Related Issues (20)
- Multipel input quantization HOT 1
- Quantized model - how to properly save and use QuantizationSimModel HOT 4
- Remove aimet_torch dependency from aimet_onnx unit tests
- Fix bokeh server port collision issue
- Utils - ERROR -Functional ops that are not marked as math invariant were found in the model. AIMET features will not work properly for such ops. HOT 4
- Mistake in the comment in the Adaround example script HOT 1
- Fix a bug when calculating per-channel gradients in range learning
- Keras - Range Learning TF Enhanced BN Fold to Scale Drop in Accuarcy
- PyTorch quantizeDequantize unable to handle non-contiguous input tensors
- Restore mutable BNs to correct state TF BN reestimation
- When is_symmetric of Quantization Simulation Configuration file is True, offset in the encoding file is not 0 HOT 6
- Foldable BN check on (conv, conv), concat, bn.
- get_input_shape_batch_size does not work for 4-dim tensors
- Variable length intermediate conv padding check
- The.pth model saved by save_checkpoint is inconsistent with the.pth model exported by this model HOT 5
- Refactor long import in test_elementwise_ops.py
- What is the paper referenced by QAT with Range Learning? HOT 3
- TypeError in quantize_dequantize when applying QAT with certain parameters HOT 8
- Implement autograd-friendly parameter quantization mechanism
- Add ElementwiseOps for Argmin, Argmax, Ceil and Floor HOT 1
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