Use bool type for attr in cross_entropy_op.

paddle/operators/cross_entropy_op.cc

@@ -35,19 +35,16 @@ class CrossEntropyOp : public framework::OperatorWithKernel {
     PADDLE_ENFORCE_EQ(x->dims().size(), 2, "Input(X)'s rank must be 2.");
     PADDLE_ENFORCE_EQ(label->dims().size(), 2,
                       "Input(Label)'s rank must be 2.");
-    // TODO(xinghai-sun): remove this check after swtiching to bool
-    PADDLE_ENFORCE(ctx.Attr<int>("soft_label") == 0 ||
-                   ctx.Attr<int>("soft_label") == 1);
     PADDLE_ENFORCE_EQ(x->dims()[0], label->dims()[0],
                       "The 1st dimension of Input(X) and Input(Label) must "
                       "be equal.");
-    if (ctx.Attr<int>("soft_label") == 1) {
+    if (ctx.Attr<bool>("soft_label")) {
       PADDLE_ENFORCE_EQ(x->dims()[1], label->dims()[1],
-                        "If Attr(soft_label) == 1, The 2nd dimension of "
+                        "If Attr(soft_label) == true, The 2nd dimension of "
                         "Input(X) and Input(Label) must be equal.");
     } else {
       PADDLE_ENFORCE_EQ(label->dims()[1], 1,
-                        "If Attr(soft_label) == 0, The 2nd dimension of "
+                        "If Attr(soft_label) == false, The 2nd dimension of "
                         "Input(Label) must be 1.");
     }
 
@@ -74,9 +71,6 @@ class CrossEntropyGradientOp : public framework::OperatorWithKernel {
     PADDLE_ENFORCE_EQ(dy->dims().size(), 2, "Input(Y@Grad)'s rank must be 2.");
     PADDLE_ENFORCE_EQ(label->dims().size(), 2,
                       "Input(Label)'s rank must be 2.");
-    // TODO(xinghai-sun): remove this check after swtiching to bool
-    PADDLE_ENFORCE(ctx.Attr<int>("soft_label") == 0 ||
-                   ctx.Attr<int>("soft_label") == 1);
     PADDLE_ENFORCE_EQ(x->dims()[0], label->dims()[0],
                       "The 1st dimension of Input(X) and Input(Label) must "
                       "be equal.");
@@ -85,13 +79,13 @@ class CrossEntropyGradientOp : public framework::OperatorWithKernel {
                       "be equal.");
     PADDLE_ENFORCE_EQ(dy->dims()[1], 1,
                       "The 2nd dimension of Input(Y@Grad) must be 1.");
-    if (ctx.Attr<int>("soft_label") == 1) {
+    if (ctx.Attr<bool>("soft_label")) {
       PADDLE_ENFORCE_EQ(x->dims()[1], label->dims()[1],
-                        "If Attr(soft_label) == 1, The 2nd dimension of "
+                        "If Attr(soft_label) == true, The 2nd dimension of "
                         "Input(X) and Input(Label) must be equal.");
     } else {
       PADDLE_ENFORCE_EQ(label->dims()[1], 1,
-                        "If Attr(soft_label) == 0, The 2nd dimension of "
+                        "If Attr(soft_label) == false, The 2nd dimension of "
                         "Input(Label) must be 1.");
     }
 
@@ -108,7 +102,8 @@ class CrossEntropyOpMaker : public framework::OpProtoAndCheckerMaker {
     AddInput("X", "The first input of CrossEntropyOp");
     AddInput("Label", "The second input of CrossEntropyOp");
     AddOutput("Y", "The output of CrossEntropyOp");
-    AddAttr<int>("soft_label", "Is soft label. Default zero.").SetDefault(0);
+    AddAttr<bool>("soft_label", "Is soft label. Default zero.")
+        .SetDefault(false);
 
     AddComment(R"DOC(
 CrossEntropy Operator.
@@ -116,12 +111,12 @@ CrossEntropy Operator.
 It supports both standard cross-entropy and soft-label cross-entropy loss
 computation.
 1) One-hot cross-entropy:
-    soft_label = 0, Label[i, 0] indicates the class index for sample i:
+    soft_label = False, Label[i, 0] indicates the class index for sample i:
 
                 Y[i] = -log(X[i, Label[i]])
 
 2) Soft-label cross-entropy:
-    soft_label = 1, Label[i, j] indicates the soft label of class j
+    soft_label = True, Label[i, j] indicates the soft label of class j
     for sample i:
 
                 Y[i] = \sum_j{-Label[i, j] * log(X[i, j])}

paddle/operators/cross_entropy_op.cu

@@ -102,7 +102,7 @@ class CrossEntropyOpCUDAKernel : public framework::OpKernel {
     int grid = (n + block - 1) / block;
     // TODO(qingqing) launch kernel on specified stream
     // base on ExecutionContext.
-    if (ctx.Attr<int>("soft_label") == 1) {
+    if (ctx.Attr<bool>("soft_label")) {
       auto* label_data = ctx.Input<Tensor>("Label")->data<T>();
       SoftCrossEntropyKernel<T><<<grid, block>>>(y_data, x_data, label_data, n,
                                                  d);
@@ -137,7 +137,7 @@ class CrossEntropyGradientOpCUDAKernel : public framework::OpKernel {
     grid = (n + block - 1) / block;
     // TODO(qingqing): launch kernel on specified stream
     // base on ExecutionContext.
-    if (ctx.Attr<int>("soft_label") == 1) {
+    if (ctx.Attr<bool>("soft_label")) {
       auto* label_data = label->data<T>();
       SoftCrossEntropyGradientKernel<T><<<grid, block>>>(
           dx_data, dy_data, x_data, label_data, n, d);

paddle/operators/cross_entropy_op.h

@@ -51,7 +51,7 @@ class CrossEntropyOpKernel : public framework::OpKernel {
     int batch_size = x->dims()[0];
     int class_num = x->dims()[1];
 
-    if (ctx.Attr<int>("soft_label") == 1) {
+    if (ctx.Attr<bool>("soft_label")) {
       auto* label_data = ctx.Input<Tensor>("Label")->data<T>();
       int index = 0;
       for (int i = 0; i < batch_size; ++i) {
@@ -92,7 +92,7 @@ class CrossEntropyGradientOpKernel : public framework::OpKernel {
     int class_num = x->dims()[1];
 
     // TODO(qingqing): make zero setting an common function.
-    if (ctx.Attr<int>("soft_label") == 1) {
+    if (ctx.Attr<bool>("soft_label")) {
       auto* label_data = ctx.Input<Tensor>("Label")->data<T>();
       int index = 0;
       for (int i = 0; i < batch_size; ++i) {

python/paddle/v2/framework/tests/test_cross_entropy_op.py

@@ -19,7 +19,7 @@ class TestCrossEntropyOp1(OpTest):
             dtype="float32")
         self.inputs = {"X": X, "Label": label}
         self.outputs = {"Y": cross_entropy}
-        self.attrs = {'soft_label': 0}
+        self.attrs = {'soft_label': False}
 
     def test_check_output(self):
         self.check_output()
@@ -45,7 +45,7 @@ class TestCrossEntropyOp2(OpTest):
             axis=1, keepdims=True).astype("float32")
         self.inputs = {'X': X, 'Label': label}
         self.outputs = {'Y': cross_entropy}
-        self.attrs = {'soft_label': 1}
+        self.attrs = {'soft_label': True}
 
     def test_check_output(self):
         self.check_output()
@@ -76,7 +76,7 @@ class TestCrossEntropyOp3(OpTest):
             axis=1, keepdims=True).astype("float32")
         self.inputs = {'X': X, 'Label': label}
         self.outputs = {'Y': cross_entropy}
-        self.attrs = {'soft_label': 1}
+        self.attrs = {'soft_label': True}
 
     def test_check_output(self):
         self.check_output()