[Misc] Fix quantization-related typos (#31116)

Signed-off-by: c0de128 <kevin.mckay@outlook.com>

tests/kernels/moe/modular_kernel_tools/common.py

@@ -258,16 +258,16 @@ class Config:
                     f"{self.fe_supported_types()}."
                 )
 
-        # Check block quanization support
-        is_block_quatized = self.quant_block_shape is not None
-        if is_block_quatized and self.quant_dtype is None:
+        # Check block quantization support
+        is_block_quantized = self.quant_block_shape is not None
+        if is_block_quantized and self.quant_dtype is None:
             return False, "No block quantization support."
 
-        if is_block_quatized and not self.is_block_quant_supported():
+        if is_block_quantized and not self.is_block_quant_supported():
             return False, "Mismatched block quantization support."
 
         # deep_gemm only works with block-quantized
-        if self.needs_deep_gemm() and not is_block_quatized:
+        if self.needs_deep_gemm() and not is_block_quantized:
             return False, "Needs DeepGEMM but not block quantized."
 
         # Check dependencies (turn into asserts?)

tests/quantization/test_fp8.py

@@ -217,7 +217,7 @@ def test_scaled_fp8_quant(dtype) -> None:
     ref_y, inv_scale = ops.scaled_fp8_quant(x, None)
     ref_y = per_tensor_dequantize(ref_y, inv_scale, dtype)
 
-    # Reference dynamic quantizaton
+    # Reference dynamic quantization
     y = quantize_ref(x, inv_scale)
     torch.testing.assert_close(ref_y, per_tensor_dequantize(y, inv_scale, dtype))
 

vllm/utils/deep_gemm.py

@@ -389,7 +389,7 @@ def should_use_deepgemm_for_fp8_linear(
 
     # Verify DeepGEMM N/K dims requirements
     # NOTE: Also synchronized with test_w8a8_block_fp8_deep_gemm_matmul
-    # test inside kernels/quatization/test_block_fp8.py
+    # test inside kernels/quantization/test_block_fp8.py
     N_MULTIPLE = 64
     K_MULTIPLE = 128