CODEWITHSUNDEEP
pythontensorflowanacondaconda
Francesco Borg
Francesco Borg

Reputation: 57

tensorflow: ModuleNotFoundError: No module named 'tensorflow.python.tools'?

I'm trying to install tensorflow, to do so I use the following: conda install -c conda-forge/label/cf201901 tensorflow

However when I import tensorflow the following error raises up: ModuleNotFoundError: No module named 'tensorflow.python.tools'. I took a look at other questions here but the solutions didn't work for me. Can you help?

I'm using python 3.7.1 and conda 4.12.0

Upvotes: 0

Views: 2109

Answers (2)

Jirayu Kaewprateep
Jirayu Kaewprateep

Reputation: 766

I found these generics errors they posted in the tutorials saved_model and their recommendation is exactly use of these functions tf.compat.v1.saved_model.utils.build_tensor_info or tf.compat.v1.saved_model.build_tensor_info. build_tensor_info

It is about the version target, provides the methods used, and the target versions. Using compatibilities matrixes or compile from Github.

Requirements:
1. Ubuntu 20.04.03
2. Anaconda 3-2022.05-Linux-x86_64

1. sudo apt-get install pip
2. pip install see
3. bash Anaconda 3-2022.05-Linux-x86_64
4. sudo /root/anaconda3/bin/conda install -c conda-forge/label/cf201901 tensorflow

[ Generics Errors from the target function ]:

WARNING:tensorflow:From /tmpfs/src/tf_docs_env/lib/python3.7/site-packages/tensorflow/python/tools/saved_model_cli.py:451: load (from tensorflow.python.saved_model.loader_impl) is deprecated and will be removed in a future version.
    Instructions for updating:
    This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.loader.load or tf.compat.v1.saved_model.load. There will be a new function for importing SavedModels in Tensorflow 2.0.
    INFO:tensorflow:Saver not created because there are no variables in the graph to restore
    INFO:tensorflow:The specified SavedModel has no variables; no checkpoints were restored.
    Result for output key output:
    12.0

[ Recommendation ]:

This function will only be available through the v1 compatibility library as
tf.compat.v1.saved_model.utils.build_tensor_info 
or
tf.compat.v1.saved_model.build_tensor_info

[ Sample ]:

import os
from os.path import exists

import tensorflow as tf
import tensorflow.compat.v1 as tf1

tf.compat.v1.disable_eager_execution()
outputs = [ ]

def remove_dir(path):
    try:
        shutil.rmtree(path)
    except:
        pass

def add_two(input):
    return input + 2

with tf.Graph().as_default() as g:
  with tf1.Session() as sess:
    input = tf1.placeholder(tf.float32, shape=[])
    output = add_two(input)
    print("add two output: ", sess.run(output, {input: 3.}))

    # Save with SavedModelBuilder
    builder = tf1.saved_model.Builder('saved-model-builder')
    sig_def = tf1.saved_model.predict_signature_def(
        inputs={'input': input},
        outputs={'output': output})
    builder.add_meta_graph_and_variables(
        sess, tags=["serve"], signature_def_map={
            tf.saved_model.DEFAULT_SERVING_SIGNATURE_DEF_KEY: sig_def
    })
    builder.save()
    
# Save with build_tensor_info
build_tensor_info = tf.compat.v1.saved_model.build_tensor_info( tf.constant( outputs, dtype=tf.int32 ) )
print( build_tensor_info )

Upvotes: 0

user18918345
user18918345

Reputation:

By default Tensorflow will be installed on GPU. To install on CPU run this command pip install tensorflow-cpu

If that doesn't work try pip install tensorflow

If you are using anaconda environment, you can try conda install tensorflow I hope this will help you.

Upvotes: 1

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