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【PIR API adaptor No.45-47】Migrate some ops into pir #58682

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Merged
0x45f merged 13 commits into from
Nov 20, 2023
Merged

【PIR API adaptor No.45-47】Migrate some ops into pir #58682

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e17f0ee
migrate crop, cross, softmax_with_cross_entropy into pir
longranger2 Nov 4, 2023
2876ba5
Update test_crop_op.py
longranger2 Nov 7, 2023
8d68a01
Update test_cross_op.py
longranger2 Nov 7, 2023
82721e8
Update test_cross_op.py
longranger2 Nov 7, 2023
7495a01
fix bug
longranger2 Nov 8, 2023
e944f73
fix bug
longranger2 Nov 8, 2023
b02c830
fix bug
longranger2 Nov 8, 2023
5607cd6
fix bug
longranger2 Nov 8, 2023
416c252
fix bug
longranger2 Nov 13, 2023
f170160
fix bug
longranger2 Nov 14, 2023
fd31de5
Update test_softmax_with_cross_entropy_op.py
longranger2 Nov 15, 2023
5a152a1
Update test_softmax_with_cross_entropy_op.py
longranger2 Nov 16, 2023
a8a26cf
fix bug
longranger2 Nov 16, 2023
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8 changes: 6 additions & 2 deletions python/paddle/nn/functional/loss.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,11 @@
from paddle.utils import deprecated

from ...base.data_feeder import check_variable_and_dtype
from ...base.framework import _current_expected_place, in_pir_mode
from ...base.framework import (
_current_expected_place,
in_dynamic_or_pir_mode,
in_pir_mode,
)
from ...base.layer_helper import LayerHelper
from ...common_ops_import import Variable
from ...tensor.manipulation import reshape
Expand Down Expand Up @@ -267,7 +271,7 @@ def base_softmax_with_cross_entropy(
)
if input_dims - 1 == label_dims:
label = paddle.unsqueeze(label, axis=axis)
if in_dynamic_mode():
if in_dynamic_or_pir_mode():
softmax, loss = _C_ops.cross_entropy_with_softmax(
logits,
label,
Expand Down
2 changes: 1 addition & 1 deletion python/paddle/tensor/linalg.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1466,7 +1466,7 @@ def cross(x, y, axis=9, name=None):
[0., 0., 0.],
[0., 0., 0.]])
"""
if in_dynamic_mode():
if in_dynamic_or_pir_mode():
axis = K_DEFAULT_DIM if axis is None else axis
return _C_ops.cross(x, y, axis)
else:
Expand Down
7 changes: 5 additions & 2 deletions python/paddle/tensor/manipulation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -780,7 +780,10 @@ def crop(x, shape=None, offsets=None, name=None):
x, 'x', ['float32', 'float64', 'int32', 'int64'], 'crop_tensor'
)
check_type(
shape, 'shape', (list, tuple, Variable, type(None)), 'crop_tensor'
shape,
'shape',
(list, tuple, Variable, type(None), paddle.pir.OpResult),
'crop_tensor',
)
check_type(
offsets, 'offsets', (list, tuple, Variable, type(None)), 'crop_tensor'
Expand All @@ -792,7 +795,7 @@ def crop(x, shape=None, offsets=None, name=None):
if shape is None:
shape = x.shape

if in_dynamic_mode():
if in_dynamic_or_pir_mode():
return _C_ops.crop(x, shape, offsets)

out = helper.create_variable_for_type_inference(x.dtype)
Expand Down
8 changes: 4 additions & 4 deletions test/legacy_test/test_crop_tensor_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -81,10 +81,10 @@ def initTestCase(self):
self.offsets = [1, 2]

def test_check_output(self):
self.check_output()
self.check_output(check_pir=True)

def test_check_grad_normal(self):
self.check_grad(['X'], 'Out')
self.check_grad(['X'], 'Out', check_pir=True)


class TestCase1(TestCropTensorOp):
Expand Down Expand Up @@ -182,10 +182,10 @@ def initTestCase(self):
self.shape_attr = [0, 0]

def test_check_output(self):
self.check_output()
self.check_output(check_pir=True)

def test_check_grad_normal(self):
self.check_grad(["X"], "Out")
self.check_grad(["X"], "Out", check_pir=True)


class TestCropTensorOpTensorAttrCase1(TestCropTensorOpTensorAttr):
Expand Down
30 changes: 20 additions & 10 deletions test/legacy_test/test_cross_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,8 @@

import paddle
from paddle import base
from paddle.base import Program, core, program_guard
from paddle.base import core
from paddle.pir_utils import test_with_pir_api


class TestCrossOp(OpTest):
Expand Down Expand Up @@ -47,10 +48,10 @@ def init_output(self):
self.outputs = {'Out': np.array(z_list).reshape(self.shape)}

def test_check_output(self):
self.check_output()
self.check_output(check_pir=True)

def test_check_grad_normal(self):
self.check_grad(['X', 'Y'], 'Out')
self.check_grad(['X', 'Y'], 'Out', check_pir=True)


class TestCrossOpCase1(TestCrossOp):
Expand Down Expand Up @@ -116,13 +117,15 @@ def test_check_output(self):
if core.is_compiled_with_cuda():
place = core.CUDAPlace(0)
if core.is_bfloat16_supported(place):
self.check_output_with_place(place)
self.check_output_with_place(place, check_pir=True)

def test_check_grad_normal(self):
if core.is_compiled_with_cuda():
place = core.CUDAPlace(0)
if core.is_bfloat16_supported(place):
self.check_grad_with_place(place, ['X', 'Y'], 'Out')
self.check_grad_with_place(
place, ['X', 'Y'], 'Out', check_pir=True
)


class TestCrossAPI(unittest.TestCase):
Expand All @@ -134,34 +137,41 @@ def input_data(self):
[[1.0, 1.0, 1.0], [1.0, 1.0, 1.0], [1.0, 1.0, 1.0]]
).astype('float32')

@test_with_pir_api
def test_cross_api(self):
self.input_data()

main = paddle.static.Program()
startup = paddle.static.Program()
# case 1:
with program_guard(Program(), Program()):
with paddle.static.program_guard(main, startup):
x = paddle.static.data(name='x', shape=[-1, 3], dtype="float32")
y = paddle.static.data(name='y', shape=[-1, 3], dtype="float32")
z = paddle.cross(x, y, axis=1)
exe = base.Executor(base.CPUPlace())
(res,) = exe.run(
main,
feed={'x': self.data_x, 'y': self.data_y},
fetch_list=[z.name],
fetch_list=[z],
return_numpy=False,
)
expect_out = np.array(
[[0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]
)
np.testing.assert_allclose(expect_out, np.array(res), rtol=1e-05)

main = paddle.static.Program()
startup = paddle.static.Program()
# case 2:
with program_guard(Program(), Program()):
with paddle.static.program_guard(main, startup):
x = paddle.static.data(name='x', shape=[-1, 3], dtype="float32")
y = paddle.static.data(name='y', shape=[-1, 3], dtype="float32")
z = paddle.cross(x, y)
exe = base.Executor(base.CPUPlace())
(res,) = exe.run(
main,
feed={'x': self.data_x, 'y': self.data_y},
fetch_list=[z.name],
fetch_list=[z],
return_numpy=False,
)
expect_out = np.array(
Expand All @@ -170,7 +180,7 @@ def test_cross_api(self):
np.testing.assert_allclose(expect_out, np.array(res), rtol=1e-05)

# case 3:
with program_guard(Program(), Program()):
with paddle.static.program_guard(main, startup):
x = paddle.static.data(name="x", shape=[-1, 3], dtype="float32")
y = paddle.static.data(name='y', shape=[-1, 3], dtype='float32')

Expand Down
54 changes: 32 additions & 22 deletions test/legacy_test/test_softmax_with_cross_entropy_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -153,27 +153,27 @@ def setUp(self):

def test_check_output(self):
if self.python_api is not None:
self.check_output()
self.check_output()
self.check_output(check_pir=True)
self.check_output(check_pir=True)

def test_check_grad(self):
if core.is_compiled_with_rocm():
if self.python_api is not None:
self.check_grad(
["Logits"],
"Loss",
max_relative_error=5e-1,
["Logits"], "Loss", max_relative_error=5e-1, check_pir=True
)
# HIP will have accuracy fail when using float32 in CPU place
self.check_grad(["Logits"], "Loss", max_relative_error=5e-1)
self.check_grad(
["Logits"], "Loss", max_relative_error=5e-1, check_pir=True
)
else:
if self.python_api is not None:
self.check_grad(
["Logits"],
"Loss",
numeric_grad_delta=0.001,
["Logits"], "Loss", numeric_grad_delta=0.001, check_pir=True
)
self.check_grad(["Logits"], "Loss", numeric_grad_delta=0.001)
self.check_grad(
["Logits"], "Loss", numeric_grad_delta=0.001, check_pir=True
)


class TestSoftmaxWithCrossEntropyOpInt32(TestSoftmaxWithCrossEntropyOp):
Expand Down Expand Up @@ -509,13 +509,15 @@ def setUp(self):

def test_check_output(self):
if self.python_api is not None:
self.check_output()
self.check_output()
self.check_output(check_pir=True)
self.check_output(check_pir=True)

def test_check_grad(self):
if self.python_api is not None:
self.check_grad(["Logits"], "Loss")
self.check_grad(["Logits"], "Loss", max_relative_error=0.1)
self.check_grad(["Logits"], "Loss", check_pir=True)
self.check_grad(
["Logits"], "Loss", max_relative_error=0.1, check_pir=True
)


class TestSoftmaxWithCrossEntropyOpNoCudnnFp16(
Expand All @@ -534,8 +536,12 @@ def initParams(self):

def test_check_grad(self):
if self.python_api is not None:
self.check_grad(["Logits"], "Loss", max_relative_error=0.1)
self.check_grad(["Logits"], "Loss", max_relative_error=0.1)
self.check_grad(
["Logits"], "Loss", max_relative_error=0.1, check_pir=True
)
self.check_grad(
["Logits"], "Loss", max_relative_error=0.1, check_pir=True
)


class TestSoftmaxWithCrossEntropyOp2(TestSoftmaxWithCrossEntropyOp):
Expand All @@ -557,19 +563,23 @@ def initParams(self):

def test_check_output(self):
if self.python_api is not None:
self.check_output()
self.check_output()
self.check_output(check_pir=True)
self.check_output(check_pir=True)

def test_check_grad(self):
if core.is_compiled_with_rocm():
# HIP will have accuracy fail when using float32 in CPU place
if self.python_api is not None:
self.check_grad(["Logits"], "Loss", max_relative_error=0.1)
self.check_grad(["Logits"], "Loss", max_relative_error=0.1)
self.check_grad(
["Logits"], "Loss", max_relative_error=0.1, check_pir=True
)
self.check_grad(
["Logits"], "Loss", max_relative_error=0.1, check_pir=True
)
else:
if self.python_api is not None:
self.check_grad(["Logits"], "Loss")
self.check_grad(["Logits"], "Loss")
self.check_grad(["Logits"], "Loss", check_pir=True)
self.check_grad(["Logits"], "Loss", check_pir=True)


class TestSoftmaxWithCrossEntropyOp3(TestSoftmaxWithCrossEntropyOp):
Expand Down