How to make Keras use Tensorflow backend in Anaconda?

To configure Keras to use TensorFlow as the backend in Anaconda, follow these steps:

Step 1: Install Anaconda

First, ensure Anaconda is installed on your system. Download the installer from the Anaconda official website and proceed with installation.

Step 2: Create a New conda Environment

To avoid package and version conflicts across different projects, it is recommended to create a new conda environment for each project. Open the terminal or Anaconda command prompt and run the following command:

bash
conda create -n keras_env python=3.8

Here, keras_env is the name of the new environment, and python=3.8 specifies the Python version.

Step 3: Activate the New Environment

Use the following command to activate the newly created environment:

bash
conda activate keras_env

Step 4: Install TensorFlow and Keras

In the activated environment, install TensorFlow and Keras. TensorFlow can directly serve as the backend for Keras; use the following commands to install:

bash
conda install tensorflow
pip install keras

Step 5: Verify Installation

After installation, perform a simple test to confirm that Keras can use TensorFlow as the backend. Create a simple Python script, such as test_keras.py, with the following content:

python
import keras
from keras.models import Sequential
from keras.layers import Dense

model = Sequential([
    Dense(32, input_shape=(784,)),
    Dense(10, activation='softmax'),
])

model.compile(optimizer='adam',
              loss='categorical_crossentropy',
              metrics=['accuracy'])

print('Using TensorFlow version:', keras.backend.tensorflow_backend.tf.__version__)

Step 6: Run the Test Script

Activate your environment in the terminal and run the script:

bash
python test_keras.py

After running, it should display the TensorFlow version and confirm no errors occurred, indicating that Keras has successfully used TensorFlow as the backend.

This method sets up a clear environment for your project while ensuring that package and dependency versions do not conflict.