ZhennanQin commented on a change in pull request #13697: [MKLDNN] Enable signed
int8 support for convolution.
URL: https://github.com/apache/incubator-mxnet/pull/13697#discussion_r244628274
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File path: example/quantization/imagenet_gen_qsym_mkldnn.py
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@@ -140,8 +140,8 @@ def save_params(fname, arg_params, aux_params,
logger=None):
' thresholds. This mode is expected to produce
the best inference accuracy of all three'
' kinds of quantized models if the calibration
dataset is representative enough of the'
' inference dataset.')
- parser.add_argument('--quantized-dtype', type=str, default='uint8',
- choices=['int8', 'uint8'],
+ parser.add_argument('--quantized-dtype', type=str, default='auto',
Review comment:
@KellenSunderland Deep understanding of MKLDNNquantization is always
welcome, which will help to use it better eventually. For your question, the
answer is simple. MKLDNN transform data from fp32 to uint8 with scale and
**zero shift**, which means, any negative value will be cut off to zero, it's
equivalent to relu + quantize.
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