apeforest commented on a change in pull request #14749: [Mxnet-1397] Support
symbolic api for requantize and dequantize
URL: https://github.com/apache/incubator-mxnet/pull/14749#discussion_r277123561
##########
File path: tests/python/quantization/test_quantization.py
##########
@@ -124,7 +150,40 @@ def check_requantize(shape, min_calib_range=None,
max_calib_range=None):
assert_almost_equal(qdata_int8.asnumpy(), qdata_int8_np, atol = 1)
assert_almost_equal(min_output.asnumpy(), np.array([min_output_np]))
assert_almost_equal(max_output.asnumpy(), np.array([max_output_np]))
+
+ def check_requantize_with_symbol(shape, min_calib_range=None,
max_calib_range=None):
+ qdata = mx.nd.random.uniform(low=-1000.0, high=1000.0,
shape=shape).astype('int32')
+ min_range = mx.nd.array([-1010.0])
+ max_range = mx.nd.array([1020.0])
+ sym_data = mx.sym.Variable('data')
+ sym_min_range = mx.sym.Variable('min_range')
+ sym_max_range = mx.sym.Variable('max_range')
+ if min_calib_range is None or max_calib_range is None:
+ requant = mx.sym.contrib.requantize(sym_data, sym_min_range,
sym_max_range)
+ out = requant.bind(ctx=mx.cpu(), args={'data':qdata,
'min_range':min_range,
Review comment:
use `ctx=mx.current_context()` so this test can cover both CPU and GPU
computation?
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
With regards,
Apache Git Services
