tensorflow issue?

[tdmseismo]

I successfully installed the package but I get an error when I try to run the first tutorial file: "01_True_positive_and_false_negative_examples_of_the_EqT_model.py".

I would appreciate it if you could help me to solve this problem. I have already tried to reinstall tensorflow and keras but the issue still persists.

The error is as below:

Using TensorFlow backend.

---

TypeError Traceback (most recent call last)
in
12 import numpy as np
13 import matplotlib.pyplot as plt
---> 14 from keras.models import load_model, Model
15 from EqT_libs.EqT_utils import DataGeneratorPrediction, picker, generate_arrays_from_file
16 from EqT_libs.EqT_utils import f1, SeqSelfAttention, FeedForward, LayerNormalization

~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/keras/init.py in
1 from future import absolute_import
2
----> 3 from . import utils
4 from . import activations
5 from . import applications

~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/keras/utils/init.py in
4 from . import data_utils
5 from . import io_utils
----> 6 from . import conv_utils
7 from . import losses_utils
8 from . import metrics_utils

~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/keras/utils/conv_utils.py in
7 from six.moves import range
8 import numpy as np
----> 9 from .. import backend as K
10
11

~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/keras/backend/init.py in
----> 1 from .load_backend import epsilon
2 from .load_backend import set_epsilon
3 from .load_backend import floatx
4 from .load_backend import set_floatx
5 from .load_backend import cast_to_floatx

~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/keras/backend/load_backend.py in
88 elif _BACKEND == 'tensorflow':
89 sys.stderr.write('Using TensorFlow backend.\n')
---> 90 from .tensorflow_backend import *
91 else:
92 # Try and load external backend.

~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py in
3 from future import print_function
4
----> 5 import tensorflow as tf
6 from tensorflow.python.eager import context
7 from tensorflow.python.framework import device as tfdev

~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/tensorflow/init.py in
26
27 # pylint: disable=g-bad-import-order
---> 28 from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import
29 from tensorflow.python.tools import module_util as _module_util
30

~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/tensorflow/python/init.py in
61
62 # Framework
---> 63 from tensorflow.python.framework.framework_lib import * # pylint: disable=redefined-builtin
64 from tensorflow.python.framework.versions import *
65 from tensorflow.python.framework import config

~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/tensorflow/python/framework/framework_lib.py in
23 # Classes used when building a Graph.
24 from tensorflow.python.framework.device import DeviceSpec
---> 25 from tensorflow.python.framework.ops import Graph
26 from tensorflow.python.framework.ops import Operation
27 from tensorflow.python.framework.ops import Tensor
~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/tensorflow/python/framework/ops.py in
52 from tensorflow.python.framework import versions
53 from tensorflow.python.ops import control_flow_util
---> 54 from tensorflow.python.platform import app
55 from tensorflow.python.platform import tf_logging as logging
56 from tensorflow.python.util import compat

~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/tensorflow/python/platform/app.py in
21 import sys as _sys
22
---> 23 from absl.app import run as _run
24
25 from tensorflow.python.platform import flags

~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/absl/app.py in
35
36 from absl import command_name
---> 37 from absl import flags
38 from absl import logging
39

~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/absl/flags/init.py in
33 import warnings
34
---> 35 from absl.flags import _argument_parser
36 from absl.flags import _defines
37 from absl.flags import _exceptions

~/Programs/miniconda3/envs/seqt/lib/python3.6/site-packages/absl/flags/_argument_parser.py in
80
81
---> 82 class ArgumentParser(Generic[_T], metaclass=_ArgumentParserCache):
83 """Base class used to parse and convert arguments.
84

TypeError: metaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its bases

[MrXiaoXiao]

It seems that the problem is caused by incorrect installation of tensorflow and keras. What verions of tensorflow and keras are you using?

[tdmseismo]

I have followed the installation guide provided in the site. Here is the list of installed packages:
$ conda list | grep "tensorflow"
tensorflow 1.14.0 hc3e5e64_0 conda-forge
tensorflow-base 1.14.0 py36hc3e5e64_0 conda-forge
tensorflow-estimator 1.14.0 py36h5ca1d4c_0 conda-forge
tensorflow-gpu 1.14.0 h0d30ee6_0

$ conda list | grep "keras"
keras-applications 1.0.8 py_1 conda-forge
keras-base 2.3.1 py36_0
keras-gpu 2.3.1 0
keras-preprocessing 1.1.2 pyhd8ed1ab_0 conda-forge
keras-rectified-adam 0.20.0 pypi_0 pypi

[MrXiaoXiao]

You can try to install tensorflow and keras through anaconda channel (conda install -c anaconda tensorflow=1.14 keras=2.3.1). This might solve your problem.

[tdmseismo]

Thanks for the suggestion but the issue still persists!

[heloproc]

It seems like there is a conflict with the metaclass in your code. The metaclass of a derived class must be a subclass of the metaclasses of all its bases. Double-check the inheritance hierarchy of your classes to ensure that the metaclasses are compatible.
Or is there some conflicting metaclasses used in your code? Just check it