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Fix initial value of loop variable in RNN op (#4055)

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Hariharan Seshadri 2020-05-28 19:19:39 -07:00 committed by GitHub
parent 6d03470587
commit c55634d2e6
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2 changed files with 34 additions and 3 deletions
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5
onnxruntime/core/providers/cpu/rnn/rnn.h
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@ -35,8 +35,9 @@ class RNN : public OpKernel {
}
ORT_ENFORCE(activations_.size() == static_cast<size_t>(num_directions));
for (int direction = 1; direction < num_directions; direction++) {
ORT_ENFORCE(allowed_activations.find(activations_[direction]) != allowed_activations.end());
for (int direction = 0; direction < num_directions; direction++) {
ORT_ENFORCE(allowed_activations.find(activations_[direction]) != allowed_activations.end(),
"RNN op: Invalid activation attribute - ", activations_[direction]);
}
}

32
onnxruntime/test/providers/cpu/rnn/rnn_op_test.cc
View file

@ -430,7 +430,7 @@ TEST(RNNTest, RNN_bidirectional_1) {
std::vector<int64_t> R_dims = {num_directions, hidden_size, hidden_size};
std::vector<float> R_data({// forward
1.0F, 1.0F,
1.0F, 1.0F,
1.0F, 1.0F,
// reverse
1.0F, 1.0F,
1.0F, 1.0F});
@ -837,5 +837,35 @@ TEST(RNNTest, RNN_bidirectional_with_sequence_lens) {
test.Run(OpTester::ExpectResult::kExpectSuccess, "", {kCudaExecutionProvider, kTensorrtExecutionProvider});
}
TEST(RNNTest, RNN_with_invalid_activation_load_failure) {
OpTester test("RNN");
int64_t num_directions = 1, input_size = 1, hidden_size = 1, seq_length = 1;
test.AddAttribute("activations", vector<string>(num_directions, "Invalid_activation"));
test.AddAttribute("direction", "reverse");
test.AddAttribute("hidden_size", hidden_size);
int batch_size = 1;
std::vector<int64_t> X_dims = {seq_length, batch_size, input_size};
std::vector<float> X_data{0.F};
test.AddInput<float>("X", X_dims, X_data);
std::vector<int64_t> W_dims = {num_directions, hidden_size, input_size};
std::vector<float> W_data({0.F});
test.AddInput<float>("W", W_dims, W_data);
std::vector<int64_t> R_dims = {num_directions, hidden_size, hidden_size};
std::vector<float> R_data({0.F});
test.AddInput<float>("R", R_dims, R_data);
std::vector<int64_t> Y_dims = {seq_length, num_directions, batch_size, hidden_size};
std::vector<float> Y_data({0.F});
test.AddOutput<float>("Y", Y_dims, Y_data);
test.Run(OpTester::ExpectResult::kExpectFailure, "RNN op: Invalid activation attribute - Invalid_activation",
{kCudaExecutionProvider, kTensorrtExecutionProvider});
}
} // namespace test
} // namespace onnxruntime