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104 lines
2.7 KiB
Python
104 lines
2.7 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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"""
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platform interface file
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"""
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import enum
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import paddle
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class _Backend(enum.Enum):
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NATIVE_ATTN = enum.auto()
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APPEND_ATTN = enum.auto()
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MLA_ATTN = enum.auto()
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FLASH_ATTN = enum.auto()
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BLOCK_ATTN = enum.auto()
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class Platform:
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"""
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Platform base class, all device class will be derived from it
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"""
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device_name: str
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def is_cuda(self) -> bool:
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"""
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whether platform is cuda
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"""
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return paddle.is_compiled_with_cuda() and not paddle.is_compiled_with_rocm()
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def is_npu(self) -> bool:
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"""
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whether platform is npu
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"""
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return paddle.is_compiled_with_custom_device("npu")
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def is_xpu(self) -> bool:
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"""
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whether platform is xpu
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"""
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return paddle.is_compiled_with_xpu()
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def is_cpu(self) -> bool:
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"""
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whether platform is cpu
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"""
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return paddle.device.get_device().lower() == "cpu"
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def is_dcu(self) -> bool:
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"""
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whether platform is dcu
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"""
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return paddle.is_compiled_with_rocm()
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def is_iluvatar(self) -> bool:
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"""
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whether platform is iluvatar gpu
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"""
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return paddle.is_compiled_with_custom_device("iluvatar_gpu")
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def is_gcu(self) -> bool:
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"""
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whether platform is gcu
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"""
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return paddle.is_compiled_with_custom_device("gcu")
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@classmethod
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def get_attention_backend_cls(self, selected_backend):
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"""Get the attention backend"""
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return ""
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@classmethod
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def verify_quant(self, quant):
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"""
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Verify whether the quantization is supported by the current platform.
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"""
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if self.supported_quantization and quant not in self.supported_quantization:
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raise ValueError(f"{quant} quantization is currently not supported in " f"{self.device_name}.")
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@classmethod
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def available(self):
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"""Return whether the device is available"""
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return True
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@classmethod
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def supports_fp8(self) -> bool:
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"""
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Returns whether the current platform supports FP8 types.
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"""
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return False
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