Fix SAME padding calc when stride>ksize (#1991)

ry · Vijay Vasudevan · commit cf7ce8a7879b · 2016-04-18T18:05:45.000-07:00
Adds a failing test case for conv2d ksize=1, stride=2, padding=same,
input=4x4

Adds tests convering that case for pooling ops too.

There's one test case I found that fails in a different way that
I left commented out with R=C=8, K=2, S=4. The error is:
F tensorflow/stream_executor/cuda/cuda_dnn.cc:483] could not set cudnn convolution descriptor: CUDNN_STATUS_BAD_PARAM
diff --git a/tensorflow/core/kernels/ops_util.cc b/tensorflow/core/kernels/ops_util.cc
@@ -54,16 +54,14 @@ Status Get2dOutputSizeVerbose(const int in_height, const int in_width,
       *new_width = ceil(in_width / static_cast<float>(col_stride));
       // Calculate padding for top/bottom/left/right, spilling any excess
       // padding to bottom and right.
-      const int pad_needed_height =
-          (*new_height - 1) * row_stride + filter_height - in_height;
+      const int pad_needed_height = std::max(0,
+          (*new_height - 1) * row_stride + filter_height - in_height);
       *pad_top = pad_needed_height / 2;
-      CHECK_GE(pad_needed_height, 0);
       *pad_bottom = pad_needed_height - *pad_top;
 
-      const int pad_needed_width =
-          (*new_width - 1) * col_stride + filter_width - in_width;
+      const int pad_needed_width = std::max(0,
+          (*new_width - 1) * col_stride + filter_width - in_width);
       *pad_left = pad_needed_width / 2;
-      CHECK_GE(pad_needed_width, 0);
       *pad_right = pad_needed_width - *pad_left;
       break;
   }
diff --git a/tensorflow/python/kernel_tests/conv_ops_test.py b/tensorflow/python/kernel_tests/conv_ops_test.py
@@ -327,11 +327,26 @@ def testConv2DKernelSmallerThanStrideValid(self):
                        expected=expected_output)
 
   def testConv2DKernelSmallerThanStrideSame(self):
-    expected_output = [1, 3, 7, 9]
     self._VerifyValues(tensor_in_sizes=[1, 3, 3, 1],
                        filter_in_sizes=[1, 1, 1, 1],
                        strides=[2, 2], padding="SAME",
-                       expected=expected_output)
+                       expected=[1, 3, 7, 9])
+
+    self._VerifyValues(tensor_in_sizes=[1, 4, 4, 1],
+                       filter_in_sizes=[1, 1, 1, 1],
+                       strides=[2, 2], padding="SAME",
+                       expected=[1, 3, 9, 11])
+
+    self._VerifyValues(tensor_in_sizes=[1, 4, 4, 1],
+                       filter_in_sizes=[2, 2, 1, 1],
+                       strides=[3, 3], padding="SAME",
+                       expected=[44, 28, 41, 16])
+
+    # TODO this currently fails.
+    #self._VerifyValues(tensor_in_sizes=[1, 8, 8, 1],
+    #                   filter_in_sizes=[2, 2, 1, 1],
+    #                   strides=[4, 4], padding="SAME",
+    #                   expected=[72, 112, 392, 432])
 
   # Testing for backprops
   def _RunAndVerifyBackpropInput(self, input_sizes, filter_sizes, output_sizes,
diff --git a/tensorflow/python/kernel_tests/pooling_ops_test.py b/tensorflow/python/kernel_tests/pooling_ops_test.py
@@ -370,32 +370,35 @@ def testDepthwiseMaxPool2x2DepthWindow3(self):
                        expected=[3.0, 6.0, 9.0, 12.0, 15.0, 18.0, 21.0, 24.0],
                        use_gpu=False)
 
-  def testKernelSmallerThanStride(self):
+  def testKernelSmallerThanStrideValid(self):
     for use_gpu in [True, False]:
-        self._VerifyValues(tf.nn.max_pool, input_sizes=[1, 3, 3, 1],
-                           ksize=[1, 1, 1, 1], strides=[1, 2, 2, 1],
-                           padding="SAME",
-                           expected=[1, 3, 7, 9],
-                           use_gpu=use_gpu)
-
         self._VerifyValues(tf.nn.max_pool, input_sizes=[1, 7, 7, 1],
                            ksize=[1, 2, 2, 1], strides=[1, 3, 3, 1],
                            padding="VALID",
                            expected=[9, 12, 30, 33],
                            use_gpu=use_gpu)
 
-        self._VerifyValues(tf.nn.avg_pool, input_sizes=[1, 3, 3, 1],
-                           ksize=[1, 1, 1, 1], strides=[1, 2, 2, 1],
-                           padding="SAME",
-                           expected=[1, 3, 7, 9],
-                           use_gpu=use_gpu)
-
         self._VerifyValues(tf.nn.avg_pool, input_sizes=[1, 7, 7, 1],
                            ksize=[1, 2, 2, 1], strides=[1, 3, 3, 1],
                            padding="VALID",
                            expected=[5, 8, 26, 29],
                            use_gpu=use_gpu)
 
+  def testKernelSmallerThanStrideSame(self):
+    for use_gpu in [True, False]:
+        for pool_func in [tf.nn.max_pool, tf.nn.avg_pool]:
+            self._VerifyValues(pool_func, input_sizes=[1, 3, 3, 1],
+                               ksize=[1, 1, 1, 1], strides=[1, 2, 2, 1],
+                               padding="SAME",
+                               expected=[1, 3, 7, 9],
+                               use_gpu=use_gpu)
+
+            self._VerifyValues(pool_func, input_sizes=[1, 4, 4, 1],
+                               ksize=[1, 1, 1, 1], strides=[1, 2, 2, 1],
+                               padding="SAME",
+                               expected=[1, 3, 9, 11],
+                               use_gpu=use_gpu)
+
 
   def _testDepthwiseMaxPoolInvalidConfig(self, in_size, ksize, strides,
                                          error_msg, use_gpu=False):
