Numpy TypeError с импортом GPFlow в iPython ⇐ Python

[Anonymous]

Я установил gpflow и просто попытался импортировать его с помощью ipython . Но я получил ошибку, как ниже. < /P>

Код: Выделить всё

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[2], line 1
----> 1 import gpflow

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/gpflow/__init__.py:17
1 # Copyright 2016-2020 The GPflow Contributors. All Rights Reserved.
2 #
3 # Licensed under the Apache License, Version 2.0 (the "License");
(...)     14
15 # flake8: noqa
---> 17 from . import (
18     conditionals,
19     config,
20     covariances,
21     expectations,
22     experimental,
23     functions,
24     inducing_variables,
25     kernels,
26     kullback_leiblers,
27     likelihoods,
28     logdensities,
29     mean_functions,
30     models,
31     monitor,
32     optimizers,
33     posteriors,
34     probability_distributions,
35     quadrature,
36     utilities,
37 )
38 from .base import Module, Parameter
39 from .config import default_float, default_int, default_jitter

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/gpflow/conditionals/__init__.py:1
----> 1 from . import conditionals, multioutput, sample_conditionals
2 from .dispatch import conditional, sample_conditional
3 from .uncertain_conditionals import uncertain_conditional

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/gpflow/conditionals/conditionals.py:17
1 # Copyright 2017-2020 The GPflow Contributors. All Rights Reserved.
2 #
3 # Licensed under the Apache License, Version 2.0 (the "License");
(...)     12 # See the License for the specific language governing permissions and
13 # limitations under the License.
15 from typing import Optional
---> 17 import tensorflow as tf
18 from check_shapes import check_shapes
20 from ..base import MeanAndVariance

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/tensorflow/__init__.py:37
34 import sys as _sys
35 import typing as _typing
---> 37 from tensorflow.python.tools import module_util as _module_util
38 from tensorflow.python.util.lazy_loader import LazyLoader as _LazyLoader
40 # Make sure code inside the TensorFlow codebase can use tf2.enabled() at import.

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/tensorflow/python/__init__.py:45
43 from tensorflow.python import distribute
44 # from tensorflow.python import keras
---> 45 from tensorflow.python.feature_column import feature_column_lib as feature_column
46 # from tensorflow.python.layers import layers
47 from tensorflow.python.module import module

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/tensorflow/python/feature_column/feature_column_lib.py:18
15 """FeatureColumns: tools for ingesting and representing features."""
17 # pylint: disable=unused-import,line-too-long,wildcard-import,g-bad-import-order
---> 18 from tensorflow.python.feature_column.feature_column import *
19 from tensorflow.python.feature_column.feature_column_v2 import *
20 from tensorflow.python.feature_column.sequence_feature_column import *

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/tensorflow/python/feature_column/feature_column.py:143
141 from tensorflow.python.framework import sparse_tensor as sparse_tensor_lib
142 from tensorflow.python.framework import tensor_shape
--> 143 from tensorflow.python.layers import base
144 from tensorflow.python.ops import array_ops
145 from tensorflow.python.ops import check_ops

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/tensorflow/python/layers/base.py:16
1 # Copyright 2015 The TensorFlow Authors.  All Rights Reserved.
2 #
3 # Licensed under the Apache License, Version 2.0 (the "License");
(...)     13 # limitations under the License.
14 # =============================================================================
15 """Contains the base Layer class, from which all layers inherit."""
---> 16 from tensorflow.python.keras.legacy_tf_layers import base
18 InputSpec = base.InputSpec
20 keras_style_scope = base.keras_style_scope

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/tensorflow/python/keras/__init__.py:25
22 from tensorflow.python.keras import distribute
24 # See b/110718070#comment18 for more details about this import.
---> 25 from tensorflow.python.keras import models
27 from tensorflow.python.keras.engine.input_layer import Input
28 from tensorflow.python.keras.engine.sequential import Sequential

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/tensorflow/python/keras/models.py:22
20 from tensorflow.python.keras import metrics as metrics_module
21 from tensorflow.python.keras import optimizer_v1
---> 22 from tensorflow.python.keras.engine import functional
23 from tensorflow.python.keras.engine import sequential
24 from tensorflow.python.keras.engine import training

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/tensorflow/python/keras/engine/functional.py:32
30 from tensorflow.python.keras.engine import input_spec
31 from tensorflow.python.keras.engine import node as node_module
---> 32 from tensorflow.python.keras.engine import training as training_lib
33 from tensorflow.python.keras.engine import training_utils
34 from tensorflow.python.keras.saving.saved_model import network_serialization

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/tensorflow/python/keras/engine/training.py:54
52 from tensorflow.python.keras.mixed_precision import loss_scale_optimizer as lso
53 from tensorflow.python.keras.mixed_precision import policy
---> 54 from tensorflow.python.keras.saving import hdf5_format
55 from tensorflow.python.keras.saving import save
56 from tensorflow.python.keras.saving import saving_utils

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/tensorflow/python/keras/saving/hdf5_format.py:37
35 # pylint: disable=g-import-not-at-top
36 try:
---> 37   import h5py
38   HDF5_OBJECT_HEADER_LIMIT = 64512
39 except ImportError:

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/h5py/__init__.py:45
36     _warn(("h5py is running against HDF5 {0} when it was built against {1}, "
37            "this may cause problems").format(
38             '{0}.{1}.{2}'.format(*version.hdf5_version_tuple),
39             '{0}.{1}.{2}'.format(*version.hdf5_built_version_tuple)
40     ))
43 _errors.silence_errors()
---> 45 from ._conv import register_converters as _register_converters, \
46                    unregister_converters as _unregister_converters
47 _register_converters()
48 atexit.register(_unregister_converters)

File h5py/_conv.pyx:1, in init h5py._conv()

File h5py/h5r.pyx:1, in init h5py.h5r()

File h5py/h5p.pyx:1, in init h5py.h5p()

File h5py/h5t.pyx:300, in init h5py.h5t()

File h5py/h5t.pyx:295, in h5py.h5t._get_available_ftypes()

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/numpy/core/getlimits.py:504, in finfo.__new__(cls, dtype)
502 if obj is not None:
503     return obj
--> 504 obj = object.__new__(cls)._init(dtype)
505 for dt in dtypes:
506     cls._finfo_cache[dt] = obj

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/numpy/core/getlimits.py:532, in finfo._init(self, dtype)
530 self._str_resolution = machar._str_resolution.strip()
531 self._str_smallest_normal = machar._str_smallest_normal.strip()
--> 532 self._str_smallest_subnormal = machar._str_smallest_subnormal.strip()
533 return self

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/numpy/core/getlimits.py:89, in MachArLike._str_smallest_subnormal(self)
86 @property
87 def _str_smallest_subnormal(self):
88     """Return the string representation of the smallest subnormal."""
--->  89     return self._float_to_str(self.smallest_subnormal)

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/numpy/core/getlimits.py:119, in MachArLike._float_to_str(self, value)
111 def _float_to_str(self, value):
112     """Converts float to str.
113
114     Parameters
(...)    117         value to be converted.
118     """
--> 119     return self.params['fmt'] % array(_fr0(value)[0], self.ftype)

File ~/miniconda3/envs/gpr/lib/python3.11/site-packages/numpy/core/arrayprint.py:1575, in _array_str_implementation(a, max_line_width, precision, suppress_small, array2string)
1571 def _array_str_implementation(
1572         a, max_line_width=None, precision=None, suppress_small=None,
1573         array2string=array2string):
1574     """Internal version of array_str() that allows overriding array2string."""
-> 1575     if (_format_options['legacy'] 
Версии модулей следующие.

numpy версия: 1.24.3

gpflow версия: 2.10.0

версия Python: 3.11.5

ipython version: 9.4.0
< /p>
Одна чудая по поводу этой ошибки, эта ошибка на самом деле разочаровываю, если я не использую ipython. Если я использую только обычный python 

(это означает, что тип «Python» в терминале вместо «ipython» для запуска Python) и сделайте импорт gpflow , то он работает без Numpy TypeError выше. Но я чувствую себя намного комфортно с Ipython платформой для использования Python, и поэтому я надеюсь использовать gpflow в ipython .
Итак, могу ли я вас спросить, как я могу решить эту проблему?

Подробнее здесь: https://stackoverflow.com/questions/797 ... in-ipython