============================= INT8 Quantized TFLite Support Status ============================= Only a subset of tflite ops supports INT8 data type. If your model includes an unsupported op, the quantized converter will raise an error.
You can check all INT8 ops below:
- ADD
- AVERAGE_POOL_2D
- CONCATENATION
- CONV_2D
- DEPTHWISE_CONV_2D
- FULLY_CONNECTED
- L2_NORMALIZATION
- LOGISTIC
- MAX_POOL_2D
- MUL
- RESHAPE
- RESIZE_BILINEAR
- SOFTMAX
- SPACE_TO_DEPTH
- TANH
- PAD
- GATHER
- BATCH_TO_SPACE_ND
- SPACE_TO_BATCH_ND
- TRANSPOSE
- MEAN
- SUB
- SUM
- SQUEEZE
- LOG_SOFTMAX
- MAXIMUM
- ARG_MAX
- MINIMUM
- LESS
- PADV2
- GREATER
- GREATER_EQUAL
- LESS_EQUAL
- SLICE
- EQUAL
- NOT_EQUAL
- SHAPE
- QUANTIZE
- RELU
- LEAKY_RELU
Note that CONCATENATION is in the supported op list, but we recommend that you avoid using it. CONCATENATION will bring additional quantization error and may lead to significant degradation of accuracy.