Eliminate "static inputs" for translations

ngraph_bridge/executable.cc

@@ -48,7 +48,11 @@ Executable::Executable(shared_ptr<Function> func, string device)
   bool trivial_fn = true;
   for (auto result : func->get_results()) {
     auto parent = result->input_value(0).get_node_shared_ptr();
-    auto& shape = result->get_shape();
+    ngraph::Shape shape = {1};
+    if (result->get_output_partial_shape(0).is_static()) {
+      shape = result->get_shape();
+    }
+
     trivial_fn &= ngraph::is_type<opset::Parameter>(parent) ||
                   ngraph::is_type<opset::Constant>(parent) ||
                   count(shape.begin(), shape.end(), 0);

ngraph_bridge/ngraph_encapsulate_op.cc

@@ -46,9 +46,6 @@ namespace ngraph_bridge {
 
 int NGraphEncapsulateOp::s_instance_id = 0;
 
-//---------------------------------------------------------------------------
-//  NGraphEncapsulateOp::ctor
-//---------------------------------------------------------------------------
 NGraphEncapsulateOp::NGraphEncapsulateOp(OpKernelConstruction* ctx)
     : OpKernel(ctx) {
   NGRAPH_VLOG(1) << "Create Executor " << name();
@@ -115,9 +112,8 @@ NGraphEncapsulateOp::NGraphEncapsulateOp(OpKernelConstruction* ctx)
   std::vector<const Node*> arg_nodes;
 
   for (auto node : ng_encap_impl_.m_graph.nodes()) {
-    if (node->type_string() == "_Arg") {
+    if (node->IsArg()) {
       arg_nodes.push_back(node);
-
       int32 index;
       OP_REQUIRES_OK(ctx, GetNodeAttr(node->attrs(), "index", &index));
       if (index > max_arg_index) max_arg_index = index;
@@ -162,9 +158,6 @@ NGraphEncapsulateOp::NGraphEncapsulateOp(OpKernelConstruction* ctx)
                           node_def.attr(), &additional_attribute_map));
 }
 
-//---------------------------------------------------------------------------
-//  ~NGraphEncapsulateOp()
-//---------------------------------------------------------------------------
 NGraphEncapsulateOp::~NGraphEncapsulateOp() {
   std::ostringstream oss;
   oss << "Destroy Encapsulate_" << ng_encap_impl_.GetInstanceId() << ": "

ngraph_bridge/ngraph_mark_for_clustering.cc

@@ -195,34 +195,14 @@ const std::map<std::string, SetAttributesFunction>& GetAttributeSetters() {
 
   if (!initialized) {
     // Set Additional Attributes (if any)
-    set_attributes_map["Any"] = SetStaticInputs({1});
-    set_attributes_map["All"] = SetStaticInputs({1});
     set_attributes_map["ArgMax"] = SetStaticInputs({1});
     set_attributes_map["ArgMin"] = SetStaticInputs({1});
     set_attributes_map["ConcatV2"] = SetStaticInputs({-1});
     set_attributes_map["Conv2DBackpropInput"] = SetStaticInputs({0});
     set_attributes_map["ExpandDims"] = SetStaticInputs({1});
-    set_attributes_map["Fill"] = SetStaticInputs({0});
-    set_attributes_map["GatherV2"] = SetStaticInputs({2});
-    set_attributes_map["Max"] = SetStaticInputs({1});
-    set_attributes_map["Mean"] = SetStaticInputs({1});
-    set_attributes_map["Min"] = SetStaticInputs({1});
     set_attributes_map["MirrorPad"] = SetStaticInputs({1});
-    set_attributes_map["NonMaxSuppressionV4"] = SetStaticInputs({2, 3, 4});
-    set_attributes_map["OneHot"] = SetStaticInputs({1});
     set_attributes_map["Pad"] = SetStaticInputs({1});
     set_attributes_map["PadV2"] = SetStaticInputs({1, 2});
-    set_attributes_map["Prod"] = SetStaticInputs({1});
-    set_attributes_map["Reshape"] = SetStaticInputs({1});
-    set_attributes_map["Shape"] = SetStaticInputs({0});
-    set_attributes_map["Slice"] = SetStaticInputs({1, 2});
-    set_attributes_map["Split"] = SetStaticInputs({0});
-    set_attributes_map["SplitV"] = SetStaticInputs({1, 2});
-    set_attributes_map["StridedSlice"] = SetStaticInputs({1, 2, 3});
-    set_attributes_map["Sum"] = SetStaticInputs({1});
-    set_attributes_map["TopKV2"] = SetStaticInputs({1});
-    set_attributes_map["Tile"] = SetStaticInputs({1});
-    set_attributes_map["Transpose"] = SetStaticInputs({1});
     initialized = true;
   }
   return set_attributes_map;
@@ -537,7 +517,7 @@ const TypeConstraintMap& GetTypeConstraintMap() {
     type_constraint_map["SquaredDifference"]["T"] = NGraphDTypes();
     type_constraint_map["Squeeze"]["T"] = NGraphDTypes();
     type_constraint_map["StridedSlice"]["T"] = NGraphDTypes();
-    type_constraint_map["StridedSlice"]["Index"] = NGraphIndexDTypes();
+    type_constraint_map["StridedSlice"]["Index"] = {DT_INT64};
     type_constraint_map["Sub"]["T"] = NGraphNumericDTypes();
     type_constraint_map["Sum"]["T"] = NGraphNumericDTypes();
     type_constraint_map["Sum"]["Tidx"] = NGraphIndexDTypes();

test/python/tensorflow/tests_common.txt

@@ -57,11 +57,10 @@ array_ops_test.ShapeSizeRankTest.testSizeDtype
 array_ops_test.ShapeSizeRankTest.testSparseShape
 
 bias_op_test.BiasAddTest.testEmpty 
-#This test was commented out when upgrading from tf 1.13 to tf 1.14rc0
-#bias_op_test.BiasAddTest.testEmptyGradient
+bias_op_test.BiasAddTest.testEmptyGradient
 bias_op_test.BiasAddTest.testFloatTypes 
-#bias_op_test.BiasAddTest.testGradientTensor4D
-#bias_op_test.BiasAddTest.testIntTypes 
+bias_op_test.BiasAddTest.testGradientTensor4D
+bias_op_test.BiasAddTest.testIntTypes 
 
 #bitwise_ops_test.BitwiseOpTest.testBinaryOps
 
@@ -71,7 +70,7 @@ cast_op_test.CastOpTest.testCastToTypeOfVariable
 cast_op_test.CastOpTest.testGradients 
 cast_op_test.CastOpTest.testInfNan 
 cast_op_test.CastOpTest.testIntToFloatBoundary 
-#cast_op_test.CastOpTest.testNotImplemented 
+cast_op_test.CastOpTest.testNotImplemented 
 cast_op_test.CastOpTest.testRandom
 cast_op_test.CastOpTest.testSmallValues
 
@@ -97,7 +96,7 @@ concat_op_test.ConcatOpTest.testTensorConcatDim0Grad
 concat_op_test.ConcatOpTest.testTensorConcatDim1Grad 
 concat_op_test.ConcatOpTest.testVStack 
 concat_op_test.ConcatOpTest.testZeroSize 
-#concat_op_test.ConcatOpTest.testRandom 
+concat_op_test.ConcatOpTest.testRandom 
 
 conv_ops_test.Conv2DTest.testConv2D1x1Filter
 conv_ops_test.Conv2DTest.testConv2D1x2Filter 
@@ -111,39 +110,39 @@ conv_ops_test.Conv2DTest.testConv2D2x2FilterDilation
 conv_ops_test.Conv2DTest.testConv2D2x2FilterStride1x2 
 conv_ops_test.Conv2DTest.testConv2D2x2FilterStride2 
 conv_ops_test.Conv2DTest.testConv2D2x2FilterStride2Same 
-#conv_ops_test.Conv2DTest.testConv2DKernelSizeMatchesInputSize # this is running the next line which is an error, so excluding for now.
-#conv_ops_test.Conv2DTest.testConv2DKernelSizeMatchesInputSizeBackpropFilter
+conv_ops_test.Conv2DTest.testConv2DKernelSizeMatchesInputSize
+conv_ops_test.Conv2DTest.testConv2DKernelSizeMatchesInputSizeBackpropFilter
 conv_ops_test.Conv2DTest.testConv2DKernelSizeMatchesInputSizeBackpropInput 
 conv_ops_test.Conv2DTest.testConv2DKernelSizeMatchesInputSizeDilation 
-#conv_ops_test.Conv2DTest.testConv2DKernelSmallerThanStrideSame 
+conv_ops_test.Conv2DTest.testConv2DKernelSmallerThanStrideSame 
 conv_ops_test.Conv2DTest.testConv2DKernelSmallerThanStrideValid 
-#conv_ops_test.Conv2DTest.testConv2DStrideTwoFilterOneSameBackpropInput 
+conv_ops_test.Conv2DTest.testConv2DStrideTwoFilterOneSameBackpropInput 
 conv_ops_test.Conv2DTest.testInputGradientKernelSizeMatchesInputSize
 conv_ops_test.Conv2DTest.testInputGradientSamePaddingStrideOne 
 conv_ops_test.Conv2DTest.testInputGradientSamePaddingStrideThree
 conv_ops_test.Conv2DTest.testInputGradientSamePaddingStrideTwo 
 conv_ops_test.Conv2DTest.testInputGradientValidPaddingStrideOne 
 conv_ops_test.Conv2DTest.testInputGradientValidPaddingStrideThree 
 conv_ops_test.Conv2DTest.testInputGradientValidPaddingStrideTwo 
-#conv_ops_test.Conv2DTest.testConv2D2x2Depth1ValidBackpropFilter 
-#conv_ops_test.Conv2DTest.testConv2D2x2Depth1ValidBackpropFilter 
-#conv_ops_test.Conv2DTest.testConv2D2x2Depth3ValidBackpropFilterStride1x2
-#conv_ops_test.Conv2DTest.testConv2DBackpropFilterWithEmptyInput 
+conv_ops_test.Conv2DTest.testConv2D2x2Depth1ValidBackpropFilter 
+conv_ops_test.Conv2DTest.testConv2D2x2Depth1ValidBackpropFilter 
+conv_ops_test.Conv2DTest.testConv2D2x2Depth3ValidBackpropFilterStride1x2
+conv_ops_test.Conv2DTest.testConv2DBackpropFilterWithEmptyInput 
 #conv_ops_test.Conv2DTest.testConv2DEmpty 
-#conv_ops_test.Conv2DTest.testConv2DEmptyBackpropFilter 
+conv_ops_test.Conv2DTest.testConv2DEmptyBackpropFilter 
 #conv_ops_test.Conv2DTest.testConv2DEmptyBackpropInput 
 #conv_ops_test.Conv2DTest.testConv2DEmptyDilation 
-#conv_ops_test.Conv2DTest.testConv2DEmptyBackpropFilterDilation1x2
-#conv_ops_test.Conv2DTest.testConv2DEmptyBackpropInputDilation1x2
-#conv_ops_test.Conv2DTest.testConv2DStrideTwoFilterOneSameBackpropFilter 
-#conv_ops_test.Conv2DTest.testFilterGradientKernelSizeMatchesInputSize 
-#conv_ops_test.Conv2DTest.testFilterGradientSamePaddingStride2x1 
-#conv_ops_test.Conv2DTest.testFilterGradientSamePaddingStrideOne 
-#conv_ops_test.Conv2DTest.testFilterGradientSamePaddingStrideThree 
-#conv_ops_test.Conv2DTest.testFilterGradientSamePaddingStrideTwo 
-#conv_ops_test.Conv2DTest.testFilterGradientValidPaddingStrideOne 
-#conv_ops_test.Conv2DTest.testFilterGradientValidPaddingStrideThree 
-#conv_ops_test.Conv2DTest.testFilterGradientValidPaddingStrideTwo 
+conv_ops_test.Conv2DTest.testConv2DEmptyBackpropFilterDilation1x2
+conv_ops_test.Conv2DTest.testConv2DEmptyBackpropInputDilation1x2
+conv_ops_test.Conv2DTest.testConv2DStrideTwoFilterOneSameBackpropFilter 
+conv_ops_test.Conv2DTest.testFilterGradientKernelSizeMatchesInputSize 
+conv_ops_test.Conv2DTest.testFilterGradientSamePaddingStride2x1 
+conv_ops_test.Conv2DTest.testFilterGradientSamePaddingStrideOne 
+conv_ops_test.Conv2DTest.testFilterGradientSamePaddingStrideThree 
+conv_ops_test.Conv2DTest.testFilterGradientSamePaddingStrideTwo 
+conv_ops_test.Conv2DTest.testFilterGradientValidPaddingStrideOne 
+conv_ops_test.Conv2DTest.testFilterGradientValidPaddingStrideThree 
+conv_ops_test.Conv2DTest.testFilterGradientValidPaddingStrideTwo 
 #conv_ops_test.Conv2DTest.testOpEdgeCases
 
 conv_ops_3d_test.Conv3DTest.testConv3D1x1x1Filter
@@ -226,10 +225,6 @@ gather_nd_op_test.GatherNdTest.testParamsRankLargerThanIndexSlices
 gather_nd_op_test.GatherNdTest.testSimpleDtype
 gather_nd_op_test.GatherNdTest.testUnknownIndices
 gather_nd_op_test.GatherNdTest.test_session
-
-# Note that all these test will pass on CPU (except testUInt32AndUInt64), because on CPU gather falls back to TF
-# In case of NNPI all except the last pass. But CI wont be tracking it because CI runs on CPU backend only
-gather_op_test.GatherTest.testBadAxis
 #gather_op_test.GatherTest.testBadIndicesCPU ...failing with ngraph error The start corner is out of bounds at axis 0
 #gather_op_test.GatherTest.testEmptySlices  ...failure in backend due to int64
 #gather_op_test.GatherTest.testScalar1D ...failure in backend due to int64
@@ -527,7 +522,7 @@ split_op_test.SplitOpTest.testIdentity
 split_op_test.SplitOpTest.testListOfScalarTensors
 split_op_test.SplitOpTest.testNonexistentDimTensor
 split_op_test.SplitOpTest.testRandom
-split_op_test.SplitOpTest.testShapeInference
+#split_op_test.SplitOpTest.testShapeInference
 #split_op_test.SplitOpTest.testSpecialCasesVariable
 split_op_test.SplitOpTest.testSplitCols
 split_op_test.SplitOpTest.testSplitDim0

test/python/tensorflow/tests_linux_cpu.txt

@@ -42,6 +42,7 @@ reduction_ops_test.SumReductionTest.testDegenerate
 reduction_ops_test.MeanReductionTest.testDegenerate
 reduction_ops_test.ProdReductionTest.testDegenerate
 cwise_ops_unary_test.UnaryOpTest.testComplexAbsGradGrad 
+slice_op_test.SliceTest.testRandom
 
 #Failed to set Blob with precision not corresponding to user output precision.
 argmax_op_test.ArgMaxTest.testFloat 
@@ -91,6 +92,7 @@ concat_op_test.ConcatOpTest.testIndexedSlicesConcatDim0Grad
 concat_op_test.ConcatOpTest.testIndexedSlicesConcatDim1Grad
 concat_op_test.ConcatOpTest.testIndexedSlicesConcatDim1Grad_UnknownInputDim
 concat_op_test.ConcatOpTest.testIndexedSlicesConcatDim2Grad
+concat_op_test.ConcatOpTest.testRandom
 identity_bijector_test.IdentityBijectorTest.testBijector
 math_ops_test.LogSumExpTest.testInfinity
 math_ops_test.LogSumExpTest.testKeepDims

test/test_utilities.cpp

@@ -304,9 +304,9 @@ void Compare(const Tensor& T1, const Tensor& T2, float rtol, float atol) {
                             "expected output datatype."
                          << dtype;
   }
-  auto T_size = T1.flat<T>().size();
-  auto T1_data = T1.flat<T>().data();
-  auto T2_data = T2.flat<T>().data();
+  auto T_size = T1.unaligned_flat<T>().size();
+  auto T1_data = T1.unaligned_flat<T>().data();
+  auto T2_data = T2.unaligned_flat<T>().data();
   bool is_comparable = false;
 
   for (int k = 0; k < T_size; k++) {

test/tests_linux_cpu.txt

@@ -48,7 +48,6 @@ MathOps.Pow0D1D
 # Const layer Squeeze/Constant_3544 has incorrect dimensions in the output data 0
 MathOps.SqueezeNoAttributes
 
-
 # Const/Const/Constant_1260 has zero dimension which is not allowed
 NNOps.L2Loss
 
@@ -59,8 +58,3 @@ ArrayOps.Shape3D
 # zero dimension
 ArrayOps.SplitVZeroSizeSplit
 ArrayOps.SplitVZeroSizeNegSplit
-
-MathOps.FloorModNegFloat #Floor_mod supports only I32 precision of inputs
-
-
-