import unittest from paddle.v2.fluid.framework import Program from paddle.v2.fluid.framework import g_main_program class TestProgram(unittest.TestCase): def test_program(self): b = g_main_program.current_block() self.assertEqual(-1, b.parent_idx) self.assertEqual(0, b.idx) b = g_main_program.create_block() self.assertEqual(1, b.idx) self.assertEqual(0, b.parent_idx) b = g_main_program.create_block() self.assertEqual(2, b.idx) self.assertEqual(1, b.parent_idx) g_main_program.rollback() b = g_main_program.current_block() self.assertEqual(1, b.idx) self.assertEqual(0, b.parent_idx) b = g_main_program.create_block() self.assertEqual(3, b.idx) self.assertEqual(1, b.parent_idx) g_main_program.rollback() b = g_main_program.current_block() self.assertEqual(1, b.idx) self.assertEqual(0, b.parent_idx) def test_program_clone(self): prog = Program() x = prog.global_block().create_var( name='X', shape=[1000, 784], dtype='float32') y = prog.global_block().create_var( name='Y', shape=[784, 100], dtype='float32') out = prog.global_block().create_var(name='Out', dtype='float32') prog.global_block().append_op( type="mul", inputs={'X': [x], 'Y': [y]}, outputs={'Out': [out]}) # FIXME(yuyang18): We manual compare the output string, since the order # of variable could be changed. print prog print prog.clone() def test_parse_program_from_string(self): prog = Program() x = prog.global_block().create_var( name='X', shape=[1000, 784], dtype='float32') y = prog.global_block().create_var( name='Y', shape=[784, 100], dtype='float32') out = prog.global_block().create_var(name='Out', dtype='float32') prog.global_block().append_op( type="mul", inputs={'X': [x], 'Y': [y]}, outputs={'Out': [out]}) binary_str = prog.desc.serialize_to_string() prog_restored = Program.parse_from_string(binary_str) print prog print prog_restored def test_append_backward(self): prog = Program() block = prog.global_block() mul_x = block.create_var( dtype="float32", shape=[5, 10], lod_level=0, name="mul.x") mul_y = block.create_var( dtype="float32", shape=[10, 8], lod_level=0, name="mul.y") mul_out = block.create_var( dtype="float32", shape=[5, 8], lod_level=0, name="mul.out") mul_op = block.append_op( type="mul", inputs={"X": [mul_x], "Y": mul_y}, outputs={"Out": [mul_out]}, attrs={"x_num_col_dims": 1}) add_y = block.create_var( dtype="float32", shape=[5, 8], lod_level=0, name="add.y") add_out = block.create_var( dtype="float32", shape=[5, 8], lod_level=0, name="add.out") add_op = block.append_op( type="elementwise_add", inputs={"X": mul_out, "Y": add_y}, outputs={"Out": add_out}, attrs={"x_num_col_dims": 1}) mean_out = block.create_var( dtype="float32", shape=[1], lod_level=0, name="mean.out") block.append_op( type="mean", inputs={"X": add_out}, outputs={"Out": mean_out}) self.assertEqual(mul_op.idx, 0) self.assertEqual(add_op.idx, 1) param_to_grad = prog.append_backward(mean_out, set()) def grad_name(name): return name + "@GRAD" for var_name in ("mul.x", "mul.y", "mul.out", "add.y", "add.out", "mean.out"): self.assertEqual(param_to_grad[var_name][0], grad_name(var_name)) self.assertEqual(param_to_grad[var_name][1], 0) expect_ops = [ "mul", "elementwise_add", "mean", "fill_constant", "mean_grad", "elementwise_add_grad", "mul_grad" ] actual_ops = [] for op in block.ops: actual_ops.append(op.type) self.assertEqual(actual_ops, expect_ops) if __name__ == '__main__': unittest.main()