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Merged
0x45f merged 1 commit into from
Jan 17, 2024
Merged

[PIR]Open uts for 221-230 #60799

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34 changes: 20 additions & 14 deletions test/legacy_test/test_activation_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1221,6 +1221,7 @@ def test_dygraph_api(self):
for r in [out1, out2]:
np.testing.assert_allclose(out_ref, r.numpy(), rtol=1e-05)

@test_with_pir_api
def test_errors(self):
with static_guard():
with paddle.static.program_guard(paddle.static.Program()):
Expand All @@ -1232,10 +1233,11 @@ def test_errors(self):
)
self.assertRaises(TypeError, F.tanhshrink, x_int32)
# support the input dtype is float16
x_fp16 = paddle.static.data(
name='x_fp16', shape=[12, 10], dtype='float16'
)
F.tanhshrink(x_fp16)
if paddle.is_compiled_with_cuda():
x_fp16 = paddle.static.data(
name='x_fp16', shape=[12, 10], dtype='float16'
)
F.tanhshrink(x_fp16)


def ref_hardshrink(x, threshold):
Expand Down Expand Up @@ -4411,6 +4413,7 @@ def test_dygraph_api(self):
for r in [out1, out2]:
np.testing.assert_allclose(out_ref, r.numpy(), rtol=1e-05)

@test_with_pir_api
def test_errors(self):
with static_guard():
with paddle.static.program_guard(paddle.static.Program()):
Expand All @@ -4422,10 +4425,11 @@ def test_errors(self):
)
self.assertRaises(TypeError, F.thresholded_relu, x_int32)
# support the input dtype is float16
x_fp16 = paddle.static.data(
name='x_fp16', shape=[12, 10], dtype='float16'
)
F.thresholded_relu(x_fp16)
if paddle.is_compiled_with_cuda():
x_fp16 = paddle.static.data(
name='x_fp16', shape=[12, 10], dtype='float16'
)
F.thresholded_relu(x_fp16)


def ref_hardsigmoid(x, slope=0.166666666666667, offset=0.5):
Expand Down Expand Up @@ -4642,6 +4646,7 @@ def test_base_api(self):
out_ref = ref_swish(self.x_np)
np.testing.assert_allclose(out_ref, res[0], rtol=1e-05)

@test_with_pir_api
def test_errors(self):
with static_guard():
with paddle.static.program_guard(paddle.static.Program()):
Expand All @@ -4653,10 +4658,11 @@ def test_errors(self):
)
self.assertRaises(TypeError, F.swish, x_int32)
# support the input dtype is float16
x_fp16 = paddle.static.data(
name='x_fp16', shape=[12, 10], dtype='float16'
)
F.swish(x_fp16)
if paddle.is_compiled_with_cuda():
x_fp16 = paddle.static.data(
name='x_fp16', shape=[12, 10], dtype='float16'
)
F.swish(x_fp16)


def ref_mish(x, threshold=20.0):
Expand Down Expand Up @@ -4943,7 +4949,7 @@ def test_check_grad(self):
create_test_act_fp16_class(TestSTanh)
create_test_act_fp16_class(TestSoftplus, check_pir=True)
create_test_act_fp16_class(TestSoftsign, check_pir=True)
create_test_act_fp16_class(TestThresholdedRelu)
create_test_act_fp16_class(TestThresholdedRelu, check_pir=True)
create_test_act_fp16_class(TestHardSigmoid, check_pir=True)
create_test_act_fp16_class(TestSwish)
create_test_act_fp16_class(TestHardSwish, check_prim=True, check_pir=True)
Expand Down Expand Up @@ -5112,7 +5118,7 @@ def test_check_grad(self):
create_test_act_bf16_class(TestSTanh)
create_test_act_bf16_class(TestSoftplus, check_pir=True)
create_test_act_bf16_class(TestSoftsign, check_pir=True)
create_test_act_bf16_class(TestThresholdedRelu)
create_test_act_bf16_class(TestThresholdedRelu, check_pir=True)
create_test_act_bf16_class(TestHardSigmoid, check_pir=True)
create_test_act_bf16_class(TestSwish)
create_test_act_bf16_class(TestHardSwish, check_prim=True, check_pir=True)
Expand Down
1 change: 1 addition & 0 deletions test/legacy_test/test_temporal_shift_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -173,6 +173,7 @@ def test_static_fp16_gpu(self):
fetch_list=[y],
)

@test_with_pir_api
def test_error(self):
def attr_data_format():
input = paddle.randn([6, 4, 2, 2])
Expand Down
15 changes: 12 additions & 3 deletions test/legacy_test/test_triangular_solve_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,7 @@
import paddle
from paddle import base
from paddle.base import Program, core, program_guard
from paddle.pir_utils import test_with_pir_api

paddle.enable_static()

Expand Down Expand Up @@ -749,7 +750,9 @@ def setUp(self):
self.place.append(paddle.CUDAPlace(0))

def check_static_result(self, place):
with base.program_guard(base.Program(), base.Program()):
with paddle.static.program_guard(
paddle.static.Program(), paddle.static.Program()
):
x = paddle.static.data(name="x", shape=[3, 3], dtype=self.dtype)
y = paddle.static.data(name="y", shape=[3, 2], dtype=self.dtype)
z = paddle.linalg.triangular_solve(x, y)
Expand All @@ -760,12 +763,13 @@ def check_static_result(self, place):

exe = base.Executor(place)
fetches = exe.run(
base.default_main_program(),
paddle.static.default_main_program(),
feed={"x": x_np, "y": y_np},
fetch_list=[z],
)
np.testing.assert_allclose(fetches[0], z_np, rtol=1e-05)

@test_with_pir_api
def test_static(self):
for place in self.place:
self.check_static_result(place=place)
Expand All @@ -790,7 +794,7 @@ def run(place):


class TestTriangularSolveOpError(unittest.TestCase):
def test_errors(self):
def test_errors1(self):
with program_guard(Program(), Program()):
# The input type of solve_op must be Variable.
x1 = base.create_lod_tensor(
Expand All @@ -801,6 +805,11 @@ def test_errors(self):
)
self.assertRaises(TypeError, paddle.linalg.triangular_solve, x1, y1)

@test_with_pir_api
def test_errors2(self):
with paddle.static.program_guard(
paddle.static.Program(), paddle.static.Program()
):
# The data type of input must be float32 or float64.
x2 = paddle.static.data(name="x2", shape=[30, 30], dtype="bool")
y2 = paddle.static.data(name="y2", shape=[30, 10], dtype="bool")
Expand Down