From 0a837cb224746e38e33e0676c566076f92027067 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E5=A7=9C=E6=B0=B8=E4=B9=85?= <34344716+yjjiang11@users.noreply.github.com> Date: Tue, 27 Dec 2022 10:06:37 +0800 Subject: [PATCH] rm _in_legacy part3 (#49264) --- python/paddle/fft.py | 64 +------------------ .../incubate/operators/graph_send_recv.py | 17 +---- python/paddle/incubate/tensor/manipulation.py | 63 +++++++++--------- python/paddle/incubate/tensor/math.py | 39 +++++------ python/paddle/signal.py | 17 +---- 5 files changed, 53 insertions(+), 147 deletions(-) diff --git a/python/paddle/fft.py b/python/paddle/fft.py index 7718e038c77..22525e3c620 100644 --- a/python/paddle/fft.py +++ b/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], diff --git a/python/paddle/incubate/operators/graph_send_recv.py b/python/paddle/incubate/operators/graph_send_recv.py index ed330775653..e433d145bf9 100644 --- a/python/paddle/incubate/operators/graph_send_recv.py +++ b/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( diff --git a/python/paddle/incubate/tensor/manipulation.py b/python/paddle/incubate/tensor/manipulation.py index 4d65934e2e6..4e39dfa0c79 100644 --- a/python/paddle/incubate/tensor/manipulation.py +++ b/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 diff --git a/python/paddle/incubate/tensor/math.py b/python/paddle/incubate/tensor/math.py index 923f8a590bb..79074836b0d 100644 --- a/python/paddle/incubate/tensor/math.py +++ b/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( diff --git a/python/paddle/signal.py b/python/paddle/signal.py index 20a925c0f36..52315f5e5d6 100644 --- a/python/paddle/signal.py +++ b/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 ) -- GitLab