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【pir】delete wrong old ir while_loop test add pir test #60328

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Merged
xiaoguoguo626807 merged 12 commits into from
Dec 27, 2023
Merged

【pir】delete wrong old ir while_loop test add pir test #60328

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001d799
optimize backward
xiaoguoguo626807 Dec 8, 2023
05ca298
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
xiaoguoguo626807 Dec 11, 2023
4fd113e
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
xiaoguoguo626807 Dec 12, 2023
8f60538
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
xiaoguoguo626807 Dec 13, 2023
4e261d4
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
xiaoguoguo626807 Dec 25, 2023
4095782
modfiy while_loop
xiaoguoguo626807 Dec 25, 2023
82eb01b
delete print
xiaoguoguo626807 Dec 26, 2023
c678b7b
Merge branch 'develop' into while_4
xiaoguoguo626807 Dec 26, 2023
bb6e413
Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into…
xiaoguoguo626807 Dec 26, 2023
af7e5d2
modify append_full_like use copy value
xiaoguoguo626807 Dec 26, 2023
a695acd
clear
xiaoguoguo626807 Dec 26, 2023
c3b4268
clear
xiaoguoguo626807 Dec 26, 2023
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17 changes: 4 additions & 13 deletions python/paddle/autograd/ir_backward.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -574,7 +574,6 @@ def make_input_with_input_stopgradient(op):
return inputs, input_grad_stopgradients

def update_input_grad_map(op, input_grads, all_inputs):
_, fwd_value_to_block_argument_map = argument_to_value(op)
i = 0
for input, grad_semantic in zip(all_inputs, get_grad_semantic_info(op)):
if not grad_semantic:
Expand Down Expand Up @@ -631,8 +630,11 @@ def append_yield(
if len(state.value_to_valuegrad[value]) > 1:
append_add_n(value)
else:
new_value = return_map_value(
value, control_flow_value_to_copyvalue_map
)
value_grad = append_full_like(
0.0, value, value, state, backward_ops
0.0, new_value, value, state, backward_ops
)
input_grad = state.value_to_valuegrad[value][0][0]

Expand Down Expand Up @@ -762,16 +764,6 @@ def argument_to_value(while_op):
for sub_fwd_block, sub_bwd_block in zip(
op.blocks(), grad_op.blocks()
):
# update grad_op structure
if grad_op.name() == "pd_op.while":
(
_,
sub_bwd_block_argument_to_value_map,
) = argument_to_value(grad_op)
else:
sub_bwd_block_argument_to_value_map = (
ValueDict()
)
sub_state = state.copy(sub_fwd_block)
sub_backward_ops = []
append_backward_ops(
Expand All @@ -784,7 +776,6 @@ def argument_to_value(while_op):
no_grad_set,
sub_backward_ops,
sub_state,
sub_bwd_block_argument_to_value_map,
)
# update input_grad map
update_input_grad_map(op, input_grads, origin_inputs)
Expand Down
95 changes: 47 additions & 48 deletions test/legacy_test/test_while_loop_op.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -254,66 +254,63 @@ def internal_body(j, init, sums):


class TestApiWhileLoop_Backward(unittest.TestCase):
# TODO(zhangbo): Support while grad exe for pir
# @test_with_pir_api
def test_while_loop_backward(self):
def cond(i, x):
return paddle.less_than(i, eleven)
with paddle.pir_utils.IrGuard():

def cond(i, x):
return paddle.less_than(i, eleven)

def body(i, x):
x = paddle.multiply(x=i, y=i)
i = paddle.increment(i)
return [i, x]

main_program = paddle.static.Program()
startup_program = paddle.static.Program()
with paddle.static.program_guard(main_program, startup_program):
i = paddle.static.data(name='i', shape=[1], dtype='float32')
i.stop_gradient = False
i.persistable = True
eleven = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=11
)
one = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=1
)
x = paddle.static.data(name='x', shape=[1], dtype='float32')
x.stop_gradient = False
x.persistable = True

def body(i, x):
x = paddle.multiply(x=i, y=i)
i = paddle.increment(i)
return [i, x]
out = paddle.static.nn.while_loop(cond, body, [i, x])
mean = paddle.mean(out[1])
grad_list = append_backward(mean)

main_program = paddle.static.Program()
startup_program = paddle.static.Program()
with paddle.static.program_guard(main_program, startup_program):
i = paddle.static.data(name='i', shape=[1], dtype='float32')
i.stop_gradient = False
i.persistable = True
eleven = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=11
)
one = paddle.tensor.fill_constant(
shape=[1], dtype='float32', value=1
place = (
base.CUDAPlace(0)
if core.is_compiled_with_cuda()
else base.CPUPlace()
)
x = paddle.static.data(name='x', shape=[1], dtype='float32')
x.stop_gradient = False
x.persistable = True

out = paddle.static.nn.while_loop(cond, body, [i, x])
mean = paddle.mean(out[1])
grad_list = append_backward(mean)
exe = base.Executor(place)

place = (
base.CUDAPlace(0)
if core.is_compiled_with_cuda()
else base.CPUPlace()
)
exe = base.Executor(place)
feed_i = np.ones(1).astype('float32')
feed_x = np.ones(1).astype('float32')
data = np.asarray([100]).astype('float32')
i_grad = np.asarray([0]).astype('float32')
x_grad = np.asarray([0]).astype('float32')

feed_i = np.ones(1).astype('float32')
feed_x = np.ones(1).astype('float32')
data = np.asarray([100]).astype('float32')
i_grad = np.asarray([110]).astype('float32')

if paddle.framework.in_pir_mode():
for p, g in grad_list:
if p == i:
if p.is_same(i):
di = g
elif p.is_same(x):
dx = g
res = exe.run(
main_program,
feed={'i': feed_i, 'x': feed_x},
fetch_list=[mean, di],
fetch_list=[mean, di, dx],
)
else:
res = exe.run(
main_program,
feed={'i': feed_i, 'x': feed_x},
fetch_list=[mean.name, i.grad_name, x.grad_name],
)
np.testing.assert_allclose(np.asarray(res[0]), data, rtol=1e-05)
np.testing.assert_allclose(np.asarray(res[1]), i_grad, rtol=1e-05)
np.testing.assert_allclose(np.asarray(res[0]), data, rtol=1e-05)
np.testing.assert_allclose(np.asarray(res[1]), i_grad, rtol=1e-05)
np.testing.assert_allclose(np.asarray(res[2]), x_grad, rtol=1e-05)

@test_with_pir_api
def test_while_loop_backward2(self):
Expand Down Expand Up @@ -356,6 +353,7 @@ def body(i, x):
fetch_list = [out[1]]
for p, g in grad_list:
fetch_list.append(g)

res = exe.run(
main_program,
feed={'i': feed_i, 'x': feed_x},
Expand All @@ -367,6 +365,7 @@ def body(i, x):
feed={'i': feed_i, 'x': feed_x},
fetch_list=[out[1].name, i.grad_name, x.grad_name],
)

np.testing.assert_allclose(np.asarray(res[0]), data, rtol=1e-05)
np.testing.assert_allclose(np.asarray(res[1]), i_grad, rtol=1e-05)
np.testing.assert_allclose(np.asarray(res[2]), x_grad, rtol=1e-05)
Expand Down