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@@ -100,6 +100,8 @@ class DSSMLayer(nn.Layer):
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def forward(self, left_features, right_features):
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# 获取两个视频的特征表示
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+ paddle.static.Print(left_vec, message="lqc left model input shape:")
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+ paddle.static.Print(right_vec, message="lqc right model input shape:")
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left_vec, right_vec = self.get_vectors(left_features, right_features)
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paddle.static.Print(left_vec, message="lqc left model output shape:")
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paddle.static.Print(right_vec, message="lqc right model output shape:")
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@@ -128,14 +130,16 @@ class DSSMLayer(nn.Layer):
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for i, layer in enumerate(self._left_tower):
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left_vec = layer(left_vec)
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- paddle.static.Print(left_vec, message=f"After layer {i}:")
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+ paddle.static.Print(left_vec, message=f"After left layer {i}:")
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# 处理右视频特征
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right_embedded = self._process_features(right_features, self.right_embeddings)
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# right_vec = right_embedded
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right_vec = paddle.reshape(right_embedded, [-1, self.feature_num * self.embedding_dim])
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+ paddle.static.Print(right_vec, message=f"lqc lqc left_vec:")
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for layer in self._right_tower:
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right_vec = layer(right_vec)
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+ paddle.static.Print(right_vec, message=f"After left layer {i}:")
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# 确保输出是L2归一化的
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left_vec = F.normalize(left_vec, p=2, axis=1)
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