Fix using numpy scalars in Python API (#2520)

* fixed numpy scalars

* reverted tests changes

* python style fixed

diff --git a/inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api.pyx b/inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api.pyx
index 4da22a3..cea04fc 100644 (file)
--- a/inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api.pyx
+++ b/inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api.pyx
@@ -1614,6 +1614,8 @@ cdef class BlobBuffer:
         cdef SizeVector shape
         if len(representation_shape) == 0:
             shape = desc.getDims()
+            if layout_int_to_str_map[desc.getLayout()] == 'SCALAR':
+                shape = [1]
         else:
             shape = representation_shape
         cdef Py_ssize_t itemsize = deref(ptr).element_size()

diff --git a/inference-engine/ie_bridges/python/tests/test_Blob.py b/inference-engine/ie_bridges/python/tests/test_Blob.py
index a70c421..4a382c5 100644 (file)
--- a/inference-engine/ie_bridges/python/tests/test_Blob.py
+++ b/inference-engine/ie_bridges/python/tests/test_Blob.py
@@ -110,6 +110,15 @@ def test_write_to_buffer_int64():
     assert np.array_equal(blob.buffer, ones_arr)
 
 
+def test_write_numpy_scalar_int64():
+    tensor_desc = TensorDesc("I64", [], "SCALAR")
+    scalar = np.array(0, dtype=np.int64)
+    blob = Blob(tensor_desc, scalar)
+    scalar_to_write = np.array(1, dtype=np.int64)
+    blob.buffer[:] = scalar_to_write
+    assert np.array_equal(blob.buffer, np.atleast_1d(scalar_to_write))
+
+
 def test_incompatible_array_and_td():
     tensor_desc = TensorDesc("FP32", [1, 3, 127, 127], "NCHW")
     array = np.zeros(shape=(1, 2, 3, 4), dtype=np.float32)

diff --git a/ngraph/python/tests/__init__.py b/ngraph/python/tests/__init__.py
index 4c78909..d926461 100644 (file)
--- a/ngraph/python/tests/__init__.py
+++ b/ngraph/python/tests/__init__.py
@@ -74,8 +74,6 @@ xfail_issue_35911 = xfail_test(reason="Assertion error: Pad model mismatch error
 xfail_issue_35912 = xfail_test(reason="RuntimeError: Error of validate layer: B with type: "
                                       "Pad. Cannot parse parameter pads_end  from IR for layer B. "
                                       "Value -1,0 cannot be casted to int.")
-xfail_issue_35914 = xfail_test(reason="IndexError: too many indices for array: "
-                                      "array is 0-dimensional, but 1 were indexed")
 xfail_issue_35915 = xfail_test(reason="RuntimeError: Eltwise node with unsupported combination "
                                       "of input and output types")
 xfail_issue_35916 = xfail_test(reason="RuntimeError: Unsupported input dims count for layer Z")

diff --git a/ngraph/python/tests/test_onnx/test_backend.py b/ngraph/python/tests/test_onnx/test_backend.py
index e73f70a..db0fb74 100644 (file)
--- a/ngraph/python/tests/test_onnx/test_backend.py
+++ b/ngraph/python/tests/test_onnx/test_backend.py
@@ -34,7 +34,6 @@ from tests import (BACKEND_NAME,
                    xfail_issue_38086,
                    xfail_issue_38087,
                    xfail_issue_35923,
-                   xfail_issue_35914,
                    xfail_issue_36483,
                    xfail_issue_34323,
                    xfail_issue_35915,
@@ -214,19 +213,6 @@ tests_expected_to_fail = [
     (xfail_issue_35923,
         "OnnxBackendNodeModelTest.test_prelu_broadcast_cpu",
         "OnnxBackendNodeModelTest.test_prelu_example_cpu"),
-    (xfail_issue_35914,
-        "OnnxBackendNodeModelTest.test_dequantizelinear_cpu",
-        "OnnxBackendNodeModelTest.test_pow_bcast_scalar_cpu",
-        "OnnxBackendNodeModelTest.test_clip_example_cpu",
-        "OnnxBackendNodeModelTest.test_clip_inbounds_cpu",
-        "OnnxBackendNodeModelTest.test_clip_outbounds_cpu",
-        "OnnxBackendNodeModelTest.test_clip_default_int8_min_cpu",
-        "OnnxBackendNodeModelTest.test_clip_default_int8_max_cpu",
-        "OnnxBackendNodeModelTest.test_gemm_default_scalar_bias_cpu",
-        "OnnxBackendNodeModelTest.test_clip_cpu",
-        "OnnxBackendNodeModelTest.test_clip_default_max_cpu",
-        "OnnxBackendNodeModelTest.test_clip_default_min_cpu",
-        "OnnxBackendNodeModelTest.test_clip_splitbounds_cpu"),
     (xfail_issue_36483,
         "OnnxBackendNodeModelTest.test_ceil_cpu",
         "OnnxBackendNodeModelTest.test_ceil_example_cpu"),
@@ -347,7 +333,9 @@ tests_expected_to_fail = [
         "OnnxBackendNodeModelTest.test_and_bcast4v4d_cpu",
         "OnnxBackendNodeModelTest.test_argmin_no_keepdims_example_cpu",
         "OnnxBackendNodeModelTest.test_clip_default_int8_inbounds_cpu",
-        "OnnxBackendNodeModelTest.test_and2d_cpu"),
+        "OnnxBackendNodeModelTest.test_and2d_cpu",
+        "OnnxBackendNodeModelTest.test_clip_default_int8_min_cpu",
+        "OnnxBackendNodeModelTest.test_clip_default_int8_max_cpu"),
     (xfail_issue_38091,
         "OnnxBackendNodeModelTest.test_round_cpu",
         "OnnxBackendNodeModelTest.test_mvn_cpu",

diff --git a/ngraph/python/tests/test_onnx/test_ops_logical.py b/ngraph/python/tests/test_onnx/test_ops_logical.py
index c2202cc..246b52f 100644 (file)
--- a/ngraph/python/tests/test_onnx/test_ops_logical.py
+++ b/ngraph/python/tests/test_onnx/test_ops_logical.py
@@ -18,15 +18,15 @@ import onnx
 import pytest
 
 from tests.test_onnx.utils import run_node
-from tests import xfail_issue_35914, xfail_issue_35915
+from tests import xfail_issue_35915
 
 
 @pytest.mark.parametrize(
     "onnx_op, numpy_func, data_type",
     [
-        pytest.param("And", np.logical_and, np.bool, marks=xfail_issue_35914),
-        pytest.param("Or", np.logical_or, np.bool, marks=xfail_issue_35914),
-        pytest.param("Xor", np.logical_xor, np.bool, marks=xfail_issue_35914),
+        pytest.param("And", np.logical_and, np.bool),
+        pytest.param("Or", np.logical_or, np.bool),
+        pytest.param("Xor", np.logical_xor, np.bool),
         pytest.param("Equal", np.equal, np.int32, marks=xfail_issue_35915),
         pytest.param("Greater", np.greater, np.int32, marks=xfail_issue_35915),
         pytest.param("Less", np.less, np.int32, marks=xfail_issue_35915),