paddle.summary 的使用问题

paddle.summary 的使用问题

今天在使用paddle.summary打印模型的时候出现了下面的错误：

---------------------------------------------------------------------------ValueError Traceback (most recent call last) in 5 recall_model=DNNRecallLayer(sparse_feature_number=600000, sparse_feature_dim=9, fc_sizes=fc_sizes) 6 ----> 7 param_info = paddle.summary(recall_model,input_size=[(1,),(4,),(3,),(1,)]) 8 print(param_info) 9 /opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/hapi/model_summary.py in summary(net, input_size, dtypes) 147 148 _input_size = _check_input(_input_size)--> 149 result, params_info = summary_string(net, _input_size, dtypes) 150 print(result) 151 in summary_string(model, input_size, dtypes)/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/base.py in _decorate_function(func, *args, **kwargs) 313 def _decorate_function(func, *args, **kwargs): 314 with self:--> 315 return func(*args, **kwargs) 316 317 @decorator.decorator/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/hapi/model_summary.py in summary_string(model, input_size, dtypes) 274 275 # make a forward pass--> 276 model(*x) 277 278 # remove these hooks/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py in __call__(self, *inputs, **kwargs) 889 self._built = True 890 --> 891 outputs = self.forward(*inputs, **kwargs) 892 893 for forward_post_hook in self._forward_post_hooks.values(): in forward(self, batch_size, user_sparse_inputs, mov_sparse_inputs, label_input) 60 user_sparse_embed_seq = [] 61 for s_input in user_sparse_inputs:---> 62 emb = self.embedding(s_input) 63 emb = paddle.reshape(emb, shape=[-1, self.sparse_feature_dim]) 64 user_sparse_embed_seq.append(emb)/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py in __call__(self, *inputs, **kwargs) 889 self._built = True 890 --> 891 outputs = self.forward(*inputs, **kwargs) 892 893 for forward_post_hook in self._forward_post_hooks.values():/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/nn/layer/common.py in forward(self, x) 1288 padding_idx=self._padding_idx, 1289 sparse=self._sparse,-> 1290 name=self._name)/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/nn/functional/input.py in embedding(x, weight, padding_idx, sparse, name) 200 return core.ops.lookup_table_v2( 201 weight, x, 'is_sparse', sparse, 'is_distributed', False,--> 202 'remote_prefetch', False, 'padding_idx', padding_idx) 203 else: 204 helper = LayerHelper('embedding', **locals())ValueError: (InvalidArgument) Tensor holds the wrong type, it holds float, but desires to be int64_t. [Hint: Expected valid == true, but received valid:0 != true:1.] (at /paddle/paddle/fluid/framework/tensor_impl.h:33) [operator < lookup_table_v2 > error]

我的代码为：

# 定义训练的轮次epochs=3# 定义模型fc_sizes=[512, 256, 128, 32]recall_model=DNNRecallLayer(sparse_feature_number=600000, sparse_feature_dim=9, fc_sizes=fc_sizes)param_info = paddle.summary(recall_model,input_size=[(2,),(4,),(3,),(1,)])print(param_info)

解决方法

# 定义训练的轮次epochs=3# 定义模型fc_sizes=[512, 256, 128, 32]recall_model=DNNRecallLayer(sparse_feature_number=600000, sparse_feature_dim=9, fc_sizes=fc_sizes)param_info = paddle.summary(recall_model,input_size=[(2,),(4,),(3,),(1,)],dtypes=int)print(param_info)

这样就行了，需要设置一个dtypes参数

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