[ROCm/DCU] Remove BF16 workarounds: is_bfloat16_available, delete_pass, _keep_in_fp32_modules

paddlex/inference/models/common/static_infer.py

@@ -404,10 +404,6 @@ def _create(
                 # TODO(changdazhou): use a black list instead
                 if self._model_name == "PP-DocLayoutV3":
                     config.delete_pass("matmul_add_act_fuse_pass")
-                # ROCm does not support fused_conv2d_add_act kernel, delete the fuse passes
-                if paddle.is_compiled_with_rocm():
-                    config.delete_pass("conv2d_add_act_fuse_pass")
-                    config.delete_pass("conv2d_add_fuse_pass")
             elif self._option.device_type == "npu":
                 config.enable_custom_device("npu", self._option.device_id)
                 if hasattr(config, "enable_new_ir"):
@@ -457,11 +453,6 @@ def _create(
                 config.disable_mkldnn()
                 if hasattr(config, "enable_new_executor"):
                     config.enable_new_executor()
-                # XXX: is_compiled_with_rocm() must be True on dcu platform ?
-                if paddle.is_compiled_with_rocm():
-                    # Delete unsupported passes in dcu
-                    config.delete_pass("conv2d_add_act_fuse_pass")
-                    config.delete_pass("conv2d_add_fuse_pass")
             elif self._option.device_type == "iluvatar_gpu":
                 config.enable_custom_device("iluvatar_gpu", int(self._option.device_id))
                 if hasattr(config, "enable_new_ir"):
@@ -486,20 +477,13 @@ def _create(
                 if hasattr(config, "enable_new_executor"):
                     config.enable_new_executor()
                 config.set_optimization_level(3)
-                if paddle.is_compiled_with_rocm():
-                    config.delete_pass("conv2d_add_act_fuse_pass")
-                    config.delete_pass("conv2d_add_fuse_pass")
         config.enable_memory_optim()
         for del_p in self._option.delete_pass:
             config.delete_pass(del_p)
 
         # Disable paddle inference logging
         if not DEBUG:
             config.disable_glog_info()
-        # ROCm does not support fused_conv2d_add_act kernel, delete the fuse passes
-        if paddle.is_compiled_with_rocm():
-            config.delete_pass("conv2d_add_act_fuse_pass")
-            config.delete_pass("conv2d_add_fuse_pass")
 
         predictor = paddle.inference.create_predictor(config)
 

paddlex/inference/models/common/transformers/utils.py

@@ -86,6 +86,9 @@ def device_guard(device="cpu", dev_id=0):
         paddle.set_device(device)
     elif device in ["gpu", "xpu", "npu"]:
         paddle.set_device("{}:{}".format(device, dev_id))
+    elif device == "dcu":
+        # DCU/ROCm: Paddle does not accept "dcu" as device name; use "gpu" instead
+        paddle.set_device("gpu:{}".format(dev_id))
     try:
         yield
     finally:

paddlex/inference/models/doc_vlm/modeling/paddleocr_vl/_paddleocr_vl.py

@@ -41,6 +41,25 @@
 import paddle
 import paddle.nn as nn
 
+# ROCm compatibility: Paddle HIP wheel (<=3.4.0.dev20260408) did not register
+# phi::bfloat16 for the layer_norm kernel.  This shim casts through FP32 on ROCm.
+# Remove once PaddlePaddle/Paddle PR (add bfloat16 to HIP layer_norm kernel) merges.
+if paddle.is_compiled_with_rocm():
+    import paddle.nn.functional as _F_compat
+    _orig_ln_fwd = paddle.nn.LayerNorm.forward
+    def _rocm_bf16_safe_ln_fwd(self, input):
+        if input.dtype == paddle.bfloat16:
+            x32 = paddle.cast(input, paddle.float32)
+            w = getattr(self, 'weight', None)
+            b = getattr(self, 'bias', None)
+            w32 = paddle.cast(w, paddle.float32) if w is not None else None
+            b32 = paddle.cast(b, paddle.float32) if b is not None else None
+            out = _F_compat.layer_norm(x32, self._normalized_shape, w32, b32, self._epsilon)
+            return paddle.cast(out, paddle.bfloat16)
+        return _orig_ln_fwd(self, input)
+    paddle.nn.LayerNorm.forward = _rocm_bf16_safe_ln_fwd
+    del _F_compat, _orig_ln_fwd, _rocm_bf16_safe_ln_fwd
+
 from ....common.transformers.transformers.model_outputs import (
     CausalLMOutputWithCrossAttentions,
     ModelOutput,
@@ -65,9 +84,6 @@ class PaddleOCRVLForConditionalGeneration(Ernie4_5PretrainedModel):
     _tied_weights_keys = ["lm_head.weight"]
     config_class = PaddleOCRVLConfig
     _no_split_modules = ["Ernie4_5DecoderLayer", "SiglipEncoderLayer"]
-    # Keep visual encoder in fp32 for ROCm stability (MIOpen bf16 conv has bugs)
-    # This also improves precision for vision processing
-    _keep_in_fp32_modules = ["visual", "mlp_AR"]
     base_model_prefix = ""
 
     def __init__(self, config):

paddlex/inference/utils/misc.py

@@ -31,7 +31,7 @@ def is_bfloat16_available(device):
     device_type, _ = parse_device(device)
     return (
         "npu" in get_device_type() or paddle.amp.is_bfloat16_supported()
-    ) and device_type in ("gpu", "npu", "xpu", "mlu", "metax_gpu", "iluvatar_gpu")
+    ) and device_type in ("gpu", "dcu", "npu", "xpu", "mlu", "metax_gpu", "iluvatar_gpu")
 
 
 def is_float16_available(device):