# 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.

import numpy as np
import paddle

from fastdeploy.model_executor.ops.xpu import update_inputs

np.random.seed(2023)

bs = 48
max_bs = 64
max_input_length = 6144

stop_flags = np.random.randint(0, 2, max_bs).astype("bool")
not_need_stop = np.array([1], "bool")
seq_lens_this_time = np.zeros([bs], "int32")
seq_lens_encoder = np.zeros([max_bs], "int32")
seq_lens_decoder = np.zeros([max_bs], "int32")
for i in range(bs):
    if i % 2 == 0:
        seq_lens_encoder[i] = i
        seq_lens_this_time[i] = i
    else:
        seq_lens_decoder[i] = i
        seq_lens_this_time[i] = 1
input_ids_np = np.random.randint(1, 10, [max_bs, max_input_length], "int64")
stop_nums = np.array([max_bs], "int64")
next_tokens = np.random.randint(1, 10, [max_bs], "int64")
is_block_step = np.random.randint(0, 2, [max_bs]).astype("bool")

stop_flags = paddle.to_tensor(stop_flags)
not_need_stop = paddle.to_tensor(not_need_stop, place=paddle.CPUPlace())
seq_lens_this_time = paddle.to_tensor(seq_lens_this_time)
seq_lens_encoder = paddle.to_tensor(seq_lens_encoder)
seq_lens_decoder = paddle.to_tensor(seq_lens_decoder)
input_ids = paddle.to_tensor(input_ids_np)
stop_nums = paddle.to_tensor(stop_nums)
next_tokens = paddle.to_tensor(next_tokens)
is_block_step = paddle.to_tensor(is_block_step)

print("stop_flags:\n", stop_flags)
print("not_need_stop:\n", not_need_stop)
print("seq_lens_this_time:\n", seq_lens_this_time)
print("seq_lens_encoder:\n", seq_lens_encoder)
print("seq_lens_decoder:\n", seq_lens_decoder)
print("input_ids:\n", input_ids)
print("stop_nums:\n", stop_nums)
print("next_tokens:\n", next_tokens)
print("is_block_step:\n", is_block_step)

update_inputs(stop_flags, not_need_stop, seq_lens_this_time, seq_lens_encoder,
              seq_lens_decoder, input_ids, stop_nums, next_tokens,
              is_block_step)

print("-" * 50)
print("stop_flags:\n", stop_flags)
print("not_need_stop:\n", not_need_stop)
print("seq_lens_this_time:\n", seq_lens_this_time)
print("seq_lens_encoder:\n", seq_lens_encoder)
print("seq_lens_decoder:\n", seq_lens_decoder)
print("input_ids:\n", input_ids)
print("stop_nums:\n", stop_nums)
print("next_tokens:\n", next_tokens)

ref_not_need_stop_out = np.array([True])
ref_seq_lens_this_time_out = np.array([
    0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1,
    0, 1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1
], "int32")
ref_seq_lens_encoder_out = np.array([
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
], "int32")
ref_seq_lens_decoder_out = np.array([
    0, 0, 2, 0, 0, 6, 0, 8, 8, 10, 0, 12, 12, 0, 0, 0, 0, 0, 0, 0, 20, 22, 0,
    24, 24, 0, 26, 28, 0, 0, 0, 32, 32, 0, 34, 0, 0, 38, 0, 40, 0, 0, 42, 0, 0,
    46, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0
], "int32")
input_ids_np[:, 0] = np.array([
    6, 5, 9, 8, 6, 2, 8, 1, 3, 1, 3, 6, 9, 8, 1, 9, 1, 8, 8, 6, 7, 6, 5, 3, 5,
    9, 3, 6, 3, 9, 8, 8, 8, 8, 4, 8, 7, 4, 2, 3, 5, 8, 4, 2, 5, 6, 8, 9, 6, 7,
    4, 2, 4, 6, 2, 3, 4, 9, 7, 2, 1, 8, 7, 8
], "int64")

assert not_need_stop.numpy(
) == ref_not_need_stop_out, 'Check not_need_stop failed.'
assert np.all(seq_lens_this_time.numpy() ==
              ref_seq_lens_this_time_out), 'Check seq_lens_this_time failed.'
assert np.all(seq_lens_encoder.numpy() ==
              ref_seq_lens_encoder_out), 'Check seq_lens_encoder failed.'
assert np.all(seq_lens_decoder.numpy() ==
              ref_seq_lens_decoder_out), 'Check seq_lens_decoder failed.'
assert np.all(input_ids.numpy() == input_ids_np), 'Check input_ids failed.'
