mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
70 lines
2.4 KiB
Python
70 lines
2.4 KiB
Python
# SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
|
|
# SPDX-License-Identifier: Apache-2.0
|
|
#
|
|
# 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 os
|
|
import sys
|
|
import unittest
|
|
|
|
import torch
|
|
from parameterized import parameterized
|
|
|
|
import tensorrt_llm
|
|
from tensorrt_llm import Tensor
|
|
|
|
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
|
|
from utils.util import (create_session, run_session, skip_bf16_pre_ampere,
|
|
unittest_name_func)
|
|
|
|
|
|
class TestIdentity(unittest.TestCase):
|
|
|
|
def setUp(self):
|
|
tensorrt_llm.logger.set_level('error')
|
|
|
|
@parameterized.expand([('float32', False), ('float32', True),
|
|
('float16', False), ('float16', True),
|
|
('bfloat16', False), ('bfloat16', True)],
|
|
name_func=unittest_name_func)
|
|
def test_identity(self, dtype, use_plugin):
|
|
# Skip tests that are not supported in pre-ampere architecture
|
|
skip_bf16_pre_ampere(dtype)
|
|
|
|
x_data = torch.randn(
|
|
(4, 6, 3, 4),
|
|
dtype=tensorrt_llm._utils.str_dtype_to_torch(dtype),
|
|
device="cuda")
|
|
|
|
# construct trt network
|
|
builder = tensorrt_llm.Builder()
|
|
network = builder.create_network()
|
|
if use_plugin:
|
|
network.plugin_config.identity_plugin = dtype
|
|
|
|
with tensorrt_llm.net_guard(network):
|
|
x = Tensor(name='x',
|
|
shape=x_data.shape,
|
|
dtype=tensorrt_llm.str_dtype_to_trt(dtype))
|
|
output = tensorrt_llm.functional.identity(x)
|
|
output.mark_output('output', dtype)
|
|
|
|
# trt run
|
|
session = create_session(builder, network, precision=dtype)
|
|
inputs = {
|
|
'x': x_data,
|
|
}
|
|
outputs = run_session(session, inputs)
|
|
|
|
# compare diff
|
|
torch.testing.assert_close(x_data, outputs['output'])
|