I am trying to train a model on Google Cloud ML Engine with this command. I installed tensorflow with Anaconda.But while I training model , this error appears:
-Import error:No module named Cython.Build
Command "python setup.py egg_info" failed with error code 1 in /tmp/pip-install-0eA9cj/pycocotools/
I also added this line on setup.py :
"REQUIRED_PACKAGES = ['Pillow>=1.0', 'Matplotlib>=2.1', 'Cython>=0.28', 'pycocotools>=2.0.0'
But the problem is not solved,is there any idea to solve this problem?
Thanks in advance...
Same error for me, This is what worked for me, I added an extra --packages to my gcloud command, the packages i've downloaded from pip web repository as zip files and added as the below flag
--packages your-folder/Cython-0.28.1.tar.gz,your-folder/pycocotools-2.0.0.tar.gz --packages <your other object-detection and slim packages here>
Related
I want to use USAS semantic tagger in Google Colab using the instructions here
pip install https://github.com/UCREL/pymusas-models/releases/download/en_dual_none_contextual-0.3.1/en_dual_none_contextual-0.3.1-py3-none-any.whl
python -m spacy download en_core_web_sm
import spacy
I install the package using the above code. And then run the following:
# We exclude the following components as we do not need them.
nlp = spacy.load('en_core_web_sm', exclude=['parser', 'ner'])
# Load the English PyMUSAS rule based tagger in a separate spaCy pipeline
english_tagger_pipeline = spacy.load('en_dual_none_contextual')
# Adds the English PyMUSAS rule based tagger to the main spaCy pipeline
nlp.add_pipe('pymusas_rule_based_tagger', source=english_tagger_pipeline)
I encounter the following error for the second line:
TypeError: load_model_from_init_py() got an unexpected keyword
argument 'enable'
Note that this error doesn't show up when running the same code on my local machine. Only in Google Colab...
My sapCy version was too high. That's how I solved it:
!pip3 install spacy==3.2.3
I trained a custom CNN model using keras and tensorflow 2.2.0 as background. After that, I saved the model as .ckpt file having assets, variables, .pb file as subfolders init. After that to convert it into IR in openvino documentation it is given that we have use the following command:
**To convert such TensorFlow model:
Go to the <INSTALL_DIR>/deployment_tools/model_optimizer directory
Run the mo_tf.py script with a path to the SavedModel directory to convert a model:
python3 mo_tf.py --saved_model_dir <SAVED_MODEL_DIRECTORY>**
so, I went to the following directory as mentioned and tired the following command:
python3 mo_tf.py --saved_model_dir C:\Users\vyas\Desktop\saved_model\cp.ckpt
There is no output or anything. There is no error also.
Also, I tried the following command:
python3 mo_tf.py --saved_model_dir C:\Users\vyas\Desktop\saved_model\cp.ckpt --output_dir C:\Users\vyas\Desktop\out
Still there is no output.
Can someone please help.
I am using tensorflow 2.2.0
Can someone please help me with this
--saved_model_dir must provide a path to the SavedModel directory.
Modify your command as follows:
python3 mo_tf.py --saved_model_dir C:\Users\vyas\Desktop\saved_model
I am trying to build summerize_graph which is a tensorflow tool used to visualize the graph of model. I build this tool using bazel - referred link
$ bazel build tensorflow/tools/graph_transforms:summarize_graph
when I am trying to use it with this command
$ ./summarize_graph --in_graph=20170512-110547.pb
is giving this error
./summarize_graph: symbol lookup error: /home/sneha/.cache/bazel/_bazel_sneha/5493eb67fb8c3272a4d7ed9f724aa3c2/execroot/org_tensorflow/bazel-out/k8-opt/bin/tensorflow/tools/graph_transforms/../../../_solib_k8/_U_S_Stensorflow_Stools_Sgraph_Utransforms_Csummarize_Ugraph___Utensorflow/libtensorflow_framework.so.2: undefined symbol: _ZN10tensorflow19IsGoogleCudaEnabledEv
So I am not getting whether I should install cuda or what ? Please help !! Thank you so much.
Following the tutorial on TensorFlow for Poets (Android) (https://codelabs.developers.google.com/codelabs/tensorflow-for-poets-2/#0)
Attempting to use Inception model instead of Mobilenet
Trying to strip DecodeJpeg Op from the retrained model using strip_unused.py, but encountered the following error.
Error:
/home/user/tensorflow/bin/python: Error while finding spec for 'tensorflow.python.tools.strip_unused.py' (AttributeError: module 'tensorflow.python.tools.strip_unused' has no attribute '__path__')
Command line:
python -m tensorflow.python.tools.strip_unused.py --input_graph=tf_files/retrained_graph.pb --output_graph=tf_files/stripped_graph.pb --input_node_names="Mul" --output_node_names="final_result" --input_binary=true
Machine:
Ubuntu 16.04 LTS
Python 3.5.2
TensorFlow 1.4.1
Any assistance is greatly appreciated. Thanks!
Might be due to the typo mistake as file extension .py was specified. This seemed to work:
python -m tensorflow.python.tools.strip_unused --input_graph=tf_files/retrained_graph.pb --output_graph=tf_files/stripped_graph.pb --input_node_names="Mul" --output_node_names="final_result" --input_binary=true
Result: 997 ops in the final graph.
I am trying to run to get R + deepwater + tensorflow to work on a MBP.
The following have been installed.
Python 3.6.1
TensorFlow 1.1
The Hello, TensorFlow example on the TensorFlow website is working fine.
R version 3.4.0
curl -O http://h2o-release.s3.amazonaws.com/h2o/master/3904/R/src/contrib/h2o_3.11.0.3904.tar.gz
R CMD INSTALL h2o_3.11.0.3904.tar.gz
curl -O http://s3.amazonaws.com/h2o-deepwater/public/nightly/latest/h2o_3.11.0.tar.gz
R CMD INSTALL h2o_3.11.0.tar.gz
I am trying run the following example provided on the h2o website.
require(h2o)
h2o.init()
train <- h2o.importFile("https://h2o-public-test-data.s3.amazonaws.com/bigdata/laptop/mnist/train.csv.gz")
target <- "C785"
features <- setdiff(names(train), target)
train[target] <- as.factor(train[target])
model <- h2o.deepwater(x=features, y=target, training_frame=train, epochs=100, activation="Rectifier",
hidden=c(200,200), ignore_const_cols=FALSE, mini_batch_size=256, input_dropout_ratio=0.1,
hidden_dropout_ratios=c(0.5,0.5), stopping_rounds=3, stopping_tolerance=0.05,
stopping_metric="misclassification", score_interval=2, score_duty_cycle=0.5, score_training_samples=1000,
score_validation_samples=1000, nfolds=5, gpu=FALSE, seed=1234, backend="tensorflow")
The error I get is Error: java.lang.RuntimeException: Unable to initialize backend: Cannot find TensorFlow native library for OS: darwin, architecture: x86_64. Based on what I read on SO and the git page, I was under the impression that one does not need to build for the Mac platform.
One other thing that I tried was to use the info from https://github.com/rstudio/tensorflow. When I run install_tensorflow() I get Error: Prerequisites for installing TensorFlow not available. Please help!
We don't provide H2O+deepwater builds for MacOS. The one you downloaded is built for Linux machines (tested on Ubuntu), it's mentioned on the download page.
If you want to run it on MacOS you'd have to build both DeepWater and then H2O yourself.