mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-06 09:07:10 +08:00
352 lines
6.1 KiB
Python
352 lines
6.1 KiB
Python
# Copyright (c) 2025 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 numpy as np
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import paddle
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from fastdeploy.model_executor.ops.xpu import update_inputs
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np.random.seed(2023)
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bs = 48
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max_bs = 64
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max_input_length = 6144
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stop_flags = np.random.randint(0, 2, max_bs).astype("bool")
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not_need_stop = np.array([1], "bool")
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seq_lens_this_time = np.zeros([bs], "int32")
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seq_lens_encoder = np.zeros([max_bs], "int32")
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seq_lens_decoder = np.zeros([max_bs], "int32")
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for i in range(bs):
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if i % 2 == 0:
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seq_lens_encoder[i] = i
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seq_lens_this_time[i] = i
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else:
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seq_lens_decoder[i] = i
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seq_lens_this_time[i] = 1
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input_ids_np = np.random.randint(1, 10, [max_bs, max_input_length], "int64")
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stop_nums = np.array([max_bs], "int64")
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next_tokens = np.random.randint(1, 10, [max_bs], "int64")
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is_block_step = np.random.randint(0, 2, [max_bs]).astype("bool")
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stop_flags = paddle.to_tensor(stop_flags)
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not_need_stop = paddle.to_tensor(not_need_stop, place=paddle.CPUPlace())
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seq_lens_this_time = paddle.to_tensor(seq_lens_this_time)
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seq_lens_encoder = paddle.to_tensor(seq_lens_encoder)
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seq_lens_decoder = paddle.to_tensor(seq_lens_decoder)
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input_ids = paddle.to_tensor(input_ids_np)
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stop_nums = paddle.to_tensor(stop_nums)
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next_tokens = paddle.to_tensor(next_tokens)
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is_block_step = paddle.to_tensor(is_block_step)
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print("stop_flags:\n", stop_flags)
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print("not_need_stop:\n", not_need_stop)
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print("seq_lens_this_time:\n", seq_lens_this_time)
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print("seq_lens_encoder:\n", seq_lens_encoder)
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print("seq_lens_decoder:\n", seq_lens_decoder)
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print("input_ids:\n", input_ids)
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print("stop_nums:\n", stop_nums)
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print("next_tokens:\n", next_tokens)
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print("is_block_step:\n", is_block_step)
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update_inputs(
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stop_flags,
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not_need_stop,
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seq_lens_this_time,
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seq_lens_encoder,
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seq_lens_decoder,
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input_ids,
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stop_nums,
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next_tokens,
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is_block_step,
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)
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print("-" * 50)
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print("stop_flags:\n", stop_flags)
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print("not_need_stop:\n", not_need_stop)
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print("seq_lens_this_time:\n", seq_lens_this_time)
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print("seq_lens_encoder:\n", seq_lens_encoder)
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print("seq_lens_decoder:\n", seq_lens_decoder)
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print("input_ids:\n", input_ids)
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print("stop_nums:\n", stop_nums)
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print("next_tokens:\n", next_tokens)
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ref_not_need_stop_out = np.array([True])
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ref_seq_lens_this_time_out = np.array(
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[
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0,
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0,
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1,
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0,
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0,
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1,
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0,
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1,
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1,
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1,
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0,
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1,
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1,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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1,
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1,
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0,
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1,
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1,
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0,
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1,
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1,
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0,
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0,
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0,
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1,
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1,
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0,
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1,
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0,
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0,
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1,
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0,
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1,
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0,
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0,
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1,
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0,
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0,
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1,
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1,
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1,
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],
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"int32",
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)
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ref_seq_lens_encoder_out = np.array(
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[
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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],
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"int32",
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)
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ref_seq_lens_decoder_out = np.array(
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[
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0,
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0,
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2,
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0,
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0,
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6,
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0,
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8,
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8,
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10,
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0,
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12,
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12,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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20,
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22,
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0,
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24,
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24,
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0,
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26,
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28,
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0,
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0,
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0,
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32,
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32,
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0,
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34,
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0,
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0,
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38,
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0,
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40,
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0,
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0,
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42,
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0,
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0,
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46,
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46,
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48,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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0,
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],
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"int32",
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)
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input_ids_np[:, 0] = np.array(
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[
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6,
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5,
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9,
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8,
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6,
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2,
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8,
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1,
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3,
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1,
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3,
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6,
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9,
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8,
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1,
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9,
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1,
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8,
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8,
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6,
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7,
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6,
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5,
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3,
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5,
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9,
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3,
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6,
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3,
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9,
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8,
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8,
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8,
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8,
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4,
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8,
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7,
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4,
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2,
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3,
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5,
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8,
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4,
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2,
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5,
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6,
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8,
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9,
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6,
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7,
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4,
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2,
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4,
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6,
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2,
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3,
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4,
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9,
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7,
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2,
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1,
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8,
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7,
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8,
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],
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"int64",
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)
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assert not_need_stop.numpy() == ref_not_need_stop_out, "Check not_need_stop failed."
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assert np.all(seq_lens_this_time.numpy() == ref_seq_lens_this_time_out), "Check seq_lens_this_time failed."
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assert np.all(seq_lens_encoder.numpy() == ref_seq_lens_encoder_out), "Check seq_lens_encoder failed."
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assert np.all(seq_lens_decoder.numpy() == ref_seq_lens_decoder_out), "Check seq_lens_decoder failed."
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assert np.all(input_ids.numpy() == input_ids_np), "Check input_ids failed."
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