avoid out_size less than 1

test=develop

paddle/fluid/operators/interpolate_op.cu

@@ -220,12 +220,17 @@ class InterpolateOpCUDAKernel : public framework::OpKernel<T> {
     int in_chw = c * in_hw;
     int out_chw = c * out_hw;
 
-    float ratio_h = (align_corners && out_h > 1)
-                        ? static_cast<float>(in_h - 1) / (out_h - 1)
-                        : static_cast<float>(in_h) / out_h;
-    float ratio_w = (align_corners && out_w > 1)
-                        ? static_cast<float>(in_w - 1) / (out_w - 1)
-                        : static_cast<float>(in_w) / out_w;
+    float ratio_h = 0.f;
+    float ratio_w = 0.f;
+    if (out_h > 1) {
+      ratio_h = (align_corners) ? static_cast<float>(in_h - 1) / (out_h - 1)
+                                : static_cast<float>(in_h) / out_h;
+    }
+    if (out_w > 1) {
+      ratio_w = (align_corners && out_w > 1)
+                    ? static_cast<float>(in_w - 1) / (out_w - 1)
+                    : static_cast<float>(in_w) / out_w;
+    }
 
     if (in_h == out_h && in_w == out_w) {
       framework::TensorCopy(*input, ctx.GetPlace(), output);
@@ -290,12 +295,17 @@ class InterpolateGradOpCUDAKernel : public framework::OpKernel<T> {
     int in_chw = c * in_hw;
     int out_chw = c * out_hw;
 
-    float ratio_h = (align_corners && out_h > 1)
-                        ? static_cast<float>(in_h - 1) / (out_h - 1)
-                        : static_cast<float>(in_h) / out_h;
-    float ratio_w = (align_corners && out_w > 1)
-                        ? static_cast<float>(in_w - 1) / (out_w - 1)
-                        : static_cast<float>(in_w) / out_w;
+    float ratio_h = 0.f;
+    float ratio_w = 0.f;
+    if (out_h > 1) {
+      ratio_h = (align_corners) ? static_cast<float>(in_h - 1) / (out_h - 1)
+                                : static_cast<float>(in_h) / out_h;
+    }
+    if (out_w > 1) {
+      ratio_w = (align_corners && out_w > 1)
+                    ? static_cast<float>(in_w - 1) / (out_w - 1)
+                    : static_cast<float>(in_w) / out_w;
+    }
 
     if (in_h == out_h && in_w == out_w) {
       framework::TensorCopy(*output_grad, ctx.GetPlace(), input_grad);

paddle/fluid/operators/interpolate_op.h

@@ -191,12 +191,18 @@ class InterpolateKernel : public framework::OpKernel<T> {
       return;
     }
 
-    float ratio_h = (align_corners && out_h > 1)
-                        ? static_cast<float>(in_h - 1) / (out_h - 1)
-                        : static_cast<float>(in_h) / out_h;
-    float ratio_w = (align_corners && out_w > 1)
-                        ? static_cast<float>(in_w - 1) / (out_w - 1)
-                        : static_cast<float>(in_w) / out_w;
+    float ratio_h = 0.f;
+    float ratio_w = 0.f;
+
+    if (out_h > 1) {
+      ratio_h = (align_corners) ? static_cast<float>(in_h - 1) / (out_h - 1)
+                                : static_cast<float>(in_h) / out_h;
+    }
+    if (out_w > 1) {
+      ratio_w = (align_corners && out_w > 1)
+                    ? static_cast<float>(in_w - 1) / (out_w - 1)
+                    : static_cast<float>(in_w) / out_w;
+    }
 
     if ("bilinear" == interp_method) {
       BilinearInterpolation<T>(*input, output, ratio_h, ratio_w, in_h, in_w, n,
@@ -244,12 +250,18 @@ class InterpolateGradKernel : public framework::OpKernel<T> {
       return;
     }
 
-    float ratio_h = (align_corners && out_h > 1)
-                        ? static_cast<float>(in_h - 1) / (out_h - 1)
-                        : static_cast<float>(in_h) / out_h;
-    float ratio_w = (align_corners && out_w > 1)
-                        ? static_cast<float>(in_w - 1) / (out_w - 1)
-                        : static_cast<float>(in_w) / out_w;
+    float ratio_h = 0.f;
+    float ratio_w = 0.f;
+
+    if (out_h > 1) {
+      ratio_h = (align_corners) ? static_cast<float>(in_h - 1) / (out_h - 1)
+                                : static_cast<float>(in_h) / out_h;
+    }
+    if (out_w > 1) {
+      ratio_w = (align_corners && out_w > 1)
+                    ? static_cast<float>(in_w - 1) / (out_w - 1)
+                    : static_cast<float>(in_w) / out_w;
+    }
 
     if ("bilinear" == interp_method) {
       BilinearInterpolationGrad<T>(*output_grad, input_grad, ratio_h, ratio_w,

python/paddle/fluid/tests/unittests/test_bilinear_interp_op.py

@@ -37,14 +37,16 @@ def bilinear_interp_np(input,
     batch_size, channel, in_h, in_w = input.shape
 
     ratio_h = ratio_w = 0.0
-    if (align_corners and out_h > 1):
-        ratio_h = (in_h - 1.0) / (out_h - 1.0)
-    else:
-        ratio_h = 1.0 * in_h / out_h
-    if (align_corners and out_w > 1):
-        ratio_w = (in_w - 1.0) / (out_w - 1.0)
-    else:
-        ratio_w = 1.0 * in_w / out_w
+    if out_h > 1:
+        if (align_corners):
+            ratio_h = (in_h - 1.0) / (out_h - 1.0)
+        else:
+            ratio_h = 1.0 * in_h / out_h
+    if out_w > 1:
+        if (align_corners):
+            ratio_w = (in_w - 1.0) / (out_w - 1.0)
+        else:
+            ratio_w = 1.0 * in_w / out_w
 
     out = np.zeros((batch_size, channel, out_h, out_w))
 

python/paddle/fluid/tests/unittests/test_nearest_interp_op.py

@@ -36,14 +36,16 @@ def nearest_neighbor_interp_np(X,
     n, c, in_h, in_w = X.shape
 
     ratio_h = ratio_w = 0.0
-    if (align_corners and out_h > 1):
-        ratio_h = (in_h - 1.0) / (out_h - 1.0)
-    else:
-        ratio_h = 1.0 * in_h / out_h
-    if (align_corners and out_w > 1):
-        ratio_w = (in_w - 1.0) / (out_w - 1.0)
-    else:
-        ratio_w = 1.0 * in_w / out_w
+    if (out_h > 1):
+        if (align_corners):
+            ratio_h = (in_h - 1.0) / (out_h - 1.0)
+        else:
+            ratio_h = 1.0 * in_h / out_h
+    if (out_w > 1):
+        if (align_corners):
+            ratio_w = (in_w - 1.0) / (out_w - 1.0)
+        else:
+            ratio_w = 1.0 * in_w / out_w
 
     out = np.zeros((n, c, out_h, out_w))