Temp fix to unblock diff train

backends/vulkan/_passes/int4_weight_only_quantizer.py

@@ -7,11 +7,31 @@
 import torch
 import torch.nn.functional as F
 
-from torchao.quantization.GPTQ.GPTQ import _check_linear_int4_k
 from torchao.quantization.unified import Quantizer
 from torchao.quantization.utils import groupwise_affine_quantize_tensor
 
 
+# TODO: import from from torchao.quantization.GPTQ.GPTQ import _check_linear_int4_k
+# Once diff train catches up
+def _check_linear_int4_k(k, group_size=1, inner_k_tiles=None):
+    """
+    Check if the dimensions are compatible with int4 quantization.
+
+    Args:
+        k: The dimension size to check
+        group_size: The group size for quantization
+        inner_k_tiles: The inner k tiles size
+
+    Returns:
+        bool: Whether the dimensions are compatible
+    """
+    k_divisible_by_group_size = k % group_size == 0
+    if inner_k_tiles is not None:
+        k_divisible_by_16_times_inner_k_tiles = k % (inner_k_tiles * 16) == 0
+        return k_divisible_by_group_size and k_divisible_by_16_times_inner_k_tiles
+    return k_divisible_by_group_size
+
+
 # This module is copied from torchao.quantization.GPTQ.WeightOnlyInt4Linear with
 # changes at the annotated lines.
 class VkWeightOnlyInt4Linear(torch.nn.Module):