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fix: on-the-fly int4 quantize parameter
Before this PR: ``` [rank1]: TypeError: quantize_int4() got multiple values for argument 'output_device' ```
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1 changed files with 2 additions and 2 deletions
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@ -10,7 +10,7 @@ from typing import Callable, Optional
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import torch
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from fairscale.nn.model_parallel.initialize import get_model_parallel_rank
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from torch import Tensor, nn
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from torch import nn, Tensor
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from torch.nn import functional as F
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from ...datatypes import QuantizationMode
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@ -91,7 +91,7 @@ def convert_to_quantized_model(
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log_status(f"Rank {rank}: Quantizing int4 weights from bf16")
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def apply_quantization(_, weight):
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return quantize_int4(weight, fp8_activation_scale_ub, output_device=torch.device("cuda"))
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return quantize_int4(weight, output_device=torch.device("cuda"))
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else:
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fp8_scales_path = os.path.join(checkpoint_dir, f"fp8_scales_{rank}.pt")
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