wehub-resource-sync
121 lines
5.1 KiB
Python
121 lines
5.1 KiB
Python
# Copyright (c) 2025 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.
|
|
|
|
from __future__ import annotations
|
|
|
|
import unittest
|
|
|
|
from test_case_base import (
|
|
TestCaseBase,
|
|
test_instruction_translator_cache_context,
|
|
)
|
|
|
|
import paddle
|
|
from paddle.jit.sot.psdb import check_no_breakgraph
|
|
|
|
|
|
@check_no_breakgraph
|
|
def tensor_with_marked_dynamic_dims(tensor):
|
|
return tensor + 1
|
|
|
|
|
|
@check_no_breakgraph
|
|
def multiple_tensors_with_marked_dynamic_dims(tensor1, tensor2):
|
|
return tensor1.sum() + tensor2.sum()
|
|
|
|
|
|
class TestUserSpecifiedDynamicDims(TestCaseBase):
|
|
def test_auto_inferred_dynamic_dims(self):
|
|
with test_instruction_translator_cache_context() as ctx:
|
|
self.assertEqual(ctx.translate_count, 0)
|
|
x1 = paddle.rand([5, 6], dtype='float32')
|
|
self.assert_results(tensor_with_marked_dynamic_dims, x1)
|
|
self.assertEqual(ctx.translate_count, 1)
|
|
x2 = paddle.rand([4, 6], dtype='float32')
|
|
self.assert_results(tensor_with_marked_dynamic_dims, x2)
|
|
self.assertEqual(ctx.translate_count, 2)
|
|
x3 = paddle.rand([3, 6], dtype='float32')
|
|
self.assert_results(tensor_with_marked_dynamic_dims, x3)
|
|
self.assertEqual(ctx.translate_count, 2)
|
|
|
|
def test_user_specified_dynamic_dims(self):
|
|
with test_instruction_translator_cache_context() as ctx:
|
|
self.assertEqual(ctx.translate_count, 0)
|
|
x1 = paddle.rand([5, 6], dtype='float32')
|
|
paddle.jit.marker.dynamic_dims(x1, [0])
|
|
self.assert_results(tensor_with_marked_dynamic_dims, x1)
|
|
self.assertEqual(ctx.translate_count, 1)
|
|
x2 = paddle.rand([4, 6], dtype='float32')
|
|
self.assert_results(tensor_with_marked_dynamic_dims, x2)
|
|
self.assertEqual(ctx.translate_count, 1)
|
|
x3 = paddle.rand([3, 6], dtype='float32')
|
|
self.assert_results(tensor_with_marked_dynamic_dims, x3)
|
|
self.assertEqual(ctx.translate_count, 1)
|
|
|
|
def test_user_specified_multiple_dynamic_dims(self):
|
|
with test_instruction_translator_cache_context() as ctx:
|
|
self.assertEqual(ctx.translate_count, 0)
|
|
x1 = paddle.rand([5, 6], dtype='float32')
|
|
paddle.jit.marker.dynamic_dims(x1, [0, 1])
|
|
self.assert_results(tensor_with_marked_dynamic_dims, x1)
|
|
self.assertEqual(ctx.translate_count, 1)
|
|
x2 = paddle.rand([4, 6], dtype='float32')
|
|
self.assert_results(tensor_with_marked_dynamic_dims, x2)
|
|
self.assertEqual(ctx.translate_count, 1)
|
|
x3 = paddle.rand([3, 7], dtype='float32')
|
|
self.assert_results(tensor_with_marked_dynamic_dims, x3)
|
|
self.assertEqual(ctx.translate_count, 1)
|
|
|
|
def test_multiple_tensors_with_marked_dynamic_dims(self):
|
|
with test_instruction_translator_cache_context() as ctx:
|
|
self.assertEqual(ctx.translate_count, 0)
|
|
x1 = paddle.rand([5, 6], dtype='float32')
|
|
x2 = paddle.rand([5, 6], dtype='float32')
|
|
paddle.jit.marker.dynamic_dims(x1, [0])
|
|
paddle.jit.marker.dynamic_dims(x2, [0])
|
|
self.assert_results(
|
|
multiple_tensors_with_marked_dynamic_dims, x1, x2
|
|
)
|
|
self.assertEqual(ctx.translate_count, 1)
|
|
x3 = paddle.rand([4, 6], dtype='float32')
|
|
x4 = paddle.rand([5, 6], dtype='float32')
|
|
self.assert_results(
|
|
multiple_tensors_with_marked_dynamic_dims, x3, x4
|
|
)
|
|
self.assertEqual(ctx.translate_count, 1)
|
|
x5 = paddle.rand([4, 6], dtype='float32')
|
|
x6 = paddle.rand([4, 6], dtype='float32')
|
|
self.assert_results(
|
|
multiple_tensors_with_marked_dynamic_dims, x5, x6
|
|
)
|
|
self.assertEqual(ctx.translate_count, 1)
|
|
|
|
def test_mix_auto_inferred_and_specified_dynamic_dims(self):
|
|
with test_instruction_translator_cache_context() as ctx:
|
|
self.assertEqual(ctx.translate_count, 0)
|
|
x1 = paddle.rand([5, 6], dtype='float32')
|
|
paddle.jit.marker.dynamic_dims(x1, [0])
|
|
self.assert_results(tensor_with_marked_dynamic_dims, x1)
|
|
self.assertEqual(ctx.translate_count, 1)
|
|
x2 = paddle.rand([4, 6], dtype='float32')
|
|
self.assert_results(tensor_with_marked_dynamic_dims, x2)
|
|
self.assertEqual(ctx.translate_count, 1)
|
|
x3 = paddle.rand([3, 7], dtype='float32')
|
|
self.assert_results(tensor_with_marked_dynamic_dims, x3)
|
|
self.assertEqual(ctx.translate_count, 2)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|