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# Quantization Schemes

AMD Quark for ONNX is capable of handling `per tensor` and `per channel` quantization, supporting both symmetric and asymmetric methods.

- Per Tensor Quantization means quantizing the tensor with one scalar. The scaling factor is a scalar.

- Per Channel Quantization means that for each dimension, typically the channel dimension of a tensor, you quantize the values in the tensor with different quantization parameters. The scaling factor is a 1-D tensor with the length of the quantization axis. For the input tensor with shape `(D0, ..., Di, ..., Dn)` and `ch_axis=i`, the scaling factor is a 1-D tensor of length `Di`.