quantize#
- class diffsptk.UniformQuantization(abs_max=1, n_bit=8, quantizer='mid-rise')[source]#
- See this page for details. The gradient is copied from the subsequent module. - Parameters:
- abs_maxfloat > 0
- The absolute maximum value of the input waveform. 
- n_bitint >= 1
- The number of quantization bits. 
- quantizer[‘mid-rise’, ‘mid-tread’]
- The quantizer type. 
 
 - forward(x)[source]#
- Quantize the input waveform. - Parameters:
- xTensor [shape=(…,)]
- The input waveform. 
 
- Returns:
- outTensor [shape=(…,)]
- The quantized waveform. 
 
 - Examples - >>> x = diffsptk.ramp(-4, 4) >>> quantize = diffsptk.UniformQuantization(4, 2) >>> y = quantize(x).int() >>> y tensor([0, 0, 1, 1, 2, 2, 3, 3, 3], dtype=torch.int32) 
 
- diffsptk.functional.quantize(x, abs_max=1, n_bit=8, quantizer='mid-rise')[source]#
- Quantize the input waveform. - Parameters:
- xTensor [shape=(…,)]
- The input waveform. 
- abs_maxfloat > 0
- The absolute maximum value of the input waveform. 
- n_bitint >= 1
- The number of quantization bits. 
- quantizer[‘mid-rise’, ‘mid-tread’]
- The quantizer type. 
 
- Returns:
- outTensor [shape=(…,)]
- The quantized waveform. 
 
 
See also