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@@ -100,18 +100,18 @@ 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_features, message="lqc left model input shape:")
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- #paddle.static.Print(right_features, message="lqc right model input shape:")
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+ paddle.static.Print(left_features, message="lqc left model input shape:")
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+ paddle.static.Print(right_features, 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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+ 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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# 计算相似度
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sim_score = F.cosine_similarity(
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left_vec,
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right_vec,
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axis=1
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).reshape([-1, 1])
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-
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+ paddle.static.Print(sim_score, message="lqc sim_score shape:")
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return sim_score, left_vec, right_vec
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def get_vectors(self, left_features, right_features):
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often