                        optim: torch.optim.Optimizer,
-                       loss_fn: torch.nn.Module) -> torch.nn.Module:
-    '''Function, which runs training over a single epoch in the dataloader and returns the model'''
+                       loss_fn: torch.nn.Module,
+                       epoch_idx = 0,
+                       lr_scheduler = None,
+                       writer = None) -> torch.nn.Module:
+    '''Function, which runs training over a single epoch in the dataloader and returns the model. Do not forget to set the model into train mode and zero_grad() optimizer before backward.'''
+    if epoch_idx == 0:
+        val_acc, val_loss = validate(model, val_loader, loss_fn)
+        if writer is not None:
+            writer.add_scalar("Accuracy/val", val_acc, 0)
+            writer.add_scalar("Loss/val", val_loss, 0)
     model.train()
+    for idx, (data, labels) in tqdm(enumerate(train_loader), total=num_batches):
+         pass #do something
     return model
 
-def lr_find(model, train_dl, loss_fn, min_lr=1e-7, max_lr=100, steps = 50):
-    '''Function, which runs the mock training over with different learning rates'''
+def lr_find(model: torch.nn.Module,
+            train_dl:torch.utils.data.DataLoader,
+            loss_fn:torch.nn.Module,
+            min_lr: float=1e-7, max_lr:float=100, steps:int = 50)-> Tuple:
+    '''Function, which run the training for a small number of iterations, increasing the learning rate and storing the losses. Model initialization is saved before training and restored after training'''
     lrs = np.ones(steps)
     losses = np.ones(steps)
     return losses, lrs
 
 
-def validate(model: torch.nn.Module, val_loader: torch.utils.data.DataLoader) -> float:
+def validate(model: torch.nn.Module,
+             val_loader: torch.utils.data.DataLoader,
+             loss_fn: torch.nn.Module) -> float:
     '''Function, which runs the module over validation set and returns accuracy'''
     print ("Starting validation")
     acc = 0
-    return acc
+    loss = 0
+    for idx, (data, labels) in tqdm(enumerate(val_loader), total=len(val_loader)):
+        with torch.no_grad():
+             pass #do something
+    return acc, loss
 
 
 
 class TestFolderDataset(torch.utils.data.Dataset):
-    ''''''
+    '''Class, which reads images in folder and serves as test dataset'''
     def __init__(self, folder_name, transform = None):
         return
     def __getitem__(self, index):
@@ -96,7 +125,7 @@ class TestFolderDataset(torch.utils.data.Dataset):
         return ln
         
 
-def get_predictions(model, test_dl):
-    '''Outputs prediction over test data loader'''
+def get_predictions(model: torch.nn.Module, test_dl: torch.utils.data.DataLoader)->torch.Tensor :
+    '''Function, which predicts class indexes for image in data loader. Ouput shape: [N, 1], where N is number of image in the dataset'''
     out = torch.zeros(len(test_dl)).long()
     return out

conda_env_yaml/environment-cpu.yml

 name: mpv-assignments-cpu-only
 channels:
   - pytorch
+  - conda-forge
   - defaults
 dependencies:
-  - _anaconda_depends=2019.03=py36_0
-  - _libgcc_mutex=0.1=main
-  - alabaster=0.7.12=py36_0
-  - anaconda=custom=py36_1
-  - anaconda-client=1.7.2=py36_0
-  - anaconda-project=0.8.4=py_0
-  - asn1crypto=1.3.0=py36_0
-  - astroid=2.3.3=py36_0
-  - astropy=4.0=py36h7b6447c_0
-  - atomicwrites=1.3.0=py36_1
-  - attrs=19.3.0=py_0
-  - babel=2.8.0=py_0
-  - backcall=0.1.0=py36_0
-  - backports=1.0=py_2
-  - backports.os=0.1.1=py36_0
-  - backports.shutil_get_terminal_size=1.0.0=py36_2
-  - beautifulsoup4=4.8.2=py36_0
-  - bitarray=1.2.1=py36h7b6447c_0
-  - bkcharts=0.2=py36_0
-  - blas=1.0=mkl
-  - bleach=3.1.0=py36_0
-  - blosc=1.16.3=hd408876_0
-  - bokeh=1.4.0=py36_0
-  - boto=2.49.0=py36_0
-  - bottleneck=1.3.1=py36hdd07704_0
-  - bzip2=1.0.8=h7b6447c_0
-  - ca-certificates=2020.1.1=0
-  - cairo=1.14.12=h8948797_3
-  - certifi=2019.11.28=py36_0
-  - cffi=1.14.0=py36h2e261b9_0
-  - chardet=3.0.4=py36_1003
-  - click=7.0=py36_0
-  - cloudpickle=1.3.0=py_0
-  - clyent=1.2.2=py36_1
-  - colorama=0.4.3=py_0
-  - contextlib2=0.6.0.post1=py_0
-  - cpuonly=1.0=0
-  - cryptography=2.8=py36h1ba5d50_0
-  - curl=7.68.0=hbc83047_0
-  - cycler=0.10.0=py36_0
-  - cython=0.29.15=py36he6710b0_0
-  - cytoolz=0.10.1=py36h7b6447c_0
-  - dask=2.10.1=py_0
-  - dask-core=2.10.1=py_0
-  - dbus=1.13.12=h746ee38_0
-  - decorator=4.4.1=py_0
-  - defusedxml=0.6.0=py_0
-  - distributed=2.10.0=py_0
-  - docutils=0.16=py36_0
-  - entrypoints=0.3=py36_0
-  - et_xmlfile=1.0.1=py36_0
-  - expat=2.2.6=he6710b0_0
-  - fastcache=1.1.0=py36h7b6447c_0
-  - flask=1.1.1=py_0
-  - fontconfig=2.13.0=h9420a91_0
-  - freetype=2.9.1=h8a8886c_1
-  - fribidi=1.0.5=h7b6447c_0
-  - fsspec=0.6.2=py_0
-  - get_terminal_size=1.0.0=haa9412d_0
-  - gevent=1.4.0=py36h7b6447c_0
-  - glib=2.63.1=h5a9c865_0
-  - gmp=6.1.2=h6c8ec71_1
-  - gmpy2=2.0.8=py36h10f8cd9_2
-  - graphite2=1.3.13=h23475e2_0
-  - greenlet=0.4.15=py36h7b6447c_0
-  - gst-plugins-base=1.14.0=hbbd80ab_1
-  - gstreamer=1.14.0=hb453b48_1
-  - h5py=2.10.0=py36h7918eee_0
-  - harfbuzz=1.8.8=hffaf4a1_0
-  - hdf5=1.10.4=hb1b8bf9_0
-  - heapdict=1.0.1=py_0
-  - html5lib=1.0.1=py36_0
-  - hypothesis=5.4.1=py_0
-  - icu=58.2=h9c2bf20_1
-  - idna=2.8=py36_0
-  - imageio=2.6.1=py36_0
-  - imagesize=1.2.0=py_0
-  - importlib_metadata=1.5.0=py36_0
-  - intel-openmp=2020.0=166
-  - ipykernel=5.1.4=py36h39e3cac_0
-  - ipython=7.12.0=py36h5ca1d4c_0
-  - ipython_genutils=0.2.0=py36_0
-  - ipywidgets=7.5.1=py_0
-  - isort=4.3.21=py36_0
-  - itsdangerous=1.1.0=py36_0
-  - jbig=2.1=hdba287a_0
-  - jdcal=1.4.1=py_0
-  - jedi=0.16.0=py36_0
-  - jeepney=0.4.2=py_0
-  - jinja2=2.11.1=py_0
-  - joblib=0.14.1=py_0
-  - jpeg=9b=h024ee3a_2
-  - json5=0.9.1=py_0
-  - jsonschema=3.2.0=py36_0
-  - jupyter=1.0.0=py36_7
-  - jupyter_client=5.3.4=py36_0
-  - jupyter_console=6.1.0=py_0
-  - jupyter_core=4.6.1=py36_0
-  - jupyterlab=1.2.6=pyhf63ae98_0
-  - jupyterlab_server=1.0.6=py_0
-  - keyring=21.1.0=py36_0
-  - kiwisolver=1.1.0=py36he6710b0_0
-  - krb5=1.17.1=h173b8e3_0
-  - lazy-object-proxy=1.4.3=py36h7b6447c_0
-  - ld_impl_linux-64=2.33.1=h53a641e_7
-  - libcurl=7.68.0=h20c2e04_0
-  - libedit=3.1.20181209=hc058e9b_0
-  - libffi=3.2.1=hd88cf55_4
-  - libgcc-ng=9.1.0=hdf63c60_0
-  - libgfortran-ng=7.3.0=hdf63c60_0
-  - libpng=1.6.37=hbc83047_0
-  - libsodium=1.0.16=h1bed415_0
-  - libssh2=1.8.2=h1ba5d50_0
-  - libstdcxx-ng=9.1.0=hdf63c60_0
-  - libtiff=4.1.0=h2733197_0
-  - libtool=2.4.6=h7b6447c_5
-  - libuuid=1.0.3=h1bed415_2
-  - libxcb=1.13=h1bed415_1
-  - libxml2=2.9.9=hea5a465_1
-  - libxslt=1.1.33=h7d1a2b0_0
-  - llvmlite=0.31.0=py36hd408876_0
-  - locket=0.2.0=py36_1
-  - lxml=4.5.0=py36hefd8a0e_0
-  - lz4-c=1.8.1.2=h14c3975_0
-  - lzo=2.10=h49e0be7_2
-  - markupsafe=1.1.1=py36h7b6447c_0
-  - matplotlib=3.1.3=py36_0
-  - matplotlib-base=3.1.3=py36hef1b27d_0
-  - mccabe=0.6.1=py36_1
-  - mistune=0.8.4=py36h7b6447c_0
-  - mkl=2020.0=166
-  - mkl-service=2.3.0=py36he904b0f_0
-  - mkl_fft=1.0.15=py36ha843d7b_0
-  - mkl_random=1.1.0=py36hd6b4f25_0
-  - mock=4.0.1=py_0
-  - more-itertools=8.2.0=py_0
-  - mpc=1.1.0=h10f8cd9_1
-  - mpfr=4.0.1=hdf1c602_3
-  - mpmath=1.1.0=py36_0
-  - msgpack-python=0.6.1=py36hfd86e86_1
-  - multipledispatch=0.6.0=py36_0
-  - nbconvert=5.6.1=py36_0
-  - nbformat=5.0.4=py_0
-  - ncurses=6.1=he6710b0_1
-  - networkx=2.4=py_0
-  - ninja=1.9.0=py36hfd86e86_0
-  - nltk=3.4.5=py36_0
-  - nose=1.3.7=py36_2
-  - notebook=6.0.3=py36_0
-  - numba=0.48.0=py36h0573a6f_0
-  - numexpr=2.7.1=py36h423224d_0
-  - numpy=1.18.1=py36h4f9e942_0
-  - numpy-base=1.18.1=py36hde5b4d6_1
-  - numpydoc=0.9.2=py_0
-  - olefile=0.46=py36_0
-  - openpyxl=3.0.3=py_0
-  - openssl=1.1.1d=h7b6447c_4
-  - packaging=20.1=py_0
-  - pandas=1.0.1=py36h0573a6f_0
-  - pandoc=2.2.3.2=0
-  - pandocfilters=1.4.2=py36_1
-  - pango=1.42.4=h049681c_0
-  - parso=0.6.1=py_0
-  - partd=1.1.0=py_0
-  - path=13.1.0=py36_0
-  - path.py=12.4.0=0
-  - pathlib2=2.3.5=py36_0
-  - patsy=0.5.1=py36_0
-  - pcre=8.43=he6710b0_0
-  - pep8=1.7.1=py36_0
-  - pexpect=4.8.0=py36_0
-  - pickleshare=0.7.5=py36_0
-  - pillow=7.0.0=py36hb39fc2d_0
-  - pip=20.0.2=py36_1
-  - pixman=0.38.0=h7b6447c_0
-  - pluggy=0.13.1=py36_0
-  - ply=3.11=py36_0
-  - prometheus_client=0.7.1=py_0
-  - prompt_toolkit=3.0.3=py_0
-  - psutil=5.6.7=py36h7b6447c_0
-  - ptyprocess=0.6.0=py36_0
-  - py=1.8.1=py_0
-  - pycodestyle=2.5.0=py36_0
-  - pycosat=0.6.3=py36h7b6447c_0
-  - pycparser=2.19=py36_0
-  - pycrypto=2.6.1=py36h14c3975_9
-  - pycurl=7.43.0.5=py36h1ba5d50_0
-  - pyflakes=2.1.1=py36_0
-  - pygments=2.5.2=py_0
-  - pylint=2.4.4=py36_0
-  - pyodbc=4.0.30=py36he6710b0_0
-  - pyopenssl=19.1.0=py36_0
-  - pyparsing=2.4.6=py_0
-  - pyqt=5.9.2=py36h05f1152_2
-  - pyrsistent=0.15.7=py36h7b6447c_0
-  - pysocks=1.7.1=py36_0
-  - pytables=3.6.1=py36h71ec239_0
-  - pytest=5.3.5=py36_0
-  - pytest-arraydiff=0.3=py36h39e3cac_0
-  - pytest-astropy=0.8.0=py_0
-  - pytest-astropy-header=0.1.2=py_0
-  - pytest-doctestplus=0.5.0=py_0
-  - pytest-openfiles=0.4.0=py_0
-  - pytest-remotedata=0.3.2=py36_0
-  - python=3.6.10=h0371630_0
-  - python-dateutil=2.8.1=py_0
-  - pytorch=1.4.0=py3.6_cpu_0
-  - pytz=2019.3=py_0
-  - pywavelets=1.1.1=py36h7b6447c_0
-  - pyyaml=5.3=py36h7b6447c_0
-  - pyzmq=18.1.1=py36he6710b0_0
-  - qt=5.9.7=h5867ecd_1
-  - qtawesome=0.6.1=py_0
-  - qtconsole=4.6.0=py_1
-  - qtpy=1.9.0=py_0
-  - readline=7.0=h7b6447c_5
-  - requests=2.22.0=py36_1
-  - rope=0.16.0=py_0
-  - ruamel_yaml=0.15.87=py36h7b6447c_0
-  - scikit-image=0.16.2=py36h0573a6f_0
-  - scikit-learn=0.22.1=py36hd81dba3_0
-  - scipy=1.4.1=py36h0b6359f_0
-  - seaborn=0.10.0=py_0
-  - secretstorage=3.1.2=py36_0
-  - send2trash=1.5.0=py36_0
-  - setuptools=45.2.0=py36_0
-  - simplegeneric=0.8.1=py36_2
-  - singledispatch=3.4.0.3=py36_0
-  - sip=4.19.8=py36hf484d3e_0
-  - six=1.14.0=py36_0
-  - snappy=1.1.7=hbae5bb6_3
-  - snowballstemmer=2.0.0=py_0
-  - sortedcollections=1.1.2=py36_0
-  - sortedcontainers=2.1.0=py36_0
-  - soupsieve=1.9.5=py36_0
-  - sphinx=2.4.0=py_0
-  - sphinxcontrib=1.0=py36_1
-  - sphinxcontrib-applehelp=1.0.1=py_0
-  - sphinxcontrib-devhelp=1.0.1=py_0
-  - sphinxcontrib-htmlhelp=1.0.2=py_0
-  - sphinxcontrib-jsmath=1.0.1=py_0
-  - sphinxcontrib-qthelp=1.0.2=py_0
-  - sphinxcontrib-serializinghtml=1.1.3=py_0
-  - sphinxcontrib-websupport=1.2.0=py_0
-  - spyder=3.3.6=py36_0
-  - spyder-kernels=0.5.2=py36_0
-  - sqlalchemy=1.3.13=py36h7b6447c_0
-  - sqlite=3.31.1=h7b6447c_0
-  - statsmodels=0.11.0=py36h7b6447c_0
-  - sympy=1.5.1=py36_0
-  - tblib=1.6.0=py_0
-  - terminado=0.8.3=py36_0
-  - testpath=0.4.4=py_0
-  - tk=8.6.8=hbc83047_0
-  - toolz=0.10.0=py_0
-  - torchvision=0.5.0=py36_cpu
-  - tornado=6.0.3=py36h7b6447c_3
-  - traitlets=4.3.3=py36_0
-  - typed-ast=1.4.1=py36h7b6447c_0
-  - unicodecsv=0.14.1=py36_0
-  - unixodbc=2.3.7=h14c3975_0
-  - urllib3=1.25.8=py36_0
-  - wcwidth=0.1.8=py_0
-  - webencodings=0.5.1=py36_1
-  - werkzeug=1.0.0=py_0
-  - wheel=0.34.2=py36_0
-  - widgetsnbextension=3.5.1=py36_0
-  - wrapt=1.11.2=py36h7b6447c_0
-  - wurlitzer=2.0.0=py36_0
-  - xlrd=1.2.0=py36_0
-  - xlsxwriter=1.2.7=py_0
-  - xlwt=1.3.0=py36_0
-  - xz=5.2.4=h14c3975_4
-  - yaml=0.1.7=had09818_2
-  - zeromq=4.3.1=he6710b0_3
-  - zict=1.0.0=py_0
-  - zipp=2.2.0=py_0
-  - zlib=1.2.11=h7b6447c_3
-  - zstd=1.3.7=h0b5b093_0
+  - _libgcc_mutex=0.1
+  - attrs=19.3.0
+  - backcall=0.1.0
+  - blas=1.0
+  - bleach=3.1.4
+  - ca-certificates=2020.4.5.1
+  - certifi=2020.4.5.1
+  - cpuonly=1.0
+  - decorator=4.4.2
+  - defusedxml=0.6.0
+  - entrypoints=0.3
+  - freetype=2.9.1
+  - importlib-metadata=1.6.0
+  - importlib_metadata=1.6.0
+  - intel-openmp=2020.0
+  - ipykernel=5.2.1
+  - ipython=7.13.0
+  - ipython_genutils=0.2.0
+  - ipywidgets=7.5.1
+  - jedi=0.17.0
+  - jinja2=2.11.2
+  - jpeg=9b
+  - jsonschema=3.2.0
+  - jupyter_client=6.1.3
+  - jupyter_core=4.6.3
+  - ld_impl_linux-64=2.33.1
+  - libedit=3.1.20181209
+  - libffi=3.2.1
+  - libgcc-ng=9.1.0
+  - libgfortran-ng=7.3.0
+  - libpng=1.6.37
+  - libsodium=1.0.17
+  - libstdcxx-ng=9.1.0
+  - libtiff=4.1.0
+  - markupsafe=1.1.1
+  - mistune=0.8.4
+  - mkl=2020.0
+  - mkl-service=2.3.0
+  - mkl_fft=1.0.15
+  - mkl_random=1.1.0
+  - nbconvert=5.6.1
+  - nbformat=5.0.6
+  - ncurses=6.2
+  - ninja=1.9.0
+  - notebook=6.0.3
+  - numpy=1.18.1
+  - numpy-base=1.18.1
+  - olefile=0.46
+  - openssl=1.1.1f
+  - pandoc=2.9.2.1
+  - parso=0.7.0
+  - pexpect=4.8.0
+  - pickleshare=0.7.5
+  - pillow=7.0.0
+  - pip=20.0.2
+  - prometheus_client=0.7.1
+  - prompt-toolkit=3.0.5
+  - ptyprocess=0.6.0
+  - pygments=2.6.1
+  - pyrsistent=0.16.0
+  - python=3.6.10
+  - python-dateutil=2.8.1
+  - python_abi=3.6
+  - pytorch=1.4.0
+  - readline=8.0
+  - send2trash=1.5.0
+  - setuptools=46.1.3
+  - six=1.14.0
+  - sqlite=3.31.1
+  - testpath=0.4.4
+  - tk=8.6.8
+  - torchvision=0.5.0
+  - tornado=6.0.4
+  - traitlets=4.3.3
+  - wcwidth=0.1.9
+  - wheel=0.34.2
+  - widgetsnbextension=3.5.1
+  - xz=5.2.5
+  - zeromq=4.3.2
+  - zipp=3.1.0
+  - zlib=1.2.11
+  - zstd=1.3.7
   - pip:
-    - kornia==0.2.0
-    - opencv-contrib-python==4.2.0.32
-prefix: /home/old-ufo/anaconda3/envs/mpv-assignments-cpu-only
+    - absl-py==0.9.0
+    - cachetools==4.1.0
+    - chardet==3.0.4
+    - cycler==0.10.0
+    - google-auth==1.14.0
+    - google-auth-oauthlib==0.4.1
+    - grpcio==1.28.1
+    - idna==2.9
+    - ipython-genutils==0.2.0
+    - kiwisolver==1.2.0
+    - kornia==0.2.1
+    - markdown==3.2.1
+    - matplotlib==3.2.1
+    - oauthlib==3.1.0
+    - opencv-contrib-python==4.2.0.34
+    - pandas==1.0.3
+    - pandocfilters==1.4.2
+    - protobuf==3.11.3
+    - pyasn1==0.4.8
+    - pyasn1-modules==0.2.8
+    - pyparsing==2.4.7
+    - pytz==2019.3
+    - pyzmq==19.0.0
+    - requests==2.23.0
+    - requests-oauthlib==1.3.0
+    - rsa==4.0
+    - scipy==1.4.1
+    - seaborn==0.10.0
+    - tensorboard==2.2.1
+    - tensorboard-plugin-wit==1.6.0.post3
+    - tensorboardx==2.0
+    - terminado==0.8.3
+    - tqdm==4.45.0
+    - urllib3==1.25.9
+    - webencodings==0.5.1
+    - werkzeug==1.0.1
 

conda_env_yaml/environment-gpu.yml

-name: mpv-assignments
+name: mpv-assignments-gpu
 channels:
   - pytorch
+  - conda-forge
   - defaults
 dependencies:
-  - _anaconda_depends=2019.03=py36_0
-  - _libgcc_mutex=0.1=main
-  - alabaster=0.7.12=py36_0
-  - anaconda=custom=py36_1
-  - anaconda-client=1.7.2=py36_0
-  - anaconda-project=0.8.4=py_0
-  - asn1crypto=1.3.0=py36_0
-  - astroid=2.3.3=py36_0
-  - astropy=4.0=py36h7b6447c_0
-  - atomicwrites=1.3.0=py36_1
-  - attrs=19.3.0=py_0
-  - babel=2.8.0=py_0
-  - backcall=0.1.0=py36_0
-  - backports=1.0=py_2
-  - backports.os=0.1.1=py36_0
-  - backports.shutil_get_terminal_size=1.0.0=py36_2
-  - beautifulsoup4=4.8.2=py36_0
-  - bitarray=1.2.1=py36h7b6447c_0
-  - bkcharts=0.2=py36_0
-  - blas=1.0=mkl
-  - bleach=3.1.0=py36_0
-  - blosc=1.16.3=hd408876_0
-  - bokeh=1.4.0=py36_0
-  - boto=2.49.0=py36_0
-  - bottleneck=1.3.1=py36hdd07704_0
-  - bzip2=1.0.8=h7b6447c_0
-  - ca-certificates=2020.1.1=0
-  - cairo=1.14.12=h8948797_3
-  - certifi=2019.11.28=py36_0
-  - cffi=1.14.0=py36h2e261b9_0
-  - chardet=3.0.4=py36_1003
-  - click=7.0=py36_0
-  - cloudpickle=1.3.0=py_0
-  - clyent=1.2.2=py36_1
-  - colorama=0.4.3=py_0
-  - contextlib2=0.6.0.post1=py_0
-  - cryptography=2.8=py36h1ba5d50_0
-  - cudatoolkit=10.1.243=h6bb024c_0
-  - curl=7.68.0=hbc83047_0
-  - cycler=0.10.0=py36_0
-  - cython=0.29.15=py36he6710b0_0
-  - cytoolz=0.10.1=py36h7b6447c_0
-  - dask=2.10.1=py_0
-  - dask-core=2.10.1=py_0
-  - dbus=1.13.12=h746ee38_0
-  - decorator=4.4.1=py_0
-  - defusedxml=0.6.0=py_0
-  - distributed=2.10.0=py_0
-  - docutils=0.16=py36_0
-  - entrypoints=0.3=py36_0
-  - et_xmlfile=1.0.1=py36_0
-  - expat=2.2.6=he6710b0_0
-  - fastcache=1.1.0=py36h7b6447c_0
-  - flask=1.1.1=py_0
-  - fontconfig=2.13.0=h9420a91_0
-  - freetype=2.9.1=h8a8886c_1
-  - fribidi=1.0.5=h7b6447c_0
-  - fsspec=0.6.2=py_0
-  - get_terminal_size=1.0.0=haa9412d_0
-  - gevent=1.4.0=py36h7b6447c_0
-  - glib=2.63.1=h5a9c865_0
-  - gmp=6.1.2=h6c8ec71_1
-  - gmpy2=2.0.8=py36h10f8cd9_2
-  - graphite2=1.3.13=h23475e2_0
-  - greenlet=0.4.15=py36h7b6447c_0
-  - gst-plugins-base=1.14.0=hbbd80ab_1
-  - gstreamer=1.14.0=hb453b48_1
-  - h5py=2.10.0=py36h7918eee_0
-  - harfbuzz=1.8.8=hffaf4a1_0
-  - hdf5=1.10.4=hb1b8bf9_0
-  - heapdict=1.0.1=py_0
-  - html5lib=1.0.1=py36_0
-  - hypothesis=5.4.1=py_0
-  - icu=58.2=h9c2bf20_1
-  - idna=2.8=py36_0
-  - imageio=2.6.1=py36_0
-  - imagesize=1.2.0=py_0
-  - importlib_metadata=1.5.0=py36_0
-  - intel-openmp=2020.0=166
-  - ipykernel=5.1.4=py36h39e3cac_0
-  - ipython=7.12.0=py36h5ca1d4c_0
-  - ipython_genutils=0.2.0=py36_0
-  - ipywidgets=7.5.1=py_0
-  - isort=4.3.21=py36_0
-  - itsdangerous=1.1.0=py36_0
-  - jbig=2.1=hdba287a_0
-  - jdcal=1.4.1=py_0
-  - jedi=0.16.0=py36_0
-  - jeepney=0.4.2=py_0
-  - jinja2=2.11.1=py_0
-  - joblib=0.14.1=py_0
-  - jpeg=9b=h024ee3a_2
-  - json5=0.9.1=py_0
-  - jsonschema=3.2.0=py36_0
-  - jupyter=1.0.0=py36_7
-  - jupyter_client=5.3.4=py36_0
-  - jupyter_console=6.1.0=py_0
-  - jupyter_core=4.6.1=py36_0
-  - jupyterlab=1.2.6=pyhf63ae98_0
-  - jupyterlab_server=1.0.6=py_0
-  - keyring=21.1.0=py36_0
-  - kiwisolver=1.1.0=py36he6710b0_0
-  - krb5=1.17.1=h173b8e3_0
-  - lazy-object-proxy=1.4.3=py36h7b6447c_0
-  - ld_impl_linux-64=2.33.1=h53a641e_7
-  - libcurl=7.68.0=h20c2e04_0
-  - libedit=3.1.20181209=hc058e9b_0
-  - libffi=3.2.1=hd88cf55_4
-  - libgcc-ng=9.1.0=hdf63c60_0
-  - libgfortran-ng=7.3.0=hdf63c60_0
-  - libpng=1.6.37=hbc83047_0
-  - libsodium=1.0.16=h1bed415_0
-  - libssh2=1.8.2=h1ba5d50_0
-  - libstdcxx-ng=9.1.0=hdf63c60_0
-  - libtiff=4.1.0=h2733197_0
-  - libtool=2.4.6=h7b6447c_5
-  - libuuid=1.0.3=h1bed415_2
-  - libxcb=1.13=h1bed415_1
-  - libxml2=2.9.9=hea5a465_1
-  - libxslt=1.1.33=h7d1a2b0_0
-  - llvmlite=0.31.0=py36hd408876_0
-  - locket=0.2.0=py36_1
-  - lxml=4.5.0=py36hefd8a0e_0
-  - lz4-c=1.8.1.2=h14c3975_0
-  - lzo=2.10=h49e0be7_2
-  - markupsafe=1.1.1=py36h7b6447c_0
-  - matplotlib=3.1.3=py36_0
-  - matplotlib-base=3.1.3=py36hef1b27d_0
-  - mccabe=0.6.1=py36_1
-  - mistune=0.8.4=py36h7b6447c_0
-  - mkl=2020.0=166
-  - mkl-service=2.3.0=py36he904b0f_0
-  - mkl_fft=1.0.15=py36ha843d7b_0
-  - mkl_random=1.1.0=py36hd6b4f25_0
-  - mock=4.0.1=py_0
-  - more-itertools=8.2.0=py_0
-  - mpc=1.1.0=h10f8cd9_1
-  - mpfr=4.0.1=hdf1c602_3
-  - mpmath=1.1.0=py36_0
-  - msgpack-python=0.6.1=py36hfd86e86_1
-  - multipledispatch=0.6.0=py36_0
-  - nbconvert=5.6.1=py36_0
-  - nbformat=5.0.4=py_0
-  - ncurses=6.1=he6710b0_1
-  - networkx=2.4=py_0
-  - ninja=1.9.0=py36hfd86e86_0
-  - nltk=3.4.5=py36_0
-  - nose=1.3.7=py36_2
-  - notebook=6.0.3=py36_0
-  - numba=0.48.0=py36h0573a6f_0
-  - numexpr=2.7.1=py36h423224d_0
-  - numpy=1.18.1=py36h4f9e942_0
-  - numpy-base=1.18.1=py36hde5b4d6_1
-  - numpydoc=0.9.2=py_0
-  - olefile=0.46=py36_0
-  - openpyxl=3.0.3=py_0
-  - openssl=1.1.1d=h7b6447c_4
-  - packaging=20.1=py_0
-  - pandas=1.0.1=py36h0573a6f_0
-  - pandoc=2.2.3.2=0
-  - pandocfilters=1.4.2=py36_1
-  - pango=1.42.4=h049681c_0
-  - parso=0.6.1=py_0
-  - partd=1.1.0=py_0
-  - path=13.1.0=py36_0
-  - path.py=12.4.0=0
-  - pathlib2=2.3.5=py36_0
-  - patsy=0.5.1=py36_0
-  - pcre=8.43=he6710b0_0
-  - pep8=1.7.1=py36_0
-  - pexpect=4.8.0=py36_0
-  - pickleshare=0.7.5=py36_0
-  - pillow=7.0.0=py36hb39fc2d_0
-  - pip=20.0.2=py36_1
-  - pixman=0.38.0=h7b6447c_0
-  - pluggy=0.13.1=py36_0
-  - ply=3.11=py36_0
-  - prometheus_client=0.7.1=py_0
-  - prompt_toolkit=3.0.3=py_0
-  - psutil=5.6.7=py36h7b6447c_0
-  - ptyprocess=0.6.0=py36_0
-  - py=1.8.1=py_0
-  - pycodestyle=2.5.0=py36_0
-  - pycosat=0.6.3=py36h7b6447c_0
-  - pycparser=2.19=py36_0
-  - pycrypto=2.6.1=py36h14c3975_9
-  - pycurl=7.43.0.5=py36h1ba5d50_0
-  - pyflakes=2.1.1=py36_0
-  - pygments=2.5.2=py_0
-  - pylint=2.4.4=py36_0
-  - pyodbc=4.0.30=py36he6710b0_0
-  - pyopenssl=19.1.0=py36_0
-  - pyparsing=2.4.6=py_0
-  - pyqt=5.9.2=py36h05f1152_2
-  - pyrsistent=0.15.7=py36h7b6447c_0
-  - pysocks=1.7.1=py36_0
-  - pytables=3.6.1=py36h71ec239_0
-  - pytest=5.3.5=py36_0
-  - pytest-arraydiff=0.3=py36h39e3cac_0
-  - pytest-astropy=0.8.0=py_0
-  - pytest-astropy-header=0.1.2=py_0
-  - pytest-doctestplus=0.5.0=py_0
-  - pytest-openfiles=0.4.0=py_0
-  - pytest-remotedata=0.3.2=py36_0
-  - python=3.6.10=h0371630_0
-  - python-dateutil=2.8.1=py_0
-  - pytorch=1.4.0=py3.6_cuda10.1.243_cudnn7.6.3_0
-  - pytz=2019.3=py_0
-  - pywavelets=1.1.1=py36h7b6447c_0
-  - pyyaml=5.3=py36h7b6447c_0
-  - pyzmq=18.1.1=py36he6710b0_0
-  - qt=5.9.7=h5867ecd_1
-  - qtawesome=0.6.1=py_0
-  - qtconsole=4.6.0=py_1
-  - qtpy=1.9.0=py_0
-  - readline=7.0=h7b6447c_5
-  - requests=2.22.0=py36_1
-  - rope=0.16.0=py_0
-  - ruamel_yaml=0.15.87=py36h7b6447c_0
-  - scikit-image=0.16.2=py36h0573a6f_0
-  - scikit-learn=0.22.1=py36hd81dba3_0
-  - scipy=1.4.1=py36h0b6359f_0
-  - seaborn=0.10.0=py_0
-  - secretstorage=3.1.2=py36_0
-  - send2trash=1.5.0=py36_0
-  - setuptools=45.2.0=py36_0
-  - simplegeneric=0.8.1=py36_2
-  - singledispatch=3.4.0.3=py36_0
-  - sip=4.19.8=py36hf484d3e_0
-  - six=1.14.0=py36_0
-  - snappy=1.1.7=hbae5bb6_3
-  - snowballstemmer=2.0.0=py_0
-  - sortedcollections=1.1.2=py36_0
-  - sortedcontainers=2.1.0=py36_0
-  - soupsieve=1.9.5=py36_0
-  - sphinx=2.4.0=py_0
-  - sphinxcontrib=1.0=py36_1
-  - sphinxcontrib-applehelp=1.0.1=py_0
-  - sphinxcontrib-devhelp=1.0.1=py_0
-  - sphinxcontrib-htmlhelp=1.0.2=py_0
-  - sphinxcontrib-jsmath=1.0.1=py_0
-  - sphinxcontrib-qthelp=1.0.2=py_0
-  - sphinxcontrib-serializinghtml=1.1.3=py_0
-  - sphinxcontrib-websupport=1.2.0=py_0
-  - spyder=3.3.6=py36_0
-  - spyder-kernels=0.5.2=py36_0
-  - sqlalchemy=1.3.13=py36h7b6447c_0
-  - sqlite=3.31.1=h7b6447c_0
-  - statsmodels=0.11.0=py36h7b6447c_0
-  - sympy=1.5.1=py36_0
-  - tblib=1.6.0=py_0
-  - terminado=0.8.3=py36_0
-  - testpath=0.4.4=py_0
-  - tk=8.6.8=hbc83047_0
-  - toolz=0.10.0=py_0
-  - torchvision=0.5.0=py36_cu101
-  - tornado=6.0.3=py36h7b6447c_3
-  - traitlets=4.3.3=py36_0
-  - typed-ast=1.4.1=py36h7b6447c_0
-  - unicodecsv=0.14.1=py36_0
-  - unixodbc=2.3.7=h14c3975_0
-  - urllib3=1.25.8=py36_0
-  - wcwidth=0.1.8=py_0
-  - webencodings=0.5.1=py36_1
-  - werkzeug=1.0.0=py_0
-  - wheel=0.34.2=py36_0
-  - widgetsnbextension=3.5.1=py36_0
-  - wrapt=1.11.2=py36h7b6447c_0
-  - wurlitzer=2.0.0=py36_0
-  - xlrd=1.2.0=py36_0
-  - xlsxwriter=1.2.7=py_0
-  - xlwt=1.3.0=py36_0
-  - xz=5.2.4=h14c3975_4
-  - yaml=0.1.7=had09818_2
-  - zeromq=4.3.1=he6710b0_3
-  - zict=1.0.0=py_0
-  - zipp=2.2.0=py_0
-  - zlib=1.2.11=h7b6447c_3
-  - zstd=1.3.7=h0b5b093_0
+  - _libgcc_mutex=0.1
+  - attrs=19.3.0
+  - backcall=0.1.0
+  - blas=1.0
+  - bleach=3.1.4
+  - ca-certificates=2020.4.5.1
+  - certifi=2020.4.5.1
+  - cudatoolkit=10.1.243
+  - decorator=4.4.2
+  - defusedxml=0.6.0
+  - entrypoints=0.3
+  - freetype=2.9.1
+  - importlib-metadata=1.6.0
+  - importlib_metadata=1.6.0
+  - intel-openmp=2020.0
+  - ipykernel=5.2.1
+  - ipython=7.13.0
+  - ipython_genutils=0.2.0
+  - ipywidgets=7.5.1
+  - jedi=0.17.0
+  - jinja2=2.11.2
+  - jpeg=9b
+  - jsonschema=3.2.0
+  - jupyter_client=6.1.3
+  - jupyter_core=4.6.3
+  - ld_impl_linux-64=2.33.1
+  - libedit=3.1.20181209
+  - libffi=3.2.1
+  - libgcc-ng=9.1.0
+  - libgfortran-ng=7.3.0
+  - libpng=1.6.37
+  - libsodium=1.0.17
+  - libstdcxx-ng=9.1.0
+  - libtiff=4.1.0
+  - markupsafe=1.1.1
+  - mistune=0.8.4
+  - mkl=2020.0
+  - mkl-service=2.3.0
+  - mkl_fft=1.0.15
+  - mkl_random=1.1.0
+  - nbconvert=5.6.1
+  - nbformat=5.0.6
+  - ncurses=6.2
+  - ninja=1.9.0
+  - notebook=6.0.3
+  - numpy=1.18.1
+  - numpy-base=1.18.1
+  - olefile=0.46
+  - openssl=1.1.1g
+  - pandoc=2.9.2.1
+  - parso=0.7.0
+  - pexpect=4.8.0
+  - pickleshare=0.7.5
+  - pillow=7.0.0
+  - pip=20.0.2
+  - prometheus_client=0.7.1
+  - prompt-toolkit=3.0.5
+  - ptyprocess=0.6.0
+  - pygments=2.6.1
+  - pyrsistent=0.16.0
+  - python=3.6.10
+  - python-dateutil=2.8.1
+  - python_abi=3.6
+  - pytorch=1.4.0
+  - readline=8.0
+  - send2trash=1.5.0
+  - setuptools=46.1.3
+  - six=1.14.0
+  - sqlite=3.31.1
+  - testpath=0.4.4
+  - tk=8.6.8
+  - torchvision=0.5.0
+  - tornado=6.0.4
+  - traitlets=4.3.3
+  - wcwidth=0.1.9
+  - wheel=0.34.2
+  - widgetsnbextension=3.5.1
+  - xz=5.2.5
+  - zeromq=4.3.2
+  - zipp=3.1.0
+  - zlib=1.2.11
+  - zstd=1.3.7
   - pip:
-    - kornia==0.2.0
-    - opencv-contrib-python==4.2.0.32
-prefix: /home/old-ufo/anaconda3/envs/mpv-assignments
+    - absl-py==0.9.0
+    - cachetools==4.1.0
+    - chardet==3.0.4
+    - cycler==0.10.0
+    - google-auth==1.14.0
+    - google-auth-oauthlib==0.4.1
+    - grpcio==1.28.1
+    - idna==2.9
+    - ipython-genutils==0.2.0
+    - kiwisolver==1.2.0
+    - kornia==0.2.1
+    - markdown==3.2.1
+    - matplotlib==3.2.1
+    - oauthlib==3.1.0
+    - opencv-contrib-python==4.2.0.34
+    - pandas==1.0.3
+    - pandocfilters==1.4.2
+    - protobuf==3.11.3
+    - pyasn1==0.4.8
+    - pyasn1-modules==0.2.8
+    - pyparsing==2.4.7
+    - pytz==2019.3
+    - pyzmq==19.0.0
+    - requests==2.23.0
+    - requests-oauthlib==1.3.0
+    - rsa==4.0
+    - scipy==1.4.1
+    - seaborn==0.10.0
+    - tensorboard==2.2.1
+    - tensorboard-plugin-wit==1.6.0.post3
+    - tensorboardx==2.0
+    - terminado==0.8.3
+    - tqdm==4.45.0
+    - urllib3==1.25.9
+    - webencodings==0.5.1
+    - werkzeug==1.0.1