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_r277123627
##########
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,
+ 'max_range':max_range})
+ qdata_int8, min_output, max_output = out.forward()
+ else:
+ requant = mx.sym.contrib.requantize(sym_data, sym_min_range,
sym_max_range,
+ min_calib_range,
max_calib_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?
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