Update documents

doc/python/index.md

@@ -5,21 +5,17 @@ To install the package package, checkout [Build and Installation Instruction](..
 There are three types of documents you can find about mxnet.
 
 * [Tutorials](#tutorials) are self contained materials that introduces a certain usecases of mxnet.
-* [Code Examples](#code-examples) contains links to codes.
+* [Code Examples](../../example) contains example codes.
 * [Python API Documents](#python-api-documents) contains documents about specific module, as well as reference of all API functions.
 
 Tutorials
 ---------
 * [Python Overview Tutorial](tutorial.md)
 
-Code Examples
--------------
-* [CIFAR 10 Example](../../example/cifar10)
-
 Python API Documents
 --------------------
 * [High Level Model Training Related API](model.md)
 * [NDArray API](ndarray.md)
 * [Symbolic API](symbol.md)
 * [KVStore API](kvstore.md)
-* [Data Loading API](io.md)
+* [Data Loading API](io.md)

doc/python/model.md

@@ -31,8 +31,16 @@ model = mx.model.FeedForward.create(
      num_round=num_round,
      learning_rate=0.01)
 ```
-
 You can also use scikit-learn style construct and fit function to create a model.
+```python
+# create a model using sklearn-style two step way
+model = mx.model.FeedForward.create(
+     softmax,
+     num_round=num_round,
+     learning_rate=0.01)
+
+mode.fit(X=data_set)
+```
 For more information, you can refer to [Model API Reference](#model-api-reference).
 
 Save the Model

doc/python/ndarray.md

@@ -103,3 +103,20 @@ NDArray API Reference
 .. automodule:: mxnet.ndarray
     :members:
 ```
+
+NDArray Random API Reference
+----------------------------
+
+```eval_rst
+.. automodule:: mxnet.random
+    :members:
+```
+
+
+Context API Reference
+---------------------
+
+```eval_rst
+.. automodule:: mxnet.context
+    :members:
+```

doc/python/symbol.md

@@ -115,4 +115,3 @@ Execution API Reference
 .. automodule:: mxnet.executor
     :members:
 ```
-

example/README.md

@@ -13,5 +13,4 @@ Python Howto
 [Python Howto](python-howto) is a folder containing short snippet of code
 introducing a certain feature of mxnet.
 
-***List of Examples***
-* [Configuring Net to get Multiple Ouputs](python-howto/multiple_outputs.py)
+

example/cifar10/README.md

@@ -1,3 +1,7 @@
+CIFAR 10 Example
+================
+* [cifar10.py](cifar10.py) provides an example to train a network-in-network style model on CIFAR-10
+
 
 Machine: Dual Xeon E5-1650 3.5GHz, 4 GTX 980, Cuda 6.5
 

example/cifar10/cifar10.py

@@ -123,8 +123,19 @@ def SimpleFactory(data, ch_1x1, ch_3x3):
 logging.basicConfig(level=logging.DEBUG)
 
 gpus = [mx.gpu(i) for i in range(num_gpus)]
+# Use create functional style to train a model
 model = mx.model.FeedForward.create(
     symbol=softmax, ctx=gpus,
     X=train_dataiter, eval_data=test_dataiter,
     num_round=num_round,
     learning_rate=0.05, momentum=0.9, wd=0.00001)
+
+# Alternatively, you can use sklearn-style two-step API, as follows
+"""
+model = mx.model.FeedForward(
+    symbol=softmax, ctx=gpus,
+    num_round=num_round,
+    learning_rate=0.05, momentum=0.9, wd=0.00001)
+
+model.fit(X=train_dataiter, eval_data=test_dataiter)
+"""

example/python-howto/README.md

@@ -0,0 +1,4 @@
+Python Howto Examples
+=====================
+* [Configuring Net to get Multiple Ouputs](python-howto/multiple_outputs.py)
+* [Configuring Image Record Iterator](python-howto/data_iter.py)

example/python-howto/multiple_outputs.py

@@ -18,4 +18,3 @@
 # executor.forward()
 # executor.output[0] will be value of fc1
 # executor.output[1] will be value of softmax
-

include/mxnet/ndarray.h

@@ -313,10 +313,10 @@ class NDArray {
       if (static_data || delay_alloc) {
         Engine::Get()->DeleteVariable([](RunContext s) {}, shandle.ctx, var);
       } else {
-	Storage::Handle h = this->shandle;
-	Engine::Get()->DeleteVariable([h](RunContext s) {
-	    Storage::Get()->Free(h);
-	  }, shandle.ctx, var);
+        Storage::Handle h = this->shandle;
+        Engine::Get()->DeleteVariable([h](RunContext s) {
+            Storage::Get()->Free(h);
+          }, shandle.ctx, var);
       }
     }
   };

src/engine/threaded_engine.h

@@ -15,6 +15,7 @@
 #include <condition_variable>
 #include <atomic>
 #include <mutex>
+#include <string>
 #include "./engine_impl.h"
 #include "../common/object_pool.h"
 
@@ -256,13 +257,13 @@ class ThreadedEngine : public Engine {
         ThreadedEngine::OnCompleteStatic, threaded_opr);
     if (!shutdown_phase_) {
       try {
-	threaded_opr->fn(run_ctx, callback);
+        threaded_opr->fn(run_ctx, callback);
       } catch(dmlc::Error &e) {
-	std::string what = e.what();
-	if (what.find("driver shutting down") == std::string::npos &&
-	    !shutdown_phase_) {
-	  LOG(FATAL) << e.what();
-	}
+        std::string what = e.what();
+        if (what.find("driver shutting down") == std::string::npos &&
+            !shutdown_phase_) {
+          LOG(FATAL) << e.what();
+        }
       }
     } else {
       callback();