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Fix the issue described by #106769 #108340

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Fix the issue described by #106769 #108340

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3b6991f
Fix the issue described by #106769
FFFrog Aug 31, 2023
73c6576
add some tests on raising error
FFFrog Sep 6, 2023
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2 changes: 1 addition & 1 deletion aten/src/ATen/native/RNN.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -1552,7 +1552,7 @@ std::tuple<Tensor, Tensor> lstm_cell(
check_rnn_cell_forward_input(input, w_ih.sym_size(1));
auto hidden_size = w_hh.sym_size(1);
check_rnn_cell_forward_hidden(input, hx[0], hidden_size, 0);
check_rnn_cell_forward_hidden(input, hx[1], std::move(hidden_size), 0);
check_rnn_cell_forward_hidden(input, hx[1], std::move(hidden_size), 1);
static at::Tensor undefined;
return LSTMCell<CellParams>{}(input, std::make_tuple(hx[0], hx[1]), CellParams{w_ih, w_hh, b_ih, b_hh, undefined});
}
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150 changes: 144 additions & 6 deletions test/cpp/api/modules.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -4355,6 +4355,7 @@ TEST_F(ModulesTest, CrossMapLRN2d) {
TEST_F(ModulesTest, RNNCell) {
torch::manual_seed(0);
auto rnn = RNNCell(1, 2);

auto input = torch::randn({3, 1});
auto hx = torch::randn({3, 2});
auto output = rnn(input, hx);
Expand All @@ -4366,15 +4367,51 @@ TEST_F(ModulesTest, RNNCell) {
expected =
torch::tensor({{-0.0775, 0.6688}, {-0.0734, 0.4759}, {-0.0725, 0.4225}});
ASSERT_TRUE(torch::allclose(output, expected, 1e-05, 2e-04));

input = torch::randn({1});
hx = torch::randn({2});
output = rnn(input, hx);
expected = torch::tensor({0.2808, 0.6505});
ASSERT_TRUE(torch::allclose(output, expected, 1e-05, 2e-04));

{
auto input = torch::randn({3, 2});
auto hx = torch::randn({3, 2});
ASSERT_THROWS_WITH(
rnn(input, hx), "input has inconsistent input_size: got 2 expected 1");
}

{
auto input = torch::randn({3, 1});
auto hx = torch::randn({3, 1});
ASSERT_THROWS_WITH(
rnn(input, hx),
"hidden0 has inconsistent hidden_size: got 1, expected 2");
}

{
auto input = torch::randn({3, 1, 1, 1, 1});
auto hx = torch::randn({3, 2});
ASSERT_THROWS_WITH(
rnn(input, hx), "Expected input to be 1D or 2D, got 5D instead");
}

{
auto input = torch::randn({3, 1});
auto hx = torch::randn({3, 1, 1, 1, 2});
ASSERT_THROWS_WITH(
rnn(input, hx), "Expected hidden to be 1D or 2D, got 5D instead");
}
}

TEST_F(ModulesTest, LSTMCell) {
torch::manual_seed(0);
auto rnn = LSTMCell(1, 2);
auto lstm = LSTMCell(1, 2);

auto input = torch::randn({3, 1});
auto hx = torch::randn({3, 2});
auto cx = torch::randn({3, 2});
auto output = rnn(input, std::make_tuple(hx, cx));
auto output = lstm(input, std::make_tuple(hx, cx));
auto output_hx = std::get<0>(output);
auto output_cx = std::get<1>(output);
auto expected_hx =
Expand All @@ -4384,7 +4421,7 @@ TEST_F(ModulesTest, LSTMCell) {
ASSERT_TRUE(torch::allclose(output_hx, expected_hx, 1e-05, 2e-04));
ASSERT_TRUE(torch::allclose(output_cx, expected_cx, 1e-05, 2e-04));

output = rnn(input);
output = lstm(input);
output_hx = std::get<0>(output);
output_cx = std::get<1>(output);
expected_hx =
Expand All @@ -4393,22 +4430,123 @@ TEST_F(ModulesTest, LSTMCell) {
torch::tensor({{-0.2679, 0.2180}, {-0.3049, 0.3493}, {-0.2896, 0.2853}});
ASSERT_TRUE(torch::allclose(output_hx, expected_hx, 1e-05, 2e-04));
ASSERT_TRUE(torch::allclose(output_cx, expected_cx, 1e-05, 2e-04));

input = torch::randn({1});
hx = torch::randn({2});
cx = torch::randn({2});
output = lstm(input, std::make_tuple(hx, cx));
output_hx = std::get<0>(output);
output_cx = std::get<1>(output);
expected_hx = torch::tensor({-0.0443, 0.1537});
expected_cx = torch::tensor({-0.1195, 0.2144});
ASSERT_TRUE(torch::allclose(output_hx, expected_hx, 1e-05, 2e-04));
ASSERT_TRUE(torch::allclose(output_cx, expected_cx, 1e-05, 2e-04));

{
auto input = torch::randn({3, 2});
auto hx = torch::randn({3, 2});
auto cx = torch::randn({3, 2});
ASSERT_THROWS_WITH(
lstm(input, std::make_tuple(hx, cx)),
"input has inconsistent input_size: got 2 expected 1");
}

{
auto input = torch::randn({3, 1});
auto hx = torch::randn({3, 1});
auto cx = torch::randn({3, 2});
ASSERT_THROWS_WITH(
lstm(input, std::make_tuple(hx, cx)),
"hidden0 has inconsistent hidden_size: got 1, expected 2");
}

{
auto input = torch::randn({3, 1});
auto hx = torch::randn({3, 2});
auto cx = torch::randn({3, 1});
ASSERT_THROWS_WITH(
lstm(input, std::make_tuple(hx, cx)),
"hidden1 has inconsistent hidden_size: got 1, expected 2");
}

{
auto input = torch::randn({3, 1, 1, 1, 1});
auto hx = torch::randn({3, 1});
auto cx = torch::randn({3, 1});
ASSERT_THROWS_WITH(
lstm(input, std::make_tuple(hx, cx)),
"Expected input to be 1D or 2D, got 5D instead");
}

{
auto input = torch::randn({3, 1});
auto hx = torch::randn({3, 1, 1, 1, 2});
auto cx = torch::randn({3, 2});
ASSERT_THROWS_WITH(
lstm(input, std::make_tuple(hx, cx)),
"Expected hx[0] to be 1D or 2D, got 5D instead");
}

{
auto input = torch::randn({3, 1});
auto hx = torch::randn({3, 2});
auto cx = torch::randn({3, 1, 1, 1, 2});
ASSERT_THROWS_WITH(
lstm(input, std::make_tuple(hx, cx)),
"Expected hx[1] to be 1D or 2D, got 5D instead");
}
}

TEST_F(ModulesTest, GRUCell) {
torch::manual_seed(0);
auto rnn = GRUCell(1, 2);
auto gru = GRUCell(1, 2);

auto input = torch::randn({3, 1});
auto hx = torch::randn({3, 2});
auto output = rnn(input, hx);
auto output = gru(input, hx);
auto expected =
torch::tensor({{1.0243, 0.3227}, {-0.5659, 0.0330}, {-0.4030, -0.2800}});
ASSERT_TRUE(torch::allclose(output, expected, 1e-05, 2e-04));

output = rnn(input);
output = gru(input);
expected =
torch::tensor({{-0.0085, 0.1095}, {-0.1291, 0.2675}, {-0.1339, 0.2725}});
ASSERT_TRUE(torch::allclose(output, expected, 1e-05, 2e-04));

input = torch::randn({1});
hx = torch::randn({2});
output = gru(input, hx);
expected = torch::tensor({-1.0058, -0.3025});
ASSERT_TRUE(torch::allclose(output, expected, 1e-05, 2e-04));

{
auto input = torch::randn({3, 2});
auto hx = torch::randn({3, 2});
ASSERT_THROWS_WITH(
gru(input, hx), "input has inconsistent input_size: got 2 expected 1");
}

{
auto input = torch::randn({3, 1});
auto hx = torch::randn({3, 1});
ASSERT_THROWS_WITH(
gru(input, hx),
"hidden0 has inconsistent hidden_size: got 1, expected 2");
}

{
auto input = torch::randn({3, 1, 1, 1, 1});
auto hx = torch::randn({3, 2});
ASSERT_THROWS_WITH(
gru(input, hx), "Expected input to be 1D or 2D, got 5D instead");
}

{
auto input = torch::randn({3, 1});
auto hx = torch::randn({3, 1, 1, 1, 2});
ASSERT_THROWS_WITH(
gru(input, hx), "Expected hidden to be 1D or 2D, got 5D instead");
}
}

TEST_F(ModulesTest, PrettyPrintLinear) {
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6 changes: 1 addition & 5 deletions torch/csrc/api/include/torch/nn/modules/rnn.h
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Expand Up @@ -277,11 +277,7 @@ class TORCH_API RNNCellImplBase : public torch::nn::Cloneable<Derived> {
Tensor bias_hh;

protected:
void check_forward_input(const Tensor& input) const;
void check_forward_hidden(
const Tensor& input,
const Tensor& hx,
std::string hidden_label) const;
void check_forward_input(const Tensor& input, const std::string name) const;
virtual std::string get_nonlinearity_str() const;
};
} // namespace detail
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