Function RunMinTest

tensorflow/c/c_api_test.cc:1000–1040

If `device` is non-empty, run Min op on that device. Otherwise run it on the default device (CPU).

// If `device` is non-empty, run Min op on that device.
// Otherwise run it on the default device (CPU).
void RunMinTest(const string& device, bool use_XLA) {
  TF_Status* s = TF_NewStatus();
  TF_Graph* graph = TF_NewGraph();

  // Make a placeholder operation.
  TF_Operation* feed = Placeholder(graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Make a constant operation with the scalar "0", for axis.
  TF_Operation* one = ScalarConst(0, graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Create a session for this graph.
  CSession csession(graph, s, use_XLA);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  if (!device.empty()) {
    LOG(INFO) << "Setting op Min on device " << device;
  }
  TF_Operation* min = MinWithDevice(feed, one, graph, device, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Run the graph.
  csession.SetInputs({{feed, Int32Tensor({3, 2, 5})}});
  csession.SetOutputs({min});
  csession.Run(s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_Tensor* out = csession.output_tensor(0);
  ASSERT_TRUE(out != nullptr);
  EXPECT_EQ(TF_INT32, TF_TensorType(out));
  EXPECT_EQ(0, TF_NumDims(out));  // scalar
  ASSERT_EQ(sizeof(int32), TF_TensorByteSize(out));
  int32* output_contents = static_cast<int32*>(TF_TensorData(out));
  EXPECT_EQ(2, *output_contents);

  // Clean up
  csession.CloseAndDelete(s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_DeleteGraph(graph);
  TF_DeleteStatus(s);
}

TEST(CAPI, Session_Min_CPU) { RunMinTest(/*device=*/"", /*use_XLA=*/false); }