paddle复现pytorch踩坑(二）：paddleAPI对照表（百度论文复现营活动提供）

百度提供了paddlepaddle对应pytorch的API对照表
环境：paddlepaddle1.8
百度论文复现营活动：论文复现营

Pytorch的API名称	Paddle的API名称
torch.abs	fluid.layers.abs(x, name=None)
torch.acos	fluid.layers.acos(x, name=None)
torch.add	fluid.layers.elementwise_add(x, y, axis=-1, act=None, name=None)
torch.allclose	fluid.layers.allclose
torch.arange	fluid.layers.range(start, end, step, dtype)
torch.argmax	fluid.layers.argmax
torch.argmin	fluid.layers.argmin
torch.argsort	fluid.layers.argsort(input, axis=-1, descending=False, name=None)
torch.as_strided	fluid.layers.strided_slice(input, axes, starts, ends, strides):
torch.asin	fluid.layers.asin(x, name=None)
torch.atan	fluid.layers.atan(x, name=None)
torch.cat	fluid.layers.concat(input, axis=0, name=None)
torch.ceil	fluid.layers.ceil
torch.chunk	fluid.layers.unstack(x, axis=0, num=None)
torch.cos	fluid.layers.cos
torch.cumsum	fluid.layers.cumsum(x, axis=None, exclusive=None, reverse=None)
torch.diag	fluid.layer.diag(diagonal)
torch.diag_embed	fluid.layer.diag_embed
torch.div	fluid.layers.elementwise_div(x, y, axis=-1, act=None, name=None)
torch.eq	fluid.layers.equal(x, y, cond=None)
torch.equal	fluid.layers.elementwise_equal(x, y, name=None)
torch.equal	fluid.layers.equal(x, y, cond=None)
torch.erf	fluid.layers.erf(x)
torch.exp	fluid.layers.exp(x, name=None)
torch.eye	fluid.layers.eye(num_rows, num_columns=None, batch_shape=None, dtype=‘float32’)
torch.flatten	fluid.layers.flatten
torch.flip	fluid.layers.flip
torch.floor	fluid.layers.floor(x, name=None)
torch.fmod	fluid.layers.elementwise_mod(x, y, axis=-1, act=None, name=None)
torch.from_numpy	fluid.dygraph.to_variable(value, block=None, name=None)
torch.full	fluid.layers.full(shape, fill_value, out=None, dtype=None, device=None, stop_gradient=True, name=None)
torch.full_like	fluid.layers.full_like
torch.gather	fluid.layers.gather(input, axis, index, out=None, sparse_grad=False, name=None)
torch.ge	fluid.layers.greater_equal
torch.gt	fluid.layers.greater_than
torch.le	fluid.layers.less_equal
torch.linspace	fluid.layers.linspace(start, stop, num, dtype)
torch.log	fluid.layers.log(x, name=None)
torch.logical_not	fluid.layers.logical_not(x, out=None, name=None)
torch.logical_xor	fluid.layers.logical_xor(x, y, out=None, name=None)
torch.lt	fluid.layers.less_than
torch.masked_select	fluid.layers.masked_select
torch.matmul	fluid.layers.matmul(x, y, transpose_x=False, transpose_y=False, alpha=1.0, name=None)
torch.max	fluid.layers.max(input, axis=None, keepdim=False, out=None, name=None) -> (Tensor, LongTensor)
torch.mean	fluid.layers.reduce_mean(input, dim=None, keep_dim=False, name=None)
torch.min	fluid.layers.min
torch.mm	fluid.layers.mm
torch.mul	fluid.layers.mul
torch.mv	fluid.layers.matmul(x, y, transpose_x=False, transpose_y=False, alpha=1.0, name=None)
torch.ne	fluid.layers.not_equal
torch.nn.AdaptiveAvgPool2d	fluid.layers.adaptive_pool2d
torch.nn.AdaptiveAvgPool3d	fluid.layers.adaptive_pool3d
torch.nn.AdaptiveMaxPool2d	fluid.layers.adaptive_pool2d
torch.nn.AdaptiveMaxPool3d	fluid.layers.adaptive_pool3d
torch.nn.add_module	fluid.dygraph.Layer.add_sublayer(name, sublayer)
torch.nn.append	fluid.dygraph.LayerList.append(sublayer)
torch.nn.append	fluid.dygraph.ParameterList.append(parameter)
torch.nn.AvgPool2d	fluid.layers.pool2d(pool_type为’avg’)
torch.nn.AvgPool3d	fluid.layers.pool3d(pool_type为’avg’)
torch.nn.BatchNorm1d	fluid.layers.batch_norm(input, act=None, is_test=False, momentum=0.9, epsilon=1e-05, param_attr=None, bias_attr=None, data_layout=‘NCHW’, in_place=False, name=None, moving_mean_name=None, moving_variance_name=None, do_model_average_for_mean_and_var=False, use_global_stats=False)
torch.nn.BatchNorm2d	fluid.layers.batch_norm(input, act=None, is_test=False, momentum=0.9, epsilon=1e-05, param_attr=None, bias_attr=None, data_layout=‘NCHW’, in_place=False, name=None, moving_mean_name=None, moving_variance_name=None, do_model_average_for_mean_and_var=False, use_global_stats=False)
torch.nn.BatchNorm3d	fluid.layers.batch_norm(input, act=None, is_test=False, momentum=0.9, epsilon=1e-05, param_attr=None, bias_attr=None, data_layout=‘NCHW’, in_place=False, name=None, moving_mean_name=None, moving_variance_name=None, do_model_average_for_mean_and_var=False, use_global_stats=False)
torch.nn.Bilinear	fluid.layers.bilinear_tensor_product(x, y, size, act=None, name=None, param_attr=None, bias_attr=None)
torch.nn.ConstantPad1d	fluid.layers.pad
torch.nn.ConstantPad2d	fluid.layers.pad / fluid.layers.pad2d
torch.nn.ConstantPad3d