jackwish commented on a change in pull request #4714: Mxnet parser for Qnn
dialect
URL: https://github.com/apache/incubator-tvm/pull/4714#discussion_r368292444
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File path: python/tvm/relay/frontend/mxnet.py
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@@ -1075,6 +1097,378 @@ def _mx_cond(inputs, attrs, subgraphs):
return ret
+def _qnn_quantize(inputs, attrs):
+ out_dtype = 'int8'
+ out_type = attrs.get_str('out_type')
+ if out_type == 'auto':
+ if attrs.has_attr('min_calib_range') and
attrs.has_attr('max_calib_range'):
+ if attrs.get_float('min_calib_range') >= 0:
+ out_dtype = 'uint8'
+ else:
+ out_dtype = 'int8'
+ else:
+ out_dtype = out_type
+ if out_dtype not in {'int8', 'uint8'}:
+ raise ValueError('Unsupported out_dtype: %s' % out_dtype)
+ min_calib_range = attrs.get_float('min_calib_range', 0.0)
+ max_calib_range = attrs.get_float('max_calib_range', 0.0)
Review comment:
That's interesting, if there is not `min/max_calib_range` provided, we are
expecting the range to be `[0.0, 0.0)`? I am not very familiar with MxNet
calibration method, but it appears to me that the *detault* min/max can derive
from `out_dtype`?
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