[DOC/TOPI] Add API doc for topi (#226)

* [DOC/TOPI] Add API doc for topi

* fix lint

docs/api/python/index.rst

@@ -15,3 +15,4 @@ Python API
    function
    contrib
    dev
+   topi

docs/api/python/topi.rst

+TVM Operator Inventory
+----------------------
+.. automodule:: topi
+
+Index
+~~~~~
+
+**List of operators**
+
+.. autosummary::
+
+   topi.exp
+   topi.tanh
+   topi.log
+   topi.sqrt
+   topi.nn.relu
+   topi.nn.scale_shift
+   topi.nn.depthwise_conv2d
+
+
+**List of schedules**
+
+.. autosummary::
+
+   topi.cuda.schedule_depthwise_conv2d_map
+
+
+topi
+~~~~
+.. autofunction:: topi.exp
+.. autofunction:: topi.tanh
+.. autofunction:: topi.log
+.. autofunction:: topi.sqrt
+
+topi.nn
+~~~~~~~
+.. autofunction:: topi.nn.relu
+.. autofunction:: topi.nn.scale_shift
+.. autofunction:: topi.nn.depthwise_conv2d
+
+topi.cuda
+~~~~~~~~~
+.. automodule:: topi.cuda
+
+.. autofunction:: topi.cuda.schedule_depthwise_conv2d_map

docs/conf.py

@@ -23,8 +23,8 @@ from recommonmark.transform import AutoStructify
 # add these directories to sys.path here. If the directory is relative to the
 # documentation root, use os.path.abspath to make it absolute, like shown here.
 curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
-libpath = os.path.join(curr_path, '../python/')
-sys.path.insert(0, libpath)
+sys.path.insert(0, os.path.join(curr_path, '../python/'))
+sys.path.insert(0, os.path.join(curr_path, '../topi/python'))
 
 # -- General configuration ------------------------------------------------
 

topi/README.md

 # TVM Operator Inventory
 
 topi is the operator collection library for TVM intended at sharing the effort of crafting and
-optimizing tvm generated kernels. The goal
+optimizing tvm generated kernels. The goal:
 
 - Provide sugars for operator declaration
 - Give common primitives for fused op creation.

topi/python/topi/__init__.py

 # pylint: disable=redefined-builtin, wildcard-import
-"""TVM Operator Inventory."""
+"""TVM Operator Inventory.
+
+TOPI is the operator collection library for TVM intended at sharing the effort of crafting and
+optimizing tvm generated kernels.
+"""
 from __future__ import absolute_import as _abs
 
-from .ewise import *
+from .math import *
+from . import nn
+from . import cuda

topi/python/topi/cuda/__init__.py

 # pylint: disable=redefined-builtin, wildcard-import
-"""CUDA specific declaration and schedule."""
+"""CUDA specific declaration and schedules."""
 from __future__ import absolute_import as _abs
 
-from .depthwise_conv2d_map import *
+from .depthwise_conv2d_map import schedule_depthwise_conv2d_map

topi/python/topi/cuda/depthwise_conv2d_map.py

@@ -4,8 +4,9 @@ import tvm
 from ..nn.util import get_const_tuple
 
 def schedule_depthwise_conv2d_map(op):
-    """Schedule for depthwise_conv2d and auto fusion with
-    one-to-one-mapping operators, e.g. scale-shift and relu.
+    """Schedule for depthwise_conv2d  map ops.
+
+    This include scale-shift and relu.
 
     Parameters
     ----------

topi/python/topi/ewise.py → topi/python/topi/math.py

@@ -85,20 +85,3 @@ def sigmoid(x):
         The result.
     """
     return tvm.compute(x.shape, lambda *i: tvm.sigmoid(x(*i)))
-
-
-@tvm.tag_scope(tag="ewise")
-def relu(x):
-    """Take relu of input x.
-
-    Parameters
-    ----------
-    x : tvm.Tensor
-        Input argument.
-
-    Returns
-    -------
-    y : tvm.Tensor
-        The result.
-    """
-    return tvm.compute(x.shape, lambda *i: tvm.max(x(*i), 0))

topi/python/topi/nn/__init__.py

@@ -2,6 +2,6 @@
 """Neural network operators"""
 from __future__ import absolute_import as _abs
 
-from .util import *
 from .mapping import *
+from .ewise import *
 from .conv import *

topi/python/topi/nn/conv.py

@@ -7,7 +7,7 @@ from .util import get_const_tuple
 
 @tvm.tag_scope(tag="depthwise_conv2d")
 def depthwise_conv2d(Input, Filter, Stride, padding):
-    """Depthwise convolution operator, as depthwise_conv2d in tensorflow.
+    """Depthwise convolution operator.
 
     Parameters
     ----------

topi/python/topi/nn/ewise.py

+"""Elementwise operators"""
+from __future__ import absolute_import as _abs
+import tvm
+
+@tvm.tag_scope(tag="ewise")
+def relu(x):
+    """Take relu of input x.
+
+    Parameters
+    ----------
+    x : tvm.Tensor
+        Input argument.
+
+    Returns
+    -------
+    y : tvm.Tensor
+        The result.
+    """
+    return tvm.compute(x.shape, lambda *i: tvm.max(x(*i), 0))

topi/recipe/conv/depthwise_conv2d_map_test.py

@@ -55,7 +55,7 @@ def test_depthwise_conv2d_map():
     # Declare
     DepthwiseConv2d = topi.nn.depthwise_conv2d(Input, Filter, Stride, padding)
     ScaleShift = topi.nn.scale_shift(DepthwiseConv2d, Scale, Shift)
-    Relu = topi.ewise.relu(ScaleShift)
+    Relu = topi.nn.relu(ScaleShift)
     # Schedule
     s1 = schedule_depthwise_conv2d_map(DepthwiseConv2d.op)
     s2 = schedule_depthwise_conv2d_map(ScaleShift.op)