Prepare for Keras-MXNet v2.2.2 release

awslabs · Aug 15, 2018 · 01d59d3 · 01d59d3
2 parents c0f4ef6 + 840d757
commit 01d59d3
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diff --git a/.coveragerc b/.coveragerc
@@ -1,6 +1,7 @@
 [report]
 # Regexes for lines to exclude from consideration
 exclude_lines =
+    pragma: no cover
     os.remove
     except ImportError
     # Don't complain if tests don't hit defensive assertion code:

diff --git a/.travis.yml b/.travis.yml
@@ -54,19 +54,19 @@ install:
   # install PIL for preprocessing tests
   - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then
       conda install pil;
-    elif [[ "$TRAVIS_PYTHON_VERSION" == "3.6" ]]; then
+    else
       conda install Pillow;
     fi
 
   - pip install -e .[tests]
 
   # install TensorFlow (CPU version).
   - pip install tensorflow==1.7
-
-  # install Apache MXNet (CPU version).
+  
+    # install Apache MXNet (CPU version).
   - pip install mxnet
   - pip install --upgrade numpy
-
+  
   # install cntk
   - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then
       pip install https://cntk.ai/PythonWheel/CPU-Only/cntk-2.5.1-cp27-cp27mu-linux_x86_64.whl;

diff --git a/ISSUE_TEMPLATE.md b/ISSUE_TEMPLATE.md
@@ -5,6 +5,8 @@ Thank you!
 - [ ] Check that you are up-to-date with the master branch of Keras. You can update with:
 pip install git+git://github.com/awslabs/keras-apache-mxnet.git --upgrade --no-deps
 
+- [ ] If running on MXNet, check that you are up-to-date with the latest version. The installation
+instructions can be found [here](http://mxnet.incubator.apache.org/install/index.html?platform=Linux&language=Python&processor=CPU)
 - [ ] If running on TensorFlow, check that you are up-to-date with the latest version. The installation instructions can be found [here](https://www.tensorflow.org/get_started/os_setup).
 
 - [ ] If running on Theano, check that you are up-to-date with the master branch of Theano. You can update with:

diff --git a/PULL_REQUEST_TEMPLATE.md b/PULL_REQUEST_TEMPLATE.md
@@ -0,0 +1,10 @@
+### Summary
+
+### Related Issues
+
+### PR Overview
+
+- [ ] This PR requires new unit tests [y/n] (make sure tests are included)
+- [ ] This PR requires to update the documentation [y/n] (make sure the docs are up-to-date)
+- [ ] This PR is backwards compatible [y/n]
+- [ ] This PR changes the current API [y/n]
diff --git a/benchmark/README.md b/benchmark/README.md
@@ -6,6 +6,7 @@
 2. [Library Versions](#library-versions)
 3. [CNN Benchmarks](#cnn-benchmarks)
     1. [CNN Benchmark Results](#cnn-benchmark-results)
+    2. [CNN Inference Benchmark Results](#cnn-inference-benchmark-results)
 4. [RNN Benchmarks (Experimental)](#rnn-benchmarks-experimental)
 5. [Setup](#setup)
 6. [How to Run CNN Benchmarks](#how-to-run-cnn-benchmarks)
@@ -89,7 +90,16 @@ NOTE:
 You can see more benchmark experiments with different instance types, batch_size and other parameters in [detailed CNN 
 results document](benchmark_result/CNN_result.md).
 
-
+
+### CNN Inference Benchmark Results
+
+#### ResNet50-Synthetic Data
+
+| Instance Type | GPUs  | Batch Size  | Keras-MXNet (img/sec)  | Keras-TensorFlow (img/sec)  |
+|---|---|---|---|---|
+|  C5.X Large |  0 |  32 | 5.79  | 3.27  |
+|  C5.8X Large | 0  | 32  | 27.9  | 18.2  |
+
 ```
 NOTE:
     1. Image_data_format for MXNet backend - 'channels_first'
@@ -192,6 +202,18 @@ For TensorFlow backend benchmarks:
     $ sh run_tf_backend.sh 8_gpu_config resnet50 False 20 # For 8 GPU Benchmarks
 ```
 
+### ResNet50-Synthetic Inference Benchmarks
+
+For MXNet backend inference benchmarks:
+```
+    $ sh run_mxnet_backend.sh cpu_config resnet50 True 20
+```
+
+For TensorFlow backend inference benchmarks:
+```
+    $ sh run_tf_backend.sh cpu_config resnet50 True 20
+```
+
 The last parameter, 20, in the command is the number of epoch.
 
 ## How to Run RNN Benchmarks
@@ -260,4 +282,4 @@ For TensorFlow backend benchmarks:
 ## References
 
 * [TensorFlow Keras Benchmarks](https://github.com/tensorflow/benchmarks/tree/keras-benchmarks/scripts/keras_benchmarks)
-* [lstm_text_generation.py](https://github.com/keras-team/keras/blob/master/examples/lstm_text_generation.py)
+* [lstm_text_generation.py](https://github.com/keras-team/keras/blob/master/examples/lstm_text_generation.py)
diff --git a/benchmark/benchmark_result/cnn_inference_speed.png b/benchmark/benchmark_result/cnn_inference_speed.png
diff --git a/benchmark/scripts/run_benchmark.py b/benchmark/scripts/run_benchmark.py
@@ -66,8 +66,11 @@ def get_backend_version():
 
 use_dataset_tensors = False
 if args.epochs:
-    model.run_benchmark(gpus=config['gpus'], inference=inference, use_dataset_tensors=use_dataset_tensors, epochs=int(args.epochs))
+    model.run_benchmark(gpus=config['gpus'], inference=inference,
+                        use_dataset_tensors=use_dataset_tensors,
+                        epochs=int(args.epochs))
 else:
-    model.run_benchmark(gpus=config['gpus'], inference=inference, use_dataset_tensors=use_dataset_tensors)
+    model.run_benchmark(gpus=config['gpus'], inference=inference,
+                        use_dataset_tensors=use_dataset_tensors)
 if args.dry_run:
     print("Model :total_time", model.test_name, model.total_time)
diff --git a/docs/autogen.py b/docs/autogen.py
@@ -99,6 +99,7 @@
     'deserialize',
     'get',
     'set_image_dim_ordering',
+    'normalize_data_format',
     'image_dim_ordering',
     'get_variable_shape',
 }
@@ -114,7 +115,7 @@
 PAGES = [
     {
         'page': 'models/sequential.md',
-        'functions': [
+        'methods': [
             models.Sequential.compile,
             models.Sequential.fit,
             models.Sequential.evaluate,
@@ -130,7 +131,7 @@
     },
     {
         'page': 'models/model.md',
-        'functions': [
+        'methods': [
             models.Model.compile,
             models.Model.fit,
             models.Model.evaluate,
@@ -341,32 +342,6 @@
 ROOT = 'http://keras.io/'
 
 
-def get_earliest_class_that_defined_member(member, cls):
-    ancestors = get_classes_ancestors([cls])
-    result = None
-    for ancestor in ancestors:
-        if member in dir(ancestor):
-            result = ancestor
-    if not result:
-        return cls
-    return result
-
-
-def get_classes_ancestors(classes):
-    ancestors = []
-    for cls in classes:
-        ancestors += cls.__bases__
-    filtered_ancestors = []
-    for ancestor in ancestors:
-        if ancestor.__name__ in ['object']:
-            continue
-        filtered_ancestors.append(ancestor)
-    if filtered_ancestors:
-        return filtered_ancestors + get_classes_ancestors(filtered_ancestors)
-    else:
-        return filtered_ancestors
-
-
 def get_function_signature(function, method=True):
     wrapped = getattr(function, '_original_function', None)
     if wrapped is None:
@@ -395,10 +370,6 @@ def get_function_signature(function, method=True):
         signature = st[:-2] + ')'
     else:
         signature = st + ')'
-
-    if not method:
-        # Prepend the module name.
-        signature = clean_module_name(function.__module__) + '.' + signature
     return post_process_signature(signature)
 
 
@@ -409,12 +380,15 @@ def get_class_signature(cls):
     except (TypeError, AttributeError):
         # in case the class inherits from object and does not
         # define __init__
-        class_signature = clean_module_name(cls.__module__) + '.' + cls.__name__ + '()'
+        class_signature = "{clean_module_name}.{cls_name}()".format(
+            clean_module_name=clean_module_name(cls.__module__),
+            cls_name=cls.__name__
+        )
     return post_process_signature(class_signature)
 
 
 def post_process_signature(signature):
-    parts = re.split('\.(?!\d)', signature)
+    parts = re.split(r'\.(?!\d)', signature)
     if len(parts) >= 4:
         if parts[1] == 'layers':
             signature = 'keras.layers.' + '.'.join(parts[3:])
@@ -459,7 +433,7 @@ def code_snippet(snippet):
 
 
 def count_leading_spaces(s):
-    ws = re.search('\S', s)
+    ws = re.search(r'\S', s)
     if ws:
         return ws.start()
     else:
@@ -468,7 +442,8 @@ def count_leading_spaces(s):
 
 def process_list_block(docstring, starting_point, leading_spaces, marker):
     ending_point = docstring.find('\n\n', starting_point)
-    block = docstring[starting_point:None if ending_point == -1 else ending_point - 1]
+    block = docstring[starting_point:(None if ending_point == -1 else
+                                      ending_point - 1)]
     # Place marker for later reinjection.
     docstring = docstring.replace(block, marker)
     lines = block.split('\n')
@@ -596,7 +571,6 @@ def process_docstring(docstring):
             shutil.copy(fpath, new_fpath)
 
 
-# Take care of index page.
 def read_file(path):
     with open(path) as f:
         return f.read()
@@ -616,16 +590,37 @@ def collect_class_methods(cls, methods):
 def render_function(function, method=True):
     subblocks = []
     signature = get_function_signature(function, method=method)
-    signature = signature.replace(function.__module__ + '.', '')
-    level = 3
-    subblocks.append('#' * level + ' ' + function.__name__ + '\n')
+    if method:
+        signature = signature.replace(
+            clean_module_name(function.__module__) + '.', '')
+    subblocks.append('### ' + function.__name__ + '\n')
     subblocks.append(code_snippet(signature))
     docstring = function.__doc__
     if docstring:
         subblocks.append(process_docstring(docstring))
     return '\n\n'.join(subblocks)
 
 
+def read_page_data(page_data, type):
+    assert type in ['classes', 'functions', 'methods']
+    data = page_data.get(type, [])
+    for module in page_data.get('all_module_{}'.format(type), []):
+        module_data = []
+        for name in dir(module):
+            if name[0] == '_' or name in EXCLUDE:
+                continue
+            module_member = getattr(module, name)
+            if (inspect.isclass(module_member) and type == 'classes' or
+               inspect.isfunction(module_member) and type == 'functions'):
+                instance = module_member
+                if module.__name__ in instance.__module__:
+                    if instance not in module_data:
+                        module_data.append(instance)
+        module_data.sort(key=lambda x: id(x))
+        data += module_data
+    return data
+
+
 if __name__ == '__main__':
     readme = read_file('../README.md')
     index = read_file('templates/index.md')
@@ -635,22 +630,9 @@ def render_function(function, method=True):
 
     print('Generating docs for Keras %s.' % keras.__version__)
     for page_data in PAGES:
-        blocks = []
-        classes = page_data.get('classes', [])
-        for module in page_data.get('all_module_classes', []):
-            module_classes = []
-            for name in dir(module):
-                if name[0] == '_' or name in EXCLUDE:
-                    continue
-                module_member = getattr(module, name)
-                if inspect.isclass(module_member):
-                    cls = module_member
-                    if cls.__module__ == module.__name__:
-                        if cls not in module_classes:
-                            module_classes.append(cls)
-            module_classes.sort(key=lambda x: id(x))
-            classes += module_classes
+        classes = read_page_data(page_data, 'classes')
 
+        blocks = []
         for element in classes:
             if not isinstance(element, (list, tuple)):
                 element = (element, [])
@@ -675,20 +657,12 @@ def render_function(function, method=True):
                     [render_function(method, method=True) for method in methods]))
             blocks.append('\n'.join(subblocks))
 
-        functions = page_data.get('functions', [])
-        for module in page_data.get('all_module_functions', []):
-            module_functions = []
-            for name in dir(module):
-                if name[0] == '_' or name in EXCLUDE:
-                    continue
-                module_member = getattr(module, name)
-                if inspect.isfunction(module_member):
-                    function = module_member
-                    if module.__name__ in function.__module__:
-                        if function not in module_functions:
-                            module_functions.append(function)
-            module_functions.sort(key=lambda x: id(x))
-            functions += module_functions
+        methods = read_page_data(page_data, 'methods')
+
+        for method in methods:
+            blocks.append(render_function(method, method=True))
+
+        functions = read_page_data(page_data, 'functions')
 
         for function in functions:
             blocks.append(render_function(function, method=False))
@@ -706,7 +680,8 @@ def render_function(function, method=True):
         if os.path.exists(path):
             template = read_file(path)
             assert '{{autogenerated}}' in template, ('Template found for ' + path +
-                                                     ' but missing {{autogenerated}} tag.')
+                                                     ' but missing {{autogenerated}}'
+                                                     ' tag.')
             mkdown = template.replace('{{autogenerated}}', mkdown)
             print('...inserting autogenerated content into template:', path)
         else:

diff --git a/docs/templates/applications.md b/docs/templates/applications.md
@@ -533,15 +533,6 @@ MobileNet model, with weights pre-trained on ImageNet.
 
 Note that this model only supports the data format `'channels_last'` (height, width, channels).
 
-To load a MobileNet model via `load_model`, import the custom object `relu6` and pass it to the `custom_objects` parameter.
-
-E.g.
-
-```python
-model = load_model('mobilenet.h5', custom_objects={
-                   'relu6': mobilenet.relu6})
-```
-
 The default input size for this model is 224x224.
 
 ### Arguments
@@ -732,15 +723,6 @@ MobileNetV2 model, with weights pre-trained on ImageNet.
 
 Note that this model only supports the data format `'channels_last'` (height, width, channels).
 
-To load a MobileNetV2 model via `load_model`, import the custom object `relu6` and pass it to the `custom_objects` parameter.
-
-E.g.
-
-```python
-model = load_model('mobilenet_v2.h5', custom_objects={
-                   'relu6': mobilenetv2.relu6})
-```
-
 The default input size for this model is 224x224.
 
 ### Arguments