Comments (2)
How can I create smaller size shared library for use pre-trained tensorflow model, for Android, iOS, Windows application?
from serving.
Closing as the size of the binary has been reduced significantly. Feel free to re-open if this is still an issue!
from serving.
Related Issues (20)
- Failed to build TF serving from source HOT 4
- Segmentation Fault in TF 2.11 HOT 9
- Create special docker images for AVX2/FMA et al support, with special tags HOT 2
- Memory usage of TensorFlow models HOT 7
- Continuous batching HOT 3
- Increased memory usage on TF 2.11 HOT 4
- TensorBoard profile showing high usage of relu HOT 6
- Building tensorflow serving with TCMalloc HOT 1
- Unable to compile prediction_service.proto for Golang HOT 4
- TF Serving batching for Sparse Tensors HOT 6
- TF Serving gets stuck in the polling loop due to a non-existing model provided in config file HOT 3
- Evaluate using Profile-Guided Optimization (PGO) and LLVM BOLT HOT 3
- TensorFlow serving seems to have no version attribute HOT 3
- GPU inference in Docker container fails due to missing libdevice directory HOT 4
- CPU Memory occupied by TF Serving even though serving is on GPU HOT 6
- Version 2.15 release? HOT 7
- Mismatch between TensorRT version used in TF 2.14 GPU docker images for tensorflow/serving and tensorflow/tensorflow causes segfault during inference HOT 1
- Critical Vulnerability HOT 3
- Who to contact for security issues HOT 3
- Difference between Metrics emitted by TF Serving HOT 4
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from serving.