[Cleanup] Remove unreachable _legacy_C_ops branches

python/paddle/nn/functional/pooling.py

@@ -14,7 +14,7 @@
 
 import numpy as np
 
-from paddle import _C_ops, _legacy_C_ops, in_dynamic_mode
+from paddle import _C_ops, in_dynamic_mode
 from paddle.base.framework import (
     Variable,
     in_dygraph_mode,
@@ -830,24 +830,6 @@ def max_unpool1d(
             x, indices, kernel_size, stride, padding, output_size, data_format
         )
         return squeeze(output, [2])
-    elif in_dynamic_mode():
-        output = _legacy_C_ops.unpool(
-            x,
-            indices,
-            'unpooling_type',
-            'max',
-            'ksize',
-            kernel_size,
-            'strides',
-            stride,
-            'paddings',
-            padding,
-            "output_size",
-            output_size,
-            "data_format",
-            data_format,
-        )
-        return squeeze(output, [2])
 
     op_type = "unpool"
     helper = LayerHelper(op_type, **locals())
@@ -980,24 +962,6 @@ def max_unpool2d(
             x, indices, kernel_size, stride, padding, output_size, data_format
         )
         return output
-    elif in_dynamic_mode():
-        output = _legacy_C_ops.unpool(
-            x,
-            indices,
-            'unpooling_type',
-            'max',
-            'ksize',
-            kernel_size,
-            'strides',
-            stride,
-            'paddings',
-            padding,
-            "output_size",
-            output_size,
-            "data_format",
-            data_format,
-        )
-        return output
 
     op_type = "unpool"
     helper = LayerHelper(op_type, **locals())
@@ -1127,24 +1091,6 @@ def max_unpool3d(
             x, indices, kernel_size, stride, padding, output_size, data_format
         )
         return output
-    elif in_dynamic_mode():
-        output = _legacy_C_ops.unpool3d(
-            x,
-            indices,
-            'unpooling_type',
-            'max',
-            'ksize',
-            kernel_size,
-            'strides',
-            stride,
-            'paddings',
-            padding,
-            "output_size",
-            output_size,
-            "data_format",
-            data_format,
-        )
-        return output
 
     op_type = "unpool3d"
     helper = LayerHelper(op_type, **locals())

python/paddle/nn/functional/vision.py

@@ -88,25 +88,12 @@ def affine_grid(theta, out_shape, align_corners=True, name=None):
             False  # ROCM platform do not have MIOPEN kernel for affine_grid
         )
 
-    if in_dygraph_mode():
+    if in_dynamic_mode():
         _out_shape = (
             out_shape.tolist() if isinstance(out_shape, Variable) else out_shape
         )
         theta = theta._use_gpudnn(use_cudnn)
         return _C_ops.affine_grid(theta, _out_shape, align_corners)
-    elif in_dynamic_mode():
-        _out_shape = (
-            out_shape.tolist() if isinstance(out_shape, Variable) else out_shape
-        )
-        return _legacy_C_ops.affine_grid(
-            theta,
-            "output_shape",
-            _out_shape,
-            "align_corners",
-            align_corners,
-            "use_cudnn",
-            use_cudnn,
-        )
     elif in_pir_mode():
         return _C_ops.affine_grid(
             theta,
@@ -311,18 +298,6 @@ def grid_sample(
 
     if in_dynamic_or_pir_mode():
         return _C_ops.grid_sample(x, grid, mode, padding_mode, align_corners)
-    elif in_dynamic_mode():
-        attrs = (
-            'mode',
-            mode,
-            'padding_mode',
-            padding_mode,
-            'align_corners',
-            align_corners,
-            'use_cudnn',
-            use_cudnn,
-        )
-        out = _legacy_C_ops.grid_sampler(x, grid, *attrs)
     else:
         helper = LayerHelper("grid_sample", **locals())
         check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'grid_sample')