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author | Nina Drozd <nina.drozd@arm.com> | 2019-05-21 11:17:10 +0100 |
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committer | Nina Drozd <nina.drozd@arm.com> | 2019-05-21 12:29:23 +0100 |
commit | 997dd8c4fc5a3fef5dd1d6bce829d4d241e4becb (patch) | |
tree | 3f19266106df4db306a45828d353b18724adc79c /README.md | |
parent | 825af454a1df237dc3b5e4996ed85c71daa72284 (diff) | |
download | armnn-997dd8c4fc5a3fef5dd1d6bce829d4d241e4becb.tar.gz |
IVGCVSW-3088 Update Readme for 19.05
* Added Readme file for ArmnnQuantizer
* Added section about ArmnnQuantizer in armnn Readme file
* Updated ModelAccuracyTool Readme file with default values for --compute
Signed-off-by: Nina Drozd <nina.drozd@arm.com>
Change-Id: I5fcead522b70086dcf63dfc6c77910a7d33d83f0
Diffstat (limited to 'README.md')
-rw-r--r-- | README.md | 5 |
1 files changed, 4 insertions, 1 deletions
@@ -28,7 +28,10 @@ The 'armnn/samples' directory contains SimpleSample.cpp. A very basic example of The 'ExecuteNetwork' program, in armnn/tests/ExecuteNetwork, has no additional dependencies beyond those required by Arm NN and the model parsers. It takes any model and any input tensor, and simply prints out the output tensor. Run with no arguments to see command-line help.
-The 'ArmnnConverter' program, in armnn/src/ArmnnConverter, has no additional dependencies beyond those required by Arm NN and the model parsers. It takes a model in TensorFlow format and produces a serialized model in Arm NN format. Run with no arguments to see command-line help. Note that this program can only convert models for which all operations are supported by the serialization tool (src/armnnSerializer).
+The 'ArmnnConverter' program, in armnn/src/armnnConverter, has no additional dependencies beyond those required by Arm NN and the model parsers. It takes a model in TensorFlow format and produces a serialized model in Arm NN format. Run with no arguments to see command-line help. Note that this program can only convert models for which all operations are supported by the serialization tool (src/armnnSerializer).
+
+The 'ArmnnQuantizer' program, in armnn/src/armnnQuantizer, has no additional dependencies beyond those required by Arm NN and the model parsers. It takes a 32-bit float network and converts it into a quantized asymmetric 8-bit or quantized symmetric 16-bit network.
+Static quantization is supported by default but dynamic quantization can be enabled if CSV file of raw input tensors is specified. Run with no arguments to see command-line help.
Note that Arm NN needs to be built against a particular version of ARM's Compute Library. The get_compute_library.sh in the scripts subdirectory will clone the compute library from the review.mlplatform.org github repository into a directory alongside armnn named 'clframework' and checkouts the correct revision
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