Dependency incompatibility when trying to Calculate Principal Directions on Google Colab

[machine-learner]

I've used the command %pip install tensorflow-gpu==1.10 following your ReadMe.
The command is run after

%pip install -r requirements.txt
%pip install dareblopy

Then I copied the find_principal_directions.py to the Colab like this:

from dataloader import *
import numpy as np
import tensorflow as tf
import principal_directions.classifier


def parse_tfrecord_np(record):
    ex = tf.train.Example()
    ex.ParseFromString(record)
    shape = ex.features.feature['shape'].int64_list.value
    data = ex.features.feature['data'].bytes_list.value[0]
    dlat = ex.features.feature['dlat'].bytes_list.value[0]
    lat = ex.features.feature['lat'].bytes_list.value[0]
    return np.fromstring(data, np.uint8).reshape(shape), np.fromstring(dlat, np.float32), np.fromstring(lat, np.float32)


class Predictions:
    def __init__(self, cfg, minibatch_gpu):
        self.minibatch_size = minibatch_gpu
        self.cfg = cfg

    def evaluate(self, logger, mapping, decoder, lod, attrib_idx):
        result_expr = []

        rnd = np.random.RandomState(5)

        with tf.Graph().as_default(), tf.Session() as sess:
            ds = tf.data.TFRecordDataset("principal_directions/generated_data.000")
            ds = ds.batch(self.minibatch_size)
            batch = ds.make_one_shot_iterator().get_next()

            classifier = principal_directions.classifier.make_classifier(attrib_idx)
            i = 0
            while True:
                try:
                    records = sess.run(batch)
                    images = []
                    dlats = []
                    lats = []
                    for r in records:
                        im, dlat, lat = parse_tfrecord_np(r)

                        # plt.imshow(im.transpose(1, 2, 0), interpolation='nearest')
                        # plt.show()

                        images.append(im)
                        dlats.append(dlat)
                        lats.append(lat)
                    images = np.stack(images)
                    dlats = np.stack(dlats)
                    lats = np.stack(lats)
                    logits = classifier.run(images, None, num_gpus=1, assume_frozen=True)
                    logits = torch.tensor(logits)
                    predictions = torch.softmax(torch.cat([logits, -logits], dim=1), dim=1)

                    result_dict = dict(latents=lats, dlatents=dlats)
                    result_dict[attrib_idx] = predictions.cpu().numpy()
                    result_expr.append(result_dict)
                    i += 1
                except tf.errors.OutOfRangeError:
                    break

        results = {key: np.concatenate([value[key] for value in result_expr], axis=0) for key in result_expr[0].keys()}

        np.save("principal_directions/wspace_att_%d" % attrib_idx, results)


def main(cfg, logger):
    torch.cuda.set_device(0)
    model = Model(
        startf=cfg.MODEL.START_CHANNEL_COUNT,
        layer_count=cfg.MODEL.LAYER_COUNT,
        maxf=cfg.MODEL.MAX_CHANNEL_COUNT,
        latent_size=cfg.MODEL.LATENT_SPACE_SIZE,
        truncation_psi=cfg.MODEL.TRUNCATIOM_PSI,
        truncation_cutoff=cfg.MODEL.TRUNCATIOM_CUTOFF,
        mapping_layers=cfg.MODEL.MAPPING_LAYERS,
        channels=cfg.MODEL.CHANNELS,
        generator=cfg.MODEL.GENERATOR,
        encoder=cfg.MODEL.ENCODER)

    model.cuda(0)
    model.eval()
    model.requires_grad_(False)

    decoder = model.decoder
    encoder = model.encoder
    mapping_tl = model.mapping_tl
    mapping_fl = model.mapping_fl
    dlatent_avg = model.dlatent_avg

    logger.info("Trainable parameters generator:")
    count_parameters(decoder)

    logger.info("Trainable parameters discriminator:")
    count_parameters(encoder)

    arguments = dict()
    arguments["iteration"] = 0

    model_dict = {
        'discriminator_s': encoder,
        'generator_s': decoder,
        'mapping_tl_s': mapping_tl,
        'mapping_fl_s': mapping_fl,
        'dlatent_avg': dlatent_avg
    }

    checkpointer = Checkpointer(cfg,
                                model_dict,
                                {},
                                logger=logger,
                                save=False)

    checkpointer.load()

    model.eval()

    layer_count = cfg.MODEL.LAYER_COUNT

    logger.info("Extracting attributes")

    decoder = nn.DataParallel(decoder)

    indices = [0, 1, 2, 3, 4, 10, 11, 17, 19]
    with torch.no_grad():
        p = Predictions(cfg, minibatch_gpu=4)
        for i in indices:
            p.evaluate(logger, mapping_fl, decoder, cfg.DATASET.MAX_RESOLUTION_LEVEL - 2, i)


if __name__ == "__main__":
    gpu_count = 1
    run(main, get_cfg_defaults(), description='StyleGAN', default_config='configs/celeba.yaml',
        world_size=gpu_count, write_log=False)

Here are the logs when I run each of the code blocks respectively:

Collecting tensorflow-gpu==1.10
  Downloading https://files.pythonhosted.org/packages/64/ca/830b7cedb073ae264d215d51bd18d7cff7a2a47e39d79f6fa23edae17bb2/tensorflow_gpu-1.10.0-cp36-cp36m-manylinux1_x86_64.whl (253.2MB)
     |████████████████████████████████| 253.3MB 52kB/s 
Requirement already satisfied: astor>=0.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.10) (0.8.1)
Collecting numpy<=1.14.5,>=1.13.3
  Downloading https://files.pythonhosted.org/packages/68/1e/116ad560de97694e2d0c1843a7a0075cc9f49e922454d32f49a80eb6f1f2/numpy-1.14.5-cp36-cp36m-manylinux1_x86_64.whl (12.2MB)
     |████████████████████████████████| 12.2MB 38.8MB/s 
Requirement already satisfied: termcolor>=1.1.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.10) (1.1.0)
Requirement already satisfied: wheel>=0.26 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.10) (0.34.2)
Requirement already satisfied: gast>=0.2.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.10) (0.3.3)
Requirement already satisfied: protobuf>=3.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.10) (3.12.4)
Requirement already satisfied: grpcio>=1.8.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.10) (1.31.0)
Collecting tensorboard<1.11.0,>=1.10.0
  Downloading https://files.pythonhosted.org/packages/c6/17/ecd918a004f297955c30b4fffbea100b1606c225dbf0443264012773c3ff/tensorboard-1.10.0-py3-none-any.whl (3.3MB)
     |████████████████████████████████| 3.3MB 44.2MB/s 
Collecting setuptools<=39.1.0
  Downloading https://files.pythonhosted.org/packages/8c/10/79282747f9169f21c053c562a0baa21815a8c7879be97abd930dbcf862e8/setuptools-39.1.0-py2.py3-none-any.whl (566kB)
     |████████████████████████████████| 573kB 42.4MB/s 
Requirement already satisfied: six>=1.10.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.10) (1.15.0)
Requirement already satisfied: absl-py>=0.1.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==1.10) (0.9.0)
Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.11.0,>=1.10.0->tensorflow-gpu==1.10) (3.2.2)
Requirement already satisfied: werkzeug>=0.11.10 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.11.0,>=1.10.0->tensorflow-gpu==1.10) (1.0.1)
Requirement already satisfied: importlib-metadata; python_version < "3.8" in /usr/local/lib/python3.6/dist-packages (from markdown>=2.6.8->tensorboard<1.11.0,>=1.10.0->tensorflow-gpu==1.10) (1.7.0)
Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.6/dist-packages (from importlib-metadata; python_version < "3.8"->markdown>=2.6.8->tensorboard<1.11.0,>=1.10.0->tensorflow-gpu==1.10) (3.1.0)
ERROR: xarray 0.15.1 has requirement numpy>=1.15, but you'll have numpy 1.14.5 which is incompatible.
ERROR: xarray 0.15.1 has requirement setuptools>=41.2, but you'll have setuptools 39.1.0 which is incompatible.
ERROR: umap-learn 0.4.6 has requirement numpy>=1.17, but you'll have numpy 1.14.5 which is incompatible.
ERROR: tifffile 2020.7.24 has requirement numpy>=1.15.1, but you'll have numpy 1.14.5 which is incompatible.
ERROR: tensorflow 2.3.0 has requirement numpy<1.19.0,>=1.16.0, but you'll have numpy 1.14.5 which is incompatible.
ERROR: tensorflow 2.3.0 has requirement tensorboard<3,>=2.3.0, but you'll have tensorboard 1.10.0 which is incompatible.
ERROR: spacy 2.2.4 has requirement numpy>=1.15.0, but you'll have numpy 1.14.5 which is incompatible.
ERROR: plotnine 0.6.0 has requirement numpy>=1.16.0, but you'll have numpy 1.14.5 which is incompatible.
ERROR: numba 0.48.0 has requirement numpy>=1.15, but you'll have numpy 1.14.5 which is incompatible.
ERROR: imgaug 0.2.9 has requirement numpy>=1.15.0, but you'll have numpy 1.14.5 which is incompatible.
ERROR: google-auth 1.17.2 has requirement setuptools>=40.3.0, but you'll have setuptools 39.1.0 which is incompatible.
ERROR: fastai 1.0.61 has requirement numpy>=1.15, but you'll have numpy 1.14.5 which is incompatible.
ERROR: datascience 0.10.6 has requirement folium==0.2.1, but you'll have folium 0.8.3 which is incompatible.
ERROR: cvxpy 1.0.31 has requirement numpy>=1.15, but you'll have numpy 1.14.5 which is incompatible.
ERROR: blis 0.4.1 has requirement numpy>=1.15.0, but you'll have numpy 1.14.5 which is incompatible.
ERROR: astropy 4.0.1.post1 has requirement numpy>=1.16, but you'll have numpy 1.14.5 which is incompatible.
ERROR: albumentations 0.1.12 has requirement imgaug<0.2.7,>=0.2.5, but you'll have imgaug 0.2.9 which is incompatible.
Installing collected packages: numpy, tensorboard, setuptools, tensorflow-gpu
  Found existing installation: numpy 1.18.5
    Uninstalling numpy-1.18.5:
      Successfully uninstalled numpy-1.18.5
  Found existing installation: tensorboard 2.3.0
    Uninstalling tensorboard-2.3.0:
      Successfully uninstalled tensorboard-2.3.0
  Found existing installation: setuptools 49.2.0
    Uninstalling setuptools-49.2.0:
      Successfully uninstalled setuptools-49.2.0
Successfully installed numpy-1.14.5 setuptools-39.1.0 tensorboard-1.10.0 tensorflow-gpu-1.10.0
WARNING: The following packages were previously imported in this runtime:
  [numpy,pkg_resources]
You must restart the runtime in order to use newly installed versions.

[autoreload of pkg_resources._vendor.six failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
AttributeError: 'NoneType' object has no attribute 'cStringIO'
]
/usr/local/lib/python3.6/dist-packages/numpy/add_newdocs.py:882: UserWarning: add_newdoc was used on a pure-python object <function empty_like at 0x7fd680b3e7b8>. Prefer to attach it directly to the source.
  """)
/usr/local/lib/python3.6/dist-packages/numpy/add_newdocs.py:1239: UserWarning: add_newdoc was used on a pure-python object <function concatenate at 0x7fd680b3e8c8>. Prefer to attach it directly to the source.
  """)
/usr/local/lib/python3.6/dist-packages/numpy/add_newdocs.py:1313: UserWarning: add_newdoc was used on a pure-python object <function inner at 0x7fd680b3e9d8>. Prefer to attach it directly to the source.
  """)
/usr/local/lib/python3.6/dist-packages/numpy/add_newdocs.py:1519: UserWarning: add_newdoc was used on a pure-python object <function where at 0x7fd680b3eae8>. Prefer to attach it directly to the source.
  """)
/usr/local/lib/python3.6/dist-packages/numpy/add_newdocs.py:1596: UserWarning: add_newdoc was used on a pure-python object <function lexsort at 0x7fd680b3ebf8>. Prefer to attach it directly to the source.
  """)
/usr/local/lib/python3.6/dist-packages/numpy/add_newdocs.py:1704: UserWarning: add_newdoc was used on a pure-python object <function can_cast at 0x7fd680b3ed08>. Prefer to attach it directly to the source.
  """)
/usr/local/lib/python3.6/dist-packages/numpy/add_newdocs.py:1804: UserWarning: add_newdoc was used on a pure-python object <function min_scalar_type at 0x7fd680b3ee18>. Prefer to attach it directly to the source.
  """)
/usr/local/lib/python3.6/dist-packages/numpy/add_newdocs.py:1873: UserWarning: add_newdoc was used on a pure-python object <function result_type at 0x7fd680b3ef28>. Prefer to attach it directly to the source.
  """)
[autoreload of numpy failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
AttributeError: module 'numpy.core.multiarray' has no attribute 'newbuffer'
]
[autoreload of numpy.core failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
ImportError: cannot import name '_numpy_tester'
]
[autoreload of numpy.core.numerictypes failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
IndexError: string index out of range
]
[autoreload of numpy.core.numeric failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
ImportError: cannot import name 'TooHardError'
]
[autoreload of numpy.lib failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
NameError: name 'type_check' is not defined
]
[autoreload of numpy.matrixlib failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
NameError: name 'defmatrix' is not defined
]
[autoreload of numpy.linalg failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
ImportError: cannot import name '_numpy_tester'
]
[autoreload of numpy.lib.function_base failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
ImportError: cannot import name 'digitize'
]
[autoreload of numpy.fft failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
ImportError: cannot import name '_FFTCache'
]
[autoreload of numpy.polynomial failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
ImportError: cannot import name '_numpy_tester'
]
[autoreload of numpy.random failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
ImportError: cannot import name '_numpy_tester'
]
[autoreload of numpy.ma failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
ImportError: cannot import name '_numpy_tester'
]
[autoreload of numpy.ma.core failed: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/IPython/extensions/autoreload.py", line 247, in check
    superreload(m, reload, self.old_objects)
AttributeError: module 'numpy' has no attribute 'rank'
]
---------------------------------------------------------------------------
ImportError                               Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow.py in <module>()
     57 
---> 58   from tensorflow.python.pywrap_tensorflow_internal import *
     59   from tensorflow.python.pywrap_tensorflow_internal import __version__

7 frames
ImportError: libcublas.so.9.0: cannot open shared object file: No such file or directory

During handling of the above exception, another exception occurred:

ImportError                               Traceback (most recent call last)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow.py in <module>()
     72 for some common reasons and solutions.  Include the entire stack trace
     73 above this error message when asking for help.""" % traceback.format_exc()
---> 74   raise ImportError(msg)
     75 
     76 # pylint: enable=wildcard-import,g-import-not-at-top,unused-import,line-too-long

ImportError: Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
    from tensorflow.python.pywrap_tensorflow_internal import *
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
    _pywrap_tensorflow_internal = swig_import_helper()
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
  File "/usr/lib/python3.6/imp.py", line 243, in load_module
    return load_dynamic(name, filename, file)
  File "/usr/lib/python3.6/imp.py", line 343, in load_dynamic
    return _load(spec)
ImportError: libcublas.so.9.0: cannot open shared object file: No such file or directory


Failed to load the native TensorFlow runtime.

See https://www.tensorflow.org/install/install_sources#common_installation_problems

for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

---------------------------------------------------------------------------
NOTE: If your import is failing due to a missing package, you can
manually install dependencies using either !pip or !apt.

To view examples of installing some common dependencies, click the
"Open Examples" button below.
---------------------------------------------------------------------------

[podgorskiy]

It uses pretrained classifiers from https://github.com/NVlabs/stylegan/blob/master/metrics/linear_separability.py

ImportError: libcublas.so.9.0: cannot open shared object file: No such file or directory
It depends on tensorflow 1.10 which depends on some old by now CUDA and cuDNN runtime.

I do not know why there is conflict of numpy versions, though.