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【PIR API adaptor No.217、256、279、280】 Migrate nn.functional.square_error_cost, nn.GaussianNLLLoss/MultiLabelSoftMarginLoss/MultiMarginLoss into pir #59913

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Merged
0x45f merged 3 commits into from
Dec 15, 2023
Merged

【PIR API adaptor No.217、256、279、280】 Migrate nn.functional.square_error_cost, nn.GaussianNLLLoss/MultiLabelSoftMarginLoss/MultiMarginLoss into pir #59913

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7635551
adapt TestSquareErrorCost
MarioLulab Dec 11, 2023
99e94ef
update multi_label_soft_margin_loss
MarioLulab Dec 15, 2023
9f90f2d
update multi_margin_loss
MarioLulab Dec 15, 2023
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3 changes: 3 additions & 0 deletions test/legacy_test/test_multi_label_soft_margin_loss.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@
import numpy as np

import paddle
from paddle.pir_utils import test_with_pir_api


def call_MultiLabelSoftMarginLoss_layer(
Expand Down Expand Up @@ -139,6 +140,7 @@ def LogSigmoid(x):


class TestMultiLabelMarginLoss(unittest.TestCase):
@test_with_pir_api
def test_MultiLabelSoftMarginLoss(self):
input = np.random.uniform(0.1, 0.8, size=(5, 5)).astype(np.float64)
label = np.random.randint(0, 2, size=(5, 5)).astype(np.float64)
Expand Down Expand Up @@ -209,6 +211,7 @@ def test_MultiLabelSoftMarginLoss_error(self):
)
paddle.enable_static()

@test_with_pir_api
def test_MultiLabelSoftMarginLoss_weights(self):
input = np.random.uniform(0.1, 0.8, size=(5, 5)).astype(np.float64)
label = np.random.randint(0, 2, size=(5, 5)).astype(np.float64)
Expand Down
5 changes: 5 additions & 0 deletions test/legacy_test/test_multimarginloss.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,6 +17,7 @@
import numpy as np

import paddle
from paddle.pir_utils import test_with_pir_api


def call_MultiMarginLoss_layer(
Expand Down Expand Up @@ -238,6 +239,7 @@ def calc_multi_margin_loss(


class TestMultiMarginLoss(unittest.TestCase):
@test_with_pir_api
def test_MultiMarginLoss(self):
batch_size = 5
num_classes = 2
Expand Down Expand Up @@ -330,6 +332,7 @@ def test_MultiMarginLoss_dimension(self):
)
paddle.enable_static()

@test_with_pir_api
def test_MultiMarginLoss_p(self):
p = 2
batch_size = 5
Expand Down Expand Up @@ -383,6 +386,7 @@ def test_MultiMarginLoss_p(self):
np.testing.assert_allclose(static_functional, dy_functional)
np.testing.assert_allclose(dy_functional, expected)

@test_with_pir_api
def test_MultiMarginLoss_weight(self):
batch_size = 5
num_classes = 2
Expand Down Expand Up @@ -436,6 +440,7 @@ def test_MultiMarginLoss_weight(self):
np.testing.assert_allclose(static_functional, dy_functional)
np.testing.assert_allclose(dy_functional, expected)

@test_with_pir_api
def test_MultiMarginLoss_static_data_shape(self):
batch_size = 5
num_classes = 2
Expand Down
43 changes: 26 additions & 17 deletions test/legacy_test/test_square_error_cost.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,34 +20,43 @@
from paddle import base
from paddle.base import core
from paddle.base.executor import Executor
from paddle.pir_utils import test_with_pir_api


class TestSquareErrorCost(unittest.TestCase):
@test_with_pir_api
def test_square_error_cost(self):
input_val = np.random.uniform(0.1, 0.5, (2, 3)).astype("float32")
label_val = np.random.uniform(0.1, 0.5, (2, 3)).astype("float32")
paddle.enable_static()
shape = [2, 3]
input_val = np.random.uniform(0.1, 0.5, shape).astype("float32")
label_val = np.random.uniform(0.1, 0.5, shape).astype("float32")

sub = input_val - label_val
np_result = sub * sub

input_var = paddle.tensor.create_tensor(dtype="float32", name="input")
label_var = paddle.tensor.create_tensor(dtype="float32", name="label")
output = paddle.nn.functional.square_error_cost(
input=input_var, label=label_var
)

for use_cuda in (
[False, True] if core.is_compiled_with_cuda() else [False]
):
place = base.CUDAPlace(0) if use_cuda else base.CPUPlace()
exe = Executor(place)
(result,) = exe.run(
base.default_main_program(),
feed={"input": input_val, "label": label_val},
fetch_list=[output],
)

np.testing.assert_allclose(np_result, result, rtol=1e-05)
with paddle.static.program_guard(paddle.static.Program()):
input_var = paddle.static.data(
name="input", shape=shape, dtype="float32"
)
label_var = paddle.static.data(
name="label", shape=shape, dtype="float32"
)
output = paddle.nn.functional.square_error_cost(
input=input_var, label=label_var
)

place = base.CUDAPlace(0) if use_cuda else base.CPUPlace()
exe = Executor(place)
(result,) = exe.run(
paddle.static.default_main_program(),
feed={"input": input_val, "label": label_val},
fetch_list=[output],
)

np.testing.assert_allclose(np_result, result, rtol=1e-05)


class TestSquareErrorInvalidInput(unittest.TestCase):
Expand Down