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【PIR API adaptor No.160、204、216 】 Migrate NLLLoss/BCEWithLogitsLoss/MarginRankingLoss into pir #58832

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merged 14 commits into from
Nov 27, 2023
Merged

【PIR API adaptor No.160、204、216 】 Migrate NLLLoss/BCEWithLogitsLoss/MarginRankingLoss into pir #58832

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8faa4d4
add one test
DrRyanHuang Nov 8, 2023
74b964f
160,204,216
DrRyanHuang Nov 8, 2023
13a27ba
fix dtype => _dtype
DrRyanHuang Nov 11, 2023
f5f2e0e
_dtype in_pir_mode
DrRyanHuang Nov 16, 2023
9e97aca
Merge branch 'develop' into BCEWithLogitsLoss
DrRyanHuang Nov 17, 2023
825bf97
add .name && dtype
DrRyanHuang Nov 18, 2023
126a6c7
rm @test_with_pir_api of run_static_api
DrRyanHuang Nov 18, 2023
ce62d67
fix _dtype
DrRyanHuang Nov 23, 2023
a238587
change if branch
DrRyanHuang Nov 23, 2023
5332478
rm @test_with_pir_api of test_errors
DrRyanHuang Nov 23, 2023
6402000
fix sf
DrRyanHuang Nov 24, 2023
f0c5acf
try to fix segmentation fault
DrRyanHuang Nov 24, 2023
f5659b4
fix codestyle && fix nll_loss
DrRyanHuang Nov 25, 2023
982248c
add if branch due to Segmentation fault
DrRyanHuang Nov 25, 2023
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10 changes: 5 additions & 5 deletions python/paddle/nn/functional/loss.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -17,13 +17,13 @@
# TODO: define loss functions of neural network
import paddle
from paddle import _C_ops, base, in_dynamic_mode
from paddle.framework import core
from paddle.static.nn.control_flow import Assert
from paddle.utils import deprecated

from ...base.data_feeder import check_variable_and_dtype
from ...base.framework import (
_current_expected_place,
core,
in_dynamic_or_pir_mode,
in_pir_mode,
)
Expand Down Expand Up @@ -800,7 +800,7 @@ def binary_cross_entropy_with_logits(
% reduction
)

if in_dynamic_mode():
if in_dynamic_or_pir_mode():
one = _C_ops.full(
[1],
1.0,
Expand Down Expand Up @@ -1197,11 +1197,11 @@ def margin_ranking_loss(
"The value of 'reduction' in MarginRankingLoss should be 'sum', 'mean' or 'none', but "
"received %s, which is not allowed." % reduction
)
if in_dynamic_mode():
if in_dynamic_or_pir_mode():
out = _C_ops.subtract(other, input)
out = _C_ops.multiply(out, label)
if margin != 0.0:
margin = base.dygraph.base.to_variable([margin], dtype=out.dtype)
margin = paddle.to_tensor([margin], dtype=out.dtype)
out = _C_ops.add(out, margin)
out = _C_ops.relu(out)
if reduction == 'sum':
Expand Down Expand Up @@ -1440,7 +1440,7 @@ def nll_loss(

n = input_shape[0]
c = input_shape[1]
if in_dynamic_mode():
if in_dynamic_or_pir_mode():
if input_dims != 2 and input_dims != 4:
input = _C_ops.reshape(input, [n, c, 1, -1])
label = _C_ops.reshape(label, [n, 1, -1])
Expand Down
160 changes: 95 additions & 65 deletions test/legacy_test/test_bce_with_logits_loss.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,7 @@

import paddle
from paddle import base
from paddle.pir_utils import test_with_pir_api


def call_bce_layer(
Expand Down Expand Up @@ -49,9 +50,10 @@ def test_static(
functional=False,
):
paddle.enable_static()
prog = paddle.static.Program()
startup_prog = paddle.static.Program()
with paddle.static.program_guard(prog, startup_prog):

with paddle.static.program_guard(
paddle.static.Program(), paddle.static.Program()
):
logit = paddle.static.data(
name='logit', shape=logit_np.shape, dtype='float64'
)
Expand Down Expand Up @@ -79,7 +81,7 @@ def test_static(
else:
res = call_bce_layer(logit, label, weight, reduction, pos_weight)
exe = paddle.static.Executor(place)
(static_result,) = exe.run(prog, feed=feed_dict, fetch_list=[res])
(static_result,) = exe.run(feed=feed_dict, fetch_list=[res])
return static_result


Expand Down Expand Up @@ -147,41 +149,51 @@ def test_BCEWithLogitsLoss(self):
reductions = ['sum', 'mean', 'none']
for place in places:
for reduction in reductions:
static_result = test_static(
place, logit_np, label_np, reduction=reduction
)
dy_result = test_dygraph(
place, logit_np, label_np, reduction=reduction
)
expected = calc_bce_with_logits_loss(
logit_np, label_np, reduction
)
np.testing.assert_allclose(static_result, expected, rtol=1e-05)
np.testing.assert_allclose(static_result, dy_result, rtol=1e-05)
np.testing.assert_allclose(dy_result, expected, rtol=1e-05)
static_functional = test_static(
place,
logit_np,
label_np,
reduction=reduction,
functional=True,
)
dy_functional = test_dygraph(
place,
logit_np,
label_np,
reduction=reduction,
functional=True,
)

np.testing.assert_allclose(
static_functional, expected, rtol=1e-05
)
np.testing.assert_allclose(
static_functional, dy_functional, rtol=1e-05
expected = calc_bce_with_logits_loss(
logit_np, label_np, reduction
)

np.testing.assert_allclose(dy_result, expected, rtol=1e-05)
np.testing.assert_allclose(dy_functional, expected, rtol=1e-05)

@test_with_pir_api
def test_dynamic_or_pir_mode():
static_result = test_static(
place, logit_np, label_np, reduction=reduction
)
static_functional = test_static(
place,
logit_np,
label_np,
reduction=reduction,
functional=True,
)
np.testing.assert_allclose(
static_result, expected, rtol=1e-05
)
np.testing.assert_allclose(
static_result, dy_result, rtol=1e-05
)

np.testing.assert_allclose(
static_functional, expected, rtol=1e-05
)
np.testing.assert_allclose(
static_functional, dy_functional, rtol=1e-05
)

test_dynamic_or_pir_mode()

def test_BCEWithLogitsLoss_weight(self):
logit_np = np.random.uniform(0.1, 0.8, size=(2, 3, 4, 10)).astype(
np.float64
Expand All @@ -196,13 +208,6 @@ def test_BCEWithLogitsLoss_weight(self):
else base.CPUPlace()
)
for reduction in ['sum', 'mean', 'none']:
static_result = test_static(
place,
logit_np,
label_np,
weight_np=weight_np,
reduction=reduction,
)
dy_result = test_dygraph(
place,
logit_np,
Expand All @@ -213,17 +218,6 @@ def test_BCEWithLogitsLoss_weight(self):
expected = calc_bce_with_logits_loss(
logit_np, label_np, reduction, weight_np=weight_np
)
np.testing.assert_allclose(static_result, expected, rtol=1e-05)
np.testing.assert_allclose(static_result, dy_result, rtol=1e-05)
np.testing.assert_allclose(dy_result, expected, rtol=1e-05)
static_functional = test_static(
place,
logit_np,
label_np,
weight_np=weight_np,
reduction=reduction,
functional=True,
)
dy_functional = test_dygraph(
place,
logit_np,
Expand All @@ -232,12 +226,39 @@ def test_BCEWithLogitsLoss_weight(self):
reduction=reduction,
functional=True,
)
np.testing.assert_allclose(static_functional, expected, rtol=1e-05)
np.testing.assert_allclose(
static_functional, dy_functional, rtol=1e-05
)
np.testing.assert_allclose(dy_result, expected, rtol=1e-05)
np.testing.assert_allclose(dy_functional, expected, rtol=1e-05)

@test_with_pir_api
def test_dynamic_or_pir_mode():
static_result = test_static(
place,
logit_np,
label_np,
weight_np=weight_np,
reduction=reduction,
)

static_functional = test_static(
place,
logit_np,
label_np,
weight_np=weight_np,
reduction=reduction,
functional=True,
)
np.testing.assert_allclose(static_result, expected, rtol=1e-05)
np.testing.assert_allclose(static_result, dy_result, rtol=1e-05)

np.testing.assert_allclose(
static_functional, expected, rtol=1e-05
)
np.testing.assert_allclose(
static_functional, dy_functional, rtol=1e-05
)

test_dynamic_or_pir_mode()

def test_BCEWithLogitsLoss_pos_weight(self):
logit_np = np.random.uniform(0.1, 0.8, size=(2, 3, 4, 10)).astype(
np.float64
Expand All @@ -253,27 +274,13 @@ def test_BCEWithLogitsLoss_pos_weight(self):
else base.CPUPlace()
)
reduction = "mean"
static_result = test_static(
place, logit_np, label_np, weight_np, reduction, pos_weight_np
)

dy_result = test_dygraph(
place, logit_np, label_np, weight_np, reduction, pos_weight_np
)
expected = calc_bce_with_logits_loss(
logit_np, label_np, reduction, weight_np, pos_weight_np
)
np.testing.assert_allclose(static_result, expected, rtol=1e-05)
np.testing.assert_allclose(static_result, dy_result, rtol=1e-05)
np.testing.assert_allclose(dy_result, expected, rtol=1e-05)
static_functional = test_static(
place,
logit_np,
label_np,
weight_np,
reduction,
pos_weight_np,
functional=True,
)
dy_functional = test_dygraph(
place,
logit_np,
Expand All @@ -283,10 +290,33 @@ def test_BCEWithLogitsLoss_pos_weight(self):
pos_weight_np,
functional=True,
)
np.testing.assert_allclose(static_functional, expected, rtol=1e-05)
np.testing.assert_allclose(static_functional, dy_functional, rtol=1e-05)
np.testing.assert_allclose(dy_result, expected, rtol=1e-05)
np.testing.assert_allclose(dy_functional, expected, rtol=1e-05)

@test_with_pir_api
def test_dynamic_or_pir_mode():
static_result = test_static(
place, logit_np, label_np, weight_np, reduction, pos_weight_np
)
static_functional = test_static(
place,
logit_np,
label_np,
weight_np,
reduction,
pos_weight_np,
functional=True,
)

np.testing.assert_allclose(static_result, expected, rtol=1e-05)
np.testing.assert_allclose(static_result, dy_result, rtol=1e-05)
np.testing.assert_allclose(static_functional, expected, rtol=1e-05)
np.testing.assert_allclose(
static_functional, dy_functional, rtol=1e-05
)

test_dynamic_or_pir_mode()

def test_BCEWithLogitsLoss_error(self):
paddle.disable_static()
self.assertRaises(
Expand Down
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