Sindhu/bfloat16 support (#399)

bazel/BUILD

@@ -44,6 +44,7 @@ cc_library(
         "ngraph_bridge/ngraph_partial_shapes.h",
         "ngraph_bridge/ngraph_prefetch_shared_data.h",
         "ngraph_bridge/ngraph_pipelined_tensors.h",
+        "ngraph_bridge/ngraph_register_stub_kernels.h",
         "ngraph_bridge/ngraph_rewrite_for_tracking.h",
         "ngraph_bridge/ngraph_tensor_manager.h",
         "ngraph_bridge/ngraph_timer.h",
@@ -89,6 +90,7 @@ cc_library(
         "ngraph_bridge/ngraph_mark_for_clustering.cc",
         "ngraph_bridge/ngraph_partial_shapes.cc",
         "ngraph_bridge/ngraph_pipelined_tensors.cc",
+        "ngraph_bridge/ngraph_register_stub_kernels.cc",
         "ngraph_bridge/ngraph_rewrite_for_tracking.cc",
         "ngraph_bridge/ngraph_tensor_manager.cc",
         "ngraph_bridge/ngraph_tracked_variable.cc",

ngraph_bridge/CMakeLists.txt

@@ -53,6 +53,7 @@ set(SRC
    ngraph_freshness_tracker.cc
    ngraph_mark_for_clustering.cc
    ngraph_partial_shapes.cc
+   ngraph_register_stub_kernels.cc   
    ngraph_rewrite_for_tracking.cc
    ngraph_rewrite_pass.cc
    ngraph_tensor_manager.cc

ngraph_bridge/enable_variable_ops/ngraph_variable_modifiers.cc

@@ -33,133 +33,27 @@
 #include "ngraph_bridge/ngraph_utils.h"
 #include "ngraph_bridge/ngraph_var.h"
 
+#include "ngraph_bridge/ngraph_register_stub_kernels.h"
+
 using namespace std;
 namespace ng = ngraph;
 
 namespace tensorflow {
 
 namespace ngraph_bridge {
-/* -------------------------------------------------
-//
-// NGraphApplyMomentumOp
-//
----------------------------------------------------*/
-
-class NGraphApplyMomentumOp : public OpKernel {
- private:
- public:
-  explicit NGraphApplyMomentumOp(OpKernelConstruction* context)
-      : OpKernel(context) {
-    OP_REQUIRES(context, false,
-                errors::Internal("This constructor should not get called",
-                                 name(), "\n"));
-  }
-
-  //---------------------------------------------------------------------------
-  //  ~NGraphApplyMomentumOp()
-  //---------------------------------------------------------------------------
-  ~NGraphApplyMomentumOp() override {}
-
-  // This will never be called
-  void Compute(OpKernelContext* context) override {
-    OP_REQUIRES(
-        context, false,
-        errors::Internal("This kernel should not get called", name(), "\n"));
-  }  // end of compute function
-};   // end of NGraphApplyGradientDescent class definition
-
-REGISTER_KERNEL_BUILDER(Name("NGraphApplyMomentum").Device(DEVICE_CPU),
-                        NGraphApplyMomentumOp);
-/* -------------------------------------------------
-//
-// NGraphApplyGradientDescentOp
-//
----------------------------------------------------*/
-
-class NGraphApplyGradientDescentOp : public OpKernel {
- private:
- public:
-  explicit NGraphApplyGradientDescentOp(OpKernelConstruction* context)
-      : OpKernel(context) {
-    OP_REQUIRES(context, false,
-                errors::Internal("This constructor should not get called",
-                                 name(), "\n"));
-  }
-
-  //---------------------------------------------------------------------------
-  //  ~NGraphApplyGradientDescentOp()
-  //---------------------------------------------------------------------------
-  ~NGraphApplyGradientDescentOp() override {}
-
-  // This will never be called
-  void Compute(OpKernelContext* context) override {
-    OP_REQUIRES(
-        context, false,
-        errors::Internal("This kernel should not get called", name(), "\n"));
-  }  // end of compute function
-};   // end of NGraphApplyGradientDescent class definition
-
-REGISTER_KERNEL_BUILDER(Name("NGraphApplyGradientDescent").Device(DEVICE_CPU),
-                        NGraphApplyGradientDescentOp);
-
-/* -------------------------------------------------
-//
-// NGraphAssignSubOp
-//
----------------------------------------------------*/
-
-// Computes *input[0] = *input[0] - input[1]
-class NGraphAssignSubOp : public OpKernel {
- private:
-  // bool use_exclusive_lock_; //TF op has this
-  ~NGraphAssignSubOp() override {}
-
- public:
-  explicit NGraphAssignSubOp(OpKernelConstruction* context)
-      : OpKernel(context) {
-    OP_REQUIRES(context, false,
-                errors::Internal("This constructor should not get called",
-                                 name(), "\n"));
-  }
-
-  void Compute(OpKernelContext* context) override {
-    OP_REQUIRES(
-        context, false,
-        errors::Internal("This kernel should not get called", name(), "\n"));
-  }
-};
-
-REGISTER_KERNEL_BUILDER(Name("NGraphAssignSub").Device(DEVICE_CPU),
-                        NGraphAssignSubOp);
-
-/* -------------------------------------------------
-//
-// NGraphAssignAddOp
-//
----------------------------------------------------*/
-
-// Computes *input[0] = *input[0] + input[1]
-class NGraphAssignAddOp : public OpKernel {
- public:
-  explicit NGraphAssignAddOp(OpKernelConstruction* context)
-      : OpKernel(context) {
-    OP_REQUIRES(context, false,
-                errors::Internal("This constructor should not get called",
-                                 name(), "\n"));
-  }
-
-  void Compute(OpKernelContext* context) override {
-    OP_REQUIRES(
-        context, false,
-        errors::Internal("This kernel should not get called", name(), "\n"));
-  }
-
- private:
-  ~NGraphAssignAddOp() override {}
-};
 
-REGISTER_KERNEL_BUILDER(Name("NGraphAssignAdd").Device(DEVICE_CPU),
-                        NGraphAssignAddOp);
+// Register NGraphOptimizers here
+// These Optimizer Ops are replaced by a TF computational subgraph
+// in ReplaceModifiers Rewrite Pass. Hence, these Stub Kernels/Op will never get
+// called
+
+// Keep them in alphabetical order
+REGISTER_NGRAPH_STUB_KERNEL("NGraphApplyGradientDescent");
+REGISTER_NGRAPH_STUB_KERNEL("NGraphApplyMomentum");
+REGISTER_NGRAPH_STUB_KERNEL(
+    "NGraphAssignAdd");  //*input[0] = *input[0] + input[1]
+REGISTER_NGRAPH_STUB_KERNEL(
+    "NGraphAssignSub");  //*input[0] = *input[0] - input[1]
 
 }  // namespace ngraph_bridge
 

ngraph_bridge/ngraph_register_stub_kernels.cc

@@ -0,0 +1,70 @@
+/*******************************************************************************
+ * Copyright 2019-2020 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.
+ *******************************************************************************/
+
+#include "tensorflow/core/framework/op.h"
+#include "tensorflow/core/framework/op_kernel.h"
+
+#include "ngraph_bridge/ngraph_register_stub_kernels.h"
+
+using namespace std;
+
+namespace tensorflow {
+
+namespace ngraph_bridge {
+
+/* -------------------------------------------------
+//
+// NGraphStubOp
+//
+---------------------------------------------------*/
+// Constructor
+NGStubOp::NGStubOp(OpKernelConstruction* context) : OpKernel(context) {
+  OP_REQUIRES(
+      context, false,
+      errors::Internal("The constructor for OpType ", type_string(),
+                       "should not get called. This Op is expected to have "
+                       "been encapsulated or replaced by other ops. Op Name: ",
+                       name(), "\n"));
+}
+// Compute
+void NGStubOp::Compute(OpKernelContext* context) {
+  OP_REQUIRES(
+      context, false,
+      errors::Internal("This kernel for OpType ", type_string(),
+                       "should not get called. This Op is expected to have "
+                       "been encapsulated or replaced by other ops. Op Name: ",
+                       name(), "\n"));
+}
+// Destructor
+NGStubOp::~NGStubOp() {}
+
+/* ------------------------------------------------- */
+
+// Register Bfloat Stub Kernels
+
+// TF Ops that work on bfloat DataType get assigned Device XLA_CPU
+// Since nGraph-bridge OPs work on TF DEVICE_CPU we are registering stub
+// bfloat16 kernels here. The expectation is when we register the stub kernels
+// for bfloat16 TF is going to assign DEVICE_CPU to the respective Ops and
+// we will encapsulate them
+// These Stub Kernels/Op will never get called
+
+// Keep them in alphabetical order
+REGISTER_NGRAPH_STUB_BFLOAT_KERNEL("Conv2D")
+
+}  // namespace ngraph_bridge
+
+}  // namespace tensorflow

ngraph_bridge/ngraph_register_stub_kernels.h

@@ -0,0 +1,56 @@
+/*******************************************************************************
+ * Copyright 2019-2020 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.
+ *******************************************************************************/
+#ifndef NGRAPH_TF_BRIDGE_REGISTER_STUB_KERNELS_H_
+#define NGRAPH_TF_BRIDGE_REGISTER_STUB_KERNELS_H_
+
+#include "tensorflow/core/framework/op.h"
+#include "tensorflow/core/framework/op_kernel.h"
+
+using namespace std;
+
+namespace tensorflow {
+
+namespace ngraph_bridge {
+
+/* -------------------------------------------------
+//
+// NGStubOp
+//
+---------------------------------------------------*/
+
+class NGStubOp : public OpKernel {
+ public:
+  explicit NGStubOp(OpKernelConstruction* context);
+
+  void Compute(OpKernelContext* context) override;
+
+ private:
+  ~NGStubOp() override;
+};
+
+#define REGISTER_NGRAPH_STUB_KERNEL(optype) \
+  REGISTER_KERNEL_BUILDER(Name(optype).Device(DEVICE_CPU), NGStubOp);
+
+#define REGISTER_NGRAPH_STUB_BFLOAT_KERNEL(optype)                   \
+  REGISTER_KERNEL_BUILDER(                                           \
+      Name(optype).Device(DEVICE_CPU).TypeConstraint<bfloat16>("T"), \
+      NGStubOp);
+
+}  // namespace ngraph_bridge
+
+}  // namespace tensorflow
+
+#endif  // NGRAPH_TF_BRIDGE_REGISTER_STUB_KERNELS_H_

ngraph_bridge/ngraph_utils.cc

@@ -223,6 +223,11 @@ Status TensorToStream(std::ostream& ostream, const Tensor& tensor) {
     case DT_BOOL:
       TensorDataToStream<bool>(ostream, n_elements, data);
       break;
+    case DT_BFLOAT16:
+      return errors::Internal(
+          "TensorToStream got data type bfloat16. No compatible standard C++ "
+          "data type.");
+      break;
     default:
       return errors::Internal("TensorToStream got unsupported data type ",
                               DataType_Name(tensor.dtype()));
@@ -272,6 +277,8 @@ Status TFDataTypeToNGraphElementType(DataType tf_dt,
       break;
     case DataType::DT_QINT32:
       *ng_et = ng::element::i32;
+    case DataType::DT_BFLOAT16:
+      *ng_et = ng::element::bf16;
       break;
     default:
       return errors::Unimplemented("Unsupported TensorFlow data type: ",
@@ -322,15 +329,16 @@ void print_node_histogram(const std::unordered_map<string, int>& histogram,
 
 const gtl::ArraySlice<DataType>& NGraphDTypes() {
   static gtl::ArraySlice<DataType> result{
-      DT_FLOAT,  DT_DOUBLE, DT_INT8,   DT_INT16, DT_INT32, DT_INT64, DT_UINT8,
-      DT_UINT16, DT_UINT32, DT_UINT64, DT_BOOL,  DT_QINT8, DT_QUINT8};
+      DT_FLOAT, DT_DOUBLE, DT_INT8,   DT_INT16,   DT_INT32,
+      DT_INT64, DT_UINT8,  DT_UINT16, DT_UINT32,  DT_UINT64,
+      DT_BOOL,  DT_QINT8,  DT_QUINT8, DT_BFLOAT16};
   return result;
 }
 
 const gtl::ArraySlice<DataType>& NGraphNumericDTypes() {
   static gtl::ArraySlice<DataType> result{
-      DT_FLOAT, DT_DOUBLE, DT_INT8,   DT_INT16,  DT_INT32,
-      DT_INT64, DT_UINT8,  DT_UINT16, DT_UINT32, DT_UINT64};
+      DT_FLOAT, DT_DOUBLE, DT_INT8,   DT_INT16,  DT_INT32,   DT_INT64,
+      DT_UINT8, DT_UINT16, DT_UINT32, DT_UINT64, DT_BFLOAT16};
   return result;
 }
 
@@ -358,7 +366,7 @@ const gtl::ArraySlice<DataType>& NGraphSupportedQuantizedDTypes() {
 }
 
 const gtl::ArraySlice<DataType>& NGraphRealDTypes() {
-  static gtl::ArraySlice<DataType> result{DT_FLOAT, DT_DOUBLE};
+  static gtl::ArraySlice<DataType> result{DT_FLOAT, DT_DOUBLE, DT_BFLOAT16};
   return result;
 }