[
https://issues.apache.org/jira/browse/MXNET-1397?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
shoubhik bhattacharya updated MXNET-1397:
-----------------------------------------
Description:
Reproducible code
{code:java}
from mxnet.ndarray.contrib import quantize, requantize, dequantize
from mxnet import nd
import numpy as np
import mxnet as mx
{code}
{code:java}
# requantize and dequantize work with ndarry
data = nd.array(np.random.uniform(size=(5,5))) min_ = data_.min() max_ =
data_.max()
a,b,c = quantize(data_, min_, max_)
requantize(a.astype('int32'),b,c)
#output
[ [[ 94 120 32 92 73] [ 32 105 110 112 100] [ 13 72 57 111 127] [ 20 2 118 37
119] [ 40 70 26 77 56]] <NDArray 5x5 @cpu(0)>, [-1.1555843e-07] <NDArray 1
@cpu(0)>, [1.1555843e-07] <NDArray 1 @cpu(0)>]
{code}
{code:java}
# requantize and dequantize do not work with symbolic api
data__ = nd.array(np.random.uniform(size=(5,5)))
min__ = data__.min()
max__ = data__.max()
data_ = mx.sym.Variable('data_')
min_ = mx.sym.Variable('min_')
max_ = mx.sym.Variable('max_')
quant, q_min, q_max = mx.sym.contrib.quantize(data_, min_, max_)
requant, requant_min, requant_max =
mx.sym.contrib.requantize(quant.astype('int32'), q_min, q_max,
min_calib_range=None,max_calib_range=None)
dequant = mx.sym.contrib.dequantize(requant, requant_min, requant_max)
ex = dequant.bind(ctx=mx.cpu(), args={'data_':data__, 'min_':min__,
'max_':max__})
out = ex.forward()
ex.outputs[0].asnumpy()
#output
---------------------------------------------------------------------------
MXNetError Traceback (most recent call last)
<ipython-input-38-01aee958ded9> in <module>
8
9 quant, q_min, q_max = mx.sym.contrib.quantize(data_, min_, max_)
---> 10 requant = mx.sym.contrib.requantize(quant.astype('int32'), q_min, q_max)
11
12
~/anaconda/anaconda3/envs/mxnet_1_4_p36/lib/python3.6/site-packages/mxnet/symbol/register.py
in requantize(data, min_range, max_range, min_calib_range, max_calib_range,
name, attr, out, **kwargs)
~/anaconda/anaconda3/envs/mxnet_1_4_p36/lib/python3.6/site-packages/mxnet/_ctypes/symbol.py
in _symbol_creator(handle, args, kwargs, keys, vals, name)
133 s._compose(*args, name=name)
134 elif kwargs:
--> 135 s._compose(name=name, **kwargs)
136 else:
137 s._compose(name=name)
~/anaconda/anaconda3/envs/mxnet_1_4_p36/lib/python3.6/site-packages/mxnet/symbol/symbol.py
in _compose(self, *args, **kwargs)
480 args = c_handle_array(args)
481 check_call(_LIB.MXSymbolCompose(
--> 482 self.handle, name, num_args, keys, args))
483
484 def __getitem__(self, index):
~/anaconda/anaconda3/envs/mxnet_1_4_p36/lib/python3.6/site-packages/mxnet/base.py
in check_call(ret)
250 """
251 if ret != 0:
--> 252 raise MXNetError(py_str(_LIB.MXGetLastError()))
253
254
MXNetError: [10:38:07] src/core/symbolic.cc:351: Not enough argument to call
operator _contrib_requantize{code}
was:
Reproducable code
{code:java}
from mxnet.ndarray.contrib import quantize, requantize, dequantize
from mxnet import nd
import numpy as np
import mxnet as mx
{code}
{code:java}
# requantize and dequantize work with ndarry
data = nd.array(np.random.uniform(size=(5,5))) min_ = data_.min() max_ =
data_.max()
a,b,c = quantize(data_, min_, max_)
requantize(a.astype('int32'),b,c)
#output
[ [[ 94 120 32 92 73] [ 32 105 110 112 100] [ 13 72 57 111 127] [ 20 2 118 37
119] [ 40 70 26 77 56]] <NDArray 5x5 @cpu(0)>, [-1.1555843e-07] <NDArray 1
@cpu(0)>, [1.1555843e-07] <NDArray 1 @cpu(0)>]
{code}
{code:java}
# requantize and dequantize do not work with symbolic api
data__ = nd.array(np.random.uniform(size=(5,5)))
min__ = data__.min()
max__ = data__.max()
data_ = mx.sym.Variable('data_')
min_ = mx.sym.Variable('min_')
max_ = mx.sym.Variable('max_')
quant, q_min, q_max = mx.sym.contrib.quantize(data_, min_, max_)
requant, requant_min, requant_max =
mx.sym.contrib.requantize(quant.astype('int32'), q_min, q_max,
min_calib_range=None,max_calib_range=None)
dequant = mx.sym.contrib.dequantize(requant, requant_min, requant_max)
ex = dequant.bind(ctx=mx.cpu(), args={'data_':data__, 'min_':min__,
'max_':max__})
out = ex.forward()
ex.outputs[0].asnumpy()
#output
---------------------------------------------------------------------------
MXNetError Traceback (most recent call last)
<ipython-input-38-01aee958ded9> in <module>
8
9 quant, q_min, q_max = mx.sym.contrib.quantize(data_, min_, max_)
---> 10 requant = mx.sym.contrib.requantize(quant.astype('int32'), q_min, q_max)
11
12
~/anaconda/anaconda3/envs/mxnet_1_4_p36/lib/python3.6/site-packages/mxnet/symbol/register.py
in requantize(data, min_range, max_range, min_calib_range, max_calib_range,
name, attr, out, **kwargs)
~/anaconda/anaconda3/envs/mxnet_1_4_p36/lib/python3.6/site-packages/mxnet/_ctypes/symbol.py
in _symbol_creator(handle, args, kwargs, keys, vals, name)
133 s._compose(*args, name=name)
134 elif kwargs:
--> 135 s._compose(name=name, **kwargs)
136 else:
137 s._compose(name=name)
~/anaconda/anaconda3/envs/mxnet_1_4_p36/lib/python3.6/site-packages/mxnet/symbol/symbol.py
in _compose(self, *args, **kwargs)
480 args = c_handle_array(args)
481 check_call(_LIB.MXSymbolCompose(
--> 482 self.handle, name, num_args, keys, args))
483
484 def __getitem__(self, index):
~/anaconda/anaconda3/envs/mxnet_1_4_p36/lib/python3.6/site-packages/mxnet/base.py
in check_call(ret)
250 """
251 if ret != 0:
--> 252 raise MXNetError(py_str(_LIB.MXGetLastError()))
253
254
MXNetError: [10:38:07] src/core/symbolic.cc:351: Not enough argument to call
operator _contrib_requantize{code}
> mxnet.ndarray.contrib requantize and dequantize not working with symbolic api
> -----------------------------------------------------------------------------
>
> Key: MXNET-1397
> URL: https://issues.apache.org/jira/browse/MXNET-1397
> Project: Apache MXNet
> Issue Type: Bug
> Components: Apache MXNet C/C++ API
> Reporter: shoubhik bhattacharya
> Assignee: Amol Lele
> Priority: Major
>
> Reproducible code
>
> {code:java}
> from mxnet.ndarray.contrib import quantize, requantize, dequantize
> from mxnet import nd
> import numpy as np
> import mxnet as mx
> {code}
> {code:java}
> # requantize and dequantize work with ndarry
> data = nd.array(np.random.uniform(size=(5,5))) min_ = data_.min() max_ =
> data_.max()
> a,b,c = quantize(data_, min_, max_)
> requantize(a.astype('int32'),b,c)
> #output
> [ [[ 94 120 32 92 73] [ 32 105 110 112 100] [ 13 72 57 111 127] [ 20 2 118 37
> 119] [ 40 70 26 77 56]] <NDArray 5x5 @cpu(0)>, [-1.1555843e-07] <NDArray 1
> @cpu(0)>, [1.1555843e-07] <NDArray 1 @cpu(0)>]
> {code}
> {code:java}
> # requantize and dequantize do not work with symbolic api
> data__ = nd.array(np.random.uniform(size=(5,5)))
> min__ = data__.min()
> max__ = data__.max()
> data_ = mx.sym.Variable('data_')
> min_ = mx.sym.Variable('min_')
> max_ = mx.sym.Variable('max_')
> quant, q_min, q_max = mx.sym.contrib.quantize(data_, min_, max_)
> requant, requant_min, requant_max =
> mx.sym.contrib.requantize(quant.astype('int32'), q_min, q_max,
> min_calib_range=None,max_calib_range=None)
> dequant = mx.sym.contrib.dequantize(requant, requant_min, requant_max)
> ex = dequant.bind(ctx=mx.cpu(), args={'data_':data__, 'min_':min__,
> 'max_':max__})
> out = ex.forward()
> ex.outputs[0].asnumpy()
> #output
> ---------------------------------------------------------------------------
> MXNetError Traceback (most recent call last)
> <ipython-input-38-01aee958ded9> in <module>
> 8
> 9 quant, q_min, q_max = mx.sym.contrib.quantize(data_, min_, max_)
> ---> 10 requant = mx.sym.contrib.requantize(quant.astype('int32'), q_min,
> q_max)
> 11
> 12
> ~/anaconda/anaconda3/envs/mxnet_1_4_p36/lib/python3.6/site-packages/mxnet/symbol/register.py
> in requantize(data, min_range, max_range, min_calib_range, max_calib_range,
> name, attr, out, **kwargs)
> ~/anaconda/anaconda3/envs/mxnet_1_4_p36/lib/python3.6/site-packages/mxnet/_ctypes/symbol.py
> in _symbol_creator(handle, args, kwargs, keys, vals, name)
> 133 s._compose(*args, name=name)
> 134 elif kwargs:
> --> 135 s._compose(name=name, **kwargs)
> 136 else:
> 137 s._compose(name=name)
> ~/anaconda/anaconda3/envs/mxnet_1_4_p36/lib/python3.6/site-packages/mxnet/symbol/symbol.py
> in _compose(self, *args, **kwargs)
> 480 args = c_handle_array(args)
> 481 check_call(_LIB.MXSymbolCompose(
> --> 482 self.handle, name, num_args, keys, args))
> 483
> 484 def __getitem__(self, index):
> ~/anaconda/anaconda3/envs/mxnet_1_4_p36/lib/python3.6/site-packages/mxnet/base.py
> in check_call(ret)
> 250 """
> 251 if ret != 0:
> --> 252 raise MXNetError(py_str(_LIB.MXGetLastError()))
> 253
> 254
> MXNetError: [10:38:07] src/core/symbolic.cc:351: Not enough argument to call
> operator _contrib_requantize{code}
>
>
>
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