导入ktrain时遇到错误，tensorflow没有名为swish的属性

Question

导入ktrain时，我得到以下错误：

AttributeError: module 'tensorflow_core.keras.activations' has no attribute 'swish'

有没有人能帮帮忙，告诉我该怎么做？同样的方法在google colab上也很有效。

完全错误：

AttributeError                            Traceback (most recent call last)
<ipython-input-3-d851226d5f91> in <module>
----> 1 import ktrain
      2 from ktrain import text

~/opt/anaconda3/envs/Anmol/lib/python3.7/site-packages/ktrain/__init__.py in <module>
      1 from .version import __version__
----> 2 from . import imports as I
      3 from .core import ArrayLearner, GenLearner, get_predictor, load_predictor, release_gpu_memory
      4 from .vision.learner import ImageClassLearner
      5 from .text.learner import BERTTextClassLearner, TransformerTextClassLearner

~/opt/anaconda3/envs/Anmol/lib/python3.7/site-packages/ktrain/imports.py in <module>
    227 logging.getLogger("transformers").setLevel(logging.ERROR)
    228 try:
--> 229     import transformers
    230 except ImportError:
    231     warnings.warn("transformers not installed - needed by various models in 'text' module")

~/opt/anaconda3/envs/Anmol/lib/python3.7/site-packages/transformers/__init__.py in <module>
    133 
    134 # Pipelines
--> 135 from .pipelines import (
    136     Conversation,
    137     ConversationalPipeline,

~/opt/anaconda3/envs/Anmol/lib/python3.7/site-packages/transformers/pipelines.py in <module>
     46     import tensorflow as tf
     47 
---> 48     from .modeling_tf_auto import (
     49         TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
     50         TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,

~/opt/anaconda3/envs/Anmol/lib/python3.7/site-packages/transformers/modeling_tf_auto.py in <module>
     49 from .configuration_utils import PretrainedConfig
     50 from .file_utils import add_start_docstrings
---> 51 from .modeling_tf_albert import (
     52     TFAlbertForMaskedLM,
     53     TFAlbertForMultipleChoice,

~/opt/anaconda3/envs/Anmol/lib/python3.7/site-packages/transformers/modeling_tf_albert.py in <module>
     22 import tensorflow as tf
     23 
---> 24 from .activations_tf import get_tf_activation
     25 from .configuration_albert import AlbertConfig
     26 from .file_utils import (

~/opt/anaconda3/envs/Anmol/lib/python3.7/site-packages/transformers/activations_tf.py in <module>
     52     "gelu": tf.keras.layers.Activation(gelu),
     53     "relu": tf.keras.activations.relu,
---> 54     "swish": tf.keras.activations.swish,
     55     "silu": tf.keras.activations.swish,
     56     "gelu_new": tf.keras.layers.Activation(gelu_new),

AttributeError: module 'tensorflow_core.keras.activations' has no attribute 'swish'  ```

Answer 1

好的，所以Mac和M1有一些问题。已按照以下步骤解决问题：(https://github.com/apple/tensorflow_macos/issues/48)

• Anaconda启动新环境如果存在

，请卸载tensorflow和tensorboard

• 将x86_64文件夹中的所有文件从11_0重命名为10_16。

tensorflow_macos-0.1a0-cp38-cp38-macosx_10_16_x86_64.whl

• 示例

在Conda控制台中，使用您的用户名替换'username‘：

• pip install pip pip setuptools cached-property six

pip install "/Users/username/Downloads/tensorflow_macos/x86_64/grpcio-1.33.2-cp38-cp38-macosx_10_16_x86_64.whl"

• pip install "/Users/username/Downloads/tensorflow_macos/x86_64/h5py-2.10.0-cp38-cp38-macosx_10_16_x86_64.whl"
• pip install“/Users/
• /Downloads/tensorflow_macos/x86_64/numpy-1.18.5-cp38-cp38-macosx_10_16_x86_64.whl"
• pip install "/Users/username/Downloads/tensorflow_macos/x86_64/scipy-1.5.4-cp38-cp38-macosx_10_16_x86_64.whl"
• pip install "/Users/username/Downloads/tensorflow_macos/x86_64/tensorflow_addons-0.11.2+mlcompute-cp38-cp38-macosx_10_16_x86_64. "/Users/username/Downloads/tensorflow_macos/x86_64/tensorflow_macos-0.1a0-cp38-cp38-macosx_10_16_x86_64.whl"

“

• pip安装absl-py astunparse扁平缓冲区gast google_pasta keras_preprocessing opt_einsum协议pip tensorflow_estimator typing_extensions wrapt typing_extensions wrapt wheel typeguard
• pip install”/Users/username/Downloads/tensorflow_macos/x86_64/tensorflow_macos-0.1a0-cp38-cp38-macosx_10_16_x86_64.whl“

Answer 2

检查用于Tensorflow (和转换器)的版本。您可以在GitHub：https://github.com/amaiya/ktrain/issues/255中查看此问题

我使用ktrain==0.25.4和tensorflow==2.4.1，一切都正常。