rm _in_legacy part3 (#49264)

python/paddle/fft.py

@@ -18,9 +18,9 @@ import numpy as np
 
 import paddle
 
-from . import _C_ops, _legacy_C_ops
+from . import _C_ops
 from .fluid.data_feeder import check_variable_and_dtype
-from .fluid.framework import _in_legacy_dygraph, in_dygraph_mode
+from .fluid.framework import in_dygraph_mode
 from .fluid.layer_helper import LayerHelper
 from .tensor.attribute import is_floating_point, is_integer
 from .tensor.creation import _complex_to_real_dtype, _real_to_complex_dtype
@@ -1445,9 +1445,6 @@ def fft_c2c(x, n, axis, norm, forward, name):
     check_variable_and_dtype(x, 'x', ['complex64', 'complex128'], op_type)
     if in_dygraph_mode():
         out = _C_ops.fft_c2c(x, axes, norm, forward)
-    elif _in_legacy_dygraph():
-        attrs = ('axes', axes, 'normalization', norm, 'forward', forward)
-        out = getattr(_legacy_C_ops, op_type)(x, *attrs)
     else:
         inputs = {
             'X': [x],
@@ -1480,18 +1477,6 @@ def fft_r2c(x, n, axis, norm, forward, onesided, name):
 
     if in_dygraph_mode():
         out = _C_ops.fft_r2c(x, axes, norm, forward, onesided)
-    elif _in_legacy_dygraph():
-        attrs = (
-            'axes',
-            axes,
-            'normalization',
-            norm,
-            'forward',
-            forward,
-            'onesided',
-            onesided,
-        )
-        out = getattr(_legacy_C_ops, op_type)(x, *attrs)
     else:
         inputs = {
             'X': [x],
@@ -1536,21 +1521,6 @@ def fft_c2r(x, n, axis, norm, forward, name):
             out = _C_ops.fft_c2r(x, axes, norm, forward, n)
         else:
             out = _C_ops.fft_c2r(x, axes, norm, forward, 0)
-    elif _in_legacy_dygraph():
-        if n is not None:
-            attrs = (
-                'axes',
-                axes,
-                'normalization',
-                norm,
-                'forward',
-                forward,
-                'last_dim_size',
-                n,
-            )
-        else:
-            attrs = ('axes', axes, 'normalization', norm, 'forward', forward)
-        out = getattr(_legacy_C_ops, op_type)(x, *attrs)
     else:
         inputs = {
             'X': [x],
@@ -1607,9 +1577,6 @@ def fftn_c2c(x, s, axes, norm, forward, name):
 
     if in_dygraph_mode():
         out = _C_ops.fft_c2c(x, axes, norm, forward)
-    elif _in_legacy_dygraph():
-        attrs = ('axes', axes, 'normalization', norm, 'forward', forward)
-        out = getattr(_legacy_C_ops, op_type)(x, *attrs)
     else:
         inputs = {
             'X': [x],
@@ -1661,18 +1628,6 @@ def fftn_r2c(x, s, axes, norm, forward, onesided, name):
 
     if in_dygraph_mode():
         out = _C_ops.fft_r2c(x, axes, norm, forward, onesided)
-    elif _in_legacy_dygraph():
-        attrs = (
-            'axes',
-            axes,
-            'normalization',
-            norm,
-            'forward',
-            forward,
-            'onesided',
-            onesided,
-        )
-        out = getattr(_legacy_C_ops, op_type)(x, *attrs)
     else:
         inputs = {
             'X': [x],
@@ -1739,21 +1694,6 @@ def fftn_c2r(x, s, axes, norm, forward, name):
             out = _C_ops.fft_c2r(x, axes, norm, forward, s[-1])
         else:
             out = _C_ops.fft_c2r(x, axes, norm, forward, 0)
-    elif _in_legacy_dygraph():
-        if s:
-            attrs = (
-                'axes',
-                axes,
-                'normalization',
-                norm,
-                'forward',
-                forward,
-                'last_dim_size',
-                s[-1],
-            )
-        else:
-            attrs = ('axes', axes, 'normalization', norm, 'forward', forward)
-        out = getattr(_legacy_C_ops, op_type)(x, *attrs)
     else:
         inputs = {
             'X': [x],

python/paddle/incubate/operators/graph_send_recv.py

@@ -15,14 +15,14 @@
 import numpy as np
 
 import paddle.utils.deprecated as deprecated
-from paddle import _C_ops, _legacy_C_ops
+from paddle import _C_ops
 from paddle.fluid.data_feeder import (
     check_dtype,
     check_type,
     check_variable_and_dtype,
     convert_dtype,
 )
-from paddle.fluid.framework import Variable, _in_legacy_dygraph, in_dygraph_mode
+from paddle.fluid.framework import Variable, in_dygraph_mode
 from paddle.fluid.layer_helper import LayerHelper
 from paddle.fluid.layers.tensor import cast
 
@@ -124,19 +124,6 @@ def graph_send_recv(
 
     # TODO(daisiming): Should we add judgement for out_size: max(dst_index) + 1.
 
-    if _in_legacy_dygraph():
-        out_size = convert_out_size_to_list(out_size)
-        out, tmp = _legacy_C_ops.graph_send_recv(
-            x,
-            src_index,
-            dst_index,
-            None,
-            'reduce_op',
-            pool_type.upper(),
-            'out_size',
-            out_size,
-        )
-        return out
     if in_dygraph_mode():
         out_size = convert_out_size_to_list(out_size)
         return _C_ops.send_u_recv(

python/paddle/incubate/tensor/manipulation.py

@@ -12,9 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from paddle import _C_ops, _legacy_C_ops
+from paddle import _C_ops
 from paddle.fluid.data_feeder import check_variable_and_dtype
-from paddle.fluid.framework import _in_legacy_dygraph, in_dygraph_mode
+from paddle.fluid.framework import in_dygraph_mode
 from paddle.fluid.layer_helper import LayerHelper
 
 __all__ = []
@@ -49,35 +49,32 @@ def _npu_identity(x, format=-1):
     """
     if in_dygraph_mode():
         return _C_ops.npu_identity(x, format)
+    else:
+        check_variable_and_dtype(
+            x,
+            'x',
+            [
+                'bool',
+                'int8',
+                'uint8',
+                'int16',
+                'int32',
+                'int64',
+                'float16',
+                'float32',
+                'float64',
+            ],
+            'npu_identity',
+        )
 
-    if _in_legacy_dygraph():
-        return _legacy_C_ops.npu_identity(x, 'format', format)
-
-    check_variable_and_dtype(
-        x,
-        'x',
-        [
-            'bool',
-            'int8',
-            'uint8',
-            'int16',
-            'int32',
-            'int64',
-            'float16',
-            'float32',
-            'float64',
-        ],
-        'npu_identity',
-    )
-
-    helper = LayerHelper('npu_identity', **locals())
-    out = helper.create_variable_for_type_inference(
-        dtype=x.dtype, stop_gradient=x.stop_gradient
-    )
-    helper.append_op(
-        type='npu_identity',
-        inputs={'x': [x]},
-        outputs={'out': [out]},
-        attrs={'format': format},
-    )
-    return out
+        helper = LayerHelper('npu_identity', **locals())
+        out = helper.create_variable_for_type_inference(
+            dtype=x.dtype, stop_gradient=x.stop_gradient
+        )
+        helper.append_op(
+            type='npu_identity',
+            inputs={'x': [x]},
+            outputs={'out': [out]},
+            attrs={'format': format},
+        )
+        return out

python/paddle/incubate/tensor/math.py

@@ -15,7 +15,7 @@
 import paddle.utils.deprecated as deprecated
 from paddle import _C_ops, _legacy_C_ops
 from paddle.fluid.data_feeder import check_variable_and_dtype
-from paddle.fluid.framework import _in_legacy_dygraph, in_dygraph_mode
+from paddle.fluid.framework import in_dygraph_mode
 from paddle.fluid.layer_helper import LayerHelper, _non_static_mode
 
 __all__ = []
@@ -65,29 +65,24 @@ def segment_sum(data, segment_ids, name=None):
     """
     if in_dygraph_mode():
         return _C_ops.segment_pool(data, segment_ids, "SUM")[0]
-    if _in_legacy_dygraph():
-        out, tmp = _legacy_C_ops.segment_pool(
-            data, segment_ids, 'pooltype', "SUM"
+    else:
+        check_variable_and_dtype(
+            data, "X", ("float32", "float64", "int32", "int64"), "segment_pool"
+        )
+        check_variable_and_dtype(
+            segment_ids, "SegmentIds", ("int32", "int64"), "segment_pool"
         )
-        return out
-
-    check_variable_and_dtype(
-        data, "X", ("float32", "float64", "int32", "int64"), "segment_pool"
-    )
-    check_variable_and_dtype(
-        segment_ids, "SegmentIds", ("int32", "int64"), "segment_pool"
-    )
 
-    helper = LayerHelper("segment_sum", **locals())
-    out = helper.create_variable_for_type_inference(dtype=data.dtype)
-    summed_ids = helper.create_variable_for_type_inference(dtype=data.dtype)
-    helper.append_op(
-        type="segment_pool",
-        inputs={"X": data, "SegmentIds": segment_ids},
-        outputs={"Out": out, "SummedIds": summed_ids},
-        attrs={"pooltype": "SUM"},
-    )
-    return out
+        helper = LayerHelper("segment_sum", **locals())
+        out = helper.create_variable_for_type_inference(dtype=data.dtype)
+        summed_ids = helper.create_variable_for_type_inference(dtype=data.dtype)
+        helper.append_op(
+            type="segment_pool",
+            inputs={"X": data, "SegmentIds": segment_ids},
+            outputs={"Out": out, "SummedIds": summed_ids},
+            attrs={"pooltype": "SUM"},
+        )
+        return out
 
 
 @deprecated(

python/paddle/signal.py

@@ -14,7 +14,7 @@
 
 import paddle
 from paddle import _C_ops, _legacy_C_ops
-from paddle.fluid.framework import _in_legacy_dygraph, in_dygraph_mode
+from paddle.fluid.framework import in_dygraph_mode
 
 from .fft import fft_c2c, fft_c2r, fft_r2c
 from .fluid.data_feeder import check_variable_and_dtype
@@ -125,23 +125,10 @@ def frame(x, frame_length, hop_length, axis=-1, name=None):
                 f'but got ({frame_length}) > ({x.shape[axis]}).'
             )
 
-    op_type = 'frame'
-
     if in_dygraph_mode():
         return _C_ops.frame(x, frame_length, hop_length, axis)
-
-    if _in_legacy_dygraph():
-        attrs = (
-            'frame_length',
-            frame_length,
-            'hop_length',
-            hop_length,
-            'axis',
-            axis,
-        )
-        op = getattr(_legacy_C_ops, op_type)
-        out = op(x, *attrs)
     else:
+        op_type = 'frame'
         check_variable_and_dtype(
             x, 'x', ['int32', 'int64', 'float16', 'float32', 'float64'], op_type
         )