[GitHub] ysh329 commented on a change in pull request #7363: Add tensorboard configure into ./common/fit.py and ./train_mnist.py

2017-08-10 Thread git 
ysh329 commented on a change in pull request #7363: Add tensorboard configure 
into ./common/fit.py and ./train_mnist.py
URL: https://github.com/apache/incubator-mxnet/pull/7363#discussion_r132612116
 
 

 ##
 File path: example/image-classification/common/fit.py
 ##
 @@ -168,10 +168,16 @@ def fit(args, network, data_loader, **kwargs):
 
 # callbacks that run after each batch
 batch_end_callbacks = [mx.callback.Speedometer(args.batch_size, 
args.disp_batches)]
+eval_end_callbacks = []
 if 'batch_end_callback' in kwargs:
 cbs = kwargs['batch_end_callback']
 batch_end_callbacks += cbs if isinstance(cbs, list) else [cbs]
 
 Review comment:
   @zihaolucky 
   I assigned `eval_end_callbacks` with same value as `batch_end_ballbacks`, 
but log about validation set still print for each epoch, not 
`args.disp_batches`.
   ```Python
   batch_end_callbacks = [mx.callback.Speedometer(args.batch_size, 
args.disp_batches)]
   eval_end_callbacks = [mx.callback.Speedometer(args.batch_size, 
args.disp_batches)]
   ```
 

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[GitHub] piiswrong commented on issue #7425: Tensorcore fullyconnected support

2017-08-10 Thread git 
piiswrong commented on issue #7425: Tensorcore fullyconnected support
URL: https://github.com/apache/incubator-mxnet/pull/7425#issuecomment-321739426
 
 
   This is overly complicated. Can we integrate it into 
https://github.com/apache/incubator-mxnet/pull/7147/files#diff-a1979d5d2d7e1986eab94cc82bcccd78R101
 and use use this in the original fc operator?
 

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[GitHub] eric-haibin-lin closed issue #7346: [OP] Input gamma mutated in Batch Norm

2017-08-10 Thread git 
eric-haibin-lin closed issue #7346: [OP] Input gamma mutated in Batch Norm
URL: https://github.com/apache/incubator-mxnet/issues/7346
 
 
   
 

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[GitHub] zhaoningning commented on issue #7414: why rnn train speed is not stable,sometims very slow?

2017-08-10 Thread git 
zhaoningning commented on issue #7414: why rnn train speed is not 
stable,sometims very slow?
URL: 
https://github.com/apache/incubator-mxnet/issues/7414#issuecomment-321734980
 
 
   I used mxnet.callback.Speedometer, so yes, I think 30 samples/sec is the 
mean speed  for a batch,and I fixed the input image size, so it's not variable 
sequence length;  
   
   ps: I tried training two models at the same time(using the same cnn+rnn ) 
with different gpus on a server,the training  speeds of two process almost the 
same,and when one training speed become 600 samples/sec, the other training 
speed also grow to nearly 600 samples/sec, when one training speed slow 
down,the other training slow down  as well;  And  during the low training speed 
time, most of cpus is  free, and gpus are  almost free.
   
   
   
   
 

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[GitHub] akturtle commented on issue #7281: Gradient function not returning enough gradient

2017-08-10 Thread git 
akturtle commented on issue #7281: Gradient function not returning enough 
gradient
URL: 
https://github.com/apache/incubator-mxnet/issues/7281#issuecomment-321734174
 
 
   @eldercrow Do you use some custom layers?
 

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[GitHub] thirdwing commented on issue #7375: Can I set instance weight when training?

2017-08-10 Thread git 
thirdwing commented on issue #7375: Can I set instance weight when training?
URL: 
https://github.com/apache/incubator-mxnet/issues/7375#issuecomment-321731082
 
 
   Can you give more details on what you mean by "set instance weight"?
   
   I am sorry that I don't understand your problem.
   
   On 10 Aug 2017 8:10 p.m., "reg.zhuce"  wrote:
   
   @thirdwing  Thanks
   Any proposals for my problem?
   
   ?
   You are receiving this because you were mentioned.
   Reply to this email directly, view it on GitHub
   
,
   or mute the thread
   

   .
   
 

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[GitHub] eric-haibin-lin commented on issue #7414: why rnn train speed is not stable,sometims very slow?

2017-08-10 Thread git 
eric-haibin-lin commented on issue #7414: why rnn train speed is not 
stable,sometims very slow?
URL: 
https://github.com/apache/incubator-mxnet/issues/7414#issuecomment-321729637
 
 
   Is 30 samples/sec the speed for a batch? Do you have variable sequence 
length? 
 

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[GitHub] eric-haibin-lin opened a new issue #7426: mx random seed doesn't work for random_uniform/random_normal on gpu

2017-08-10 Thread git 
eric-haibin-lin opened a new issue #7426: mx random seed doesn't work for 
random_uniform/random_normal on gpu
URL: https://github.com/apache/incubator-mxnet/issues/7426
 
 
   For bugs or installation issues, please provide the following information.
   The more information you provide, the more likely people will be able to 
help you.
   
   ## Environment info
   Operating System: DL AMI
   
   Or if installed from source: 
   
   MXNet commit hash (`git rev-parse HEAD`): 
251ae71a20d8318ab20f4c19520f74b881fdf3ff
   
   ## Minimum reproducible example
   if you are using your own code, please provide a short script that 
reproduces the error.
   ```
   import mxnet as mx
   import numpy as np
   shape = (2, 2)
   out1 = mx.nd.zeros(shape=shape, ctx=mx.gpu(0))
   out2 = mx.nd.zeros(shape=shape, ctx=mx.gpu(0))
   mx.random.seed(0)
   np.random.seed(0)
   mx.nd.random_uniform(out=out1)
   print(out1.asnumpy())
   mx.random.seed(0)
   np.random.seed(0)
   mx.nd.random_uniform(out=out2)
   print(out2.asnumpy())
   ```
   
   ```
   [[ 0.74021935  0.9209938 ]
[ 0.03902049  0.96896291]]
   
   [[ 0.92514056  0.4463501 ]
[ 0.66731918  0.10993068]]
   ```
   
 

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[GitHub] ysh329 commented on a change in pull request #7363: Add tensorboard configure into ./common/fit.py and ./train_mnist.py

2017-08-10 Thread git 
ysh329 commented on a change in pull request #7363: Add tensorboard configure 
into ./common/fit.py and ./train_mnist.py
URL: https://github.com/apache/incubator-mxnet/pull/7363#discussion_r132612116
 
 

 ##
 File path: example/image-classification/common/fit.py
 ##
 @@ -168,10 +168,16 @@ def fit(args, network, data_loader, **kwargs):
 
 # callbacks that run after each batch
 batch_end_callbacks = [mx.callback.Speedometer(args.batch_size, 
args.disp_batches)]
+eval_end_callbacks = []
 if 'batch_end_callback' in kwargs:
 cbs = kwargs['batch_end_callback']
 batch_end_callbacks += cbs if isinstance(cbs, list) else [cbs]
 
 Review comment:
   @zihaolucky 
   I assigned `eval_end_callbacks` with same value as `batch_end_ballbacks`, 
but log about validation set still print for each epoch, not 
`args.disp_batches`.
   ```Python
batch_end_callbacks = [mx.callback.Speedometer(args.batch_size, 
args.disp_batches)]
   eval_end_callbacks = [mx.callback.Speedometer(args.batch_size, 
args.disp_batches)]
   ```
 

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[GitHub] DickJC123 opened a new pull request #7425: Tensorcore fullyconnected support

2017-08-10 Thread git 
DickJC123 opened a new pull request #7425: Tensorcore fullyconnected support
URL: https://github.com/apache/incubator-mxnet/pull/7425
 
 
   Adds TensorCore algo support to the FullyConnected operator for users with 
NVIDIA Volta / cuda9 / cudnn7.  On by default, this can be disabled through an 
environment variable as in:
   
   export MXNET_CUDA_ALLOW_TENSOR_CORE=0
   
   Applies to float16 I/O instances only.
 

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[GitHub] ysh329 commented on issue #7424: train_mnist.py failed: TypeError: __init__() got an unexpected keyword argument 'multi_precision'

2017-08-10 Thread git 
ysh329 commented on issue #7424: train_mnist.py failed: TypeError: __init__() 
got an unexpected keyword argument 'multi_precision'
URL: 
https://github.com/apache/incubator-mxnet/issues/7424#issuecomment-321723869
 
 
   @ptrendx @mli @howard0su 
   After I comment this line below about `multi_precision`, it's fixed. It 
seems a not complete feature?
   ```Python
   optimizer_params = {
   'learning_rate': lr,
   'momentum' : args.mom,
   'wd' : args.wd,
   'lr_scheduler': lr_scheduler,}
   #'multi_precision': True}
   ```
 

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[GitHub] regzhuce commented on issue #7375: Can I set instance weight when training?

2017-08-10 Thread git 
regzhuce commented on issue #7375: Can I set instance weight when training?
URL: 
https://github.com/apache/incubator-mxnet/issues/7375#issuecomment-321723588
 
 
   @thirdwing Thanks
   Any proposals for my problem?
 

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[GitHub] piiswrong commented on issue #7393: add depthwise convolution's gpu version optimization

2017-08-10 Thread git 
piiswrong commented on issue #7393: add depthwise convolution's gpu version 
optimization
URL: https://github.com/apache/incubator-mxnet/pull/7393#issuecomment-321722267
 
 
   @crazy-cat Still not compiling on windows: 
https://builds.apache.org/blue/organizations/jenkins/incubator-mxnet/detail/PR-7393/2/pipeline
 

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[GitHub] ysh329 commented on a change in pull request #7363: Add tensorboard configure into ./common/fit.py and ./train_mnist.py

2017-08-10 Thread git 
ysh329 commented on a change in pull request #7363: Add tensorboard configure 
into ./common/fit.py and ./train_mnist.py
URL: https://github.com/apache/incubator-mxnet/pull/7363#discussion_r132610329
 
 

 ##
 File path: example/image-classification/common/fit.py
 ##
 @@ -168,10 +168,16 @@ def fit(args, network, data_loader, **kwargs):
 
 # callbacks that run after each batch
 batch_end_callbacks = [mx.callback.Speedometer(args.batch_size, 
args.disp_batches)]
+eval_end_callbacks = []
 if 'batch_end_callback' in kwargs:
 cbs = kwargs['batch_end_callback']
 batch_end_callbacks += cbs if isinstance(cbs, list) else [cbs]
 
+# tensorboard logs
+if "eval_end_callback" in kwargs:
+   cbs = kwargs['eval_end_callback']
+eval_end_callbacks += cbs if isinstance(cbs, list) else [cbs]
 
 Review comment:
   I verified this in current master branch, but there's some problem about 
`common/fit.py` as below:
   train_mnist.py failed: TypeError: __init__() got an unexpected keyword 
argument 'multi_precision' ? Issue #7424 ? apache/incubator-mxnet
   https://github.com/apache/incubator-mxnet/issues/7424
   
   I verified that runs in MXNet 0.10.0 Release is okay.
 

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[GitHub] ysh329 opened a new issue #7424: train_mnist.py failed: TypeError: __init__() got an unexpected keyword argument 'multi_precision'

2017-08-10 Thread git 
ysh329 opened a new issue #7424: train_mnist.py failed: TypeError: __init__() 
got an unexpected keyword argument 'multi_precision'
URL: https://github.com/apache/incubator-mxnet/issues/7424
 
 
   Release 0.10.0 is okay.   
   However, Current master branch (git clone --recursive 
https://github.com/apache/incubator-mxnet.git) occurs this problem as below 
(running in the official docker, then I cloned from github.com and run this 
train_mnist.py) :   
   ```Shell
   root@8acd2b8afd12:~/incubator-mxnet-origin/example/image-classification# 
python train_mnist.py
   INFO:root:start with arguments Namespace(add_stn=False, batch_size=64, 
disp_batches=100, dtype='float32', gpus=None, kv_store='device', 
load_epoch=None, lr=0.05, lr_factor=0.1, lr_step_epochs='10', 
model_prefix=None, mom=0.9, monitor=0, network='mlp', num_classes=10, 
num_epochs=20, num_examples=6, num_layers=None, optimizer='sgd', test_io=0, 
top_k=0, wd=0.0001)
   Traceback (most recent call last):
 File "train_mnist.py", line 91, in 
   eval_end_callback = eval_end_callbacks)
 File 
"/root/incubator-mxnet-origin/example/image-classification/common/fit.py", line 
207, in fit
   monitor= monitor)
 File "/mxnet/python/mxnet/module/base_module.py", line 465, in fit
   optimizer_params=optimizer_params)
 File "/mxnet/python/mxnet/module/module.py", line 478, in init_optimizer
   **optimizer_params)
 File "/mxnet/python/mxnet/optimizer.py", line 128, in create_optimizer
   return Optimizer.opt_registry[name.lower()](**kwargs)
 File "/mxnet/python/mxnet/optimizer.py", line 328, in __init__
   super(SGD, self).__init__(**kwargs)
   TypeError: __init__() got an unexpected keyword argument 'multi_precision'
   ```
 

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[GitHub] qiaomuf opened a new pull request #7423: Do not use LG in case of DMLC_GLOG_DEFINED enabled

2017-08-10 Thread git 
qiaomuf opened a new pull request #7423: Do not use LG in case of 
DMLC_GLOG_DEFINED enabled
URL: https://github.com/apache/incubator-mxnet/pull/7423
 
 
   When DMLC_GLOG_DEFINED is enabled, glog will be used and LG will not be 
defined. Use LG will cause compilation failure.
 

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[GitHub] chinakook commented on issue #7393: add depthwise convolution's gpu version optimization

2017-08-10 Thread git 
chinakook commented on issue #7393: add depthwise convolution's gpu version 
optimization
URL: https://github.com/apache/incubator-mxnet/pull/7393#issuecomment-321719808
 
 
   Nice work, It's a good feature for mobilenet!
 

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[GitHub] EsraaRagaa opened a new issue #7422: Data provided by data_shapes don't match names specified by data_names

2017-08-10 Thread git 
EsraaRagaa opened a new issue #7422: Data provided by data_shapes don't match 
names specified by data_names
URL: https://github.com/apache/incubator-mxnet/issues/7422
 
 
   I am trying to train my data with mxnet, the data are 20x20 images
   I put my data in a csv files in the form:
   label, pixel1, pixel2, ..., pixel400
   0,...
   1,...
   and my labels are 0 or 1,
   this is the code I used:
   batch_size = 2
   
   
   train_iterator = mx.io.NDArrayIter(X_train, Y_train, batch_size=batch_size)
   validate_iterator = mx.io.NDArrayIter(X_validate, Y_validate, 
batch_size=batch_size)
   
   ##first convelutional layer
   conv1 = mx.sym.Convolution(data=data, kernel=(3,3), num_filter=6)
   relu1 = mx.sym.Activation(data=conv1, act_type="relu")
   pool1 = mx.sym.Pooling(data=relu1, pool_type="max", kernel=(2,2), 
stride=(2,2))
   
   ##second convelutional layer
   conv2 = mx.sym.Convolution(data=pool1, kernel=(6,6), num_filter=12)
   relu2 = mx.sym.Activation(data=conv2, act_type="relu")
   pool2 = mx.sym.Pooling(data=relu2, pool_type="max", kernel=(2,2), 
stride=(2,2))
   
   ##first fully connected layer
   flatten = mx.sym.flatten(data=pool2)
   fc1 = mx.symbol.FullyConnected(data=flatten, num_hidden=12 )
   
   ##softmax loss
   lenet = mx.sym.SoftmaxOutput(data=fc1, name='softmax')
   
   ##create a trainable module on CPU 0
   lenet_model = mx.mod.Module(symbol=lenet, context=mx.cpu())
   device = mx.cpu()
   
   ##train using parameters
   
   '''
   model = mx.model.FeedForward.create(lenet_model,
   X = X_train,
   y = Y_train,
   ctx = device,
   num_epoch = 10)
   '''
   lenet_model.fit(train_iterator,
eval_data=validate_iterator,
optimizer='sgd',
optimizer_params={'learning_rate':0.1},
eval_metric='acc',
batch_end_callback = 
mx.callback.Speedometer(batch_size, 100),
num_epoch=10)
   # the error is:
Traceback (most recent call last):
   
 File "", line 7, in 
   num_epoch=10)
   
 File 
"C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\base_module.py",
 line 459, in fit
   for_training=True, force_rebind=force_rebind)
   
 File 
"C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\module.py",
 line 372, in bind
   self.data_names, self.label_names, data_shapes, label_shapes)
   
 File 
"C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\base_module.py",
 line 70, in _parse_data_desc
   _check_names_match(data_names, data_shapes, 'data', True)
   
 File 
"C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\base_module.py",
 line 62, in _check_names_match
   raise ValueError(msg)
   
   ValueError: Data provided by data_shapes don't match names specified by 
data_names ([DataDesc[_0_data,(2,),,NCHW], 
DataDesc[_1_data,(2,),,NCHW], DataDesc[_2_data,(2,),,NCHW], DataDesc[_3_data,(2,),,NCHW], 
DataDesc[_4_data,(2,),,NCHW], DataDesc[_5_data,(2,),,NCHW], DataDesc[_6_data,(2,),,NCHW], 
DataDesc[_7_data,(2,),,NCHW], DataDesc[_8_data,(2,),,NCHW], DataDesc[_9_data,(2,),,NCHW], 
DataDesc[_10_data,(2,),,NCHW], 
DataDesc[_11_data,(2,),,NCHW], 
DataDesc[_12_data,(2,),,NCHW], 
DataDesc[_13_data,(2,),,NCHW], 
DataDesc[_14_data,(2,),,NCHW], 
DataDesc[_15_data,(2,),,NCHW], 
DataDesc[_16_data,(2,),,NCHW], DataDesc[_17_data,(
 2,),,NCHW],
   ...
   ...
   ...
   ...
   , DataDesc[_2773_data,(2,),,NCHW], 
DataDesc[_2774_data,(2,),,NCHW], 
DataDesc[_2775_data,(2,),,NCHW], 
DataDesc[_2776_data,(2,),,NCHW], 
DataDesc[_2777_data,(2,),,NCHW]] vs. ['data'])
   
   # What should the data look like, what is wrong in the code, please?
   I am using win10, python2, mxnet 0.10, anaconda2
   Thanks in advance
   
 

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[GitHub] rahul003 opened a new pull request #7421: Resolve more compile warnings

2017-08-10 Thread git 
rahul003 opened a new pull request #7421: Resolve more compile warnings
URL: https://github.com/apache/incubator-mxnet/pull/7421
 
 
   All sign compare warnings. Warnings in fIrst two files showed up on GPU and 
the last file is a test file which had sign compare warnings. All of these 
occurrences don't need sign for the variable.
 

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[GitHub] EsraaRagaa opened a new issue #7420: How to pass CSVIter (images flatten in .csv file) to MXNet ?

2017-08-10 Thread git 
EsraaRagaa opened a new issue #7420: How to pass CSVIter (images flatten in 
.csv file) to MXNet ?
URL: https://github.com/apache/incubator-mxnet/issues/7420
 
 
   # Hello, 
   I am trying to train my data with mxnet, the data are 20x20 images 
   I put my data in a csv files in the form:
   label, pixel1, pixel2, ..., pixel400
   0,...
   1,...
   and my labels are 0 or 1, 
   # this is the code I used:
   -
   train_data = pd.read_csv("training_set_flatten_rows_mxnet.csv")
   keys = ['pixel.'+str(i) for i in range(1,402)]
   X_train = train_data[keys[1:]].get_values()
   X_train = X_train.reshape((2779,1,20,20))
   Y_train = train_data['pixel.1'].get_values().reshape((2779,1))
   
   validate_data = pd.read_csv("validation_set_flatten_rows_mxnet.csv")
   keys = ['pixel.'+str(i) for i in range(1,402)]
   X_validate = validate_data[keys[1:]].get_values()
   X_validate = X_validate.reshape((692,1,20,20))
   Y_validate = validate_data['pixel.1'].get_values().reshape((692,1))
   
   train_iterator = mx.io.NDArrayIter(X_train, Y_train, batch_size=batch_size)
   validate_iterator = mx.io.NDArrayIter(X_validate, Y_validate, 
batch_size=batch_size)
   
   # first convelutional layer
   conv1 = mx.sym.Convolution(data=data, kernel=(3,3), num_filter=6)
   relu1 = mx.sym.Activation(data=conv1, act_type="relu")
   pool1 = mx.sym.Pooling(data=relu1, pool_type="max", kernel=(2,2), 
stride=(2,2))
   
   # second convelutional layer
   conv2 = mx.sym.Convolution(data=pool1, kernel=(6,6), num_filter=12)
   relu2 = mx.sym.Activation(data=conv2, act_type="relu")
   pool2 = mx.sym.Pooling(data=relu2, pool_type="max", kernel=(2,2), 
stride=(2,2))
   
   # first fully connected layer
   flatten = mx.sym.flatten(data=pool2)
   fc1 = mx.symbol.FullyConnected(data=flatten, num_hidden=12 )
   # softmax loss
   lenet = mx.sym.SoftmaxOutput(data=fc1, name='softmax')
   # create a trainable module on CPU 0
   lenet_model = mx.mod.Module(symbol=lenet, context=mx.cpu())
   device = mx.cpu()
   # train using parameters
   '''
   model = mx.model.FeedForward.create(lenet_model,
   X = X_train,
   y = Y_train,
   ctx = device,
   num_epoch = 10)
   '''
   lenet_model.fit(train_iterator,
   eval_data=validate_iterator,
   optimizer='sgd',
   optimizer_params={'learning_rate':0.1},
   eval_metric='acc',
   batch_end_callback = mx.callback.Speedometer(batch_size, 
100),
   num_epoch=10)
   
   -
   
   # the error is:
   
   Traceback (most recent call last):
   
 File "", line 7, in 
   num_epoch=10)
   
 File 
"C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\base_module.py",
 line 459, in fit
   for_training=True, force_rebind=force_rebind)
   
 File 
"C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\module.py",
 line 388, in bind
   state_names=self._state_names)
   
 File 
"C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\executor_group.py",
 line 214, in __init__
   self.bind_exec(data_shapes, label_shapes, shared_group)
   
 File 
"C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\executor_group.py",
 line 310, in bind_exec
   shared_group))
   
 File 
"C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\executor_group.py",
 line 582, in _bind_ith_exec
   shared_buffer=shared_data_arrays, **input_shapes)
   
 File 
"C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\symbol.py",
 line 1375, in simple_bind
   raise RuntimeError('simple_bind failed')
   
   RuntimeError: simple_bind failed
   
   # If I comment this line in the model.fit ::
#batch_end_callback = mx.callback.Speedometer(batch_size, 100),
   
   # I get error: 
   WARNING:root:Already bound, ignoring bind()
   Traceback (most recent call last):
   
 File "", line 7, in 
   num_epoch=10)
   
 File 
"C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\base_module.py",
 line 463, in fit
   allow_missing=allow_missing, force_init=force_init)
   
 File 
"C:\Users\...\Anaconda2\lib\site-packages\mxnet-0.10.1-py2.7.egg\mxnet\module\module.py",
 line 272, in init_params
   for name, arr in self._arg_params.items():
   
   AttributeError: 'NoneType' object has no attribute 'items'
   
   I guess the error is from the the data load and passing to mxnet. 
   I don't know what does this mean and what shall I do, help me, please.
   
   
   I am using win10, python2, mxnet 0.10, anaconda2
   Thanks in advance
   
 

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[GitHub] mli commented on issue #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
mli commented on issue #7418: Enable Apache Rat + add more license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#issuecomment-321700025
 
 
   why add a new `tools/license_header.sh`. there is already a python version, 
which is able to remove ` Copyright (c) 2016 by Contributors`. The future work 
I mean is merging two headers, one is for licensen, the other is the header 
documents. 
   
   to process other files such as .js, one only need to add an entry into 
`_LANGS`
 

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[GitHub] pracheer commented on issue #7413: Initial commit of an MXNet converter.

2017-08-10 Thread git 
pracheer commented on issue #7413: Initial commit of an MXNet converter.
URL: https://github.com/apache/incubator-mxnet/pull/7413#issuecomment-321691020
 
 
   Thanks @srikris for this. Looks like @madjam just merged your changes. We'll 
take it from here. Thanks a ton!
 

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[GitHub] sergeykolychev commented on issue #7334: cannot use ImageIter in Perl package

2017-08-10 Thread git 
sergeykolychev commented on issue #7334: cannot use ImageIter in Perl package
URL: 
https://github.com/apache/incubator-mxnet/issues/7334#issuecomment-321690309
 
 
   @dokechin the changes to Image.pm were merged to master branch.
 

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[GitHub] madjam closed pull request #7413: Initial commit of an MXNet converter.

2017-08-10 Thread git 
madjam closed pull request #7413: Initial commit of an MXNet converter.
URL: https://github.com/apache/incubator-mxnet/pull/7413
 
 
   
 

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[incubator-mxnet] branch master updated: Initial commit of an MXNet converter. (#7413)

2017-08-10 Thread madjam 
This is an automated email from the ASF dual-hosted git repository.

madjam pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/master by this push:
 new 1a3faa6  Initial commit of an MXNet converter. (#7413)
1a3faa6 is described below

commit 1a3faa63f2a24820427e6454f5d6eaa72ea636c1
Author: Krishna Sridhar <1875987+srik...@users.noreply.github.com>
AuthorDate: Thu Aug 10 15:22:07 2017 -0700

Initial commit of an MXNet converter. (#7413)
---
 tools/coreml/__init__.py|  18 ++
 tools/coreml/_layers.py | 397 ++
 tools/coreml/_mxnet_converter.py| 210 
 tools/coreml/test_mxnet_converer.py | 477 
 4 files changed, 1102 insertions(+)

diff --git a/tools/coreml/__init__.py b/tools/coreml/__init__.py
new file mode 100644
index 000..e56490a
--- /dev/null
+++ b/tools/coreml/__init__.py
@@ -0,0 +1,18 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+from _mxnet_converter import *
diff --git a/tools/coreml/_layers.py b/tools/coreml/_layers.py
new file mode 100644
index 000..5148984
--- /dev/null
+++ b/tools/coreml/_layers.py
@@ -0,0 +1,397 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+# 
+#   http://www.apache.org/licenses/LICENSE-2.0
+# 
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+import numpy as _np
+
+def _get_input_output_name(net, node, index = 0):
+name = node['name']
+inputs = node['inputs']
+
+if index == 'all':
+input_name = [_get_node_name(net, inputs[id][0]) for id in 
range(len(inputs))]
+elif type(index) == int:
+input_name = _get_node_name(net, inputs[0][0])
+else:
+input_name = [_get_node_name(net, inputs[id][0]) for id in index]
+return input_name, name
+
+def _get_node_name(net, node_id):
+return net['nodes'][node_id]['name']
+
+def _get_node_shape(net, node_id):
+return net['nodes'][node_id]['shape']
+
+def convert_transpose(net, node, model, builder):
+"""Convert a transpose layer from mxnet to coreml.
+
+Parameters
+--
+network: net
+A mxnet network object.
+
+layer: node
+Node to convert.
+
+model: model
+An model for MXNet
+
+builder: NeuralNetworkBuilder
+A neural network builder object.
+"""
+input_name, output_name = _get_input_output_name(net, node)
+name = node['name']
+param = node['attr']
+from ast import literal_eval
+axes = literal_eval(param['axes'])
+builder.add_permute(name, input_name, output_name, axes)
+
+def convert_flatten(net, node, model, builder):
+"""Convert a flatten layer from mxnet to coreml.
+
+Parameters
+--
+network: net
+A mxnet network object.
+
+layer: node
+Node to convert.
+
+model: model
+An model for MXNet
+
+builder: NeuralNetworkBuilder
+A neural network builder object.
+"""
+input_name, output_name = _get_input_output_name(net, node)
+name = node['name']
+builder.add_flatten(0, name, input_name, output_name)
+
+def convert_softmax(net, node, model, builder):
+"""Convert a softmax layer from mxnet to coreml.
+
+Parameters
+--
+network: net
+A mxnet network object.
+
+layer: node
+Node to convert.
+
+model: model
+An model for MXNet
+
+builder: NeuralNetworkBuilder
+A neural network builder object.
+"""
+input_name, output_name = _get_input_out

[GitHub] piiswrong commented on issue #7417: Update mxnet in maven timely?

2017-08-10 Thread git 
piiswrong commented on issue #7417: Update mxnet in maven timely?
URL: 
https://github.com/apache/incubator-mxnet/issues/7417#issuecomment-321688945
 
 
   @javelinjs Let's release static build on maven?
 

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[GitHub] smarthi commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
smarthi commented on a change in pull request #7418: Enable Apache Rat + add 
more license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132581823
 
 

 ##
 File path: cpp-package/example/feature_extract/prepare_data_with_opencv.cpp
 ##
 @@ -1,3 +1,22 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * 
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
 /*!
  * Copyright (c) 2015 by Contributors
  */
 
 Review comment:
   ? 
 

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[incubator-mxnet-site] branch asf-site updated: Remove copyright

2017-08-10 Thread lxn2 
This is an automated email from the ASF dual-hosted git repository.

lxn2 pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet-site.git


The following commit(s) were added to refs/heads/asf-site by this push:
 new 46142fd  Remove copyright
46142fd is described below

commit 46142fd05edbaf3cff44b6960fc7f2e362072591
Author: Nguyen 
AuthorDate: Thu Aug 10 14:56:50 2017 -0700

Remove copyright
---
 index.html | 1 -
 1 file changed, 1 deletion(-)

diff --git a/index.html b/index.html
index eee2ff2..b0a0b55 100644
--- a/index.html
+++ b/index.html
@@ -336,7 +336,6 @@ Previous Navbar Layout End -->
 
 
 
- © 2015-2017 DMLC. All rights reserved. 
 
  
 https://maxcdn.bootstrapcdn.com/bootstrap/3.3.6/js/bootstrap.min.js";>

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['"comm...@mxnet.apache.org" '].

[GitHub] Lyken17 commented on issue #7376: MXbox -- a simple and flexible vision toolbox for mxnet framework.

2017-08-10 Thread git 
Lyken17 commented on issue #7376: MXbox -- a simple and flexible vision toolbox 
for mxnet framework.
URL: 
https://github.com/apache/incubator-mxnet/issues/7376#issuecomment-321681785
 
 
   @szha  Gluon's documentation seems to be under construction.  Could u show 
some examples of `mx.symbol`?  In fact `mxbox` provides 
[`mx.transforms.lambda`](https://github.com/Lyken17/mxbox/blob/master/mxbox/transforms/general.py#L140)
  which allows user to easily create extensions . Thus supports for `mx.symbol` 
should not be a trouble issue.
   
   @zhreshold Gluon and mxbox are both inspired by torchvision, so they have 
many same functions. What I think is to keep the relation of `mxbox` and 
`mxnet`  like `pytorch` and `torchvision` -- standalone but strongly connected. 
The advantage of doing this is people can develop `mxbox` without affecting 
`mxnet` (push to `mxbox` only), and user can always enjoy the latest update of 
mxbox from PyPi.
   
   Maintaining a standalone toolbox will not be a nightmare, instead, it brings 
faster update -- for example, a new network comes out, once I get the 
definition scripts and the pretrained weight, I can upload to `mxnet` and give 
a release immediately, where in mxnet, it requires a reviewer to merge in and 
extra time to release a new version on PyPi.
   
   We all aim for a good toolbox, and I think a standalone repo is a better 
choice. But as I mentioned, my free time on next semester is very limited, so 
to merge in or not, actually depends on later maintainers' idea. If he thinks 
merging to be a better choice, I will create a pull request after construction 
for `model` is finished.
   
   
 

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[GitHub] kevinthesun opened a new pull request #7419: Add resnet50_v2, resnet101_V2 and resnet152_v2 gluon pre-trained model

2017-08-10 Thread git 
kevinthesun opened a new pull request #7419: Add resnet50_v2, resnet101_V2 and 
resnet152_v2 gluon pre-trained model
URL: https://github.com/apache/incubator-mxnet/pull/7419
 
 
   @szha 
 

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[GitHub] Lyken17 commented on issue #7376: MXbox -- a simple and flexible vision toolbox for mxnet framework.

2017-08-10 Thread git 
Lyken17 commented on issue #7376: MXbox -- a simple and flexible vision toolbox 
for mxnet framework.
URL: 
https://github.com/apache/incubator-mxnet/issues/7376#issuecomment-321681785
 
 
   @szha  Gluon's documentation seems to be under construction.  Could u show 
some examples of `mx.symbol`?  In fact `mxbox` provides 
[`mx.transforms.lambda`](https://github.com/Lyken17/mxbox/blob/master/mxbox/transforms/general.py#L140)
  which allows user to easily create extensions . Thus supports for `mx.symbol` 
should not be a trouble issue.
   
   @zhreshold Gluon and mxbox are both inspired by torchvision, so they have 
many same functions. What I think is to keep the relation of `mxbox` and 
`mxnet`  like `pytorch` and `torchvision` -- standalone but strongly connected. 
The advantage of doing this is people can develop `mxbox` without affecting 
`mxnet` (push to `mxbox` only), and user can always enjoy the latest update of 
mxbox from PyPi.
   
   Maintaining a standalone toolbox will not be a nightmare, instead, it will 
brings faster update -- for example, a new network comes out, I can upload to 
`mxnet` and give a release immediately, once I get the definition scripts and 
the pretrained weight. where in mxnet, it requires a reviewer to merge in and 
extra time for a new release on PyPi.
   
   We all aim for a good toolbox, and as I mentioned, my free time on next 
semester is very limited. So to merge in or not, actually depends on later 
maintainers' idea. If you all think merging to be a better choice, I will 
create a pull request after construction for `model` is finished.
   
   
 

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[GitHub] lxn2 commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
lxn2 commented on a change in pull request #7418: Enable Apache Rat + add more 
license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132574958
 
 

 ##
 File path: amalgamation/jni/org/dmlc/mxnet/MxnetException.java
 ##
 @@ -1,5 +1,25 @@
 package org.dmlc.mxnet;
 
+/*
 
 Review comment:
   Looks like the tool did a few other funky things...I'll go through all the 
files...
 

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[GitHub] lxn2 commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
lxn2 commented on a change in pull request #7418: Enable Apache Rat + add more 
license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132574261
 
 

 ##
 File path: cpp-package/example/feature_extract/prepare_data_with_opencv.cpp
 ##
 @@ -1,3 +1,22 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * 
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
 /*!
  * Copyright (c) 2015 by Contributors
  */
 
 Review comment:
   Sounds like @mli is putting it into future work
 

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[GitHub] lxn2 commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
lxn2 commented on a change in pull request #7418: Enable Apache Rat + add more 
license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132573886
 
 

 ##
 File path: amalgamation/jni/org/dmlc/mxnet/MxnetException.java
 ##
 @@ -1,5 +1,25 @@
 package org.dmlc.mxnet;
 
+/*
 
 Review comment:
   This was added by the Apache Rat tool...
 

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[GitHub] lxn2 commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
lxn2 commented on a change in pull request #7418: Enable Apache Rat + add more 
license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132573730
 
 

 ##
 File path: cpp-package/example/charRNN.cpp
 ##
 @@ -1,3 +1,22 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * 
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
 
 Review comment:
   Oh right. The ".yml" line in rat-exclude should cover travis.yml file.
 

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[GitHub] smarthi commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
smarthi commented on a change in pull request #7418: Enable Apache Rat + add 
more license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132571396
 
 

 ##
 File path: amalgamation/jni/org/dmlc/mxnet/MxnetException.java
 ##
 @@ -1,5 +1,25 @@
 package org.dmlc.mxnet;
 
+/*
 
 Review comment:
   yup, please move that to beginning on Line 1
 

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[GitHub] smarthi commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
smarthi commented on a change in pull request #7418: Enable Apache Rat + add 
more license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132571276
 
 

 ##
 File path: cpp-package/example/charRNN.cpp
 ##
 @@ -1,3 +1,22 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * 
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
 
 Review comment:
   not the comment, sorry about that - i commented on wrong line. I was asking 
if u r gonna include '.travis.yml' also to the rat-exclude list - if we r using 
Travis i,e
 

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[GitHub] smarthi commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
smarthi commented on a change in pull request #7418: Enable Apache Rat + add 
more license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132571023
 
 

 ##
 File path: cpp-package/example/feature_extract/prepare_data_with_opencv.cpp
 ##
 @@ -1,3 +1,22 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * 
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
 /*!
  * Copyright (c) 2015 by Contributors
  */
 
 Review comment:
   yes 'copyright' comments in all files.  
 

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[GitHub] piiswrong commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
piiswrong commented on a change in pull request #7418: Enable Apache Rat + add 
more license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132569729
 
 

 ##
 File path: amalgamation/jni/org/dmlc/mxnet/MxnetException.java
 ##
 @@ -1,5 +1,25 @@
 package org.dmlc.mxnet;
 
+/*
 
 Review comment:
   why is it under package?
 

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[GitHub] lxn2 commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
lxn2 commented on a change in pull request #7418: Enable Apache Rat + add more 
license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132567183
 
 

 ##
 File path: cpp-package/example/feature_extract/prepare_data_with_opencv.cpp
 ##
 @@ -1,3 +1,22 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * 
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
 /*!
  * Copyright (c) 2015 by Contributors
  */
 
 Review comment:
   Do you mean all the "copyright" statements? For all files?
 

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[GitHub] lxn2 commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
lxn2 commented on a change in pull request #7418: Enable Apache Rat + add more 
license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132566879
 
 

 ##
 File path: cpp-package/example/charRNN.cpp
 ##
 @@ -1,3 +1,22 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * 
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
 
 Review comment:
   Did you mean for this comment to be in .rat-excludes? If so I've excluded 
all .yml's
 

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[GitHub] lxn2 closed pull request #7402: Add disclaimer and download link

2017-08-10 Thread git 
lxn2 closed pull request #7402: Add disclaimer and download link
URL: https://github.com/apache/incubator-mxnet/pull/7402
 
 
   
 

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[incubator-mxnet] branch master updated: Add disclaimer and download link (#7402)

2017-08-10 Thread lxn2 
This is an automated email from the ASF dual-hosted git repository.

lxn2 pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/master by this push:
 new aed297a  Add disclaimer and download link (#7402)
aed297a is described below

commit aed297aed61dc96afc93565fda2dda85f1a2749b
Author: Yao Wang 
AuthorDate: Thu Aug 10 13:58:20 2017 -0700

Add disclaimer and download link (#7402)

* Add disclaimer and download link

* Fix
---
 docs/_static/mxnet-theme/index.html  |  7 
 docs/_static/mxnet.css   | 14 
 docs/build_version_doc/AddPackageLink.py | 58 
 docs/build_version_doc/build_doc.sh  |  2 ++
 docs/get_started/install.md  |  2 ++
 5 files changed, 83 insertions(+)

diff --git a/docs/_static/mxnet-theme/index.html 
b/docs/_static/mxnet-theme/index.html
index c4f3c48..b39e710 100644
--- a/docs/_static/mxnet-theme/index.html
+++ b/docs/_static/mxnet-theme/index.html
@@ -127,3 +127,10 @@
 
   
 
+
+
+https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/apache_incubator_logo.png";
 height=60>
+
+Apache MXNet is an effort undergoing incubation at The Apache Software 
Foundation (ASF), sponsored by the Apache Incubator. 
Incubation is required of all newly accepted projects until a further review 
indicates that the infrastructure, communications, and decision making process 
have stabilized in a manner consistent with other successful ASF projects. 
While incubation status is not necessarily a reflection of the completeness or 
stability of the code, it  [...]
+
+
\ No newline at end of file
diff --git a/docs/_static/mxnet.css b/docs/_static/mxnet.css
index 6f6d8cd..db2c5a2 100644
--- a/docs/_static/mxnet.css
+++ b/docs/_static/mxnet.css
@@ -717,6 +717,14 @@ li.dropdown-submenu ul.dropdown-menu a {
 filter: grayscale(0%);
 }
 
+.section-disclaimer {
+padding: 3em 3em 3em;
+}
+
+.section-disclaimer p {
+padding-top: 2em;
+}
+
 .footer{
 padding-top: 40px;
 }
@@ -1244,3 +1252,9 @@ div.download_btn a:hover {
 padding-bottom: 3px;
 font-style: italic;
 }
+
+/*Download source-*/
+#download-source-package {
+display: none;
+padding-top: 40px;
+}
diff --git a/docs/build_version_doc/AddPackageLink.py 
b/docs/build_version_doc/AddPackageLink.py
new file mode 100644
index 000..8fe04b5
--- /dev/null
+++ b/docs/build_version_doc/AddPackageLink.py
@@ -0,0 +1,58 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+import os
+import argparse
+from bs4 import BeautifulSoup as bs
+
+parser = argparse.ArgumentParser(description="Add download package link.",
+ 
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+parser.add_argument('--file_path', type=str, 
default='docs/_build/html/get_started/install.html',
+help='file to be modified')
+parser.add_argument('--current_version', type=str, default='master',
+help='Current version')
+
+if __name__ == '__main__':
+args = parser.parse_args()
+tag = args.current_version
+
+src_url = "http://www.apache.org/dyn/closer.cgi/incubator/"; \
+  "mxnet/%s-incubating/apache-mxnet-src-%s-incubating.tar.gz" % 
(tag, tag)
+pgp_url = "http://www.apache.org/dyn/closer.cgi/incubator/"; \
+  "mxnet/%s-incubating/apache-mxnet-src-%s-incubating.tar.gz.asc" 
% (tag, tag)
+sha_url = "http://www.apache.org/dyn/closer.cgi/incubator/"; \
+  "mxnet/%s-incubating/apache-mxnet-src-%s-incubating.tar.gz.sha" 
% (tag, tag)
+md5_url = "http://www.apache.org/dyn/closer.cgi/incubator/"; \
+  "mxnet/%s-incubating/apache-mxnet-src-%s-incubating.tar.gz.md5" 
% (tag, tag)
+
+download_str = ""
+download_str += "" \
+"" \
+" Source for %s" % (src_url, tag)
+download_str += "PGP" % 
(pgp_url)
+download_str += "SHA-256" % 
(sha_url)
+download_str += "MD5" % 
(md5_url)
+download_str += ""
+
+with open(args.file_path, 'r') as html_file:
+content = bs(html

[GitHub] smarthi commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
smarthi commented on a change in pull request #7418: Enable Apache Rat + add 
more license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132564377
 
 

 ##
 File path: docs/_static/mxnet-theme/footer.html
 ##
 @@ -1,5 +1,24 @@
+
+
 
 
-   ? 2015-2017 DMLC. All rights reserved. 
+   ?? 2015-2017 DMLC. All rights reserved. 
 
 Review comment:
   This shuldn't be there.
 

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[GitHub] smarthi commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
smarthi commented on a change in pull request #7418: Enable Apache Rat + add 
more license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132564018
 
 

 ##
 File path: cpp-package/example/charRNN.cpp
 ##
 @@ -1,3 +1,22 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * 
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
 
 Review comment:
   do u also wanna add .travis.yml here?  If the project's setup for Travis 
i.e.?
 

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[GitHub] smarthi commented on a change in pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
smarthi commented on a change in pull request #7418: Enable Apache Rat + add 
more license headers
URL: https://github.com/apache/incubator-mxnet/pull/7418#discussion_r132564179
 
 

 ##
 File path: cpp-package/example/feature_extract/prepare_data_with_opencv.cpp
 ##
 @@ -1,3 +1,22 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ * 
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ * 
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
 /*!
  * Copyright (c) 2015 by Contributors
  */
 
 Review comment:
   This is gonna be purged later. correct? 
 

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[GitHub] lxn2 opened a new pull request #7418: Enable Apache Rat + add more license headers

2017-08-10 Thread git 
lxn2 opened a new pull request #7418: Enable Apache Rat + add more license 
headers
URL: https://github.com/apache/incubator-mxnet/pull/7418
 
 
   This PR enables Apache Rat to run as part of the sanity check. It also 
includes the .rat-excludes file which will make Rat ignore files/folders that 
match those names. Also ran Rat to add the remaining license headers to files 
missed.
 

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[GitHub] wetliu commented on issue #7064: is "num_group" implement mobilenet?

2017-08-10 Thread git 
wetliu commented on issue #7064: is "num_group" implement mobilenet?
URL: 
https://github.com/apache/incubator-mxnet/issues/7064#issuecomment-321664196
 
 
   I tested the speed between TF depth wise convolution with the 1x1 
convolution and the normal convolution. The speed of depth wise conv with the 
1*1 operator is 2 times as fast as the normal convolution. I think the group 
trick is similar to the depth-wise convolution, but it seems there is some 
difference (I am not very sure).
 

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[GitHub] wetliu commented on issue #7064: is "num_group" implement mobilenet?

2017-08-10 Thread git 
wetliu commented on issue #7064: is "num_group" implement mobilenet?
URL: 
https://github.com/apache/incubator-mxnet/issues/7064#issuecomment-321664196
 
 
   I tested the speed between TF depth wise convolution with the 1*1 
convolution and the normal convolution. The speed of depth wise conv with the 
1*1 operator is 2 times as fast as the normal convolution. I think the group 
trick is similar to the depth-wise convolution, but it seems there is some 
difference (I am not very sure).
 

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[GitHub] szha commented on issue #7397: OSError: /home_dir/mxnet/mxnet/python/mxnet/../../lib/libmxnet.so: undefined symbol: cblas_ddot

2017-08-10 Thread git 
szha commented on issue #7397: OSError: 
/home_dir/mxnet/mxnet/python/mxnet/../../lib/libmxnet.so: undefined symbol: 
cblas_ddot
URL: 
https://github.com/apache/incubator-mxnet/issues/7397#issuecomment-321663862
 
 
   Since it complains about missing cblas symbols, consider adding openblas to 
linker flags.
 

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[incubator-mxnet] branch sparse deleted (was e35df52)

2017-08-10 Thread cjolivier01 
This is an automated email from the ASF dual-hosted git repository.

cjolivier01 pushed a change to branch sparse
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git.


 was e35df52  Squash of haibin/sparse branch into apache/sparse

This change permanently discards the following revisions:

 discard e35df52  Squash of haibin/sparse branch into apache/sparse

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[GitHub] piiswrong commented on issue #7398: inconsistent results when infering

2017-08-10 Thread git 
piiswrong commented on issue #7398: inconsistent results when infering
URL: 
https://github.com/apache/incubator-mxnet/issues/7398#issuecomment-321656099
 
 
   Try compare the images from imagerecorditer and get_image?
 

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[GitHub] thirdwing commented on issue #6629: Not enough information to get shape

2017-08-10 Thread git 
thirdwing commented on issue #6629: Not enough information to get shape
URL: 
https://github.com/apache/incubator-mxnet/issues/6629#issuecomment-321618518
 
 
   @haimeh Thank you for pointing out this.
   
   I will look into it.
 

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[incubator-mxnet] branch master updated: add Sequential compatibility to rnn layers (#7352)

2017-08-10 Thread jxie 
This is an automated email from the ASF dual-hosted git repository.

jxie pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/master by this push:
 new c55fc57  add Sequential compatibility to rnn layers (#7352)
c55fc57 is described below

commit c55fc571d22ec458365d87740b589827ddfd86cf
Author: Sheng Zha 
AuthorDate: Thu Aug 10 10:24:03 2017 -0700

add Sequential compatibility to rnn layers (#7352)
---
 python/mxnet/gluon/rnn/rnn_layer.py | 46 -
 tests/python/unittest/test_gluon_rnn.py | 29 +
 2 files changed, 63 insertions(+), 12 deletions(-)

diff --git a/python/mxnet/gluon/rnn/rnn_layer.py 
b/python/mxnet/gluon/rnn/rnn_layer.py
index a9bcee5..86b7c61 100644
--- a/python/mxnet/gluon/rnn/rnn_layer.py
+++ b/python/mxnet/gluon/rnn/rnn_layer.py
@@ -168,10 +168,13 @@ class _RNNLayer(Block):
 states.append(func(name='%sh0_%d'%(self.prefix, i), **info))
 return states
 
-def forward(self, inputs, states):
+def forward(self, inputs, states=None):
+batch_size = inputs.shape[self._layout.find('N')]
+skip_states = states is None
+if skip_states:
+states = self.begin_state(batch_size)
 if isinstance(states, ndarray.NDArray):
 states = [states]
-batch_size = inputs.shape[self._layout.find('N')]
 for state, info in zip(states, self.state_info(batch_size)):
 if state.shape != info['shape']:
 raise ValueError(
@@ -182,8 +185,12 @@ class _RNNLayer(Block):
 self.i2h_weight[i].shape = (self._gates*self._hidden_size, 
inputs.shape[2])
 self.i2h_weight[i]._finish_deferred_init()
 if inputs.context.device_type == 'gpu':
-return self._forward_gpu(inputs, states)
-return self._forward_cpu(inputs, states)
+out = self._forward_gpu(inputs, states)
+else:
+out = self._forward_cpu(inputs, states)
+
+# out is (output, state)
+return out[0] if skip_states else out
 
 def _forward_cpu(self, inputs, states):
 ns = len(states)
@@ -282,10 +289,12 @@ class RNN(_RNNLayer):
 If `bidirectional` is True, output shape will instead be
 `(sequence_length, batch_size, 2*num_hidden)`
 
-Recurrent state shape:
-The recurrent state's shape is `(num_layers, batch_size, num_hidden)`.
-If `bidirectional` is True, state shape will instead be
+Recurrent state:
+The recurrent state is an NDArray with shape `(num_layers, batch_size, 
num_hidden)`.
+If `bidirectional` is True, the recurrent state shape will instead be
 `(2*num_layers, batch_size, num_hidden)`
+If input recurrent state is None, zeros are used as default begin 
states,
+and the output recurrent state is omitted.
 
 
 Examples
@@ -293,6 +302,9 @@ class RNN(_RNNLayer):
 >>> layer = mx.gluon.rnn.RNN(100, 3)
 >>> layer.initialize()
 >>> input = mx.nd.random_uniform(shape=(5, 3, 10))
+>>> # by default zeros are used as begin state
+>>> output = layer(input)
+>>> # manually specify begin state.
 >>> h0 = mx.nd.random_uniform(shape=(3, 3, 100))
 >>> output, hn = layer(input, h0)
 """
@@ -379,11 +391,13 @@ class LSTM(_RNNLayer):
 If `bidirectional` is True, output shape will instead be
 `(sequence_length, batch_size, 2*num_hidden)`
 
-Recurrent state shape:
+Recurrent state:
 The recurrent state is a list of two NDArrays. Both has shape
 `(num_layers, batch_size, num_hidden)`.
-If `bidirectional` is True, state shape will instead be
+If `bidirectional` is True, each recurrent state will instead have 
shape
 `(2*num_layers, batch_size, num_hidden)`.
+If input recurrent state is None, zeros are used as default begin 
states,
+and the output recurrent state is omitted.
 
 
 Examples
@@ -391,6 +405,9 @@ class LSTM(_RNNLayer):
 >>> layer = mx.gluon.rnn.LSTM(100, 3)
 >>> layer.initialize()
 >>> input = mx.nd.random_uniform(shape=(5, 3, 10))
+>>> # by default zeros are used as begin state
+>>> output = layer(input)
+>>> # manually specify begin state.
 >>> h0 = mx.nd.random_uniform(shape=(3, 3, 100))
 >>> c0 = mx.nd.random_uniform(shape=(3, 3, 100))
 >>> output, hn = layer(input, [h0, c0])
@@ -474,10 +491,12 @@ class GRU(_RNNLayer):
 If `bidirectional` is True, output shape will instead be
 `(sequence_length, batch_size, 2*num_hidden)`
 
-Recurrent state shape:
-The recurrent state's shape is `(num_layers, batch_size, num_hidden)`.
-If `bidirectional` is True, state shape will instead be
+Recurrent state:
+The recurrent state is an NDArray with shape `(num_layers, batch_size, 
num_hidden)`.
+If `bidirectional` i

[GitHub] piiswrong closed pull request #7352: add Sequential compatibility to rnn layers

2017-08-10 Thread git 
piiswrong closed pull request #7352: add Sequential compatibility to rnn layers
URL: https://github.com/apache/incubator-mxnet/pull/7352
 
 
   
 

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[GitHub] piiswrong closed pull request #7322: add verification to gluon dataset

2017-08-10 Thread git 
piiswrong closed pull request #7322: add verification to gluon dataset
URL: https://github.com/apache/incubator-mxnet/pull/7322
 
 
   
 

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[incubator-mxnet] branch master updated: add verification to gluon dataset (#7322)

2017-08-10 Thread jxie 
This is an automated email from the ASF dual-hosted git repository.

jxie pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/master by this push:
 new 0d1407f  add verification to gluon dataset (#7322)
0d1407f is described below

commit 0d1407fb69c1f3a71ef6c8d717d97d5aa0a44061
Author: Sheng Zha 
AuthorDate: Thu Aug 10 10:20:39 2017 -0700

add verification to gluon dataset (#7322)

* add verification to gluon dataset

* fix

* rename variables

* add tests

* fix doc
---
 docs/api/python/gluon.md|  4 +--
 python/mxnet/gluon/data/vision.py   | 40 ++---
 python/mxnet/gluon/model_zoo/model_store.py | 25 +---
 python/mxnet/gluon/model_zoo/vision/__init__.py | 13 ++--
 python/mxnet/gluon/utils.py | 36 --
 tests/python/unittest/test_gluon_data.py|  4 +++
 6 files changed, 85 insertions(+), 37 deletions(-)

diff --git a/docs/api/python/gluon.md b/docs/api/python/gluon.md
index 6e213bb..ac63774 100644
--- a/docs/api/python/gluon.md
+++ b/docs/api/python/gluon.md
@@ -239,6 +239,7 @@ Model zoo provides pre-defined and pre-trained models to 
help bootstrap machine
 
 ```eval_rst
 .. currentmodule:: mxnet.gluon.model_zoo.vision
+.. automodule:: mxnet.gluon.model_zoo.vision
 ```
 
 ```eval_rst
@@ -508,8 +509,7 @@ Model zoo provides pre-defined and pre-trained models to 
help bootstrap machine
 .. automodule:: mxnet.gluon.data.vision
 :members:
 
-.. automodule:: mxnet.gluon.model_zoo.vision
-:members:
+.. automethod:: mxnet.gluon.model_zoo.vision.get_model
 .. automethod:: mxnet.gluon.model_zoo.vision.resnet18_v1
 .. automethod:: mxnet.gluon.model_zoo.vision.resnet34_v1
 .. automethod:: mxnet.gluon.model_zoo.vision.resnet50_v1
diff --git a/python/mxnet/gluon/data/vision.py 
b/python/mxnet/gluon/data/vision.py
index 4ddbbbd..a16e736 100644
--- a/python/mxnet/gluon/data/vision.py
+++ b/python/mxnet/gluon/data/vision.py
@@ -26,7 +26,7 @@ import struct
 import numpy as np
 
 from . import dataset
-from ..utils import download
+from ..utils import download, check_sha1
 from ... import nd
 
 
@@ -67,7 +67,8 @@ class MNIST(_DownloadedDataset):
 
 transform=lambda data, label: (data.astype(np.float32)/255, label)
 """
-def __init__(self, root, train=True, transform=lambda data, label: (data, 
label)):
+def __init__(self, root='~/.mxnet/datasets/', train=True,
+ transform=lambda data, label: (data, label)):
 super(MNIST, self).__init__(root, train, transform)
 
 def _get_data(self):
@@ -75,11 +76,15 @@ class MNIST(_DownloadedDataset):
 os.makedirs(self._root)
 url = 'http://data.mxnet.io/data/mnist/'
 if self._train:
-data_file = download(url+'train-images-idx3-ubyte.gz', self._root)
-label_file = download(url+'train-labels-idx1-ubyte.gz', self._root)
+data_file = download(url+'train-images-idx3-ubyte.gz', self._root,
+ 
sha1_hash='6c95f4b05d2bf285e1bfb0e7960c31bd3b3f8a7d')
+label_file = download(url+'train-labels-idx1-ubyte.gz', self._root,
+  
sha1_hash='2a80914081dc54586dbdf242f9805a6b8d2a15fc')
 else:
-data_file = download(url+'t10k-images-idx3-ubyte.gz', self._root)
-label_file = download(url+'t10k-labels-idx1-ubyte.gz', self._root)
+data_file = download(url+'t10k-images-idx3-ubyte.gz', self._root,
+ 
sha1_hash='c3a25af1f52dad7f726cce8cacb138654b760d48')
+label_file = download(url+'t10k-labels-idx1-ubyte.gz', self._root,
+  
sha1_hash='763e7fa3757d93b0cdec073cef058b2004252c17')
 
 with gzip.open(label_file, 'rb') as fin:
 struct.unpack(">II", fin.read(8))
@@ -110,7 +115,14 @@ class CIFAR10(_DownloadedDataset):
 
 transform=lambda data, label: (data.astype(np.float32)/255, label)
 """
-def __init__(self, root, train=True, transform=lambda data, label: (data, 
label)):
+def __init__(self, root='~/.mxnet/datasets/', train=True,
+ transform=lambda data, label: (data, label)):
+self._file_hashes = {'data_batch_1.bin': 
'aadd24acce27caa71bf4b10992e9e7b2d74c2540',
+ 'data_batch_2.bin': 
'c0ba65cce70568cd57b4e03e9ac8d2a5367c1795',
+ 'data_batch_3.bin': 
'1dd00a74ab1d17a6e7d73e185b69dbf31242f295',
+ 'data_batch_4.bin': 
'aab85764eb3584312d3c7f65fd2fd016e36a258e',
+ 'data_batch_5.bin': 
'26e2849e66a845b7f1e4614ae70f4889ae604628',
+ 'test_batch.bin': 
'67eb016db431130d61cd03c7ad570b013799c88c'}
 super(CIFAR10, self).__init__(root, train, t

[GitHub] zhreshold commented on a change in pull request #7345: add std_rgba to normalize options

2017-08-10 Thread git 
zhreshold commented on a change in pull request #7345: add std_rgba to 
normalize options
URL: https://github.com/apache/incubator-mxnet/pull/7345#discussion_r132512710
 
 

 ##
 File path: src/io/iter_normalize.h
 ##
 @@ -129,33 +129,58 @@ class ImageNormalizeIter : public IIterator {
 if (param_.mean_r > 0.0f || param_.mean_g > 0.0f ||
 param_.mean_b > 0.0f || param_.mean_a > 0.0f) {
   // subtract mean per channel
-  data[0] -= param_.mean_r;
-  if (data.shape_[0] >= 3) {
-data[1] -= param_.mean_g;
-data[2] -= param_.mean_b;
-  }
-  if (data.shape_[0] == 4) {
-data[3] -= param_.mean_a;
-  }
-  if ((param_.rand_mirror && coin_flip(rnd_)) || param_.mirror) {
-outimg_ = mirror(data * contrast + illumination) * param_.scale;
-  } else {
-outimg_ = (data * contrast + illumination) * param_.scale;
+  switch (data.shape_[0]) {
+case 4: {
+  data[3] -= param_.mean_a;
+}
+case 3: {
+  data[2] -= param_.mean_b;
+}
+case 2: {
+  data[1] -= param_.mean_g;
+}
+case 1: {
+  data[0] -= param_.mean_r;
+  break;
+}
+default: {
+  // possible?
+}
   }
 } else if (!meanfile_ready_ || param_.mean_img.length() == 0) {
   // do not subtract anything
-  if ((param_.rand_mirror && coin_flip(rnd_)) || param_.mirror) {
-outimg_ = mirror(data) * param_.scale;
-  } else {
-outimg_ = F(data) * param_.scale;
-  }
 } else {
   CHECK(meanfile_ready_);
-  if ((param_.rand_mirror && coin_flip(rnd_)) || param_.mirror) {
-outimg_ = mirror((data - meanimg_) * contrast + illumination) * 
param_.scale;
-  } else {
-outimg_ = ((data - meanimg_) * contrast + illumination) * param_.scale;
+  data -= meanimg_;
+}
+// apply contrast and illumination jitter
+data = data * contrast + illumination;
+// apply std per channel
+switch (data.shape_[0]) {
+  case 4: {
+if (param_.std_a > 0.0f) data[3] /= param_.std_a;
   }
+  case 3: {
+if (param_.std_b > 0.0f) data[2] /= param_.std_b;
+  }
+  case 2: {
+if (param_.std_g > 0.0f) data[1] /= param_.std_g;
+  }
+  case 1: {
+if (param_.std_r > 0.0f) data[0] /= param_.std_r;
+break;
+  }
+  default: {
+// possible?
+  }
+}
+// scale the values globally
+data *= param_.scale;
 
 Review comment:
   It's happening after sub-mean, before std, so I guess contrast aug should 
happen before mean?
 

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[GitHub] haimeh commented on issue #6629: Not enough information to get shape

2017-08-10 Thread git 
haimeh commented on issue #6629: Not enough information to get shape
URL: 
https://github.com/apache/incubator-mxnet/issues/6629#issuecomment-321613657
 
 
   Also, a mistake one might make, so for reference I am adding it here.
   The shape inference may not always work with a chained composition such as:
 ```
   discouragedSelfMatches <- mx.symbol.broadcast_mul(lhs = 
mx.symbol.broadcast_equal(lhs = distances,

   rhs = mx.symbol.min(distances),
   rhs = 
mx.symbol.max(distances))
   ```
   but it will work if the symbols are separated, for instance:
 ```
   selfMatches <- mx.symbol.broadcast_equal(lhs = distances,
  rhs = mx.symbol.min(distances))
 discouragedSelfMatches <- mx.symbol.broadcast_mul(lhs=selfMatches, 
 
rhs=mx.symbol.max(distances))
   ```
 

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[GitHub] piiswrong commented on a change in pull request #7345: add std_rgba to normalize options

2017-08-10 Thread git 
piiswrong commented on a change in pull request #7345: add std_rgba to 
normalize options
URL: https://github.com/apache/incubator-mxnet/pull/7345#discussion_r132511274
 
 

 ##
 File path: src/io/iter_normalize.h
 ##
 @@ -129,33 +129,58 @@ class ImageNormalizeIter : public IIterator {
 if (param_.mean_r > 0.0f || param_.mean_g > 0.0f ||
 param_.mean_b > 0.0f || param_.mean_a > 0.0f) {
   // subtract mean per channel
-  data[0] -= param_.mean_r;
-  if (data.shape_[0] >= 3) {
-data[1] -= param_.mean_g;
-data[2] -= param_.mean_b;
-  }
-  if (data.shape_[0] == 4) {
-data[3] -= param_.mean_a;
-  }
-  if ((param_.rand_mirror && coin_flip(rnd_)) || param_.mirror) {
-outimg_ = mirror(data * contrast + illumination) * param_.scale;
-  } else {
-outimg_ = (data * contrast + illumination) * param_.scale;
+  switch (data.shape_[0]) {
+case 4: {
+  data[3] -= param_.mean_a;
+}
+case 3: {
+  data[2] -= param_.mean_b;
+}
+case 2: {
+  data[1] -= param_.mean_g;
+}
+case 1: {
+  data[0] -= param_.mean_r;
+  break;
+}
+default: {
+  // possible?
+}
   }
 } else if (!meanfile_ready_ || param_.mean_img.length() == 0) {
   // do not subtract anything
-  if ((param_.rand_mirror && coin_flip(rnd_)) || param_.mirror) {
-outimg_ = mirror(data) * param_.scale;
-  } else {
-outimg_ = F(data) * param_.scale;
-  }
 } else {
   CHECK(meanfile_ready_);
-  if ((param_.rand_mirror && coin_flip(rnd_)) || param_.mirror) {
-outimg_ = mirror((data - meanimg_) * contrast + illumination) * 
param_.scale;
-  } else {
-outimg_ = ((data - meanimg_) * contrast + illumination) * param_.scale;
+  data -= meanimg_;
+}
+// apply contrast and illumination jitter
+data = data * contrast + illumination;
+// apply std per channel
+switch (data.shape_[0]) {
+  case 4: {
+if (param_.std_a > 0.0f) data[3] /= param_.std_a;
   }
+  case 3: {
+if (param_.std_b > 0.0f) data[2] /= param_.std_b;
+  }
+  case 2: {
+if (param_.std_g > 0.0f) data[1] /= param_.std_g;
+  }
+  case 1: {
+if (param_.std_r > 0.0f) data[0] /= param_.std_r;
+break;
+  }
+  default: {
+// possible?
 
 Review comment:
   should fail on default
 

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[GitHub] piiswrong commented on a change in pull request #7345: add std_rgba to normalize options

2017-08-10 Thread git 
piiswrong commented on a change in pull request #7345: add std_rgba to 
normalize options
URL: https://github.com/apache/incubator-mxnet/pull/7345#discussion_r132511245
 
 

 ##
 File path: src/io/iter_normalize.h
 ##
 @@ -129,33 +129,58 @@ class ImageNormalizeIter : public IIterator {
 if (param_.mean_r > 0.0f || param_.mean_g > 0.0f ||
 param_.mean_b > 0.0f || param_.mean_a > 0.0f) {
   // subtract mean per channel
-  data[0] -= param_.mean_r;
-  if (data.shape_[0] >= 3) {
-data[1] -= param_.mean_g;
-data[2] -= param_.mean_b;
-  }
-  if (data.shape_[0] == 4) {
-data[3] -= param_.mean_a;
-  }
-  if ((param_.rand_mirror && coin_flip(rnd_)) || param_.mirror) {
-outimg_ = mirror(data * contrast + illumination) * param_.scale;
-  } else {
-outimg_ = (data * contrast + illumination) * param_.scale;
+  switch (data.shape_[0]) {
+case 4: {
+  data[3] -= param_.mean_a;
+}
+case 3: {
+  data[2] -= param_.mean_b;
+}
+case 2: {
+  data[1] -= param_.mean_g;
+}
+case 1: {
+  data[0] -= param_.mean_r;
+  break;
+}
+default: {
+  // possible?
+}
   }
 } else if (!meanfile_ready_ || param_.mean_img.length() == 0) {
   // do not subtract anything
-  if ((param_.rand_mirror && coin_flip(rnd_)) || param_.mirror) {
-outimg_ = mirror(data) * param_.scale;
-  } else {
-outimg_ = F(data) * param_.scale;
-  }
 } else {
   CHECK(meanfile_ready_);
-  if ((param_.rand_mirror && coin_flip(rnd_)) || param_.mirror) {
-outimg_ = mirror((data - meanimg_) * contrast + illumination) * 
param_.scale;
-  } else {
-outimg_ = ((data - meanimg_) * contrast + illumination) * param_.scale;
+  data -= meanimg_;
+}
+// apply contrast and illumination jitter
+data = data * contrast + illumination;
+// apply std per channel
+switch (data.shape_[0]) {
+  case 4: {
+if (param_.std_a > 0.0f) data[3] /= param_.std_a;
   }
+  case 3: {
+if (param_.std_b > 0.0f) data[2] /= param_.std_b;
+  }
+  case 2: {
+if (param_.std_g > 0.0f) data[1] /= param_.std_g;
+  }
+  case 1: {
+if (param_.std_r > 0.0f) data[0] /= param_.std_r;
+break;
+  }
+  default: {
+// possible?
+  }
+}
+// scale the values globally
+data *= param_.scale;
 
 Review comment:
   The computation was condensed in one line because its faster that way.
   
   Are you sure contrast and illumination should happen after std?
 

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[incubator-mxnet] branch master updated: Hotfix mx.image documents (#7404)

2017-08-10 Thread jxie 
This is an automated email from the ASF dual-hosted git repository.

jxie pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/master by this push:
 new 59d7170  Hotfix mx.image documents (#7404)
59d7170 is described below

commit 59d717074aae05cf47f69ab8589747bca572cd49
Author: Joshua Z. Zhang 
AuthorDate: Thu Aug 10 09:54:42 2017 -0700

Hotfix mx.image documents (#7404)

* fix typo and incorrect doc

* Fix doc formats

* fix doc con't
---
 python/mxnet/image/detection.py | 36 ++--
 python/mxnet/image/image.py | 31 +--
 2 files changed, 35 insertions(+), 32 deletions(-)

diff --git a/python/mxnet/image/detection.py b/python/mxnet/image/detection.py
index 142ba25..43131f0 100644
--- a/python/mxnet/image/detection.py
+++ b/python/mxnet/image/detection.py
@@ -483,15 +483,15 @@ def CreateDetAugmenter(data_shape, resize=0, rand_crop=0, 
rand_pad=0, rand_gray=
rand_mirror=False, mean=None, std=None, brightness=0, 
contrast=0,
saturation=0, pca_noise=0, hue=0, inter_method=2, 
min_object_covered=0.1,
aspect_ratio_range=(0.75, 1.33), area_range=(0.05, 3.0),
-   min_eject_coverage=0.3, max_attempts=50, pad_val=(128, 
128, 128)):
+   min_eject_coverage=0.3, max_attempts=50, pad_val=(127, 
127, 127)):
 """Create augmenters for detection.
 
 Parameters
 --
 data_shape : tuple of int
-shape for output data
+Shape for output data
 resize : int
-resize shorter edge if larger than 0 at the begining
+Resize shorter edge if larger than 0 at the begining
 rand_crop : float
 [0, 1], probability to apply random cropping
 rand_pad : float
@@ -499,23 +499,23 @@ def CreateDetAugmenter(data_shape, resize=0, rand_crop=0, 
rand_pad=0, rand_gray=
 rand_gray : float
 [0, 1], probability to convert to grayscale for all channels
 rand_mirror : bool
-whether apply horizontal flip to image with probability 0.5
+Whether to apply horizontal flip to image with probability 0.5
 mean : np.ndarray or None
-mean pixel values for [r, g, b]
+Mean pixel values for [r, g, b]
 std : np.ndarray or None
-standard deviations for [r, g, b]
+Standard deviations for [r, g, b]
 brightness : float
-brightness jittering range (percent)
+Brightness jittering range (percent)
 contrast : float
-contrast jittering range
+Contrast jittering range (percent)
 saturation : float
-saturation jittering range
+Saturation jittering range (percent)
 hue : float
-hue jittering range
+Hue jittering range (percent)
 pca_noise : float
-pca noise level
+Pca noise level (percent)
 inter_method : int, default=2(Area-based)
-interpolation method for all resizing operations
+Interpolation method for all resizing operations
 
 Possible values:
 0: Nearest Neighbors Interpolation.
@@ -550,7 +550,7 @@ def CreateDetAugmenter(data_shape, resize=0, rand_crop=0, 
rand_pad=0, rand_gray=
 Number of attempts at generating a cropped/padded region of the image 
of the
 specified constraints. After max_attempts failures, return the 
original image.
 pad_val: float
-pixel value to be filled when padding is enabled. pad_val will 
automatically
+Pixel value to be filled when padding is enabled. pad_val will 
automatically
 be subtracted by mean and divided by std if applicable.
 
 Examples
@@ -627,7 +627,7 @@ class ImageDetIter(ImageIter):
 Parameters
 --
 aug_list : list or None
-augmenter list for generating distorted images
+Augmenter list for generating distorted images
 batch_size : int
 Number of examples per batch.
 data_shape : tuple
@@ -657,7 +657,7 @@ class ImageDetIter(ImageIter):
 data_name : str
 Data name for provided symbols.
 label_name : str
-name for detection labels
+Name for detection labels
 kwargs : ...
 More arguments for creating augmenter. See mx.image.CreateDetAugmenter.
 """
@@ -723,7 +723,7 @@ class ImageDetIter(ImageIter):
 obj_width = int(raw[1])
 if (raw.size - header_width) % obj_width != 0:
 msg = "Label shape %s inconsistent with annotation width %d." \
-%(str(raw.shape, obj_width))
+%(str(raw.shape), obj_width)
 raise RuntimeError(msg)
 out = np.reshape(raw[header_width:], (-1, obj_width))
 # remove bad ground-truths
@@ -738,9 +738,9 @@ class ImageDetIter(ImageIter):
 Parameters
 --
 data_shape : tuple or None
-

[GitHub] piiswrong closed pull request #7404: Hotfix mx.image documents

2017-08-10 Thread git 
piiswrong closed pull request #7404: Hotfix mx.image documents
URL: https://github.com/apache/incubator-mxnet/pull/7404
 
 
   
 

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[GitHub] thirdwing closed issue #7364: MxnetR chunk-wise neural nets

2017-08-10 Thread git 
thirdwing closed issue #7364: MxnetR chunk-wise neural nets
URL: https://github.com/apache/incubator-mxnet/issues/7364
 
 
   
 

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[incubator-mxnet] branch master updated: [R][MISC] update Makefile/Jenkinsfile; use mx.ctx.default() in R test (#7401)

2017-08-10 Thread qkou 
This is an automated email from the ASF dual-hosted git repository.

qkou pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/master by this push:
 new 613132e  [R][MISC] update Makefile/Jenkinsfile; use mx.ctx.default() 
in R test (#7401)
613132e is described below

commit 613132e2b6c6573b184b467aed5cf50dbb91aa47
Author: Qiang Kou (KK) 
AuthorDate: Thu Aug 10 15:19:28 2017 +

[R][MISC] update Makefile/Jenkinsfile; use mx.ctx.default() in R test 
(#7401)
---
 Jenkinsfile |   4 +-
 Makefile|   1 +
 R-package/README.md |   6 --
 R-package/tests/testthat.R  |   4 --
 R-package/tests/testthat/get_data.R |  13 
 R-package/tests/testthat/test_img_seg.R |   7 +-
 R-package/tests/testthat/test_lstm.R|   7 +-
 R-package/tests/testthat/test_model.R   | 117 +---
 R-package/tests/testthat/test_ndarray.R |   9 ++-
 example/captcha/README.md   |   2 +-
 10 files changed, 142 insertions(+), 28 deletions(-)

diff --git a/Jenkinsfile b/Jenkinsfile
index 370c2b3..632789a 100644
--- a/Jenkinsfile
+++ b/Jenkinsfile
@@ -325,11 +325,11 @@ try {
 init_git()
 unpack_lib('gpu')
 timeout(time: max_time, unit: 'MINUTES') {
-  sh "${docker_run} cpu rm -rf .Renviron"
+  sh "${docker_run} gpu rm -rf .Renviron"
   sh "${docker_run} gpu mkdir -p /workspace/ut-r-gpu/site-library"
   sh "${docker_run} gpu make rpkg USE_BLAS=openblas 
R_LIBS=/workspace/ut-r-gpu/site-library"
   sh "${docker_run} gpu R CMD INSTALL 
--library=/workspace/ut-r-gpu/site-library mxnet_current_r.tar.gz"
-  sh "${docker_run} gpu make rpkgtest 
R_LIBS=/workspace/ut-r-gpu/site-library"
+  sh "${docker_run} gpu make rpkgtest 
R_LIBS=/workspace/ut-r-gpu/site-library R_GPU_ENABLE=1"
 }
   }
 }
diff --git a/Makefile b/Makefile
index ed74214..560b77a 100644
--- a/Makefile
+++ b/Makefile
@@ -398,6 +398,7 @@ rpkg:
Rscript -e "require(roxygen2); roxygen2::roxygenise('R-package')"
R CMD build --no-build-vignettes R-package
rm -rf mxnet_current_r.tar.gz
+   rm -rf R-package/src/image_recordio.h
mv mxnet_*.tar.gz mxnet_current_r.tar.gz
 
 rpkgtest:
diff --git a/R-package/README.md b/R-package/README.md
index e150f17..6576700 100644
--- a/R-package/README.md
+++ b/R-package/README.md
@@ -1,7 +1,5 @@
 https://raw.githubusercontent.com/dmlc/dmlc.github.io/master/img/logo-m/mxnetR.png
 width=155/> Deep Learning for R
 ==
-[![Build 
Status](https://travis-ci.org/dmlc/mxnet.svg?branch=master)](https://travis-ci.org/dmlc/mxnet)
-[![Documentation 
Status](https://readthedocs.org/projects/mxnet/badge/?version=latest)](http://mxnet.readthedocs.io/en/latest/api/r/index.html)
 
 You have found MXNet R Package! The MXNet R packages brings flexible and 
efficient GPU
 computing and state-of-art deep learning to R.
@@ -12,10 +10,6 @@ computing and state-of-art deep learning to R.
 
 Sounds exciting? This page contains links to all the related documentation of 
the R package.
 
-Resources
--
-* [MXNet R Package Document](http://mxnet.io/get_started/install.html)
-  - Check this out for detailed documents, examples and installation guides.
 
 Installation
 
diff --git a/R-package/tests/testthat.R b/R-package/tests/testthat.R
deleted file mode 100644
index f002e4c..000
--- a/R-package/tests/testthat.R
+++ /dev/null
@@ -1,4 +0,0 @@
-library(testthat)
-library(mxnet)
-
-test_check("mxnet")
diff --git a/R-package/tests/testthat/get_data.R 
b/R-package/tests/testthat/get_data.R
index 555e5e9..6d8de85 100644
--- a/R-package/tests/testthat/get_data.R
+++ b/R-package/tests/testthat/get_data.R
@@ -92,3 +92,16 @@ GetISBI_data <- function() {
 file.remove('data/ISBI.zip')
   }
 }
+
+GetCaptcha_data <- function() {
+  if (!dir.exists("data")) {
+dir.create("data/")
+  }
+  if (!file.exists('data/captcha_example/captcha_train.rec') |
+  !file.exists('data/captcha_example/captcha_test.rec')) {
+
download.file('https://s3-us-west-2.amazonaws.com/apache-mxnet/R/data/captcha_example.zip',
+  destfile = 'data/captcha_example.zip')
+unzip('data/captcha_example.zip', exdir = 'data/')
+file.remove('data/captcha_example.zip')
+  }
+}
diff --git a/R-package/tests/testthat/test_img_seg.R 
b/R-package/tests/testthat/test_img_seg.R
index ba5c9cd..fbca92e 100644
--- a/R-package/tests/testthat/test_img_seg.R
+++ b/R-package/tests/testthat/test_img_seg.R
@@ -2,6 +2,11 @@ require(mxnet)
 
 source("get_data.R")
 
+if (Sys.getenv("R_GPU_ENABLE") != "" & as.integer(Sys.getenv("R_GPU_ENABLE")) 
== 1) {
+  mx.ctx.default(new = mx.gpu())
+  message("Using GPU for testing.")
+}
+
 print_inferred_shape <- functi

[GitHub] thirdwing closed pull request #7401: [R][MISC] update Makefile/Jenkinsfile; use mx.ctx.default() in R test

2017-08-10 Thread git 
thirdwing closed pull request #7401: [R][MISC] update Makefile/Jenkinsfile; use 
mx.ctx.default() in R test
URL: https://github.com/apache/incubator-mxnet/pull/7401
 
 
   
 

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[GitHub] larroy commented on issue #7416: update submoules with android fixes

2017-08-10 Thread git 
larroy commented on issue #7416: update submoules with android fixes
URL: https://github.com/apache/incubator-mxnet/pull/7416#issuecomment-321573812
 
 
   Pending on merging PRs on submodules
 

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[GitHub] tornadomeet commented on issue #7374: fix consistency of cpu/gpu in stn

2017-08-10 Thread git 
tornadomeet commented on issue #7374: fix consistency of cpu/gpu in stn
URL: https://github.com/apache/incubator-mxnet/pull/7374#issuecomment-321548210
 
 
   @piiswrong Done.
 

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[GitHub] kurt-o-sys commented on issue #7349: time series delay output mxnet

2017-08-10 Thread git 
kurt-o-sys commented on issue #7349: time series delay output mxnet
URL: 
https://github.com/apache/incubator-mxnet/issues/7349#issuecomment-321528156
 
 
   OK... I'm not sure if I get it. I'll have to play a little more, I guess. 
Training the above network:
   
   mx.model.FeedForward.create(regression, X=...,  ...)
   
   Right? Since the network is unrolled, it can be considered as a normal 
FeedForward model? (It looks a bit odd to me to put `FeedForward` to train the 
rnn, and I actually want to have a rnn as a result, so I continuously add new 
data). 
 

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[GitHub] larroy commented on issue #7416: update submoules with android fixes

2017-08-10 Thread git 
larroy commented on issue #7416: update submoules with android fixes
URL: https://github.com/apache/incubator-mxnet/pull/7416#issuecomment-321525871
 
 
   @KellenSunderland
 

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[GitHub] nnguyen24 commented on issue #6629: Not enough information to get shape

2017-08-10 Thread git 
nnguyen24 commented on issue #6629: Not enough information to get shape
URL: 
https://github.com/apache/incubator-mxnet/issues/6629#issuecomment-321520742
 
 
   Thank you @thirdwing , I will give it a try.
 

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[GitHub] maxenceliu opened a new issue #7417: Update mxnet in maven timely?

2017-08-10 Thread git 
maxenceliu opened a new issue #7417: Update mxnet in maven timely?
URL: https://github.com/apache/incubator-mxnet/issues/7417
 
 
   in the maven repository, the mxnet version is much delayed. Furmore, it 
depends on opencv, in which the case our server doesn't need opencv.
 

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[GitHub] larroy opened a new pull request #7416: update submoules with android fixes

2017-08-10 Thread git 
larroy opened a new pull request #7416: update submoules with android fixes
URL: https://github.com/apache/incubator-mxnet/pull/7416
 
 
   
 

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[GitHub] idealboy commented on issue #5452: When executing "train_mnist.py" with two machines, no response returns

2017-08-10 Thread git 
idealboy commented on issue #5452: When executing "train_mnist.py" with two 
machines, no response returns
URL: 
https://github.com/apache/incubator-mxnet/issues/5452#issuecomment-321508451
 
 
   it is probably because of the firewall in the machine, try to close it.
 

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[GitHub] train-test-laura commented on issue #7364: MxnetR chunk-wise neural nets

2017-08-10 Thread git 
train-test-laura commented on issue #7364: MxnetR chunk-wise neural nets
URL: 
https://github.com/apache/incubator-mxnet/issues/7364#issuecomment-321505488
 
 
   Hi Thirdwind,
   thank you very much - this seems to be exactly what I was looking for. 
   That is easier than I expected it to be - just taking arg.params and 
aux.params from model 1 (chunk 1) and take it to model 2 (chunk 2) and so on - 
great!
   
 

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[GitHub] n1kt0 commented on issue #4851: error: ISO C++ forbids comparison between pointer and integer

2017-08-10 Thread git 
n1kt0 commented on issue #4851: error: ISO C++ forbids comparison between 
pointer and integer
URL: 
https://github.com/apache/incubator-mxnet/issues/4851#issuecomment-321500185
 
 
   I've switched in the mean time to tensorflow and keras because i had to do 
my thesis and didn't have any more time to play around but i'm still interested 
after my thesis in a month or so to look at mxnet
 

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[GitHub] yonadavs opened a new issue #7415: Caffe-converter convert_model.py fail

2017-08-10 Thread git 
yonadavs opened a new issue #7415: Caffe-converter convert_model.py fail
URL: https://github.com/apache/incubator-mxnet/issues/7415
 
 
   Hi, tried converting a caffe model.
   The convert_symbol ran successfully, but the convert_model crashed.
   I know the model works fine on caffe. I don't know any details about the 
model.
   
   ## Environment info
   Operating System:
   Ubuntu 16.04
   
   Package used (Python/R/Scala/Julia):
   Python
   
   MXNet commit hash (`git rev-parse HEAD`):
   89e3ee3ea7c223db8c65ddd8c94c6e787d7c52df
   If you are using python package, please provide
   
   Python version and distribution:
   python 2.7
   
   ## Error Message:
   Please paste the full error message, including stack trace.
   
   converting layer fc6, wmat shape = (22440, 512)fc6_bias not found in 
arg_shape_dic.
   skipping layer softmaxloss1 of type SoftmaxWithLoss
   skipping layer center_loss_1 of type CenterLoss
   Traceback (most recent call last):
 File "convert_model.py", line 220, in 
   main()
 File "convert_model.py", line 216, in main
   convert_model(args.prototxt, args.caffemodel, args.save_model_name)
 File "convert_model.py", line 198, in convert_model
   assert len(layer_blobs) == 0
   AssertionError
   
   ## Steps to reproduce
   
   1. run tools/caffe_converter>python convert_model.py proto caffemodel 
filename
   
   
 

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