* gnu/packages/machine-learning.scm (tensorflow)[arguments]: Add build phase 'patch-cmake-file-to-install-c-headers; move setting of LDFLAGS from 'build-pip-package to 'unpack-third-party-sources; move 'build-pip-package after 'install phase. [source]: Add patch. * gnu/packages/patches/tensorflow-c-api-fix.patch: New file. * gnu/local.mk (dist_patch_DATA): Add it.
		
			
				
	
	
		
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			312 lines
		
	
	
	
		
			13 KiB
		
	
	
	
		
			Diff
		
	
	
	
	
	
| From eb61daae91432be0b07bb2f6854887bedfa6fc95 Mon Sep 17 00:00:00 2001
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| From: Asim Shankar <ashankar@google.com>
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| Date: Tue, 26 Jun 2018 00:57:33 -0700
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| Subject: [PATCH] [C API]: Bugfix for TF_AddGradients.
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| 
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| TF_AddGradients could create nodes in the graph with names that conflicted with
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| other nodes in the graph. This would most clearly happen if TF_AddGradients()
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| was called twice on the same graph, and could also happen if there were other
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| nodes in the graph that happened to have "gradients" as a prefix of their name.
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| 
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| Fix that.
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| 
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| The added test in c_api_test.cc would fail in the call to TF_SessionRun() with
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|   Node 'gradients/OnesLike' is not unique
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| without the changes to c_api.cc and c_api_internal.h
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| 
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| While at it, also fixed a possible name collision bug when using the C++ API
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| to constructor graphs (using Scope).
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| 
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| Thanks @karllessard for pointing this out.
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| 
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| PiperOrigin-RevId: 202087996
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| ---
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|  tensorflow/c/c_api.cc                    | 13 ++++-
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|  tensorflow/c/c_api_test.cc               | 65 ++++++++++++++++++++++--
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|  tensorflow/c/c_test_util.cc              |  7 +++
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|  tensorflow/c/c_test_util.h               |  3 ++
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|  tensorflow/cc/framework/scope.cc         | 30 ++++++++---
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|  tensorflow/cc/framework/scope_internal.h |  3 +-
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|  tensorflow/cc/framework/scope_test.cc    | 10 ++++
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|  7 files changed, 116 insertions(+), 15 deletions(-)
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| 
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| diff --git a/tensorflow/c/c_api.cc b/tensorflow/c/c_api.cc
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| index 09a03639d6fa3..37c8302e08bc3 100644
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| --- a/tensorflow/c/c_api.cc
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| +++ b/tensorflow/c/c_api.cc
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| @@ -2414,7 +2414,18 @@ void TF_AddGradients(TF_Graph* g, TF_Output* y, int ny, TF_Output* x, int nx,
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|      for (int i = first_new_node_id; i < g->graph.num_node_ids(); ++i) {
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|        Node* n = g->graph.FindNodeId(i);
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|        if (n == nullptr) continue;
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| -      g->name_map[n->name()] = n;
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| +      // We have a convoluted scheme here: Using the C++ graph construction API
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| +      // to add potentially many nodes to the graph without running the checks
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| +      // (such as uniqueness of the names of nodes) we run with other functions
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| +      // that add a node to the graph (like TF_FinishOperation).
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| +      if (!g->name_map.insert(std::make_pair(n->name(), n)).second) {
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| +        status->status = tensorflow::errors::Internal(
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| +            "BUG: The API allowed construction of a graph with duplicate node "
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| +            "names (",
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| +            n->name(),
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| +            "). This is a bug. Please file an issue at "
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| +            "https://github.com/tensorflow/tensorflow/issues.");
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| +      }
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|      }
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|    }
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|  
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| diff --git a/tensorflow/c/c_api_test.cc b/tensorflow/c/c_api_test.cc
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| index 577f10c5e69ea..bc04b53fbb7fa 100644
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| --- a/tensorflow/c/c_api_test.cc
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| +++ b/tensorflow/c/c_api_test.cc
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| @@ -1160,7 +1160,7 @@ TEST(CAPI, GetOpDef) {
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|  }
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|  
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|  void StringVectorToArrays(const std::vector<string>& v,
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| -                          std::unique_ptr<const void* []>* ptrs,
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| +                          std::unique_ptr<const void*[]>* ptrs,
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|                            std::unique_ptr<size_t[]>* lens) {
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|    ptrs->reset(new const void*[v.size()]);
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|    lens->reset(new size_t[v.size()]);
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| @@ -1196,7 +1196,7 @@ class CApiColocationTest : public ::testing::Test {
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|  
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|    void SetViaStringList(TF_OperationDescription* desc,
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|                          const std::vector<string>& list) {
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| -    std::unique_ptr<const void* []> list_ptrs;
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| +    std::unique_ptr<const void*[]> list_ptrs;
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|      std::unique_ptr<size_t[]> list_lens;
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|      StringVectorToArrays(list, &list_ptrs, &list_lens);
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|      TF_SetAttrStringList(desc, tensorflow::kColocationAttrName, list_ptrs.get(),
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| @@ -1700,6 +1700,61 @@ TEST_F(CApiGradientsTest, OpWithNoGradientRegistered_NoGradInputs) {
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|    TestGradientsError(false);
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|  }
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|  
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| +void ScalarFloatFromTensor(const TF_Tensor* t, float* f) {
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| +  ASSERT_TRUE(t != nullptr);
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| +  ASSERT_EQ(TF_FLOAT, TF_TensorType(t));
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| +  ASSERT_EQ(0, TF_NumDims(t));
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| +  ASSERT_EQ(4, TF_TensorByteSize(t));
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| +  float* p = static_cast<float*>(TF_TensorData(t));
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| +  *f = *p;
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| +}
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| +
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| +TEST_F(CApiGradientsTest, MultipleCallsToAddGradients) {
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| +  const float X = 3.0f, Y = 7.0f;
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| +  TF_Operation* x = Placeholder(graph_, s_, "x", TF_FLOAT);
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| +  TF_Operation* y = Placeholder(graph_, s_, "y", TF_FLOAT);
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| +  TF_Operation* xy = Mul(x, y, graph_, s_, "xy");
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| +  TF_Output dxy_dx, dxy_dy;
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| +
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| +  TF_Output outputs[1] = {{xy, 0}};
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| +  TF_Output inputs[1] = {{x, 0}};
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| +  TF_AddGradients(graph_, outputs, 1, inputs, 1, nullptr, s_, &dxy_dx);
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| +  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
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| +
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| +  inputs[0] = {y, 0};
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| +  TF_AddGradients(graph_, outputs, 1, inputs, 1, nullptr, s_, &dxy_dy);
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| +  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
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| +
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| +  TF_SessionOptions* opts = TF_NewSessionOptions();
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| +  TF_Session* sess = TF_NewSession(graph_, opts, s_);
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| +  TF_DeleteSessionOptions(opts);
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| +  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
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| +
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| +  TF_Output feeds[] = {{x, 0}, {y, 0}};
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| +  TF_Tensor* feedValues[] = {FloatTensor(X), FloatTensor(Y)};
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| +  TF_Output fetches[] = {dxy_dx, dxy_dy};
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| +  TF_Tensor* fetchValues[] = {nullptr, nullptr};
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| +
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| +  TF_SessionRun(sess, nullptr /* run_options */, feeds, feedValues, 2, fetches,
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| +                fetchValues, 2, nullptr /* target_opers */, 0,
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| +                nullptr /* run_metadata */, s_);
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| +  TF_DeleteTensor(feedValues[0]);
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| +  TF_DeleteTensor(feedValues[1]);
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| +  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
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| +  TF_DeleteSession(sess, s_);
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| +  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
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| +
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| +  float dxy_dxValue = 0.0f, dxy_dyValue = 0.0f;
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| +  ScalarFloatFromTensor(fetchValues[0], &dxy_dxValue);
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| +  EXPECT_EQ(Y, dxy_dxValue);
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| +
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| +  ScalarFloatFromTensor(fetchValues[1], &dxy_dyValue);
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| +  EXPECT_EQ(X, dxy_dyValue);
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| +
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| +  TF_DeleteTensor(fetchValues[0]);
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| +  TF_DeleteTensor(fetchValues[1]);
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| +}
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| +
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|  // REGISTER_OP for CApiAttributesTest test cases.
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|  // Registers two ops, each with a single attribute called 'v'.
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|  // The attribute in one op will have a type 'type', the other
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| @@ -1784,7 +1839,7 @@ TEST_F(CApiAttributesTest, String) {
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|  
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|  TEST_F(CApiAttributesTest, StringList) {
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|    std::vector<string> list = {"bugs", "bunny", "duck"};
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| -  std::unique_ptr<const void* []> list_ptrs;
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| +  std::unique_ptr<const void*[]> list_ptrs;
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|    std::unique_ptr<size_t[]> list_lens;
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|    StringVectorToArrays(list, &list_ptrs, &list_lens);
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|    int list_total_size = 0;
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| @@ -1800,7 +1855,7 @@ TEST_F(CApiAttributesTest, StringList) {
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|    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
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|  
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|    EXPECT_TF_META("v", list.size(), TF_ATTR_STRING, list_total_size);
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| -  std::unique_ptr<void* []> values(new void*[list.size()]);
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| +  std::unique_ptr<void*[]> values(new void*[list.size()]);
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|    std::unique_ptr<size_t[]> lens(new size_t[list.size()]);
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|    std::unique_ptr<char[]> storage(new char[list_total_size]);
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|    TF_OperationGetAttrStringList(oper, "v", values.get(), lens.get(),
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| @@ -2025,7 +2080,7 @@ TEST_F(CApiAttributesTest, TensorShapeProtoList) {
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|    tensorflow::PartialTensorShape(pts2).AsProto(&proto);
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|    proto.SerializeToString(&bytes2);
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|  
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| -  std::unique_ptr<const void* []> list_ptrs;
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| +  std::unique_ptr<const void*[]> list_ptrs;
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|    std::unique_ptr<size_t[]> list_lens;
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|    const std::vector<string> list = {bytes1, bytes2};
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|    StringVectorToArrays(list, &list_ptrs, &list_lens);
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| diff --git a/tensorflow/c/c_test_util.cc b/tensorflow/c/c_test_util.cc
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| index f3b28c1708129..24eb6c069b213 100644
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| --- a/tensorflow/c/c_test_util.cc
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| +++ b/tensorflow/c/c_test_util.cc
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| @@ -216,6 +216,13 @@ TF_Operation* Min(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
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|    return MinWithDevice(l, r, graph, /*op_device=*/"", s, name);
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|  }
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|  
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| +TF_Operation* Mul(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
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| +                  TF_Status* s, const char* name) {
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| +  TF_Operation* op;
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| +  BinaryOpHelper("Mul", l, r, graph, s, name, &op, "", true);
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| +  return op;
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| +}
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| +
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|  TF_Operation* Add(TF_Output l, TF_Output r, TF_Graph* graph, TF_Status* s,
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|                    const char* name) {
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|    TF_OperationDescription* desc = TF_NewOperation(graph, "AddN", name);
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| diff --git a/tensorflow/c/c_test_util.h b/tensorflow/c/c_test_util.h
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| index c16aba666ee69..38313d647ca93 100644
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| --- a/tensorflow/c/c_test_util.h
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| +++ b/tensorflow/c/c_test_util.h
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| @@ -80,6 +80,9 @@ TF_Operation* Add(TF_Output l, TF_Output r, TF_Graph* graph, TF_Status* s,
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|  TF_Operation* Min(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
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|                    TF_Status* s, const char* name = "min");
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|  
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| +TF_Operation* Mul(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
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| +                  TF_Status* s, const char* name = "mul");
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| +
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|  // If `op_device` is non-empty, set the created op on that device.
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|  TF_Operation* MinWithDevice(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
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|                              const string& op_device, TF_Status* s,
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| diff --git a/tensorflow/cc/framework/scope.cc b/tensorflow/cc/framework/scope.cc
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| index 62a889181e787..8c886f31711eb 100644
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| --- a/tensorflow/cc/framework/scope.cc
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| +++ b/tensorflow/cc/framework/scope.cc
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| @@ -37,6 +37,11 @@ Scope& Scope::operator=(const Scope& other) {
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|    return *this;
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|  }
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|  
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| +namespace {
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| +const char kScopeSeparator[] = "/";
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| +const char kSuffixSeparator[] = "_";
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| +}  // namespace
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| +
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|  Scope::Impl::Impl(Graph* graph, Status* status, NameMap* name_map,
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|                    ShapeRefiner* refiner, bool disable_shape_inference)
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|      : graph_(graph),
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| @@ -308,19 +313,23 @@ string Scope::Impl::GetUniqueName(const string& prefix,
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|      return prefix;
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|    }
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|    auto entry = name_map_->find(prefix);
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| -  string unique_name = prefix;
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|    if (entry == name_map_->end()) {
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|      name_map_->insert({prefix, 0});
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| -  } else {
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| -    unique_name = strings::StrCat(unique_name, "_", ++entry->second);
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| +    return prefix;
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|    }
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| +  string unique_name;
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| +  do {
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| +    unique_name = strings::StrCat(prefix, kSuffixSeparator, ++entry->second);
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| +  } while (name_map_->find(unique_name) != name_map_->end());
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| +  name_map_->insert({unique_name, 0});
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|    return unique_name;
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|  }
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|  
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|  string Scope::Impl::GetNameForOp(const string& default_name) const {
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|    const string unique_name =
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|        GetUniqueName(default_name, true /* check_single_use */);
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| -  const string sep = name_.empty() || unique_name.empty() ? "" : "/";
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| +  const string sep =
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| +      name_.empty() || unique_name.empty() ? "" : kScopeSeparator;
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|    return strings::StrCat(name_, sep, unique_name);
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|  }
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|  
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| @@ -345,7 +354,8 @@ Scope Scope::NewSubScope(const string& child_scope_name) const {
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|    }
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|    const string unique_name =
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|        impl()->GetUniqueName(child_scope_name, false /* check_single_use */);
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| -  const string sep = impl()->name_.empty() || unique_name.empty() ? "" : "/";
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| +  const string sep =
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| +      impl()->name_.empty() || unique_name.empty() ? "" : kScopeSeparator;
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|    return Scope(new Impl(*this, Impl::Tags::ScopeName(),
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|                          strings::StrCat(impl()->name_, sep, unique_name),
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|                          false /* copy_names */));
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| @@ -412,7 +422,7 @@ CompositeOpScopes Scope::GetCompositeOpScopes(
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|    if (!impl()->single_use_scope()) {
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|      Scope child = NewSubScope(impl()->op_name_.empty() ? composite_op_name
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|                                                         : impl()->op_name_);
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| -    const string child_op_sep = impl()->name_.empty() ? "" : "_";
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| +    const string child_op_sep = impl()->name_.empty() ? "" : kSuffixSeparator;
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|      const string child_name =
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|          strings::StrCat(impl()->name_, child_op_sep, child.impl()->name_);
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|      return {child,
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| @@ -435,7 +445,13 @@ class InternalScope {
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|    static Scope NewScope(Graph* graph, Status* status, ShapeRefiner* refiner) {
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|      Scope::Impl::NameMap* name_map = new Scope::Impl::NameMap;
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|      for (const Node* node : graph->nodes()) {
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| -      (*name_map)[node->name()] = 0;
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| +      const string& name = node->name();
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| +      (*name_map)[name] = 0;
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| +      // Add all name prefixes ('/' separated).
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| +      size_t idx = -1;
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| +      while ((idx = name.find(kScopeSeparator, idx + 1)) != string::npos) {
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| +        (*name_map)[name.substr(0, idx)] = 0;
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| +      }
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|      }
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|      // We provide null destructors for these shared ptrs (except for name_map)
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|      // since the caller owns them and doesn't want the scope to destroy them.
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| diff --git a/tensorflow/cc/framework/scope_internal.h b/tensorflow/cc/framework/scope_internal.h
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| index 8efcfed20d0b8..58adaef2e942a 100644
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| --- a/tensorflow/cc/framework/scope_internal.h
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| +++ b/tensorflow/cc/framework/scope_internal.h
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| @@ -34,8 +34,7 @@ class Scope::Impl {
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|    // name that has not been used so far in a scope will get no suffix. Later
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|    // uses of the same name will get suffixes _1, _2, _3, etc. Multiple scopes
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|    // can share the same NameMap. For instance, a new scope created using
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| -  // WithControlDependencies() should would share the same NameMap with the
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| -  // parent.
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| +  // WithControlDependencies() would share the same NameMap with the parent.
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|    typedef std::unordered_map<string, int> NameMap;
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|  
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|    Impl(const std::shared_ptr<Graph>& graph,
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| diff --git a/tensorflow/cc/framework/scope_test.cc b/tensorflow/cc/framework/scope_test.cc
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| index 9eca9d3face34..b40b345eb8423 100644
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| --- a/tensorflow/cc/framework/scope_test.cc
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| +++ b/tensorflow/cc/framework/scope_test.cc
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| @@ -26,6 +26,16 @@ TEST(ScopeTest, BasicNames) {
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|    EXPECT_EQ(root.GetUniqueNameForOp("mul"), "mul");
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|  }
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|  
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| +TEST(ScopeTest, OpAndScopeNameCollision) {
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| +  Scope root = Scope::NewRootScope();
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| +  EXPECT_EQ(root.GetUniqueNameForOp("foo"), "foo");
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| +  EXPECT_EQ(root.GetUniqueNameForOp("foo"), "foo_1");
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| +  EXPECT_EQ(root.GetUniqueNameForOp("foo_1"), "foo_1_1");
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| +  EXPECT_EQ(root.GetUniqueNameForOp("foo_2"), "foo_2");
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| +  EXPECT_EQ(root.GetUniqueNameForOp("foo"), "foo_3");
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| +  EXPECT_EQ(root.GetUniqueNameForOp("foo_2"), "foo_2_1");
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| +}
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| +
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|  TEST(ScopeTest, HierarchicalNames) {
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|    Scope root = Scope::NewRootScope();
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|    Scope child = root.NewSubScope("child");
 |