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Commit 07cd0762 authored by Shucai Xiao's avatar Shucai Xiao
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code clean up for rnn test examples.

parent 9b422c28
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Showing with 200 additions and 239 deletions
test/cpu_rnn_ops_test.cpp
View file @ 07cd0762
......@@ -15,55 +15,56 @@ TEST_CASE(rnn_forward)
std::size_t hidden_size = 4;
std::size_t input_size = 3;
std::size_t num_dirct = 1;
std::vector<float> wf_data{0.4691,
0.3185,
-0.2227,
0.4423,
-0.0609,
-0.2803,
0.1744,
0.3146,
0.4049,
-0.3973,
-0.0890,
-0.1636};
std::vector<float> rf_data{-0.0456,
0.1061,
0.1574,
-0.4928,
-0.4300,
-0.1909,
-0.0225,
-0.2668,
0.1840,
-0.4453,
-0.4896,
0.1302,
-0.0929,
0.3545,
-0.4981,
0.0616};
std::vector<float> biasf_data{
std::vector<float> w_data{0.4691,
0.3185,
-0.2227,
0.4423,
-0.0609,
-0.2803,
0.1744,
0.3146,
0.4049,
-0.3973,
-0.0890,
-0.1636};
std::vector<float> r_data{-0.0456,
0.1061,
0.1574,
-0.4928,
-0.4300,
-0.1909,
-0.0225,
-0.2668,
0.1840,
-0.4453,
-0.4896,
0.1302,
-0.0929,
0.3545,
-0.4981,
0.0616};
std::vector<float> bias_data{
-0.4938, 0.4355, -0.3186, 0.2094, 0.1037, -0.1071, 0.4504, -0.3990};
std::vector<float> ih_data(num_dirct * batch_size * hidden_size, 0);
std::vector<float> input(seq_len * batch_size * input_size, 0);
input[0] = input[1] = 1.0;
float clip = 0.0f;
migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, hidden_size, input_size}};
migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, hidden_size, hidden_size}};
migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 2 * hidden_size}};
float clip = 0.0f;
// concatenation of hidden states as program output
{
std::vector<float> ih_data(num_dirct * batch_size * hidden_size, 0);
migraphx::program p;
migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
auto seq = p.add_literal(migraphx::literal{in_shape, input});
migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
auto ih = p.add_literal(migraphx::literal{ih_shape, ih_data});
migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, hidden_size, input_size}};
auto w = p.add_literal(migraphx::literal{w_shape, wf_data});
migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, hidden_size, hidden_size}};
auto r = p.add_literal(migraphx::literal{r_shape, rf_data});
migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 2 * hidden_size}};
auto bias = p.add_literal(migraphx::literal{b_shape, biasf_data});
auto seq = p.add_literal(migraphx::literal{in_shape, input});
auto ih = p.add_literal(migraphx::literal{ih_shape, ih_data});
auto w = p.add_literal(migraphx::literal{w_shape, w_data});
auto r = p.add_literal(migraphx::literal{r_shape, r_data});
auto bias = p.add_literal(migraphx::literal{b_shape, bias_data});
auto und = p.add_instruction(migraphx::op::undefined{});
p.add_instruction(migraphx::op::rnn{hidden_size,
......@@ -100,22 +101,14 @@ TEST_CASE(rnn_forward)
EXPECT(migraphx::verify_range(hs_data, hs_data_gold));
}
// rnn last output as program output
{
std::vector<float> ih_data(num_dirct * batch_size * hidden_size, 0);
migraphx::program p;
migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
auto seq = p.add_literal(migraphx::literal{in_shape, input});
migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
auto ih = p.add_literal(migraphx::literal{ih_shape, ih_data});
migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, hidden_size, input_size}};
auto w = p.add_literal(migraphx::literal{w_shape, wf_data});
migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, hidden_size, hidden_size}};
auto r = p.add_literal(migraphx::literal{r_shape, rf_data});
migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 2 * hidden_size}};
auto bias = p.add_literal(migraphx::literal{b_shape, biasf_data});
auto seq = p.add_literal(migraphx::literal{in_shape, input});
auto ih = p.add_literal(migraphx::literal{ih_shape, ih_data});
auto w = p.add_literal(migraphx::literal{w_shape, w_data});
auto r = p.add_literal(migraphx::literal{r_shape, r_data});
auto bias = p.add_literal(migraphx::literal{b_shape, bias_data});
auto und = p.add_instruction(migraphx::op::undefined{});
auto out_hs =
......@@ -144,6 +137,27 @@ TEST_CASE(rnn_forward)
-0.11893477};
EXPECT(migraphx::verify_range(last_output_data, last_output_data_gold));
}
// 3 args
{
migraphx::program p;
auto seq = p.add_literal(migraphx::literal{in_shape, input});
auto w = p.add_literal(migraphx::literal{w_shape, w_data});
auto r = p.add_literal(migraphx::literal{r_shape, r_data});
auto out_hs = p.add_instruction(
migraphx::op::rnn{hidden_size, {}, migraphx::op::rnn::forward, clip}, seq, w, r);
p.add_instruction(migraphx::op::rnn_last_output{}, out_hs);
p.compile(migraphx::cpu::target{});
auto last_output = p.eval({});
std::vector<float> last_output_data;
last_output.visit([&](auto out) { last_output_data.assign(out.begin(), out.end()); });
std::vector<float> last_output_data_gold{
0.2935145, -0.23719997, -0.31123261, -0.18357255, 0., 0., 0., 0.};
EXPECT(migraphx::verify_range(last_output_data, last_output_data_gold));
}
}
TEST_CASE(rnn_reverse)
......@@ -153,60 +167,56 @@ TEST_CASE(rnn_reverse)
std::size_t hidden_size = 4;
std::size_t input_size = 3;
std::size_t num_dirct = 1;
std::vector<float> wr_data{-0.0296,
-0.1341,
0.1761,
-0.2325,
-0.0717,
0.1852,
0.2720,
0.1471,
-0.1097,
0.3363,
-0.0587,
-0.2302};
std::vector<float> rr_data{0.2528,
-0.2333,
0.3973,
0.1593,
-0.0388,
0.1702,
0.3829,
-0.0712,
-0.1668,
0.3074,
-0.2854,
0.4049,
-0.3737,
-0.1051,
0.4482,
-0.2841};
std::vector<float> biasr_data{-0.3188, 0.1341, -0.4446, 0.1389, 0.3117, 0.3664, 0.2352, 0.2552};
std::vector<float> w_data{-0.0296,
-0.1341,
0.1761,
-0.2325,
-0.0717,
0.1852,
0.2720,
0.1471,
-0.1097,
0.3363,
-0.0587,
-0.2302};
std::vector<float> r_data{0.2528,
-0.2333,
0.3973,
0.1593,
-0.0388,
0.1702,
0.3829,
-0.0712,
-0.1668,
0.3074,
-0.2854,
0.4049,
-0.3737,
-0.1051,
0.4482,
-0.2841};
std::vector<float> bias_data{-0.3188, 0.1341, -0.4446, 0.1389, 0.3117, 0.3664, 0.2352, 0.2552};
std::vector<float> input(seq_len * batch_size * input_size, 0);
input[0] = input[1] = 1.0;
float clip = 0.0f;
std::vector<float> ih_data(num_dirct * batch_size * hidden_size, 0);
float clip = 0.0f;
migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, hidden_size, input_size}};
migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, hidden_size, hidden_size}};
migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 2 * hidden_size}};
migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
// concatenation of hidden states as program output
{
std::vector<float> ih_data(num_dirct * batch_size * hidden_size, 0);
migraphx::program p;
migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
auto seq = p.add_literal(migraphx::literal{in_shape, input});
migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
auto ih = p.add_literal(migraphx::literal{ih_shape, ih_data});
migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, hidden_size, input_size}};
auto w = p.add_literal(migraphx::literal{w_shape, wr_data});
migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, hidden_size, hidden_size}};
auto r = p.add_literal(migraphx::literal{r_shape, rr_data});
migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 2 * hidden_size}};
auto bias = p.add_literal(migraphx::literal{b_shape, biasr_data});
auto seq = p.add_literal(migraphx::literal{in_shape, input});
auto ih = p.add_literal(migraphx::literal{ih_shape, ih_data});
auto w = p.add_literal(migraphx::literal{w_shape, w_data});
auto r = p.add_literal(migraphx::literal{r_shape, r_data});
auto bias = p.add_literal(migraphx::literal{b_shape, bias_data});
auto und = p.add_instruction(migraphx::op::undefined{});
p.add_instruction(migraphx::op::rnn{hidden_size,
{migraphx::op::tanh{}, migraphx::op::tanh{}},
migraphx::op::rnn::reverse,
clip},
p.add_instruction(migraphx::op::rnn{hidden_size, {}, migraphx::op::rnn::reverse, clip},
seq,
w,
r,
......@@ -237,22 +247,14 @@ TEST_CASE(rnn_reverse)
EXPECT(migraphx::verify_range(hs_data, hs_data_gold));
}
// rnn last output as program output
{
std::vector<float> ih_data(num_dirct * batch_size * hidden_size, 0);
migraphx::program p;
migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
auto seq = p.add_literal(migraphx::literal{in_shape, input});
migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
auto ih = p.add_literal(migraphx::literal{ih_shape, ih_data});
migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, hidden_size, input_size}};
auto w = p.add_literal(migraphx::literal{w_shape, wr_data});
migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, hidden_size, hidden_size}};
auto r = p.add_literal(migraphx::literal{r_shape, rr_data});
migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 2 * hidden_size}};
auto bias = p.add_literal(migraphx::literal{b_shape, biasr_data});
auto seq = p.add_literal(migraphx::literal{in_shape, input});
auto ih = p.add_literal(migraphx::literal{ih_shape, ih_data});
auto w = p.add_literal(migraphx::literal{w_shape, w_data});
auto r = p.add_literal(migraphx::literal{r_shape, r_data});
auto bias = p.add_literal(migraphx::literal{b_shape, bias_data});
auto und = p.add_instruction(migraphx::op::undefined{});
auto out_hs =
......@@ -290,94 +292,54 @@ TEST_CASE(rnn_bidirectional)
std::size_t hidden_size = 4;
std::size_t input_size = 3;
std::size_t num_dirct = 2;
std::vector<float> wf_data{0.4691,
0.3185,
-0.2227,
0.4423,
-0.0609,
-0.2803,
0.1744,
0.3146,
0.4049,
-0.3973,
-0.0890,
-0.1636};
std::vector<float> wr_data{-0.0296,
-0.1341,
0.1761,
-0.2325,
-0.0717,
0.1852,
0.2720,
0.1471,
-0.1097,
0.3363,
-0.0587,
-0.2302};
std::vector<float> rf_data{-0.0456,
0.1061,
0.1574,
-0.4928,
-0.4300,
-0.1909,
-0.0225,
-0.2668,
0.1840,
-0.4453,
-0.4896,
0.1302,
-0.0929,
0.3545,
-0.4981,
0.0616};
std::vector<float> rr_data{0.2528,
-0.2333,
0.3973,
0.1593,
-0.0388,
0.1702,
0.3829,
-0.0712,
-0.1668,
0.3074,
-0.2854,
0.4049,
-0.3737,
-0.1051,
0.4482,
-0.2841};
std::vector<float> biasf_data{
-0.4938, 0.4355, -0.3186, 0.2094, 0.1037, -0.1071, 0.4504, -0.3990};
std::vector<float> biasr_data{-0.3188, 0.1341, -0.4446, 0.1389, 0.3117, 0.3664, 0.2352, 0.2552};
std::vector<float> w_data{0.4691, 0.3185, -0.2227, 0.4423, -0.0609, -0.2803,
0.1744, 0.3146, 0.4049, -0.3973, -0.0890, -0.1636,
-0.0296, -0.1341, 0.1761, -0.2325, -0.0717, 0.1852,
0.2720, 0.1471, -0.1097, 0.3363, -0.0587, -0.2302};
std::vector<float> r_data{-0.0456, 0.1061, 0.1574, -0.4928, -0.4300, -0.1909, -0.0225,
-0.2668, 0.1840, -0.4453, -0.4896, 0.1302, -0.0929, 0.3545,
-0.4981, 0.0616, 0.2528, -0.2333, 0.3973, 0.1593, -0.0388,
0.1702, 0.3829, -0.0712, -0.1668, 0.3074, -0.2854, 0.4049,
-0.3737, -0.1051, 0.4482, -0.2841};
std::vector<float> bias_data{-0.4938,
0.4355,
-0.3186,
0.2094,
0.1037,
-0.1071,
0.4504,
-0.3990,
-0.3188,
0.1341,
-0.4446,
0.1389,
0.3117,
0.3664,
0.2352,
0.2552};
std::vector<float> input(seq_len * batch_size * input_size, 0);
input[0] = input[1] = 1.0;
float clip = 0.0f;
std::vector<float> ih_data(num_dirct * batch_size * hidden_size, 0);
migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, hidden_size, input_size}};
migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, hidden_size, hidden_size}};
migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 2 * hidden_size}};
float clip = 0.0f;
// concatenation of hidden state for program output
{
std::vector<float> ih_data(num_dirct * batch_size * hidden_size, 0);
migraphx::program p;
migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
auto seq = p.add_literal(migraphx::literal{in_shape, input});
migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
auto ih = p.add_literal(migraphx::literal{ih_shape, ih_data});
auto w_data = wf_data;
w_data.insert(w_data.end(), wr_data.begin(), wr_data.end());
migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, hidden_size, input_size}};
auto w = p.add_literal(migraphx::literal{w_shape, w_data});
auto r_data = rf_data;
r_data.insert(r_data.end(), rr_data.begin(), rr_data.end());
migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, hidden_size, hidden_size}};
auto r = p.add_literal(migraphx::literal{r_shape, r_data});
auto bias_data = biasf_data;
bias_data.insert(bias_data.end(), biasr_data.begin(), biasr_data.end());
migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 2 * hidden_size}};
auto seq = p.add_literal(migraphx::literal{in_shape, input});
auto ih = p.add_literal(migraphx::literal{ih_shape, ih_data});
auto w = p.add_literal(migraphx::literal{w_shape, w_data});
auto r = p.add_literal(migraphx::literal{r_shape, r_data});
auto bias = p.add_literal(migraphx::literal{b_shape, bias_data});
auto und = p.add_instruction(migraphx::op::undefined{});
p.add_instruction(
migraphx::op::rnn{hidden_size, {}, migraphx::op::rnn::bidirectional, clip},
seq,
......@@ -400,30 +362,13 @@ TEST_CASE(rnn_bidirectional)
-0.20639211, 0.37488942};
EXPECT(migraphx::verify_range(hs_data, hs_data_gold));
}
// last rnn output for program output
{
std::vector<float> ih_data(num_dirct * batch_size * hidden_size, 0);
migraphx::program p;
migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
auto seq = p.add_literal(migraphx::literal{in_shape, input});
migraphx::shape ih_shape{migraphx::shape::float_type, {num_dirct, batch_size, hidden_size}};
auto ih = p.add_literal(migraphx::literal{ih_shape, ih_data});
auto w_data = wf_data;
w_data.insert(w_data.end(), wr_data.begin(), wr_data.end());
migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, hidden_size, input_size}};
auto w = p.add_literal(migraphx::literal{w_shape, w_data});
auto r_data = rf_data;
r_data.insert(r_data.end(), rr_data.begin(), rr_data.end());
migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, hidden_size, hidden_size}};
auto r = p.add_literal(migraphx::literal{r_shape, r_data});
auto bias_data = biasf_data;
bias_data.insert(bias_data.end(), biasr_data.begin(), biasr_data.end());
migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 2 * hidden_size}};
auto seq = p.add_literal(migraphx::literal{in_shape, input});
auto ih = p.add_literal(migraphx::literal{ih_shape, ih_data});
auto w = p.add_literal(migraphx::literal{w_shape, w_data});
auto r = p.add_literal(migraphx::literal{r_shape, r_data});
auto bias = p.add_literal(migraphx::literal{b_shape, bias_data});
auto und = p.add_instruction(migraphx::op::undefined{});
......@@ -463,26 +408,13 @@ TEST_CASE(rnn_bidirectional)
EXPECT(migraphx::verify_range(last_output_data, last_output_data_gold));
}
{
std::vector<float> ih_data(num_dirct * batch_size * hidden_size, 0);
// 4 args
{
migraphx::program p;
migraphx::shape in_shape{migraphx::shape::float_type, {seq_len, batch_size, input_size}};
auto seq = p.add_literal(migraphx::literal{in_shape, input});
auto w_data = wf_data;
w_data.insert(w_data.end(), wr_data.begin(), wr_data.end());
migraphx::shape w_shape{migraphx::shape::float_type, {num_dirct, hidden_size, input_size}};
auto w = p.add_literal(migraphx::literal{w_shape, w_data});
auto r_data = rf_data;
r_data.insert(r_data.end(), rr_data.begin(), rr_data.end());
migraphx::shape r_shape{migraphx::shape::float_type, {num_dirct, hidden_size, hidden_size}};
auto r = p.add_literal(migraphx::literal{r_shape, r_data});
auto bias_data = biasf_data;
bias_data.insert(bias_data.end(), biasr_data.begin(), biasr_data.end());
migraphx::shape b_shape{migraphx::shape::float_type, {num_dirct, 2 * hidden_size}};
auto seq = p.add_literal(migraphx::literal{in_shape, input});
auto w = p.add_literal(migraphx::literal{w_shape, w_data});
auto r = p.add_literal(migraphx::literal{r_shape, r_data});
auto bias = p.add_literal(migraphx::literal{b_shape, bias_data});
auto out_hs =
......@@ -521,6 +453,35 @@ TEST_CASE(rnn_bidirectional)
EXPECT(migraphx::verify_range(last_output_data, last_output_data_gold));
}
// 3 args
{
migraphx::program p;
auto seq = p.add_literal(migraphx::literal{in_shape, input});
auto w = p.add_literal(migraphx::literal{w_shape, w_data});
auto r = p.add_literal(migraphx::literal{r_shape, r_data});
p.add_instruction(migraphx::op::rnn{hidden_size,
{migraphx::op::tanh{}, migraphx::op::tanh{}},
migraphx::op::rnn::bidirectional,
clip},
seq,
w,
r);
p.compile(migraphx::cpu::target{});
auto last_output = p.eval({});
std::vector<float> last_output_data;
last_output.visit([&](auto out) { last_output_data.assign(out.begin(), out.end()); });
std::vector<float> last_output_data_gold{
0.6570473, 0.36392266, 0.45342238, -0.45127486, 0., 0., 0., 0.,
-0.16225325, -0.29515147, 0.39617197, 0.27068236, 0., 0., 0., 0.,
0.2935145, -0.23719997, -0.31123261, -0.18357255, 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0.};
EXPECT(migraphx::verify_range(last_output_data, last_output_data_gold));
}
}
TEST_CASE(gru_forward)
......
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