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[Add] test atleast_xd pir backward #59365

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merged 4 commits into from
Dec 5, 2023
Merged

[Add] test atleast_xd pir backward #59365

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de6078e
[Change] keep tensor from input
megemini Nov 24, 2023
36cf6e9
[Change] atleast input for pri
megemini Nov 25, 2023
887f9ad
[Change] test for pir
megemini Dec 4, 2023
74cffd6
[Change] pir grad from z to x
megemini Dec 4, 2023
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45 changes: 39 additions & 6 deletions python/paddle/tensor/manipulation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4082,8 +4082,19 @@ def atleast_1d(*inputs, name=None):
[[1.23000002]])]
"""
out = []
for tensor in inputs:
tensor = paddle.to_tensor(tensor)
for input in inputs:
if not isinstance(
input,
(
paddle.Tensor,
paddle.base.framework.Variable,
paddle.base.libpaddle.pir.OpResult,
),
):
tensor = paddle.to_tensor(input)
else:
tensor = input

if tensor.dim() == 0:
result = tensor.reshape((1,))
else:
Expand Down Expand Up @@ -4139,8 +4150,19 @@ def atleast_2d(*inputs, name=None):
[[[1.23000002]]])]
"""
out = []
for tensor in inputs:
tensor = paddle.to_tensor(tensor)
for input in inputs:
if not isinstance(
input,
(
paddle.Tensor,
paddle.base.framework.Variable,
paddle.base.libpaddle.pir.OpResult,
),
):
tensor = paddle.to_tensor(input)
else:
tensor = input

if tensor.dim() == 0:
result = tensor.reshape((1, 1))
elif tensor.dim() == 1:
Expand Down Expand Up @@ -4198,8 +4220,19 @@ def atleast_3d(*inputs, name=None):
[[[[1.23000002]]]])]
"""
out = []
for tensor in inputs:
tensor = paddle.to_tensor(tensor)
for input in inputs:
if not isinstance(
input,
(
paddle.Tensor,
paddle.base.framework.Variable,
paddle.base.libpaddle.pir.OpResult,
),
):
tensor = paddle.to_tensor(input)
else:
tensor = input

if tensor.dim() == 0:
result = tensor.reshape((1, 1, 1))
elif tensor.dim() == 1:
Expand Down
45 changes: 39 additions & 6 deletions test/legacy_test/test_atleast_xd.py
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Original file line number Diff line number Diff line change
Expand Up @@ -55,7 +55,6 @@ def generate_data(ndim, count=1, max_size=4, mix=False, dtype='int32'):
a list of data like:
[[data, dtype, shape, name], [data, dtype, shape, name] ... ]
"""

rtn = []
for d in range(ndim):
data = [
Expand Down Expand Up @@ -172,7 +171,11 @@ def _test_static_api(
shape = shapes[i]
dtype = dtypes[i]
name = names[i]
x.append(paddle.static.data(name, shape, dtype))

_x = paddle.static.data(name, shape, dtype)
_x.stop_gradient = False
x.append(_x)

# the data feeded should NOT be a Tensor
feed[name] = (
input.numpy()
Expand All @@ -181,12 +184,39 @@ def _test_static_api(
)

out = func(*x)
exe = paddle.static.Executor(place)
res = exe.run(feed=feed, fetch_list=[out])

# unwrap inputs when lenght 1
if len(inputs) == 1:
res = res[0]
out.stop_gradient = False
y = x[0]
_out = out
else:
for o in out:
o.stop_gradient = False
y = x[0]
_out = out[0]

z = _out * 123

fetch_list = [out]
if paddle.framework.in_pir_mode():
grads = paddle.autograd.ir_backward.grad(z, y)
out_grad = grads[0]
fetch_list.append(out_grad)
else:
paddle.static.append_backward(z)
out_grad = y.grad_name
fetch_list.append(out_grad)

exe = paddle.static.Executor(place)
*res, res_grad = exe.run(feed=feed, fetch_list=fetch_list)

# not check old ir
if paddle.framework.in_pir_mode():
# convert grad value to bool if dtype is bool
grad_value = 123.0 if dtypes[0] != 'bool' else True
np.testing.assert_allclose(
res_grad, np.ones_like(y) * grad_value
)

out_ref = func_ref(
func_type,
Expand All @@ -198,6 +228,9 @@ def _test_static_api(
]
)

if len(inputs) == 1:
out_ref = [out_ref]

for n, p in zip(out_ref, res):
np.testing.assert_allclose(n, p, rtol=RTOL, atol=ATOL)

Expand Down