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