Merge changes from github.

PiperOrigin-RevId: 202585094

5 files changed, 571 insertions, 4 deletions

diff --git a/tensorflow/go/attrs.go b/tensorflow/go/attrs.go
new file mode 100644
index 0000000000..f86c5737bc
--- /dev/null
+++ b/tensorflow/go/attrs.go
@@ -0,0 +1,245 @@
+/*
+Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+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.
+*/
+
+package tensorflow
+
+// #include <stdlib.h>
+// #include "tensorflow/c/c_api.h"
+import "C"
+import (
+	"fmt"
+	"unsafe"
+)
+
+// makeCShape converts a shape specified in C.int64_t into a Shape.
+func makeCShape(shape []C.int64_t) Shape {
+	s := Shape{dims: make([]int64, len(shape))}
+	for i, n := range shape {
+		s.dims[i] = int64(n)
+	}
+	return s
+}
+
+// Attr returns the value of an attribute on op. It returns an error if the
+// attribute does not exist.
+func (op *Operation) Attr(name string) (interface{}, error) {
+	cname := C.CString(name)
+	defer C.free(unsafe.Pointer(cname))
+
+	status := newStatus()
+	meta := C.TF_OperationGetAttrMetadata(op.c, cname, status.c)
+	if err := status.Err(); err != nil {
+		return nil, err
+	}
+
+	if meta.is_list == 1 {
+		return listAttribute(op, cname, meta)
+	}
+	return scalarAttribute(op, cname, meta)
+}
+
+func listAttribute(op *Operation, cname *C.char, meta C.TF_AttrMetadata) (interface{}, error) {
+	status := newStatus()
+
+	switch meta._type {
+	case C.TF_ATTR_STRING:
+		if meta.list_size == 0 {
+			return []string(nil), nil
+		}
+		values := make([]unsafe.Pointer, meta.list_size)
+		lengths := make([]C.size_t, meta.list_size)
+		// Add one element in case total_size is zero.
+		storage := make([]C.char, meta.total_size+1)
+		C.TF_OperationGetAttrStringList(op.c, cname, &values[0], &lengths[0], C.int(meta.list_size), unsafe.Pointer(&storage[0]), C.size_t(meta.total_size), status.c)
+		if err := status.Err(); err != nil {
+			return nil, err
+		}
+		list := make([]string, meta.list_size)
+		for i, val := range values {
+			length := lengths[i]
+			list[i] = C.GoStringN((*C.char)(val), C.int(length))
+		}
+		return list, nil
+
+	case C.TF_ATTR_INT:
+		if meta.list_size == 0 {
+			return []int64(nil), nil
+		}
+		list := make([]C.int64_t, meta.list_size)
+		C.TF_OperationGetAttrIntList(op.c, cname, &list[0], C.int(meta.list_size), status.c)
+		if err := status.Err(); err != nil {
+			return nil, err
+		}
+		vals := make([]int64, meta.list_size)
+		for i, val := range list {
+			vals[i] = int64(val)
+		}
+		return vals, nil
+
+	case C.TF_ATTR_FLOAT:
+		if meta.list_size == 0 {
+			return []float32(nil), nil
+		}
+		list := make([]C.float, meta.list_size)
+		C.TF_OperationGetAttrFloatList(op.c, cname, &list[0], C.int(meta.list_size), status.c)
+		if err := status.Err(); err != nil {
+			return nil, err
+		}
+		vals := make([]float32, meta.list_size)
+		for i, val := range list {
+			vals[i] = float32(val)
+		}
+		return vals, nil
+
+	case C.TF_ATTR_BOOL:
+		if meta.list_size == 0 {
+			return []bool(nil), nil
+		}
+		list := make([]C.uchar, meta.list_size)
+		C.TF_OperationGetAttrBoolList(op.c, cname, &list[0], C.int(meta.list_size), status.c)
+		if err := status.Err(); err != nil {
+			return nil, err
+		}
+		vals := make([]bool, meta.list_size)
+		for i, val := range list {
+			vals[i] = val == 1
+		}
+		return vals, nil
+
+	case C.TF_ATTR_TYPE:
+		if meta.list_size == 0 {
+			return []DataType(nil), nil
+		}
+		list := make([]C.TF_DataType, meta.list_size)
+		C.TF_OperationGetAttrTypeList(op.c, cname, &list[0], C.int(meta.list_size), status.c)
+		if err := status.Err(); err != nil {
+			return nil, err
+		}
+		vals := make([]DataType, meta.list_size)
+		for i, val := range list {
+			vals[i] = DataType(val)
+		}
+		return vals, nil
+
+	case C.TF_ATTR_TENSOR:
+		if meta.list_size == 0 {
+			return []*Tensor(nil), nil
+		}
+		list := make([]*C.TF_Tensor, meta.list_size)
+		C.TF_OperationGetAttrTensorList(op.c, cname, &list[0], C.int(meta.list_size), status.c)
+		if err := status.Err(); err != nil {
+			return nil, err
+		}
+		vals := make([]*Tensor, meta.list_size)
+		for i, t := range list {
+			vals[i] = newTensorFromC(t)
+		}
+		return vals, nil
+
+	case C.TF_ATTR_SHAPE:
+		if meta.list_size == 0 {
+			return []Shape(nil), nil
+		}
+		dims := make([]*C.int64_t, meta.list_size)
+		numDims := make([]C.int, meta.list_size)
+		// Add one element in case total_size is zero.
+		storage := make([]C.int64_t, meta.total_size+1)
+		C.TF_OperationGetAttrShapeList(op.c, cname, &dims[0], &numDims[0], C.int(meta.list_size), &storage[0], C.int(meta.total_size), status.c)
+		if err := status.Err(); err != nil {
+			return nil, err
+		}
+		list := make([]Shape, meta.list_size)
+		for i, dim := range dims {
+			numDim := numDims[i]
+			// If the number of dimensions is unknown, default to empty shape.
+			if numDim < 0 {
+				continue
+			}
+			// A []C.int64_t slice backed by C memory.
+			// See: https://github.com/golang/go/wiki/cgo#turning-c-arrays-into-go-slices
+			slice := (*[1 << 30]C.int64_t)(unsafe.Pointer(dim))[:numDim:numDim]
+			list[i] = makeCShape(slice)
+		}
+		return list, nil
+
+	default:
+		return nil, fmt.Errorf("list type %v not supported", meta._type)
+	}
+}
+
+func scalarAttribute(op *Operation, cname *C.char, meta C.TF_AttrMetadata) (interface{}, error) {
+	status := newStatus()
+
+	switch meta._type {
+	case C.TF_ATTR_STRING:
+		if meta.total_size == 0 {
+			return "", nil
+		}
+		v := make([]C.char, meta.total_size)
+		C.TF_OperationGetAttrString(op.c, cname, unsafe.Pointer(&v[0]), C.size_t(meta.total_size), status.c)
+		if err := status.Err(); err != nil {
+			return nil, err
+		}
+		return C.GoStringN(&v[0], C.int(meta.total_size)), nil
+
+	case C.TF_ATTR_INT:
+		var v C.int64_t
+		C.TF_OperationGetAttrInt(op.c, cname, &v, status.c)
+		return int64(v), status.Err()
+
+	case C.TF_ATTR_FLOAT:
+		var v C.float
+		C.TF_OperationGetAttrFloat(op.c, cname, &v, status.c)
+		return float32(v), status.Err()
+
+	case C.TF_ATTR_BOOL:
+		var v C.uchar
+		C.TF_OperationGetAttrBool(op.c, cname, &v, status.c)
+		return v == 1, status.Err()
+
+	case C.TF_ATTR_TYPE:
+		var v C.TF_DataType
+		C.TF_OperationGetAttrType(op.c, cname, &v, status.c)
+		return DataType(v), status.Err()
+
+	case C.TF_ATTR_TENSOR:
+		var v *C.TF_Tensor
+		C.TF_OperationGetAttrTensor(op.c, cname, &v, status.c)
+		if err := status.Err(); err != nil {
+			return nil, err
+		}
+		return newTensorFromC(v), nil
+
+	case C.TF_ATTR_SHAPE:
+		numDims := meta.total_size
+		// If number of dims is unknown return empty shape to indicate that.
+		if numDims < 0 {
+			return Shape{}, nil
+		}
+		if numDims == 0 {
+			return ScalarShape(), nil
+		}
+		dims := make([]C.int64_t, numDims)
+		C.TF_OperationGetAttrShape(op.c, cname, (*C.int64_t)(unsafe.Pointer(&dims[0])), C.int(numDims), status.c)
+		if err := status.Err(); err != nil {
+			return nil, err
+		}
+		return makeCShape(dims), nil
+
+	default:
+		return nil, fmt.Errorf("type %v not supported", meta._type)
+	}
+}
diff --git a/tensorflow/go/attrs_test.go b/tensorflow/go/attrs_test.go
new file mode 100644
index 0000000000..ea8af221ae
--- /dev/null
+++ b/tensorflow/go/attrs_test.go
@@ -0,0 +1,193 @@
+/*
+Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+
+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.
+*/
+
+package tensorflow
+
+import (
+	"fmt"
+	"reflect"
+	"testing"
+)
+
+func TestOperationAttrs(t *testing.T) {
+	g := NewGraph()
+
+	i := 0
+	makeConst := func(v interface{}) Output {
+		op, err := Const(g, fmt.Sprintf("const/%d/%+v", i, v), v)
+		i++
+		if err != nil {
+			t.Fatal(err)
+		}
+		return op
+	}
+
+	makeTensor := func(v interface{}) *Tensor {
+		tensor, err := NewTensor(v)
+		if err != nil {
+			t.Fatal(err)
+		}
+		return tensor
+	}
+
+	cases := []OpSpec{
+		{
+			Name: "type",
+			Type: "Placeholder",
+			Attrs: map[string]interface{}{
+				"dtype": Float,
+			},
+		},
+		{
+			Name: "list(float)",
+			Type: "Bucketize",
+			Input: []Input{
+				makeConst([]float32{1, 2, 3, 4}),
+			},
+			Attrs: map[string]interface{}{
+				"boundaries": []float32{0, 1, 2, 3, 4, 5},
+			},
+		},
+		{
+			Name: "list(float) empty",
+			Type: "Bucketize",
+			Input: []Input{
+				makeConst([]float32{}),
+			},
+			Attrs: map[string]interface{}{
+				"boundaries": []float32(nil),
+			},
+		},
+    /* TODO(ashankar): debug this issue and add it back later.
+		{
+			Name: "list(type),list(shape)",
+			Type: "InfeedEnqueueTuple",
+			Input: []Input{
+				OutputList([]Output{
+					makeConst(float32(1)),
+					makeConst([][]int32{{2}}),
+				}),
+			},
+			Attrs: map[string]interface{}{
+				"dtypes": []DataType{Float, Int32},
+				"shapes": []Shape{ScalarShape(), MakeShape(1, 1)},
+			},
+		},
+		{
+			Name: "list(type),list(shape) empty",
+			Type: "InfeedEnqueueTuple",
+			Input: []Input{
+				OutputList([]Output{
+					makeConst([][]int32{{2}}),
+				}),
+			},
+			Attrs: map[string]interface{}{
+				"dtypes": []DataType{Int32},
+				"shapes": []Shape(nil),
+			},
+		},
+		{
+			Name: "list(type) empty,string empty,int",
+			Type: "_XlaSendFromHost",
+			Input: []Input{
+				OutputList([]Output{}),
+				makeConst(""),
+			},
+			Attrs: map[string]interface{}{
+				"Tinputs":        []DataType(nil),
+				"key":            "",
+				"device_ordinal": int64(0),
+			},
+		},
+    */
+		{
+			Name: "list(int),int",
+			Type: "StringToHashBucketStrong",
+			Input: []Input{
+				makeConst(""),
+			},
+			Attrs: map[string]interface{}{
+				"num_buckets": int64(2),
+				"key":         []int64{1, 2},
+			},
+		},
+		{
+			Name: "list(int) empty,int",
+			Type: "StringToHashBucketStrong",
+			Input: []Input{
+				makeConst(""),
+			},
+			Attrs: map[string]interface{}{
+				"num_buckets": int64(2),
+				"key":         ([]int64)(nil),
+			},
+		},
+		{
+			Name: "list(string),type",
+			Type: "TensorSummary",
+			Input: []Input{
+				makeConst(""),
+			},
+			Attrs: map[string]interface{}{
+				"T":      String,
+				"labels": []string{"foo", "bar"},
+			},
+		},
+		{
+			Name: "list(string) empty,type",
+			Type: "TensorSummary",
+			Input: []Input{
+				makeConst(""),
+			},
+			Attrs: map[string]interface{}{
+				"T":      String,
+				"labels": ([]string)(nil),
+			},
+		},
+		{
+			Name: "tensor",
+			Type: "Const",
+			Attrs: map[string]interface{}{
+				"dtype": String,
+				"value": makeTensor("foo"),
+			},
+		},
+	}
+
+	for i, spec := range cases {
+		op, err := g.AddOperation(spec)
+		if err != nil {
+			t.Fatal(err)
+		}
+		for key, want := range spec.Attrs {
+			out, err := op.Attr(key)
+			if err != nil {
+				t.Fatal(err)
+			}
+			if !reflect.DeepEqual(out, want) {
+				t.Fatalf("%d. %q: Got %#v, wanted %#v", i, key, out, want)
+			}
+			wantT, ok := want.(*Tensor)
+			if ok {
+				wantVal := wantT.Value()
+				outVal := out.(*Tensor).Value()
+				if !reflect.DeepEqual(outVal, wantVal) {
+					t.Fatalf("%d. %q: Got %#v, wanted %#v", i, key, outVal, wantVal)
+				}
+			}
+		}
+	}
+}
diff --git a/tensorflow/go/op/wrappers.go b/tensorflow/go/op/wrappers.go
index b2dbdafc5f..6d9cb7c6ec 100644
--- a/tensorflow/go/op/wrappers.go
+++ b/tensorflow/go/op/wrappers.go
@@ -11210,7 +11210,7 @@ func SampleDistortedBoundingBoxAspectRatioRange(value []float32) SampleDistorted
 // SampleDistortedBoundingBoxAreaRange sets the optional area_range attribute to value.
 //
 // value: The cropped area of the image must contain a fraction of the
-// supplied image within in this range.
+// supplied image within this range.
 // If not specified, defaults to <f:0.05 f:1 >
 func SampleDistortedBoundingBoxAreaRange(value []float32) SampleDistortedBoundingBoxAttr {
 	return func(m optionalAttr) {
@@ -17969,9 +17969,10 @@ func SparseFillEmptyRowsGrad(scope *Scope, reverse_index_map tf.Output, grad_val
 }
 
 // Computes scaled exponential linear: `scale * alpha * (exp(features) - 1)`
-//
 // if < 0, `scale * features` otherwise.
 //
+// Assumes weights to have zero mean and variance 1.0 / fan_in.
+//
 // See [Self-Normalizing Neural Networks](https://arxiv.org/abs/1706.02515)
 func Selu(scope *Scope, features tf.Output) (activations tf.Output) {
 	if scope.Err() != nil {
@@ -21655,7 +21656,7 @@ func ImageSummaryBadColor(value tf.Tensor) ImageSummaryAttr {
 //    generated sequentially as '*tag*/image/0', '*tag*/image/1', etc.
 //
 // The `bad_color` argument is the color to use in the generated images for
-// non-finite input values.  It is a `unit8` 1-D tensor of length `channels`.
+// non-finite input values.  It is a `uint8` 1-D tensor of length `channels`.
 // Each element must be in the range `[0, 255]` (It represents the value of a
 // pixel in the output image).  Non-finite values in the input tensor are
 // replaced by this tensor in the output image.  The default value is the color
@@ -24048,7 +24049,7 @@ func SampleDistortedBoundingBoxV2AspectRatioRange(value []float32) SampleDistort
 // SampleDistortedBoundingBoxV2AreaRange sets the optional area_range attribute to value.
 //
 // value: The cropped area of the image must contain a fraction of the
-// supplied image within in this range.
+// supplied image within this range.
 // If not specified, defaults to <f:0.05 f:1 >
 func SampleDistortedBoundingBoxV2AreaRange(value []float32) SampleDistortedBoundingBoxV2Attr {
 	return func(m optionalAttr) {
diff --git a/tensorflow/go/operation.go b/tensorflow/go/operation.go
index 8fcad61f4c..25ec718703 100644
--- a/tensorflow/go/operation.go
+++ b/tensorflow/go/operation.go
@@ -65,6 +65,11 @@ func (op *Operation) Output(i int) Output {
 	return Output{op, i}
 }
 
+// NumInputs returns the number of inputs of op.
+func (op *Operation) NumInputs() int {
+	return int(C.TF_OperationNumInputs(op.c))
+}
+
 // Output represents one of the outputs of an operation in the graph. Has a
 // DataType (and eventually a Shape).  May be passed as an input argument to a
 // function for adding operations to a graph, or to a Session's Run() method to
@@ -123,6 +128,67 @@ func (p Output) c() C.TF_Output {
 
 func (p Output) canBeAnInput() {}
 
+// Consumers returns the inputs that consume this output.
+func (p Output) Consumers() []Consumer {
+	max := int(C.TF_OperationOutputNumConsumers(p.c()))
+	if max == 0 {
+		return nil
+	}
+	inputs := make([]C.TF_Input, max)
+	n := C.TF_OperationOutputConsumers(p.c(), (*C.TF_Input)(unsafe.Pointer(&inputs[0])), C.int(max))
+	inputs = inputs[:int(n)]
+
+	var consumers []Consumer
+	for _, consumer := range inputs {
+		consumers = append(consumers, Consumer{
+			Index: int(consumer.index),
+			Op: &Operation{
+				c: consumer.oper,
+				g: p.Op.g,
+			},
+		})
+	}
+
+	return consumers
+}
+
+// Consumer identifies a specific input of an operation that consumes the output
+// of another operation.
+type Consumer struct {
+	// Op is the Operation that is consuming the output of another operation.
+	Op *Operation
+
+	// Index is the index of the input within Op that the output of another
+	// operation is connected to.
+	Index int
+}
+
+func (p Consumer) c() C.TF_Input {
+	if p.Op == nil {
+		// Attempt to provide a more useful panic message than "nil
+		// pointer dereference".
+		panic("nil-Operation. Consumer objects should only be created by a call to Output.Consumers")
+	}
+	return C.TF_Input{oper: p.Op.c, index: C.int(p.Index)}
+}
+
+// DataType returns the type of the input.
+func (p Consumer) DataType() DataType {
+	return DataType(C.TF_OperationInputType(p.c()))
+}
+
+// Producer returns the Output that is connected to this Consumer.
+func (p Consumer) Producer() Output {
+	output := C.TF_OperationInput(p.c())
+	return Output{
+		Op: &Operation{
+			c: output.oper,
+			g: p.Op.g,
+		},
+		Index: int(output.index),
+	}
+}
+
 // Input is the interface for specifying inputs to an operation being added to
 // a Graph.
 //
diff --git a/tensorflow/go/operation_test.go b/tensorflow/go/operation_test.go
index 40c951ab8c..06b65bdfb7 100644
--- a/tensorflow/go/operation_test.go
+++ b/tensorflow/go/operation_test.go
@@ -166,6 +166,68 @@ func TestOutputDataTypeAndShape(t *testing.T) {
 	}
 }
 
+func TestOperationInputs(t *testing.T) {
+	g := NewGraph()
+	x, err := Placeholder(g, "x", Float)
+	if err != nil {
+		t.Fatal(err)
+	}
+	y, err := Placeholder(g, "y", Float)
+	if err != nil {
+		t.Fatal(err)
+	}
+	add, err := Add(g, "add", x, y)
+	if err != nil {
+		t.Fatal(err)
+	}
+	addOp := add.Op
+
+	if out := addOp.NumInputs(); out != 2 {
+		t.Fatalf("Got %d inputs, wanted 2", out)
+	}
+}
+
+func TestOperationConsumers(t *testing.T) {
+	g := NewGraph()
+	x, err := Placeholder(g, "x", Float)
+	if err != nil {
+		t.Fatal(err)
+	}
+	a, err := Neg(g, "a", x)
+	if err != nil {
+		t.Fatal(err)
+	}
+	b, err := Neg(g, "b", x)
+	if err != nil {
+		t.Fatal(err)
+	}
+
+	consumers := []*Operation{a.Op, b.Op}
+
+	xConsumers := x.Consumers()
+	if out := len(xConsumers); out != 2 {
+		t.Fatalf("Got %d consumers, wanted 2", out)
+	}
+
+	for i, consumer := range xConsumers {
+		got := consumer.Op.Name()
+		want := consumers[i].Name()
+		if got != want {
+			t.Fatalf("%d. Got op name %q, wanted %q", i, got, want)
+		}
+
+		got = consumer.Producer().Op.Name()
+		want = x.Op.Name()
+		if got != want {
+			t.Fatalf("%d. Got op name %q, wanted %q", i, got, want)
+		}
+	}
+
+	if len(b.Consumers()) != 0 {
+		t.Fatalf("expected %+v to have no consumers", b)
+	}
+}
+
 func forceGC() {
 	var mem runtime.MemStats
 	runtime.ReadMemStats(&mem)