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https://github.com/NVIDIA/TensorRT-LLM.git
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b777bd6475
* Update TensorRT-LLM --------- Co-authored-by: RunningLeon <mnsheng@yeah.net> Co-authored-by: Tlntin <TlntinDeng01@Gmail.com> Co-authored-by: ZHENG, Zhen <zhengzhen.z@qq.com> Co-authored-by: Pham Van Ngoan <ngoanpham1196@gmail.com> Co-authored-by: Nathan Price <nathan@abridge.com> Co-authored-by: Tushar Goel <tushar.goel.ml@gmail.com> Co-authored-by: Mati <132419219+matichon-vultureprime@users.noreply.github.com>
110 lines
2.9 KiB
Python
110 lines
2.9 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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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 torch
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from tensorrt_llm.layers import GroupNorm
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from tensorrt_llm.module import Module, ModuleList
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class Module1(Module):
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def __init__(self, name):
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super(Module1, self).__init__()
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self.name = name
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def forward(self):
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self.register_network_output('o1', 1)
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class Module2(Module):
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def __init__(self):
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super(Module2, self).__init__()
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self.name = 'module2'
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self.m1 = Module1('m1')
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self.m2 = Module1('m2')
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def forward(self):
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self.m1.forward()
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self.m2.forward()
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self.register_network_output('o2', 2)
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self.register_network_output('o3', 3)
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class Module3(Module):
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def __init__(self):
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super(Module3, self).__init__()
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self.name = 'module3'
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self.m1 = Module2()
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def forward(self):
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self.m1.forward()
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self.register_network_output('o4', 4)
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class Module4(Module):
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def __init__(self):
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super(Module4, self).__init__()
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self.layers = ModuleList([Module2(), Module2()])
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def forward(self):
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for l in self.layers:
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l.forward()
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class TestModule(unittest.TestCase):
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def test_module(self):
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m = Module3()
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m.forward()
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self.assertEqual(4, len(list(m.named_modules())))
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self.assertEqual(5, len(list(m.named_network_outputs())))
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self.assertEqual(
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[("", m), ("m1", m.m1), ("m1.m1", m.m1.m1), ("m1.m2", m.m1.m2)],
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list(m.named_modules()),
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)
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self.assertEqual(
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[("", m, None), ("m1", m.m1, m), ("m1.m1", m.m1.m1, m.m1),
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("m1.m2", m.m1.m2, m.m1)],
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list(m.named_modules_with_parent()),
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)
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def test_module_list(self):
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m = Module4()
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m.forward()
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self.assertEqual(8, len(list(m.named_modules())))
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self.assertEqual(8, len(list(m.named_network_outputs())))
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def test_module_named_parameter(self):
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m = GroupNorm(2, 4)
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md = {k: v for k, v in m.named_parameters()}
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tm = torch.nn.GroupNorm(2, 4)
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tmd = {k: v for k, v in tm.named_parameters()}
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self.assertEqual(len(md), len(tmd))
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for k, _ in md.items():
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self.assertIn(k, tmd)
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for k, _ in tmd.items():
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self.assertIn(k, md)
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