13.05.2019 · Just an addition to others looking for an answer for Tensorflow v2. As the others have mentioned, you can use the back-compatability to v1. But Tensorflow v2 does actually come with its own implementation of this.
02.08.2020 · tf.experimental.numpy: NumPy API on TensorFlow. This module provides a subset of NumPy API, built on top of TensorFlow operations. APIs are based on and have been tested with NumPy 1.16 version. The set of supported APIs may be expanded over time. Also future releases may change the baseline version ...
AttributeError: tensorflow_core.python.keras.api._v2.keras.layers.experimental' has no attribute 'SyncBatchNormalization' AttributeError: tensorflow_core.python.keras ...
07.08.2020 · keras建立model报错AttributeError: module ‘tensorflow_core._api.v2.config’ has no attribute ‘experimental_list_devices’解决方案：将Anaconda\Lib\site-packages\keras\backend下的def _get_available_gpus():“”"Get a list of available gpu devices (formatted as strings).#
04.04.2019 · Although Eager_execution is enabled by default in TF 2.0, I am getting errors while using .numpy() Please note that i am not using the code …
AttributeError: module 'tensorflow.compat.v1.profiler' has no attribute 'experimental'. Here's a code snippet: import tensorflow as tf import numpy as np from utils import * tf.compat.v1.enable_v2_behavior () from tensorflow.python.framework.ops import disable_eager_execution disable_eager_execution () options = tf.profiler.experimental ...
AttributeError: module 'tensorflow.compat.v1.profiler' has no attribute 'experimental' ... import numpy as np In [2]: options = tf.profiler.experimental.