fix python Executable wrapper

python/pyngraph/runtime/executable.cpp

@@ -25,7 +25,7 @@ namespace py = pybind11;
 
 void regclass_pyngraph_runtime_Executable(py::module m)
 {
-    py::class_<ngraph::runtime::Executable, std::unique_ptr<ngraph::runtime::Executable>>
+    py::class_<ngraph::runtime::Executable, std::shared_ptr<ngraph::runtime::Executable>>
         executable(m, "Executable");
     executable.doc() = "ngraph.impl.runtime.Executable wraps ngraph::runtime::Executable";
     executable.def("call",

python/test/test_ops.py

@@ -22,7 +22,7 @@ import numpy as np
 from ngraph.impl import util
 from ngraph.impl import Shape, Strides, CoordinateDiff, AxisSet, AxisVector, Coordinate
 from ngraph.impl import Type, Function, NodeVector
-from ngraph.impl.runtime import Backend
+from ngraph.impl.runtime import Backend, Executable
 from ngraph.impl.op import Acos, Asin, Atan, Cos, Sin, Tan
 from ngraph.impl.op import Cosh, Sinh, Tanh, Sqrt, Sign
 from ngraph.impl.op import Power, Negative, Ceiling, Floor
@@ -127,7 +127,8 @@ def binary_op_exec(op_str):
 
     result_arr = np.array([[0, 0], [0, 0]], dtype=np.float32)
     result.write(util.numpy_to_c(result_arr), 0, 16)
-    backend.call(backend.compile(function), [result], [a, b])
+    handle = backend.compile(function)
+    handle.call([result], [a, b])
     result.read(util.numpy_to_c(result_arr), 0, 16)
 
     a_arr = np.array([[1, 6], [7, 4]], dtype=np.float32)
@@ -156,7 +157,8 @@ def binary_op_comparison(op_str):
 
     result_arr = np.array([[False, False], [False, False]], dtype=np.bool)
     result.write(util.numpy_to_c(result_arr), 0, 4)
-    backend.call(backend.compile(function), [result], [a, b])
+    handle = backend.compile(function)
+    handle.call([result], [a, b])
     result.read(util.numpy_to_c(result_arr), 0, 4)
 
     a_arr = np.array([[1, 5], [3, 2]], dtype=np.float32)
@@ -256,7 +258,8 @@ def test_add_with_mul():
 
     result_arr = np.array([0, 0, 0, 0], dtype=np.float32)
     result.write(util.numpy_to_c(result_arr), 0, 16)
-    backend.call(backend.compile(function), [result], [a, b, c])
+    handle = backend.compile(function)
+    handle.call([result], [a, b, c])
     result.read(util.numpy_to_c(result_arr), 0, 16)
 
     a_arr = np.array([1, 2, 3, 4], dtype=np.float32)
@@ -364,7 +367,8 @@ def unary_op_exec(op_str, input_list):
 
     result_arr = np.zeros(shape_np, dtype=np.float32)
     result.write(util.numpy_to_c(result_arr), 0, 16)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, 16)
 
     a_arr = np.array(input_list, dtype=np.float32)
@@ -497,7 +501,8 @@ def test_not():
 
     result_arr = np.array([False, False], dtype=np.bool)
     result.write(util.numpy_to_c(result_arr), 0, 2)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, 2)
 
     a_arr = np.array([True, False], dtype=np.bool)
@@ -522,7 +527,9 @@ def test_sum():
 
     result_arr = np.array([0], dtype=np.float32)
     result.write(util.numpy_to_c(result_arr), 0, 4)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.get_performance_data()
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, 4)
 
     a_arr = np.array([1, 2, 3, 4], dtype=np.float32)
@@ -547,7 +554,8 @@ def test_reshape():
 
     result_arr = np.array([[0, 0], [0, 0], [0, 0]], dtype=np.float32)
     result.write(util.numpy_to_c(result_arr), 0, 24)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, 24)
 
     a_arr = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.float32)
@@ -573,7 +581,8 @@ def test_convert():
 
     result_arr = np.array([False, False, False], dtype=np.bool)
     result.write(util.numpy_to_c(result_arr), 0, 3)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, 3)
 
     a_arr = np.array([1, 5, 3], dtype=np.float32)
@@ -590,7 +599,8 @@ def test_convert():
 
     result_arr = np.array([0, 0, 0], dtype=np.int32)
     result.write(util.numpy_to_c(result_arr), 0, 12)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, 12)
 
     a_arr = np.array([1.4, 5.4, 3.9], dtype=np.float32)
@@ -614,7 +624,8 @@ def test_broadcast():
 
     result_arr = np.zeros((3, 3), dtype=np.float32)
     result.write(util.numpy_to_c(result_arr), 0, 36)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, 36)
 
     a_arr = np.array([[0], [0], [0]], dtype=np.float32)
@@ -636,7 +647,8 @@ def test_constant():
 
     result_arr = np.zeros((3, 3), dtype=np.float32)
     result.write(util.numpy_to_c(result_arr), 0, 36)
-    backend.call(backend.compile(function), [result], [])
+    handle = backend.compile(function)
+    handle.call([result], [])
     result.read(util.numpy_to_c(result_arr), 0, 36)
 
     result_arr_ref = np.arange(9).reshape(3, 3)
@@ -659,7 +671,8 @@ def test_onehot():
 
     result_arr = np.zeros((3, 3), dtype=np.float32)
     result.write(util.numpy_to_c(result_arr), 0, 36)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, 36)
 
     a_arr = np.array([1, 0, 2])
@@ -691,7 +704,8 @@ def test_concat():
 
     result_arr = np.zeros(6, dtype=np.float32).reshape(3, 2)
     result.write(util.numpy_to_c(result_arr), 0, 24)
-    backend.call(backend.compile(function), [result], [a, b, c])
+    handle = backend.compile(function)
+    handle.call([result], [a, b, c])
     result.read(util.numpy_to_c(result_arr), 0, 24)
 
     a_arr = np.array([[1, 2]], dtype=np.float32)
@@ -742,7 +756,8 @@ def test_select():
 
     result_arr = np.array([[0, 0]], dtype=np.float32)
     result.write(util.numpy_to_c(result_arr), 0, 8)
-    backend.call(backend.compile(function), [result], [a, b, c])
+    handle = backend.compile(function)
+    handle.call([result], [a, b, c])
     result.read(util.numpy_to_c(result_arr), 0, 8)
 
     result_arr_ref = np.array([[5, 8]])
@@ -773,7 +788,8 @@ def test_slice():
 
     result_arr = np.zeros(16, dtype=np.float32).reshape(4, 4)
     result.write(util.numpy_to_c(result_arr), 0, 16*4)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, 64)
 
     result_arr_ref = input_arr[lower_bounds[0]:upper_bounds[0], lower_bounds[1]:upper_bounds[1]]
@@ -792,7 +808,8 @@ def test_slice():
     result_arr = np.zeros(8, dtype=np.float32).reshape(4, 2)
 
     result.write(util.numpy_to_c(result_arr), 0, 8*4)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, 32)
 
     result_arr_ref = result_arr_ref[::strides[0], ::strides[1]]
@@ -826,7 +843,8 @@ def test_replace_slice():
 
     result_arr = np.zeros(24, dtype=np.float32).reshape(6, 4)
     result.write(util.numpy_to_c(result_arr), 0, 24*4)
-    backend.call(backend.compile(function), [result], [a, b])
+    handle = backend.compile(function)
+    handle.call([result], [a, b])
     result.read(util.numpy_to_c(result_arr), 0, 24*4)
 
     result_arr_ref = np.copy(input_arr_a)
@@ -844,7 +862,8 @@ def test_replace_slice():
                         parameter_list, 'test')
     backend = Backend.create(pytest.config.getoption('backend'))
 
-    backend.call(backend.compile(function), [result], [a, b])
+    handle = backend.compile(function)
+    handle.call([result], [a, b])
     result.read(util.numpy_to_c(result_arr), 0, 24*4)
 
     result_arr_ref = np.copy(input_arr_a)
@@ -875,7 +894,8 @@ def test_max_pool():
 
     result_arr = np.zeros(8, dtype=np.float32).reshape(1, 1, 8)
     result.write(util.numpy_to_c(result_arr), 0, 8*4)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, 32)
 
     result_arr_ref = (np.arange(8) + 2).reshape(1, 1, 8)
@@ -892,7 +912,8 @@ def test_max_pool():
     result_arr = np.zeros(size, dtype=np.float32).reshape(1, 1, size)
 
     result.write(util.numpy_to_c(result_arr), 0, size*4)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, size*4)
 
     result_arr_ref = ((np.arange(size) + 1) * 2).reshape(1, 1, size)
@@ -917,7 +938,8 @@ def test_max_pool():
 
     result_arr = np.zeros(64, dtype=np.float32).reshape(1, 1, 8, 8)
     result.write(util.numpy_to_c(result_arr), 0, 8*8*4)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, 8*8*4)
 
     result_arr_ref = ((np.arange(100).reshape(10, 10))[2:, 2:]).reshape(1, 1, 8, 8)
@@ -934,7 +956,8 @@ def test_max_pool():
     result_arr = np.zeros(size*size, dtype=np.float32).reshape(1, 1, size, size)
 
     result.write(util.numpy_to_c(result_arr), 0, size*size*4)
-    backend.call(backend.compile(function), [result], [a])
+    handle = backend.compile(function)
+    handle.call([result], [a])
     result.read(util.numpy_to_c(result_arr), 0, size*size*4)
 
     result_arr_ref = ((np.arange(100).reshape(10, 10))[2::2, 2::2]).reshape(1, 1, size, size)
@@ -1014,7 +1037,8 @@ def test_convolution():
 
     result = backend.create_tensor(element_type, Shape([1, 1, 14, 14]))
     result.write(util.numpy_to_c(result_arr), 0, 14*14*4)
-    backend.call(backend.compile(function), [result], [a, b])
+    handle = backend.compile(function)
+    handle.call([result], [a, b])
     result.read(util.numpy_to_c(result_arr), 0, 14*14*4)
 
     result_arr_ref = convolution2d(image_arr[0][0], filter_arr[0][0]).reshape(1, 1, 14, 14)
@@ -1048,7 +1072,8 @@ def test_convolution_with_strides():
     result_arr = np.zeros(16, dtype=np.float32).reshape(1, 1, 4, 4)
     result = backend.create_tensor(element_type, Shape([1, 1, 4, 4]))
     result.write(util.numpy_to_c(result_arr), 0, 4*4*4)
-    backend.call(backend.compile(function), [result], [a, b])
+    handle = backend.compile(function)
+    handle.call([result], [a, b])
 
     result.read(util.numpy_to_c(result_arr), 0, 4*4*4)
     result_arr_ref = convolution2d(image_arr[0][0], filter_arr[0][0], strides).reshape(1, 1, 4, 4)
@@ -1082,7 +1107,8 @@ def test_convolution_with_filter_dilation():
     result_arr = np.zeros(36, dtype=np.float32).reshape(1, 1, 6, 6)
     result = backend.create_tensor(element_type, Shape([1, 1, 6, 6]))
     result.write(util.numpy_to_c(result_arr), 0, 6*6*4)
-    backend.call(backend.compile(function), [result], [a, b])
+    handle = backend.compile(function)
+    handle.call([result], [a, b])
 
     result.read(util.numpy_to_c(result_arr), 0, 6*6*4)
     result_arr_ref = convolution2d(image_arr[0][0], filter_arr[0][0], strides,
@@ -1122,7 +1148,8 @@ def test_convolution_with_padding():
     result_arr = np.zeros(36, dtype=np.float32).reshape(1, 1, 6, 6)
     result = backend.create_tensor(element_type, Shape([1, 1, 6, 6]))
     result.write(util.numpy_to_c(result_arr), 0, 6*6*4)
-    backend.call(backend.compile(function), [result], [a, b])
+    handle = backend.compile(function)
+    handle.call([result], [a, b])
 
     result.read(util.numpy_to_c(result_arr), 0, 6*6*4)
     result_arr_ref = convolution2d(image_arr[0][0], filter_arr[0][0], strides,
@@ -1160,7 +1187,8 @@ def test_convolution_with_padding():
     result_arr = np.zeros(81, dtype=np.float32).reshape(1, 1, 9, 9)
     result = backend.create_tensor(element_type, Shape([1, 1, 9, 9]))
     result.write(util.numpy_to_c(result_arr), 0, 9*9*4)
-    backend.call(backend.compile(function), [result], [a, b])
+    handle = backend.compile(function)
+    handle.call([result], [a, b])
 
     result.read(util.numpy_to_c(result_arr), 0, 9*9*4)
     result_arr_ref = convolution2d(image_arr[0][0], filter_arr[0][0], strides,
@@ -1201,7 +1229,8 @@ def test_convolution_with_data_dilation():
     result_arr = np.zeros(17*17, dtype=np.float32).reshape(1, 1, 17, 17)
     result = backend.create_tensor(element_type, Shape([1, 1, 17, 17]))
     result.write(util.numpy_to_c(result_arr), 0, 17*17*4)
-    backend.call(backend.compile(function), [result], [a, b])
+    handle = backend.compile(function)
+    handle.call([result], [a, b])
 
     result.read(util.numpy_to_c(result_arr), 0, 17*17*4)
     result_arr_ref = convolution2d(image_arr[0][0], filter_arr[0][0], strides,
@@ -1248,7 +1277,8 @@ def test_convolutionBackpropData():
     result_arr = np.zeros(10*10, dtype=np.float32).reshape(1, 1, 10, 10)
     result = backend.create_tensor(element_type, Shape([1, 1, 10, 10]))
     result.write(util.numpy_to_c(result_arr), 0, 10*10*4)
-    backend.call(backend.compile(function), [result], [a, b])
+    handle = backend.compile(function)
+    handle.call([result], [a, b])
 
     result.read(util.numpy_to_c(result_arr), 0, 10*10*4)
     result_arr_ref = np.array(
@@ -1303,7 +1333,8 @@ def test_convolutionBackpropFilters():
     result_arr = np.zeros(3*3, dtype=np.float32).reshape(1, 1, 3, 3)
     result = backend.create_tensor(element_type, Shape([1, 1, 3, 3]))
     result.write(util.numpy_to_c(result_arr), 0, 3*3*4)
-    backend.call(backend.compile(function), [result], [a, b])
+    handle = backend.compile(function)
+    handle.call([result], [a, b])
 
     result.read(util.numpy_to_c(result_arr), 0, 3*3*4)
     result_arr_ref = np.array(