Myujth

Is it possible to add metadata to a tensorflow serving servable, such that this metadata is also populated in the response from the servable?

If I have a servable with the file structure:

my_servable/ 
 1541778457/ 
 variables/ 
 saved_model.pb 

For example:

```
outputs 
 key: "classes"
 value 
 dtype: DT_STRING
 tensor_shape 
 dim 
 size: 8
 
 
 string_val: "a"
 string_val: "b"
 string_val: "c"
 string_val: "d"
 string_val: "e"
 string_val: "f"
 string_val: "g"
 string_val: "h"
 

outputs 
 key: "scores"
 value 
 dtype: DT_FLOAT
 tensor_shape 
 dim 
 size: 1
 
 dim 
 size: 8
 
 
 float_val: 1.212528104588273e-06
 float_val: 5.094948463124638e-08
 float_val: 0.0009737954242154956
 float_val: 0.9988483190536499
 float_val: 3.245145592245535e-07
 float_val: 0.00010837535955943167
 float_val: 4.101086960872635e-05
 float_val: 2.676981057447847e-05
 

model_spec 
 name: "my_model"
 version 
 value: 1541778457
 
 signature_name: "prediction"

If I have something like a git hash or unique identifier for the code that generated this servable like f6ca434910504532a0d50dfd12f22d4c, is it possible to get this data in the client request?

Ideally something like:

```
outputs 
 key: "classes"
 value 
 dtype: DT_STRING
 tensor_shape 
 dim 
 size: 8
 
 
 string_val: "a"
 string_val: "b"
 string_val: "c"
 string_val: "d"
 string_val: "e"
 string_val: "f"
 string_val: "g"
 string_val: "h"
 

outputs 
 key: "scores"
 value 
 dtype: DT_FLOAT
 tensor_shape 
 dim 
 size: 1
 
 dim 
 size: 8
 
 
 float_val: 1.212528104588273e-06
 float_val: 5.094948463124638e-08
 float_val: 0.0009737954242154956
 float_val: 0.9988483190536499
 float_val: 3.245145592245535e-07
 float_val: 0.00010837535955943167
 float_val: 4.101086960872635e-05
 float_val: 2.676981057447847e-05
 

model_spec 
 name: "my_model"
 version 
 value: 1541778457
 
 hash 
 value: f6ca434910504532a0d50dfd12f22d4c
 
 signature_name: "prediction"

I tried changing the directory from 1541778457 to the hash, but this gave:

W tensorflow_serving/sources/storage_path/file_system_storage_path_source.cc:268] No versions of servable default found under base path

I suppose you could approach this problem in a couple of ways. If you want the idea to change the folder name to work, remember that folder name in this case describe your model version which I think must be an integer. I would therefore assume that you would need to convert your hash to either binary or decimal and then convert it back when you receive it.

A better solution in my opinion would be if you were able to change your model and add a variable containing your hash. And add it to the models signature_def. In python that would look something like:

// create your field
hash = tf.placeholder("f6ca434910504532a0d50dfd12f22d4c",tf.string, name="HASH")

// build tensor
hash_info = tf.saved_model.utils.build_tensor_info(hash)

// add hash_info in your output in signature_def

// then you should be able to receive that data in your request