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[Hackathon 5th No.49][pir] add some operation - Part 3 (#58219)
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@gouzil
gouzil authored Oct 23, 2023
1 parent e11ddec commit edcfda9
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22 changes: 22 additions & 0 deletions python/paddle/pir/math_op_patch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -368,6 +368,28 @@ def __impl__(self, other_var):
'__rtruediv__',
_binary_creator_('__rtruediv__', paddle.tensor.divide, True, None),
),
(
'__pow__',
_binary_creator_('__pow__', paddle.tensor.pow, False, None),
),
(
'__rpow__',
_binary_creator_('__rpow__', paddle.tensor.pow, True, None),
),
(
'__floordiv__',
_binary_creator_(
'__floordiv__', paddle.tensor.floor_divide, False, None
),
),
(
'__mod__',
_binary_creator_('__mod__', paddle.tensor.remainder, False, None),
),
(
'__matmul__',
_binary_creator_('__matmul__', paddle.tensor.matmul, False, None),
),
]

global _already_patch_opresult
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2 changes: 1 addition & 1 deletion python/paddle/tensor/math.py
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Original file line number Diff line number Diff line change
Expand Up @@ -941,7 +941,7 @@ def floor_divide(x, y, name=None):
[2, 0, 2, 2])
"""
if in_dynamic_mode():
if in_dynamic_or_pir_mode():
return _C_ops.floor_divide(x, y)
else:
return _elementwise_op(LayerHelper('elementwise_floordiv', **locals()))
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141 changes: 141 additions & 0 deletions test/legacy_test/test_math_op_patch_pir.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,12 +16,153 @@
import unittest
import warnings

import numpy as np

import paddle
from paddle import base

paddle.enable_static()
paddle.device.set_device("cpu")


def new_program():
# TODO(gouzil): Optimize program code
main_program = paddle.static.Program()
startup_program = paddle.static.Program()
place = base.CPUPlace()
exe = base.Executor(place)
return (
main_program,
exe,
paddle.static.program_guard(
main_program=main_program, startup_program=startup_program
),
)


class TestMathOpPatchesPir(unittest.TestCase):
def test_pow(self):
# Calculate results in dynamic graphs
paddle.disable_static()
x_np = np.random.random([10, 1024]).astype('float32')
y_np = np.random.random([10, 1024]).astype('float32')
res_np_b = x_np**y_np
res_np_c = paddle.pow(paddle.to_tensor(x_np), 2)
# TODO(gouzil): solve paddle.fill_constant problem
# res_np_d = x_np.__pow__(2)
# res_np_e = x_np.__rpow__(2)
paddle.enable_static()
# Calculate results under pir
with paddle.pir_utils.IrGuard():
main_program, exe, program_guard = new_program()
with program_guard:
x = paddle.static.data(
name='x', shape=[10, 1024], dtype='float32'
)
y = paddle.static.data(
name='y', shape=[10, 1024], dtype='float32'
)
b = x**y
c = x.pow(2)
# d = x.__pow__(2)
# e = x.__rpow__(2)
# TODO(gouzil): Why not use `paddle.static.default_main_program()`？
# Because different case do not isolate parameters (This is a known problem)
(b_np, c_np) = exe.run(
main_program,
feed={"x": x_np, "y": y_np},
fetch_list=[b, c],
)
np.testing.assert_allclose(res_np_b, b_np, rtol=1e-05)
np.testing.assert_allclose(res_np_c, c_np, rtol=1e-05)
# np.testing.assert_allclose(res_np_d, d_np, rtol=1e-05)
# np.testing.assert_allclose(res_np_e, e_np, rtol=1e-05)

def test_mod(self):
paddle.disable_static()
x_np = np.random.randint(1, 100, size=[10, 1024], dtype=np.int64)
y_np = np.random.randint(1, 100, size=[10, 1024], dtype=np.int64)
res_np_b = x_np % y_np
res_np_c = paddle.mod(paddle.to_tensor(x_np), paddle.to_tensor(y_np))
res_np_d = x_np.__mod__(y_np)
paddle.enable_static()
with paddle.pir_utils.IrGuard():
main_program, exe, program_guard = new_program()
with program_guard:
x = paddle.static.data(
name='x', shape=[10, 1024], dtype='int64'
)
y = paddle.static.data(
name='y', shape=[10, 1024], dtype='int64'
)
b = x % y
c = x.mod(y)
d = x.__mod__(y)
(b_np, c_np, d_np) = exe.run(
main_program,
feed={"x": x_np, "y": y_np},
fetch_list=[b, c, d],
)
np.testing.assert_allclose(res_np_b, b_np, atol=1e-05)
np.testing.assert_allclose(res_np_c, c_np, atol=1e-05)
np.testing.assert_allclose(res_np_d, d_np, atol=1e-05)

def test_matmul(self):
paddle.disable_static()
x_np = np.random.uniform(-1, 1, [2, 3]).astype('float32')
y_np = np.random.uniform(-1, 1, [3, 5]).astype('float32')
res_np_b = x_np @ y_np # __matmul__
res_np_c = paddle.matmul(paddle.to_tensor(x_np), paddle.to_tensor(y_np))
res_np_d = x_np.__matmul__(y_np)
paddle.enable_static()
with paddle.pir_utils.IrGuard():
main_program, exe, program_guard = new_program()
with program_guard:
x = paddle.static.data(name='x', shape=[2, 3], dtype='float32')
y = paddle.static.data(name='y', shape=[3, 5], dtype='float32')
b = x @ y
c = x.matmul(y)
d = x.__matmul__(y)
(b_np, c_np, d_np) = exe.run(
main_program,
feed={"x": x_np, "y": y_np},
fetch_list=[b, c, d],
)
np.testing.assert_allclose(res_np_b, b_np, atol=1e-05)
np.testing.assert_allclose(res_np_c, c_np, atol=1e-05)
np.testing.assert_allclose(res_np_d, d_np, atol=1e-05)

def test_floordiv(self):
paddle.disable_static()
x_np = np.full([10, 1024], 10, np.int64)
y_np = np.full([10, 1024], 2, np.int64)
res_np_b = x_np // y_np
res_np_c = paddle.floor_divide(
paddle.to_tensor(x_np), paddle.to_tensor(y_np)
)
res_np_d = x_np.__floordiv__(y_np)
paddle.enable_static()
with paddle.pir_utils.IrGuard():
main_program, exe, program_guard = new_program()
with program_guard:
x = paddle.static.data(
name='x', shape=[10, 1024], dtype='int64'
)
y = paddle.static.data(
name='y', shape=[10, 1024], dtype='int64'
)
b = x // y
c = x.floor_divide(y)
d = x.__floordiv__(y)
(b_np, c_np, d_np) = exe.run(
main_program,
feed={"x": x_np, "y": y_np},
fetch_list=[b, c, d],
)
np.testing.assert_allclose(res_np_b, b_np, atol=1e-05)
np.testing.assert_allclose(res_np_c, c_np, atol=1e-05)
np.testing.assert_allclose(res_np_d, d_np, atol=1e-05)

def test_item(self):
with paddle.pir_utils.IrGuard():
x = paddle.static.data(name='x', shape=[3, 2, 1])
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