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[Feature][XPU] add custom kernels for mtp (#3537)

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lengxia
2025-08-25 10:14:17 +08:00
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parent bdbac0aa3d
commit 137e539456
93 changed files with 13954 additions and 2 deletions
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custom_ops/xpu_ops/test/test_update_inputs.py Normal file
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# 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."