fix zlib.

Author: Xinlei Chen

configure

@@ -183,7 +183,7 @@ while true; do
 
   fromuser=""
   if [ -z "$CUDA_TOOLKIT_PATH" ]; then
-    default_cuda_path=/usr/local/cuda-8.0
+    default_cuda_path=/usr/local/cuda-7.5
     if is_windows; then
       if [ -z "$CUDA_PATH" ]; then
         default_cuda_path="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v8.0"
@@ -236,7 +236,7 @@ while true; do
 
   fromuser=""
   if [ -z "$CUDNN_INSTALL_PATH" ]; then
-    default_cudnn_path=/home/xinleic/tools/cudnn-v5.1-2
+    default_cudnn_path=/home/xinleic/tools/cudnn-v5.1
     read -p "Please specify the location where cuDNN $TF_CUDNN_VERSION library is installed. Refer to README.md for more details. [Default is $default_cudnn_path]: " CUDNN_INSTALL_PATH
     fromuser="1"
     if [ -z "$CUDNN_INSTALL_PATH" ]; then
@@ -331,14 +331,14 @@ done
 # Since Cuda toolkit is not backward-compatible, this is not guaranteed to work.
 while true; do
   fromuser=""
-  default_cuda_compute_capabilities="3.5,5.2,6.1"
+  default_cuda_compute_capabilities="3.5,5.2"
   if [ -z "$TF_CUDA_COMPUTE_CAPABILITIES" ]; then
 cat << EOF
 Please specify a list of comma-separated Cuda compute capabilities you want to build with.
 You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
 Please note that each additional compute capability significantly increases your build time and binary size.
 EOF
-    read -p "[Default is: \"3.5,5.2,6.1\"]: " TF_CUDA_COMPUTE_CAPABILITIES
+    read -p "[Default is: \"3.5,5.2\"]: " TF_CUDA_COMPUTE_CAPABILITIES
     fromuser=1
   fi
   if [ -z "$TF_CUDA_COMPUTE_CAPABILITIES" ]; then

tensorflow/python/ops/image_ops.py

@@ -81,6 +81,9 @@
 @@crop_to_bounding_box
 @@extract_glimpse
 
+@@resample_and_pad
+@@resize_and_pad
+
 @@crop_and_resize
 
 ## Flipping, Rotating and Transposing

tensorflow/python/ops/image_ops_impl.py

@@ -366,7 +366,31 @@ def resample_and_pad(image, offset_height, offset_width,
   if len(image.get_shape()) == 3:
     image = array_ops.expand_dims(image, 0)
   batch_size, _, _, depth = _ImageDimensions(image)
-  resized = resample(image, [height, width])
+  resized = gen_image_ops.resample(image, [height, width])
+  after_padding_width = target_width - offset_width - width
+  after_padding_height = target_height - offset_height - height
+  paddings = array_ops.reshape(
+    array_ops.pack([0, 0,
+                    offset_height, after_padding_height,
+                    offset_width, after_padding_width,
+                    0, 0]),
+    [4, 2])
+  padded = array_ops.pad(resized, paddings)
+  padded_shape = [None if _is_tensor(i) else i
+                  for i in [batch_size, target_height, target_width, depth]]
+  padded.set_shape(padded_shape)
+  return padded
+
+
+# Added by X
+def resize_and_pad(image, offset_height, offset_width,
+                    height, width,
+                    target_height, target_width):
+  # written by X, no back propagation through roi, but anyway
+  if len(image.get_shape()) == 3:
+    image = array_ops.expand_dims(image, 0)
+  batch_size, _, _, depth = _ImageDimensions(image)
+  resized = gen_image_ops.resize_bilinear(image, [height, width])
   after_padding_width = target_width - offset_width - width
   after_padding_height = target_height - offset_height - height
   paddings = array_ops.reshape(

tensorflow/workspace.bzl

@@ -238,9 +238,8 @@ def tf_workspace(path_prefix = "", tf_repo_name = ""):
 
   native.new_http_archive(
     name = "zlib_archive",
-    url = "http://zlib.net/zlib-1.2.8.tar.gz",
-    sha256 = "36658cb768a54c1d4dec43c3116c27ed893e88b02ecfcb44f2166f9c0b7f2a0d",
-    strip_prefix = "zlib-1.2.8",
+    url = "http://zlib.net/zlib-1.2.11.tar.gz",
+    strip_prefix = "zlib-1.2.11",
     build_file = str(Label("//:zlib.BUILD")),
   )