提交 0e0a2d04 编写于 作者: D dengkaipeng 提交者: ceci3

fix API.spec. test=develop

上级 dbb8d078
......@@ -128,6 +128,7 @@ paddle.fluid.layers.row_conv (ArgSpec(args=['input', 'future_context_size', 'par
paddle.fluid.layers.multiplex (ArgSpec(args=['inputs', 'index'], varargs=None, keywords=None, defaults=None), ('document', '013795af319e2e86d3506741941078ee'))
paddle.fluid.layers.layer_norm (ArgSpec(args=['input', 'scale', 'shift', 'begin_norm_axis', 'epsilon', 'param_attr', 'bias_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(True, True, 1, 1e-05, None, None, None, None)), ('document', 'de6a906950bae9f3c245cb744d22b94e'))
paddle.fluid.layers.group_norm (ArgSpec(args=['input', 'groups', 'epsilon', 'param_attr', 'bias_attr', 'act', 'data_layout', 'name'], varargs=None, keywords=None, defaults=(1e-05, None, None, None, 'NCHW', None)), ('document', '419c3a24a83cc89219a029cf4092788b'))
paddle.fluid.layers.spectral_norm (ArgSpec(args=['weight', 'dim', 'power_iters', 'eps', 'name'], varargs=None, keywords=None, defaults=(0, 1, 1e-12, None)), ('document', '14ceee8c63b2f4664c45cb8f0664e25a'))
paddle.fluid.layers.softmax_with_cross_entropy (ArgSpec(args=['logits', 'label', 'soft_label', 'ignore_index', 'numeric_stable_mode', 'return_softmax'], varargs=None, keywords=None, defaults=(False, -100, True, False)), ('document', 'bce1b75e3d95b75cacd1099655cbb3c3'))
paddle.fluid.layers.smooth_l1 (ArgSpec(args=['x', 'y', 'inside_weight', 'outside_weight', 'sigma'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'c6b175d253c55baf4b9c0eca9b1dda88'))
paddle.fluid.layers.one_hot (ArgSpec(args=['input', 'depth'], varargs=None, keywords=None, defaults=None), ('document', '6148b6a555cbfb62fdcd030d8982c18c'))
......
......@@ -86,7 +86,7 @@ class SpectralNormOpMaker : public framework::OpProtoAndCheckerMaker {
"H is the 1st dimentions of Weight after reshape"
"corresponding by Attr(dim). As for Attr(dim) = 1"
"in conv2d layer with weight shape [M, C, K1, K2]"
"Weight will be reshape to [C, M*K1*Kw], U will"
"Weight will be reshape to [C, M*K1*K2], U will"
"be in shape [C, 1].");
AddInput("V",
"The weight_v tensor of spectral_norm operator, "
......
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