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75 lines
2.1 KiB
Python
75 lines
2.1 KiB
Python
# Copyright (c) 2024 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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"""tune_cutlass_fp8int4_gemm"""
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import os
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import paddle
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from tqdm import tqdm
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from fastdeploy.model_executor.ops.gpu import scaled_gemm_f8_i4_f16
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def tune_scaled_gemm_f8_i4_f16(ns: list, ks: list, dtype="int8", is_test=True, is_read_from_file=False):
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"""
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Tune fp8 int4 gemm.
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"""
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assert len(ns) == len(ks), "list[n] and list[k] should have the same length!"
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os.environ["FLAGS_fastdeploy_op_configs"] = "tune"
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mm_tmp = []
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for m in range(1, 4, 1):
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mm_tmp.append(m)
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for m in range(4, 16, 4):
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mm_tmp.append(m)
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for m in range(16, 64, 16):
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mm_tmp.append(m)
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for m in range(64, 256, 32):
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mm_tmp.append(m)
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for m in range(256, 512, 64):
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mm_tmp.append(m)
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for m in range(512, 1024, 128):
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mm_tmp.append(m)
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for m in range(1024, 8192, 1024):
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mm_tmp.append(m)
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# Note the end value is 32769 to include 32768
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for m in range(8192, 32769, 4096):
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mm_tmp.append(m)
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for m in tqdm(mm_tmp):
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for idx in range(0, len(ns)):
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n = ns[idx]
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k = ks[idx]
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A = paddle.cast(paddle.ones((m, k)), "float8_e4m3fn")
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B = paddle.cast(paddle.ones((n // 2, k)), "int8")
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w_scale = paddle.ones(n)
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scaled_gemm_f8_i4_f16(
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x=A.cuda(),
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y=B.cuda(),
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scale=paddle.cast(w_scale, dtype).cuda(),
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zero_points=None,
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bias=None,
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out_scale=1.0,
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groupsize=-1,
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out_dtype=dtype,
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)
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