def __init__(self, config, xnor=False):
self.bits = 1 if xnor else 2
self.hls_type = XnorPrecisionType() if xnor else IntegerPrecisionType(width=2, signed=True)
self.alpha = config['config']['alpha']
# Use the QKeras quantizer to handle any stochastic / alpha stuff
self.quantizer_fn = get_quantizer(config)
# Then we use our BinaryQuantizer to convert to '0,1' format
self.binary_quantizer = BinaryQuantizer(1) if xnor else BinaryQuantizer(2)
def __init__(self, config):
self.quantizer_fn = get_quantizer(config)
self.alpha = config['config'].get('alpha', None)
if config['class_name'] == 'quantized_bits':
self.bits = config['config']['bits']
self.hls_type = get_type(config)
# ! includes stochastic_ternary
elif 'ternary' in config['class_name']:
self.bits = 2
self.hls_type = IntegerPrecisionType(width=2, signed=True)
# ! includes stochastic_binary
elif 'binary' in config['class_name']:
self.bits = 1
self.hls_type = XnorPrecisionType()
else:
print("Unsupported quantizer: " + config['class_name'])
self.bits = 16
self.hls_type = FixedPrecisionType(width=16, integer=6, signed=True)
def __init__(self, config):
self.bits = config['config']['bits']
self.quantizer_fn = get_quantizer(config)
self.hls_type = ExponentPrecisionType(width=self.bits, signed=True)