108 lines
3.6 KiB
Python
108 lines
3.6 KiB
Python
"""
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Copyright (c) 2024 by FlashInfer team.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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"""
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import torch
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import flashinfer
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from flashinfer.utils import PosEncodingMode
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def test_warmpup_llama():
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flashinfer.jit.build_jit_specs(
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[
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flashinfer.activation.gen_act_and_mul_module("silu"),
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flashinfer.norm.gen_norm_module(),
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flashinfer.sampling.gen_sampling_module(),
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flashinfer.quantization.gen_quantization_module(),
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flashinfer.page.gen_page_module(),
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flashinfer.decode.gen_batch_decode_module(
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torch.float16,
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torch.float16,
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torch.float16,
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torch.int32,
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128, # head_dim_qk
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128, # head_dim_vo
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PosEncodingMode.NONE.value,
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False, # use_sliding_window
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False, # use_logits_soft_cap
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),
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flashinfer.prefill.gen_batch_prefill_module(
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"fa2", # backend
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torch.float16,
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torch.float16,
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torch.float16,
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torch.int32,
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128, # head_dim_qk
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128, # head_dim_vo
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PosEncodingMode.NONE.value,
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False, # use_sliding_window
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False, # use_logits_soft_cap
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False, # use_fp16_qk_reduction
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),
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],
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verbose=False,
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)
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def test_warmpup_llama_sm90():
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flashinfer.jit.build_jit_specs(
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[
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flashinfer.activation.gen_act_and_mul_module("silu"),
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flashinfer.norm.gen_norm_module(),
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flashinfer.sampling.gen_sampling_module(),
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flashinfer.quantization.gen_quantization_module(),
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flashinfer.page.gen_page_module(),
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flashinfer.decode.gen_batch_decode_module(
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torch.float16,
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torch.float16,
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torch.float16,
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torch.int32,
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128, # head_dim_qk
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128, # head_dim_vo
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PosEncodingMode.NONE.value,
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False, # use_sliding_window
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False, # use_logits_soft_cap
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),
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flashinfer.prefill.gen_batch_prefill_module(
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"fa2", # backend
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torch.float16,
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torch.float16,
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torch.float16,
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torch.int32,
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128, # head_dim_qk
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128, # head_dim_vo
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PosEncodingMode.NONE.value,
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False, # use_sliding_window
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False, # use_logits_soft_cap
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False, # use_fp16_qk_reduction
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),
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flashinfer.prefill.gen_batch_prefill_module(
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"fa3", # backend
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torch.float16,
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torch.float16,
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torch.float16,
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torch.int32,
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128, # head_dim_qk
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128, # head_dim_vo
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PosEncodingMode.NONE.value,
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False, # use_sliding_window
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False, # use_logits_soft_cap
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False, # use_fp16_qk_reduction
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),
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],
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verbose=False,
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)
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