Quantization

Post-training weight quantization utilities and Qwix integration.

taktiny.utils.quantization.quantize_linear_weight(array, rule, input_axis_count, batch_axis_count=0, scale_dtype=None)[source]
Return type:

Any

Parameters:

  • array (Any)

  • rule (Any)

  • input_axis_count (int)

  • batch_axis_count (int)

  • scale_dtype (Any)

taktiny.utils.quantization.quantize_conv_weight(array, rule, output_axis_count=1, scale_dtype=None)[source]

Quantizes a convolution kernel per structured output channel.

Return type:

Any

Parameters:

  • array (Any)

  • rule (Any)

  • output_axis_count (int)

  • scale_dtype (Any)

taktiny.utils.quantization.quantize_embedding_weight(array, rule, scale_dtype=None, vocabulary_axis_count=1)[source]
Return type:

Any

Parameters:

  • array (Any)

  • rule (Any)

  • scale_dtype (Any)

  • vocabulary_axis_count (int)

taktiny.utils.quantization.quantization_rules(quantization)[source]
Return type:

tuple[QuantizationRule, ...]

Parameters:

quantization (Any)