wehub-resource-sync
364 lines
8.5 KiB
Python
364 lines
8.5 KiB
Python
# Copyright (c) 2023 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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# GET_ITER (new)
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# FOR_ITER (new)
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from __future__ import annotations
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import unittest
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from test_case_base import (
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TestCaseBase,
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test_instruction_translator_cache_context,
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)
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import paddle
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from paddle.jit import sot
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from paddle.jit.sot import symbolic_translate
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from paddle.jit.sot.utils import strict_mode_guard
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def gener():
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yield 1
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yield 2
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yield 3
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def for_list_1(x: paddle.Tensor):
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for i in [1, 2, 3]:
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x += i
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if x > 2:
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x += 1
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else:
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x -= 1
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return x
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def for_list_2(x: paddle.Tensor):
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for i in [1, 2, 3]:
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x += i
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if i > 2:
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x += 1
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else:
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x -= 1
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return x
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def for_dict(x: paddle.Tensor):
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map = {1: 2, 3: 4}
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for k in map.keys():
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x += k
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for v in map.values():
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x += v
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for k, v in map.items():
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x += k
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x += v
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return x
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def for_iter(x, it):
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for item in it:
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x += item
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return x
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def for_for_fallback(x, it):
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for i in [1, 2, 3]:
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for item in it:
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x += item
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return x
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def for_break(x: paddle.Tensor, it):
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for i in [1, 2, 3]:
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x += i
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if i == 2:
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break
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for i in it:
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x += i
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if i == 2:
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break
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return x
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def for_continue(x: paddle.Tensor, it):
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for i in [1, 2, 3]:
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if i == 2:
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continue
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x += i
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for i in it:
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if i == 2:
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continue
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x += i
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return x
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def for_enumerate_var_with_nested_range(x_array):
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x = paddle.tensor.fill_constant([1], 'int32', 0)
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x_array = paddle.to_tensor(x_array)
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for i, num in enumerate(x_array):
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for idx in range(num):
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x = x + num
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return x
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def for_create_tmp_in_loop(x, it):
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s = x
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for i in it:
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tmp = i
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s += tmp
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return s, tmp
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def for_without_zero_iter(self_res_dict, output):
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res_dict = {"logits": output}
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for res_key in list(self_res_dict):
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res_dict[res_key] = self_res_dict.pop(res_key)
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return res_dict
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def for_reconstruct_range_iter():
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for i in range(3):
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sot.psdb.breakgraph()
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global_var_name = None
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def for_tmp_var_with_same_name_as_global_var():
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total = 0
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for i in range(3):
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global_var_name = i + 3
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sot.psdb.breakgraph()
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total += global_var_name
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return total
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def for_layer_list(layer_list, x):
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for net in layer_list:
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x = net(x)
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return x
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class TestForLoop(TestCaseBase):
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@strict_mode_guard(False)
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def test_list(self):
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a = paddle.to_tensor(1)
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self.assert_results(for_list_1, a)
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def test_list_with_fallback(self):
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a = paddle.to_tensor(1)
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self.assert_results(for_list_2, a)
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def test_dict(self):
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a = paddle.to_tensor(1)
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self.assert_results(for_dict, a)
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@strict_mode_guard(False)
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def test_fallback(self):
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a = paddle.to_tensor(1)
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sym_output = symbolic_translate(for_iter)(a, gener())
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paddle_output = for_iter(a, gener())
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self.assert_nest_match(sym_output, paddle_output)
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@strict_mode_guard(False)
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def test_for_iter_fallback(self):
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a = paddle.to_tensor(1)
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sym_output = symbolic_translate(for_iter)(a, gener())
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paddle_output = for_iter(a, gener())
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self.assert_nest_match(sym_output, paddle_output)
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@strict_mode_guard(False)
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def test_for_break(self):
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a = paddle.to_tensor(1)
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sym_output = symbolic_translate(for_break)(a, gener())
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paddle_output = for_break(a, gener())
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self.assert_nest_match(sym_output, paddle_output)
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@strict_mode_guard(False)
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def test_for_continue(self):
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a = paddle.to_tensor(1)
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sym_output = symbolic_translate(for_continue)(a, gener())
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paddle_output = for_continue(a, gener())
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self.assert_nest_match(sym_output, paddle_output)
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@strict_mode_guard(False)
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def test_create_var_in_loop(self):
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x = paddle.to_tensor(1, dtype="float32")
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a = [1, 2, 3]
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self.assert_results(for_create_tmp_in_loop, x, a)
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sym_output = symbolic_translate(for_create_tmp_in_loop)(x, iter(a))
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paddle_output = for_create_tmp_in_loop(x, iter(a))
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self.assert_nest_match(sym_output, paddle_output)
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@strict_mode_guard(False)
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def test_create_var_in_loop_with_same_name_as_global(self):
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self.assert_results(for_tmp_var_with_same_name_as_global_var)
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def test_for_without_zero_iter(self):
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self_res_dict = {}
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output = paddle.to_tensor(2)
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self.assert_results(for_without_zero_iter, self_res_dict, output)
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@strict_mode_guard(False)
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def test_reconstruct_range_iter(self):
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self.assert_results(for_reconstruct_range_iter)
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def test_layer_list(self):
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layers = paddle.nn.LayerList()
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for i in range(5):
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layers.append(paddle.nn.Linear(5, 5))
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x = paddle.rand([5], dtype="float32")
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self.assert_results(for_layer_list, layers, x)
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def run_list_comp(x):
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out = [s.chunk(2, axis=1) for s in x]
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return out
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class TestListComp(TestCaseBase):
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def test_list_comp(self):
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x = [paddle.randn([1, 4]), paddle.randn([1, 4])]
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self.assert_results(run_list_comp, x)
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def for_enumerate_cache(func_list, x):
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out = None
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for idx, func in enumerate(func_list):
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out = func(x[idx])
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return out
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class TestEnumerateCache(TestCaseBase):
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def test_run(self):
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func_list = [
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paddle.nn.Linear(10, 10),
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]
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x = [
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paddle.randn([5, 10]),
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]
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with test_instruction_translator_cache_context() as ctx:
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out = symbolic_translate(for_enumerate_cache)(func_list, x)
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out = symbolic_translate(for_enumerate_cache)(func_list, x)
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self.assertEqual(ctx.translate_count, 1)
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# after_loop_fn need zzz, and zzz is created as UndefinedVar when generating loop body
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# do not set zzz as UndefinedVar again
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def undefined_var_case_0():
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for i in [1, 2]:
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sot.psdb.breakgraph()
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zzz = i
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zzz = zzz + 1
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return zzz
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# after_loop_fn need create zzz as UndefinedVar
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def undefined_var_case_1():
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for i in [1, 2]:
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sot.psdb.breakgraph()
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aaa = i
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for i in [1, 3]:
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zzz = i
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zzz = zzz + 1
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return zzz
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class TestUndefinedVarInRiskyCodes(TestCaseBase):
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@strict_mode_guard(False)
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def test_undefined_var_case_0(self):
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self.assert_results(undefined_var_case_0)
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@strict_mode_guard(False)
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def test_undefined_var_case_1(self):
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self.assert_results(undefined_var_case_1)
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def comp_with_fallback(x):
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paddle.jit.sot.psdb.fallback()
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y = [len(t) for t in x]
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return paddle.to_tensor(y)
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class TestListCompWithFallback(TestCaseBase):
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@strict_mode_guard(False)
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def test_list_comp_with_fallback(self):
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x = [paddle.randn([4, 6])]
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self.assert_results(comp_with_fallback, x)
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def for_arange(x):
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for i in paddle.arange(0, 5):
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x = x + i
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return x
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class TestArange(TestCaseBase):
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def test_arange(self):
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x = paddle.to_tensor(1)
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self.assert_results(for_arange, x)
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def for_break_with_load_same_consts(x: paddle.Tensor):
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y = None
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z = None
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for i in [1, 2, 3]:
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if y is None:
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y = i
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if z is None:
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z = i
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x += y + z
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sot.psdb.breakgraph()
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return x
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class TestForBreakWithLoadSameConsts(TestCaseBase):
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@strict_mode_guard(False)
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def test_for_break_with_load_same_consts(self):
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x = paddle.to_tensor(1)
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self.assert_results(for_break_with_load_same_consts, x)
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def for_break_with_write_pre_defined_name(x: paddle.Tensor):
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y = None
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for i in [1, 2, 3]:
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y = i
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sot.psdb.breakgraph()
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return x + 1
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class TestForBreakWithWritePreDefinedName(TestCaseBase):
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@strict_mode_guard(False)
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def test_for_break_with_write_pre_defined_name(self):
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x = paddle.to_tensor(1)
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self.assert_results(for_break_with_write_pre_defined_name, x)
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if __name__ == "__main__":
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unittest.main()
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