wehub-resource-sync
311 lines
9.2 KiB
Python
311 lines
9.2 KiB
Python
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
import unittest
|
|
|
|
import numpy as np
|
|
from get_test_cover_info import (
|
|
XPUOpTestWrapper,
|
|
check_run_big_shape_test,
|
|
create_test_class,
|
|
get_xpu_op_support_types,
|
|
)
|
|
from op_test import convert_float_to_uint16, convert_uint16_to_float
|
|
from op_test_xpu import XPUOpTest
|
|
|
|
import paddle
|
|
from paddle import base
|
|
from paddle.base import Program, core, program_guard
|
|
|
|
typeid_dict = {
|
|
'int16': int(core.VarDesc.VarType.INT16),
|
|
'int32': int(core.VarDesc.VarType.INT32),
|
|
'int64': int(core.VarDesc.VarType.INT64),
|
|
'float32': int(core.VarDesc.VarType.FP32),
|
|
'float16': int(core.VarDesc.VarType.FP16),
|
|
'bfloat16': int(core.VarDesc.VarType.BF16),
|
|
'bool': int(core.VarDesc.VarType.BOOL),
|
|
'int8': int(core.VarDesc.VarType.INT8),
|
|
'uint8': int(core.VarDesc.VarType.UINT8),
|
|
'float64': int(core.VarDesc.VarType.FP64),
|
|
'complex64': int(core.VarDesc.VarType.COMPLEX64),
|
|
'complex128': int(core.VarDesc.VarType.COMPLEX128),
|
|
}
|
|
|
|
|
|
class XPUTestCastOp(XPUOpTestWrapper):
|
|
def __init__(self):
|
|
self.op_name = 'cast'
|
|
self.use_dynamic_create_class = True
|
|
|
|
def dynamic_create_class(self):
|
|
base_class = self.TestCastOp
|
|
classes = []
|
|
for out_type in {
|
|
'float16',
|
|
'bfloat16',
|
|
'float32',
|
|
'int32',
|
|
'int64',
|
|
'int8',
|
|
'uint8',
|
|
'bool',
|
|
'float64',
|
|
}:
|
|
class_name = 'XPUTestCastOp_outtype_' + out_type
|
|
attr_dict = {'out_typename': out_type}
|
|
classes.append([class_name, attr_dict])
|
|
return base_class, classes
|
|
|
|
class TestCastOp(XPUOpTest):
|
|
def setUp(self):
|
|
self.init_shape()
|
|
ipt = np.random.random(size=self.shape)
|
|
in_typename = self.in_type_str
|
|
out_typename = (
|
|
'float32'
|
|
if not hasattr(self, 'out_typename')
|
|
else self.out_typename
|
|
)
|
|
|
|
if in_typename == "bfloat16":
|
|
ipt_x = convert_float_to_uint16(ipt)
|
|
else:
|
|
ipt_x = ipt.astype(in_typename)
|
|
|
|
if out_typename == "bfloat16":
|
|
opt = convert_uint16_to_float(convert_float_to_uint16(ipt_x))
|
|
else:
|
|
opt = ipt_x.astype(out_typename)
|
|
|
|
self.inputs = {'X': ipt_x}
|
|
self.outputs = {'Out': opt}
|
|
self.attrs = {
|
|
'in_dtype': typeid_dict[in_typename],
|
|
'out_dtype': typeid_dict[out_typename],
|
|
}
|
|
self.op_type = 'cast'
|
|
self.__class__.no_need_check_grad = True
|
|
|
|
def init_shape(self):
|
|
self.shape = [10, 10]
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape1(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [1, 8192, 5120]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape2(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [1, 8192]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape3(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [1, 8192, 1, 128]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape4(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [8192]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape5(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [31776]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape6(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [5120]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape7(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [3456]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape8(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [1920]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape9(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [31776, 5120]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape10(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [5120, 1920]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape11(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [640, 5120]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape12(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [5120, 3456]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape13(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [1728, 5120]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape14(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [5120, 31776]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape15(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [27724]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape16(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [32, 5120]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape17(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [1728, 32]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape18(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [32, 3456]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape19(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [32, 3456]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape20(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [5120, 32]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape21(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [640, 32]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape22(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [32, 1920]
|
|
|
|
@check_run_big_shape_test()
|
|
class TestCastOpLargeShape23(TestCastOp):
|
|
def init_shape(self):
|
|
self.shape = [19984]
|
|
|
|
|
|
support_types = get_xpu_op_support_types('cast')
|
|
real_types = [t for t in support_types if t != 'complex64']
|
|
for stype in real_types:
|
|
create_test_class(globals(), XPUTestCastOp, stype)
|
|
|
|
if 'complex64' in support_types:
|
|
|
|
class TestCastOpComplex1(XPUOpTest):
|
|
def setUp(self):
|
|
self.init_shape()
|
|
ipt = np.random.random(size=self.shape)
|
|
|
|
in_typename = 'float32'
|
|
out_typename = 'complex64'
|
|
|
|
ipt_x = ipt.astype(in_typename)
|
|
opt = ipt_x.astype(out_typename)
|
|
|
|
self.inputs = {'X': ipt_x}
|
|
self.outputs = {'Out': opt}
|
|
self.attrs = {
|
|
'in_dtype': typeid_dict[in_typename],
|
|
'out_dtype': typeid_dict[out_typename],
|
|
}
|
|
self.op_type = 'cast'
|
|
self.__class__.no_need_check_grad = True
|
|
|
|
def init_shape(self):
|
|
self.shape = [10, 10]
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
class TestCastOpComplex2(XPUOpTest):
|
|
def setUp(self):
|
|
self.init_shape()
|
|
|
|
real_part = np.random.random(size=self.shape)
|
|
imag_part = np.random.random(size=self.shape)
|
|
ipt = real_part + 1j * imag_part
|
|
|
|
in_typename = 'complex64'
|
|
out_typename = 'float32'
|
|
|
|
ipt_x = ipt.astype(in_typename)
|
|
opt = ipt_x.real.astype(out_typename)
|
|
|
|
self.inputs = {'X': ipt_x}
|
|
self.outputs = {'Out': opt}
|
|
self.attrs = {
|
|
'in_dtype': typeid_dict[in_typename],
|
|
'out_dtype': typeid_dict[out_typename],
|
|
}
|
|
self.op_type = 'cast'
|
|
self.__class__.no_need_check_grad = True
|
|
|
|
def init_shape(self):
|
|
self.shape = [10, 10]
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
|
|
class TestCastOpError(unittest.TestCase):
|
|
def test_errors(self):
|
|
with program_guard(Program(), Program()):
|
|
# The input type of cast_op must be Variable.
|
|
x1 = base.create_lod_tensor(
|
|
np.array([[-1]]), [[1]], base.XPUPlace(0)
|
|
)
|
|
self.assertRaises(TypeError, paddle.cast, x1, 'int32')
|
|
|
|
|
|
class TestCastOpEmpty(unittest.TestCase):
|
|
def test_cast_op_empty(self):
|
|
if paddle.is_compiled_with_xpu():
|
|
paddle.set_device('xpu')
|
|
paddle.disable_static()
|
|
data = paddle.ones([0, 10], dtype='float32')
|
|
out = paddle.cast(data, 'int32')
|
|
self.assertEqual(out.shape, data.shape)
|
|
self.assertEqual(out.dtype, paddle.int32)
|
|
paddle.enable_static()
|
|
|
|
|
|
if __name__ == '__main__':
|
|
paddle.enable_static()
|
|
unittest.main()
|