Fused quant linear kernel (#19490)#19490
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Summary: Fused quant linear kernel (out = inp @ weight^T + bias) with optional dequantize/quantize. Supports 4 sets of qparams (inp, weight, bias, out), optional bias, and per-tensor/per-channel quantization. Reviewed By: mvartani-meta Differential Revision: D103754853
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Summary: Fused quant linear kernel (out = inp @ weight^T + bias) with optional dequantize/quantize. Supports 4 sets of qparams (inp, weight, bias, out), optional bias, and per-tensor/per-channel quantization. Reviewed By: mvartani-meta Differential Revision: D103754853
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Summary: Fused quant linear kernel (out = inp @ weight^T + bias) with optional dequantize/quantize. Supports 4 sets of qparams (inp, weight, bias, out), optional bias, and per-tensor/per-channel quantization. Reviewed By: mvartani-meta Differential Revision: D103754853
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Summary: Fused quant linear kernel (out = inp @ weight^T + bias) with optional dequantize/quantize. Supports 4 sets of qparams (inp, weight, bias, out), optional bias, and per-tensor/per-channel quantization. Reviewed By: mvartani-meta Differential Revision: D103754853
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Summary: Fused quant hardswish kernel with optional dequantize/quantize. Unary op that applies x * min(max(x+3, 0), 6) / 6. Supports per-tensor and per-channel quantization. Reviewed By: mvartani-meta Differential Revision: D103754780
Summary: Fused quant batch matrix multiply kernel with optional dequantize/quantize. Binary op on 3D tensors [B,M,K] x [B,K,N] -> [B,M,N]. Supports per-tensor and per-channel quantization. Reviewed By: mvartani-meta Differential Revision: D103754815
Summary: Fused quant linear kernel (out = inp @ weight^T + bias) with optional dequantize/quantize. Supports 4 sets of qparams (inp, weight, bias, out), optional bias, and per-tensor/per-channel quantization. Reviewed By: mvartani-meta Differential Revision: D103754853
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Summary: Fused quant linear kernel (out = inp @ weight^T + bias) with optional dequantize/quantize. Supports 4 sets of qparams (inp, weight, bias, out), optional bias, and per-tensor/per-channel quantization. Reviewed By: mvartani-meta Differential Revision: D103754853
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Summary:
Fused quant linear kernel (out = inp @ weight^T + bias) with optional dequantize/quantize. Supports 4 sets of qparams (inp, weight, bias, out), optional bias, and per-tensor/per-channel quantization.
Reviewed By: mvartani-meta
Differential Revision: D103754853