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PerRow

class torch.ao.quantization.observer.PerRow[source][source]

Represents row-wise granularity in quantization.

This is a special case of per-axis quantization and is unique to Float8 matmuls where the input is quantized with a block_size of (1, …, input.shape[-1]). And the weight is quantized with a block_size of (1, weight.shape[1]).

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