wehub-resource-sync
235 lines
9.0 KiB
Python
235 lines
9.0 KiB
Python
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import warnings
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import paddle
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from paddle.base import core
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paddle.enable_static()
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def execute(main_program, startup_program):
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if paddle.is_compiled_with_xpu():
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place = paddle.XPUPlace(0)
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else:
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place = paddle.CPUPlace()
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exe = paddle.static.Executor(place)
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exe.run(startup_program)
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exe.run(main_program)
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def get_valid_warning_num(warning, w):
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num = 0
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for i in range(len(w)):
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if warning in str(w[i].message):
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num += 1
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return num
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class TestDeviceGuard(unittest.TestCase):
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def test_device_guard(self):
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with paddle.pir_utils.OldIrGuard():
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main_program = paddle.static.Program()
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startup_program = paddle.static.Program()
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with paddle.static.program_guard(main_program, startup_program):
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data1 = paddle.full(
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shape=[1, 3, 8, 8], fill_value=0.5, dtype='float32'
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)
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data2 = paddle.full(
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shape=[1, 3, 5, 5], fill_value=0.5, dtype='float32'
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)
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shape = paddle.shape(data2)
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with paddle.static.device_guard("cpu"):
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shape = paddle.slice(shape, axes=[0], starts=[0], ends=[4])
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with paddle.static.device_guard("xpu"):
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out = paddle.crop(data1, shape=shape)
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# check if the device attr is set correctly
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all_ops = main_program.global_block().ops
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device_attr_name = (
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core.op_proto_and_checker_maker.kOpDeviceAttrName()
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)
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for op in all_ops:
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if op.type == 'slice':
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self.assertEqual(op.desc.attr(device_attr_name), "cpu")
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if op.type == 'crop_tensor':
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self.assertEqual(op.desc.attr(device_attr_name), "xpu")
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execute(main_program, startup_program)
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def test_device_guard_with_id(self):
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with paddle.pir_utils.OldIrGuard():
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main_program = paddle.static.Program()
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startup_program = paddle.static.Program()
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with paddle.static.program_guard(main_program, startup_program):
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data1 = paddle.full(
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shape=[1, 3, 8, 8], fill_value=0.5, dtype='float32'
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)
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data2 = paddle.full(
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shape=[1, 3, 5, 5], fill_value=0.5, dtype='float32'
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)
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shape = paddle.shape(data2)
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with paddle.static.device_guard("cpu"):
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shape = paddle.slice(shape, axes=[0], starts=[0], ends=[4])
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with paddle.static.device_guard("xpu:1"):
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out = paddle.crop(data1, shape=shape)
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# check if the device attr is set correctly
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all_ops = main_program.global_block().ops
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device_attr_name = (
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core.op_proto_and_checker_maker.kOpDeviceAttrName()
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)
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for op in all_ops:
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if op.type == 'slice':
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self.assertEqual(op.desc.attr(device_attr_name), "cpu")
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if op.type == 'crop_tensor':
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self.assertEqual(op.desc.attr(device_attr_name), "xpu:1")
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execute(main_program, startup_program)
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def test_cpu_only_op(self):
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main_program = paddle.static.Program()
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startup_program = paddle.static.Program()
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with paddle.static.program_guard(main_program, startup_program):
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x = paddle.full(
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shape=[2, 255, 13, 13], fill_value=0.3, dtype='float32'
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)
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gt_box = paddle.full(
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shape=[2, 6, 4], fill_value=0.5, dtype='float32'
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)
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gt_label = paddle.full(shape=[2, 6], fill_value=1.0, dtype='int32')
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gt_score = paddle.full(
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shape=[2, 6], fill_value=0.5, dtype='float32'
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)
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anchors = [
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10,
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13,
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16,
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30,
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33,
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23,
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30,
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61,
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62,
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45,
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59,
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119,
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116,
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90,
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156,
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198,
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373,
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326,
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]
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anchor_mask = [0, 1, 2]
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with paddle.static.device_guard("xpu"):
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# yolo_loss has cpu kernel, so its cpu kernel will be executed
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loss = paddle.vision.ops.yolo_loss(
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x=x,
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gt_box=gt_box,
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gt_label=gt_label,
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gt_score=gt_score,
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anchors=anchors,
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anchor_mask=anchor_mask,
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class_num=80,
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ignore_thresh=0.7,
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downsample_ratio=32,
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)
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execute(main_program, startup_program)
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def test_without_kernel_op(self):
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with paddle.pir_utils.OldIrGuard():
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main_program = paddle.static.Program()
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startup_program = paddle.static.Program()
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with paddle.static.program_guard(main_program, startup_program):
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i = paddle.full(shape=[1], dtype='int64', fill_value=0)
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loop_len = paddle.full(shape=[1], dtype='int64', fill_value=10)
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cond = paddle.less_than(x=i, y=loop_len)
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with warnings.catch_warnings(record=True) as w:
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warnings.simplefilter("always")
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with paddle.static.device_guard("cpu"):
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while_op = paddle.static.nn.control_flow.While(
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cond=cond
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)
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with while_op.block():
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i = paddle.increment(x=i, value=1)
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paddle.assign(
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paddle.less_than(x=i, y=loop_len), cond
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)
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warning = "The Op(while) is not support to set device."
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warning_num = get_valid_warning_num(warning, w)
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assert warning_num == 1
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all_ops = main_program.global_block().ops
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device_attr_name = (
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core.op_proto_and_checker_maker.kOpDeviceAttrName()
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)
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for op in all_ops:
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if op.type == 'while':
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self.assertEqual(op.desc.attr(device_attr_name), "")
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execute(main_program, startup_program)
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def test_error(self):
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def device_attr():
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with paddle.static.device_guard("cpu1"):
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out = paddle.full(shape=[1], fill_value=0.2, dtype='float32')
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def device_attr2():
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with paddle.static.device_guard("cpu:1"):
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out = paddle.full(shape=[1], fill_value=0.2, dtype='float32')
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self.assertRaises(ValueError, device_attr)
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self.assertRaises(ValueError, device_attr2)
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# check if op_descs have op_device attr
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def test_op_descs_device_attr(self):
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with paddle.pir_utils.OldIrGuard():
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main_program = paddle.static.Program()
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startup_program = paddle.static.Program()
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with paddle.static.program_guard(main_program, startup_program):
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data1 = paddle.static.data(
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name="data_1", shape=[4, 2], dtype="float32"
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)
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label = paddle.static.data(
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name="label", shape=[4, 1], dtype="int64"
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)
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fc1 = paddle.static.nn.fc(x=data1, size=10)
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fc2 = paddle.static.nn.fc(x=fc1, size=10)
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with paddle.static.device_guard("xpu"):
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out = paddle.nn.functional.softmax_with_cross_entropy(
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logits=fc1 + fc2, label=label
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)
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loss = paddle.mean(out)
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opt = paddle.optimizer.SGD(0.1)
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opt.minimize(loss)
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all_ops = main_program.global_block().ops
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device_attr_name = (
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core.op_proto_and_checker_maker.kOpDeviceAttrName()
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)
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for op in all_ops:
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self.assertEqual(True, op.desc.has_attr(device_attr_name))
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# fill_constant(backward op) is append to mean op, which should have
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# the same op_device value as mean op
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if op.desc == 'fill_constant':
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self.assertEqual(op.desc.attr(device_attr_name), "xpu")
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if __name__ == '__main__':
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unittest.main()
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