[v0.1.0] Silee2/python binding (#674)

* Remove unsupported linker flags for Mac build.

* Restructure python binding.
Put low level direct wrapper for ngraph c++ API into ngraph/impl
Move high level API from ngraph_api to ngraph

* Move CMakeLists.txt to its own PR

Author: silee2

doc/examples/onnx_example.py

@@ -21,10 +21,10 @@
 # Convert a serialized ONNX model to an ngraph model
 from ngraph_onnx.onnx_importer.importer import import_onnx_model
 ng_model = import_onnx_model(onnx_protobuf)[0]
- 
 
-# Using ngraph_api, create a callable computation object
-import ngraph_api as ng
+ 
+# Using an ngraph runtime (CPU backend), create a callable computation
+import ngraph as ng
 runtime = ng.runtime(manager_name='CPU')
 resnet = runtime.computation(ng_model['output'], *ng_model['inputs'])
 

python/README.md

@@ -44,7 +44,7 @@ pip install -r test_requirements.txt
 Then run a test.
 ```
 pytest test/test_ops.py
-pytest test/ngraph_api/*
+pytest test/ngraph/*
 ```
 
 ## Running tests with tox
@@ -70,7 +70,7 @@ You can run tests using only Python 3 or 2 using the `-e` (environment) switch:
 
 You can check styles in a particular code directory by specifying the path:
 
-    tox ngraph_api/
+    tox ngraph/
 
 In case of problems, try to recreate the virtual environments by deleting the `.tox` directory:
 

python/examples/basic.py

@@ -16,7 +16,7 @@
 """Usage example for the ngraph Pythonic API."""
 
 import numpy as np
-import ngraph_api as ng
+import ngraph as ng
 
 shape = [2, 2]
 A = ng.parameter(shape, name='A')

python/examples/mnist_mlp.py

@@ -14,12 +14,12 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ******************************************************************************
-from ngraph import Type, Function
-from ngraph import Node
-from ngraph.op import Parameter, Maximum, Reshape, Dot, Broadcast
-from ngraph.op import Constant, Exp, Log, Sum
-from ngraph.op import Greater, Convert, Reduce
-from ngraph.op import OneHot
+from ngraph.impl import Type, Function
+from ngraph.impl import Node, Shape, AxisVector, AxisSet
+from ngraph.impl.op import Parameter, Maximum, Reshape, Dot, Broadcast
+from ngraph.impl.op import Constant, Exp, Log, Sum
+from ngraph.impl.op import Greater, Convert, Reduce
+from ngraph.impl.op import OneHot
 
 from typing import List, Dict, Set
 
@@ -29,13 +29,13 @@
 bz = 53
 lr = 0.2
 
-Input = Parameter(float_element_type, [bz, 28, 28])
-Label = Parameter(int_element_type, [bz])
-LabelOneHot = Convert((OneHot(Label, [bz, 10], 1)), float_element_type)
+Input = Parameter(float_element_type, Shape([bz, 28, 28]))
+Label = Parameter(int_element_type, Shape([bz]))
+LabelOneHot = Convert((OneHot(Label, Shape([bz, 10]), 1)), float_element_type)
 
-MaxParam1 = Parameter(float_element_type, [])
-MaxParam2 = Parameter(float_element_type, [])
-MaxFn = Function([Maximum(MaxParam1, MaxParam2)],
+MaxParam1 = Parameter(float_element_type, Shape([]))
+MaxParam2 = Parameter(float_element_type, Shape([]))
+MaxFn = Function(Maximum(MaxParam1, MaxParam2),
                  [MaxParam1, MaxParam2],
                  'mnist')
 
@@ -44,10 +44,10 @@ def make_scalar_constant(elem_type, scalar, shape=None, axis_set=None):
     # type: (int, float, List[int], Set[int]) -> float
     """Create a Constant node for scalar value."""
     if shape is None:
-        shape = []
+        shape = Shape([])
     if axis_set is None:
-        axis_set = set()
-    scalar_shape = []  # type: List[int]
+        axis_set = AxisSet(set())
+    scalar_shape = Shape([])  # type: List[int]
     constant_op = Constant(elem_type, scalar_shape, [scalar])
     constant_broadcast = Broadcast(constant_op, shape, axis_set)
     return constant_broadcast
@@ -60,7 +60,7 @@ def make_float32_constant(scalar, shape=None, axis_set=None):
         shape = []
     if axis_set is None:
         axis_set = set()
-    return make_scalar_constant(Type.f32, scalar, shape, axis_set)
+    return make_scalar_constant(Type.f32, scalar, Shape(shape), AxisSet(axis_set))
 
 
 def make_float32_constant_like(scalar, op):  # type: (float, Node) -> float
@@ -69,7 +69,7 @@ def make_float32_constant_like(scalar, op):  # type: (float, Node) -> float
     shape = op.get_shape()
     for i in range(len(shape)):
         v.add(i)
-    return make_float32_constant(scalar, shape, v)
+    return make_float32_constant(scalar, Shape(shape), AxisSet(v))
 
 
 def transpose(op, order):  # type: (Node, List[int]) -> Node
@@ -78,7 +78,7 @@ def transpose(op, order):  # type: (Node, List[int]) -> Node
     for i in range(len(order)):
         v.append(op.get_shape()[order[i]])
     new_shape = v
-    return Reshape(op, order, new_shape)
+    return Reshape(op, AxisVector(order), Shape(new_shape))
 
 
 def relu(op):  # type: (Node) -> Node
@@ -87,45 +87,45 @@ def relu(op):  # type: (Node) -> Node
 
 
 # Flatten
-X1 = Reshape(Input, [0, 1, 2], [bz, 784])
+X1 = Reshape(Input, AxisVector([0, 1, 2]), Shape([bz, 784]))
 
 # Normalize
 X2 = X1 / make_float32_constant_like(255., X1)
 
 # Affine 1
-W1 = Parameter(float_element_type, [784, 100])
-b1 = Parameter(float_element_type, [100])
-X3 = Dot(X2, W1) + Broadcast(b1, [bz, 100], {0})
+W1 = Parameter(float_element_type, Shape([784, 100]))
+b1 = Parameter(float_element_type, Shape([100]))
+X3 = Dot(X2, W1) + Broadcast(b1, Shape([bz, 100]), AxisSet({0}))
 X4 = relu(X3)
 
 # Affine 2
-W2 = Parameter(float_element_type, [100, 10])
-b2 = Parameter(float_element_type, [10])
-X5 = Dot(X4, W2) + Broadcast(b2, [bz, 10], {0})
+W2 = Parameter(float_element_type, Shape([100, 10]))
+b2 = Parameter(float_element_type, Shape([10]))
+X5 = Dot(X4, W2) + Broadcast(b2, Shape([bz, 10]), AxisSet({0}))
 
 # Softmax
 Logits = X5
 Exp = Exp(Logits)
-Max = Reduce(Exp, make_float32_constant(0., [], set()), MaxFn, {1})
-MaxBroadcast = Broadcast(Max, [bz, 10], {1})
+Max = Reduce(Exp, make_float32_constant(0., [], set()), MaxFn, AxisSet({1}))
+MaxBroadcast = Broadcast(Max, Shape([bz, 10]), AxisSet({1}))
 Softmax = Exp / MaxBroadcast
 
 # Loss
 LogSoftmax = Log(Softmax)
-Loss = Sum(LogSoftmax * LabelOneHot, {0, 1}) / make_float32_constant(float(bz), [], set())
+Loss = Sum(LogSoftmax * LabelOneHot, AxisSet({0, 1})) / make_float32_constant(float(bz), [], set())
 
 # Derivatives
 dLogits = Softmax - LabelOneHot
 dX5 = dLogits
 
-dX4 = Dot(dX5, transpose(W2, [1, 0]))
-dW2 = Dot(transpose(X4, [1, 0]), dX5)
-db2 = Sum(dX5, {0})
+dX4 = Dot(dX5, transpose(W2, Shape([1, 0])))
+dW2 = Dot(transpose(X4, Shape([1, 0])), dX5)
+db2 = Sum(dX5, AxisSet({0}))
 
 dX3 = Convert((Greater(X3, make_float32_constant(0., [bz, 100], {0, 1}))), float_element_type) * dX4
-dX2 = Dot(dX3, transpose(W1, [1, 0]))
-dW1 = Dot(transpose(X2, [1, 0]), dX3)
-db1 = Sum(dX3, {0})
+dX2 = Dot(dX3, transpose(W1, Shape([1, 0])))
+dW1 = Dot(transpose(X2, Shape([1, 0])), dX3)
+db1 = Sum(dX3, AxisSet({0}))
 
 nW1 = W1 - make_float32_constant_like(lr, dW1) * dW1
 nb1 = b1 - make_float32_constant_like(lr, db1) * db1

python/ngraph/__init__.py

@@ -1,5 +1,5 @@
 # ******************************************************************************
-# Copyright 2017-2018 Intel Corporation
+# Copyright 2018 Intel Corporation
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -13,36 +13,43 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ******************************************************************************
-"""
-Package: ngraph
-Low level wrappers for the nGraph c++ api.
-"""
+"""ngraph module namespace, exposing factory functions for all ops and other classes."""
 
-# flake8: noqa
+from ngraph.ops import absolute
+from ngraph.ops import absolute as abs
+from ngraph.ops import add
+from ngraph.ops import avg_pool
+from ngraph.ops import broadcast
+from ngraph.ops import ceiling
+from ngraph.ops import ceiling as ceil
+from ngraph.ops import constant
+from ngraph.ops import convert
+from ngraph.ops import convolution
+from ngraph.ops import divide
+from ngraph.ops import dot
+from ngraph.ops import equal
+from ngraph.ops import exp
+from ngraph.ops import floor
+from ngraph.ops import greater
+from ngraph.ops import greater_eq
+from ngraph.ops import log
+from ngraph.ops import less
+from ngraph.ops import less_eq
+from ngraph.ops import logical_not
+from ngraph.ops import max
+from ngraph.ops import maximum
+from ngraph.ops import max_pool
+from ngraph.ops import min
+from ngraph.ops import minimum
+from ngraph.ops import multiply
+from ngraph.ops import negative
+from ngraph.ops import not_equal
+from ngraph.ops import parameter
+from ngraph.ops import prod
+from ngraph.ops import reshape
+from ngraph.ops import sqrt
+from ngraph.ops import subtract
+from ngraph.ops import sum
+from ngraph.ops import tanh
 
-import sys
-import six
-
-# workaround to load the libngraph.so with RTLD_GLOBAL
-if six.PY3:
-    import os
-    flags = os.RTLD_NOW | os.RTLD_GLOBAL
-else:
-    import ctypes
-    flags = sys.getdlopenflags() | ctypes.RTLD_GLOBAL
-sys.setdlopenflags(flags)
-
-from _pyngraph import Function
-from _pyngraph import Node
-from _pyngraph import NodeVector
-from _pyngraph import Type
-from _pyngraph import TensorViewType
-from _pyngraph import Shape
-from _pyngraph import Strides
-from _pyngraph import CoordinateDiff
-from _pyngraph import AxisSet
-from _pyngraph import AxisVector
-from _pyngraph import Coordinate
-
-from _pyngraph import serialize
-from _pyngraph import util
+from ngraph.runtime import runtime

python/ngraph_api/exceptions.py renamed to python/ngraph/exceptions.py

@@ -0,0 +1,48 @@
+# ******************************************************************************
+# Copyright 2017-2018 Intel Corporation
+#
+# Licensed 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.
+# ******************************************************************************
+"""
+Package: ngraph
+Low level wrappers for the nGraph c++ api.
+"""
+
+# flake8: noqa
+
+import sys
+import six
+
+# workaround to load the libngraph.so with RTLD_GLOBAL
+if six.PY3:
+    import os
+    flags = os.RTLD_NOW | os.RTLD_GLOBAL
+else:
+    import ctypes
+    flags = sys.getdlopenflags() | ctypes.RTLD_GLOBAL
+sys.setdlopenflags(flags)
+
+from _pyngraph import Function
+from _pyngraph import Node
+from _pyngraph import NodeVector
+from _pyngraph import Type
+from _pyngraph import TensorViewType
+from _pyngraph import Shape
+from _pyngraph import Strides
+from _pyngraph import CoordinateDiff
+from _pyngraph import AxisSet
+from _pyngraph import AxisVector
+from _pyngraph import Coordinate
+
+from _pyngraph import serialize
+from _pyngraph import util