[Bugfix][AMD] Update torch_bindings so that scaled_fp4_quant isn't build on ROCm (#13235)

csrc/ops.h

@@ -177,6 +177,10 @@ void cutlass_scaled_sparse_mm(torch::Tensor& out, torch::Tensor const& a,
                               std::optional<torch::Tensor> const& bias);
 
 std::vector<torch::Tensor> cutlass_sparse_compress(torch::Tensor const& a);
+
+void scaled_fp4_quant(torch::Tensor& output, torch::Tensor const& input,
+                      torch::Tensor& output_scale,
+                      torch::Tensor const& input_scale);
 #endif
 
 void static_scaled_int8_quant(torch::Tensor& out, torch::Tensor const& input,
@@ -194,10 +198,6 @@ torch::Tensor gptq_gemm(torch::Tensor a, torch::Tensor b_q_weight,
 
 void gptq_shuffle(torch::Tensor q_weight, torch::Tensor q_perm, int64_t bit);
 
-void scaled_fp4_quant(torch::Tensor& output, torch::Tensor const& input,
-                      torch::Tensor& output_scale,
-                      torch::Tensor const& input_scale);
-
 void static_scaled_fp8_quant(torch::Tensor& out, torch::Tensor const& input,
                              torch::Tensor const& scale);
 

csrc/torch_bindings.cpp

@@ -385,6 +385,13 @@ TORCH_LIBRARY_EXPAND(TORCH_EXTENSION_NAME, ops) {
       "bool silu_activation,"
       "int pad_slot_id) -> ()");
   ops.impl("causal_conv1d_fwd", torch::kCUDA, &causal_conv1d_fwd);
+
+  // Compute NVFP4 block quantized tensor.
+  ops.def(
+      "scaled_fp4_quant(Tensor! output, Tensor input,"
+      "                 Tensor! output_scale, Tensor input_scale) -> ()");
+  ops.impl("scaled_fp4_quant", torch::kCUDA, &scaled_fp4_quant);
+
 #endif
 
   // Quantized GEMM for GPTQ.
@@ -421,12 +428,6 @@ TORCH_LIBRARY_EXPAND(TORCH_EXTENSION_NAME, ops) {
   ops.impl("dynamic_per_token_scaled_fp8_quant", torch::kCUDA,
            &dynamic_per_token_scaled_fp8_quant);
 
-  // Compute NVFP4 block quantized tensor.
-  ops.def(
-      "scaled_fp4_quant(Tensor! output, Tensor input,"
-      "                 Tensor! output_scale, Tensor input_scale) -> ()");
-  ops.impl("scaled_fp4_quant", torch::kCUDA, &scaled_fp4_quant);
-
   // Compute int8 quantized tensor for given scaling factor.
   ops.def(
       "static_scaled_int8_quant(Tensor! result, Tensor input, Tensor scale,"

vllm/_custom_ops.py

@@ -774,6 +774,7 @@ def scaled_fp4_quant(
             two values are packed into a uint8 and float8_e4m3 scaling factors
             in the sizzled layout.
     """
+    assert not current_platform.is_rocm()
     assert input.ndim >= 1, (
         f'input.ndim needs to be >= 1, but got {input.ndim}.')
     other_dims = 1 if input.ndim == 1 else -1