Open rkazants opened 4 months ago
.take
Thank you for looking into this issue! Please let us know if you have any questions or require any help.
Hello @Vishwa44, is there anything we could help you with?
Hi @p-wysocki , I'm having a hard time navigating through your opset, if you can share me any relevant documentation, it will be really helpful
Could you please share your specific questions? Without them I can only recommend the Technical Guide, which is an entry point to our technical documentation.
Hi @Vishwa44, do you have any update on this task?
Best regards, Roman
hi is this issue still being worked on or is this open for taking @Vishwa44 @rkazants
I'm reopening the issue due to current assignee's inactivity.
assign to me
hey sir I submitted the pull request but sir I can't solve the rebase problem can you please help me
Hi @Aryan8912, I release this GFI due to 2 weeks are over and PR is unclear how to support MatrixSetDiagV3
.
.take
Thank you for looking into this issue! Please let us know if you have any questions or require any help.
Hello @YukumoHunter, are you still working on that issue? Do you need any help?
Hello @YukumoHunter, are you still working on that issue? Do you need any help?
Hi, I got a little busy with other work the last couple of weeks but I'm working on it now!
Hi @p-wysocki, I started working on the issue but I am unsure about the loader implementation. I looked through the latest opset but I don't think the ops there are applicable to MatrixSetDiagV3. Does this mean I am supposed to implement the operation behavior directly in the loader? Or perhaps did I miss any other useful functions that might help?
cc @rkazants
Context
OpenVINO component responsible for support of TensorFlow models is called as TensorFlow Frontend (TF FE). TF FE converts a model represented in TensorFlow opset to a model in OpenVINO opset.
In order to infer TensorFlow models with MatrixSetDiagV3 operation by OpenVINO, TF FE needs to be extended with this operation support.
What needs to be done?
For MatrixSetDiagV3 operation support, you need to implement the corresponding loader into TF FE op directory and to register it into the dictionary of Loaders. One loader is responsible for conversion (or decomposition) of one type of TensorFlow operation.
Here is an example of loader implementation for TensorFlow
Einsum
operation:In this example,
translate_einsum_op
converts TFEinsum
into OVEinsum
.NodeContext
object passed into the loader packs all info about inputs and attributes ofEinsum
operation. The loader retrieves an attribute of the equation by using theNodeContext::get_attribute()
method, prepares input vector, createsEinsum
operation from OV opset and returns a vector of outputs.Responsibility of a loader is to parse operation attributes, prepare inputs and express TF operation via OV operations sub-graph. Example for
Einsum
demonstrates the resulted sub-graph with one operation. In PR https://github.com/openvinotoolkit/openvino/pull/19007 you can see operation decomposition into multiple node sub-graph.Once you are done with implementation of the translator, you need to implement the corresponding layer tests
test_tf_MatrixInverse.py
and put it into layer_tests/tensorflow_tests directory. Example how to run some layer test:Hint
Check out how
MatrixBandPart
was implemented here: https://github.com/openvinotoolkit/openvino/pull/23082Example Pull Requests
Resources
Contact points
Ticket
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