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new 8e0f627 add doc for gluon, sym/nd contrib (#7284)
8e0f627 is described below
commit 8e0f627bbcf7b8f22c35e32a9b968f41ca1439e7
Author: Sheng Zha <[email protected]>
AuthorDate: Wed Aug 2 16:19:41 2017 -0700
add doc for gluon, sym/nd contrib (#7284)
* add doc for contrib
* docs for gluon, sym/nd contrib
---
Makefile | 3 +-
docs/api/python/gluon.md | 497 ++++++++++++++++++++++----
docs/api/python/ndarray.md | 34 ++
docs/api/python/symbol.md | 34 ++
python/mxnet/gluon/model_zoo/vision/resnet.py | 2 +
5 files changed, 492 insertions(+), 78 deletions(-)
diff --git a/Makefile b/Makefile
index f200b87..5c7f54d 100644
--- a/Makefile
+++ b/Makefile
@@ -13,6 +13,7 @@ endif
ifndef DMLC_CORE
DMLC_CORE = $(ROOTDIR)/dmlc-core
endif
+CORE_INC = $(wildcard $(DMLC_CORE)/include/*/*.h)
ifndef NNVM_PATH
NNVM_PATH = $(ROOTDIR)/nnvm
@@ -291,7 +292,7 @@ build/plugin/%.o: plugin/%.cc
$(NVCC) $(NVCCFLAGS) $(CUDA_ARCH) -Xcompiler "$(CFLAGS) -Isrc/operator"
-M -MT $*_gpu.o $< >$*_gpu.d
$(NVCC) -c -o $@ $(NVCCFLAGS) $(CUDA_ARCH) -Xcompiler "$(CFLAGS)
-Isrc/operator" $<
-%.o: %.cc
+%.o: %.cc $(CORE_INC)
@mkdir -p $(@D)
$(CXX) -std=c++11 -c $(CFLAGS) -MMD -Isrc/operator -c $< -o $@
diff --git a/docs/api/python/gluon.md b/docs/api/python/gluon.md
index cda4a07..6e213bb 100644
--- a/docs/api/python/gluon.md
+++ b/docs/api/python/gluon.md
@@ -21,58 +21,379 @@ in Python and then deploy with symbolic graph in C++ and
Scala.
## Parameter
```eval_rst
-.. currentmodule:: mxnet.gluon
+.. autosummary::
+ :nosignatures:
+
+ Parameter
+ ParameterDict
```
+## Containers
+
```eval_rst
-.. currentmodule:: mxnet.gluon
-.. autoclass:: mxnet.gluon.Parameter
- :members:
-.. autoclass:: mxnet.gluon.ParameterDict
- :members:
+.. autosummary::
+ :nosignatures:
+
+ Block
+ HybridBlock
+ SymbolBlock
```
+## Neural Network Layers
+
+```eval_rst
+.. currentmodule:: mxnet.gluon.nn
+```
+
+### Containers
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ Sequential
+ HybridSequential
+```
+
+
+### Basic Layers
+
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ Dense
+ Activation
+ Dropout
+ BatchNorm
+ LeakyReLU
+ Embedding
+```
+
+
+### Convolutional Layers
+
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ Conv1D
+ Conv2D
+ Conv3D
+ Conv1DTranspose
+ Conv2DTranspose
+ Conv3DTranspose
+```
+
+
+
+### Pooling Layers
-## Containers
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ MaxPool1D
+ MaxPool2D
+ MaxPool3D
+ AvgPool1D
+ AvgPool2D
+ AvgPool3D
+ GlobalMaxPool1D
+ GlobalMaxPool2D
+ GlobalMaxPool3D
+ GlobalAvgPool1D
+ GlobalAvgPool2D
+ GlobalAvgPool3D
+```
+
+
+
+## Recurrent Layers
+
+```eval_rst
+.. currentmodule:: mxnet.gluon.rnn
+```
+
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ RecurrentCell
+ RNN
+ LSTM
+ GRU
+ RNNCell
+ LSTMCell
+ GRUCell
+ SequentialRNNCell
+ BidirectionalCell
+ DropoutCell
+ ZoneoutCell
+ ResidualCell
+```
+
+
+## Trainer
```eval_rst
.. currentmodule:: mxnet.gluon
-.. autoclass:: mxnet.gluon.Block
- :members:
- .. automethod:: forward
-.. autoclass:: mxnet.gluon.HybridBlock
- :members:
+.. autosummary::
+ :nosignatures:
- .. automethod:: hybrid_forward
+ Trainer
```
-## Neural Network Layers
+
+## Loss functions
```eval_rst
-.. currentmodule:: mxnet.gluon.nn
+.. currentmodule:: mxnet.gluon.loss
```
-### Containers
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ L2Loss
+ L1Loss
+ SoftmaxCrossEntropyLoss
+ KLDivLoss
+```
+
+## Utilities
```eval_rst
-.. currentmodule:: mxnet.gluon.nn
+.. currentmodule:: mxnet.gluon.utils
+```
- .. automethod:: __call__
-.. autoclass:: mxnet.gluon.nn.Sequential
- :members:
-.. autoclass:: mxnet.gluon.nn.HybridSequential
- :members:
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ split_data
+ split_and_load
+ clip_global_norm
```
+## Data
-### Basic Layers
+```eval_rst
+.. currentmodule:: mxnet.gluon.data
+```
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ Dataset
+ ArrayDataset
+ RecordFileDataset
+ ImageRecordDataset
+```
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ Sampler
+ SequentialSampler
+ RandomSampler
+ BatchSampler
+```
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ DataLoader
+```
+
+### Vision
+
+```eval_rst
+.. currentmodule:: mxnet.gluon.data.vision
+```
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ MNIST
+ CIFAR10
+```
+
+## Model Zoo
+
+Model zoo provides pre-defined and pre-trained models to help bootstrap
machine learning applications.
+
+### Vision
+
+```eval_rst
+.. currentmodule:: mxnet.gluon.model_zoo.vision
+```
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ get_model
+```
+
+#### ResNet
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ resnet18_v1
+ resnet34_v1
+ resnet50_v1
+ resnet101_v1
+ resnet152_v1
+ resnet18_v2
+ resnet34_v2
+ resnet50_v2
+ resnet101_v2
+ resnet152_v2
+```
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ ResNetV1
+ ResNetV2
+ BasicBlockV1
+ BasicBlockV2
+ BottleneckV1
+ BottleneckV2
+ get_resnet
+```
+
+#### VGG
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ vgg11
+ vgg13
+ vgg16
+ vgg19
+ vgg11_bn
+ vgg13_bn
+ vgg16_bn
+ vgg19_bn
+```
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ VGG
+ get_vgg
+```
+#### Alexnet
```eval_rst
-.. currentmodule:: mxnet.gluon.nn
+.. autosummary::
+ :nosignatures:
+
+ alexnet
+```
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ AlexNet
+```
+
+#### DenseNet
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ densenet121
+ densenet161
+ densenet169
+ densenet201
+```
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ DenseNet
+```
+
+#### SqueezeNet
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ squeezenet1_0
+ squeezenet1_1
+```
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ SqueezeNet
+```
+
+#### Inception
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ inception_v3
+```
+
+```eval_rst
+.. autosummary::
+ :nosignatures:
+
+ Inception3
+```
+
+## API Reference
+
+<script type="text/javascript"
src='../../_static/js/auto_module_index.js'></script>
+
+```eval_rst
+.. autoclass:: mxnet.gluon.Parameter
+ :members:
+.. autoclass:: mxnet.gluon.ParameterDict
+ :members:
+
+.. autoclass:: mxnet.gluon.Block
+ :members:
+
+ .. automethod:: __call__
+.. autoclass:: mxnet.gluon.HybridBlock
+ :members:
+.. autoclass:: mxnet.gluon.SymbolBlock
+ :members:
+
+.. autoclass:: mxnet.gluon.nn.Sequential
+ :members:
+.. autoclass:: mxnet.gluon.nn.HybridSequential
+ :members:
.. autoclass:: mxnet.gluon.nn.Dense
:members:
.. autoclass:: mxnet.gluon.nn.Activation
@@ -85,14 +406,6 @@ in Python and then deploy with symbolic graph in C++ and
Scala.
:members:
.. autoclass:: mxnet.gluon.nn.Embedding
:members:
-```
-
-
-### Convolutional Layers
-
-
-```eval_rst
-.. currentmodule:: mxnet.gluon.nn
.. autoclass:: mxnet.gluon.nn.Conv1D
:members:
.. autoclass:: mxnet.gluon.nn.Conv2D
@@ -105,15 +418,6 @@ in Python and then deploy with symbolic graph in C++ and
Scala.
:members:
.. autoclass:: mxnet.gluon.nn.Conv3DTranspose
:members:
-```
-
-
-
-### Pooling Layers
-
-
-```eval_rst
-.. currentmodule:: mxnet.gluon.nn
.. autoclass:: mxnet.gluon.nn.MaxPool1D
:members:
.. autoclass:: mxnet.gluon.nn.MaxPool2D
@@ -138,18 +442,7 @@ in Python and then deploy with symbolic graph in C++ and
Scala.
:members:
.. autoclass:: mxnet.gluon.nn.GlobalAvgPool3D
:members:
-```
-
-
-## Recurrent Layers
-
-```eval_rst
-.. currentmodule:: mxnet.gluon.rnn
-```
-
-
-```eval_rst
.. autoclass:: mxnet.gluon.rnn.RecurrentCell
:members:
@@ -176,26 +469,10 @@ in Python and then deploy with symbolic graph in C++ and
Scala.
:members:
.. autoclass:: mxnet.gluon.rnn.ResidualCell
:members:
-```
-
-## Trainer
-
-```eval_rst
-.. currentmodule:: mxnet.gluon
-```
-
-
-```eval_rst
.. autoclass:: mxnet.gluon.Trainer
:members:
-```
-
-
-## Loss functions
-```eval_rst
-.. currentmodule:: mxnet.gluon.loss
.. autoclass:: mxnet.gluon.loss.L2Loss
:members:
.. autoclass:: mxnet.gluon.loss.L1Loss
@@ -204,19 +481,85 @@ in Python and then deploy with symbolic graph in C++ and
Scala.
:members:
.. autoclass:: mxnet.gluon.loss.KLDivLoss
:members:
-```
+.. automethod:: mxnet.gluon.utils.split_data
-## Utilities
+.. automethod:: mxnet.gluon.utils.split_and_load
-```eval_rst
-.. currentmodule:: mxnet.gluon.utils
-```
+.. automethod:: mxnet.gluon.utils.clip_global_norm
+.. autoclass:: mxnet.gluon.data.Dataset
+ :members:
+.. autoclass:: mxnet.gluon.data.ArrayDataset
+ :members:
+.. autoclass:: mxnet.gluon.data.RecordFileDataset
+ :members:
+.. autoclass:: mxnet.gluon.data.ImageRecordDataset
+ :members:
+.. autoclass:: mxnet.gluon.data.Sampler
+ :members:
+.. autoclass:: mxnet.gluon.data.SequentialSampler
+ :members:
+.. autoclass:: mxnet.gluon.data.RandomSampler
+ :members:
+.. autoclass:: mxnet.gluon.data.BatchSampler
+ :members:
+.. autoclass:: mxnet.gluon.data.DataLoader
+ :members:
+.. automodule:: mxnet.gluon.data.vision
+ :members:
-```eval_rst
-.. automethod:: mxnet.gluon.utils.split_data
-.. automethod:: mxnet.gluon.utils.split_and_load
-.. automethod:: mxnet.gluon.utils.clip_global_norm
+.. automodule:: mxnet.gluon.model_zoo.vision
+ :members:
+.. automethod:: mxnet.gluon.model_zoo.vision.resnet18_v1
+.. automethod:: mxnet.gluon.model_zoo.vision.resnet34_v1
+.. automethod:: mxnet.gluon.model_zoo.vision.resnet50_v1
+.. automethod:: mxnet.gluon.model_zoo.vision.resnet101_v1
+.. automethod:: mxnet.gluon.model_zoo.vision.resnet152_v1
+.. automethod:: mxnet.gluon.model_zoo.vision.resnet18_v2
+.. automethod:: mxnet.gluon.model_zoo.vision.resnet34_v2
+.. automethod:: mxnet.gluon.model_zoo.vision.resnet50_v2
+.. automethod:: mxnet.gluon.model_zoo.vision.resnet101_v2
+.. automethod:: mxnet.gluon.model_zoo.vision.resnet152_v2
+.. automethod:: mxnet.gluon.model_zoo.vision.get_resnet
+.. autoclass:: mxnet.gluon.model_zoo.vision.ResNetV1
+ :members:
+.. autoclass:: mxnet.gluon.model_zoo.vision.BasicBlockV1
+ :members:
+.. autoclass:: mxnet.gluon.model_zoo.vision.BottleneckV1
+ :members:
+.. autoclass:: mxnet.gluon.model_zoo.vision.ResNetV2
+ :members:
+.. autoclass:: mxnet.gluon.model_zoo.vision.BasicBlockV2
+ :members:
+.. autoclass:: mxnet.gluon.model_zoo.vision.BottleneckV2
+ :members:
+.. automethod:: mxnet.gluon.model_zoo.vision.vgg11
+.. automethod:: mxnet.gluon.model_zoo.vision.vgg13
+.. automethod:: mxnet.gluon.model_zoo.vision.vgg16
+.. automethod:: mxnet.gluon.model_zoo.vision.vgg19
+.. automethod:: mxnet.gluon.model_zoo.vision.vgg11_bn
+.. automethod:: mxnet.gluon.model_zoo.vision.vgg13_bn
+.. automethod:: mxnet.gluon.model_zoo.vision.vgg16_bn
+.. automethod:: mxnet.gluon.model_zoo.vision.vgg19_bn
+.. automethod:: mxnet.gluon.model_zoo.vision.get_vgg
+.. autoclass:: mxnet.gluon.model_zoo.vision.VGG
+ :members:
+.. automethod:: mxnet.gluon.model_zoo.vision.alexnet
+.. autoclass:: mxnet.gluon.model_zoo.vision.AlexNet
+ :members:
+.. automethod:: mxnet.gluon.model_zoo.vision.densenet121
+.. automethod:: mxnet.gluon.model_zoo.vision.densenet161
+.. automethod:: mxnet.gluon.model_zoo.vision.densenet169
+.. automethod:: mxnet.gluon.model_zoo.vision.densenet201
+.. autoclass:: mxnet.gluon.model_zoo.vision.DenseNet
+ :members:
+.. automethod:: mxnet.gluon.model_zoo.vision.squeezenet1_0
+.. automethod:: mxnet.gluon.model_zoo.vision.squeezenet1_1
+.. autoclass:: mxnet.gluon.model_zoo.vision.SqueezeNet
+ :members:
+.. automethod:: mxnet.gluon.model_zoo.vision.inception_v3
+.. autoclass:: mxnet.gluon.model_zoo.vision.Inception3
+ :members:
```
<script>auto_index("api-reference");</script>
diff --git a/docs/api/python/ndarray.md b/docs/api/python/ndarray.md
index a782b91..5e9f7e1 100644
--- a/docs/api/python/ndarray.md
+++ b/docs/api/python/ndarray.md
@@ -463,6 +463,37 @@ In the rest of this document, we first overview the
methods provided by the
Custom
```
+## Contrib
+
+```eval_rst
+.. warning:: This package contains experimental APIs and may change in the
near future.
+```
+
+The `contrib.ndarray` module contains many useful experimental APIs for new
features. This is a place for the community to try out the new features, so
that feature contributors can receive feedback.
+
+```eval_rst
+.. currentmodule:: mxnet.contrib.ndarray
+
+.. autosummary::
+ :nosignatures:
+
+ CTCLoss
+ DeformableConvolution
+ DeformablePSROIPooling
+ MultiBoxDetection
+ MultiBoxPrior
+ MultiBoxTarget
+ MultiProposal
+ PSROIPooling
+ Proposal
+ count_sketch
+ ctc_loss
+ dequantize
+ fft
+ ifft
+ quantize
+```
+
## API Reference
<script type="text/javascript"
src='../../_static/js/auto_module_index.js'></script>
@@ -474,6 +505,9 @@ In the rest of this document, we first overview the methods
provided by the
.. automodule:: mxnet.random
:members:
+.. automodule:: mxnet.contrib.ndarray
+ :members:
+
```
<script>auto_index("api-reference");</script>
diff --git a/docs/api/python/symbol.md b/docs/api/python/symbol.md
index 0ebb869..dd455ee 100644
--- a/docs/api/python/symbol.md
+++ b/docs/api/python/symbol.md
@@ -480,6 +480,37 @@ Composite multiple symbols into a new one by an operator.
Custom
```
+## Contrib
+
+```eval_rst
+.. warning:: This package contains experimental APIs and may change in the
near future.
+```
+
+The `contrib.symbol` module contains many useful experimental APIs for new
features. This is a place for the community to try out the new features, so
that feature contributors can receive feedback.
+
+```eval_rst
+.. currentmodule:: mxnet.contrib.symbol
+
+.. autosummary::
+ :nosignatures:
+
+ CTCLoss
+ DeformableConvolution
+ DeformablePSROIPooling
+ MultiBoxDetection
+ MultiBoxPrior
+ MultiBoxTarget
+ MultiProposal
+ PSROIPooling
+ Proposal
+ count_sketch
+ ctc_loss
+ dequantize
+ fft
+ ifft
+ quantize
+```
+
## API Reference
<script type="text/javascript"
src='../../_static/js/auto_module_index.js'></script>
@@ -488,6 +519,9 @@ Composite multiple symbols into a new one by an operator.
.. automodule:: mxnet.symbol
:members:
+.. automodule:: mxnet.contrib.symbol
+ :members:
+
```
<script>auto_index("api-reference");</script>
diff --git a/python/mxnet/gluon/model_zoo/vision/resnet.py
b/python/mxnet/gluon/model_zoo/vision/resnet.py
index 2870911..5e2adad 100644
--- a/python/mxnet/gluon/model_zoo/vision/resnet.py
+++ b/python/mxnet/gluon/model_zoo/vision/resnet.py
@@ -4,6 +4,8 @@
from __future__ import division
__all__ = ['ResNetV1', 'ResNetV2',
+ 'BasicBlockV1', 'BasicBlockV2',
+ 'BottleneckV1', 'BottleneckV2',
'resnet18_v1', 'resnet34_v1', 'resnet50_v1', 'resnet101_v1',
'resnet152_v1',
'resnet18_v2', 'resnet34_v2', 'resnet50_v2', 'resnet101_v2',
'resnet152_v2',
'get_resnet']
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