提交 efa6f0df 编写于 作者: Y Yibing Liu

Remove inplace args in unsqueeze & squeeze ops

上级 26710ccd
......@@ -143,8 +143,8 @@ paddle.fluid.layers.smooth_l1 ArgSpec(args=['x', 'y', 'inside_weight', 'outside_
paddle.fluid.layers.one_hot ArgSpec(args=['input', 'depth'], varargs=None, keywords=None, defaults=None)
paddle.fluid.layers.autoincreased_step_counter ArgSpec(args=['counter_name', 'begin', 'step'], varargs=None, keywords=None, defaults=(None, 1, 1))
paddle.fluid.layers.reshape ArgSpec(args=['x', 'shape', 'actual_shape', 'act', 'inplace', 'name'], varargs=None, keywords=None, defaults=(None, None, True, None))
paddle.fluid.layers.squeeze ArgSpec(args=['input', 'axes', 'inplace', 'name'], varargs=None, keywords=None, defaults=(False, None))
paddle.fluid.layers.unsqueeze ArgSpec(args=['input', 'axes', 'inplace', 'name'], varargs=None, keywords=None, defaults=(False, None))
paddle.fluid.layers.squeeze ArgSpec(args=['input', 'axes', 'name'], varargs=None, keywords=None, defaults=(False, None))
paddle.fluid.layers.unsqueeze ArgSpec(args=['input', 'axes', 'name'], varargs=None, keywords=None, defaults=(False, None))
paddle.fluid.layers.lod_reset ArgSpec(args=['x', 'y', 'target_lod'], varargs=None, keywords=None, defaults=(None, None))
paddle.fluid.layers.lrn ArgSpec(args=['input', 'n', 'k', 'alpha', 'beta', 'name'], varargs=None, keywords=None, defaults=(5, 1.0, 0.0001, 0.75, None))
paddle.fluid.layers.pad ArgSpec(args=['x', 'paddings', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0.0, None))
......
......@@ -4486,7 +4486,7 @@ def reshape(x, shape, actual_shape=None, act=None, inplace=True, name=None):
return helper.append_activation(out)
def squeeze(input, axes, inplace=False, name=None):
def squeeze(input, axes, name=None):
"""
Remove single-dimensional entries from the shape of a tensor. Takes a
parameter axes with a list of axes to squeeze. If axes is not provided, all
......@@ -4534,7 +4534,7 @@ def squeeze(input, axes, inplace=False, name=None):
return out
def unsqueeze(input, axes, inplace=False, name=None):
def unsqueeze(input, axes, name=None):
"""
Insert single-dimensional entries to the shape of a tensor. Takes one
required argument axes, a list of dimensions that will be inserted.
......
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