Bani / merge NGTF-2442 & NGTF-2515 into r0.19

ngraph_bridge/ngraph_utils.h

@@ -128,32 +128,34 @@ Status ValuesFromConstNode(const NodeDef& node,
       n_elements *= shape.dim(i).size();
     }
     values->resize(n_elements);
+    auto val_lastsaved = (T)0;  // cast
     for (auto i = 0; i < n_elements; i++) {
       auto& tensor = node.attr().at("value").tensor();
       auto dt = node.attr().at("dtype").type();
+      int64 val_size = 0;
+      auto val_i = (T)0;  // cast
       switch (dt) {
         // TODO(amprocte/NGRAPH-2502): there are more element types to support
         // here
         case DT_INT32:
-          (*values)[i] = (tensor.int_val_size() == 1 ? tensor.int_val()[0]
-                                                     : tensor.int_val()[i]);
+          val_size = tensor.int_val_size();
+          if (val_size > i) val_i = tensor.int_val()[i];
           break;
         case DT_INT64:
-          (*values)[i] = (tensor.int64_val_size() == 1 ? tensor.int64_val()[0]
-                                                       : tensor.int64_val()[i]);
+          val_size = tensor.int64_val_size();
+          if (val_size > i) val_i = tensor.int64_val()[i];
           break;
         case DT_FLOAT:
-          (*values)[i] = (tensor.float_val_size() == 1 ? tensor.float_val()[0]
-                                                       : tensor.float_val()[i]);
+          val_size = tensor.float_val_size();
+          if (val_size > i) val_i = tensor.float_val()[i];
           break;
         case DT_BOOL:
-          (*values)[i] = (tensor.bool_val_size() == 1 ? tensor.bool_val()[0]
-                                                      : tensor.bool_val()[i]);
+          val_size = tensor.bool_val_size();
+          if (val_size > i) val_i = tensor.bool_val()[i];
           break;
         case DT_DOUBLE:
-          (*values)[i] =
-              (tensor.double_val_size() == 1 ? tensor.double_val()[0]
-                                             : tensor.double_val()[i]);
+          val_size = tensor.double_val_size();
+          if (val_size > i) val_i = tensor.double_val()[i];
           break;
         default:
           NGRAPH_VLOG(0)
@@ -165,6 +167,14 @@ Status ValuesFromConstNode(const NodeDef& node,
                                        DataType_Name(dt),
                                        " on an empty tensor");
       }
+      if (val_size == 0) {
+        return errors::InvalidArgument("Empty values vector");
+      } else if (i < val_size) {
+        (*values)[i] = val_i;
+        val_lastsaved = val_i;
+      } else {
+        (*values)[i] = val_lastsaved;
+      }
     }
   } else {
     values->resize(tensor_content_size / sizeof(VecT));

test/python/test_const.py

@@ -0,0 +1,95 @@
+# ==============================================================================
+#  Copyright 2018-2019 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.
+# ==============================================================================
+"""nGraph TensorFlow bridge Const operation test
+
+"""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import pytest
+
+import tensorflow as tf
+import os
+
+from common import NgraphTest
+
+# Uncomment for debugging; Also add -s in command like, e.g.
+# (venv-tf-py3) [build_cmake]$
+# NGRAPH_TF_LOG_PLACEMENT=1 NGRAPH_TF_VLOG_LEVEL=6 pytest -s -k test_const_scalarval ../test/python/test_const.py
+import logging
+logging.basicConfig(level=logging.DEBUG)
+
+
+class TestConstOperations(NgraphTest):
+
+    def test_const_listvals(self):
+        zz = tf.constant([1, 2, 3, 4, 5, 6], dtype=float, shape=[2, 3])
+
+        def run_test(sess):
+            return sess.run(zz)
+
+        assert (
+            self.with_ngraph(run_test) == self.without_ngraph(run_test)).all()
+
+    def test_const_listvals_2(self):
+        zz = tf.constant([[1, 2, 3], [4, 5, 6]], dtype=float, shape=[2, 3])
+
+        def run_test(sess):
+            return sess.run(zz)
+
+        assert (
+            self.with_ngraph(run_test) == self.without_ngraph(run_test)).all()
+
+    def test_const_scalarval(self):
+        zz = tf.constant(-3, dtype=float, shape=[2, 3])
+
+        def run_test(sess):
+            return sess.run(zz)
+
+        assert (
+            self.with_ngraph(run_test) == self.without_ngraph(run_test)).all()
+
+    def test_const_lastfill(self):
+        zz = tf.constant([1, 2], dtype=float, shape=[2, 3])
+
+        def run_test(sess):
+            return sess.run(zz)
+
+        assert (
+            self.with_ngraph(run_test) == self.without_ngraph(run_test)).all()
+
+    def test_const_empty(self):
+        log = logging.getLogger('test_const_empty')
+        zz = tf.constant([], dtype=float, shape=[2, 3])
+
+        def run_test(sess):
+            log.debug('Invoking sess.run(zz)')
+            return sess.run(zz)
+
+        # Ideally we want same behavior for both TF & NG, but for now we are deviating,
+        # NGraph will throw error, but TF will fill in zeros
+        # assert (
+        #    self.with_ngraph(run_test) == self.without_ngraph(run_test)).all()
+
+        # Test to see that exception is raised in NG
+        try:
+            # This test is expected to fail currently
+            res = self.with_ngraph(run_test)
+            assert False, 'Failed, expected test to raise error'
+        except:
+            log.debug('Passed, expected NG to raise error...')
+            assert True