73 lines
2.9 KiB
Python
73 lines
2.9 KiB
Python
"""
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2026.2.1
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2026.2.1
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4.57.6
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0.24.0
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__UNSLOTH_VERSIONING__
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"""
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# Unsloth auto generated code
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# Copyright 2023-present Daniel Han-Chen, Michael Han-Chen & the Unsloth team. All rights reserved.
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU Lesser General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU Lesser General Public License
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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import os
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import torch
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import importlib.util
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import math
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if importlib.util.find_spec("unsloth_studio") is None:
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UNSLOTH_STUDIO_ENABLED = False
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else:
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UNSLOTH_STUDIO_ENABLED = os.environ.get("UNSLOTH_STUDIO_DISABLED", "0") == "0"
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pass
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from typing import Any, List, Optional, Tuple, Union, Dict, Set, Callable
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import math
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UNSLOTH_ENABLE_LOGGING = os.environ.get("UNSLOTH_ENABLE_LOGGING", "0") == "1"
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UNSLOTH_ENABLE_CCE = os.environ.get("UNSLOTH_ENABLE_CCE", "1") == "1"
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UNSLOTH_COMPILE_DISABLE = os.environ.get("UNSLOTH_COMPILE_DISABLE", "0") in ("1", "partial",)
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import logging
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logger_compiler = logging.getLogger(__name__)
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if UNSLOTH_ENABLE_LOGGING:
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logger_compiler.setLevel(logging.DEBUG)
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global INFERENCE_RUNS
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INFERENCE_RUNS = 0
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try:
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import torch._dynamo.eval_frame as torch_dynamo_eval_frame
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torch_dynamo_eval_frame._stance.stance
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torch_compiler_set_stance = torch.compiler.set_stance
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except:
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torch_dynamo_eval_frame = None
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torch_compiler_set_stance = None
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pass
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from unsloth_zoo import DEVICE_TYPE_TORCH, DEVICE_COUNT
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torch_compile_options = {'epilogue_fusion': True, 'max_autotune': False, 'shape_padding': True, 'trace.enabled': False, 'triton.cudagraphs': False, 'debug': False, 'dce': True, 'memory_planning': True, 'coordinate_descent_tuning': False, 'trace.graph_diagram': False, 'compile_threads': 32, 'group_fusion': True, 'disable_progress': True, 'verbose_progress': False, 'triton.multi_kernel': 0, 'triton.use_block_ptr': False, 'triton.enable_persistent_tma_matmul': True, 'triton.autotune_at_compile_time': False, 'triton.cooperative_reductions': False, 'cuda.compile_opt_level': '-O2', 'cuda.enable_cuda_lto': True, 'combo_kernels': False, 'benchmark_combo_kernel': True, 'combo_kernel_foreach_dynamic_shapes': True}
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from torch import Tensor
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import torch
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import torch.nn as nn
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from torch.nn import functional as F
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from typing import Any, List, Optional, Tuple, Union, Dict, Set, Callable
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def forward(self, input: Tensor) -> Tensor:
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return F.layer_norm(
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input, self.normalized_shape, self.weight, self.bias, self.eps
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).to(input.dtype).to(input.dtype)
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