8.1.1.8.1.2. blueoil.quantizations.linear¶
8.1.1.8.1.2.1. Module Contents¶
8.1.1.8.1.2.1.1. Functions¶
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Linear mid tread half quantizer. |
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blueoil.quantizations.linear.linear_mid_tread_half_quantizer(bit=None, max_value=None, backward=None, dtype=tf.float32)¶ Linear mid tread half quantizer.
This quantization creates a linear mid tread half quantizer. If backward is provided, this backward will be used in backpropagation.
This quantization method is DoReFa-Net 1 activation quantization variant, the difference from DoReFa-Net 1 is to be able to change max_value.
op_type is
LinearMidTreadHalfQuantizer.Forward is:
\[\begin{split}\mathbf{X} & = \text{clip}\big(\mathbf{X}, 0, max\_value\big)\\ \mathbf{Y} & = \begin{cases} \mathbf{X}, & \text{if $bit$ is 32} \\ \frac{\text{round}\big(\frac{\mathbf{X}}{max\_value} \cdot (2^{bit}-1)\big)}{2^{bit}-1} \cdot max\_value, & otherwise \end{cases}\end{split}\]Default backward is:
\[\begin{split}\frac{\partial Loss}{\partial \mathbf{X}} = \begin{cases} \frac{\partial Loss}{\partial y}, & \text{if $0 < x < max\_value$}\\ 0, & otherwise \end{cases}\end{split}\]- Parameters
bit (int) – Specify the bit of quantization.
max_value (int) – Be used for shift and clip.
backward (callable) – Be used in backpropagation.
dtype (tf.DType) – Define the data type of args of forward and backward.
- Returns
forward function (grad_func defined).
- Return type
callable