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How to create a tensorflow serving client for the 'wide and deep' model?

I've created a model based on the 'wide and deep' example (https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/learn/wide_n_deep_tutorial.py).
I've exported the model as follows:
m = build_estimator(model_dir)
m.fit(input_fn=lambda: input_fn(df_train, True), steps=FLAGS.train_steps)
results = m.evaluate(input_fn=lambda: input_fn(df_test, True), steps=1)
print('Model statistics:')
for key in sorted(results):
print("%s: %s" % (key, results[key]))
print('Done training!!!')
# Export model
export_path = sys.argv[-1]
print('Exporting trained model to %s' % export_path)
m.export(
export_path,
input_fn=serving_input_fn,
use_deprecated_input_fn=False,
input_feature_key=INPUT_FEATURE_KEY
My question is, how do I create a client to make predictions from this exported model? Also, have I exported the model correctly?
Ultimately I need to be able do this in Java too. I suspect I can do this by creating Java classes from proto files using gRPC.
Documentation is very sketchy, hence why I am asking on here.
Many thanks!

I wrote a simple tutorial Exporting and Serving a TensorFlow Wide & Deep Model.
TL;DR
To export an estimator there are four steps:
Define features for export as a list of all features used during estimator initialization.
Create a feature config using create_feature_spec_for_parsing.
Build a serving_input_fn suitable for use in serving using input_fn_utils.build_parsing_serving_input_fn.
Export the model using export_savedmodel().
To run a client script properly you need to do three following steps:
Create and place your script somewhere in the /serving/ folder, e.g. /serving/tensorflow_serving/example/
Create or modify corresponding BUILD file by adding a py_binary.
Build and run a model server, e.g. tensorflow_model_server.
Create, build and run a client that sends a tf.Example to our tensorflow_model_server for the inference.
For more details look at the tutorial itself.

Just spent a solid week figuring this out. First off, m.export is going to deprecated in a couple weeks, so instead of that block, use: m.export_savedmodel(export_path, input_fn=serving_input_fn).
Which means you then have to define serving_input_fn(), which of course is supposed to have a different signature than the input_fn() defined in the wide and deep tutorial. Namely, moving forward, I guess it's recommended that input_fn()-type things are supposed to return an InputFnOps object, defined here.
Here's how I figured out how to make that work:
from tensorflow.contrib.learn.python.learn.utils import input_fn_utils
from tensorflow.python.ops import array_ops
from tensorflow.python.framework import dtypes
def serving_input_fn():
features, labels = input_fn()
features["examples"] = tf.placeholder(tf.string)
serialized_tf_example = array_ops.placeholder(dtype=dtypes.string,
shape=[None],
name='input_example_tensor')
inputs = {'examples': serialized_tf_example}
labels = None # these are not known in serving!
return input_fn_utils.InputFnOps(features, labels, inputs)
This is probably not 100% idiomatic, but I'm pretty sure it works. For now.

financequotes API returning null values

I have downloaded an API called "financequotes" for Java (Link: http://financequotes-api.com/) and have attempted to use it for a project. It has been imported into my class path and all the methods run, however when I ask for a stocks details
Stock s = new Stock("INTC");
s.print();
I am given back all the details which should have been obtained online as null including name, currency, quote, etc.
Why is this?
ALTERNATIVELY - Could you suggest another finance API which is relatively simple to use to gather basic financial data?
Thanks

The creator of the API has answered - Here was the problem
The code doesn't have a request to Yahoo Finance yet. There's 2 alternative ways to fix this.
Request it through the YahooFinance static methods
Stock stock = YahooFinance.get("INTC");
stock.print();
Force a refresh of the stock's quote by using the getQuote(boolean refresh) method
Stock stock = new Stock("INTC");
stock.getQuote(true);
stock.print();
This will automatically also load/refresh the statistics and dividend data.

Intrinio provides a simple to use API for financial information. It looks like you are a Java user, there are packages on for connecting via rest API and for connecting to real time prices via websocket.
The API is easy to use for stock prices, fundamentals, options, analyst estimates, etc. This tutorial will get you started, but here is an example in curl:
curl "https://api.intrinio.com/prices?ticker=AAPL" -u "API_Password:API_Username"

How to implement filter and pagination in apache olingo v4 web service

I am new to apache olingo web service. I struck for the past two weeks to implement filter and pagination to my service.I am using latest olingo version 4. I google it and looked many blogs but there is no clear explanation. Kindly help me with sample code.It will be more use full for me.
Following are my scenario,
I am gettting the data from existing web service as XML and then i parse the XML using JAXB make it as list of entity in olingo web services.
Here how can i apply filter. If i having $filter in my URL means it throws page not found exception. If i remove that means it will work and give full result.
My question is How to apply olingo filter in XML string or
How to apply it in List of entity which i having it in a method.
Kindly give me the explenation with some sample code.
I need to give pagination to my response JSON.I need to limit the JSON value as 25 per page and need to next page URL also(For 25 to 50) like that.
How to implement this also.
I overcome lots of blogs but didn't work for me.
Here
https://templth.wordpress.com/2015/04/03/handling-odata-queries-with-elasticsearch/
In this blog,They didn't explain with full code.My problem is,I am getting data from existing web service as XML string and parse it and having in list of entity.
And I also refer this blog,
https://olingo.apache.org/doc/odata2/tutorials/Olingo_Tutorial_AdvancedRead_FilterVisitor.html
In this blog also they tell how to construct the query,My problem is how to implement $filter,$select etc from ODATA in my web service and how to filter from xml string or list of entity
Kindly suggest me with sample code.Thanks.

The Olingo team provides a huge amount of well organized help resources. The sample projects can be found by these instructions:
http://olingo.staging.apache.org/doc/odata4/tutorials/prerequisites/prerequisites.html#tutorial-sources
Complete tutorial about hte pagination can be found here:
https://olingo.apache.org/doc/odata4/tutorials/sqo_tcs/tutorial_sqo_tcs.html
I can also provide you the sample code. For example, if talking about the pagination, in your EntityCollectionProcessor implementation you just have to read the top and skip parameters and use them when generating a query to your existing web service using XML, JSON or whatever:
int skipNumber = 0;
SkipOption skipOption = uriInfo.getSkipOption();
if (skipOption != null) {
skipNumber = skipOption.getValue();
}
int topNumber = -1;
TopOption topOption = uriInfo.getTopOption();
if (topOption != null) {
topNumber = topOption.getValue();
}
EntityCollection responseEntityCollection = getDataFromService(edmEntitySet, skipNumber, topNumber);
Here the getDataFromService method generates a request to your services passing the top/skip parameters and retrieves the response. It is not advisable to filter the result set on the OData service side. Some additional steps you can find in the above mentioned tutorial.
Filtering is more complex but the main idea you can find from here:
https://olingo.apache.org/doc/odata4/tutorials/sqo_f/tutorial_sqo_f.html

How to Know Model Type using AWS Java SDK for Machine Learning

I am using AWS Java SDK to generate RealTime Predictions. To get the output of prediction i need to know what kind of machine learning model is being used is it binary , regression or multiclass. I have only the model id which i can use to locate model.Is there any API or some other way through which i can know the model type in my application.
I have searched through the documentation but haven't found anything that suits my requirement.

You can get the model type by calling the GetMLModel API.
AmazonMachineLearningClient client = ...;
GetMLModelRequest request = new GetMLModelRequest().withMLModelId("...");
client.getMLModel(request).getMLModelType();

Find Universe meta Data Information in BO SDK R4

I am new to BO, I need to find universe name and the corresponding metadata information like(Table name, column names, join conditions etc...). I am unable to find proper way to start. I looked with Data Access SDK, Semantic SDk.
Can any one please provide me the sample code or procedure for starting..
I googled a lot but i am unable to find any sample examples
I looked into this link but that code will work only on R2 Server.
http://www.forumtopics.com/busobj/viewtopic.php?t=67088
Help is Highly Apprecitated.....

Assuming you're talking about IDT based universes, you'll need to code some Java. The JavaDoc for the API is available here.
In a nutshell, you do something like this:
SlContext context = SlContext.create() ;
LocalResourceService service = context.getService(LocalResourceService.class) ;
String blxFile = service.retrieve("universe.unx","output directory") ;
RelationalBusinessLayer businessLayer = (RelationalBusinessLayer)service.load(blxFile);
RootFolder rootFolder = businessLayer.getRootFolder() ;
Once you have a hook on the rootFolder, you can use the getChildren() method to drill into the folder structure and access the various subfolders/business objects available.
You may also want to check the CmsResourceService class to access universes stored on the repository.

To get the information you are after will require a 2 part solution. Part 1 use the Rebean SDK looking at WebI reports for the Universe and object names being used with in it.
Part 2 is to break out your favorite COM programming tool, since I try to avoid COM I use the Excel Macro editor, and access the BusinessObjects Designer library. Main code snippets that I currently have are:
Dim boUniv As Designer.Universe
Dim tbl As Designer.Table
For Each tbl In boUniv.Tables
Debug.Print tbl.Name
Next tbl
This prints all of the tables in a universe.
You will need to combine the 2 parts on your own for a dependency list between WebI reports and Universes.