Question

我正在尝试在检查回购后编译TensorFlow。我已经达到了谷歌protobuf错误的地步：

.btn {
    transition: all .3s ease;
    border-radius: 3px;
    padding: 5px 15px;
}
.btn-lg {
    padding: 15px 25px;
}
.btn-primary {
    background: #556270;
    background: -webkit-linear-gradient(to right, #FF6B6B, #556270);
    background: linear-gradient(to right, #FF6B6B, #556270);
    color: white;
    border: 0px;
    padding: 5px 15px;
    border-radius: 3px;
}
.btn-primary:hover, .btn-primary:focus, .btn-primary:hover:active {
    background: #11998e;
    background: -webkit-linear-gradient(to right, #38ef7d, #11998e);
    background: linear-gradient(to right, #38ef7d, #11998e);
    color: white;
    outline: none !important;
}
.button {
    display: inline-block;
    padding: 5px 15px;
    background: #556270;
    background: -webkit-linear-gradient(to right, #FF6B6B, #556270);
    background: linear-gradient(to right, #FF6B6B, #556270);
    color: white;
    transition: all .3s ease;
    border-radius: 3px;
}
.button:hover, .button:focus, .button:hover:active {
    background: #11998e;
    background: -webkit-linear-gradient(to right, #38ef7d, #11998e);
    background: linear-gradient(to right, #38ef7d, #11998e);
}

有没有人遇到过这个问题？关于如何解决这个问题的任何想法？

（我在OSX 10.11.5的虚拟环境中使用Python 2.7）

Answer 1

幸运的是，其他人已经不仅有同样的问题，而且还找到了修复并分享了它。感谢Daniel Trebbien的comments on protobuf和eigen我可以在OSX上用GPU支持编译张量流：

>>> import tensorflow as tf
>>> tf.__version__
'1.6.0-rc0'
>>> sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
2018-02-19 22:22:12.194516: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:859] OS X does not support NUMA - returning NUMA node zero
2018-02-19 22:22:12.195011: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1331] Found device 0 with properties: 
name: GeForce GT 750M major: 3 minor: 0 memoryClockRate(GHz): 0.9255
pciBusID: 0000:01:00.0
totalMemory: 2.00GiB freeMemory: 12.58MiB
2018-02-19 22:22:12.195038: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1410] Adding visible gpu devices: 0
2018-02-19 22:22:14.563665: I tensorflow/core/common_runtime/gpu/gpu_device.cc:911] Device interconnect StreamExecutor with strength 1 edge matrix:
2018-02-19 22:22:14.563700: I tensorflow/core/common_runtime/gpu/gpu_device.cc:917]      0 
2018-02-19 22:22:14.563707: I tensorflow/core/common_runtime/gpu/gpu_device.cc:930] 0:   N 
2018-02-19 22:22:14.563798: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1021] Creating TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 65 MB memory) -> physical GPU (device: 0, name: GeForce GT 750M, pci bus id: 0000:01:00.0, compute capability: 3.0)
Device mapping:
/job:localhost/replica:0/task:0/device:GPU:0 -> device: 0, name: GeForce GT 750M, pci bus id: 0000:01:00.0, compute capability: 3.0
2018-02-19 22:22:14.697626: I tensorflow/core/common_runtime/direct_session.cc:297] Device mapping:
/job:localhost/replica:0/task:0/device:GPU:0 -> device: 0, name: GeForce GT 750M, pci bus id: 0000:01:00.0, compute capability: 3.0

供参考，以下是评论中提出的补丁：

--- a/tensorflow/workspace.bzl
+++ b/tensorflow/workspace.bzl
@@ -353,11 +353,11 @@ def tf_workspace(path_prefix="", tf_repo_name=""):
   tf_http_archive(
       name = "protobuf_archive",
       urls = [
-          "https://mirror.bazel.build/github.com/google/protobuf/archive/396336eb961b75f03b25824fe86cf6490fb75e3a.tar.gz",
-          "https://github.com/google/protobuf/archive/396336eb961b75f03b25824fe86cf6490fb75e3a.tar.gz",
+          "https://mirror.bazel.build/github.com/dtrebbien/protobuf/archive/50f552646ba1de79e07562b41f3999fe036b4fd0.tar.gz",
+          "https://github.com/dtrebbien/protobuf/archive/50f552646ba1de79e07562b41f3999fe036b4fd0.tar.gz",
       ],
-      sha256 = "846d907acf472ae233ec0882ef3a2d24edbbe834b80c305e867ac65a1f2c59e3",
-      strip_prefix = "protobuf-396336eb961b75f03b25824fe86cf6490fb75e3a",
+      sha256 = "eb16b33431b91fe8cee479575cee8de202f3626aaf00d9bf1783c6e62b4ffbc7",
+      strip_prefix = "protobuf-50f552646ba1de79e07562b41f3999fe036b4fd0",
   )

--- a/tensorflow/workspace.bzl
+++ b/tensorflow/workspace.bzl
@@ -120,11 +120,11 @@ def tf_workspace(path_prefix="", tf_repo_name=""):
   tf_http_archive(
       name = "eigen_archive",
       urls = [
-          "https://mirror.bazel.build/bitbucket.org/eigen/eigen/get/2355b229ea4c.tar.gz",
-          "https://bitbucket.org/eigen/eigen/get/2355b229ea4c.tar.gz",
+          "https://mirror.bazel.build/bitbucket.org/dtrebbien/eigen/get/374842a18727.tar.gz",
+          "https://bitbucket.org/dtrebbien/eigen/get/374842a18727.tar.gz",
       ],
-      sha256 = "0cadb31a35b514bf2dfd6b5d38205da94ef326ec6908fc3fd7c269948467214f",
-      strip_prefix = "eigen-eigen-2355b229ea4c",
+      sha256 = "fa26e9b9ff3a2692b092d154685ec88d6cb84d4e1e895006541aff8603f15c16",
+      strip_prefix = "dtrebbien-eigen-374842a18727",
       build_file = str(Label("//third_party:eigen.BUILD")),
   )

如何修复OSX上的tensorflow protobuf编译错误？

1 个答案: