jinhuang415 commented on a change in pull request #10433: [MXNET-290] MKLDNN
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r193410323
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File path: tests/python/quantization/test_quantization.py
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@@ -409,11 +441,19 @@ def test_quantize_sym_with_calib():
sym = get_fp32_sym()
offline_params = [name for name in sym.list_arguments()
if not name.startswith('data') and not
name.endswith('label')]
- qsym = mx.contrib.quant._quantize_symbol(sym,
offline_params=offline_params)
- requantize_op_names = ['requantize_conv', 'requantize_fc']
- th_dict = {'conv_output': (np.random.uniform(low=100.0, high=200.0),
np.random.uniform(low=100.0, high=200.0)),
- 'fc_output': (np.random.uniform(low=100.0, high=200.0),
np.random.uniform(low=100.0, high=200.0))}
- op_name_to_th_name = {'requantize_conv': 'conv_output', 'requantize_fc':
'fc_output'}
+ if is_test_for_mkldnn():
+ dtype = 'uint8'
Review comment:
Currently MKLDNN quantization only support uint8 as input data so we made
separate logic for mkldnn.
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